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12th International Conference on Cyber and IT Service Management, CITSM 2024

作者： Malik Matin, Iik Muhamad Yulianti, Susana Dwi Cahyani, Rifka Nur Sulthanah, Nisrina Tsany Kadarwati, Dinda Marcheta, Noorlela Computer and Informatics Engineering Politeknik Negeri Jakarta Depok Indonesia

ISBN: (纸本)9798331528799

Motorcycles are one of the most flexible means of transportation, especially in urban areas. Motorcycles are prone to theft. This is because access to ignition is easier than other vehicles such as cars. For this reason, a motorcycle security system was developed that has two main systems, namely a tracking system (vehicle tracker) and a keyless ignition system using a LoRa-based Smart SIM (e-driver License) card. The results of functionality and integration tests show that the entire system can be interconnected and work according to the system plan. Performance testing shows that the GPS module performs better when in open space conditions. The average time required by the system to start the vehicle using Smart SIM is 2.83 seconds, start the engine for 6.46 seconds, and turn off the vehicle for 5.18 seconds. The vibration sensor has a presentation error rate of 28% in detecting vibrations. The LoRa module has a greater transmission range in LOS (Line of Sight) conditions. © 2024 IEEE.

关键词： Motorcycles

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A Procedure with MySQL Python for Developing Data Warehouse and Analytics Using Data from a Greek Soft Drinks Company

A Procedure with MySQL Python for Developing Data Warehouse ...

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2024 International Conference on Applied Mathematics and computer Science, ICAMCS 2024

作者： Tsakiridis, Sotirios Tsimpiris, Alkiviadis Angeioplastis, Athanasios Papaioannou, Nikolaos Mastorocostas, Paris Varsamis, Dimitrios International Hellenic University Dept. Computer Informatics and Telecommunications Engineering Serres Greece University of West Attica Dept. Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798350363807

The research focuses on the process of creating a data warehouse to meet the decision-making needs of a Greek beverage company. The data cover the period from 2018 to 2022. The developed data warehouse schema follows the star schema, with one fact table and five-dimension tables. Based on this structure, a web application was developed in PHP, which displays reports, charts, and analyses on the company's performance through interactive queries. Additionally, prediction functions tailored to the company's data were developed in Python. The process followed, the queries for creating the data warehouse, as well as the commands for creating analyses and predictions, serve as a useful guide for other companies that wish to upgrade the capabilities of their ERP systems. © 2024 IEEE.

关键词： Data warehouses

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Designing a skilled soccer team for RoboCup: exploring skill-set-primitives through reinforcement learning

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Neural Computing and Applications 2025年 1-36页

作者： Abreu, Miguel Reis, Luís Paulo Lau, Nuno LIACC/LASI/FEUP Artificial Intelligence and Computer Science Laboratory Faculty of Engineering University of Porto Porto Portugal IEETA/LASI/DETI Institute of Electronics and Informatics Engineering of Aveiro Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal

The RoboCup 3D soccer simulation league serves as a competitive platform for showcasing innovation in autonomous humanoid robot agents through simulated soccer matches. Our team, FC Portugal, developed a new codebase from scratch in Python after RoboCup 2021. The team’s performance relies on a set of skills centered around novel unifying primitives and a custom, symmetry-extended version of the proximal policy optimization algorithm. Our methods have been thoroughly tested in official RoboCup matches, where FC Portugal has won the last two main competitions, in 2022 and 2023. This paper presents our training framework, as well as a timeline of skills developed using our skill-set-primitives, which considerably improve the sample efficiency and stability of skills, and motivate seamless transitions. We start with a significantly fast Sprint-Kick developed in 2021 and progress to the most recent skill set, including a multi-purpose omnidirectional walk, a dribble with unprecedented ball control, a solid kick, and a push skill. The push addresses low-level collision scenarios and high-level strategies to increase ball possession. We address the resource-intensive nature of this task through an innovative multi-agent learning approach. Finally, we release the team’s codebase to the RoboCup community, providing other teams with a robust and modern foundation upon which they can build new features. © The Author(s) 2025.

关键词： Reinforcement learning

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An Empirical Study of Unanswered Python-Related Questions on Stack Overflow

An Empirical Study of Unanswered Python-Related Questions on...

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2024 International Conference on Information Technology Research and Innovation, ICITRI 2024

作者： Nugroho, Yusuf Sulistyo Halim, Salsabil Aisyah Abdul Islam, Syful Kurniawan, Yogiek Indra Erlina, Tati Universitas Muhammadiyah Surakarta Informatics Engineering Faculty of Communication and Informatics Surakarta Indonesia BSMRSTU Computer Science and Engineering Faculty of Engineering Gopalganj Bangladesh Universitas Jenderal Soedirman Informatics Engineering Faculty of Engineering Purwokerto Indonesia Universitas Andalas Computer Engineering Faculty of Information Technology Padang Indonesia

ISBN: (纸本)9798350376210

As a high-level programming language, Python supports user-friendly coding and system integration. It is not only used for data analytics but is also applied in software development. Although it has several benefits, users have various issues while running Python code. When programmers face issues, they often use Stack Overflow (SO) to get assistance for their problems. However, many Pythonrelated questions on SO are not responded to and remain unanswered. Thus, in this paper, we analyzed these unanswered questions to identify potential weaknesses of user and discussion characteristics. We applied a mixed-methods approach, including quantitative and qualitative analysis of user reputation, question types, and discussion topics. Our analysis shows that unanswered questions are mostly from low-reputation users (72.52%), followed by mid-reputation users (17.93%), and high-reputation users (9.5 5%). The distribution of the unanswered question types shows that low-reputation users ask more 'how' type of question (38.90%) followed by mid and high-reputation users. In contrast, the 'what' and 'why' questions are mostly posted by high-reputation users, followed by mid and low-reputation users. Our word-cloud analysis suggests a correlation between user reputation and the question topics. We acknowledge that there are limitations in our study, include potential misclassifications due to the time of posting and biases in manual labeling, which may affect the accuracy of our findings. This study provides insights into unanswered questions posted by the community, open up potential areas for future work such as improving support mechanisms and community engagement. © 2024 IEEE.

关键词： Python

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Predicting Student Academic Performance Using an Optimised Regression Machine Learning Model 9

Predicting Student Academic Performance Using an Optimised R...

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9th IEEE International Conference on Adaptive Science and Technology, ICAST 2024

作者： Martey, Ezekiel Mensah Abdullah, Abubakar Appiah, Obed Department of Computer Science and Engineering Tarkwa Ghana Department of Computer Science and Informatics Sunyani Ghana

ISBN: (纸本)9798350385403

Machine learning has emerged as one transformative tool in predicting student academic performance. This study evaluates machine learning models regression in predicting student academic performance. It can be found optimised Support Vector Regression (SVR) model accurately predicts student academic performance using a benchmark dataset from Kaggle. The approach incorporated Recursive Feature Elimination (RFE) for optimal feature selection while key parameters of the SVR model are tuned through grid search optimisation to enhance model performance. The optimised SVR model achieves exceptional predictive accuracy with an R-squared value of 0.97, Mean Absolute Error of 2.98, Mean Squared Error of 13.28, Root Mean Squared Error of 3.64, Median Absolute Error of 2.65, and Mean Absolute Percentage Error of 0.23. Comparative analysis demonstrates the superior performance of optimised SVR model against Decision Tree, Random Forest, K-Nearest Neighbors, Bayesian Ridge, and Gradient Boosting models. Experimental results demonstrate the validity of robustness and reliability of our approach, offering valuable insights for educational institutions to develop targeted interventions and support systems. © 2024 IEEE.

关键词： Educational Data Mining Grid Search Optimization Machine Learning Recursive Feature Elimination Student Performance Prediction

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CBIR framework for Diagnosing COVID 19 in Chest X-Ray Images using Deep learning by integrating Photometric Data Augmentation 9

CBIR framework for Diagnosing COVID 19 in Chest X-Ray Images...

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9th IEEE International Conference on Adaptive Science and Technology, ICAST 2024

作者： Martey, Ezekiel Mensah Appiah, Obed Sitti, Mensah Nusetor, Foster Delali Department of Computer Science and Engineering Tarkwa Ghana Department of Computer Science and Informatics Sunyani Ghana

ISBN: (纸本)9798350385403

computer-Aided Diagnostic (CAD) systems enhance clinical decision-making, providing more accurate and streamlined processes. CAD systems based on Content-Based Image Retrieval (CBIR) serve as visual tools that strengthen the reliability of clinical decisions. While deep learning-based CAD systems have shown significant progress in extracting insights from X-rays and medical images, they often struggle due to their reliance on large datasets and high computational demands. These challenges are particularly acute in the medical domain, where datasets are frequently limited and imbalanced. This paper presents a framework for diagnosing COVID-19 from X-ray images, combining deep learning with photometric data augmentation. The proposed approach focuses on two core tasks: image retrieval and classification, which depend on robust feature representation. Using Euclidean distance measures, we utilise a modified EfficientNet-B3 model for feature extraction and examine the effects of transfer learning and fine-tuning on retrieval and diagnostic accuracy. Evaluating binary and multiclass datasets reveals that the proposed method performs strongly in classification tasks, with notable effectiveness in binary and multiclass scenarios. Compared to state-of-the-art techniques, our approach demonstrates superior accuracy for binary classification of X-ray images, outperforming most existing models. © 2024 IEEE.

关键词： COVID-19

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Attention-optimized vision-enhanced prompt learning for few-shot multi-modal sentiment analysis

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Neural Computing and Applications 2024年第33期36卷 21091-21105页

作者： Zhou, Zikai Qiao, Baiyou Feng, Haisong Han, Donghong Wu, Gang School of Computer Science and Engineering Northeastern University Shenyang110819 China School of Informatics Xiamen University Xiamen361105 China

To fulfill the explosion of multi-modal data, multi-modal sentiment analysis (MSA) emerged and attracted widespread attention. Unfortunately, conventional multi-modal research relies on large-scale datasets. On the one hand, collecting and annotating large-scale datasets is challenging and resource-intensive. On the other hand, the training on large-scale datasets also increases the research cost. However, the few-shot MSA (FMSA), which is proposed recently, requires only few samples for training. Therefore, in comparison, it is more practical and realistic. There have been approaches to investigating the prompt-based method in the field of FMSA, but they have not sufficiently considered or leveraged the information specificity of visual modality. Thus, we propose a vision-enhanced prompt-based model based on graph structure to better utilize vision information for fusion and collaboration in encoding and optimizing prompt representations. Specifically, we first design an aggregation-based multi-modal attention module. Then, based on this module and the biaffine attention, we construct a syntax–semantic dual-channel graph convolutional network to optimize the encoding of learnable prompts by understanding the vision-enhanced information in semantic and syntactic knowledge. Finally, we propose a collaboration-based optimization module based on the collaborative attention mechanism, which employs visual information to collaboratively optimize prompt representations. Extensive experiments conducted on both coarse-grained and fine-grained MSA datasets have demonstrated that our model significantly outperforms the baseline models. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Semantics

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Concentric Blocking Techniques for Improved Feature Extraction in Local Binary Pattern (LBP) Systems 9

Concentric Blocking Techniques for Improved Feature Extracti...

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9th IEEE International Conference on Adaptive Science and Technology, ICAST 2024

作者： Appiah, Obed Martey, Ezekiel Mensah Department of Computer Science and Informatics Sunyani Ghana Department of Computer Science and Engineering Tarkwa Ghana

ISBN: (纸本)9798350385403

The domain of image analysis has seen rapid advancements, particularly feature extraction techniques, driven by the increasing demand for accurate and efficient results. Among these advancements, Local Binary Patterns (LBP) have gained prominence due to their simplicity and computational efficiency. However, traditional LBP methods often need help with image orientation and scale variations, common in real-world scenarios. To address these challenges, this study explores the potential of concentric blocking methods as an alternative to conventional grid-based blocking techniques. Concentric blocking, which organizes image data into circular or spiral patterns, is hypothesized to enhance the robustness and accuracy of LBP-based systems by better accommodating geometric transformations. The study uses multiple LBP variants to compare traditional grid-based blocking with concentric blocking techniques across various image analysis tasks, including face recognition and texture classification. Experimental results demonstrate that the proposed ring-centric technique significantly outperforms traditional methods in precision and computational efficiency. Precision values for the proposed Ring Centric technique reach up to 90.73% for the basic LBP and 88.47% for Neighboring LBP with Distance (NLBPD), indicating its superior performance in handling variations in orientation and scale. Additionally, the technique demonstrates lower running times, making it a highly efficient and accurate choice for image retrieval tasks. This study highlights the importance of image-blocking strategies in enhancing the performance of LBP-based systems and underscores the potential of concentric blocking methods in overcoming the limitations of traditional approaches. The findings contribute to developing more resilient and efficient image analysis systems, with significant implications for applications in computer vision, medical diagnostics, and security systems. © 2024 IEEE.

关键词： Local binary pattern

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A Personalized Fitness Application for Injury Rehabilitation Using Artificial Neural Networks 19

A Personalized Fitness Application for Injury Rehabilitation...

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19th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2024

作者： Kalofonos, Nikolaos Troussas, Christos Krouska, Akrivi Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798331504502

This paper presents a personalized fitness mobile application with the use of Artificial Intelligence (AI), namely Artificial Neural Networks (ANN), which contributes to injury rehabilitation. It automatically generates customized workout plans on a weekly basis, taking into consideration user-supplied data on issues such as injury type, fitness level, body mass index, and available equipment. The system continuously updates the workout plans with the help of feedback provided by the user to achieve the best recovery process. Built with React Native for the frontend and Django for the backend, this application guarantees access anytime, anywhere, with smooth data treatment. The paper further reflects on the general implications of using AI in e-fitness, stresses intuitive user interfaces, and furthers possibilities such technologies could undergo. © 2024 IEEE.

关键词： Electronic health record

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An Ethereum Based e-Voting System 16th

An Ethereum Based e-Voting System

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16th EAI International Conference on Wireless Internet, WiCON 2023

作者： Spanos, Achilleas Kantzavelou, Ioanna Department of Informatics and Computer Engineering University of West Attica Athens Greece

ISBN: (纸本)9783031580529

Developing an electronic voting system that would replace the old, traditional electing procedures has been a concern of many researchers for years. Blockchain technology could provide some guarantees for voting platforms, such as transparency, immutability, and confidentiality. In most research works, secure and reliable electronic voting systems are required to address known security, anonymity, and fraud issues. This paper presents a secure decentralized electronic voting system, named the EtherVote, which is based on the Ethereum Blockchain network focusing on eligible citizens’ identification. The EtherVote is a serverless e-voting model, thus improving security, privacy, and election costs. An effective method for voter registration and identification to enhance security is proposed. Among the main properties the EtherVote holds are storing encrypted votes, efficiency in handling elections with numerous participants, and simplicity. The system is tested and evaluated, vulnerabilities and possible attacks are exposed, and a discussion examines opportunities for enhancing the proposed e-voting system. © ICST Institute for computer Sciences, Social informatics and Telecommunications engineering 2024.

关键词： Smart contract

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