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7 pages, 557 KiB

Open AccessProceeding Paper

The Application and Performance Comparison of Different Versions of YOLO Image Recognition Systems

by You-Shyang Chen and Yi-Xuan Chen

Eng. Proc. 2025, 98(1), 1; https://doi.org/10.3390/engproc2025098001 - 30 May 2025

Viewed by 702

With advancements in computational power and artificial intelligence (AI), image recognition has become more efficient and widely used. You Only Look Once (YOLO) stands out for its fast and accurate object detection, making it popular among researchers. The technology enhances daily life, from [...] Read more.

With advancements in computational power and artificial intelligence (AI), image recognition has become more efficient and widely used. You Only Look Once (YOLO) stands out for its fast and accurate object detection, making it popular among researchers. The technology enhances daily life, from smartphone facial recognition improving security to thermal imaging aiding public health during the pandemic. However, identifying the right image recognition system for varied image types remains challenging. By evaluating the performance of YOLO’s versions (e.g., YOLOv3 and YOLOv4) regarding structure, speed, accuracy, and adaptability, we identified appropriate algorithms for specific tasks, recommending optimal image recognition techniques for different applications. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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10 pages, 1229 KiB

Open AccessProceeding Paper

Heart Rate Variability-Based Non-Invasive Method for Ovulation Detection

by Yen-Hua Lee and Wei-Wen Hung

Eng. Proc. 2025, 98(1), 2; https://doi.org/10.3390/engproc2025098002 - 30 May 2025

Viewed by 217

Abstract

Monitoring women’s health during the menstrual cycle is crucial. Traditional methods for estimating ovulation dates involve measuring body temperature and analyzing blood, urine, cervical mucus, or saliva. While effective, these methods come with various advantages and limitations. Therefore, we introduce a novel approach [...] Read more.

Monitoring women’s health during the menstrual cycle is crucial. Traditional methods for estimating ovulation dates involve measuring body temperature and analyzing blood, urine, cervical mucus, or saliva. While effective, these methods come with various advantages and limitations. Therefore, we introduce a novel approach to more easily and accurately detect both the menstrual period and the ovulation date. After gathering essential physiological data from test subjects, the ovulation date is predicted. Heart rate waveform signals are used to identify physiological parameters linked to ovulation, enhancing prediction accuracy without relying on consumable items such as test strips or patches. By integrating non-invasive image signal processing technology and heart rate variability analysis algorithms, the timing of ovulation within the menstrual cycle is accurately predicted. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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6 pages, 362 KiB

Open AccessProceeding Paper

An Integrated Fuzzy Convolutional Neural Network Model for Stock Price Prediction

by Jia-Wen Wang and Jr-Shian Chen

Eng. Proc. 2025, 98(1), 3; https://doi.org/10.3390/engproc2025098003 - 30 May 2025

Viewed by 309

Abstract

Stock market forecasting has always been researched extensively in Social Sciences. In this research, Fuzzy time series with deep learning is widely adopted to create a fuzzy convolutional neural network integration model as this model enhances the fuzzification of values to enhance feature [...] Read more.

Stock market forecasting has always been researched extensively in Social Sciences. In this research, Fuzzy time series with deep learning is widely adopted to create a fuzzy convolutional neural network integration model as this model enhances the fuzzification of values to enhance feature characteristics using two-dimensional input data in convolutional neural networks (CNNs). This allows the model to retain complete feature information. The fuzzy convolutional neural network (FCNN) model autonomously learns and extracts crucial features by integrating stock market data, resulting in improved forecasting accuracy. In this study, the model was tested for forecasting the Taiwan Weighted Stock Index and metrics such as the mean squared error (MSE) and mean absolute error (MAE), and the results were compared with the real data. The results showed that the model provided accurate predictions. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 502 KiB

Open AccessProceeding Paper

Adaptive Frequency and Assignment Algorithm for Context-Based Arithmetic Compression Codes for H.264 Video Intraframe Encoding

by Huang-Chun Hsu and Jian-Jiun Ding

Eng. Proc. 2025, 98(1), 4; https://doi.org/10.3390/engproc2025098004 - 4 Jun 2025

Viewed by 256

Abstract

In modern communication technology, short videos are increasingly used on social media platforms. The advancement of video codecs is pivotal in communication. In this study, we developed a new scheme to encode the residue of intraframes. For the H.264 baseline profile, we used [...] Read more.

In modern communication technology, short videos are increasingly used on social media platforms. The advancement of video codecs is pivotal in communication. In this study, we developed a new scheme to encode the residue of intraframes. For the H.264 baseline profile, we used context-based arithmetic variable-length coding (CAVLC) to encode the residue of integer transforms in a block-wise manner. In the developed method, the DC and AC coefficients are separated. In addition, context assignment, adaptive scanning, range increment, and mutual learning are adopted in a mixture of fixed-length and variable-length schemes, and block-wise compressions of the frequency table are applied to obtain improved compression rates. Compressing the frequency prevents CAVLC from being hindered by horizontally/vertically dominated blocks. The developed method outperforms CAVLC, with average reductions of 7.81, 8.58, and 7.88% in quarter common intermediate format (QCIF), common intermediate format (CIF), and full high-definition (FHD) inputs. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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5 pages, 701 KiB

Open AccessProceeding Paper

Development of Artificial Urine Using Commonly Available Ingredients for Ultraviolet–Visible Spectroscopy

by Patryk Sokołowski and Maria Babińska

Eng. Proc. 2025, 98(1), 5; https://doi.org/10.3390/engproc2025098005 - 5 Jun 2025

Viewed by 302

Abstract

A simple urine phantom was developed to replicate the ultraviolet–visible (UV–Vis) spectrum of healthy human urine. Made from four safe and widely available ingredients, it addresses the challenges of biological samples, including safety risks and storage issues. The spectroscopic analysis results confirmed strong [...] Read more.

A simple urine phantom was developed to replicate the ultraviolet–visible (UV–Vis) spectrum of healthy human urine. Made from four safe and widely available ingredients, it addresses the challenges of biological samples, including safety risks and storage issues. The spectroscopic analysis results confirmed strong similarity to natural urine, making the phantom appropriate for testing spectroscopic methods, calibrating optical devices, and evaluating diagnostic sensors. It can also serve as a starting point for advanced phantoms tailored to specific patient needs or diseases. This reliable alternative facilitates research in optical diagnostics or biosensor development by simplifying preliminary sensor testing. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 176 KiB

Open AccessProceeding Paper

Applying the Analytical Hierarchy Process to Exploring Demand and Technology Preferences in InsurTech: Focusing on Consumer Concerns

by Mei-Su Chen and Yung-Cheng Liao

Eng. Proc. 2025, 98(1), 6; https://doi.org/10.3390/engproc2025098006 - 9 Jun 2025

Viewed by 249

Abstract

By employing the analytic hierarchy process (AHP), we investigated consumer demand and preferences for InsurTech technologies. A survey was conducted with 350 respondents, yielding 348 completed questionnaires and achieving a response rate of 99.4%. After consistency checks, 78 invalid questionnaires were excluded, resulting [...] Read more.

By employing the analytic hierarchy process (AHP), we investigated consumer demand and preferences for InsurTech technologies. A survey was conducted with 350 respondents, yielding 348 completed questionnaires and achieving a response rate of 99.4%. After consistency checks, 78 invalid questionnaires were excluded, resulting in 270 valid responses, with an effective response rate of 77.3%. Using the Analytic Hierarchy Process (AHP), five critical dimensions were identified as top priorities for insurance companies implementing InsurTech solutions: (1) video insurance and mobile applications, (2) blockchain-based claims processing, (3) robo-advisors, (4) the Internet of Things (IoT), and (5) big data analytics. Video and mobile applications, along with blockchain, accounted for over 30% of the total importance of evaluating InsurTech technologies. Among the assessment criteria, “mobile applications” and “remote insurance” had the highest weights, highlighting their roles in the InsurTech service model. Insurance providers need to prioritize these two dimensions when designing their InsurTech service models to enhance service convenience and the customer experience. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

6 pages, 185 KiB

Open AccessProceeding Paper

Analysis of Severity of Losses and Wastes in Taiwan’s Agri-Food Supply Chain Using Best–Worst Method and Multi-Criteria Decision-Making

by Wen-Hua Yang, Yi-Chang Chen and Ya-Jhu Yang

Eng. Proc. 2025, 98(1), 8; https://doi.org/10.3390/engproc2025098008 - 9 Jun 2025

Viewed by 335

Abstract

Food loss and waste are critical challenges in Taiwan’s agri-food supply chain, deteriorating security and resource efficiency. By employing the best–worst method (BWM), a multi-criteria decision-making model was developed in this study to evaluate the severity of losses and wastes. Combining literature review [...] Read more.

Food loss and waste are critical challenges in Taiwan’s agri-food supply chain, deteriorating security and resource efficiency. By employing the best–worst method (BWM), a multi-criteria decision-making model was developed in this study to evaluate the severity of losses and wastes. Combining literature review results with expert survey analysis results, key loss points, and mitigation strategies were identified to enhance sustainability and efficiency in Taiwan’s agricultural food system. Among the seven stages of the agricultural food supply chain, supermarket waste (16.95%) was identified as the severest, followed by government policies (16.63%), restaurant waste (15.35%), processing loss (14.71%), production site loss (13.64%), household waste (11.93%), and logistics/storage/distribution loss (10.79%). In the subcategories of each supply chain stage, the eight severe issues were identified as “Inadequate planning and control of overall production and marketing policies” under government policies, “Adverse climate conditions” and “Imbalance in production and marketing” under production site loss, “Inaccurate market demand forecasting” and “Poor inventory management at supermarkets” under supermarket waste, and “Improper storage management of ingredients leading to spoilage” as well as “Inability to accurately forecast demand due to menu diversity” under restaurant waste. The least severe issues included “Poor production techniques” under production site loss. Other minor issues included “Inefficient use of ingredients due to poor cooking skills”, “Festive culture and traditional customs”, and “Suboptimal food labeling design”, all of which contributed to household waste. Based on these findings, we proposed recommendations to mitigate food loss and waste in Taiwan’s agricultural food supply chain from practical, policy, and academic perspectives. The results of this study serve as a reference for relevant organizations and stakeholders. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

7 pages, 181 KiB

Open AccessProceeding Paper

Generative Artificial Intelligence-Based Gamified Programming Teaching System: Promoting Peer Competition and Learning Motivation

by You-Jen Chen, Ze-Ping Chen, Chien-Hung Lai and Chen-Wei Peng

Eng. Proc. 2025, 98(1), 9; https://doi.org/10.3390/engproc2025098009 - 12 Jun 2025

Viewed by 349

Abstract

In traditional programming education, teachers typically design fixed questions and standard answers, manually grading the solutions submitted by students. This process not only requires significant time and effort from educators but may also fail to provide timely and personalized feedback due to limited [...] Read more.

In traditional programming education, teachers typically design fixed questions and standard answers, manually grading the solutions submitted by students. This process not only requires significant time and effort from educators but may also fail to provide timely and personalized feedback due to limited teaching resources. To alleviate these burdens and enhance teaching efficiency, this study leverages generative artificial intelligence (AI) technology to develop a system capable of automatically generating questions and grading answers. Students engage in programming exercises through a gamified approach, with the system providing instant feedback on their answers. Additionally, student performance is displayed via leaderboards, incorporating peer competition to boost learning motivation. According to a user survey, the gamified system demonstrates significant advantages: 56.67% of students found the system easy to use; 40% considered the system well-integrated; 60% indicated that they quickly mastered the system’s functionality, and over half (53.33%) believed that the leaderboard effectively enhanced their competitive awareness and motivation. These results suggest that the system not only reduces teachers’ workload but also increases student engagement and learning outcomes through gamified design. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

14 pages, 1599 KiB

Open AccessProceeding Paper

Values of Reused Unused Space Under Bridges

by Huang-Liang Lee, Yi-Han Lin and Wen-Bor Lu

Eng. Proc. 2025, 98(1), 10; https://doi.org/10.3390/engproc2025098010 - 13 Jun 2025

Viewed by 426

Abstract

In the development of the city, land planning must be precise and collective, emphasizing the multi-functional usability of space. The space under bridges can be utilized for urban development. However, the space under bridges has been researched only based on the theoretical operation [...] Read more.

In the development of the city, land planning must be precise and collective, emphasizing the multi-functional usability of space. The space under bridges can be utilized for urban development. However, the space under bridges has been researched only based on the theoretical operation of space, and the psychological values of the attributes of the space under bridges held by users have been rarely studied. Therefore, we explored the attributes of the space under bridges using the critical chain method and interviews with the stakeholders. The characteristic attributes were identified with regional implications. The attributes need to be considered in the spatial planning to enhance the space utilization under bridges. The results of this study present important information for policymakers or designers to plan the use of space. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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21 pages, 635 KiB

Open AccessProceeding Paper

Fuzzy Set Qualitative Comparative Analysis to Explore Elementary and Secondary School Teachers’ Behavior and Influencing Factors in Using Digital Learning Tools

by Nai-Chen Chen, Wu-Chuan Yang and Ming-Lung Wu

Eng. Proc. 2025, 98(1), 11; https://doi.org/10.3390/engproc2025098011 - 17 Jun 2025

Viewed by 184

Abstract

We investigated the configurational conditions influencing primary and secondary school teachers’ behavioral intentions (BIs) and usage behavior (UB) in adopting digital learning tools by using fuzzy set qualitative comparative analysis (fsQCA) and Tobit analysis. Based on the extended unified theory of acceptance and [...] Read more.

We investigated the configurational conditions influencing primary and secondary school teachers’ behavioral intentions (BIs) and usage behavior (UB) in adopting digital learning tools by using fuzzy set qualitative comparative analysis (fsQCA) and Tobit analysis. Based on the extended unified theory of acceptance and use of technology (UTAUT2) and by integrating TPK, configurations that drive or hinder teachers’ use of digital tools were identified. The results revealed that BI formation is driven by the core combination of facilitating conditions (FC) and hedonic motivation (HM); the synergy of FC, HM, and TPK; and the interplay of TPK and HM. UB was significantly promoted by the combinations of H with BI and TPK with BI. Conversely, the low levels of H and BI, or H and TPK lowered the levels of UB. By integrating fsQCA and Tobit analysis, the complex and asymmetric effects in digital tool adoption were understood, and recommendations were proposed to develop differentiated support strategies based on these configurational findings. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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18 pages, 1640 KiB

Open AccessProceeding Paper

Future Agenda on Higher Education Policy Using Artificial Intelligence Tools: A Review and Bibliometric Analysis

by Sai Manideep Appana, Ravi Sankar Pasupuleti, Jagadish Tulimelli, Yedukondalu Dokku, Wen-Kuo Chen and Venkateswarlu Nalluri

Eng. Proc. 2025, 98(1), 12; https://doi.org/10.3390/engproc2025098012 - 17 Jun 2025

Viewed by 391

Abstract

Artificial intelligence (AI) has emerged as a transformative force in higher education, reshaping pedagogical practices, administrative processes, and the overall learning experience. In this study, we analyzed 398 academic documents in the Scopus database, from 2014 to 2024, to explore the discourse surrounding [...] Read more.

Artificial intelligence (AI) has emerged as a transformative force in higher education, reshaping pedagogical practices, administrative processes, and the overall learning experience. In this study, we analyzed 398 academic documents in the Scopus database, from 2014 to 2024, to explore the discourse surrounding AI in higher education. Utilizing the Biblioshiny tool for bibliometric analysis, key insights were revealed across sources, keywords, citation patterns, authorship trends, international collaboration, annual growth rate, document age, and references. The analysis results highlighted the diversity of sources contributing to the discourse, the breadth of topics covered by keywords, and the significant impact of research using citation metrics. Collaborative efforts, particularly international collaboration, have played a prominent role in advancing AI research in academia. A rapidly evolving scholarly landscape is characterized by substantial annual growth and a relatively recent body of literature. The results of this study offer a basis for scholars, practitioners, and policymakers to further investigate specific content, methodologies, quality, impact of sources, keyword clustering, authorship dynamics, longitudinal trends, and citation patterns. The results also contribute to advancing the understanding of AI’s role in higher education and informs future research directions in the domain. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 618 KiB

Open AccessProceeding Paper

Implementing Finger Movement Measure System with Music-Gamification Elements

by Sinan Chen, Xian Wu, Atsuko Hayashi and Masahide Nakamura

Eng. Proc. 2025, 98(1), 13; https://doi.org/10.3390/engproc2025098013 - 17 Jun 2025

Viewed by 323

Abstract

Dexterity of the fingers is crucial in physical function, as it directly impacts daily activities and is closely connected to cognitive function. The production of brain-derived neurotrophic factor (BDNF) is related to the fingertips in motion. In previous research, we developed a finger [...] Read more.

Dexterity of the fingers is crucial in physical function, as it directly impacts daily activities and is closely connected to cognitive function. The production of brain-derived neurotrophic factor (BDNF) is related to the fingertips in motion. In previous research, we developed a finger motion measurement system for the elderly by integrating image recognition technology with a touch panel. However, despite the system’s ability to capture fine-grained coordinate changes at the moment when fingers touch the panel, the experiment was unengaging for participants. Therefore, we improved the system for measuring finger motion to be less exhausting and more enjoyable. We incorporated music and gamification elements at the moments of finger touch. We obtained a selection of representative rhythm tracks and implemented animated materials in gamification. The participants’ fatigue and enjoyment were measured based on “responsiveness” and “focus” using a quantitative evaluation method. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 1240 KiB

Open AccessProceeding Paper

Design and Application of Virtual Simulation Technology in Contextualized Live-Streaming E-Commerce Teaching

by Kun Peng, Dorothy DeWitt and Seng Yue Wong

Eng. Proc. 2025, 98(1), 14; https://doi.org/10.3390/engproc2025098014 - 18 Jun 2025

Viewed by 257

Abstract

We explored how VR technology models can be applied to live-streaming e-commerce teaching. We employed relevant real-time data analysis and feedback to design a virtual simulation experimental platform to provide students with personalized experiences in live-streaming e-commerce operations in traditional e-commerce courses. In [...] Read more.

We explored how VR technology models can be applied to live-streaming e-commerce teaching. We employed relevant real-time data analysis and feedback to design a virtual simulation experimental platform to provide students with personalized experiences in live-streaming e-commerce operations in traditional e-commerce courses. In this study, different contexts were integrated into live-streaming e-commerce teaching, and a standardized course for contextualized live-streaming e-commerce teaching was designed in a standardized process consisting of the following steps: “introduction link”, “theoretical explanation”, “virtual simulation operation”, and “summary and feedback”. Virtual simulation technology was standardized in contextualized live-streaming e-commerce teaching by simplifying the design of live-streaming e-commerce courses to enhance students’ practical skills. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 1398 KiB

Open AccessProceeding Paper

Analysis of Three-Stage Visit Behavior of Tourists Using ChatGPT: Agenda for Future Study

by Pahrudin Pahrudin, Li-Wei Liu, Anfitri Kristin Sihombing and Idrus Jamalulel

Eng. Proc. 2025, 98(1), 15; https://doi.org/10.3390/engproc2025098015 - 18 Jun 2025

Viewed by 293

Abstract

Chat generative pre-trained transformer (ChatGPT) is an artificial intelligence (AI) engine. Research on tourism using ChatGPT has gained traction from scholars all over the world. However, limited studies on ChatGPT and the tourism industry have been conducted using an analysis of three-stage visit [...] Read more.

Chat generative pre-trained transformer (ChatGPT) is an artificial intelligence (AI) engine. Research on tourism using ChatGPT has gained traction from scholars all over the world. However, limited studies on ChatGPT and the tourism industry have been conducted using an analysis of three-stage visit behavior. We analyzed the current trend in tourism research using ChatGPT with a bibliometric analysis based on the Scopus database. A total of 110 documents were used in this study for document review, and R studio Version 2022.12.0+353 was used to analyze the documents. The results present indicators for a systematic review of the documents, such as the number of publications and co-word analysis. A theoretical system was developed in this study to explore travelers’ behavior using ChatGPT in the pre-, during, and post-travel periods. The study results contribute to the development of the tourism industry to understand tourist behavior using ChatGPT. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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11 pages, 1036 KiB

Open AccessProceeding Paper

Empowering Community Developers with Digital Skills: Training in No-Code Mobile Applications in Effective Fieldwork Survey

by Phiraphath Phansiri, Pornsaran Kanthong, Suthida Songseeda, Santikorn Pinyong, Piyanart Imdee and Suriya Klangrit

Eng. Proc. 2025, 98(1), 16; https://doi.org/10.3390/engproc2025098016 - 18 Jun 2025

Viewed by 420

Abstract

This article presents the concept and principles of digital technology for community development and community developers. An approach for creating no-code mobile applications for community developers’ fieldwork surveys is also proposed to organize a digital technology skill training program focused on no-code mobile [...] Read more.

This article presents the concept and principles of digital technology for community development and community developers. An approach for creating no-code mobile applications for community developers’ fieldwork surveys is also proposed to organize a digital technology skill training program focused on no-code mobile application development for community developers. The training program consists of a two-day hands-on workshop in no-code mobile application development with 50 community developers participating in its development. A 70% increase in participants’ knowledge of utilizing digital technology for local community development was observed, with all participants (100%) successfully developing no-code mobile applications for surveying data on their communities. Additionally, the participants expressed high satisfaction with the training format and content, with an average score of 4.80. Digital technology knowledge is essential for contemporary community development efforts. Empowering community developers, especially those engaged in fieldwork, to independently acquire mobile app development skills or access continuous learning resources significantly enhances their professional capacity. This empowerment leads to more effective and efficient community development practices, particularly in community data collection. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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11 pages, 1110 KiB

Open AccessProceeding Paper

Evaluation Index for Healing Gardens in Computer-Aided Design

by Cheng-Kai Weng, Chao-Feng Lai and Wei-Chieh Yeh

Eng. Proc. 2025, 98(1), 17; https://doi.org/10.3390/engproc2025098017 - 19 Jun 2025

Viewed by 399

Abstract

We developed an evaluation index model for healing gardens designed using computer-aided design. The landscape therapy theory, innovative methodologies such as the fuzzy Delphi method, and the analytic hierarchy process (AHP) were integrated into the model. Three core design indices for healing gardens—somatosensory [...] Read more.

We developed an evaluation index model for healing gardens designed using computer-aided design. The landscape therapy theory, innovative methodologies such as the fuzzy Delphi method, and the analytic hierarchy process (AHP) were integrated into the model. Three core design indices for healing gardens—somatosensory elements, visual components, and physical activity features—were identified and analyzed using the developed index model in this study. Plant diversity was identified as the most significant factor, followed by modeling aesthetics, color variety, plant healing properties, spatial recreational features, sensory richness, unobstructed circulation, and barrier-free design. While the developed evaluation index model has limitations, it is a novel and systematic model based on innovative computing methods to assess and enhance contemporary healing garden design. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 225 KiB

Open AccessProceeding Paper

Retail Service Quality Assessment Using Interval-Valued Pythagorean Fuzzy Approach

by Venkateswarlu Nalluri, Sai Manideep Appana, Alaparthi Naga Bhushan, Jing-Rong Chang and Long-Sheng Chen

Eng. Proc. 2025, 98(1), 18; https://doi.org/10.3390/engproc2025098018 - 20 Jun 2025

Viewed by 187

Abstract

In this study, a service quality (SQ) quantitative assessment method for retail industry operations was established to transform the perceptions and expectations of consumers into measurement framework requirements in the Indian market. The benefit of the recently created framework using interval-valued Pythagorean fuzzy [...] Read more.

In this study, a service quality (SQ) quantitative assessment method for retail industry operations was established to transform the perceptions and expectations of consumers into measurement framework requirements in the Indian market. The benefit of the recently created framework using interval-valued Pythagorean fuzzy to analyze the SQ is to handle imprecise human assessments, which is lacking in traditional SQ assessment methods. Therefore, we proposed a two-stage SQ assessment method by applying an extended novel Fuzzy methodology. We conducted a systematic literature review to identify the service quality and its products in the framework of the retail industry. In addition, we identified the gaps and proposed the measurement framework through consumer expectations and perceptions gaps. The present research findings confirmed that reliability and tangibility are important SQ dimensions reflecting the customer’s opinions. The findings help retail businesses make collective decisions on high-priority areas and effectively allocate resources to meet the needs of their customers. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

8 pages, 1063 KiB

Open AccessProceeding Paper

Predicting Student Success in English Tests Using Artificial Intelligence Algorithm

by Thao-Trang Huynh-Cam, Dat Tan Truong, Long-Sheng Chen, Tzu-Chuen Lu and Venkateswarlu Nalluri

Eng. Proc. 2025, 98(1), 19; https://doi.org/10.3390/engproc2025098019 - 20 Jun 2025

Viewed by 309

Abstract

In Vietnam, English proficiency is a graduation requirement and offers students great opportunities to win scholarships and employability after graduation. Universities in the Mekong Delta region (MDR) often face challenges in foresting students’ English proficiency despite continuous assistance offered. Although students have taken [...] Read more.

In Vietnam, English proficiency is a graduation requirement and offers students great opportunities to win scholarships and employability after graduation. Universities in the Mekong Delta region (MDR) often face challenges in foresting students’ English proficiency despite continuous assistance offered. Although students have taken online supplementary courses (OSC) delivered through e-learning systems to support their English formal classes for several years, students’ successes in English tests with such supplementary courses and the predictors of this issue remain unknown. Therefore, we developed a model to predict students’ success in English final tests based on behaviors and grades in OSC using logistic regression (LR) and classification and regression tree (CART) classifiers. A total of 109 students of OSC in a target university in MDR participated in this study, and the result showed that CART (area under the curve (AUC) = 89.3%) was slightly better than LR. The outcomes of this study contribute to students’ success in English tests and the enhancement of the effectiveness of online supplementary courses for English improvements. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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9 pages, 1819 KiB

Open AccessProceeding Paper

Magic of Water: Exploration of Production Process with Fluid Effects in Film and Advertisement in Computer-Aided Design

by Nan-Hu Lu

Eng. Proc. 2025, 98(1), 20; https://doi.org/10.3390/engproc2025098020 - 27 Jun 2025

Viewed by 238

Abstract

Fluid effects are important in films and advertisements, where their realism and aesthetic quality directly impact the visual experience. With the rapid advancement of digital technology and computer-aided design (CAD), modern visual effects are used to simulate various water-related phenomena, such as flowing [...] Read more.

Fluid effects are important in films and advertisements, where their realism and aesthetic quality directly impact the visual experience. With the rapid advancement of digital technology and computer-aided design (CAD), modern visual effects are used to simulate various water-related phenomena, such as flowing water, ocean waves, and raindrops. However, creating these realistic effects is not solely dependent on advanced software and hardware; it also requires an understanding of the technical and artistic aspects of visual effects artists. In the creation process, the artist must possess a keen aesthetic sense and innovative thinking to craft stunning visual effects to overcome technological constraints. Whether depicting the grandeur of turbulent ocean scenes or the romance of gentle rain, the artist needs to transform fluid effects into expressive visual language to enhance emotional impact, aligning with the storyline and the director’s vision. The production process of fluid effects typically involves the following critical steps. First, the visual effects artist utilizes CAD-based tools, particle systems, or fluid simulation software to model the dynamic behavior of water. This process demands a solid foundation in physics and the ability to adjust parameters flexibly according to the specific needs of the scene, ensuring that the fluid motion appears natural and smooth. Next, in the rendering stage, the simulated fluid is transformed into realistic imagery, requiring significant computational power and precise handling of lighting effects. Finally, in the compositing stage, the fluid effects are seamlessly integrated with live-action footage, making the visual effects appear as though they are parts of the actual scene. In this study, the technical details of creating fluid effects using free software such as Blender were explored. How advanced CAD tools are utilized to achieve complex water effects was also elucidated. Additionally, case studies were conducted to illustrate the creative processes involved in visual effects production to understand how to seamlessly blend technology with artistry to create unforgettable visual spectacles. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 1945 KiB

Open AccessProceeding Paper

Serious Game Design Integrating Design–Play–Experience Framework: Digital Interactive Experience Exploring Ecology of Palaeoloxodon

by Tzu-Chuen Lu, Yu-Ci Chen and Chun-Hsiang Chang

Eng. Proc. 2025, 98(1), 21; https://doi.org/10.3390/engproc2025098021 - 27 Jun 2025

Viewed by 250

Abstract

In this study, we developed a game related to Palaeoloxodon huaihoensis to enhance public interest in learning about its ecology. The game integrates education and entertainment elements at four interactive levels “See Sea Bones,” “Assembling Organs,” “Bacterias Cleaner,” and “Painting Elephant” to allow [...] Read more.

In this study, we developed a game related to Palaeoloxodon huaihoensis to enhance public interest in learning about its ecology. The game integrates education and entertainment elements at four interactive levels “See Sea Bones,” “Assembling Organs,” “Bacterias Cleaner,” and “Painting Elephant” to allow players to explore the fossil structure, internal organs, and historical background of Palaeoloxodon huaihoensis. In the design process, we incorporated the design–play–experience framework and the gameplay–purpose–scope (GPS) model to balance entertainment and education. To evaluate the effectiveness of the developed game, a questionnaire survey on a Likert scale was conducted with 180 participants visiting the National Museum of Natural Science, Taiwan. The results indicated that the majority of the players were satisfied with the game’s design and content, particularly in terms of its ability to stimulate creativity. This research demonstrated the potential of games in museum education and provides insights for future optimization. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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9 pages, 1107 KiB

Open AccessProceeding Paper

Predicting the Learning Performance of Minority Students in a Vietnamese High School Using Artificial Intelligence Algorithms

by Hai-Duy Le, Thao-Trang Huynh-Cam, Long-Sheng Chen, Vo Phan Thu Ngan and Tzu-Chuen Lu

Eng. Proc. 2025, 98(1), 22; https://doi.org/10.3390/engproc2025098022 - 27 Jun 2025

Viewed by 315

Abstract

This study aims to predict and discover important factors for the learning performance of students belonging to two ethnic groups—Khmer and Chinese (Hoa) students—in Soc Trang with the use of random forest (RF) and Gaussian Naïve Bayes (GNB) classifiers based on students’ demographics [...] Read more.

This study aims to predict and discover important factors for the learning performance of students belonging to two ethnic groups—Khmer and Chinese (Hoa) students—in Soc Trang with the use of random forest (RF) and Gaussian Naïve Bayes (GNB) classifiers based on students’ demographics and grade point average (GPA) scores. The study involved 174 Khmer and Chinese (Hoa) students in Grade 10 in a high school in Soc Trang Province, Vietnam. The results showed that, for Khmer students, GNB was better than RF, with an F1 score of 100%. Mathematics was the most important subject leading Khmer students to very good or poor performance. For Chinese (Hoa) students, both classifiers showed the same accuracy performance. Scores in Literature and English in Semester 1 impacted Chinese (Hoa) students’ performance. The results of this study provide a reference for formulating a policy to improve the learning performance of minority students to prevent dropouts. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 426 KiB

Open AccessProceeding Paper

Using Artificial Intelligence to Support Students in Developing Startup Products in English as a Foreign Language Course

by Wen-Chi Hu and Shih-Tsung Hsu

Eng. Proc. 2025, 98(1), 23; https://doi.org/10.3390/engproc2025098023 - 27 Jun 2025

Viewed by 176

Abstract

We explored the use of artificial intelligence (AI) in enhancing the English proficiency of students in the English as a Foreign Language (EFL) course through a startup product development curriculum. In the course, real-world business scenarios of startup companies were offered for students [...] Read more.

We explored the use of artificial intelligence (AI) in enhancing the English proficiency of students in the English as a Foreign Language (EFL) course through a startup product development curriculum. In the course, real-world business scenarios of startup companies were offered for students to analyze English communication skills on crowdfunding platforms and in product promotional videos. The EFL students used entrepreneurial skills to create and present their product videos in a team to the class who acted as potential investors. Pre- and post-test analyses were conducted to assess the impact of AI-assisted learning on enhancing English listening and reading ability. Significant improvements were observed, suggesting AI-enhanced entrepreneurial experiences and the listening and reading ability of the EFL students. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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12 pages, 2527 KiB

Open AccessProceeding Paper

Structural Properties of Co-Citation and Co-Occurrence Networks in Cold Chain Logistic Management Using Bibliometric Computation

by Yu-Jin Hsu, Chih-Wen Hsiao and Kuei-Kuei Lai

Eng. Proc. 2025, 98(1), 24; https://doi.org/10.3390/engproc2025098024 - 30 Jun 2025

Viewed by 188

Abstract

In the past two decades, particularly through the pandemic, the demand for real-time logistics has significantly increased. Cold chain logistics ensures specific temperature conditions for perishable goods such as food and pharmaceuticals, which is crucial for maintaining product quality, safety, and regulatory compliance. [...] Read more.

In the past two decades, particularly through the pandemic, the demand for real-time logistics has significantly increased. Cold chain logistics ensures specific temperature conditions for perishable goods such as food and pharmaceuticals, which is crucial for maintaining product quality, safety, and regulatory compliance. The integration of the Internet of Things (IoT) into cold chain logistics has transformed supply chain operations. The COVID-19 pandemic and the global urgency for vaccine distribution accelerated the adoption of cold chain technologies, emphasizing their role in preserving perishable goods’ integrity. IoT enables real-time monitoring, remote control, predictive analytics, and data-driven decision-making, all of which are essential for modern logistics. We conducted a bibliometric analysis of 50 publications from 1997 to 2024 to examine IoT’s role in cold chain management. Through co-occurrence and co-citation network analysis, core themes, influential works, and major contributors were identified. Thematic mapping highlighted the importance of temperature monitoring, logistics optimization, and risk management. Additionally, the transition from conventional logistics practices to IoT-driven methodologies was investigated in cold chain operations. The findings of this study provide a basis for understanding the structural properties of co-citation and co-occurrence networks in cold chain logistics and the evolving landscape of cold chain technology, and its impact on logistics, emphasizing the importance of intelligent, reliable, and sustainable cold chain systems to meet the growing demands in global supply chains. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 2062 KiB

Open AccessProceeding Paper

Visualized Diagnostic Assessment Data for Syllabus Design in English as Foreign Language: A Model for Enhancing Language Learning Needs in Higher Education

by Tsui-Ying Lin and Ya-Wen Lin

Eng. Proc. 2025, 98(1), 25; https://doi.org/10.3390/engproc2025098025 - 27 Jun 2025

Viewed by 146

Abstract

Data visualization has empowered analyzing, exploring, and communicating data effectively. It has been widely adopted across diverse disciplines. However, research indicates that data visualization in education is mainly favored in distance learning environments, leaving traditional classroom settings largely unexplored. Moreover, despite the growing [...] Read more.

Data visualization has empowered analyzing, exploring, and communicating data effectively. It has been widely adopted across diverse disciplines. However, research indicates that data visualization in education is mainly favored in distance learning environments, leaving traditional classroom settings largely unexplored. Moreover, despite the growing emphasis on data-driven decision-making in education, a notable gap exists in using visualized assessment data to develop curriculum planning in language classrooms. Therefore, we developed a model for syllabus design and material development in an EFL classroom in Taiwan based on diagnostic test results. An online adaptive diagnostic test was used to gather visualized assessment data, which was analyzed with an AI tool to identify language learning needs and to develop the syllabus design and materials. By incorporating visualized diagnostic assessment data into the decision-making process, educators can design responsive and individualized syllabi that meet the needs of students. This approach enhances the effectiveness of language teaching and makes curriculum development more accessible and manageable for educators. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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9 pages, 1208 KiB

Open AccessProceeding Paper

Application of Artificial Intelligence to Improve Chip Defect Detection Using Semiconductor Equipment

by Chung-Jen Fu, Hsuan-Lin Chen and Huo-Yen Tseng

Eng. Proc. 2025, 98(1), 26; https://doi.org/10.3390/engproc2025098026 - 30 Jun 2025

Viewed by 459

Abstract

We investigated the application of artificial intelligence (AI) technology for the inspection of semiconductor process equipment to address key issues such as low production efficiency and high equipment failure rates. The semiconductor industry, being central to modern technology, requires complex and precise processes [...] Read more.

We investigated the application of artificial intelligence (AI) technology for the inspection of semiconductor process equipment to address key issues such as low production efficiency and high equipment failure rates. The semiconductor industry, being central to modern technology, requires complex and precise processes where even minor defects lead to product failures, negatively impacting yield and increasing costs. Traditional inspection methods are not adequate for modern high-precision, high-efficiency production demands. By integrating advanced AI technologies, such as machine learning, deep learning, and pattern recognition, large volumes of experimental data are collected and analyzed to optimize process parameters, enhance stability, and improve product yield. By using AI, the identification and classification of defects are automated to predict potential equipment failures and reduce downtime and overall costs. By combining AI with automated optical inspection (AOI) systems, a widely used defect detection tool has been developed for semiconductor manufacturing. However, under complex conditions, AOI systems are prone to producing false positives, resulting in overkill rates above 20%. This wastes perfect products and increases the cost due to the need for manual re-inspection, hindering production efficiency. This study aims to improve wafer inspection accuracy using AI technology and reduce false alarms and overkill rates. By developing intelligent detection models, the system automatically filters out false defects and minimizes manual intervention, boosting inspection efficiency. We explored how AI is used to analyze inspection data to identify process issues and optimize workflows. The results contribute to the reduction in labor and time costs, improving equipment performance, and significantly benefitting semiconductor production management. The AI-driven method can be applied to other manufacturing processes to enhance efficiency and product quality and support the sustainable growth of the semiconductor industry. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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6 pages, 488 KiB

Open AccessProceeding Paper

Optimizing Safety Net Installation on Construction Sites Using YOLO and the Novel Linear Intersection over Union

by Yu-Hung Tsai, Meng-Hsiun Tsai, Yun-Hui Lai and Hsien-Chung Huang

Eng. Proc. 2025, 98(1), 27; https://doi.org/10.3390/engproc2025098027 - 30 Jun 2025

Viewed by 183

Abstract

This study aims to evaluate whether safety nets on construction sites are correctly installed using an image processing and deep learning technique. The developed method performs data preprocessing, including horizontal flipping, rotation, and contrast-limited adaptive histogram equalization, and then applies the YOLO model [...] Read more.

This study aims to evaluate whether safety nets on construction sites are correctly installed using an image processing and deep learning technique. The developed method performs data preprocessing, including horizontal flipping, rotation, and contrast-limited adaptive histogram equalization, and then applies the YOLO model to estimate the accuracy of safety net installation. The developed method significantly improved the accuracy of the YOLO model detection and mitigated errors associated with large safety net surfaces and slanted steel beams using the novel linear intersection over union as a metric. The proposed method effectively improved the assessment of safety net installation. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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9 pages, 989 KiB

Open AccessProceeding Paper

Motion Capture System in Performance Assessment of Playing Piano: Establishing the Center for Music Performance Science and Musicians’ Medicine in China

by Qing Yang, Chieko Mibu and Yuchi Zhang

Eng. Proc. 2025, 98(1), 28; https://doi.org/10.3390/engproc2025098028 - 1 Jul 2025

Viewed by 309

Abstract

This article introduces China’s first Center for Music Performance Science and Musicians’ Medicine. In the center, motion capture (MoCap) technology is used to study piano performance and musicians’ health. An idea and methodology to assess the performance of piano performance are developed in [...] Read more.

This article introduces China’s first Center for Music Performance Science and Musicians’ Medicine. In the center, motion capture (MoCap) technology is used to study piano performance and musicians’ health. An idea and methodology to assess the performance of piano performance are developed in the center. The center uses high-precision MoCap system to analyze movement efficiency, posture, joint angles, and coordination of pianists. By addressing physical challenges, the center promotes healthier, more efficient practice ways, especially for adolescent piano learners. The pioneering research results bridge the gap between music performance (art) and science, positioning China as a leader in music performance science and musicians’ health. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 922 KiB

Open AccessProceeding Paper

Application of Generative Artificial Intelligence in Design Education: An Exploration and Analysis to Enhance Student Creativity

by Chi-Wei Lee

Eng. Proc. 2025, 98(1), 29; https://doi.org/10.3390/engproc2025098029 - 2 Jul 2025

Viewed by 356

Abstract

Generative Artificial Intelligence (GenAI) is transforming design, but its integration into education presents challenges. This study investigates GenAI’s application in visual design courses to enhance student creativity. Through hands-on projects using text/image generation tools for design competitions and a questionnaire survey (N = [...] Read more.

Generative Artificial Intelligence (GenAI) is transforming design, but its integration into education presents challenges. This study investigates GenAI’s application in visual design courses to enhance student creativity. Through hands-on projects using text/image generation tools for design competitions and a questionnaire survey (N = 102) assessing creativity factors (sensitivity, fluency, flexibility, originality, elaboration), GenAI’s impact was evaluated. Findings show GenAI significantly enhanced textual creativity (fluency, flexibility). Its effect on visual originality was perceived as less impactful, though project outcomes were successful. GenAI boosts efficiency and creativity, but pedagogy must balance AI aid with fostering critical thinking and unique expression. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 589 KiB

Open AccessProceeding Paper

Dynamic Program Analysis and Visualized Learning System in University Programming Courses

by Pei-Wen Lin, Shu-Han Yu and Chien-Hung Lai

Eng. Proc. 2025, 98(1), 30; https://doi.org/10.3390/engproc2025098030 - 2 Jul 2025

Viewed by 215

Abstract

To correspond to the advancement of technology, programming has become an indispensable course in university curricula. However, students easily become confused by the rules governing program execution or by complex logical structures. Mastering program structure and logic often is a significant challenge for [...] Read more.

To correspond to the advancement of technology, programming has become an indispensable course in university curricula. However, students easily become confused by the rules governing program execution or by complex logical structures. Mastering program structure and logic often is a significant challenge for beginners, especially. Despite the availability of information on programming on various websites and tools, including generative artificial intelligence (AI), there is still a gap between conceptual understanding and practical application for beginners. They overlook important implementation details or struggle to grasp the flow of a program, making the mastery of program logic a persistent challenge. To address these issues, we have developed a system that dynamically generates process architecture diagrams. Users upload their code, and the system produces corresponding diagrams that decompose and execute the code line by line. Its visual representation allows users to observe the program’s execution and aids them in comprehending the sequence and operational flow of the code. By understanding the structure and logic of the program intuitively, this system supplements traditional teaching methods and AI-assisted question-and-answer tools. The experimental results demonstrated that students found the system helpful to track their learning progress (87%) and improved their understanding of program code (81%). Additionally, 84% of students reported that the system was easy to use, highlighting its user-friendliness. In terms of student interest, 83% of students agreed that the interactive elements made learning more engaging, indicating that the system positively contributed to dynamic and enjoyable learning. However, 63% of students reported an improvement in coding and were influenced by the complexity of the programming tasks assigned. Despite this, the overall satisfaction with the system developed in this study was high. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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14 pages, 12026 KiB

Open AccessProceeding Paper

Numerical Modeling of Post-Tensioned Concrete Flat Slabs with Unbonded Tendons in Fire

by Ya Wei, Daoan Fan and Francis T. K. Au

Eng. Proc. 2025, 98(1), 31; https://doi.org/10.3390/engproc2025098031 - 4 Jul 2025

Viewed by 131

Abstract

The structural fire of post-tensioned concrete flat slabs with unbonded tendons has not been well investigated so far. An investigation based on experimental results was conducted in this study using a numerical model. Three-dimensional nonlinear finite element models of the flat slabs were [...] Read more.

The structural fire of post-tensioned concrete flat slabs with unbonded tendons has not been well investigated so far. An investigation based on experimental results was conducted in this study using a numerical model. Three-dimensional nonlinear finite element models of the flat slabs were established by employing the software ABAQUS, where nonlinear material models of concrete and prestressing steel tendons at elevated temperatures were incorporated. Meanwhile, both the transient creep strain of concrete and thermal creep strain of prestressing steel were explicitly considered, based on which the numerical results obtained agreed well with those of the tests for vertical displacements and crack patterns of slabs. The variations in the tendon stresses were examined as well. The effects of tendon distribution, level of prestressing, and slab soffit area exposed to fire were investigated in relation to the structural responses of the slabs. Tendon distribution had a minor effect, while the level of prestressing and area exposed to fire had significant effects. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 771 KiB

Open AccessProceeding Paper

Dynamic Oral English Assessment System Based on Large Language Models for Learners

by Jiaqi Yu and Hafriza Binti Burhanudeen

Eng. Proc. 2025, 98(1), 32; https://doi.org/10.3390/engproc2025098032 - 7 Jul 2025

Viewed by 188

Abstract

The rapid development of science and technology enables technological innovations to change the way of English oral learning. Based on the use of a large language model (LLM), we developed a novel dynamic evaluation system for oral English, LLM-DAELSL, which combines daily oral [...] Read more.

The rapid development of science and technology enables technological innovations to change the way of English oral learning. Based on the use of a large language model (LLM), we developed a novel dynamic evaluation system for oral English, LLM-DAELSL, which combines daily oral habits and a textbook outline. The model integrates commonly used vocabulary from everyday social speech and authoritative prior knowledge, such as oral language textbooks. It also combines traditional large-scale semantic models with probabilistic algorithms to serve as an oral assessment tool for undergraduate students majoring in English-related fields in universities. The model provides corrective feedback to effectively enhance the proficiency of English learners through guided training at any time and place. The technological principle of the model involves inputting prior template knowledge into the language model for reverse guidance and utilizing the textbooks provided by China’s Ministry of Education. The model facilitates the practice and evaluation of pronunciation, grammar, vocabulary, and fluency. The six-month tracking results showed that the oral proficiency of the system learners was significantly improved in the four aspects, which provides a reference for other language learning method developments. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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14 pages, 1442 KiB

Open AccessProceeding Paper

Large Language Models in Low-Altitude Economy: A Novel Framework for Empowering Aerial Operations and Services

by Jun Wang and Yawei Shi

Eng. Proc. 2025, 98(1), 33; https://doi.org/10.3390/engproc2025098033 - 4 Jul 2025

Viewed by 247

Abstract

The advent of large language models (LLMs), characterized by their immense scale, deep understanding of language nuances, and remarkable generative capabilities, has sparked a revolution across numerous industries and reshaped the way of machines’ comprehension of human languages. In this context, the low-altitude [...] Read more.

The advent of large language models (LLMs), characterized by their immense scale, deep understanding of language nuances, and remarkable generative capabilities, has sparked a revolution across numerous industries and reshaped the way of machines’ comprehension of human languages. In this context, the low-altitude economy, an emerging domain that encompasses a wide spectrum of activities and services leveraging unmanned aerial vehicles (UAVs), drones, and other low-flying platforms, benefits significantly from the integration of LLMs. We developed a novel framework to explore the applications of LLMs in the low-altitude economy, outlining how these advanced models enhance aerial operations, optimize service delivery, and foster innovation in a rapidly evolving industry. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 1541 KiB

Open AccessProceeding Paper

Chiral Recognition of Carnitine Enantiomers Using Graphene Oxide-Modified Cadmium Telluride Quantum Dots

by Haiyan Yuan, Yu Ma, Yuhui Zhang, Jidong Yang, Zhiyuan Mei, Chengcheng Pi and Yuan Peng

Eng. Proc. 2025, 98(1), 34; https://doi.org/10.3390/engproc2025098034 - 8 Jul 2025

Viewed by 142

Abstract

Carnitine (CA) is a chiral amino acid and mostly comes from meat and dairy products. CA cannot be found in fruits, vegetables, or other plants, so vegetarians are deficient in CA. CA exists in the form of D-carnitine (D-CA) and L-carnitine (L-CA); only [...] Read more.

Carnitine (CA) is a chiral amino acid and mostly comes from meat and dairy products. CA cannot be found in fruits, vegetables, or other plants, so vegetarians are deficient in CA. CA exists in the form of D-carnitine (D-CA) and L-carnitine (L-CA); only L-carnitine has biological activity. L-CA promotes the oxidation of fatty acids and then causes the effect of weight loss. In this study, the fluorescence probe was established by using graphene oxide-modified cadmium telluride (CdTe) QDs (GO-CdTe QDs) for the chiral recognition of carnitine enantiomers. GO-CdTe QDs present fluorescence. D-CA enhances the fluorescence spectral signal of the GO-CdTe QDs system, while L-CA weakens its spectral signal. Based on this phenomenon, we determined D-carnitine and L-carnitine. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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9 pages, 631 KiB

Open AccessProceeding Paper

Allocation of Integrated Medical Nursing Homes

by Wenjie Du and Bingda Zhang

Eng. Proc. 2025, 98(1), 35; https://doi.org/10.3390/engproc2025098035 - 8 Jul 2025

Viewed by 121

Abstract

The location-allocation of nursing homes was examined by combining the entropy weight evaluation model and robust allocation model. The data of the elderly in Xuhui District in 2024 after the pandemic were used in this study. We constructed an evaluation index system by [...] Read more.

The location-allocation of nursing homes was examined by combining the entropy weight evaluation model and robust allocation model. The data of the elderly in Xuhui District in 2024 after the pandemic were used in this study. We constructed an evaluation index system by establishing the evaluation index principle of nursing homes’ location. Secondly, the polyhedral uncertainty set was used to predict the number of critical patients, and a model of robust configuration with capacity limitation and time constraints was constructed to minimize costs. The entropy weight method provided empirical results for the selection of nursing homes, and the robust configuration model ensured timely medical treatment. The feasibility and robustness of the mathematical model and solution method were verified, and the performance and advantages of the uncertain model over the deterministic model were proved. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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10 pages, 1113 KiB

Open AccessProceeding Paper

Examination of Nanochannels in Diluted Magnetic Doped CoTiSb Semiconductor

by Yuehua Chang

Eng. Proc. 2025, 98(1), 36; https://doi.org/10.3390/engproc2025098036 - 11 Jul 2025

Viewed by 108

Abstract

The first-principles calculation method was used to study doping elements with atomic numbers in the range of 23–30 (V–Zn) to form a single-atomic-spin nanochannel in a CoTiSb matrix. In a Ni-Sb single-atomic chain with high spin polarization and hole electrical conductivity, V-Sb, Mn-Sb, [...] Read more.

The first-principles calculation method was used to study doping elements with atomic numbers in the range of 23–30 (V–Zn) to form a single-atomic-spin nanochannel in a CoTiSb matrix. In a Ni-Sb single-atomic chain with high spin polarization and hole electrical conductivity, V-Sb, Mn-Sb, Fe-Sb, and Co-Sb single-atom chains have 100% spin polarization, indicating that a supercell containing the central atom chain has typical half-metal characteristics, and in the CoTiSb matrix, is centered on very small single-spin nanochannel forms. Using doping elements with atomic numbers between 23 and 27 (V-Co), the total magnetic moment of the supercell is constantly increasing, but the total magnetic moment of the Ni-doped supercell (Ni-Ti supercell) reduces, and a Cr-Ti supercell has an equal total magnetic moment. Doping elements Cu and Zn have atomic numbers higher than the range. Although the material of the nanochannel retains ferromagnetic properties, the spin polarization rate is reduced, and the material no longer has half-metallic properties. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 372 KiB

Open AccessProceeding Paper

Case Study of Binary Hypothesis Test Using ML

by Shang-Hua Chin and Cheng-Yu Chin

Eng. Proc. 2025, 98(1), 37; https://doi.org/10.3390/engproc2025098037 - 14 Jul 2025

Viewed by 64

Abstract

Artificial intelligence has attracted much attention due to its learning capability to solve versatile problems. Using a convolutional neural network in machine learning (ML), we investigated the binary hypothesis test, which is a fundamental problem in management and business. The simulation results showed [...] Read more.

Artificial intelligence has attracted much attention due to its learning capability to solve versatile problems. Using a convolutional neural network in machine learning (ML), we investigated the binary hypothesis test, which is a fundamental problem in management and business. The simulation results showed that the proposed method is comparable with the conventional optimum likelihood ratio test for the aspect of type I and II errors. Moreover, the learning capability of ML is promising for complicated data, the properties of which, such as probability distribution and/or statistical data, i.e., mean, variance, and others, are not known. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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6 pages, 766 KiB

Open AccessProceeding Paper

Acoustics of Nature: Rebuilding Human–Plant Connection Through Art and Technology

by Wei Peng

Eng. Proc. 2025, 98(1), 38; https://doi.org/10.3390/engproc2025098038 - 18 Jul 2025

Viewed by 74

Abstract

An innovative approach is explored to reconnect urban populations with nature through the integration of technology and artistic expression. In a case study of London’s Canary Wharf, environmental sensor data of sound and visual art were analyzed to create new pathways for human–plant [...] Read more.

An innovative approach is explored to reconnect urban populations with nature through the integration of technology and artistic expression. In a case study of London’s Canary Wharf, environmental sensor data of sound and visual art were analyzed to create new pathways for human–plant interaction. By transforming plant biological data into accessible artistic experiences, interdisciplinary methods spanning environmental science, plant biology, and artistic practice can enhance ecological awareness and engagement. The synthesized approach in this study offers promising solutions for addressing the growing disconnect between urban communities and their natural environment. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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6 pages, 2004 KiB

Open AccessProceeding Paper

Exploring Global Research Trends in Internet of Things and Total Quality Management for Industry 4.0 and Smart Manufacturing

by Chih-Wen Hsiao and Hong-Wun Chen

Eng. Proc. 2025, 98(1), 39; https://doi.org/10.3390/engproc2025098039 - 21 Jul 2025

Abstract

Amid the accelerated digital transformation and with the growing demand for smart manufacturing, the applications of the Internet of Things (IoT) and total quality management (TQM) have attracted increasing attention. Using R for bibliometric analysis, we explored research trends in IoT and TQM [...] Read more.

Amid the accelerated digital transformation and with the growing demand for smart manufacturing, the applications of the Internet of Things (IoT) and total quality management (TQM) have attracted increasing attention. Using R for bibliometric analysis, we explored research trends in IoT and TQM in terms of digital transformation and smart manufacturing. Data were gathered from the Web of Science from 1998 to 2025, with a total of 787 publications from 265 sources involving 2326 authors. A total of 31% of the authors collaborated internationally, indicating global interest in this topic. The publications had 33.65 citations on average, totaling 33,599 citations. Wang L.H. and Tao F. were identified as important authors. Keywords of “Industry 4.0”, “cyber-physical systems”, and “big data” underscore the technological significance of IoT and TQM. Major journals such as the Journal of Manufacturing Systems and IEEE Access had notable academic influence. Co-citation analysis results revealed that IoT and TQM played a significant role in driving digital transformation and enhancing production efficiency, offering references for enterprises in strategic planning for smart manufacturing. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 386 KiB

Open AccessProceeding Paper

Effectiveness of Cooperative Learning on English Learning Using Experimental Design in Elementary School: A Case Study of the Quizlet Online Platform

by Chih-Wei Lin, Ya-Fang Hsieh, Chi-Pei Ou Yang, Shan-Shan Chen, Chin-Cheng Yang and Chuan Chang

Eng. Proc. 2025, 98(1), 8007; https://doi.org/10.3390/engproc2025098007 - 9 Jun 2025

Viewed by 339

Abstract

We examined the effects of cooperative learning on learning satisfaction and learning effectiveness of elementary school students on the Quizlet online platform using an experimental design approach. Third and fourth-grade students from an elementary school in Taichung City were recruited in this study. [...] Read more.

We examined the effects of cooperative learning on learning satisfaction and learning effectiveness of elementary school students on the Quizlet online platform using an experimental design approach. Third and fourth-grade students from an elementary school in Taichung City were recruited in this study. A total of 55 students participated in this study and were grouped into the experimental group (28) and the control group (27). The experimental group engaged in game-based cooperative learning activities, while the control group participated in individual learning sessions. After eight weeks of the intervention in which one 30 min session was conducted every week, data on learning satisfaction and learning effectiveness were collected using a questionnaire. The collected data were analyzed to obtain descriptive statistics, independent sample t-tests, Pearson correlation analysis, and regression analysis. The participants in the experimental group reported improved learning satisfaction, learning environments, learning outcomes, and peer interactions compared with the control group. The experimental group also scored higher in learning effectiveness including skills. Significant differences were observed in learning satisfaction and effectiveness across genders and grade levels. A strong positive correlation indicated that higher learning satisfaction improved learning effectiveness among elementary students. Learning satisfaction was a significant predictor of learning effectiveness, highlighting the importance of cooperative learning for better learning outcomes. The results of this study provide a reference for elementary English teachers to incorporate online platforms in their teaching practices. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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