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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Ibraheem, Ahmed Salman Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq Department of Computer Technical Engineering Baghdad Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

An advanced hybrid renewable energy collecting and storage system prototype that utilizes water flow as its primary power source. Additionally, the system incorporates an energy monitoring system based on the Internet of Things (IoT) technology. The device effectively harnesses energy from the movement of water, storing it for future use in low-voltage applications. It demonstrates a maximum daily energy capture capacity of about 100Wh. The energy monitoring system, based on the Internet of Things (IoT), enables the real-time and remote monitoring of energy harvesting and usage. We thoroughly assessed the energy harvesting component across different situations to identify the crucial parameters that impact energy output. The results of our study demonstrate that several elements, including the spatial separation 'between the energy harvester and the water source, Water flow' speed, sensor orientation, and sensor density, all play significant roles in determining the quantity of energy collected. This research shows that it is possible to integrate IoT technology with hydropower renewable energy systems. It provides significant perspectives on enhancing energy extraction efficiency in practical scenarios. © 2024 IEEE.

关键词： harvesting renewable energy IoT storage energy water flow energy

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Improving VANET Localization Performance with Data Verification: Challenges and Solutions

Improving VANET Localization Performance with Data Verificat...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Kadhim, Aqeel Kamil Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisa Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

In VANETs, the important and effective applications of vehicle localization include safety and communication applications. Thus, it is difficult to get very accurate localization in the dynamic and often very fluctuating environment of VANET. This research responds to this challenge with a keen thrust on improving vehicle localization using the Mobility Data Verification process. The primary goal of this work is to achieve high accuracy of vehicle positioning within VANET by checking the coherence of mobility data of moving vehicles. Hence, we present a concept that builds upon Mobility Data Verification to provide real-time location details from vehicles. Both GPS and onboard sensors feed this method, which uses a multi-level verification to flag out or eliminate the errors of deliberately spoofed data points. We use simulations to evaluate and validate the effectiveness of the proposed verification approach. As the proposed system, our previously developed and fine-tuned weighted localization (OWL) strategy does so. The performance evaluation results suggest that our proposed solution is feasible to distinguish automobiles that are not trustworthy and improve the performance of the localization algorithm. © 2024 IEEE.

关键词： Vane pumps

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Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning 13th

Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesia...

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13th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2024

作者： Ouyang, Hui Chen, Cheng Tang, Ke Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9783031578076

Dynamic Bayesian Networks (DBNs), renowned for their interpretability, have become increasingly vital in representing complex stochastic processes in various domains such as gene expression analysis, healthcare, and traffic prediction. Structure learning of DBNs from data is a challenging endeavor, particularly for datasets with thousands of variables. Most current algorithms for DBN structure learning are adaptations from those used in static Bayesian Networks (BNs), and are typically focused on smaller-scale problems. In order to solve large-scale problems while taking full advantage of existing algorithms, this paper introduces a novel divide-and-conquer strategy, originally developed for static BNs, and adapts it for large-scale DBN structure learning. Additionally, we leverage the prior knowledge of 2 Time-sliced BNs (2-TBNs), a special class of DBNs, to enhance the performance of this strategy. Our approach significantly improves the scalability and accuracy of 2-TBN structure learning. Designed experiments demonstrate the effectiveness of our method, showing substantial improvements over existing algorithms in both computational efficiency and structure learning accuracy. In problem instances with more than 1,000 variables, our proposed approach on average improves two accuracy metrics by 74.45% and 110.94%, respectively, while reducing runtime by an average of 93.65%. Moreover, in problem instances with more than 10,000 variables, our proposed approach successfully completed the task in a matter of hours, whereas the baseline algorithm failed to produce a reasonable result within a one-day runtime limit. © IFIP International Federation for Information Processing 2024.

关键词： Bayesian networks

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An Improved Structure for Academic Information Services through AI Chatbots

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Journal of engineering science and Technology Review 2023年第5期16卷 164-173页

作者： Ula, Mutammimul Hardi, Richki Hipiny, Irwandi Department of Information Systems Faculty of Engineering Universitas Malikussaleh Aceh Indonesia Department of informatics Universitas Mulia Balikpapan Indonesia Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Sarawak Malaysia

Academic information service is the most critical factor that must be considered in a university. Service quality is an important indicator affecting all academics’ satisfaction and loyalty. Improvement of information services on campus has been a lot of research focusing on academics. Meanwhile, the software aspect has received less attention. Researchers have previously discussed information service frameworks but have not accommodated future needs. Software that must be considered can quickly respond to the user, one of which is a chatbot. Chatbots can be used to solve problems related to question-and-answer services, especially for academic institutions that do not have specific resources to handle this work. With chatbots, redundant user questions can be handled automatically. Chatbots are increasingly being offered as an alternative source of customer service. For a user to use a chatbot for this purpose, the user must trust the chatbot to provide the necessary support. To overcome this knowledge gap, a framework can integrate software, stakeholders, and academics in higher education. Therefore it is necessary to conduct new research to help answer future needs. © 2023 School of science, IHU. All rights reserved.

关键词： Information services

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Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text

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computers, Materials & Continua 2022年第5期71卷 2497-2513页

作者： Mohammad Alamgeer Fahd N.Al-Wesabi Huda G.Iskandar Imran Khan Nadhem Nemri Mohammad Medani Mohammed Abdullah Al-Hagery Ali Mohammed Al-Sharafi Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaMalaysia Department of Electrical Engineering University of Engineering and Technology PeshawarPakistan Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA

Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication *** this paper,a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking(SFASCDW)is proposed for content authentication and tampering detection of English text.A first-level order of alphanumeric mechanism,based on hidden Markov model,is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed *** researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English ***,he extracts the features of the interrelationship among the contexts of the text,utilizes the extracted features as watermark information,and validates it later with the studied English text to detect any *** has been implemented using PHP with VS code *** robustness,effectiveness,and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks,namely insertion,reorder,and *** SFASCDW was found to be effective and could be applicable in detecting any possible tampering.

关键词： Watermarking soft computing text analysis hidden Markov model content authentication

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IOT Based Smart Parking System Using Ensemble Learning

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Intelligent Automation & Soft Computing 2023年第6期36卷 3637-3656页

作者： Walaa H.Elashmawi Ahmad Akram Mohammed Yasser Menna Hisham Manar Mohammed Noha Ihab Ahmed Ali Department of Computer Science Faculty of Computers and InformaticsSuez Canal University4.5 Km the Ring RoadIsmailiaIsmailia41522Egypt Department of Computer Engineering and Software Systems Faculty of EngineeringAin Shams UniversityAl-Abbaseya4543070Egypt Department of Computer Science Faculty of Computer ScienceMisr International University28 KM Cairo–Ismailia RoadCairo44971Egypt College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Higher Future Institute for Specialized Technological Studies Cairo3044Egypt

Parking space is usually very limited in major cities,especially Cairo,leading to traffic congestion,air pollution,and driver *** car parking systems tend to tackle parking issues in a non-digitized *** systems require the drivers to search for an empty parking space with no guaran-tee of finding any wasting time,resources,and causing unnecessary *** address these issues,this paper proposes a digitized parking system with a proof-of-concept implementation that combines multiple technological concepts into one solution with the advantages of using IoT for real-time tracking of park-ing *** authentication and automated payments are handled using a quick response(QR)code on entry and *** experiments were done on real data collected for six different locations in Cairo via a live popular times *** machine learning models were investigated in order to estimate the occu-pancy rate of certain ***,a clear analysis of the differences in per-formance is illustrated with the final model deployed being *** has achieved the most efficient results with a R^(2) score of 85.7%.

关键词： IoT XGBoost linear regression random forest ensemble learning isolation forest

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Deep Learning Enabled Intelligent Healthcare Management System in Smart Cities Environment

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computers, Materials & Continua 2023年第2期74卷 4483-4500页

作者： Hanan Abdullah Mengash Lubna A.Alharbi Saud S.Alotaibi Sarab AlMuhaideb Nadhem Nemri Mrim M.Alnfiai Radwa Marzouk Ahmed S.Salama Mesfer Al Duhayyim Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversityTabuk71491Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Information Systems College of Science and Arts at MuhayelKing Khalid UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

In recent times,cities are getting smart and can be managed effectively through diverse architectures and *** cities have the ability to support smart medical systems that can infiltrate distinct events(i.e.,smart hospitals,smart homes,and community health centres)and scenarios(e.g.,rehabilitation,abnormal behavior monitoring,clinical decision-making,disease prevention and diagnosis postmarking surveillance and prescription recommendation).The integration of Artificial Intelligence(AI)with recent technologies,for instance medical screening gadgets,are significant enough to deliver maximum performance and improved management services to handle chronic *** latest developments in digital data collection,AI techniques can be employed for clinical decision making *** the other hand,Cardiovascular Disease(CVD)is one of the major illnesses that increase the mortality rate across the ***,wearables can be employed in healthcare systems that instigate the development of CVD detection and *** this motivation,the current study develops an Artificial Intelligence Enabled Decision Support System for CVD Disease Detection and Classification in e-healthcare environment,abbreviated as AIDSS-CDDC *** proposed AIDSS-CDDC model enables the Internet of Things(IoT)devices for healthcare data ***,the collected data is saved in cloud server for *** by,training 4484 CMC,2023,vol.74,no.2 and testing processes are executed to determine the patient’s health *** accomplish this,the presented AIDSS-CDDC model employs data preprocessing and Improved Sine Cosine Optimization based Feature Selection(ISCO-FS)*** addition,Adam optimizer with Autoencoder Gated RecurrentUnit(AE-GRU)model is employed for detection and classification of *** experimental results highlight that the proposed AIDSS-CDDC model is a promising performer compared to other existing models.

关键词： Smart cities e-healthcare decision support system cardiovascular disease deep learning feature selection

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Autoencoder-Enhanced Roommate Recommendation System 6

Autoencoder-Enhanced Roommate Recommendation System

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Zahran, Khaled Amir, Abdallah Elbanhawy, Magy Ghanem, Ingy El-Ghamry, Amir Fouad, Khaled M. Moawad, Ibrahim F. New Mansoura University Faculty of Computer Science and Engineering Egypt School of Engineering and Computer Science Mansoura University University of Hertfordshire Hosted by Global Academic Foundation Faculty of Computer and Information Sciences Egypt Benha University Information Systems Faculty of Computers and Artificial Intelligence Egypt College of Computer Science and Engineering Taibah University Department of Artificial Intelligence Saudi Arabia

ISBN: (纸本)9798350378511

This proposed system is designed for creating a new way of giving personalized recommendations by focusing on people's behaviors and preferences. The system uses traditional machine learning algorithms integrating it with deep learning techniques to get the most out of data and suggest recommendations which are designed according to each individual's unique preferences. A deep learning autoencoder is used to learn a lower-dimensional representation of the data, with an assurance on feature extraction and reconstruction accuracy. The encoded features are passed to be clustered using KMeans, with the effectiveness of clustering estimated through internal validation metrics such as silhouette score, Calinski-Harabasz index, and Davies-Bouldin index. Also, t-Distributed Stochastic Neighbor Embedding (t-SNE) is utilized for visualizing clustered data in a simple manner. Additionally, a silhouette plot is given to provide a visual representation of the silhouette scores across clusters, highlighting the degree of cohesion within clusters and separation between them. Finally, using cosine similarity that identifies similar users within the same cluster. © 2024 IEEE.

关键词： Contrastive Learning

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Usability Assessment of OpenEMR: Enhancing Healthcare Interactions 68th

Usability Assessment of OpenEMR: Enhancing Healthcare Intera...

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68th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2024

作者： Mahmoud, Abdelrahman Saleem, Jason J. University of Louisville LouisvilleKY United States Department of Computer Science and Engineering Alamein International University Matrouh New Alamein City Egypt Department of Computer Science and Engineering University of Louisville KY United States Center for Human Systems Engineering University of Louisville KY United States

Electronic medical record (EMR) systems are pivotal in modern healthcare for digitizing patient records and improving clinical workflows. However, persistent usability challenges hinder their effective adoption and user satisfaction. This study employs a comprehensive user-centered design approach to identify and address usability issues in one such EHR, an open-source system named openEMR. Our main objective was to assess openEMR’s usability through several usability metrics. In addition to a summative usability test with 10 participants, we employed usability inspection (i.e., a heuristic evaluation) to generate additional findings using multiple methods. The results from the summative usability test provide a comprehensive perspective on openEMR’s performance. In addition to task-specific observations, participants offered insights into openEMR’s overall usability through a debrief interview. Through quantitative surveys, usability testing, qualitative interviews, and a heuristic evaluation, this study identified critical usability issues, proposes targeted solutions, and discusses implications for enhancing EMR systems in healthcare settings. © 2024 Human Factors and Ergonomics Society.

关键词： Electronic health record

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FUNCTIONAL ANALYSIS OF CYBER-PHYSICAL systems FOR CONFIDENTIALITY QUANTUM RESILIENCE

FUNCTIONAL ANALYSIS OF CYBER-PHYSICAL SYSTEMS FOR CONFIDENTI...

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ASME 2024 International Design engineering Technical Conferences and computers and Information in engineering Conference, IDETC-CIE 2024

作者： Van Bossuyt, Douglas L. Hale, Britta Naval Postgraduate School Department of Systems Engineering MontereyCA United States Naval Postgraduate School Department of Computer Science MontereyCA United States

ISBN: (纸本)9780791888353

The pending development of a cryptographically relevant quantum computer (CRQC) puts cryptographic security relying on public key cryptography at risk. Such cryptography can be found throughout systems today, including cyber-physical systems, which raises a question on when to transition security to quantum resistant alternatives, i.e., post-quantum cryptography. Criticality of transition timeline and planning can be non-trivial for system managers and the cybersecurity risk of transition delay is often opaque. This paper investigates functional system modeling techniques for planning and risk mitigation against quantum threats to confidentiality in cyber-physical systems. The research in this paper applies systems engineering and design engineering tools such as Functional Modeling in the form of Functional Failure Identification and Propagation (FFIP) and Flow State Logic (FSL) to analyze flow paths and provide quantum vulnerability metrics for cyber-physical systems. Using this insight, this work further provides guidance on how such metrics can be used to plan system transition for quantum resistance. Timeline upgrade prioritization of functions and their component solutions to prepare for the threat of a CRQC is possible with the method proposed in this paper. A simplified case study of a polar research facility is presented to demonstrate the method. This paper introduces the concept of Quantum Vulnerability Information Timeline (QVIT) in the context of system modeling and demonstrates within the case study how QVIT values can be calculated for various system components to estimate preparation timelines against quantum threats. Copyright © 2024 by The United States Government.

关键词： Quantum computers

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