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International Conference on Mechatronics (ICOM)

作者： Abdulkadir Tasdelen Mohamed Hadi Habaebi Md Rafiqul Islam Dept. of Software Engineering Faculty of Engineering and Natural Sciences Ankara Yildirim Beyazit University Ankara Türkiye Faculty of Engineering IIUM Malaysia Dept. of Electrical and Computer Engineering Faculty of Engineering International Islamic University Malaysia Kuala Lumpur Malaysia

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

Blockchain technologies and cryptocurrencies have garnered significant attention for their potential to revolutionize various industries. This paper investigates the landscape of blockchain technologies in the context of cryptocurrencies, focusing on performance metrics, trade-offs, trends, and underlying issues. Through comprehensive analysis, the most utilized consensus mechanisms among the top cryptocurrencies are identified. The distribution of top mining pools by hash rate over the last two years reveals dominance by a few major pools, with implications for decentralization and security. In Bitcoin mining pool distribution, trends indicate the dominance of established pools like Foundry USA Pool and AntPool, alongside notable growth from smaller pools like MARA Pool and Luxor. Comparative analysis across different cryptocurrencies highlights variations in hashing rate, block production, and energy consumption, underscoring the complex dynamics of blockchain mining. Moreover, the comparative analysis of energy consumption in blockchain mining hardware reveals insights into energy efficiency and sustainability. Smaller mining pools demonstrate significant growth and momentum, contributing to the diversification and decentralization of mining operations.

关键词： Measurement Industries Energy consumption Mechatronics Production Market research Hardware

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Classifying Psychiatric Patients Using Machine Learning 25

Classifying Psychiatric Patients Using Machine Learning

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Alrjoob, Hmmam M. Alazaidah, Raed Batyha, Radwan Khafajeh, Hayel Elsoud, Esraa Abu Saeb Al-Sherideh, Ala'a Elrashidi, Ali Alqaraleh, Muhyeeddin Amer, Waleed Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan Zarqa University Faculty of Information Technology Department of Data Science and Ai Zarqa Jordan Applied Science Private University Faculty of Information Technology Department of Computer Science Amman Jordan Zarqa University Faculty of Information Technology Department Computer Science Zarqa Jordan Zarqa University Faculty of Information Technology Department of Cyper Security Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia Zarqa University Faculty of Information Technology Department of Software Engineering Zarqa Jordan Zarqa University Faculty on Information Technology Department of Cyber Security Zarqa Jordan

ISBN: (纸本)9798331540012

Psychological disorders are considered chronic illnesses that affect a wide range of populations. Some studies in the United States indicate that one in every eight individuals is affected by a psychological disorder. Additionally, individuals with a psychological disorder often have an impact on the nature of the lives of those around them. It is beneficial to detect the illness in its early stages to increase the likelihood of recovery. In this research, thirteen classification algorithms are used. Each algorithm has an interesting approach. It can be used to analyze several datasets where three datasets specific to Psychiatric patients were selected. The datasets have been chosen from UCI Machine Learning Repository. The datasets were re-analyzed after only 50% of the characteristics were approved after being evaluated by the several feature selection techniques. The main objective of this research is to find the best classifier and feature selection strategy in analyzing datasets of Psychiatric patients. After conducting numerous comparisons, it became evident that, the best classifier for the Autism-Adult-Data dataset are Bagging and Random Forest. As for the best learning strategy, it was found to be Functions and Trees, the best feature selection was obtained using Symmetrical Uncourt Attribute Evaluation. Both IBK and KStar classifier proved to be the best classifier for the Parkinson's dataset, Lazy demonstrated to be the most effective learning strategy, Correlation Attribute Evaluation technique yielded the best feature selection. Logistic emerged as the best classifier for planning-relax dataset, the best learning strategy was Bayes, the best feature selection was found to be Symmetrical Uncert Feature Selection. © 2024 IEEE.

关键词： Contrastive Learning

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Virtual Laboratory Learning Experience in engineering: An Extended Technology Acceptance Model (TAM) 3

Virtual Laboratory Learning Experience in Engineering: An Ex...

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3rd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2023

作者： Ahmed Alnagrat, Ahmed Jamah Ahmed, Khamiss M. S. Alkhallas, Muhannad Ismail Almakhzoom, Osama Abulaqasim Ibrahim Syed Idrus, Syed Zulkarnain Che Ismail, Rizalafande Higher Institute of Science and Technology Wadi Al-Shati Department of Computer Science and Information Technology Wadi al-Shati Fezzan Libya Sebha University Faculty of Information Technology Department of Computer Science Sebha Libya Faculty of Engineering Technology in Zuwarah Department of Software Engineering Zuwarah Libya Department of Communication Perlis Kangar01000 Malaysia Arau02600 Malaysia

ISBN: (纸本)9798350319897

This research presents an enhanced version of the Technology Acceptance Model (TAM), which integrates usability and learning objectives to evaluate the effect of adopting virtual laboratories on student performance. Data from 97 participants, gathered via a survey, was used to examine the correlation between perceived usefulness (PU), perceived ease of use (PEOU), and intention to use (IU) concerning their experiences and outcomes with a simulation-based virtual laboratory. A custom questionnaire was designed to assess TAM components, namely PU, PEOU, and IU, specifically in the context of virtual laboratory learning environments. Findings indicate that the integration of specific laboratory learning objectives fosters the creation of a more credible and authentic simulation tool. This, in turn, optimizes the learning process and enhances students' learning outcomes. The refined TAM model provides valuable insights into the determinants of user acceptance of virtual laboratories and offers practical guidance for educators and instructional designers to construct more effective and efficient virtual laboratory environments in educational contexts. © 2023 IEEE.

关键词： Virtual reality

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Characterizing Discussion Trend on Blockchain Development by Mining Stack Overflow

SSRN

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SSRN 2023年

作者： Ze, Xue Zhao, Tianyu Hao, Isabella Wei, Lili Department of Electrical and Computer Engineering Faculty of Engineering McGill University MontrealQC Canada Department of Software Engineering Faculty of Engineering McGill University MontrealQC Canada

Context: The importance of blockchain knowledge is becoming more apparent as the technology continues to grow and expand. With the increasing interest in web3-related technology and the hype of the metaverse, more people are seeking to understand blockchain and its potential applications. Thus, characterizing blockchain-related concerns on Stack Overflow, one of the most popular question-and-answer (Q&A) sites for programmers, is important for the concerned software development. Several research projects have explored the technological obstacles confronted by users. However, there is no existing study that analyzes the trend and change in blockchain-related discussions over the years. There is also a paucity of information on the community itself, the Stack Overflow users, and the important topics to ***: In this study, we investigated the developers' concerns associated with blockchain development by leveraging the Latent Dirichlet Allocation (LDA) technique. We also characterized the changing trend of blockchain discussions over the ***: We first collected 6,340 blockchain-related questions from Stack Overflow. Leveraging LDA, we discerned the most relevant topics and prevalent challenges encountered by blockchain developers. Subsequently, we depicted these findings using pie charts and embarked on a manual analysis to elucidate the trends in topic changes over the ***: The findings of our investigation reveal a predilection among users to post topics closely associated with "Hyperledger Fabric", "Blockchain Mechanism", and "Smart Contract". Notably, a pronounced surge in user engagement and the proliferation of discussions have been observed from 2018 to ***: Utilizing the LDA methodology, we have discerned a transformation in the scope of blockchain-related topics under discussion by users on Stack Overflow (SO) over the course of the year. Furthermore, our analysis has shed light on the evolving trends and the array o

关键词： Smart contract

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Automating the Diagnosis of Cucumber Plant Diseases Using Machine Learning 25

Automating the Diagnosis of Cucumber Plant Diseases Using Ma...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Banimustafa, Ahmed Qattouz, Hazem Almatarneh, Sattam Mansour, Khalid Alazaidah, Raed Bulkrock, Olla Higher Colleges of Technology Computer Information Science Dept Abu Dhabi United Arab Emirates Princess Sumaya University for Technology Software Engineering Dept Amman Jordan Zarqa University Data Science & Artificial Intelligence Dept Zarqa Jordan University of Business and Technology College of Engineering Jeddah Saudi Arabia Arab-Open University Bahrain Faculty of Computer Studies Bahrain

ISBN: (纸本)9798331540012

Farmers all over the world struggle to fight plant diseases. However, the incorrect use of pesticides can waste time, effort, and money and can also be very harmful to the environment and human health. In this work, we present an empirical study that involves identifying two pathogens related to Cucumbers plant diseases: Powdery Mildew and Alternaria Cucumerina. The study aims to develop a computer-based solution based on deep learning and machine learning algorithms to detect these diseases. To achieve this, a dataset of hundreds of samples was collected from ordinary farms in Beqaa, an agricultural region 15 KM north of Amman, Jordan. Three machine learning models were created in this study using Support Vector Machines (SVM), Logistic Regression (LR), and Multi-layer perceptron algorithms. The constructed models were applied to the dataset after embedding the dataset images using the Convolutional Neural Networks (CNN) InceptionV3 pre-trained model. The model was tested and evaluated using cross-evaluation and F1-Score, CA, AUC, Precision, Recall, and Specificity, which all showed excellent results, particularly using the SVM algorithm. The constructed methods are intended to be deployed to farms in their field condition environments using a CCTV system that can capture images of plants during growth, which can help identify plant diseases at that right stage, which would save time, effort, and money and reduce the impact of wrong and overuse of pesticides on consumers and the environment. © 2024 IEEE.

关键词： Convolutional neural networks

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SmartCoach: Comprehensive Tutor Recommender and Student Attentiveness Measuring Platform 3

SmartCoach: Comprehensive Tutor Recommender and Student Atte...

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Samarasekara, H.D.K. Hansaka, H.M.P. Rajapaksha, S.D.D. Tharaka, W.A.D.G. Manathunga, Kalpani Sriyarathna, Disni Charuka Faculty of Computing Department of Computer Science and Software Engineering Sri Lanka

ISBN: (纸本)9781665408622

With the pandemic, coaching or tutoring classes became to halt as the underlying system wasn't facilitating to adapt to emergency teaching mechanisms due to sparse of relevant technologies and tutor unawareness. SmartCoach is an integrated platform that allows students to find suitable tutors based on recommendations and other parameters like proximity, previous track record etc. using sentiment analysis and natural language processing. For tutors, SmartCoach allows publishing learning materials, automatic quiz creation, tracking attendance and, attentiveness during classes using OpenCV library. Moreover tutors get a dashboard featuring critical aspects about their classes and, personal income. This research is aimed to introduce a comprehensive distance learning platform with novel technological approaches that connect both potential students and tutors to a common platform. © 2021 IEEE.

关键词： Sentiment analysis

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A Systematic Survey on Mobile Internet of Things Security 14

A Systematic Survey on Mobile Internet of Things Security

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14th International Conference on Information Security and Cryptology, ISCTURKEY 2021

作者： Arat, Ferhat Akleylek, Sedat Samsun University Engineering Faculty Department of Software Engineering Samsun Turkey Ondokuz Mayis University Engineering Faculty Department of Computer Engineering Samsun Turkey

ISBN: (纸本)9781665407762

With its applicability and scope, IoT technology plays a role in facilitating daily life. Human independent interactions are become obligatory by technological innovations and connectivity. Mobile IoT represents the network structure created by customized smart devices with customized applications and personalized structure. Remote and simple management of industrial control systems and organizations in many different fields are became easier with M-IoT devices and network structure. M-IoT applications have emerged in all areas from smart home systems to health systems and remote access. Since M-IoT applications are characterized as the development and evolution of IoT networks, it inherits on the security issues and challenges of IoT networks. The fact that security and privacy solutions in traditional computer networks cannot be used in M-IoT networks and applications on account of many reasons, highlights the need for security solutions in this field. In this paper, we present an overview of M-IoT networks. M-IoT structure and application layer protocols are analyzed. Security challenges and vulnerabilities in M-IoT application layer and applications are emphasized. In addition, the application layer is examined and the security attacks are summarized. Furthermore, list of open problems in the literature are listed. © 2021 IEEE.

关键词： Internet of things

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Comparison of Standard Ant Colony Optimization, Dijkstra and A* Algorithms for Path Planning of Robot in an Indoor Environment

Comparison of Standard Ant Colony Optimization, Dijkstra and...

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Mechanical engineering and Robotics Research (ICMERR), International Conference on

作者： Sudeep Sharan Anh Tong Ngoc Minh Juan José Domínguez-Jiménez Peter Nauth Faculty of Computer Science and Engineering Frankfurt University of Applied Sciences Frankfurt am Main Germany UCASE Software Engineering Group School of Engineering University of Cádiz Cadiz Spain

ISBN: (数字)9798331509262

ISBN: (纸本)9798331509279

The research topic of Path planning is extremely challenging area of concentration within the field of mobile robots. However, path planning algorithms for mobile robot tasks are contingent upon the environment and its level of complexity. This paper analyzes four distinct path planning methods for simulated indoor environment. The proposed algorithms include conventional Ant Colony methods, Ant System (AS), Ant Colony System (ACS), as well as standard methods Dijkstra and AStar (A*). We analyzed and examined these algorithms by employing various metrics/maps with complexity. The results indicate that the traditional path planning algorithm Dijkstra and A* approaches surpass the other ant colony techniques in terms of both computation time and path distance.

关键词： Ant colony optimization Heuristic algorithms Stars Path planning Real-time systems Indoor environment Complexity theory Mobile robots Standards Testing

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Periodicity Analysis of Most Time Series Methods: A Review 8

Periodicity Analysis of Most Time Series Methods: A Review

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Yousif, Muneera Mohammed, Musab Ahmed Celik, Mete Hamdoon, Asmaa E. Jassim, Riham Abdullah, Noor M. College of Information Technology Ninevah University Software Department Mosul Iraq College of Education for Humanities Sciences Kirkuk University Kirkuk Iraq Erciyes University Computer Engineering Department Engineering Faculty Kayseri Turkey Water Resources Studies Center for Northern Region Projects Ministry of Water Resources of Iraq Mosul Iraq

ISBN: (纸本)9798350354423

One of the most important methods of predicting the future is through past events and data repeated over time, as time series are those data indexed using time sequentially on data points distributed according to time, and periodic time series analysis is the analysis of a series of recorded measurements of a phenomenon that are repeated more than once during specific times periods. Periodicity detection has an impact on many areas in the world, such as climate, motion, education et cetera. It is important to consider in solving problems, moreover, there are many data sets in the world, the most prominent of which is time series data, and this type of data is constantly increasing. In the study, several data periodicity analysis methods (such as autocorrelation, wavelet transform, DTW, RNN, LSTM) were inspected. © 2024 IEEE.

关键词： Autocorrelation

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AI-Based Assistant for Determining the Required Performance Level for a Safety Function 48

AI-Based Assistant for Determining the Required Performance ...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Iyenghar, Padma Hu, Yuxia Kieviet, Michael Pulvermueller, Elke Wuebbelmann, Juergen Innotec GmbH Erlenweg 12 Melle49324 Germany Osnabrueck University of Applied Sciences Faculty of Engineering and Computer Science Germany University of Osnabrueck Software Engineering Research Group Germany

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Standards such as ISO 13849 and ISO 12100 enable users to model safety related control elements with safety functions, according to a specified architecture and required performance level. In this direction, a novel Artificial Intelligence (AI)-based assistant is introduced in this paper to aid in determining the required performance level parameter by indulging the user in a dialog-based conversation regarding hazard scenarios. This will help inexperienced machinery safety personnel (e.g. mechanical engineer) to get an overview of the safety engineering aspects, before consulting with safety experts for risk assessment. © 2022 IEEE.

关键词： Artificial intelligence

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