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12 pages, 2605 KB

Open AccessProceeding Paper

Design and Development of an Oscillator-Driven Coconut Dried Kernel Scraper for Small Virgin Coconut Oil (VCO) Farmers

by Vicardo J. Aroy, John O. Estillore, Louie Jay P. Manlunas, Jaquelyn L. Quintano and Charlou C. Rivas

Eng. Proc. 2026, 143(1), 1; https://doi.org/10.3390/engproc2026143001 - 8 Jun 2026

Viewed by 515

Abstract

The traditional manual method of removing dried coconut kernels from shells is labor-intensive, time-consuming, and poses a risk of injury to workers. To address these challenges, this study developed an Oscillator-Based Coconut Dried Kernel Scraper to enhance efficiency, safety, and productivity in the [...] Read more.

The traditional manual method of removing dried coconut kernels from shells is labor-intensive, time-consuming, and poses a risk of injury to workers. To address these challenges, this study developed an Oscillator-Based Coconut Dried Kernel Scraper to enhance efficiency, safety, and productivity in the coconut processing industry. The device utilizes an oscillatory mechanism driven by an electric motor to produce a controlled scraping motion, facilitating the effective detachment of the dried kernel from the shell with minimal physical effort. Key components of the prototype include a motor-driven oscillating blade, a kernel-holding fixture, and a safety enclosure. The design emphasizes the use of locally available materials and user-friendly operation. Preliminary testing demonstrated a significant reduction in processing time and operator fatigue compared to manual scraping methods. Furthermore, the researchers conducted a comparative performance evaluation between manual and mechanized scraping, with participants indicating a strong preference for the oscillator-based scraper. The product achieved the highest scores for efficiency and user satisfaction, particularly among small- to medium-scale coconut farmers. Based on these findings, it is recommended that future improvements include enhancements in design and the integration of a capacitive sensor to automate and further refine the control system. Full article

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9 pages, 405 KB

Open AccessProceeding Paper

Development of an Automated Filament Extrusion System Using Recycled Thermoplastics for 3D Printing in Caraga State University, Cabadbaran Campus

by Marisol Jane M. Beray, Raffy V. Cosicol, Reymark C. Capunong, Larry Merl G. Caldoza and Matt Alfred A. Villahermosa

Eng. Proc. 2026, 143(1), 2; https://doi.org/10.3390/engproc2026143002 - 9 Jun 2026

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Abstract

Additive manufacturing offers transformative opportunities but faces barriers due to costly, imported filaments. This study at Caraga State University, Cabadbaran Campus, developed a prototype automated filament extrusion system using recycled thermoplastics, specifically polypropylene (PP) and PET, to address material scarcity and plastic waste. [...] Read more.

Additive manufacturing offers transformative opportunities but faces barriers due to costly, imported filaments. This study at Caraga State University, Cabadbaran Campus, developed a prototype automated filament extrusion system using recycled thermoplastics, specifically polypropylene (PP) and PET, to address material scarcity and plastic waste. Employing a developmental–descriptive design, the system integrated heating, extrusion, spooling, and microcontroller-based controls. Results confirmed functional capability, producing filaments with acceptable dimensional consistency, though challenges in accuracy and flexibility remain. The project advances sustainable, affordable 3D printing, supports circular economy principles, enhances technical education, and empowers local innovators toward inclusive, environmentally responsible manufacturing. Full article

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14 pages, 2287 KB

Open AccessProceeding Paper

Automation in Off-Grid Agriculture: Evaluation of a Solar-Powered Seeding and Fertigation System for Micro Farmers in the Philippines

by John Estillore, Wex Roid Salvador, Vic Roue Morano, Edgar Cagampang and Jemuel Milla

Eng. Proc. 2026, 143(1), 3; https://doi.org/10.3390/engproc2026143003 - 9 Jun 2026

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Abstract

This study presents the design, development, and evaluation of an integrated solar-powered seed sowing and fertilizer-watering system to enhance planting efficiency, improve resource utilization, and reduce labor in small-scale agriculture. The prototype features a 600-watt photovoltaic panel, DC motors, and a manual mechanical [...] Read more.

This study presents the design, development, and evaluation of an integrated solar-powered seed sowing and fertilizer-watering system to enhance planting efficiency, improve resource utilization, and reduce labor in small-scale agriculture. The prototype features a 600-watt photovoltaic panel, DC motors, and a manual mechanical dispensing mechanism, enabling automated seed placement, water distribution, and fertilizer application in off-grid farm environments. Development was guided by a product-based design approach using locally sourced materials to ensure cost-effectiveness, maintainability, and accessibility for rural users. Field simulations and performance trials assessed charging efficiency, seed sowing accuracy, irrigation flow rate, and fertilizer dispensing precision. Results showed high consistency in operational performance, including up to 99% seed placement accuracy, efficient water delivery, and reliable fertilizer timing, with solar energy providing adequate power storage during periods of peak irradiance. Expert evaluations using a standardized instrument demonstrated strong agreement on the system’s usability, material availability, ergonomic features, modularity, and overall functional design. Findings indicate that the system can minimize manual labor, reduce operational costs, and offer a practical transition toward clean-energy–assisted mechanization in agriculture. The study concludes that integrating renewable energy into essential farm operations can contribute to sustainable productivity and recommends future enhancements through sensor integration, increased battery capacity, and adaptive control mechanisms to support wider agricultural adoption. Full article

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12 pages, 1775 KB

Open AccessProceeding Paper

Performance Efficiency of a Newly Developed Rice Seed Cleaning Blower for Frontier and Remote (Far) Farming Communities in Northeastern Philippines

by John O. Estillore, Clyde Melgazo, Eliezer Andrei Paredes, Jeffry Polongasa, Mark Kient Paredes, Marlon Kent Agusin and Rondolph G. Mansal

Eng. Proc. 2026, 143(1), 4; https://doi.org/10.3390/engproc2026143004 - 9 Jun 2026

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Abstract

Postharvest seed cleaning is critical for ensuring high-quality rice seeds suitable for storage and planting. Traditional cleaning systems, which are often limited to one or two sieves, are insufficient for removing all impurities, resulting in reduced seed purity and potential germination issues. This [...] Read more.

Postharvest seed cleaning is critical for ensuring high-quality rice seeds suitable for storage and planting. Traditional cleaning systems, which are often limited to one or two sieves, are insufficient for removing all impurities, resulting in reduced seed purity and potential germination issues. This study was designed to enhance the rice seed cleaning system by integrating a high-efficiency blower with a triple-sieving mechanism. The system utilized three sieves with progressively smaller mesh sizes to systematically separate contaminants such as dust, broken grains, husks, and other foreign particles. A controlled airflow from the blower distributes rice seeds uniformly across the sieves, optimizing separation while minimizing mechanical damage. Compared to existing conventional systems, the proposed design demonstrated significantly improved cleaning performance, resulting in higher seed purity levels and overall enhanced seed quality. The triple-sieve configuration, coupled with precise airflow control, led to more effective impurity removal and uniform seed handling. The improved seed-cleaning system offers several agronomic benefits, including reduced postharvest losses, increased seed germination rates, and improved crop establishment. By producing cleaner, higher-quality seeds, this system has the potential to support more efficient and productive rice cultivation. Full article

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13 pages, 869 KB

Open AccessProceeding Paper

Artificial Intelligence-Enhanced Contactless Screening Kiosks: Leveraging Machine Learning for Infectious Disease Detection and Mitigation

by Marisol Jane M. Beray, Ramil B. Arante and Jofel Batutay

Eng. Proc. 2026, 143(1), 5; https://doi.org/10.3390/engproc2026143005 - 10 Jun 2026

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Abstract

The COVID-19 pandemic exposed critical limitations in conventional screening protocols, particularly in high-traffic environments where rapid, accurate, and contactless health assessment became essential to mitigate transmission risks. In response, this study presents the development of an Artificial Intelligence-Enhanced Contactless Screening Kiosk (AICS-K) that [...] Read more.

The COVID-19 pandemic exposed critical limitations in conventional screening protocols, particularly in high-traffic environments where rapid, accurate, and contactless health assessment became essential to mitigate transmission risks. In response, this study presents the development of an Artificial Intelligence-Enhanced Contactless Screening Kiosk (AICS-K) that integrates multimodal sensing, embedded systems engineering, and machine learning into a unified workflow. Utilizing a Raspberry Pi platform with computer vision, thermal sensing, QR-based contact tracing, and intelligent control logic, the system enables efficient real-time screening while minimizing human intervention. The proposed architecture demonstrates the potential of extensible, affordable AI-driven solutions for early signs detection and institutional health resilience. Full article

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11 pages, 2988 KB

Open AccessProceeding Paper

Real-Time Detection of Underground Intrusions via Vibration Sensors and Dual-Band GSM Cellular Notifications Using SIM900A Module for Electrical Laboratory Simulation

by John Estillore, Jovanie Banate, Dan Rosel Galla, Dexter Rollorata and Joseph S. Yatan

Eng. Proc. 2026, 143(1), 6; https://doi.org/10.3390/engproc2026143006 - 11 Jun 2026

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Abstract

Microfinance institutions (MFIs) are vital in promoting financial inclusion for underserved populations. However, these institutions face growing security threats, including sophisticated burglary tactics like underground tunneling. In the Philippines, notable incidents, such as the “Termite Gang” heist in Marikina City and a mall [...] Read more.

Microfinance institutions (MFIs) are vital in promoting financial inclusion for underserved populations. However, these institutions face growing security threats, including sophisticated burglary tactics like underground tunneling. In the Philippines, notable incidents, such as the “Termite Gang” heist in Marikina City and a mall robbery in Ozamiz, highlight the limitations of conventional security systems in addressing subterranean intrusions. This study addresses the gap in existing security technologies by developing a real-time detection system that integrates a vibration sensor, a Global System for Mobile Communications (GSM) module for sending real-time SMS alerts, an audible alarm, and a solar-powered backup system for continuous operation. The system was simulated in the electrical technology laboratory to enhance classroom learning. The system’s core is an Arduino Uno microcontroller that processes inputs from the SW-420 vibration sensor, activating alarms and triggering SMS notifications via the SIM900A module when it detects unusual vibrations. Simulations A, B, and C were conducted to evaluate the system’s response time, with results showing a progressive reduction in detection time from five seconds to one second, indicating improved calibration and system efficiency. These findings also support the existing literature on user interaction with vibration alerts, demonstrating high accuracy in interpreting haptic notifications and the cognitive trade-offs involved. The proposed solution offers a proactive, energy-resilient, and cost-effective security system specifically designed to address underground burglary attempts. It applies to MFIs, pawnshops, and other high-risk financial environments. Future research should explore the application of machine learning for adaptive threat detection, expand the system’s scalability, and integrate mobile applications to enable user customization and enhance alert management. Full article

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9 pages, 813 KB

Open AccessProceeding Paper

Needs and Challenges of Industrial Technology Education Learners in a Mindanao Higher Education Institution: Implications for Curriculum Enhancement

by John O. Estillore, Ramil B. Arante and Jona J. Biongcog

Eng. Proc. 2026, 143(1), 7; https://doi.org/10.3390/engproc2026143007 - 11 Jun 2026

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Abstract

Technical higher education in the Philippines is a government priority, as it equips learners with the technical knowledge and practical skills necessary to develop industry and technology-ready human capital. In parts of Mindanao, the Philippines, where socio-economic and technological challenges are significant, Industrial [...] Read more.

Technical higher education in the Philippines is a government priority, as it equips learners with the technical knowledge and practical skills necessary to develop industry and technology-ready human capital. In parts of Mindanao, the Philippines, where socio-economic and technological challenges are significant, Industrial Technology Education (ITE) learners must be equipped with relevant, comprehensive knowledge of industry trends. A sequential explanatory mixed-methods design was employed in this research, combining quantitative surveys with qualitative interviews to provide a comprehensive analysis. Five hundred twenty-six learners participated in the survey, and six were selected for in-depth interviews. The findings highlight the significant impact of familial and peer support on fostering confidence, encouraging academic perseverance, and improving mental health. However, financial hardships and inadequate emotional support remain significant obstacles. The study emphasizes the importance of cultivating an inclusive campus atmosphere via awareness efforts, accessible services, and mentorship programs to guarantee fair educational opportunities. For this reason, the implementation of personalized education plans, flexible learning, digital access, academic and educational support, and an institutional support system is highly encouraged to address learners’ essential needs. The research findings also suggest integrating mentorship programs, adopting inclusive learning practices, developing an adaptable curriculum, and providing mental health support services for learners, particularly those with disabilities. By aligning the curriculum with industry specifications and standards and providing well-planned support frameworks, higher education institutions in Mindanao can produce graduates who are professionally qualified, highly skilled, well-mannered, and career-prepared, fully equipped to meet the demands of the dynamic workforce. Full article

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14 pages, 2063 KB

Open AccessProceeding Paper

Development and Simulation of a Portable Solar Food Dehydrator: A Sustainable Learning Tool for Food Technology Education in Mindanao, Philippines

by John O. Estillore, Raffy V. Cosicol, Renissa S. Cosicol, Jeramel Rodaje, Rea Dumas and Gleciel Biñan Cabriana

Eng. Proc. 2026, 143(1), 8; https://doi.org/10.3390/engproc2026143008 - 11 Jun 2026

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Abstract

Sustainability in higher education plays a crucial role in shaping future professionals with an eco-conscious mindset. This study focuses on developing and simulating a portable solar food dehydrator as a practical application of sustainability principles in technology education. By integrating sustainability into the [...] Read more.

Sustainability in higher education plays a crucial role in shaping future professionals with an eco-conscious mindset. This study focuses on developing and simulating a portable solar food dehydrator as a practical application of sustainability principles in technology education. By integrating sustainability into the curriculum, this research enhances students’ technical skills while promoting the use of renewable energy and effective food preservation methods. Furthermore, the project aligns with green campus initiatives by encouraging energy-efficient practices and reducing food waste. This study emphasizes the significance of education for sustainable development by offering learners hands-on experience in designing eco-friendly solutions, promoting innovation, and equipping them to contribute to a more sustainable future. A food dehydrator is a device that removes moisture from food to aid in its preservation, utilizing a heat source and airflow to reduce its water content. The researchers used two methods to dehydrate food: direct sunlight (sun drying) and indirect sunlight (solar drying). The study used a developmental research design. Simulations revealed that, with solar-powered electricity, the longer the drying time, the greater the reduction in the moisture content. This was evident in the eighth experiment, which was conducted on fruits and vegetables. While drying with direct sunlight, the same trends, albeit to a lesser extent, were observed in the reduction in the moisture content of the fruits and vegetables. These insights can inform future design improvements, making the products more visually appealing and distinctive, thereby enhancing their attractiveness and novelty. Full article

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11 pages, 385 KB

Open AccessProceeding Paper

Electronically Controlled Root Crop Processor: A Laboratory Simulator for Outcome-Based TVET Learners

by Cerelo T. Tabat, Jr., Jesson S. Lunio, Chris John L. Papa and Jemery D. Noces

Eng. Proc. 2026, 143(1), 9; https://doi.org/10.3390/engproc2026143009 - 12 Jun 2026

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Abstract

This study introduces an Electronically Controlled Root Crop Processor, a compact, Arduino-powered simulator designed to transform hands-on learning for TVET students. Built with locally available materials, it seamlessly integrates grating and juice extraction while prioritizing safety, ergonomics, and user-friendly operation. Experts rated the [...] Read more.

This study introduces an Electronically Controlled Root Crop Processor, a compact, Arduino-powered simulator designed to transform hands-on learning for TVET students. Built with locally available materials, it seamlessly integrates grating and juice extraction while prioritizing safety, ergonomics, and user-friendly operation. Experts rated the prototype highly for functionality and usability, with ergonomics scoring 3.96, while aesthetics and modularity scored 3.83, highlighting areas for refinement. By bridging classroom theory and practical skills, the processor offers an interactive, real-world food processing experience, empowering learners to develop technical competencies efficiently in laboratory settings. Full article

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10 pages, 1161 KB

Open AccessProceeding Paper

Evaluation of Abaca Fiber-Reinforced Polymer Composites for Fiber-Optic Cable Strengthening: Advancing Experiential Learning for Industrial Technology Learners

by Vicardo J. Aroy, John O. Estillore, Romnick J. Labastida, Marlon A. Filipino and Junrey V. Quitorio

Eng. Proc. 2026, 143(1), 10; https://doi.org/10.3390/engproc2026143010 - 12 Jun 2026

Viewed by 769

Abstract

The study investigated the tensile strength and elongation properties of abaca fiber-reinforced polymer (AFRP) composites after varying durations of seawater soaking, with a focus on their potential for reinforcing fiber-optic cables. It aims to bridge industrial technology education, experiential learning, and green technology [...] Read more.

The study investigated the tensile strength and elongation properties of abaca fiber-reinforced polymer (AFRP) composites after varying durations of seawater soaking, with a focus on their potential for reinforcing fiber-optic cables. It aims to bridge industrial technology education, experiential learning, and green technology by evaluating abaca fiber as a sustainable alternative to synthetic aramid yarn. Conducted at Caraga State University, Cabadbaran Campus (CSUCC), the research utilized a quasi-experimental product development design involving industrial technology students and instructors. Tensile strength testing and comparative analysis were performed on abaca fiber samples (A, B, and C) subjected to different seawater soaking durations. Results show that soaking time significantly affects the fiber strength, with Sample A achieving the highest tensile strength (5631.5 MPa) and Sample C the lowest (1679.8 MPa). Findings indicate that prolonged exposure to seawater weakens abaca fiber, emphasizing the need for controlled treatment to optimize its industrial applications. This study emphasizes the importance of hands-on learning in industrial technology education, promoting critical thinking and technical skills while underscoring sustainability. The research advocates for eco-friendly materials in industrial applications and highlights the potential of abaca fiber composites. Future studies should investigate pre-treatment methods to enhance fiber durability, assess the long-term environmental performance, and conduct large-scale pilot testing to evaluate commercial viability. By integrating sustainable innovations into industrial technology education, this study contributes to advancing natural fiber composites for manufacturing and telecommunications infrastructure. Full article

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15 pages, 2677 KB

Open AccessProceeding Paper

Experts’ Evaluation of Instructional Material in Fundamentals of Food Processing for Technology and Livelihood Education

by Julanie M. Limen, Jayve G. Monton, Mary Grace C. Borja and Gladiole B. Morada

Eng. Proc. 2026, 143(1), 11; https://doi.org/10.3390/engproc2026143011 - 12 Jun 2026

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Abstract

This study focuses on the design and development of instructional materials tailored for the subject fundamentals of food processing, with the primary objective of equipping students with foundational knowledge and practical competencies essential to understanding core concepts and principles within the discipline. The [...] Read more.

This study focuses on the design and development of instructional materials tailored for the subject fundamentals of food processing, with the primary objective of equipping students with foundational knowledge and practical competencies essential to understanding core concepts and principles within the discipline. The instructional content was purposefully crafted to align with established course learning outcomes and the broader curricular framework. Drawing upon contemporary research and pedagogical best practices, the materials were customized to address the specific academic needs, interests, and learning preferences of students. Emphasis was placed on interactivity and inclusivity, with the integration of varied media formats to support diverse learning styles and enhance accessibility. The expert’s evaluation of the instructional materials is based on the three criteria: content, organization and structure, and support for learning. Overall, the instructional material has a mean of 3.71, with a verbal interpretation of high evidence and a standard deviation of 0.11, indicating high reliability. The highest mean score is 3.79 for the content category. This indicates that the instructional material is highly effective in aligning with course requirements, currently accurate, and bias-free. The lowest mean score is 3.67 on organization structure and support for learning. These scores suggest that while these areas are well regarded, they have certain aspects that could be further improved. Moreover, the materials must exhibit flexibility and adaptability to accommodate various teaching methodologies. They should seamlessly integrate with various instructional strategies, including project-based learning, problem-based learning, and hands-on activities. This versatility ensures that educators can employ diverse approaches to cater to their students’ needs and learning preferences. Full article

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11 pages, 719 KB

Open AccessProceeding Paper

Enhancing Power Tool Stability and Safety: A Portable Drill and Grinder Holder with Integrated Measurement Guide

by Cerelo T. Tabat, Jay R. De La Serna, Louie O. Besing, Mj N. Zamora and Vince Rowen F. Lopez

Eng. Proc. 2026, 143(1), 12; https://doi.org/10.3390/engproc2026143012 - 13 Jun 2026

Viewed by 660

Abstract

This study designed and developed a Portable Drill and Grinder Holder with an Integrated Measurement Guide to improve stability, safety, and accuracy in hand-held power tool operations. Addressing workshop challenges like excessive vibration and uncontrolled tool movement, the project employed a developmental research [...] Read more.

This study designed and developed a Portable Drill and Grinder Holder with an Integrated Measurement Guide to improve stability, safety, and accuracy in hand-held power tool operations. Addressing workshop challenges like excessive vibration and uncontrolled tool movement, the project employed a developmental research design involving sixteen (16) welding experts. The prototype was constructed using durable, locally available materials to ensure affordability. Evaluation results showed significant improvements in operator control, with Safety receiving the highest rating (M = 3.66). The findings confirm that the tool meets industry standards for instructional and workshop use. Full article

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11 pages, 1031 KB

Open AccessProceeding Paper

Synergy of Solar and Electric Power: Designing a Sustainable Paddy Winnowing Machine for Small-Scale Farmers

by Alfredo S. Javier, May Ann T. Abraham, Jovanie G. Mijos, Jeanifer R. Tidalgo, Cerelo T. Tabat, Jay R. De La Serna and Ritchel G. Espinosa

Eng. Proc. 2026, 143(1), 13; https://doi.org/10.3390/engproc2026143013 - 12 Jun 2026

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Abstract

This study examines the effectiveness of an innovative solar-electric paddy winnowing machine titled “Synergy of Solar and Electric Power”. Conducted in the agricultural hubs of Barangay Tagbongabong and Barangay Lemon in the Philippines, the project utilized a multi-stakeholder collaboration involving small-scale farmers, students, [...] Read more.

This study examines the effectiveness of an innovative solar-electric paddy winnowing machine titled “Synergy of Solar and Electric Power”. Conducted in the agricultural hubs of Barangay Tagbongabong and Barangay Lemon in the Philippines, the project utilized a multi-stakeholder collaboration involving small-scale farmers, students, faculty, and technical experts. Findings revealed significant improvements in operational efficiency and reduced labor requirements. Modularity and Ergonomics received the highest evaluation ratings (3.64), highlighting a user-centric design. The study concludes that this hybrid system provides a practical, eco-friendly solution for advancing sustainable agricultural mechanization in resource-limited settings. Full article

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10 pages, 1156 KB

Open AccessProceeding Paper

Double Jaw Vertical Bench Vise

by Alfredo S. Javier, Cerelo T. Tabat, Ritchel G. Espinosa, Cecile V. Ranuco, Mitcelou M. Quiaman and Raffy C. Flores

Eng. Proc. 2026, 143(1), 14; https://doi.org/10.3390/engproc2026143014 - 12 Jun 2026

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Abstract

This study focuses on the design and development of the Double Purpose Bench Vise to address safety, efficiency, and adaptability challenges in welding and fabrication environments. The project responds to limitations of conventional vises that restrict precision and increase the risk of strain-related [...] Read more.

This study focuses on the design and development of the Double Purpose Bench Vise to address safety, efficiency, and adaptability challenges in welding and fabrication environments. The project responds to limitations of conventional vises that restrict precision and increase the risk of strain-related injuries when handling heavy, irregular, or vertically oriented workpieces. Through an engineering-based development approach involving analysis, design, fabrication, and performance evaluation, the study introduces a Double Jaw Vertical Bench Vise equipped with a dual-clamping system and an integrated hydraulic jack mechanism for precise vertical adjustment with minimal physical effort. The device is designed to securely hold various materials, including metal bars, pipes, and wooden components, during cutting, grinding, shaping, welding, and assembly operations. Evaluation results from functional testing and user feedback indicate improved clamping stability, alignment accuracy, and ergonomic performance compared to traditional models, although refinements in structural optimization, weight distribution, and user interface components are recommended. The study suggests further prototype enhancement, extended field testing, and integration of advanced ergonomic and safety features to maximize durability, usability, and overall productivity in professional workshops and technical training laboratories. Full article

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9 pages, 198 KB

Open AccessProceeding Paper

An Assessment of Service Quality Satisfaction (SQS) Among Customers of Carpentry Technicians: A Multidimensional Analysis

by Cerelo T. Tabat, Jr. and Gerry B. Estrada

Eng. Proc. 2026, 143(1), 15; https://doi.org/10.3390/engproc2026143015 - 15 Jun 2026

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Abstract

This study assessed the level of service quality satisfaction among customers of carpentry technicians in Cabadbaran City, with emphasis on ten service dimensions: craftsmanship, timeliness, communication, durability, price transparency, customer service, design collaboration, reputation, and after-sales service. Employing a descriptive research design, data [...] Read more.

This study assessed the level of service quality satisfaction among customers of carpentry technicians in Cabadbaran City, with emphasis on ten service dimensions: craftsmanship, timeliness, communication, durability, price transparency, customer service, design collaboration, reputation, and after-sales service. Employing a descriptive research design, data were collected through a self-constructed questionnaire administered to customers who had previously availed of carpentry services in the city. Results indicated that overall satisfaction across all dimensions was generally positive, as reflected in customers’ agreement ratings. However, notable gaps were identified that suggest areas for improvement. Craftsmanship and timeliness emerged as the most critical concerns, with respondents citing inconsistent job quality and delays in project completion. Issues of customization and durability were also highlighted, as some customers reported limited flexibility in design options and doubts about the long-term sturdiness of products. Communication shortcomings, particularly in providing project updates and explaining processes, further affected satisfaction. Design collaboration raised concerns as several customers felt excluded from important design decisions. After-sales service received mixed evaluations, with limited follow-up once projects were completed. Price transparency was another issue, with participants expressing the need for clearer cost breakdowns and greater value for money. Reputation was considered moderately satisfactory but inconsistent due to varying customer experiences. Overall, the study emphasizes the need for carpentry technicians to strengthen critical service quality dimensions to better meet customer expectations, improve satisfaction, and enhance the sustainability of their services. Full article

9 pages, 5035 KB

Open AccessProceeding Paper

An Innovative Crab Trap Device: A Localized Laboratory Simulator for Outcome-Based Industrial Arts Education

by Cerelo T. Tabat, Jr., Alfredo S. Javier, Rondolph G. Mansal, Rogelio A. Bugtai, Jezrael Quijada and Richard A. Veray

Eng. Proc. 2026, 143(1), 16; https://doi.org/10.3390/engproc2026143016 - 15 Jun 2026

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Abstract

Crab traps are commonly used tools in both commercial and recreational fisheries to capture crabs through baited enclosures. However, the existing conventional designs often suffer from reduced catch efficiency, high bycatch rates, and rapid bait deterioration, which undermine their effectiveness and environmental sustainability. [...] Read more.

Crab traps are commonly used tools in both commercial and recreational fisheries to capture crabs through baited enclosures. However, the existing conventional designs often suffer from reduced catch efficiency, high bycatch rates, and rapid bait deterioration, which undermine their effectiveness and environmental sustainability. This study evaluated the effectiveness of an innovative crab trap setup incorporating an attractor device, designed not only to enhance crab catch rates but also to serve as a localized laboratory simulator for Outcome-Based Education (OBE) in Industrial Arts. Utilizing a developmental research design, this study was conducted in Barangay Caloc-an, Magallanes, Agusan del Norte. The research involved commercial and recreational crab fishermen, as well as electrical and electronics experts, to assist in setting up and evaluating the innovative crab trap device. The key variables examined included the type of attractor device used, the dispersal rate of the liquid bait, and the trap’s overall effectiveness in capturing crabs. Four different bait dispersal intervals were tested: 40 min, 30 min, 10 min, and 30 s. Results showed that shorter dispersal intervals significantly increased catch rates, with the 30 s interval yielding the highest and most consistent results. The developmental research framework enabled iterative testing and refinement of the trap system, allowing for continuous improvement of its components. Importantly, this study’s broader educational aim was to provide students with a practical, culturally relevant, and outcome-focused learning experience, where technical skills and scientific inquiry are applied in real-world contexts. The crab trap device served not only as a fishing tool but also as a simulated laboratory apparatus for Industrial Arts instruction, fostering skill development and engagement. Overall, this study contributes valuable insights into both fisheries management and educational innovation, demonstrating that a well-designed crab trap device can support more effective and sustainable fishing practices while also enhancing Industrial Arts education through hands-on, localized learning experiences. Full article

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11 pages, 321 KB

Open AccessProceeding Paper

Unquestioned Use of AI-Based Facial Recognition Technology in Criminal Investigations: Delhi Riots Lessons on Rights and Reliability

by Vishal Ranaware and Rahul Mishra

Eng. Proc. 2026, 143(1), 17; https://doi.org/10.3390/engproc2026143017 - 15 Jun 2026

Viewed by 1062

Abstract

In recent years, artificial intelligence (AI) has been increasingly used in criminal justice systems across the world. To achieve objectives set out through Sustainable Development Goals (SDGs), adoption of technology is inevitable and undeniable. The press release dated 25 February 2025 from India’s [...] Read more.

In recent years, artificial intelligence (AI) has been increasingly used in criminal justice systems across the world. To achieve objectives set out through Sustainable Development Goals (SDGs), adoption of technology is inevitable and undeniable. The press release dated 25 February 2025 from India’s Ministry of Law and Justice, quoting Prime Minister of India Narendra Modi to make a “justice system that will be fully future-ready”, confirmed that the Indian law enforcement agencies are integrating AI into policing and law enforcement to enhance crime detection, criminal investigation, etc. It is intended to enhance their capabilities in solving criminal cases and delivering justice speedily and more efficiently. However, the usage of AI tools in such contexts presents a double-edged sword, as evidenced by their application in a number of cases across the world like Christopher Gatlin, Nijeer Parks, the Harm Assessment Risk Tool (HART), and in India during the 2020 Delhi riots cases. As reported by the Washington Post, in Christopher Gatlin’s case it was found that the police arrested him on the basis of the facial recognition programme matching his face with the captured video footage. He spent 17 months in jail before his release by the court, observing that the police failed to conduct fair investigation. A similar incident was reported by NJ.com and CNN Business. In the investigations following the 2020 Delhi riots, Delhi Police effected over 1900 arrests in 758 riot-related cases, relying predominantly on AI-driven facial recognition matches. Subsequent court scrutiny in decided cases raised questions about reliability, leading to widespread acquittals and discharges of the accused in 82% of decided cases as of early 2025. In certain cases, AI-driven solutions have failed, leading to criminal prosecutions of innocent people based on AI-generated evidence. This study examines the reliability, validity, and ethics of AI technology in the criminal justice system in India’s unique socio-legal and political environment. The researchers analyse three interrelated axes. First, a comprehensive review of the international algorithmic policing literature to identify successes and failures. In addition, cases of AI-assisted investigations during the Delhi riots show how facial recognition systems and other AI techniques were used for inquiry. Finally, stakeholders’ perspectives, including a preliminary survey of 27 legal experts showing strong consensus on classifying AI-FRT outputs strictly as corroborative evidence and highlighting BSA insufficiencies for addressing opacity and explainability, help identify practical, procedural, and normative fault lines. Researchers noted that while AI has the potential to revolutionise resource-constrained investigative agencies, its unquestioning and uncritical adoption risks amplify pre-existing biases, undermine presumptions of innocence, and shift the burden of refuting algorithmic inference onto the accused. Independent algorithmic audits, transparent documentation of error rates and confidence thresholds, statutory guidelines on AI tool use and admissibility, and sustained capacity-building throughout the justice delivery chain are needed to integrate it into the Indian criminal justice system. Without such measures, the very tools designed and introduced to enhance accuracy threaten to undermine the fundamental norms of the criminal justice system such as fairness and due process. This fills a gap in doctrinal analysis of AI-specific evidentiary admissibility in non-Western contexts like India. This study aims to propose policy reforms, enhance judicial discourse, and promote a more circumspect trajectory for AI adoption in Indian law enforcement by mapping the potential and risks of algorithmic evidence in a non-Western legal order. Full article

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10 pages, 5909 KB

Open AccessProceeding Paper

Feasibility Assessment of Eco-Bricks: Integrating (Vivipara Angularis) Shell and Shredded Plastic Waste for Sustainable Civil and Construction Materials

by Jona J. Biongcog, Edcel John Pintoy, Kurt Justine Suizo, June Diether Ruiz and Ivy Jane Lunio

Eng. Proc. 2026, 143(1), 18; https://doi.org/10.3390/engproc2026143018 - 15 Jun 2026

Viewed by 1180

Abstract

Concrete bricks have been used in construction for over a century, often used for foundations and retaining walls. Its production contributes significantly to carbon emissions and the depletion of natural resources. Thus, this study aims to develop an outdoor brick using crushed bivalve [...] Read more.

Concrete bricks have been used in construction for over a century, often used for foundations and retaining walls. Its production contributes significantly to carbon emissions and the depletion of natural resources. Thus, this study aims to develop an outdoor brick using crushed bivalve shell (Vivipara angularis), locally known as “Ige”, as an aggregate to reduce the need for natural aggregates, which are a finite resource, and molasses as an admixture to improve the brick’s workability and strength. A series of experiments was conducted to test the bricks’ fire resistance, water absorption, and compression, aiming to determine the feasibility of making bricks from crushed bivalve shells, shredded plastic bottles, cement, sand, water, and molasses. The project used an experimental and developmental research approach. The study was conducted at the Caraga State University, Cabadbaran Campus. Results showed that (a.) Sample 2, which contains 400 g of cement, 800 g of sand, and 1200 g of bivalve freshwater shell with the ratio of 1:2:3, has good fire resistance characteristics (b.) Sample 5, which contains more plastic bottles rather than freshwater shells, performed well in water absorption and (c.) Sample 2, a mixture of 400 g of cement, 800 g of sand, and 1200 g of bivalve freshwater shell with a ratio of 1:2:3, exhibits good comprehensive strength. The study revealed that using bivalve freshwater shells can improve the durability of concrete bricks and, when combined with plastic bottles, reduce water absorption; however, it can also compromise brick durability. Full article

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11 pages, 680 KB

Open AccessProceeding Paper

Development and Evaluation of a Portable Sliding Sand Sieve for Construction and Civil Technology Laboratory Application

by Roy Vincent Perang, John Estillore, Maher Shalal Hash Baz Usa, Razen Purtado and Oliver Bernal

Eng. Proc. 2026, 143(1), 19; https://doi.org/10.3390/engproc2026143019 - 15 Jun 2026

Viewed by 636

Abstract

The study introduces a portable sliding sand sieve, transforming traditional stationary systems into an innovative solution for sand separation in the construction industry. This innovative tool offers improved mobility, durability, and operational efficiency, particularly for construction workers, civil technology students, and educators in [...] Read more.

The study introduces a portable sliding sand sieve, transforming traditional stationary systems into an innovative solution for sand separation in the construction industry. This innovative tool offers improved mobility, durability, and operational efficiency, particularly for construction workers, civil technology students, and educators in areas with limited access to advanced equipment. Utilizing a developmental research design, the study involved the conceptualization, fabrication, and evaluation of the prototype. The design incorporated locally available materials, including phenolic boards, mesh screens, steel tubing, and a sliding mechanism supported by bearings and brackets. The Input–Process–Output (IPO) model guided the development, ensuring focus on functionality, affordability, and user safety. To address this gap, the researchers aimed to design, develop, and evaluate a portable sliding sand sieve to enhance sand sieving in construction settings. Expert and student evaluators highly rated the portable sliding sand sieve for its design simplicity, functionality, durability, modularity, and ergonomics. It was praised for its ease of use, time-saving capability, and adaptability to various work environments. The sliding feature enabled continuous sand flow, enhancing productivity and reducing physical strain. Full article

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11 pages, 1699 KB

Open AccessProceeding Paper

Assessment of Technology-Enhanced Contextualized Learning Materials in Agri-Fisheries: An Expert Evaluation Using the Rosenshine Model

by John O. Estillore, Rica Florabel N. Remulta, Sannie O. Monoy, Xyra Mea E. Tabolinar and Shaira S. Sarsaba

Eng. Proc. 2026, 143(1), 20; https://doi.org/10.3390/engproc2026143020 - 16 Jun 2026

Viewed by 686

Abstract

The research aims to design and develop learning materials to be used by Agri-Fishery students. It aims to incorporate modern techniques, making it easier for the frontline to deliver the information included in the material. The use of flipbooks, PDF formats, and Canva, [...] Read more.

The research aims to design and develop learning materials to be used by Agri-Fishery students. It aims to incorporate modern techniques, making it easier for the frontline to deliver the information included in the material. The use of flipbooks, PDF formats, and Canva, a free web-based visual communication and design platform, with embedded actual field demonstration videos were made available in the developed instructional material. The ADDIE model was used to develop instructional material, highlighting the processes it employs. As the processes progressed, the learning materials were evaluated by experts in the field using the adapted Instructional Material Evaluation Checklist (IMEC). The evaluation results obtained a mean of 3.31 and an SD of 0.80, with a satisfactory remark of ‘High Evidence’. The content prevailed with the least mean of 3.22 and a standard deviation (SD) of 1.01, indicating Sufficient Evidence. The numbers from the content evaluation showed how the curriculum linked its requirements to explicit self-directed learning and outcome-based learning capabilities. Full article

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11 pages, 348 KB

Open AccessProceeding Paper

Advancing Poultry Breeding: Development of a Combined Egg Incubator and Hatchery

by Cerelo T. Tabat, Jr., Mary Nena M. Faulve, Gelmar J. Guzon, Kristian Carlo N. Pioco, Arnel C. Senoc, Jr. and Hannah C. Rosales

Eng. Proc. 2026, 143(1), 21; https://doi.org/10.3390/engproc2026143021 - 16 Jun 2026

Viewed by 730

Abstract

This study designed, developed, and evaluated a combined egg incubator and hatchery system to enhance poultry breeding efficiency, reliability, and ergonomic operation. Utilizing a developmental research design, the project addressed challenges in traditional incubation and hatching processes, including inconsistent temperature and humidity control, [...] Read more.

This study designed, developed, and evaluated a combined egg incubator and hatchery system to enhance poultry breeding efficiency, reliability, and ergonomic operation. Utilizing a developmental research design, the project addressed challenges in traditional incubation and hatching processes, including inconsistent temperature and humidity control, inadequate ventilation, frequent power interruptions, limited access to affordable materials and technical expertise, insufficient safety mechanisms, and a lack of multifunctional capability. Data were collected from 30 experts in agricultural engineering and poultry technology to evaluate design, construction, material availability, functionality, usability, safety, modularity, and ergonomics. Findings revealed the system was highly efficient, safe, and user-centered, improving hatch rates and operator comfort. Full article

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12 pages, 272 KB

Open AccessProceeding Paper

A Chaos-Theoretic Framework for Autonomous Robot Navigation in Complex and Uncertain Environments

by Konstantinos Perizes, Vassilis Alimisis and George F. Fragulis

Eng. Proc. 2026, 143(1), 22; https://doi.org/10.3390/engproc2026143022 - 16 Jun 2026

Viewed by 435

Abstract

Path planning for autonomous robots is a key problem area, particularly when faced with complicated, dynamic, or uncertain environments. Even though traditional techniques (grid-based, graph-based, sampling, and optimization-based) have already been developed to solve this problem, there are notable limitations to scalability, adaptability, [...] Read more.

Path planning for autonomous robots is a key problem area, particularly when faced with complicated, dynamic, or uncertain environments. Even though traditional techniques (grid-based, graph-based, sampling, and optimization-based) have already been developed to solve this problem, there are notable limitations to scalability, adaptability, and responsiveness with these methods. In this paper, we explore an alternative approach based on chaotic dynamical systems, specifically chaotic attractors like those produced by the Lorenz and Rössler systems. Chaotic systems are defined by several properties that could be leveraged: non-linearity, sensitivity to initial conditions, and dense coverage of the state space are three notable properties that could be used to generate trajectories that are organized, yet ultimately unpredictable. By applying numerical integration (Runge–Kutta) directly to robot motion through MATLAB R2025b simulations, chaotic states support more effective exploration, better obstacle avoidance, and more robust navigation in dynamic or adversarial environments. The paper also examines whether chaotic path planning can be applied in multi-robot systems through state coupled robots that emerge coordinated behavior while maintaining autonomous movement. This paper is a framework for chaos theory supporting adaptable, robust navigating behaviors for purposes such as autonomous vehicles, swarm robotics, and search and rescue and surveillance applications. Full article

13 pages, 2535 KB

Open AccessProceeding Paper

A BERTopic-Based Analysis of Energy Security Research: Evidence from Large-Scale Literature Mining

by Panagiotis Karsiotis and Antonios Adamopoulos

Eng. Proc. 2026, 143(1), 23; https://doi.org/10.3390/engproc2026143023 - 16 Jun 2026

Viewed by 508

Abstract

Heraclitus’ phrase “everything flows and nothing remains” perfectly captures the modern era, as conditions are changing at high speed and scientific knowledge is growing exponentially. Academic fields that attract significant attention often experience rapid expansion, driven by the growing global pool of researchers, [...] Read more.

Heraclitus’ phrase “everything flows and nothing remains” perfectly captures the modern era, as conditions are changing at high speed and scientific knowledge is growing exponentially. Academic fields that attract significant attention often experience rapid expansion, driven by the growing global pool of researchers, the increased accessibility of scientific publishing platforms, and the overall rise in scientific output. Literature concerning energy security, a topic as old as fire, has become vital to modern economies due to geopolitical upheaval, adapting traditional considerations to new realities, and the extensive body of literature serves as clear evidence of this fact. Thus, there is a clear need for innovative, scalable, and objective methodologies to systematically assess the existing body of knowledge and prioritize areas for further study. This paper proposes implementing a novel machine learning approach leveraging the BERTopic topic modeling algorithm to conduct a comprehensive and efficient exploratory analysis of energy security literature. The analysis is based on a bibliographic corpus extracted from the Scopus database covering the period 1999–2025, and identifies 14 distinct thematic clusters which indicate that energy security research is undergoing structural transformation, marked by strong emphasis on technology-specific renewable energy transitions, geographic concentration on China and Europe, and increasing integration with climate and sustainability frameworks. While contextual embedding improves semantic coherence, topic interpretation still requires expert validation as model performance is sensitive to hyperparameter configuration, potentially affecting topic stability and reproducibility. Full article

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10 pages, 340 KB

Open AccessProceeding Paper

Development of Fruit Peel Fertilizer Using Banana (Musa) and Orange (Citrus × sinensis) Peels Through Lettuce Cultivation

by Mary Nena M. Faulve, Mitchel L. Bagante, Francine Andrea V. Baño, Yesha Vercille P. Bulang and Kristine Grace P. Odvina

Eng. Proc. 2026, 143(1), 24; https://doi.org/10.3390/engproc2026143024 - 17 Jun 2026

Viewed by 1964

Abstract

This study investigated the efficacy of fruit peel-derived fertilizers from banana (Musa), orange (Citrus × sinensis), and mixed fruit peels in promoting lettuce (Lactuca sativa) growth in a hydroponic system as a sustainable alternative to synthetic nutrient [...] Read more.

This study investigated the efficacy of fruit peel-derived fertilizers from banana (Musa), orange (Citrus × sinensis), and mixed fruit peels in promoting lettuce (Lactuca sativa) growth in a hydroponic system as a sustainable alternative to synthetic nutrient solutions. The research determined the optimal concentration and application through trials, comparing effectiveness across concentrations and light exposure conditions within the first 1–2 weeks of cultivation. Findings revealed that optimal concentrations of 400–1000 g of peels per liter of water and a 3-L fertilizer combination yielded favorable outcomes under direct sunlight. The study concludes that banana and mixed peel fertilizers supported robust lettuce growth, with banana being the most effective. Full article

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9 pages, 3061 KB

Open AccessProceeding Paper

Experts’ Evaluation of an Integrated Two-in-One Lazy Susan and Dough Kneader for Laboratory Food Technology Learners

by Julanie M. Limen, Jay R. Dela Serna, Jalrymple H. Lapostre, Mechaela O. Bachinicha and Cerelo T. Tabat, Jr.

Eng. Proc. 2026, 143(1), 25; https://doi.org/10.3390/engproc2026143025 - 17 Jun 2026

Viewed by 296

Abstract

This study aims to design and develop an innovative manual kitchen tool that integrates the functionalities of a Lazy Susan and a Dough Kneader into a two-in-one setup, addressing common challenges experienced by students during laboratory activities—crowdedness, inconvenience, and physical strain associated with [...] Read more.

This study aims to design and develop an innovative manual kitchen tool that integrates the functionalities of a Lazy Susan and a Dough Kneader into a two-in-one setup, addressing common challenges experienced by students during laboratory activities—crowdedness, inconvenience, and physical strain associated with manual dough kneading. Employing a descriptive–developmental research design, the study focused on the prototype’s conceptualization, construction, and evaluation in terms of its design, construction quality and availability of materials, functionality, usability, aesthetics, modularity, and ergonomics. Survey questionnaires were administered to faculty members and field experts to assess the overall acceptability of the product. The study was conducted at Caraga State University—Cabadbaran City. Results indicated a high level of acceptability across all evaluative criteria. Although minor design issues emerged during testing, these were addressed and refined accordingly. Findings suggest that the two-in-one Lazy Susan and Dough Kneader offers significant benefits in terms of space-saving, user convenience, and manual labor reduction. With its practical design and market viability, the product is a promising tool for educational and domestic culinary settings. Further research is recommended to enhance the tool’s features, particularly by exploring the integration of solar-powered functionality to improve efficiency and sustainability. Full article

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13 pages, 716 KB

Open AccessProceeding Paper

Multi-Axis Welding Positioner: A Laboratory Simulator for Outcome-Based Instruction in Welding and Fabrication Technology Courses

by Vicardo J. Aroy, Cerelo T. Tabat, Janevic T. Caham, Rian Jemar D. Dagani, Madelyn S. Monton and Lorena Q. Renolo

Eng. Proc. 2026, 143(1), 26; https://doi.org/10.3390/engproc2026143026 - 17 Jun 2026

Viewed by 773

Abstract

This study aimed to design, develop, and evaluate a multi-axis welding positioner, designed as a laboratory simulator with 360° rotational capability and 90° tilting functionality to support outcome-based instruction in welding and fabrication technology courses. A developmental research design was employed to systematically [...] Read more.

This study aimed to design, develop, and evaluate a multi-axis welding positioner, designed as a laboratory simulator with 360° rotational capability and 90° tilting functionality to support outcome-based instruction in welding and fabrication technology courses. A developmental research design was employed to systematically address common challenges in instructional welding operations, such as limited workpiece maneuverability, inconsistent welding angles, operator fatigue, safety risks from manual repositioning, and the lack of affordable, adaptable positioning equipment. The study was conducted at Caraga State University–Cabadbaran Campus in Cabadbaran City, Agusan del Norte, and involved sixteen purposively selected experts in Welding and Fabrication Technology. These experts assessed the prototype during the design, development, and evaluation phases via a validated researcher-developed survey instrument. The welding positioner was evaluated based on the following criteria: design, construction and material availability, functionality, usability, safety, modularity, and ergonomics. Data were analyzed using descriptive statistics. Findings indicated that the prototype was highly functional, safe, and user-centered, enhancing welding accuracy and reducing operator fatigue. Of the evaluated parameters, Design, Construction, and Material Availability achieved the highest mean rating (3.61), reflecting strong structural quality and resource accessibility. Functionality received the lowest mean rating (3.51), signaling minor areas for improvement in responsiveness and component adjustability. The prototype, built from locally available, cost-effective materials, featured a motorized rotation system and a manual tilting mechanism that operated reliably during testing. The study concluded that the welding positioner met structural, ergonomic, and operational standards for use as a laboratory simulator in outcome-based welding instruction. Recommendations include integrating automated controls, enhancing portability, embedding digital monitoring features, and conducting extended performance evaluations in industrial settings. Full article

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10 pages, 1129 KB

Open AccessProceeding Paper

Lifecycle Management of Conversational AI Agents in Citizen Services Using Copilot Studio and Dataverse

by Sarat Piridi, Satyanarayana Asundi, Srinivas Kamineni and Nataraja Kumar Koduri

Eng. Proc. 2026, 143(1), 27; https://doi.org/10.3390/engproc2026143027 - 18 Jun 2026

Viewed by 465

Abstract

Lifecycle management of the conversational AI agent, in the case of Copilot Studio and Dataverse as enabling technologies, is discussed in this paper. After an in-depth examination of the academic literature, policy reports, and lifecycle models, the research also concludes that there are [...] Read more.

Lifecycle management of the conversational AI agent, in the case of Copilot Studio and Dataverse as enabling technologies, is discussed in this paper. After an in-depth examination of the academic literature, policy reports, and lifecycle models, the research also concludes that there are AI applications to be utilized in the government sector, and there are policies to be revised, alongside some ethical considerations that can and must be implemented. It has also revealed that conversational AI is so on trend that governments are employing this technology to do even more, to socialize with and serve the needs of more people in multiple languages. They can also decrease response times by 40%. But its initial condition will not endure for long. Lifecycle continuous monitoring as well as lifecycle ethics and participative design should be practiced in lifecycle governance so that nobody feels sidelined, left without influence, or interrogated. Copilot Studio is a low-code or no-code orchestration environment that runs on your code, and Dataverse ensures your data will be compatible with other systems. In the study, the theory attempts to touch on the harmonization of entities, citizen security and technical functions in the lifecycle. In this model, we will differentiate why a field-conversational AI model would lead to the creation of a vibrant, responsible, and effective service model. The technical and ethical lifecycle management of the AI integration offers a structure of accountability in which governments should extend the conversational agent according to the values held by the government. Full article

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10 pages, 827 KB

Open AccessProceeding Paper

Diffusion of Authentic Assessment in Deep Learning Approaches: The Role of Network Communication and Teacher Opinion Leadership

by Syahida Karim, Dina Siti Logayah and Mamat Ruhimat

Eng. Proc. 2026, 143(1), 28; https://doi.org/10.3390/engproc2026143028 - 22 Jun 2026

Viewed by 203

Abstract

The complexity of authentic assessment within Deep Learning frameworks often hinders teacher adoption. This study analyses the diffusion process of such an innovation at SMP Taruna Bakti Bandung using an Explanatory Sequential Mixed Methods design. Through Social Network Analysis (SNA) of the entire [...] Read more.

The complexity of authentic assessment within Deep Learning frameworks often hinders teacher adoption. This study analyses the diffusion process of such an innovation at SMP Taruna Bakti Bandung using an Explanatory Sequential Mixed Methods design. Through Social Network Analysis (SNA) of the entire teacher population and in-depth interviews, this study maps communication patterns and the roles of key actors. SNA results reveal a network structure with moderate density and subject-based clustering patterns. Qualitative findings confirm that adoption success relies heavily on opinion leaders acting as “pedagogical translators” to simplify the technical complexities of assessment. Through collaborative strategies, innovation barriers are reduced by enhancing aspects of trialability and observability. The study concludes that the adoption of authentic assessment requires synergy between formal institutional support and technical validation fostered within interpersonal trust networks, rather than relying solely on managerial instruction. Full article

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11 pages, 264 KB

Open AccessProceeding Paper

Electronic Communication and Public Relations in Secondary Education: A Quantitative Study

by Anastasios Vomvas and Maria Kouziaki

Eng. Proc. 2026, 143(1), 29; https://doi.org/10.3390/engproc2026143029 - 22 Jun 2026

Viewed by 489

Abstract

This quantitative study exαmines the pivotal role of electronic communication (EC) and public relations (PR) within secondary education institutions. In an era of rapid digital transformation, educational organizations increasingly integrate modern communication practices to enhance transparency, collaboration, and active engagement within the school [...] Read more.

This quantitative study exαmines the pivotal role of electronic communication (EC) and public relations (PR) within secondary education institutions. In an era of rapid digital transformation, educational organizations increasingly integrate modern communication practices to enhance transparency, collaboration, and active engagement within the school community. The research, based on a quantitative analysis of 196 educators and administrators, investigates perceptions regarding the frequency and effectiveness of digital tools using descriptive statistics, correlation analysis, and regression modeling. Key findings reveal a universal adoption of EC, with 72.96% of participants reporting daily use and 75.51% evaluating its effectiveness as high. Advanced statistical analysis through Multiple Linear Regression (R² = 0.538, p < 0.001) indicates that perceived effectiveness and frequency of use are the primary predictors of overall satisfaction. However, the study identifies significant institutional gaps, such as the absence of an official electronic communication protocol for crisis management (59.69%) and heightened concerns regarding data breaches (82.65%). The study concludes that there is an urgent need to establish unified communication strategies and provide continuous staff training in digital security and ethics. Full article

9 pages, 838 KB

Open AccessProceeding Paper

Forecasting Critical Spare Parts Demand in Combined Cycle Power Plant Using Ensemble Learning

by Brian Qaedi Laksono Putra and Jerry Dwi Trijoyo Purnomo

Eng. Proc. 2026, 143(1), 30; https://doi.org/10.3390/engproc2026143030 - 22 Jun 2026

Viewed by 276

Abstract

The availability of critical spare parts is essential for maintaining the reliability and operational continuity of combined cycle power plants. However, demand for critical spare parts is typically sparse, intermittent, and highly non-linear, which limits the effectiveness of conventional forecasting approaches based on [...] Read more.

The availability of critical spare parts is essential for maintaining the reliability and operational continuity of combined cycle power plants. However, demand for critical spare parts is typically sparse, intermittent, and highly non-linear, which limits the effectiveness of conventional forecasting approaches based on historical averages or expert judgment. Inaccurate demand estimation may lead to excessive inventory, high holding costs, or stock shortages that increase downtime risks. To address these challenges, this study applies ensemble learning methods to improve demand forecasting accuracy for critical spare parts in a combined cycle power plant. Procurement and usage data from 2020 to 2024 were analyzed using a time-series splitting approach, with model performance assessed using Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). To avoid bias caused by zero-demand periods, zero actual values were excluded from MAPE calculations. The results show that the tuned XGBoost model consistently performs better than Random Forest by producing lower forecasting errors and more stable predictions under intermittent demand conditions. These findings indicate that ensemble learning can support more effective procurement planning, inventory control, and maintenance decision-making in combined cycle power plant operations. Full article

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15 pages, 750 KB

Open AccessProceeding Paper

Enhancing Bitcoin Price Forecasting Through Integrated Sentiment Analysis and XGBoost Models

by Vasileios Dellopoulos, Ioannis Antoniadis, Evanggelos Saprikis and George Fragulis

Eng. Proc. 2026, 143(1), 31; https://doi.org/10.3390/engproc2026143031 - 2 Jul 2026

Viewed by 913

Abstract

This study investigates Bitcoin price forecasting using integrated sentiment analysis and gradient boosting within digital financial ecosystems. Two XGBoost models were developed using sentiment scores derived from Bitcoin news (2021–2024) and technical indicators, including GARCH-estimated volatility, Bollinger Bands, MACD, and RSI. The analysis [...] Read more.

This study investigates Bitcoin price forecasting using integrated sentiment analysis and gradient boosting within digital financial ecosystems. Two XGBoost models were developed using sentiment scores derived from Bitcoin news (2021–2024) and technical indicators, including GARCH-estimated volatility, Bollinger Bands, MACD, and RSI. The analysis uses 1042 daily Bitcoin observations and 10,025 sentiment records. Two model configurations were evaluated: one using only technical indicators and another incorporating daily aggregated sentiment scores. Model performance was assessed using Diebold–Mariano tests with Newey–West HAC variance estimation and walk-forward validation across 40 rolling windows. Contrary to expectations, sentiment features provided no statistically significant improvement over the technical-only model (p = 0.4888). Both models achieved identical test performance (R² = −0.16%). Walk-forward validation revealed substantial temporal instability (Mean R² = −126.30%, Std = 233.05%), highlighting the challenges of forecasting daily Bitcoin returns. Nevertheless, both XGBoost models significantly outperformed the random walk benchmark (DM statistic = −8.58, p < 0.0001), indicating that technical indicators capture exploitable market structure despite limited predictive accuracy for practical trading. These findings support the efficient market hypothesis and have implications for digital financial ecosystems integrating multimodal information. Full article

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13 pages, 555 KB

Open AccessProceeding Paper

The Role of AI-Driven Simulation Models in Optimizing Urban Sustainability for Smart Cities

by Abraham Samuel, Aswathy Prakash Girija, Reshma Soman Nagaparambil and Amrutha Thanka Sivan

Eng. Proc. 2026, 143(1), 32; https://doi.org/10.3390/engproc2026143032 - 7 Jul 2026

Viewed by 725

Abstract

Urban centers today face unprecedented challenges in energy management, emissions, waste disposal, and public services, as nearly 70% of the global population is projected to live in cities by 2050. The complexity and rapid evolution of urban systems underscore the pressing need for [...] Read more.

Urban centers today face unprecedented challenges in energy management, emissions, waste disposal, and public services, as nearly 70% of the global population is projected to live in cities by 2050. The complexity and rapid evolution of urban systems underscore the pressing need for stability, innovation, and adaptability, particularly regarding sustainability and digital transformation. AI-powered simulation models have emerged as transformative tools, capable of simplifying, predicting, and managing highly intricate urban systems while offering policymakers valuable insights for strategic planning. However, the integration of AI in smart and sustainable urban development presents critical legal, ethical, and regulatory concerns. This study examines these questions by evaluating existing and emerging frameworks addressing algorithmic transparency, data protection, stakeholder engagement, and sustainable development in prominent urban models including Amsterdam, Copenhagen, Singapore, Tokyo, Bangalore, and Nairobi. Comparative analysis is conducted through a doctrinal desk review, focusing on statutory provisions, international policies (EU, UN-Habitat), ISO Smart City standards, and local governance charters. Key issues addressed include the risk that AI models, if unregulated, become opaque “black boxes” that obscure both decision-making logic and accountability. Without robust standards, there is no guarantee of interoperability, revision, or representation of public interest. Equitable management, access, and inclusive participation are vital to responsible AI frameworks in urban planning. This article advances a comprehensive legal and policy framework for ensuring accountability, transparency, and stability in AI-driven city governance, bridging gaps between technological innovation, urban studies, and regulatory oversight. The proposed governance structure empowers cities to adopt multi-level, authority-driven mechanisms that safeguard the common good while leveraging AI’s potential in sustainable urban transformation. Full article

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12 pages, 1447 KB

Open AccessProceeding Paper

Machine Learning Contribution to Autism Detection Based on Theory of Mind Tasks

by Efthymia Gkarneta, Konstantinos-Filippos Kollias, Alexandra Giola Genni, Anna Triantafyllou, Panagiotis Sarigiannidis and George F. Fragulis

Eng. Proc. 2026, 143(1), 33; https://doi.org/10.3390/engproc2026143033 - 8 Jul 2026

Viewed by 483

Abstract

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental disorder marked by persistent social-communication difficulties and restricted behavioral patterns. Impairments in Theory of Mind (ToM), defined as the capacity to infer and interpret others’ mental states, are widely recognized as central to the social [...] Read more.

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental disorder marked by persistent social-communication difficulties and restricted behavioral patterns. Impairments in Theory of Mind (ToM), defined as the capacity to infer and interpret others’ mental states, are widely recognized as central to the social challenges observed in ASD. Although ToM tasks have significantly advanced the theoretical understanding of socio-cognitive deficits, their application in early detection remains limited due to subjectivity, variability in behavioral responses, and time-intensive assessment procedures. This paper presents a theoretical examination of the contribution of Machine Learning (ML) to autism detection through data derived from ToM-based tasks. We argue that ML techniques can transform behavioral, eye-tracking, and neurophysiological responses into objective, multidimensional features, enabling the identification of discriminative patterns beyond conventional statistical analyses. By integrating socio-cognitive theory with computational modeling, we propose a conceptual framework in which ML-enhanced ToM paradigms support more accurate, scalable, and non-invasive approaches to ASD detection. Full article

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11 pages, 1615 KB

Open AccessProceeding Paper

Document Route Recording System: Tool for Tracking Documents in Philippine Universities

by Adrian Forca, James Ryan Ga, Loveson Gallos and Garry Vanz Blancia

Eng. Proc. 2026, 143(1), 34; https://doi.org/10.3390/engproc2026143034 - 13 Jul 2026

Viewed by 717

Abstract

The Document Route Recording System is an intervention tool developed by Information Technology to uplift the present processes of transferring documents to various units in Philippine universities motivated by the problems that the researchers have identified in this study. The software was developed [...] Read more.

The Document Route Recording System is an intervention tool developed by Information Technology to uplift the present processes of transferring documents to various units in Philippine universities motivated by the problems that the researchers have identified in this study. The software was developed through the inspiration of the modified Waterfall model and provides three major modules: Route Creation, Acknowledgement, and Tracking, bundled as one software package. To evaluate the effectiveness of the Document Route Recording System, the ISO 25010:2015 Software Quality Instrument was utilized, and results interpreted through the descriptive research design illustrate that the objectives of the study were met effectively as all the respondents’ conclusions on quality characteristics of the software were interpreted as “Very High”. To fulfill its potential impact on the organizations, the researchers recommend fully implementing the platform to resolve the identified problems in the present system’s processes and procedures. Moreover, it is recommended for future researchers to improve and apply modern frameworks to foster further technological solutions and expand potential scope and features. Full article

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9 pages, 1555 KB

Open AccessProceeding Paper

Tripsy: An Android-Based Application for Tricycle Booking and Dispatch System in the Municipality of Romblon

by Joy Mariz M. Mindoro-Mesana, Eric John M. Manzo, Gjerck Ernst M. Aguado, Karen T. Muyo, Christopher P. Javier, Earl M. Ignacio and James Patrick M. Mesana

Eng. Proc. 2026, 143(1), 35; https://doi.org/10.3390/engproc2026143035 - 13 Jul 2026

Viewed by 832

Abstract

To meet the growing need for streamlined transit in the Municipality of Romblon, this research introduces TRIPSY, an Android-based platform for optimized tricycle dispatch and booking. The project focused on creating an intuitive interface serving three distinct groups: commuters, operators, and administrators. While [...] Read more.

To meet the growing need for streamlined transit in the Municipality of Romblon, this research introduces TRIPSY, an Android-based platform for optimized tricycle dispatch and booking. The project focused on creating an intuitive interface serving three distinct groups: commuters, operators, and administrators. While the research employed convenience sampling, a factor noted by the authors as a limitation regarding the total population of 40,554 citizens and 1295 drivers, this pilot phase successfully established a performance baseline. Empirical results from 100 passenger participants showed a high level of acceptance, yielding a weighted mean of 4.39. While the system excelled in usability and operational efficiency, “system reliability” was identified as the primary area for technical refinement. Feedback from 10 tricycle operators was even more favorable, resulting in a 4.67 mean score, though hardware compatibility remains a point for future optimization. Although the sample size was limited to a closed technical pilot designed to establish an operational baseline, TRIPSY’s alignment with international software standards and positive local reception confirm its potential as a viable transit solution. Future development will focus on enhancing system stability and cross-device integration to further solidify its efficacy in the Romblon transport sector. Full article

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12 pages, 6975 KB

Open AccessProceeding Paper

LLM for Japanese Text OCR: Automating Kuzushiji Recognition Using Decoder-Only OCR Architecture

by Damir Kim, Natalia Bogach and Evgeny Pyshkin

Eng. Proc. 2026, 143(1), 36; https://doi.org/10.3390/engproc2026143036 - 16 Jul 2026

Viewed by 355

Abstract

This study presents an application of DTrOCR approach to Japanese text optical recognition, particularly addressing the possibility of processing sophisticated writing styles such as kuzushiji or handwritten calligraphy. This approach utilizes the recently developed method which applies decoder-only transformer to the process of [...] Read more.

This study presents an application of DTrOCR approach to Japanese text optical recognition, particularly addressing the possibility of processing sophisticated writing styles such as kuzushiji or handwritten calligraphy. This approach utilizes the recently developed method which applies decoder-only transformer to the process of optical character recognition (OCR). Specifically, the current research examines the adaption of this method to the task of Japanese character recognition under the constraints of limited training and computational resources. We experimented with training the model both with and without fine-tuning using the corpora with the synthesized printed texts as well as the texts from kuzushiji—traditional Japanese cursive writing. Our findings suggest that a fine-tuned DTrOCR-based approach is promising for kuzushiji automatic recognition and can retain its accuracy on other types of Japanese texts using cursive writing. Full article

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13 pages, 7931 KB

Open AccessProceeding Paper

Evolutionary Image Augmentation with Genetic Algorithm for Enhancing CNN-Based Romblon Marble Pattern Recognition Model

by Marvin Rick G. Forcado and Sivakumar Vengusamy

Eng. Proc. 2026, 143(1), 37; https://doi.org/10.3390/engproc2026143037 - 16 Jul 2026

Viewed by 416

Abstract

This study examines the effectiveness of Genetic Algorithm (GA)-based image augmentation in enhancing Convolutional Neural Network (CNN) performance for Romblon marble texture classification. Five CNN architectures, AlexNet, InceptionV3, VGG16, MobileNet, and ResNet50, were trained and evaluated on both raw and GA-augmented datasets. Unprocessed [...] Read more.

This study examines the effectiveness of Genetic Algorithm (GA)-based image augmentation in enhancing Convolutional Neural Network (CNN) performance for Romblon marble texture classification. Five CNN architectures, AlexNet, InceptionV3, VGG16, MobileNet, and ResNet50, were trained and evaluated on both raw and GA-augmented datasets. Unprocessed dataset achieved limited accuracy, with InceptionV3 performing best at 35.33%, followed closely by VGG16 at 33.78%. In contrast, GA-augmented data significantly boosted performance, with VGG16 achieving 94.68% accuracy, followed by MobileNet (92.68%) and InceptionV3 (92.46%). Entropy loss values consistently decreased across all models, indicating improved convergence and reduced overfitting. Although ROC-AUC scores remained close to 0.5, reflecting modest improvements in class separability, overall results confirm that evolutionary augmentation enriches dataset diversity and strengthens CNN learning capacity. MobileNet showed a solid balance between accuracy and computational economy, underscoring the possibility of GA-based augmentation as a workable option for real-world marble categorization, while VGG16 emerged as the most accurate of the studied architectures. Full article

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10 pages, 1032 KB

Open AccessProceeding Paper

Development of Alumni Information Management System in a State University

by Floyd Garvilles, Johanna Clair Temporosa, Russel Belona, Jeramie Gallego, Alexis Gamao, James Ryan Ga and Garry Vanz Blancia

Eng. Proc. 2026, 143(1), 38; https://doi.org/10.3390/engproc2026143038 - 17 Jul 2026

Viewed by 804

Abstract

This study developed a web-based Alumni Information Management System in a state university to centralize alumni data, enhance networking opportunities, and support career development. Designed to be intuitive and user-friendly, the AIMS allows alumni to easily update their personal profiles, specify job preferences, [...] Read more.

This study developed a web-based Alumni Information Management System in a state university to centralize alumni data, enhance networking opportunities, and support career development. Designed to be intuitive and user-friendly, the AIMS allows alumni to easily update their personal profiles, specify job preferences, and upload resumes. The system’s design is informed by frameworks such as the Information Systems Success Model and UTAUT, ensuring high usability and acceptance. The Alumni Information Management System (AIMS) effectively enhances communication between the institution and its alumni. Centralizing alumni information has demonstrably improved engagement, streamlined networking, and empowered alumni to identify relevant career opportunities through features like job alerts, integrated application tools, and an intuitive interface. These features are effective in strengthening the bond between alumni and the institution, ultimately fostering enhanced career support and expanded networking possibilities. This research identifies and addresses a previously unrecognized need specific to state university alumni. While existing studies contribute valuable insights to alumni engagement and career support, a research gap exists regarding the integration of these services within a tailored platform for state university alumni. This study’s system offers a practical and scalable solution for universities facing similar challenges. Full article

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14 pages, 242 KB

Open AccessProceeding Paper

A Survey on Federated Learning and Edge Computing: Applications, Advantages, and Challenges

by Theodora Nevrataki, Panagiotis Radoglou-Grammatikis, Antonios Sarigiannidis, Panagiotis Sarigiannidis and George F. Fragulis

Eng. Proc. 2026, 143(1), 39; https://doi.org/10.3390/engproc2026143039 - 20 Jul 2026

Viewed by 596

Abstract

Federated learning (FL) and edge computing are transformative technologies that enhance privacy, efficiency, and real-time intelligence for distributed machine learning across diverse edge device networks. FL enables devices to collaboratively train models locally, so sensitive data remains on each device, ensuring privacy and [...] Read more.

Federated learning (FL) and edge computing are transformative technologies that enhance privacy, efficiency, and real-time intelligence for distributed machine learning across diverse edge device networks. FL enables devices to collaboratively train models locally, so sensitive data remains on each device, ensuring privacy and regulatory compliance (like GDPR and HIPAA). Edge computing complements FL by bringing data processing closer to sources such as IoT sensors and smartphones, which reduces latency, bandwidth use, and dependence on cloud servers. This architecture is vital for smart cities, healthcare, industry, and autonomous systems, supporting real-time decision-making. The review details challenges such as resource heterogeneity, communication constraints, security risks, and management complexity, while highlighting opportunities for scalable orchestration, decentralized architectures, and blockchain integration. Together, FL and edge computing create a robust paradigm for scalable, privacy-aware distributed intelligence across multiple domains. Full article

12 pages, 686 KB

Open AccessProceeding Paper

Hybrid Human–Machine Intelligence for Smart Learning: A Multidisciplinary Approach to Context-Aware, Adaptive, and Explainable Educational Systems

by Nisreen A. Alzahrani, Yerragolla Hareesh Kumar and Gopalappa Bindusree

Eng. Proc. 2026, 143(1), 40; https://doi.org/10.3390/engproc2026143040 - 20 Jul 2026

Viewed by 457

Abstract

The growing demand for personalized learning in digital education has encouraged researchers to explore artificial-intelligence-driven recommendation systems. However, most existing systems rely solely on either content-based or collaborative filtering methods, limiting their adaptability and performance in real-world educational environments. Moreover, such approaches often [...] Read more.

The growing demand for personalized learning in digital education has encouraged researchers to explore artificial-intelligence-driven recommendation systems. However, most existing systems rely solely on either content-based or collaborative filtering methods, limiting their adaptability and performance in real-world educational environments. Moreover, such approaches often face challenges related to data sparsity, cold-start issues, and limited explainability, reducing their effectiveness in diverse learner contexts. This paper introduces a novel Hybrid Human–Machine Intelligence Framework designed to build context-aware, adaptive, and transparent learning recommendation systems. Using behavioral and demographic data from the Open University Learning Analytics Dataset (OULAD), the framework employs a multi-task deep learning model to jointly predict each learner’s engagement level and preferred learning modality. These predictions serve as the foundation for a weighted hybrid recommendation engine that integrates content-based, collaborative, and knowledge-based filtering to generate highly personalized suggestions. An explainable reasoning module further translates the hybrid scores into clear, pedagogically meaningful justifications to enhance trust and instructional relevance. Experimental results demonstrate that the proposed model effectively mitigates cold-start issues and outperforms traditional machine learning baselines, achieving an RMSE of approximately 0.09, an MAE of 0.05, and an R2 value close to 0.99. The findings highlight the potential of hybrid human–machine intelligence to bridge cognitive understanding and computational learning, thereby advancing the design of adaptive and interpretable smart education systems. Full article

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15 pages, 2838 KB

Open AccessProceeding Paper

AI-Powered Analytics in Technical Communication: Advancing Information Management Toward Content Data Science

by Wolfgang Ziegler

Eng. Proc. 2026, 143(1), 41; https://doi.org/10.3390/engproc2026143041 - 20 Jul 2026

Cited by 3 | Viewed by 440

Abstract

We introduce a similarity-based ensemble framework for assessing the AI-readiness of topic-based technical content in Retrieval-Augmented Generation (RAG) contexts. Rather than evaluating RAG performance through query-and-answer measurements, the proposed approach characterizes content corpora through microscopic similarity metrics—mean similarity difference (MSD) and similarity width [...] Read more.

We introduce a similarity-based ensemble framework for assessing the AI-readiness of topic-based technical content in Retrieval-Augmented Generation (RAG) contexts. Rather than evaluating RAG performance through query-and-answer measurements, the proposed approach characterizes content corpora through microscopic similarity metrics—mean similarity difference (MSD) and similarity width (SimWidth)—derived from vector representations of individual topics. These metrics quantify the distinctiveness and contextual precision of topic ensembles, providing a corpus-specific indicator of expected RAG behavior prior to deployment. The method is validated across four separately published industry-academic research projects in the PIAI!-Lab framework in different industrial domains. Results consistently confirm that modular, PI-Class-based information architectures with concise metadata improve ensemble-level AI-readiness, while variant-rich content without metadata pre-filtering reduces context precision. Beyond the technical findings, the paper demonstrates that Content Data Science methods can be effectively integrated into advanced academic research in technical communication, bridging information management and data science methodology. Full article

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11 pages, 4274 KB

Open AccessProceeding Paper

Design and Development of iSign: An Android-Based Educational Mobile Application for Deaf and Hard-of-Hearing Individuals

by Dave D. Lota, Pia S. Estabaya, Regine N. Famini, Angelie Mae S. Madali, Kimberly M. Vargas, Wenna Mae Q. Foja and Preexcy B. Tupas

Eng. Proc. 2026, 143(1), 42; https://doi.org/10.3390/engproc2026143042 - 20 Jul 2026

Viewed by 459

Abstract

This study presents the design, development, and evaluation of iSign, an Android-based educational mobile application developed to support sign language learning among deaf and hard-of-hearing individuals in rural communities. The project was conducted using a research and development (R&D) approach guided by the [...] Read more.

This study presents the design, development, and evaluation of iSign, an Android-based educational mobile application developed to support sign language learning among deaf and hard-of-hearing individuals in rural communities. The project was conducted using a research and development (R&D) approach guided by the ADDIE instructional design framework. A preliminary needs assessment, based on municipal records and field validation, revealed limited access to structured sign language education and assistive learning resources in selected barangays of Odiongan, Romblon. The iSign application was designed as a user-centered and accessible mobile learning tool incorporating alphabet learning (A–Z), number recognition (0–9), a dictionary containing 160 commonly used vocabulary words with definitions and corresponding sign language video demonstrations, and multimedia content such as nursery rhyme songs interpreted in sign language. The system was developed using Android Studio and structured to support offline accessibility to accommodate low-connectivity environments. The application was evaluated in terms of functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability. Twenty-one community participants and four information technology experts assessed the system using a five-point Likert scale. The overall weighted mean rating of 4.0 (“Agree”) indicates that the developed application met acceptable software quality standards and user satisfaction levels. The findings demonstrate that iSign is a functional and accessible mobile learning application that can serve as a supplementary tool for sign language education in underserved communities. Full article

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9 pages, 1717 KB

Open AccessProceeding Paper

Development of PetVax: A Mobile Application for Rabies Cases

by Maria Lea E. Gatungay, Kate G. Lorite, Precy Marie A. Gerola, Lykha G. Geonigo, Naneth S. Bongar, Loveson C. Gallos and Garry Vanz Blancia

Eng. Proc. 2026, 143(1), 43; https://doi.org/10.3390/engproc2026143043 - 20 Jul 2026

Viewed by 434

Abstract

Rabies remains a significant public health concern, primarily due to unregistered pets and insufficient vaccination monitoring. This study introduces PetVax, a mobile application designed to address rabies cases by facilitating pet registration, vaccination monitoring, and communication between pet owners and local authorities. The [...] Read more.

Rabies remains a significant public health concern, primarily due to unregistered pets and insufficient vaccination monitoring. This study introduces PetVax, a mobile application designed to address rabies cases by facilitating pet registration, vaccination monitoring, and communication between pet owners and local authorities. The primary objectives are to streamline pet record management, enhance vaccination compliance, and improve accessibility to vaccination schedules. The study follows the System Development Life Cycle (SDLC) methodology, including requirements gathering, system design, development, testing, and deployment. PetVax was developed with the use of technology tools such as Flet, Python, and SQlite. The application incorporates features such as pet registration, vaccination reminders, and notifications of upcoming rabies vaccination events, with all data stored in a centralized database for easy retrieval. The results demonstrate improved pet registration accuracy, increased vaccination compliance, and enhanced accessibility to pet health records. The novelty of this research lies in its integration of digital pet health management within a user-friendly platform, ensuring real-time data accessibility for both pet owners and administrators. PetVax significantly contributes to rabies prevention efforts by providing an efficient, scalable solution for local governments and pet owners. Full article

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13 pages, 4281 KB

Open AccessProceeding Paper

A Bibliometric Analysis of Phishing Detection Using NLP in Business Enterprises

by Yadana Myint Hein, Kumuduni Ranasinghe, Noushad Sahad, Shuang Chiao Wan, Naoki Sekizawa and Yoshitaka Kuroiwa

Eng. Proc. 2026, 143(1), 44; https://doi.org/10.3390/engproc2026143044 - 21 Jul 2026

Viewed by 360

Abstract

The advancement of natural language processing (NLP), transformer architectures, and large language models (LLMs) has reshaped phishing detection research within business and enterprise environments. However, the structural evolution, thematic transitions, and collaboration patterns of this domain remain insufficiently mapped. This study conducts a [...] Read more.

The advancement of natural language processing (NLP), transformer architectures, and large language models (LLMs) has reshaped phishing detection research within business and enterprise environments. However, the structural evolution, thematic transitions, and collaboration patterns of this domain remain insufficiently mapped. This study conducts a bibliometric analysis of Scopus-indexed publications from 2020 to 2025. Using VOSviewer and Bibliometrix (RStudio), we perform performance analysis and science mapping, including co-authorship, co-citation, bibliographic coupling, and keyword co-occurrence analyses. The findings reveal a clear methodological shift from traditional machine learning toward deep learning and transformer-based architectures, particularly after 2023. Two dominant research clusters emerge: conventional feature-based phishing detection and NLP-driven AI security approaches. While large language models and multi-channel phishing detection are gaining prominence, enterprise-level implementation and interdisciplinary integration remain limited. This study identifies emerging trends, collaboration gaps, and underexplored themes, providing directions for future research and practical cybersecurity development. Full article

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11 pages, 347 KB

Open AccessProceeding Paper

Dynamic PI-Classification and UML Generation for Automotive Manual Intelligence

by Minnah Aamir and Debopriyo Roy

Eng. Proc. 2026, 143(1), 45; https://doi.org/10.3390/engproc2026143045 - 20 Jul 2026

Viewed by 332

Abstract

As industries transition to Industry 4.0 and 5.0, the reliance on intelligent information systems continues to grow. However, many technical manuals remain static, text-based documents that are difficult to search, interpret, and apply in real-world operational contexts. This paper presents Smart Manual Assistant, [...] Read more.

As industries transition to Industry 4.0 and 5.0, the reliance on intelligent information systems continues to grow. However, many technical manuals remain static, text-based documents that are difficult to search, interpret, and apply in real-world operational contexts. This paper presents Smart Manual Assistant, an automated conversational system that transforms complex automotive manuals into interactive, role-adaptable knowledge resources. The core of the system leverages a Large Language Model (LLM) to dynamically generate PI-Class metadata, organizing content according to key intrinsic and extrinsic product and information attributes. This structured metadata enables precise content classification and supports context-aware responses tailored to different user types, including drivers and service technicians. A key contribution of the system is its dual-output response mechanism. Alongside natural language explanations, the assistant automatically generates PlantUML code and the corresponding visual diagrams (e.g., activity, sequence, and component diagrams). This provides immediate visualizations of system interactions and procedural workflows, significantly improving comprehension and usability. The Smart Manual Assistant implements a complete end-to-end pipeline—from manual ingestion to intelligent, visual, and role-specific guidance. The solution is built using a Django REST backend, a Chatbase-based interface, and Zapier automation for conversation logging to Google Sheets. The results demonstrate a practical framework for transforming static technical documentation into adaptive, data-driven support systems, enhancing accessibility, training efficiency, and real-time decision-making. Full article

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13 pages, 3707 KB

Open AccessProceeding Paper

Designing Ergonomic Interfaces for Left-Handed Users: A Human–Computer Interaction (HCI) Perspective

by Wai Yie Leong

Eng. Proc. 2026, 143(1), 46; https://doi.org/10.3390/engproc2026143046 - 20 Jul 2026

Viewed by 451

Abstract

Left-handed individuals represent approximately 10% of the global population, yet most digital interfaces, interaction devices, and software workflows remain optimized for right-handed users. This asymmetry often results in reduced usability, higher cognitive load, and decreased task efficiency for left-handed users. This paper presents [...] Read more.

Left-handed individuals represent approximately 10% of the global population, yet most digital interfaces, interaction devices, and software workflows remain optimized for right-handed users. This asymmetry often results in reduced usability, higher cognitive load, and decreased task efficiency for left-handed users. This paper presents a comprehensive Human–Computer Interaction (HCI) investigation into ergonomic interface design tailored for left-handed users. Through an extensive literature review, ergonomic task analysis, and mixed-method evaluation involving motion tracking, Fitts’ Law modelling, and user experience surveys, the study identifies critical design limitations and proposes an ergonomically optimized interface framework. Experimental results demonstrate significant improvements in accuracy, comfort, and interaction speed when left-handed-oriented adaptations are applied. The findings highlight the need for inclusive interaction paradigms and provide an evidence-based design guide for developers, interface architects, and device manufacturers seeking to support equitable accessibility in digital systems. Full article

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12 pages, 2120 KB

Open AccessProceeding Paper

A Comparison of Information Architectures of Software Documentation in RAG-Based Delivery Scenarios

by Julian Muschinski, Julian Reiling, Rika Westenhoff and Wolfgang Ziegler

Eng. Proc. 2026, 143(1), 47; https://doi.org/10.3390/engproc2026143047 - 20 Jul 2026

Cited by 2 | Viewed by 253

Abstract

This paper examines the relevance of information architectures of content used for RAG-based systems within the domain of software documentation. It specifically focuses on how information architectures impact the retrieval performance of such documentation. For this purpose, the content is prepared using automated [...] Read more.

This paper examines the relevance of information architectures of content used for RAG-based systems within the domain of software documentation. It specifically focuses on how information architectures impact the retrieval performance of such documentation. For this purpose, the content is prepared using automated data processing, and its performance is evaluated through reuse metrics derived from previous research in technical communication. Furthermore, the paper investigates the effects of different truncation strategies and embedding models on retrieval performance. Finally, the sensitivity of the reuse metric MSD is evaluated by conducting a robustness test. Full article

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12 pages, 4806 KB

Open AccessProceeding Paper

Building Inspection Decision Support System for Bureau of Fire Protection in the Province of Romblon

by Joy Mariz M. Mindoro-Mesana, Ryndel V. Amorado and James Patrick M. Mesana

Eng. Proc. 2026, 143(1), 48; https://doi.org/10.3390/engproc2026143048 - 22 Jul 2026

Viewed by 341

Abstract

This research focuses on the creation and implementation of a digital Decision Support System for building inspections at the Bureau of Fire Protection (BFP) in Romblon, Romblon. For a long period, the agency has relied on traditional, paper-heavy workflows, leading to operational bottlenecks [...] Read more.

This research focuses on the creation and implementation of a digital Decision Support System for building inspections at the Bureau of Fire Protection (BFP) in Romblon, Romblon. For a long period, the agency has relied on traditional, paper-heavy workflows, leading to operational bottlenecks that necessitate modernization. This project re-imagines BFP operations by introducing a web-based framework to handle building permit and certificate applications digitally. The paper outlines the technical parameters, data structures, and configurations used to capture inspection details essential for generating official reports and Fire Safety Inspection Certificates (FSICs). Key findings highlight the success of contactless licensing procedures and the automated generation of corrective actions based on the Revised Implementing Rules and Regulations of the Philippine Fire Code (RA 9514). Evaluation via the ISO 25010:2011 metric yielded a weighted mean of 4.41, signifying a “very satisfactory” performance level for the system within the Romblon BFP office. Full article

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12 pages, 2870 KB

Open AccessProceeding Paper

Semantic Information Architectures and Topic Ensemble Properties in AI Delivery of Product Information in the Domain of Water Treatment

by Marlene Groß, Naomie Heck and Wolfgang Ziegler

Eng. Proc. 2026, 143(1), 49; https://doi.org/10.3390/engproc2026143049 - 22 Jul 2026

Cited by 1 | Viewed by 334

Abstract

This paper examines how semantic information architectures within technical communication shape topic ensemble properties being relevant for retrieval-augmented generation (RAG) systems. They allow for investigating the AI-readiness of technical content for AI-based delivery in the present domain of water treatment. The analysis characterizes [...] Read more.

This paper examines how semantic information architectures within technical communication shape topic ensemble properties being relevant for retrieval-augmented generation (RAG) systems. They allow for investigating the AI-readiness of technical content for AI-based delivery in the present domain of water treatment. The analysis characterizes the dependence of AI-driven delivery on similarity-based metrics and metadata completeness. Topic content management is operationalized within the PI-Class framework by analyzing topics with respect to content variants and versioning, and by assessing their implications for retrieval precision. Building on previous research in technical communication, the paper further investigates the role of large language models (LLMs) in supporting the content engineering phase through automated analysis of legacy documents, derivation of metadata classifications, and curation of the resulting semantic structures in knowledge graphs. Full article

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13 pages, 20548 KB

Open AccessProceeding Paper

Quantitative Evaluation of Museum Exhibition Layouts Using Visitor Flow Analysis

by Ryuki Kito, Shigeo Takahashi, Yukihide Kohira, Yohei Nishidate and Rentaro Yoshioka

Eng. Proc. 2026, 143(1), 50; https://doi.org/10.3390/engproc2026143050 - 24 Jul 2026

Viewed by 392

Abstract

Exhibition layouts in museums strongly influence visitors’ learning and viewing experiences, yet their evaluation often relies on curators’ subjective judgments. This study aims to provide objective behavioral data through visitor flow analysis to support evidence-based exhibition design. Single-board computers installed in the museum [...] Read more.

Exhibition layouts in museums strongly influence visitors’ learning and viewing experiences, yet their evaluation often relies on curators’ subjective judgments. This study aims to provide objective behavioral data through visitor flow analysis to support evidence-based exhibition design. Single-board computers installed in the museum exhibition rooms serve as sensors to detect humans in captured images using machine learning. Detected positions are projected onto a floor map using a homography transformation to reconstruct visitors’ spatiotemporal behavior. The proposed system enables server-side real-time analysis and visualization, allowing curators to quickly and objectively understand visitor movement patterns. Full article

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11 pages, 3222 KB

Open AccessProceeding Paper

KamAI: A Basic Filipino Sign Language Recognition Mobile Application Using Deep Learning

by Dave D. Lota, Catherine Bhel B. Aguila and Dayne N. Fradejas

Eng. Proc. 2026, 143(1), 51; https://doi.org/10.3390/engproc2026143051 - 30 Jul 2026

Viewed by 616

Abstract

KamAI is an Android-based mobile application designed to support the learning and recognition of basic Filipino Sign Language (FSL), the official sign language of the Deaf community in the Philippines. The system integrates Convolutional Neural Networks (CNNs) and Google MediaPipe to enable real-time [...] Read more.

KamAI is an Android-based mobile application designed to support the learning and recognition of basic Filipino Sign Language (FSL), the official sign language of the Deaf community in the Philippines. The system integrates Convolutional Neural Networks (CNNs) and Google MediaPipe to enable real-time gesture recognition for FSL letters, numbers, and common words. To evaluate the application’s overall quality and practical usability, User Acceptance Testing (UAT) was conducted using the ISO/IEC 25010 software quality framework. Six quality attributes, Functionality, Reliability, Compatibility, Usability, Efficiency, and Portability, were assessed using a five-point Likert scale. Results showed that all evaluated attributes received “Highly Acceptable” ratings, with mean scores ranging from 4.50 to 4.77. Functionality (4.73) and Portability (4.77) received the highest ratings, indicating accurate recognition performance and effective operation across various Android devices. These findings demonstrate strong user approval and confirm KamAI’s readiness for real-world deployment as a mobile assistive learning tool that promotes inclusive education and digital accessibility in the Philippine context. Full article

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22 pages, 259 KB

Open AccessProceeding Paper

A Configurable Intelligent Framework for Digital Learning Environment Assessment in Higher Education

by Iris Mihajlović, Tonći Svilokos and Mario Bilić

Eng. Proc. 2026, 143(1), 52; https://doi.org/10.3390/engproc2026143052 - 4 Aug 2026

Viewed by 296

Abstract

Digital transformation has fundamentally reshaped higher education, creating a need for adaptive systems capable of integrating technological infrastructure, learner capabilities, institutional readiness, and learning analytics into a unified decision-support environment. While existing studies predominantly examine online learning from pedagogical or behavioural perspectives, comparatively [...] Read more.

Digital transformation has fundamentally reshaped higher education, creating a need for adaptive systems capable of integrating technological infrastructure, learner capabilities, institutional readiness, and learning analytics into a unified decision-support environment. While existing studies predominantly examine online learning from pedagogical or behavioural perspectives, comparatively little attention has been devoted to configurable system architectures that support institutional monitoring and continuous optimization of digital learning ecosystems. This paper addresses this gap by proposing a configurable Digital Learning Capability Assessment Framework (DLCAF), a modular systems framework designed to assess, monitor, and optimize digital learning environments through the integration of infrastructure capabilities, digital literacy, learner motivation, technology acceptance, and institutional performance indicators. The framework employs a layered architecture comprising data acquisition, capability assessment, analytics, decision-support, and feedback modules, enabling flexible configuration according to institutional requirements and educational contexts. To demonstrate the applicability of the proposed framework, a survey involving 220 students from 27 study programs across Croatian higher education institutions was conducted during the COVID-19 digital transition. The empirical findings serve as an application case for validating the framework and illustrating how learner perceptions, technical constraints, institutional support, and digital readiness can be systematically incorporated into an adaptive decision-support process. The results indicate that technical infrastructure, learner motivation, digital competencies, communication quality, and institutional support collectively influence the effectiveness of digital learning environments. The proposed framework transforms these heterogeneous indicators into actionable institutional intelligence that supports evidence-based planning, continuous monitoring, and targeted intervention strategies. By repositioning digital learning evaluation as a systems engineering problem rather than solely an educational assessment exercise, this work contributes a reusable and extensible framework that can be deployed across diverse higher education environments. The architecture provides a foundation for future integration of artificial intelligence, learning analytics, predictive modelling, and adaptive recommendation mechanisms, supporting the development of intelligent digital learning ecosystems capable of continuous improvement and institutional decision support. Full article

11 pages, 2803 KB

Open AccessProceeding Paper

Content and AI-Delivery Analytics of Semantically Enriched Content in Engine Manufacturing

by Gia Long Nguyen, Elisabeth Alice Schardt and Wolfgang Ziegler

Eng. Proc. 2026, 143(1), 53; https://doi.org/10.3390/engproc2026143053 - 3 Aug 2026

Cited by 1 | Viewed by 174

Abstract

Standard Retrieval–Augmented Generation (RAF) often fails in safety-critical manufacturing and reveals the inherent problem of additional and inappropriate retrieved context topics. In engine manufacturing, where topic-based documentation is widely variant-driven, semantic similarity no longer correlates with technical relevance, assembly procedures for engine variants [...] Read more.

Standard Retrieval–Augmented Generation (RAF) often fails in safety-critical manufacturing and reveals the inherent problem of additional and inappropriate retrieved context topics. In engine manufacturing, where topic-based documentation is widely variant-driven, semantic similarity no longer correlates with technical relevance, assembly procedures for engine variants are linguistically often almost identical yet operationally incorrect. Recent RAG systems, relying on the LLM’s ability to discern this context noise during the generation phase, might fail to account for this extreme content-wise overlap. This paper proposes a dual-optimization strategy: ensemble sizing and semantic level enhancement. Instead of relying solely on vector similarity, we partition the retrieval space into sub-ensembles and apply a metadata scoring function. Our findings demonstrate that this hybrid approach might help to transform RAG-based systems into more variant-appropriate delivery systems essential for safety-critical environments. Full article

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12 pages, 222 KB

Open AccessProceeding Paper

A Data-Driven Analytics Configuration for Instructional Performance Monitoring in Digital Learning Ecosystems

by Ritchfildjay L. Mariscal, Rey Jay J. Abellanosa, Mhark Clester O. Sy and Jonie T. Enclonar

Eng. Proc. 2026, 143(1), 54; https://doi.org/10.3390/engproc2026143054 - 4 Aug 2026

Viewed by 285

Abstract

The increasing adoption of digital learning environments has generated large volumes of learner-generated data that can be leveraged to support instructional quality monitoring, educational performance assessment, and evidence-based decision-making. As educational institutions seek scalable mechanisms for evaluating teaching effectiveness within technology-enabled learning ecosystems, [...] Read more.

The increasing adoption of digital learning environments has generated large volumes of learner-generated data that can be leveraged to support instructional quality monitoring, educational performance assessment, and evidence-based decision-making. As educational institutions seek scalable mechanisms for evaluating teaching effectiveness within technology-enabled learning ecosystems, there is a growing need for analytics-driven systems capable of transforming learner feedback into actionable performance intelligence. This study proposes an Instructional Quality Analytics System (IQAS) designed to collect, process, analyze, and visualize instructional effectiveness indicators within digital learning environments. The proposed system architecture consists of four integrated components: feedback acquisition, instructional quality analytics, performance monitoring, and decision-support reporting. The framework utilizes structured learner-generated evaluation data to model instructional effectiveness across multiple dimensions, including content quality, instructional delivery, learning environment support, and instructional management practices. Through quantitative analytics mechanisms, the system generates performance indicators, identifies instructional strengths and improvement opportunities, and supports continuous quality assurance processes. To demonstrate the feasibility of the proposed architecture, a pilot implementation was conducted using evaluation data collected from higher education learners within a technology-supported educational environment. Analytical results indicated consistently positive instructional performance across all assessment dimensions, with content-related indicators exhibiting the strongest performance characteristics. The evaluation further demonstrated stable instructional quality profiles across learner groups, suggesting the suitability of the framework for institution-wide monitoring and benchmarking applications. The proposed Instructional Quality Analytics System contributes a scalable architecture for educational performance monitoring and instructional effectiveness assessment within digital learning ecosystems. By integrating feedback analytics, performance intelligence generation, and decision-support capabilities, the framework provides a foundation for next-generation educational monitoring platforms, quality assurance systems, and intelligent learning analytics environments. The study offers practical implications for the development of data-driven educational governance mechanisms that support continuous improvement, resource optimization, and evidence-based instructional decision-making. Full article

12 pages, 8629 KB

Open AccessProceeding Paper

Content Reuse Analytics and AI Readiness Assessment for Content in the Maritime Product Component Supplier Domain

by Jasmina Behabetz, Nadine Gatzke and Wolfgang Ziegler

Eng. Proc. 2026, 143(1), 55; https://doi.org/10.3390/engproc2026143055 - 6 Aug 2026

Viewed by 125

Abstract

This paper addresses content reuse analytics and AI readiness assessment in the domain of maritime product component suppliers, with a particular emphasis on RAG processes and the role of reuse-related metrics. Built on previous research in technical communication, content engineering, and information architectures, [...] Read more.

This paper addresses content reuse analytics and AI readiness assessment in the domain of maritime product component suppliers, with a particular emphasis on RAG processes and the role of reuse-related metrics. Built on previous research in technical communication, content engineering, and information architectures, the paper investigates how the structure, similarity characteristics, and metadata of maritime component documentation interact with RAG mechanisms when contextual information is supplied to LLMs in AI-based delivery scenarios. The paper investigates how various parameters, such as content similarity, influence retrieval accuracy and output quality while analyzing patterns of topic reuse. Full article

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15 pages, 514 KB

Open AccessProceeding Paper

A Computational Architecture for Learning Behavior Analytics in AI-Enhanced Educational System

by Ritchfildjay L. Mariscal, Nemuel H. Awid, Kurt Andrew O. Jale and Stanley J. Sy

Eng. Proc. 2026, 143(1), 56; https://doi.org/10.3390/engproc2026143056 - 10 Aug 2026

Viewed by 421

Abstract

The rapid integration of Generative Artificial Intelligence (GenAI) technologies into educational environments has generated new opportunities for developing intelligent systems capable of monitoring learner interactions, modeling learning behaviors, and supporting adaptive educational decision-making. As learners increasingly engage with AI-powered tools for content generation, [...] Read more.

The rapid integration of Generative Artificial Intelligence (GenAI) technologies into educational environments has generated new opportunities for developing intelligent systems capable of monitoring learner interactions, modeling learning behaviors, and supporting adaptive educational decision-making. As learners increasingly engage with AI-powered tools for content generation, information retrieval, problem solving, and knowledge construction, educational platforms require robust analytics architectures that can transform human–AI interaction data into actionable insights for instructors, administrators, and learning support systems. This paper proposes a computational architecture for learning behavior analytics in AI-enhanced educational environments. The architecture integrates multiple analytical components, including learner interaction monitoring, behavioral data aggregation, AI utilization profiling, performance-related indicator analysis, and decision-support modules for adaptive intervention and learner support. The proposed framework is designed to capture measurable dimensions of AI-assisted learning behavior, enabling educational systems to identify usage patterns, model learner engagement, and generate analytics-driven recommendations for instructional improvement. The architecture adopts a data-driven approach in which behavioral indicators derived from learner interactions with GenAI tools are processed through learning analytics mechanisms to support predictive modeling, learner classification, and intelligent feedback generation. The framework further incorporates dashboards and reporting components that facilitate real-time monitoring of AI-assisted learning activities and provide evidence-based insights for educational stakeholders. To demonstrate the applicability of the proposed architecture, a pilot implementation was conducted using learner interaction and perception data collected from higher education students. Preliminary analytical results indicate that task-specific AI utilization behaviors provide meaningful behavioral signals that can be incorporated into learner modeling and adaptive learning analytics processes. These findings support the feasibility of integrating GenAI interaction data into intelligent educational systems for monitoring and decision-support purposes. The proposed architecture contributes to the development of next-generation educational technologies by providing a scalable framework for learning behavior analytics, human–AI interaction modeling, and intelligent educational decision support. The study offers practical implications for the design of adaptive learning platforms, educational data analytics systems, and AI-enabled learning environments that support effective and responsible human–AI collaboration. Full article

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12 pages, 214 KB

Open AccessProceeding Paper

A Data-Driven Architecture for Digital Capability Analytics and Readiness Assessment in Technology-Enhanced Educational Systems

by Ritchfildjay L. Mariscal, Dave Francis F. Bonso, James M. Bulaga and Jericho I. Gudito

Eng. Proc. 2026, 143(1), 57; https://doi.org/10.3390/engproc2026143057 - 10 Aug 2026

Viewed by 359

Abstract

The rapid digital transformation of education has increased the demand for intelligent assessment systems and architecture capable of evaluating institutional readiness for technology-enhanced teaching, learning, and workforce development. As educational organizations adopt digital platforms, cloud-based learning environments, and globally connected instructional models, there [...] Read more.

The rapid digital transformation of education has increased the demand for intelligent assessment systems and architecture capable of evaluating institutional readiness for technology-enhanced teaching, learning, and workforce development. As educational organizations adopt digital platforms, cloud-based learning environments, and globally connected instructional models, there is a growing need for systematic frameworks that can assess human, technological, and organizational capabilities required for successful implementation. This study proposes a digital capability assessment framework for technology-enhanced educational systems that integrates instructional competency evaluation, technology readiness analysis, infrastructure assessment, and institutional support monitoring within a unified analytics-driven model. The proposed framework consists of multiple assessment components, including digital literacy measurement, technology integration capability analysis, instructional innovation indicators, collaborative learning readiness metrics, and institutional resource evaluation mechanisms. These components are designed to support continuous monitoring of digital transformation initiatives and provide evidence-based decision support for educational planning, resource allocation, and technology adoption strategies. The framework further incorporates analytics and reporting functions that enable stakeholders to identify capability gaps, evaluate implementation risks, and prioritize system improvement initiatives. To demonstrate the applicability of the framework, a pilot assessment was conducted using competency and readiness data collected from instructional personnel within a technology-enhanced educational environment. Analytical results revealed strong capability levels across digital instructional practices, technology-supported curriculum development, online learning delivery, and collaborative knowledge-sharing activities. The assessment also identified infrastructure and support-related constraints that may affect the scalability and sustainability of advanced digital learning initiatives. The proposed framework contributes a scalable architecture for institutional readiness assessment and digital capability analytics within technology-enhanced educational systems. By integrating human capability indicators, infrastructure readiness measures, and organizational support metrics into a unified evaluation model, the framework provides a foundation for intelligent decision-support systems, digital transformation monitoring platforms, and technology governance mechanisms in modern educational ecosystems. Full article

15 pages, 3803 KB

Open AccessProceeding Paper

A Modular Framework for Cloud-Based Educational Content Delivery Systems: Design, Implementation, and Quality Evaluation

by Ritchfildjay L. Mariscal, Reymark R. Boniza, Diosdado T. Erandio, Jr. and Angelou S. Tupaz

Eng. Proc. 2026, 143(1), 58; https://doi.org/10.3390/engproc2026143058 - 10 Aug 2026

Viewed by 205

Abstract

The increasing demand for scalable digital learning environments has created a need for cloud-based educational content delivery systems that support efficient resource management, platform accessibility, and quality-assured learning experiences. While low-code web development platforms have enabled rapid deployment of educational websites, many implementations [...] Read more.

The increasing demand for scalable digital learning environments has created a need for cloud-based educational content delivery systems that support efficient resource management, platform accessibility, and quality-assured learning experiences. While low-code web development platforms have enabled rapid deployment of educational websites, many implementations remain content-centric and lack systematic architectural design, deployment frameworks, and software quality evaluation mechanisms. This study proposes a modular architecture for cloud-based educational content delivery systems that integrates content management, user access, resource delivery, platform administration, and quality monitoring components within a unified web-based environment. The proposed architecture adopts a structured development framework consisting of requirements analysis, system architecture design, prototype development, deployment configuration, performance testing, and quality evaluation. The framework is designed to support the rapid development of lightweight educational platforms using low-code technologies while maintaining software engineering principles related to reliability, usability, accessibility, compatibility, and performance efficiency. The architecture further incorporates cloud-hosted deployment strategies that facilitate scalable content distribution and cross-platform accessibility for technology-enhanced learning environments. To demonstrate the feasibility of the proposed architecture, a prototype implementation was developed using a low-code web platform and deployed as a cloud-based educational content delivery system. The prototype was evaluated by expert validators using selected software product quality characteristics derived from the ISO/IEC 25010 standard. The evaluation results indicated a high level of technical acceptability across multiple quality dimensions, including performance efficiency, reliability, usability, compatibility, accessibility, and capacity. The findings support the effectiveness of the proposed architecture as a practical framework for developing quality-assured educational delivery platforms. The study contributes a replicable systems architecture and implementation framework for educational content delivery applications. The proposed model provides guidance for the design, deployment, and evaluation of cloud-based learning platforms and offers a foundation for future integration with learning analytics, adaptive content delivery mechanisms, and intelligent educational support systems. Full article

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13 pages, 1901 KB

Open AccessProceeding Paper

Modeling, Kinematic Analysis, and PID Control of a Two-Degree-of-Freedom Robotic Manipulator

by George Kirkopoulos, Stavros Gkanatsios and George F. Fragulis

Eng. Proc. 2026, 143(1), 59; https://doi.org/10.3390/engproc2026143059 - 11 Aug 2026

Viewed by 301

Abstract

The subject of this study is the control of a two-degree-of-freedom robotic arm. Initially, the theoretical foundation employed in this study is presented. Subsequently, homogeneous transformation matrices are computed utilizing the Denavit–Hartenberg (D-H) method. Subsequently, the problem of forward kinematics and inverse kinematics [...] Read more.

The subject of this study is the control of a two-degree-of-freedom robotic arm. Initially, the theoretical foundation employed in this study is presented. Subsequently, homogeneous transformation matrices are computed utilizing the Denavit–Hartenberg (D-H) method. Subsequently, the problem of forward kinematics and inverse kinematics is resolved. Subsequently, state space matrices are calculated, and finally, the parameters of the PID (Proportional Integral Derivative) controller are determined to ensure that specific specifications (e.g., overshoot, settling time, steady-state error) are met, even in the presence of disturbances. Full article

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12 pages, 240 KB

Open AccessProceeding Paper

A Data-Driven ICT-Assisted Instruction Architecture for Pervasive Skills Development in Accounting Education

by Sherryll Fetalvero, Tomas Faminial, Emelyn Montoya, Errol Foja, Eddie Fetalvero and Garry Vanz Blancia

Eng. Proc. 2026, 143(1), 60; https://doi.org/10.3390/engproc2026143060 - 11 Aug 2026

Viewed by 369

Abstract

The increasing digitalization of higher education has created the need for ICT-assisted instructional frameworks capable of supporting both technical competency development and pervasive skills acquisition. This study presents a data-driven framework for informing ICT-assisted instruction based on the assessment of accountancy students’ perceived [...] Read more.

The increasing digitalization of higher education has created the need for ICT-assisted instructional frameworks capable of supporting both technical competency development and pervasive skills acquisition. This study presents a data-driven framework for informing ICT-assisted instruction based on the assessment of accountancy students’ perceived importance and readiness regarding pervasive skills. An online survey was conducted among students enrolled in the Accountancy program at Romblon State University using a researcher-developed instrument covering personal attributes, intellectual and professional skills, interpersonal and communication skills, and professional ethics and moral values. Descriptive statistics and paired-samples t-tests were employed to identify readiness gaps across the four competency domains. Results indicate statistically significant differences between perceived importance and readiness, with communication-related competencies exhibiting the largest readiness gaps. These findings provide empirical requirements for designing human-centered ICT-assisted instructional systems that integrate digital collaboration platforms, simulations, adaptive learning technologies, and analytics-driven learning activities. The proposed framework supports evidence-based instructional configuration by aligning technology-enhanced learning environments with learner competency needs, thereby contributing to the development of more responsive educational information systems for accounting education. Full article

11 pages, 211 KB

Open AccessProceeding Paper

A Human-Centered Virtual Learning Environment Adoption Framework for Higher Education Systems

by Charmaine Shane S. Cuñada

Eng. Proc. 2026, 143(1), 61; https://doi.org/10.3390/engproc2026143061 - 11 Aug 2026

Viewed by 314

Abstract

The increasing deployment of Virtual Learning Environments (VLEs) within higher education has highlighted the need for systematic frameworks that support technology adoption among digitally diverse users. This study presents a human-centered evaluation framework for analyzing the adoption of VLEs by digital immigrant teachers [...] Read more.

The increasing deployment of Virtual Learning Environments (VLEs) within higher education has highlighted the need for systematic frameworks that support technology adoption among digitally diverse users. This study presents a human-centered evaluation framework for analyzing the adoption of VLEs by digital immigrant teachers within higher education systems. The framework was examined using qualitative evidence obtained from thirteen educators aged 50 years and above at a Philippine state university through Husserlian descriptive phenomenology and Colaizzi’s seven-step analytical approach. The analysis identified three interconnected framework dimensions—System Transition Challenges, Adaptive Configuration Strategies, and Technology-Enabled Instructional Opportunities—representing the progression from initial system adoption to sustained digital integration. Findings indicate that technical complexity, increased workload, and interaction constraints initially hinder effective VLE utilization. However, structured professional development, instructional redesign, and collaborative support functioned as key framework components that improved system usability, digital competence, and instructional performance. The proposed framework conceptualizes VLE adoption as a socio-technical process integrating user capabilities, institutional support mechanisms, and digital platform functionality. These findings contribute to the design of more resilient, user-centered, and scalable VLE implementation strategies for higher education information systems. Full article

14 pages, 225 KB

Open AccessProceeding Paper

Design and Validation of a Technology-Aided Interactive Mathematics Learning System for Primary Education

by Dana Kaye Fabiala, Jhun August Mendez II, Maria Belinda Galivo, Shairane Potoy, Liza Melchor, Hannah Grace Fampulme and Mary Diane M. Mortel

Eng. Proc. 2026, 143(1), 62; https://doi.org/10.3390/engproc2026143062 - 12 Aug 2026

Viewed by 288

Abstract

The increasing demand for technology-supported instructional solutions has created opportunities to develop learning systems that integrate curriculum alignment, instructional design, and learner-centered interaction within a unified educational framework. This study presents the design and validation of a Technology-Aided Interactive Mathematics Learning Framework that [...] Read more.

The increasing demand for technology-supported instructional solutions has created opportunities to develop learning systems that integrate curriculum alignment, instructional design, and learner-centered interaction within a unified educational framework. This study presents the design and validation of a Technology-Aided Interactive Mathematics Learning Framework that functions as an instructional support system for Grade 3 subtraction involving three- to four-digit numbers with and without regrouping. The proposed framework adopts the Four-D (4D) instructional development model as its system development methodology and incorporates structured content organization, interactive learning components, and curriculum-driven instructional configuration. A mixed-method developmental research approach was employed involving fourteen participants, including twelve Grade 3 teachers and two master teachers from public elementary schools in Alcantara, Romblon, Philippines. A needs assessment identified subtraction with regrouping as the highest-priority instructional challenge. The resulting instructional system was evaluated using the Department of Education Evaluation Rating Sheet for Print Resources and achieved an overall Very Satisfactory rating across content integrity, interface organization, presentation, instructional architecture, and information accuracy. Qualitative analysis further demonstrated that the framework supports curriculum alignment, contextual adaptability, learner engagement, and reusable instructional deployment while identifying opportunities for improving inclusivity and interface presentation. The findings demonstrate that the proposed technology-aided instructional framework provides a practical, scalable, and sustainable learning support configuration that can serve as a foundation for future intelligent educational systems, adaptive learning platforms, and digital instructional environments. Full article

7 pages, 779 KB

Open AccessProceeding Paper

MENRO: Monitoring and Management System

by Mel Eduard A. Magracia, Ian Peter R. Madrona, Jeremias F. Fabito, Onemig Mortel, Jomar V. Malsi and Lynie M. Mariño

Eng. Proc. 2026, 143(1), 63; https://doi.org/10.3390/engproc2026143063 - 13 Aug 2026

Viewed by 261

Abstract

The MENRO: Monitoring and Management System is a digital solution developed to modernize the manual operations of the Municipal Environment and Natural Resources Office (MENRO). The system provides a secure and user-friendly platform designed to streamline document handling, automate monitoring tasks, and ensure [...] Read more.

The MENRO: Monitoring and Management System is a digital solution developed to modernize the manual operations of the Municipal Environment and Natural Resources Office (MENRO). The system provides a secure and user-friendly platform designed to streamline document handling, automate monitoring tasks, and ensure accurate environmental data management. This project specifically aims to: (1) develop a user-friendly interface that enables seamless document and record management, allowing administrators to effortlessly add, edit, update, and store essential information, and (2) design a system that is capable of automatically generating comprehensive lists of apprehension receipts, including violations and penalties issued to establishments under MENRO’s jurisdiction. These functions address long-standing inefficiencies in manual monitoring, recordkeeping, and compliance tracking. The system was evaluated using the ISO/IEC 25010:2011 software quality standards, focusing on functional suitability, performance efficiency, reliability, usability, compatibility, maintainability, portability, and security. Results show high usability and strong security features, ensuring that the platform meets operational needs while safeguarding sensitive environmental and legal records. By integrating real-time data access, automated reporting, and digitized forms used in environmental compliance checks, the system enhances MENRO’s capability to uphold environmental governance with greater transparency, accuracy, and accountability. Full article

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14 pages, 728 KB

Open AccessProceeding Paper

A Distributed Governance-Constrained Cyber Risk Management Framework for Enterprise Systems

by Kavitha K J and Keerthi S

Eng. Proc. 2026, 143(1), 64; https://doi.org/10.3390/engproc2026143064 - 13 Aug 2026

Viewed by 238

Abstract

The rapid integration of digital technologies including cloud infrastructures, Internet of Things ecosystems, artificial intelligence, and large-scale enterprise platforms has reshaped the operational and architectural foundations of contemporary organizations. Although these technologies enhance flexibility, scalability, and analytics-driven decision processes, they simultaneously increase system [...] Read more.

The rapid integration of digital technologies including cloud infrastructures, Internet of Things ecosystems, artificial intelligence, and large-scale enterprise platforms has reshaped the operational and architectural foundations of contemporary organizations. Although these technologies enhance flexibility, scalability, and analytics-driven decision processes, they simultaneously increase system complexity, broaden attack surfaces, and intensify governance requirements. This manuscript adopts an engineering-oriented viewpoint on digital governance and enterprise cybersecurity, focusing on secure system architectures, policy-driven control mechanisms, and resilience-focused operational strategies. An integrated framework that unifies governance structures, quantitative risk assessment, compliance automation, cybersecurity engineering is introduced to enable secure-sustainable digital transformation across enterprise environments. Full article

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16 pages, 428 KB

Open AccessProceeding Paper

An Educational Technology Framework for Game-Based Learning of Fundamental Integer Operations

by Gerald T. Goboy, Melbert M. Gregorio, Thursday Joy G. Gaac, Reclaire Joy M. Galicia, Rosame R. Magada and Kim Jemar F. Falo

Eng. Proc. 2026, 143(1), 65; https://doi.org/10.3390/engproc2026143065 - 17 Aug 2026

Viewed by 503

Abstract

Improving foundational mathematical competency remains an important challenge in educational technology and instructional system design. This study presents the design, development, and evaluation of Z-Card, a game-based instructional framework intended to improve students’ mastery of fundamental integer operations. The instructional intervention was developed [...] Read more.

Improving foundational mathematical competency remains an important challenge in educational technology and instructional system design. This study presents the design, development, and evaluation of Z-Card, a game-based instructional framework intended to improve students’ mastery of fundamental integer operations. The instructional intervention was developed using the ADDIE instructional design model and validated through expert evaluation based on instructional objectives, design quality, organizational structure, playability, and instructional usefulness. A quasi-experimental pre-test–post-test design involving Grade 7 students was employed to evaluate learning effectiveness using paired sample t-tests and ANCOVA. The results demonstrated statistically significant improvements in mathematical performance among students exposed to the Z-Card framework, with a large treatment effect after controlling for prior knowledge. Expert evaluations likewise indicated high acceptability across all design dimensions. The findings demonstrate that structured game-based instructional systems can effectively integrate learner engagement, conceptual reinforcement, and assessment-driven instructional support. The proposed framework contributes to educational technology by providing a scalable model for designing interactive learning environments that enhance foundational mathematics instruction. Full article

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11 pages, 200 KB

Open AccessProceeding Paper

A Lightweight Cloud-Based Learning Management System Architecture Using Low-Code Web Technologies: Design, Functional Evaluation, and Deployment Framework

by Ritchfildjay L. Mariscal

Eng. Proc. 2026, 143(1), 66; https://doi.org/10.3390/engproc2026143066 - 18 Aug 2026

Viewed by 256

Abstract

The growing demand for scalable and cost-effective digital learning environments has increased interest in lightweight cloud-based learning management solutions that can support instructional delivery without the complexity and infrastructure requirements of conventional Learning Management Systems (LMSs). While enterprise LMS platforms provide extensive functionality, [...] Read more.

The growing demand for scalable and cost-effective digital learning environments has increased interest in lightweight cloud-based learning management solutions that can support instructional delivery without the complexity and infrastructure requirements of conventional Learning Management Systems (LMSs). While enterprise LMS platforms provide extensive functionality, their deployment and maintenance often require substantial technical, financial, and administrative resources. This study proposes a lightweight cloud-based LMS architecture using low-code web technologies as an alternative framework for educational content management, learner engagement, resource distribution, and instructional support. The proposed architecture integrates four functional system layers: course management, performance management, content delivery, and productivity support. These components are designed to operate within a cloud-hosted environment that leverages web-based content management, embedded digital resources, collaborative productivity tools, and centralized storage services. The architecture emphasizes accessibility, modularity, low deployment overhead, and cross-platform compatibility, enabling rapid implementation in resource-constrained educational settings. To evaluate the feasibility of the proposed architecture, a large-scale deployment was conducted involving 1765 end users interacting with the platform within an educational environment. System functionality was assessed through feature-level evaluation across the core LMS components and supported by user capability indicators related to digital engagement and platform utilization. Analytical results demonstrated strong functional performance across all architectural modules, with course management and content delivery components exhibiting the highest operational effectiveness. Findings further indicated that the cloud-based architecture successfully supported essential LMS functions through integrated web services and low-code platform technologies. The study contributes a replicable systems architecture and deployment framework for lightweight learning management environments. The proposed model offers a practical foundation for the development of cloud-based educational platforms that support scalable content delivery, learner interaction, instructional management, and future integration with learning analytics, adaptive learning engines, and intelligent educational support systems. The framework provides an engineering-oriented approach for designing accessible and sustainable digital learning infrastructures using low-code technologies. Full article

16 pages, 9523 KB

Open AccessProceeding Paper

Data Encryption Using Chaotic Systems

by Eleni Petropoulou and George F. Fragulis

Eng. Proc. 2026, 143(1), 67; https://doi.org/10.3390/engproc2026143067 - 19 Aug 2026

Viewed by 286

Abstract

This paper studies the topics of chaos and cryptography, and how chaotic systems can be used in data encryption. Previous research show that chaos can generate pseudo-random sequences and help protect data, but there are problems because many studies do not analyze security [...] Read more.

This paper studies the topics of chaos and cryptography, and how chaotic systems can be used in data encryption. Previous research show that chaos can generate pseudo-random sequences and help protect data, but there are problems because many studies do not analyze security deeply, and chaotic systems can be attacked. In this work, chaotic systems are studied, and a variation of a chaotic encryption algorithm is implemented. The security and performance of this algorithm are tested and analyzed. The results show some advantages but also limitations of chaotic encryption, and give important information for future use and research in cryptography. Full article

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11 pages, 861 KB

Open AccessProceeding Paper

An Adaptive Project Intelligence Framework for IT Project Success: Integrating Human-Centric Behavioural Signals into a Socio-Technical Decision Support Architecture

by Biju Thomas, Rohini Venkat, Sivakumar Ramasamy and Sudhakar Tharuman

Eng. Proc. 2026, 143(1), 68; https://doi.org/10.3390/engproc2026143068 - 2 Sep 2026

Viewed by 216

Abstract

Information Technology (IT) projects have historically exhibited low success rates when evaluated narrowly through the “Iron Triangle” of time, cost, and scope. Recent studies emphasize the importance of soft factors—human, psychological, and behavioral dimensions—that logically complement technical and managerial practices. The increasing complexity [...] Read more.

Information Technology (IT) projects have historically exhibited low success rates when evaluated narrowly through the “Iron Triangle” of time, cost, and scope. Recent studies emphasize the importance of soft factors—human, psychological, and behavioral dimensions—that logically complement technical and managerial practices. The increasing complexity of digital transformation initiatives has created a demand for intelligent project management systems capable of integrating technical, organizational, and behavioral information into unified decision-support environments. Existing project management frameworks primarily emphasize planning, scheduling, cost management, and resource allocation, while offering limited capability for modeling dynamic human and organizational factors that influence project outcomes. This paper proposes an Adaptive Project Intelligence Framework (APIF), a socio-technical systems architecture that models behavioral signals, organizational conditions, and project performance indicators as interconnected system components within a unified project success ecosystem. This paper proposes a conceptual model for IT project success that integrates mindfulness, creativity, and innovation behaviors. Drawing on the interdisciplinary literature in project management, psychology, and organizational studies, the model highlights how mindfulness fosters resilience and stewardship, creativity enhances decision-making and problem-solving, and innovation behaviors translate ideas into sustainable project outcomes. The paper concludes with implications for practice, limitations, and directions for future research. Full article

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13 pages, 1666 KB

Open AccessProceeding Paper

Evaluating Financial Sustainability and Internal Controls in University Catering Services in the Context of Digital Accounting Systems: A Case Study in Romblon, Philippines

by Yolly Fabito, Jr., Errol Foja, Lou Foja, Tomas Faminial, Sherryll Mindo Fetalvero and Savahna Guilene Merano

Eng. Proc. 2026, 143(1), 69; https://doi.org/10.3390/engproc2026143069 - 8 Sep 2026

Viewed by 199

Abstract

Educational institutions face pressure to strengthen audit readiness and modernize financial processes amid digital transformation. Romblon State University Catering Services supports campus operations and student training while generating income, yet sustainability depends on transparent, timely, and auditable controls. This study evaluated internal control [...] Read more.

Educational institutions face pressure to strengthen audit readiness and modernize financial processes amid digital transformation. Romblon State University Catering Services supports campus operations and student training while generating income, yet sustainability depends on transparent, timely, and auditable controls. This study evaluated internal control practices and key transaction processes using the COSO Framework and Hall’s Transaction Processing Cycles. A descriptive qualitative case study employed process walkthroughs from March to June 2024. Results indicate centralized, undocumented procedures, limited audit trails, and weak segregation of duties in purchasing, sales, and billing, alongside absent cost accumulation and allocation, constraining cost visibility and process accountability. Full article

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