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Engineering Proceedings

Engineering Proceedings is an open access journal dedicated to publishing findings resulting from conferences, workshops, and similar events, in all areas of engineering. The conference organizers and proceedings editors are responsible for managing the peer-review process and selecting papers for conference proceedings.

Imprint Information Journal Flyer Open Access ISSN: 2673-4591

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Vol. 92

IEEE ECICE 2024

Table of Contents

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Vol. 90

EASN 2024

Table of Contents

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Vol. 89

IEEE ICKII 2024

Table of Contents

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Vol. 88

ENC 2024

Table of Contents

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Vol. 85

AIAS 2024

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Vol. 84

MEST 2024

Table of Contents

Latest Articles

8 pages, 1340 KiB

Open AccessProceeding Paper

Correlation Between Nutrient Concentration and Leaf Optical Attenuation Coefficient of Brassica Rapa (Pechay) as Measured by Time-Domain Optical Coherence Tomography System

by Tristan Dave Taeza, Mark Emmanuel Witongco, Maria Cecilia Galvez, Edgar Vallar, Mark Nickole Tabafa, James Roy Lesidan, Jumar Cadondon, Jejomar Bulan and Tatsuo Shiina

Eng. Proc. 2025, 87(1), 62; https://doi.org/10.3390/engproc2025087062 - 9 May 2025

This study explores the relationship between nutrient concentration (NC) and epidermal thickness (d) of the leaves of hydroponically grown Brassica rapa and its attenuation coefficients (m) using portable Time-Domain Optical Coherence Tomography (TD-OCT), which is a non-invasive [...] Read more.

This study explores the relationship between nutrient concentration (NC) and epidermal thickness (d) of the leaves of hydroponically grown Brassica rapa and its attenuation coefficients (m) using portable Time-Domain Optical Coherence Tomography (TD-OCT), which is a non-invasive imaging technique that uses low-coherence interferometry to generate axial scans of plants’ leaves by measuring the time delay and intensity of backscattered light. The portable TD-OCT system in this study has an axial and lateral resolution of 7 m and 3 m, respectively, a scanning depth of 12 mm, and a 1310 nm Super Luminescent Diode (SLD). Several studies suggest that the differences in d and m are related to nutritional, physiological, and anatomical status. The study used the Kratky method, a simple non-circulating hydroponic system, to cultivate Brassica rapa with varying NC (25%, 50%, 75%, 100% (control), and 125%). Each treatment group used two plants. The TD-OCT sample probe was placed on a fixed holder and was oriented vertically so that light was directed downward onto the leaf’s surface to obtain the depth profile (A-scan). The distance between the probe and the leaf was adjusted to obtain the optimum interference signal. Five averaged A-scans were obtained per leaf on the 7th, 18th, and 21st days post nutrient exposure. The logarithm of the averaged A-scan is linearly fitted to extract m. The results showed a positive correlation between NC and m, which suggests that plants produce more chlorophyll and develop denser cells and increase m. There was no correlation obtained between NC and d. The study demonstrates the potential of TD-OCT as a non-destructive tool for assessing plant health and monitoring growth dynamics in hydroponic systems and m as a sensitive indicator of plant health as compared to d. The continued exploration of TD-OCT applications in agriculture can contribute to improving crop management strategies and promoting sustainable food production practices. Full article

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7 pages, 3448 KiB

Open AccessProceeding Paper

Two-Stage Beamforming Technique for GNSS Applications

by Noori BniLam, Samah Chazbeck, Szabolcs Berki, Raffaele Fiengo and Paolo Crosta

Eng. Proc. 2025, 88(1), 45; https://doi.org/10.3390/engproc2025088045 - 9 May 2025

In this paper, we introduce a robust beamforming technique using array antennas. The proposed solution constitutes two stages; the first stage exploits the space-alternating generalized expectation-maximization (SAGE) algorithm to decompose the received GNSS signal into its constituent signals, i.e., direct and reflected signals. [...] Read more.

In this paper, we introduce a robust beamforming technique using array antennas. The proposed solution constitutes two stages; the first stage exploits the space-alternating generalized expectation-maximization (SAGE) algorithm to decompose the received GNSS signal into its constituent signals, i.e., direct and reflected signals. The SAGE algorithm estimates the angle of arrival (AoA) and the received covariance matrix for both the direct and reflected signals. The second stage, on the other hand, utilizes the Minimum Variance Distortionless Response (MVDR) algorithm to produce the weight vector that steers the main beam towards the satellite’s direction and the nulls towards the multipath effect. The MVDR uses the AoA of the direct path and the covariance matrix of the reflected path to minimize the multipath effect. The experimental results reveal that the proposed technique improves the received signal strength and the location estimation accuracy, as compared to a single-antenna system. Furthermore, the proposed technique outperforms the traditional MVDR technique in the tested environment. Finally, the 95% 3D position error of the proposed solution is 5.2 m, and the position dilution of precision (pdop) is 0.84. Full article

(This article belongs to the Proceedings of European Navigation Conference 2024)

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9 pages, 430 KiB

Open AccessProceeding Paper

Enhancing Heterogeneous Multi-Robot Teaming for Planetary Exploration

by Amrita Suresh, Melvin Laux, Wiebke Brinkmann, Leon C. Danter and Frank Kirchner

Eng. Proc. 2025, 90(1), 112; https://doi.org/10.3390/engproc2025090112 - 8 May 2025

Future space missions will include multi-robot systems, with greater autonomy and a large degree of heterogeneity for a wider range of task capabilities and redundancy. It is imperative that both software (learning models, parallelizing capabilities, resource distribution, etc.) and hardware factors must be [...] Read more.

Future space missions will include multi-robot systems, with greater autonomy and a large degree of heterogeneity for a wider range of task capabilities and redundancy. It is imperative that both software (learning models, parallelizing capabilities, resource distribution, etc.) and hardware factors must be considered during decentralized task negotiation to lead to better performance of the team. By utilizing the formalism of contextual Markov decision processes, team composition can be incorporated into the learning process and used for more meaningful and reliable evaluation using measures such as total time, overall consumed energy, performance feedback from tasks, or damage incurred. Improved team performance will in turn enhance the overall results of the mission. Planetary exploration tasks often involve time, communication and energy constraints. Such missions are also prone to noisy sensor data (e.g., camera images distorted by dust), as well as wear and tear on hardware (e.g., wheels, manipulators). To ensure that such factors do not jeopardize the mission, they must be taken into account. Therefore, this paper describes a software framework for the reliable execution of tasks in constrained and dynamic environments. Our work leverages the advantages of heterogeneity for more resilient planetary missions by addressing two aspects—first, the integration of hardware parameters into the negotiation process, and second the analysis of how the integration of team performance metrics, particularly adaptability and mutual support, in task negotiation plays a role in the overall mission success. Full article

(This article belongs to the Proceedings of The 14th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)

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9 pages, 2190 KiB

Open AccessProceeding Paper

Shoe Recommendation System Integrating Generative Artificial Intelligence and Convolutional Neural Networks for Image Recognition

by Chin-Chih Chang, Chi-Hung Wei, Ray-Nan Liao, Sean Hsiao and Chyuan-Huei Thomas Yang

Eng. Proc. 2025, 92(1), 62; https://doi.org/10.3390/engproc2025092062 - 8 May 2025

We developed a shoe recommendation system that integrates generative artificial intelligence (AI) and convolutional neural networks (CNNs) to enhance image recognition and personalize recommendations. The system utilizes CNNs to accurately identify shoe types from user-uploaded images. Utilizing the capabilities of generative AI, the [...] Read more.

We developed a shoe recommendation system that integrates generative artificial intelligence (AI) and convolutional neural networks (CNNs) to enhance image recognition and personalize recommendations. The system utilizes CNNs to accurately identify shoe types from user-uploaded images. Utilizing the capabilities of generative AI, the system generates custom shoe suggestions based on weather and location. The proposed system minimizes the need for manual searching but enhances user experience by providing an efficient, automated, and visually driven solution for selecting shoes. The effectiveness of integrating image recognition and generative techniques paves the way for advancements in AI-driven fashion recommendation systems. The developed method offers a powerful tool for increasing customer engagement and satisfaction by delivering personalized and fashion-forward shoe recommendations. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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12 pages, 3580 KiB

Open AccessProceeding Paper

Speech Delay Assistive Device for Speech-to-Text Transcription Based on Machine Learning

by Maria Kristina C. Rodriguez, Gheciel Mayce M. Santos, Jennifer C. Dela Cruz and Jmi C. Dela Cruz

Eng. Proc. 2025, 92(1), 60; https://doi.org/10.3390/engproc2025092060 - 8 May 2025

Despite advances by major companies, existing technologies often misinterpret speech from individuals with speech delays. To address this challenge, a portable machine learning (ML) speech-to-text assistive device was developed for speech-delayed children. The device is composed of a Raspberry Pi 4 and Google [...] Read more.

Despite advances by major companies, existing technologies often misinterpret speech from individuals with speech delays. To address this challenge, a portable machine learning (ML) speech-to-text assistive device was developed for speech-delayed children. The device is composed of a Raspberry Pi 4 and Google Web Speech API and enables the accurate transcription of challenging speech sounds of children aged 6 to 14 years old. The device performs noise reduction and digital transcription. Its performance was validated by speech language pathologists (SLPs). The device achieved 94% word accuracy, 92% sentence accuracy, and a word error rate (WER) of 0 to 14%. The ML-based device is a significant improvement on existing speech therapy tools, offering an accessible solution for speech-delayed children. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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10 pages, 8167 KiB

Open AccessProceeding Paper

Integrating Sustainable Concepts into Blended Learning and Interactive Game System Design

by Peng-Wei Hsiao and Zheng-Qing Wang

Eng. Proc. 2025, 92(1), 59; https://doi.org/10.3390/engproc2025092059 - 8 May 2025

Food is essential for sustaining human life. While people love delicious food, they often neglect the care for it. One of the most commonly wasted foods is bread. There has not been much research on bread waste. Carbon emissions from bread are not [...] Read more.

Food is essential for sustaining human life. While people love delicious food, they often neglect the care for it. One of the most commonly wasted foods is bread. There has not been much research on bread waste. Carbon emissions from bread are not less than those from meat products. Therefore, it is necessary to integrate sustainable concepts with mixed learning approaches into a mixed reality (MR) interactive system, focusing on bakeries. We conducted field research and observations of leftover bread from eight local bakeries, categorizing and photographing them. We combined knowledge and teaching about carbon emissions with interactive games to help users understand the relationship between bread and carbon emissions. Users can learn about relevant knowledge and content by playing the MR game. The interactive game provides a reference for sustainability research in the future. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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9 pages, 2059 KiB

Open AccessProceeding Paper

Reliability Assessment of Power Distribution System in Freeport Area of Bataan

by Jomel R. Cristobal and Ronald Vincent M. Santiago

Eng. Proc. 2025, 92(1), 58; https://doi.org/10.3390/engproc2025092058 - 8 May 2025

The continuous distribution ability of electricity is defined as the effectiveness of the computation of reliability indices. Therefore, we conducted a reliability assessment and evaluated the performance of the distribution system in the Freeport Area of Bataan (FAB). For reliability assessment, software was [...] Read more.

The continuous distribution ability of electricity is defined as the effectiveness of the computation of reliability indices. Therefore, we conducted a reliability assessment and evaluated the performance of the distribution system in the Freeport Area of Bataan (FAB). For reliability assessment, software was developed to automate the computation of indices, including system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), customer average interruption frequency index (CAIFI), and customer average interruption duration index (CAIDI). Through reliability assessment and evaluation, the low-performing distribution network of the FAB was successfully identified. After the identification of the low-performing network, reconductoring and redundant feeder line projects were proposed to alleviate and reduce the occurrence of power interruptions. An analysis of its economy was also conducted, and the result showed that line reconductoring from bare conductor to insulated cable was the most feasible option since it resulted in a high benefit–cost ratio (BCR) and a positive net present value (NPV) for all evaluated cases. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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5 pages, 8804 KiB

Open AccessEditorial

Preface: 2024 IEEE 7th International Conference on Knowledge Innovation and Invention

by Teen-Hang Meen, Chun-Yen Chang and Cheng-Fu Yang

Eng. Proc. 2025, 89(1), 48; https://doi.org/10.3390/engproc2025089048 - 8 May 2025

This volume presents the proceedings of the 2024 IEEE 7th International Conference on Knowledge Innovation and Invention (IEEE ICKII 2024) [...] Full article

(This article belongs to the Proceedings of 2024 IEEE 7th International Conference on Knowledge Innovation and Invention)

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2 pages, 340 KiB

Open AccessEditorial

Statement of Peer Review

by Teen-Hang Meen, Chun-Yen Chang and Cheng-Fu Yang

Eng. Proc. 2025, 89(1), 47; https://doi.org/10.3390/engproc2025089047 - 8 May 2025

In submitting conference proceedings of the 2024 IEEE 7th International Conference on Knowledge Innovation and Invention (IEEE ICKII 2024) to Engineering Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected [...] Read more.

In submitting conference proceedings of the 2024 IEEE 7th International Conference on Knowledge Innovation and Invention (IEEE ICKII 2024) to Engineering Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...] Full article

(This article belongs to the Proceedings of 2024 IEEE 7th International Conference on Knowledge Innovation and Invention)

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9 pages, 2181 KiB

Open AccessProceeding Paper

Integrating Multi-Sensor Augmented PNT to Enhance Outdoor Human Motion Capture Using Low-Cost GNSS Receivers

by Andrea Maffia, Georgii Kurshakov, Tiziano Cosso, Vittorio Sanguineti and Giorgio Delzanno

Eng. Proc. 2025, 88(1), 44; https://doi.org/10.3390/engproc2025088044 - 8 May 2025

We are working on an innovative approach to outdoor human motion capture, using a wearable device that integrates a low-cost GNSS (Global Navigation Satellite System) receiver and an INS (Inertial Navigation System) via a zero-velocity update (ZUPT) methodology. In this study, we focused [...] Read more.

We are working on an innovative approach to outdoor human motion capture, using a wearable device that integrates a low-cost GNSS (Global Navigation Satellite System) receiver and an INS (Inertial Navigation System) via a zero-velocity update (ZUPT) methodology. In this study, we focused on using these devices to reconstruct the foot trajectory. Our work addresses the challenge of capturing precise foot movements in uncontrolled outdoor environments, a task traditionally constrained by the limitations of laboratory settings. We equipped devices that combine inertial measurement units (IMUs) with GNSS receivers in the following configuration: one on each foot and one on the head. We experimented with different GNSS data processing techniques, such as Post-Processed Kinematic (PPK) positioning with and without Moving Base (MB), and after the integration with the IMU, we obtained centimeter-level precision in horizontal and vertical positioning for various walking speeds. This integration leverages a loosely coupled GNSS/INS approach, where the GNSS solution is independently processed and subsequently used to refine the INS outputs. Enhanced by ZUPT and Madgwick filtering, this method significantly improves the trajectory reconstruction accuracy. Indeed, our research includes a study of the impact of moving speed on the performance of these low-cost GNSS receivers. These insights pave the way for future exploration into tightly coupled GNSS/INS integration using low-cost GNSS receivers, promising advancements in fields like sports science, rehabilitation, and well-being. This work seeks not only to contribute to the field of wearable technology, but also to open possibilities for further innovation in affordable, high-accuracy personal navigation and activity monitoring devices. Full article

(This article belongs to the Proceedings of European Navigation Conference 2024)

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13 pages, 3489 KiB

Open AccessProceeding Paper

Planning and Strategies for Expansion of Irrigation Services in Mountainous Areas: A Case Study of Nantou County in Taiwan

by Feng-Wen Chen, Yun-Wei Tan, Hsiu-Te Lin, Yu-Chien Cho, Ya-Ting Chang and Li-Chi Chiang

Eng. Proc. 2025, 91(1), 17; https://doi.org/10.3390/engproc2025091017 - 8 May 2025

More than half of the cultivated land belongs to the Irrigation Association. Therefore, there have been no farmland consolidation, irrigation, and drainage projects. The cultivation in the non-irrigation area suffers from poor geographical conditions and a lack of water sources. A practical planning [...] Read more.

More than half of the cultivated land belongs to the Irrigation Association. Therefore, there have been no farmland consolidation, irrigation, and drainage projects. The cultivation in the non-irrigation area suffers from poor geographical conditions and a lack of water sources. A practical planning strategy is required for expanding irrigation services. The mountainous area of Nantou County, Taiwan, has 7477 ha of available land and 4656 ha of agricultural land outside the irrigation area. Rain and streams are the main water source. There are 82 ponds, 80% of which belong to the loam soil, and the rainfall from October to February is limited. The water requirement of crops is 1.5–3.1 mm/day. Wild streams, groundwater, and rainwater are the only potential water sources due to elevation and terrain. The potential runoff is estimated to be 0–0.927 cms (m³/s) when using the SCS-CN method. Water supply and demand from October to April are limited, and the rainfall comprises 22% of the total water supply. Large reservoirs and water storage towers are required for flooding and in dry seasons. To address water storage challenges and stabilize the balance between water supply and demand, it is essential to construct additional ponds. Full article

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12 pages, 2401 KiB

Open AccessProceeding Paper

Winglet Design for Class I Mini UAV—Aerodynamic and Performance Optimization

by Eleftherios Nikolaou, Eleftherios Karatzas, Spyridon Kilimtzidis and Vassilis Kostopoulos

Eng. Proc. 2025, 90(1), 111; https://doi.org/10.3390/engproc2025090111 - 7 May 2025

The aerodynamic performance of an aircraft can be enhanced by incorporating wingtip devices, or winglets, which primarily reduce lift-induced drag created by wingtip vortices. This study outlines an optimization procedure for implementing winglets on a Class I fixed-wing mini-UAV to maximize aerodynamic efficiency [...] Read more.

The aerodynamic performance of an aircraft can be enhanced by incorporating wingtip devices, or winglets, which primarily reduce lift-induced drag created by wingtip vortices. This study outlines an optimization procedure for implementing winglets on a Class I fixed-wing mini-UAV to maximize aerodynamic efficiency and performance. After the Conceptual and Preliminary design phases, a baseline UAV was developed without winglets, adhering to specific layout constraints (e.g., wingspan, length). Various winglet designs—plate and blended types with differing heights, cant angles, and sweep angles—were then created and assessed. A Computational Fluid Dynamics (CFD) analysis was conducted to evaluate the flow around both the winglet-free UAV and configurations with each winglet design. The simulations employed Reynolds-Averaged Navier-Stokes (RANS) equations coupled with the Spalart-Allmaras turbulence model, targeting the optimal winglet configuration for enhanced aerodynamic characteristics during cruise. Charts of lift, drag, pitching moment coefficients, and lift-to-drag ratios are presented, alongside flow contours illustrating vortex characteristics for both baseline and optimized configurations. Additionally, dynamic stability analyses examined how winglets impact the UAV’s stability and control. The results demonstrated a significant improvement in aerodynamic coefficients (

C_{L m a x}

,

L / D_{m a x}

,

C_{L a}

,

C_{m a}

), leading to an increase in both range and endurance. Full article

(This article belongs to the Proceedings of The 14th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)

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10 pages, 3506 KiB

Open AccessProceeding Paper

Automated Monitoring and Control System of Solar Greenhouse Using ESP32 and Blynk Application

by Meridith Lindsey Q. Galon, Michael Vincent R. Tumaliwan and Marianne M. Sejera

Eng. Proc. 2025, 92(1), 57; https://doi.org/10.3390/engproc2025092057 - 7 May 2025

Greenhouse farming has brought a revolution in agriculture as it provides a climate favorable to crops all year round. Besides securing the production of foods of higher quality, it also extends the growing seasons and protects crops from pests and harsh weather. The [...] Read more.

Greenhouse farming has brought a revolution in agriculture as it provides a climate favorable to crops all year round. Besides securing the production of foods of higher quality, it also extends the growing seasons and protects crops from pests and harsh weather. The greenhouse is centrally controlled by the user due to the technological advancements of devices such as cell phones and a control system of temperature, which is important for the plant. To realize remote real-time automated monitoring of the greenhouse based on the user settings, an Android app was developed in this study. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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9 pages, 2975 KiB

Open AccessProceeding Paper

Classification of Non-Frozen and Frozen–Thawed Pork with Adaptive Support Vector Machine and Electronic Nose

by Paul Christian E. Artista, Abraham M. Mendoza and Dionis A. Padilla

Eng. Proc. 2025, 92(1), 56; https://doi.org/10.3390/engproc2025092056 - 7 May 2025

The quality of raw meat is important for community health as its freshness is crucial to preventing foodborne illnesses. In the United States, the related illness cases were 9.4 million cases with 55,961 hospital admissions and 1351 deaths annually. This underscores the urgent [...] Read more.

The quality of raw meat is important for community health as its freshness is crucial to preventing foodborne illnesses. In the United States, the related illness cases were 9.4 million cases with 55,961 hospital admissions and 1351 deaths annually. This underscores the urgent need for improved meat quality monitoring. This study aims to develop an electronic nose (E-nose) that can differentiate between frozen–thawed and fresh pork meat samples, thereby enhancing food safety. We designed the E-nose using MQ series gas sensor array with temperature and humidity sensors, and an Arduino Uno microcontroller. Sensors were calibrated for accurate data collection. An adaptive support vector machine (ASVM) was used for data classification. We evaluated the model’s accuracy using a confusion matrix. The ASVM model exhibited robust performance, achieving an accuracy of 88%. Its performance was evaluated with recall, F1 scores, and precision. To further enhance the model’s performance, future studies are mandated to integrate additional gas sensors, increase sample sizes, advance data preprocessing techniques, and explore different machine learning algorithms or ensemble methods. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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9 pages, 2588 KiB

Open AccessProceeding Paper

Application of Terminal Audio Mixing in Multi-Bandwidth End-to-End Encrypted Voice Conference

by Chi-Hung Lien, Ya-Ching Tu, Sheng-Lian Liao, Juei-Chi Chu, Chia-Yu Hsieh and Jyun-Jia Jhang

Eng. Proc. 2025, 92(1), 55; https://doi.org/10.3390/engproc2025092055 - 7 May 2025

Recently, the increasing frequency of cybersecurity incidents has raised concerns about communication security and personal privacy. In a zero-trust network environment, it is critically important to protect communication content and ensure that it is not intercepted, recorded, or stored without proper authorization. End-to-end [...] Read more.

Recently, the increasing frequency of cybersecurity incidents has raised concerns about communication security and personal privacy. In a zero-trust network environment, it is critically important to protect communication content and ensure that it is not intercepted, recorded, or stored without proper authorization. End-to-end encryption (E2EE) is a reliable solution for this purpose. The COVID-19 pandemic has accelerated the adoption of remote work and virtual meetings, making the security of voice conferences a critical issue. This study aims to explore the application of end-to-end encryption technology in voice conferences. We designed and implemented an end-to-end encrypted voice conferencing system based on terminal-side mixing to ensure security while also being applicable in low-bandwidth network environments. The developed system effectively prevented man-in-the-middle attacks and data wiretaps, while maintaining high performance and low latency. It can be used in low-bandwidth scenarios such as satellite networks. The end-to-end encryption technology, when combined with terminal-side voice mixing, significantly enhances the security and usability of voice conferences as a new solution for secure communication in the future. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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9 pages, 2122 KiB

Open AccessProceeding Paper

Classification of Ocimum basilicum Using a Convolutional Neural Network

by Mary Angel N. Perlas, John Isaac B. Santosildes and Jocelyn F. Villaverde

Eng. Proc. 2025, 92(1), 54; https://doi.org/10.3390/engproc2025092054 - 7 May 2025

Basil varieties were classified using a convolutional neural network (CNN) with VGG16 architecture. The developed system in this study identified and classified the variety of basil images. The system applied the contrast-limited adaptive histogram equalization (CLAHE) algorithm to the basil image in the [...] Read more.

Basil varieties were classified using a convolutional neural network (CNN) with VGG16 architecture. The developed system in this study identified and classified the variety of basil images. The system applied the contrast-limited adaptive histogram equalization (CLAHE) algorithm to the basil image in the architecture VGG16 to extract features and classify the images. The system was tested using 50 images, and the confusion matrix showed an 82.00% accuracy. An inaccurate output was caused by the wrong positions or the size of the leaf. Of the 50 basil images, 41 were correctly classified. Two models were created in the study for epochs of eight and 10. The best model study was chosen based on accuracy. The best model showed an accuracy of 97% in training for 10 epochs. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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9 pages, 5139 KiB

Open AccessProceeding Paper

You Only Look Once v8 Cattle Identification Based on Muzzle Print Pattern Using ORB and Fast Library for Approximate Nearest Neighbor Algorithms

by Allan Josef Balderas, Kaila Mae A. Pangilinan and Meo Vincent C. Caya

Eng. Proc. 2025, 92(1), 53; https://doi.org/10.3390/engproc2025092053 - 7 May 2025

Cattle identification is important in livestock management, and advanced techniques are required to identify cattle without ear tagging, branding, or any identification method that harms the cattle. This study aims to develop computer vision techniques to identify cattle based on their unique muzzle [...] Read more.

Cattle identification is important in livestock management, and advanced techniques are required to identify cattle without ear tagging, branding, or any identification method that harms the cattle. This study aims to develop computer vision techniques to identify cattle based on their unique muzzle print features. The developed method employed the YOLOv8 object detection model to detect the cattle’s muzzle. Following detection, the captured muzzle image underwent image processing. Contrast-limited adaptive histogram equalization (CLAHE) was used to enhance the image quality and obtain a prominent and detailed image of the muzzle print. Feature extraction algorithm-oriented FAST and rotated BRIEF (ORB) was applied to extract key points and detect descriptors that are crucial for the cattle identification process. The fast library for approximate nearest neighbor (FLANN) was also employed to identify individual cattle by comparing descriptors of query images from those stored in the database. To validate the developed method, its performance was evaluated on 25 different cattle. In total, 22 out of 25 were correctly identified, resulting in an overall accuracy of 88%. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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24 pages, 11713 KiB

Open AccessProceeding Paper

Overview of Electric Propulsion Motor Research for EVTOL

by Xiaopeng Zhao, Weiping Yang, Zhangjun Sun, Ying Liu and Wenyang Liu

Eng. Proc. 2024, 80(1), 46; https://doi.org/10.3390/engproc2024080046 - 7 May 2025

Electric aviation is the future development direction of aviation industry technology. Electric vertical take-off and landing aircraft(eVTOL) is an important carrier of electric aviation, whose technology research and development, processing and manufacturing, airworthiness certification and industrialization boom have been set off around the [...] Read more.

Electric aviation is the future development direction of aviation industry technology. Electric vertical take-off and landing aircraft(eVTOL) is an important carrier of electric aviation, whose technology research and development, processing and manufacturing, airworthiness certification and industrialization boom have been set off around the world. The electric propulsion technology has achieved rapid development as the key technology of eVTOL. Aiming at the demand for high torque density and high reliability of electric propulsion system, the paper analyzed the technical indexes of electric motor products of domestic and foreign benchmark enterprises. The key technologies such as motor integration, new electromagnetic topology, lightweight structure design, and high efficiency cooling is studied. It is pointed out that in order to pursue the high torque density and fault-tolerance performance, the integrated precise modeling of motor and controller, advanced materials and manufacturing technology are the development trend of the electric propulsion technology. The breakthrough of eVTOL electric propulsion technology can accelerate the commercial operation of civil eVTOL and promote the development of new quality productive forces. Full article

(This article belongs to the Proceedings of 2nd International Conference on Green Aviation (ICGA 2024))

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10 pages, 2834 KiB

Open AccessProceeding Paper

UWB-Based Positioning Is Not Invulnerable from Spoofing Attacks: A Case Study of Crazyswarm

by Mahyar Shariat, Jelena Gabela Majić, Max Brandstätter and Wolfgang Kastner

Eng. Proc. 2025, 88(1), 43; https://doi.org/10.3390/engproc2025088043 - 7 May 2025

Spoofing attacks pose a threat to drones, which can lead to their crash or takeover. As a countermeasure, the European Space Agency has implemented the Timed Efficient Loss-tolerant Authentication (TESLA) broadcast protocol in the Galileo Open Service Navigation Message Authentication (OSNMA) to detect [...] Read more.

Spoofing attacks pose a threat to drones, which can lead to their crash or takeover. As a countermeasure, the European Space Agency has implemented the Timed Efficient Loss-tolerant Authentication (TESLA) broadcast protocol in the Galileo Open Service Navigation Message Authentication (OSNMA) to detect such events. This study explores the application of TESLA in detecting spoofing attacks targeted at drone swarms that rely on positioning systems utilizing ultra-wideband (UWB) technology. The results of our experiments reaffirm that UWB-based positioning systems are not automatically invulnerable from spoofing attacks and that cryptographic methods such as TESLA are required to provide a layer of protection against spoofing attacks to detect them effectively. Full article

(This article belongs to the Proceedings of European Navigation Conference 2024)

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6 pages, 797 KiB

Open AccessProceeding Paper

Machine Learning Classifiers for Voice Health Assessment Under Simulated Room Acoustics

by Ahmed M. Yousef and Eric J. Hunter

Eng. Proc. 2024, 81(1), 16; https://doi.org/10.3390/engproc2024081016 - 7 May 2025

Machine learning (ML) robustness for voice disorder detection was evaluated using reverberation-augmented recordings. Common vocal health assessment voice features from steady vowel samples (135 pathological, 49 controls) were used to train/test six ML classifiers. Detection performance was evaluated under low-reverb and simulated medium [...] Read more.

Machine learning (ML) robustness for voice disorder detection was evaluated using reverberation-augmented recordings. Common vocal health assessment voice features from steady vowel samples (135 pathological, 49 controls) were used to train/test six ML classifiers. Detection performance was evaluated under low-reverb and simulated medium (med = 0.48 s) and high-reverb times (high = 1.82 s). All models’ performance declined with longer reverberation. Support Vector Machine exhibited slight robustness but faced performance challenges. Random Forest and Gradient Boosting, though strong under low reverb, lacked generalizability in med/high reverb. Training/testing ML on augmented data is essential to enhance their reliability in real-world voice assessments. Full article

(This article belongs to the Proceedings of The 1st International Online Conference on Bioengineering)

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