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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Spranger, Kurt T. Grimaila, Michael R. Hodson, Douglas D. Air Force Institute of Technology Dept. of Systems Engineering and Mgmt. Wright-Patterson AFBOH United States Air Force Institute of Technology Dept. of Electrical & Computer Engineering Wright-Patterson AFBOH United States

ISBN: (纸本)9798350327595

Decomposing a complex system into smaller abstract functional blocks and developing mathematical models to represent their behavior is an important activity towards developing comprehensive system understanding. In this paper, we decompose the ideal Quantum Teleportation protocol into a collection of simple quantum circuit blocks, examine the behavior of each block, and show how collections of blocks operate to create more complex circuits. We believe this approach greatly simplifies the understanding of how the Quantum Teleportation protocol works. This paper is introductory in nature and is intended to help those who are new to modeling, simulating, and analyzing ideal quantum circuits. © 2023 IEEE.

关键词： Bell State Generation (BSG) Bell State Measurement (BSM) Einstein Podolsky Rosen (EPR) pairs quantum entanglement quantum teleportation superdense coding

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Using LLMs for Annotation and ML Methods for Comparative Analysis of Large-Scale Turkish Sentiment Datasets

Using LLMs for Annotation and ML Methods for Comparative Ana...

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International Conference on computer Science and engineering (UBMK)

作者： Ercan Ezin Rukiye Savran Kiziltepe Murat Karakus Dept. of Computer Engineering Harran University Şanlıurfa Türkiye Dept. of Software Engineering Karadeniz Tech. University Trabzon Türkiye Dept. of Software Engineering Ankara University Ankara Türkiye

ISBN: (数字)9798350365887

ISBN: (纸本)9798350365894

With the increasing prevalence of e-commerce plat-forms, understanding customer sentiments expressed in product reviews is crucial for assessing platform and product performance. However, traditional sentiment analysis (SA) models often struggle with low-resource languages such as Turkish, particularly due to the language's agglutinative nature and morphological complexity. To address this, several public datasets are now available online. However, these datasets are often annotated using rule-based methods, resulting in poor accuracy for Machine Learning (ML) models. This study addresses these challenges by employing two large Turkish datasets, TRSAv1 and VSCR, and improving their sentiment annotations through advanced Large Language Models (LLMs) such as ChatGPT4o-mini. The reannotation significantly enhanced the performance of traditional ML models-Logistic Regression, Naive Bayes, Random Forest, and Support Vector Machine-especially in the neutral and negative sentiment classes, as evidenced by increased precision, recall, and F1-scores. The findings underscore the importance of thorough data preparation and demonstrate that utilizing LLMs for sentiment annotation in Turkish can lead to more reliable SA, providing a stronger foundation for developing advanced SA tailored to low-resource languages. This study is the first to employ recent LLM for relabelling Turkish customer reviews, highlighting the potential for improved accuracy in SA for low-resource languages.

关键词： Analytical models Accuracy Systematics Annotations Reviews Computational modeling Transfer learning Transformers Vectors Electronic commerce

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SafeEmbodAI: a Safety Framework for Mobile Robots in Embodied AI systems

arXiv

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arXiv 2024年

作者： Zhang, Wenxiao Kong, Xiangrui Braunl, Thomas Hong, Jin B. Dept. of Computer Science and Software Engineering The University of Western Australia Perth Australia Dept. of Electrical Electronic and Computer Engineering The University of Western Australia Perth Australia

Embodied AI systems, including AI-powered robots that autonomously interact with the physical world, stand to be significantly advanced by Large Language Models (LLMs), which enable robots to better understand complex language commands and perform advanced tasks with enhanced comprehension and adaptability, highlighting their potential to improve embodied AI capabilities. However, this advancement also introduces safety challenges, particularly in robotic navigation tasks. Improper safety management can lead to failures in complex environments and make the system vulnerable to malicious command injections, resulting in unsafe behaviours such as detours or collisions. To address these issues, we propose SafeEmbodAI, a safety framework for integrating mobile robots into embodied AI systems. SafeEmbodAI incorporates secure prompting, state management, and safety validation mechanisms to secure and assist LLMs in reasoning through multi-modal data and validating responses. We designed a metric to evaluate mission-oriented exploration, and evaluations in simulated environments demonstrate that our framework effectively mitigates threats from malicious commands and improves performance in various environment settings, ensuring the safety of embodied AI systems. Notably, In complex environments with mixed obstacles, our method demonstrates a significant performance increase of 267% compared to the baseline in attack scenarios, highlighting its robustness in challenging conditions. © 2024, CC BY.

关键词： Mobile robots

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Development of an Ontology for Bulgarian Soil Types

Development of an Ontology for Bulgarian Soil Types

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Stoyanova-Doycheva, Asya Madanska, Sebiha Bilyanov, Sheban University of Plovdiv 'Paisii Hilendarski' Dept. of Computer Systems Plovdiv Bulgaria Iict Bulgarian Academy of Sciences Sofia Bulgaria University of Architecture Civil Engineering and Geodesy Dept. of Residential Buildings Sofia Bulgaria

ISBN: (纸本)9798350312911

The article presents the development of an ontology for the Taxonomic List of Soils in Bulgaria (according to the FAO World System). In addition to soil types, the ontology includes knowledge about the different agro-climatic regions in Bulgaria that are suitable for cultivating various agricultural crops. The ontology is part of the knowledge base of the ZEMELA platform for smart agriculture. © 2023 IEEE.

关键词： Soils

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Energy-Aware Trajectory Design for UAV-mounted Full-duplex Relays 35

Energy-Aware Trajectory Design for UAV-mounted Full-duplex R...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Tyrovolas, Dimitrios Mitsiou, Nikos Boufikos, Thomas Tegos, Sotiris Mekikis, Prodromos-Vasileios Diamantoulakis, Panagiotis Ioannidis, Sotiris Liaskos, Christos Karagiannidis, George Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki54124 Greece Technical University of Crete Dept. of Electrical and Computer Engineering Chania Greece Hilti Corporation Feldkircher Strasse 100 Schaan9494 Liechtenstein University of Ioannina Computer Science Engineering Department Ioannina Greece Artificial Intelligence & Cyber Systems Research Center Lebanon

ISBN: (纸本)9798350362244

Unmanned aerial vehicles (UAVs) equipped with full-duplex relays (FDRs) are pivotal in overcoming connectivity challenges by dynamically establishing effective communication channels. However, despite their potential in network performance via trajectory optimization, integrating energy consumption models for UAV-mounted FDRs remains unexplored, crucial for trajectory design adhering to existing energy constraints. To this end, we introduce an energy-aware trajectory optimization framework to maximize network performance and user fairness within the UAV's energy constraints. Specifically, we present a detailed energy consumption model describing the operational needs of UAV-mounted FDRs and formulate a joint time-division multiple access (TDMA) user scheduling-UAV trajectory optimization problem considering the power dynamics of UAV-mounted FDRs. Finally, our simulation results highlight the role of energy awareness in achieving optimal trajectory and scheduling, contributing to UAV-mounted FDRs' performance in future networks. © 2024 IEEE.

关键词： Time division multiple access

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Holistic understanding of digital transformation of health care system as a point-of-departure for system requirements specification

Holistic understanding of digital transformation of health c...

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2024 Ongoing Research, Practitioners, Posters, Workshops, and Projects of the International Conference EGOV-CeDEM-ePart, EGOV-CeDEM-ePart-Ongoing 2024

作者： Karunaratne, Thashmee Ayele, Workneh Larsson, Aron Assom, Luigi Züniga, Gisele Dept. of Computer and Systems Sciences Stockholm University Kista 164 40 Sweden School of Industrial Engineering and Management Royal Institute of Technology/KTH Stockholm100 44 Sweden Dept. of Communication Quality Management and Information Systems Mid Sweden University Sundsvall851 70 Sweden Actadig Stockholm Sweden

The challenges regarding harmonised interoperable e-health services are enormous due to the complexity of the domain, comparatively high demands of privacy and security, implications of storing, sharing, and managing health data as well as unclear definitions and standards for patient's electronic health records. Therefore, the advantages of digitalisation are yet to reach the end user-patient, especially in the emergent regions where digital infrastructure is limited. The focus is on the north and northeast regions of Brazil, where a holistic understanding of the requirements for a digital transformation of the health care system is explored through the lens of an expert panel using a Delphi methodology, complemented by a comparison with related innovations in the digital health domain. © 2023 Copyright for this paper by its authors.

关键词： Health care

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Enhancing Women's Safety Through Customized Smartphone Sensor Data: A Human Activity Recognition System 9

Enhancing Women's Safety Through Customized Smartphone Senso...

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9th IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2023

作者： Islam, Yamina Nowrin, Sanjida Faqih, Majed Ibrahim Sultana, Fozia Bahadur, Erfanul Hoque Masum, Abdul Kadar International Islamic University Chittagong Dept. of Computer Science and Engineering Chattogram Bangladesh Signal Corps Institute Director of Research and Development Saudi Arabia Hiperdyne Artificial Intelligence Engineer Tokyo Japan Daffodil International University Dept. of Software Engineering Dhaka Bangladesh

ISBN: (纸本)9798350319651

Human activity recognition (HAR) research using smartphone sensor technology has changed people's daily lives and opened the door for numerous exciting applications due to its extensive applications in addressing real-world humancentric issues. These studies, however, mostly concentrated on a woman's daily activities and behaviours when she is attacked, such as running, walking, sleeping, eating, drinking, lying, straight punching, front kicking, and so forth. The article offers a method to foresee human behaviour using a deep learning model and evaluates the efficiency of the approach using real-world data in response to this. We offer an LSTM structure for detecting the intensity of HAR in order to track activity patterns and build a neural network with binary classification skills to evaluate the situation of women. The proposed model uses the dataset to identify human activity, which records 30 volunteers' body movements while they engage in 18 physical activities. Feature engineering is used to extract additional variables from the data in addition to that. Our proposed model achieves a 90.89% accuracy. © 2023 IEEE.

关键词： Smartphones

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Evolution of Metallic Connection Technologies of Busbar in Silicon Solar Cells: Brief Review 15

Evolution of Metallic Connection Technologies of Busbar in S...

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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： Silveira, A.M.C. Neves, M.R.M. Garcia, R. Alvarez, H. Villalva, M.G. Marques, F.C. Kretly, L.C. School of Electrical and Computer Engineering Communications Department - DECOM Campinas Brazil School of Electrical and Computer Engineering Dept. of Systems and Energy - DSE Campinas Brazil Institute of Physics Gleb Wataghin Dept. of Applied Physics - DFA Campinas Brazil Build Your Dreams Company - BYD Dept. Research and Development - R&D Campinas Brazil

ISBN: (纸本)9798350314182

This work consists of presenting a brief review of the evolution of metallic connection technologies in busbars applied to the front and rear of solar cells, thus demonstrating their fundamentals, materials and essential manufacturing processes that impact on improving the energy efficiency of solar modules. In this brief review, one can follow the technical limitations that led to the evolution of metallic connection technologies in busbars over time and their impacts on the photovoltaic market. Contributing to a broad understanding of the resistive components of solar cells that consists of the series resistance parameter. © 2023 IEEE.

关键词： Busbarless Effective Shadow Ribbon Busbar Serie Resistance Solar cell TLM Wire Busbar

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Comparing Emotion Detection Methods in Online Classrooms: YOLO Models, Multimodal LLM, and Human Baseline

Comparing Emotion Detection Methods in Online Classrooms: YO...

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IEEE Education engineering (EDUCON)

作者： Medha Mohan Ambali Parambil Salah Bouktif Munkhjargal Gochoo Fady Alnajjar Dept. Computer Science and Software Engineering United Arab Emirates University Al Ain UAE

ISBN: (数字)9798331539498

ISBN: (纸本)9798331539504

The COVID-19 pandemic has transformed learning environments, challenging educators to understand students' behaviors during the online mode of learning, in particular emotions associated with students' attention during virtual classrooms. As learning transitions between physical and virtual spaces, the ability to interpret student attention and engagement has become complex. In response to this challenge, our research investigates the use of GPT-4o, a multimodal large language model, for identifying student emotions by analyzing images in diverse learning settings. The study involved analyzing online classroom images featuring 149 faces, utilizing three distinct approaches: a computer vision model (YOLO), the multimodal LLM (GPT-4o), and a human-annotated baseline. The analysis systematically categorized facial expressions into eight emotional categories: Happy, Sad, Angry, Neutral, Contempt, Disgust, Fear, and Surprise. The findings indicate that multimodal LLMs can effectively detect student emotions, achieving an average accuracy of 93.8%, which aligns with the human baseline accuracy of 97.0%. In contrast, YOLO models maintained an average accuracy of 81.9%, performing well for basic emotions but struggling with subtle expressions. This research contributes to enhancing educational practices by providing valuable insights regarding the application of multimodal LLMs to assist educators in comprehending student emotions within both physical and digital classroom settings.

关键词： YOLO Emotion recognition Privacy Accuracy Annotations Pandemics Scalability Large language models Real-time systems Faces

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FedDist-POIRec: Federated Distillation for Point-Of-Interest Recommendation in Human Mobility Prediction 4

FedDist-POIRec: Federated Distillation for Point-Of-Interest...

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4th IEEE International Conference on Human-Machine systems, ICHMS 2024

作者： Rezaei, Esmatollah Seyedmohammadi, S. Jamal Abouei, Jamshid Plataniotis, Konstantinos N. Yazd University Dept. Of Electrical Engineering Yazd Iran Concordia University Inst. Of Information Systems Engineering Montreal Canada University Of Toronto Edward S. Rogers Sr. Department Of Electrical And Computer Engineering Toronto Canada

ISBN: (纸本)9798350315790

Next Point-of-Interest (POI) recommendation plays a vital role in human mobility prediction within Location-based Social Networks (LSBN), assisting individuals to decide on their next destination. However, traditional centralized systems rely on large datasets of previous POI check-ins, which raises privacy and computation concerns. In this regard, Federated Learning (FL) has emerged as a promising solution, enabling distributed training of machine learning models while preserving user privacy. In this paper, we propose a novel FL-based POI recommendation system, FedDist-POIRec, that utilizes Federated Distillation (FD) in a semi-synchronous framework to promote privacy, recommendation efficiency, and cope with resource heterogeneity by considering heterogeneous model architectures among users. Additionally, to alleviate the sparsity of user checkin lists, we employ a innovative knowledge aggregation technique, where the knowledge of each user is aggregated with that of users who share similar preferences. Simulation results demonstrate that FedDist-POIRec outperforms the baseline methods in terms of recommendation efficiency and communication cost, while keeping the computation cost at an acceptable level. © 2024 IEEE.

关键词： Distillation

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