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

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

ISBN: (纸本)9798350369106

This study addresses the critical aspect of data collection within Wireless Sensor Networks (WSNs), which consist of autonomous, compact sensor devices deployed to monitor environmental conditions. These networks have limited processing capacity, storage, short-range communication capabilities, and constrained battery power. A primary challenge in WSN s revolves around data gathering, particularly when employing static sinks, leading to premature energy depletion in nodes near these sinks. Integrating mobile collectors introduces the potential for energy conservation by shortening data routes. This article introduces three distinct algorithms for optimizing data collection in WSN s. Our approach involves an in-depth analysis of diverse strategies to mitigate packet collisions and facilitate the retransmission of lost packets. Our findings underscore the considerable impact that packet collisions can exert on the overall network performance during data gathering within wireless sensor networks. Through empirical exploration and analysis, we highlight the significance of these algorithms in enhancing the efficiency, energy conservation, and reliability of data collection processes within WSNs. This research sheds light on these algorithms' vital role in addressing the pressing challenges of data gathering and network performance optimization in wireless sensor networks. © 2024 IEEE.

关键词： Aircraft accidents

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A Mathematical Model for COVID-19 Image Enhancement based on Mittag-Leffler-Chebyshev Shift

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computers, Materials & Continua 2022年第10期73卷 1307-1316页

作者： Ibtisam Aldawish Hamid A.Jalab Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic UniversityRiyadh11432Saudi Arabia Department of Computer System&Technology Faculty of Computer Scienceand Information TechnologyUniversiti Malaya50603Kuala LumpurMalaysia

The lungs CT scan is used to visualize the spread of the disease across the lungs to obtain better knowledge of the state of the COVID-19 *** diagnosing of COVID-19 disease is a complex challenge that medical system face during the pandemic *** address this problem,this paper proposes a COVID-19 image enhancement based on Mittag-Leffler-Chebyshev polynomial as pre-processing step for COVID-19 detection and *** proposed approach comprises the MittagLeffler sum convoluted with Chebyshev *** idea for using the proposed image enhancement model is that it improves images with low graylevel changes by estimating the probability of each *** proposed image enhancement technique is tested on a variety of lungs computed tomography(CT)scan dataset of varying quality to demonstrate that it is robust and can resist significant quality *** blind/referenceless image spatial quality evaluator(BRISQUE),and the natural image quality evaluator(NIQE)measures for CT scans were 38.78,and 7.43 *** to the findings,the proposed image enhancement model produces the best image quality ***,this model considerably enhances the details of the given datasets,and it may be able to assist medical professionals in the diagnosing process.

关键词： CT scans COVID-19 Mittag-Leffler Chebyshev polynomial fractional calculus

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Transmission of Electromagnetic Waves Through a Clay Material 1

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Mandrić, Vanja Rupčić, Slavko Vinko, Davor Bilandžija, Domagoj Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

This paper deals with the simulation calculation of transmission (S21) and reflection (S22) parameters in a material parametrically based on clay (brick). The electromagnetic parameters of the clay that are the subject of the study are: relative permittivity Εr, loss tangent tan δ and electrical conductivity σ, while the only structural parameter is the thickness d of the sample. The values of all considered parameters are within the range of data from available literature and values that could occur due to external causes (e. g. an increase in clay moisture leads to an increase in electrical conductivity). The simulation model was carried out with the software tool ANSYS HFSS and validated with a laboratory measurement model. The laboratory model consists of a circular waveguide with an inner diameter of 150 mm and a total length of 700 mm, which is excited by 52 mm long probes placed 50 mm from the last wall of the waveguide. The lower cut-off frequency of this measurement system is 1.173 GHz, so all results (simulation and measurement) are limited by this lower cut-off frequency of the waveguide. All simulation calculations were performed for three clay sample thicknesses: 18 mm, 36 mm and 54 mm. These calculations were made with the aim of determining brick composites that have high attenuation of electromagnetic EM waves (low transmission parameter and high reflection parameter) in order to reduce the strength of EM fields inside the object made of such bricks. The measured results were used to verify the simulation model. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Circular waveguides

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Hybrid Approach for Procedural Level Generation for 2D Platformer Game

Hybrid Approach for Procedural Level Generation for 2D Platf...

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2024 Beyond technology Summit on Informatics International Conference, BTS-I2C 2024

作者： Tarigan, Jos Timanta Sukku, Erick Yudha Pratama Hardi, Sri Melvani Universitas Sumatera Utara Faculty of Computer Science and Information Technology Medan Indonesia

ISBN: (纸本)9798331508579

This research proposes a hybrid approach for a procedural level generation for our 2D platformer game. The method integrates manual level creation and procedural algorithm to generate a complete level for 2D rouge-like platformer game including the overall structure of the level, corridors, enemies, obstacles, and items. The proposed method also allowed user-input parameters that define requirement for the level such as difficulty, room numbers, enemy and item spawn probability. We developed the proposed method and implemented the system in our game, Lost Labyrinth Rouge's Odyssey. We implemented the system specifically to fit the mechanic and rules of our game. To test the performance of the system to develop a level, we performed a usability test by inviting users to play the game multiple times. The result and feedback from the respondents show that most the system was able to generate a good playability for a 2D platformer dungeon game. © 2024 IEEE.

关键词： Game design

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Distance Matrix and Markov Chain Based Sensor Localization in WSN

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computers, Materials & Continua 2022年第5期71卷 4051-4068页

作者： Omaima Bamasaq Daniyal Alghazzawi Surbhi Bhatia Pankaj Dadheech Farrukh Arslan Sudhakar Sengan Syed Hamid Hassan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversitySaudi Arabia Department of Computer Science and Engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipurRajasthanIndia University of Engineering and Technology LahorePakistan Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveliTamilnaduIndia

Applications based on Wireless Sensor Networks(WSN)have shown to be quite useful in monitoring a particular geographic area of *** geometries of the surrounding environment are essential to establish a successful WSN *** it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes(SN)in a WSN is always a challenging *** this research paper,Distance Matrix and Markov Chain(DM-MC)model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the *** method further employs a Markov Chain Model(MCM)for energy optimization and interference *** are performed against two well-known models,and the results demonstrate that the proposed algorithm improves performance by using less network resources when compared to the existing *** probability is used in the Markova chain to sustain higher energy ***,the proposed Distance Matrix and Markov Chain model decrease energy use by 31%and 25%,respectively,compared to the existing DV-Hop and CSA *** experimental results were performed against two proven models,Distance VectorHop Algorithm(DV-HopA)and Crow Search Algorithm(CSA),showing that the proposed DM-MC model outperforms both the existing models regarding localization accuracy and Energy Consumption(EC).These results add to the credibility of the proposed DC-MC model as a better model for employing node localization while establishing a WSN framework.

关键词： Wireless sensor network resource optimization routing distance matrix Markov chain

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Natural Language Processing Studies in Humancomputer Interaction: A Bibliometric Analysis and Future Research Framework 22

Natural Language Processing Studies in HumanComputer Interac...

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22nd IEEE Student Conference on Research and Development, SCOReD 2024

作者： Rashid, Farah Syazwani Binti Mohd Kamsin, Amirrudin Bin Noor, Nurul Fazmidar Binti Mohd Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System Technology Kuala Lumpur50603 Malaysia Universiti Teknologi MARA College of Computing Informatics and Mathematics Selangor Shah Alam40450 Malaysia

ISBN: (纸本)9798331510077

This study conducts a bibliometric analysis of Natural Language Processing (NLP) within Human-computer Interaction (HCI) to identify trends, challenges, and future directions. Analyzing 1,710 SCOPUS-indexed documents (1983-2024) using a PRISMA flowchart, the results show that the United States and China are leading contributors. Key developments include emotion recognition, chatbot interfaces, and speech processing, highlighting NLP's role in user-centered technologies. Despite growing applications, challenges such as reliability and ethical concerns persist. This analysis emphasizes the need for ethical frameworks and technological advancements to address deployment issues and align NLP innovations with the United Nations Sustainable Development Goals (SDGs). By mapping global research trends, this study provides insights into the transformative potential of NLP in HCI for developing inclusive and responsive systems. © 2024 IEEE.

关键词： Emotion Recognition

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Efficient and Secure Healthcare Data sharing via Blockchain for Edge-Based Internet of Medical Things

Efficient and Secure Healthcare Data sharing via Blockchain ...

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World Conference on information systems for Business Management, ISBM 2023

作者： Basudan, Sultan Faculty of computer science and information technology Jazan University Jazan Saudi Arabia

ISBN: (纸本)9789819983452

The current study aims to implement a data sharing system that uses the blockchain to ensure data privacy and security-preserving during profile corresponding. The system also utilized a bloom filter to authenticate keyword ciphertext. It also uses a key policy attribute-based encryption (KP-ABE) procedure and smart agreements for profile matching. A two-phase Stackelberg game incentive mechanism is recommended to incentivize users to engage in the system and maximize users’ profit. The security analysis section illustrates that this system model can address various security goals. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain

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Expert Review on Big Data Analytics Quality Model in Enhancing Healthcare Organizational Performance 9

Expert Review on Big Data Analytics Quality Model in Enhanci...

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9th International Conference on information Management, ICIM 2023

作者： Nasir, Wan Mohd Haffiz Mohd Jusoh, Yusmadi Yah Binti Abdullah, Rusli Bin Abdullah, Salfarina Binti Faculty of Computer Science and Information Technology Selangor Malaysia

ISBN: (纸本)9798350336382

Big Data Analytics implementation in healthcare can provide an end-to-end solution with better information value insights. This paper will highlight expert opinion in verifying the quality factors in big data analytics (BDA) that affect the performance of healthcare organizations and present the findings in developing the BDA quality model. This expert verification study was carried out through hybrid approach sessions either face-to-face or by virtual online meetings with two academicians, two specialists, one data scientist, two subject matter experts, and also as BDA expert, one industry expert, one senior ICT Director involve in healthcare, and one content validity expert. All the experts have a vast experience and implementation of BDA in healthcare. The results of these exercises have confirmed and verified ten BDA quality factors which consist of reliability, accuracy, completeness, timeliness, format, accessibility, usability, maintainability, and portability were commensurate with the research model. The analysis of this expert verification study has been done through descriptive analysis such as frequency, mean, and standard deviation. The pilot study will be commenced once the verification process and analysis are completed and the BDA quality model will be validated later through actual study. © 2023 IEEE.

关键词： Data Analytics

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Dengue Cases Prediction and Analysis using LSTM and Region-specific Data

Dengue Cases Prediction and Analysis using LSTM and Region-s...

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2024 OPJU International technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Ud Deen Shafique, Hafiz Noor Ali, Nauman Hussain, Muhammad Zunnurain Hasan, Muhammad Zulkifl Mustafa, Muzzamil Khalid, Aqsa Awan, Rimsha Ashraf, Farhan Khan, Zohaib Ahmed Javaid, Arslan University Lahore Department of Computer Engineering Information Technology Punjab Pakistan Bahria University Lahore Campus Dept. of Computer Science Zunnurain Pakistan University of Central Punjab Lahore Faculty of Information Technology Department of Computer Science Pakistan National College of Business Administration and Economics Department of Computer Science Lahore Pakistan Information Technology University Lahore Pakistan

ISBN: (纸本)9798350373783

Dengue Fever presents a substantial global health challenge, necessitating the development of accurate predictive models for effective disease management. This research paper conducts a comprehensive analysis of a Long ShortTerm Memory (LSTM) neural network-based model for forecasting Dengue cases in the Philippines. The study includes data preprocessing, model development using TensorFlow and Keras, and thorough evaluation using metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and Rsquared (R2). The dataset, 'Dengue Cases in the Philippines,' provides a detailed historical record of Dengue fever cases and fatalities across various regions, enabling a thorough analysis of temporal and spatial dynamics. Data preprocessing involves label encoding, normalization, and careful data splitting to ensure accurate model training and testing. The LSTM neural network architecture is optimized through hyperparameter tuning, including learning rate, batch size, and epochs, to improve prediction accuracy. Model performance is rigorously evaluated, with an MAE of 913, indicating areas for further improvement. While the model shows promise, there is room for refinement. This study contributes to the field by exploring the feasibility of LSTM models for Dengue prediction, with insights that may inform future research in disease forecasting and public health strategies. Limitations, ethical considerations, and recommendations for further work are discussed. © 2024 IEEE.

关键词： Electronic health record

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Adaptive Dynamic Dipper Throated Optimization for Feature Selection in Medical Data

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computers, Materials & Continua 2023年第4期75卷 1883-1900页

作者： Ghada Atteia El-Sayed M.El-kenawy Nagwan Abdel Samee Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Ahmad Taher Azar Nima Khodadadi Reham A.Ghanem Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Civil Engineering University of Science and TechnologyMiami33101USA Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Oral Biology Department Faculty of Oral and Dental MedicineDelta University for Science and TechnologyGamasaEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The rapid population growth results in a crucial problem in the early detection of diseases inmedical *** all the cancers unveiled,breast cancer is considered the second most severe ***,an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical *** recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective,reliable,and rapid responses,which could help in decreasing the death *** this paper,we propose a new algorithm for feature selection based on a hybrid between powerful and recently emerged optimizers,namely,guided whale and dipper throated *** proposed algorithm is evaluated using four publicly available breast cancer *** evaluation results show the effectiveness of the proposed approach from the accuracy and speed *** prove the superiority of the proposed algorithm,a set of competing feature selection algorithms were incorporated into the conducted *** addition,a group of statistical analysis experiments was conducted to emphasize the superiority and stability of the proposed *** best-achieved breast cancer prediction average accuracy based on the proposed algorithm is 99.453%.This result is achieved in an average time of 3.6725 s,the best result among all the competing approaches utilized in the experiments.

关键词： Medical dataset breast cancer guided whale optimizer dipper throated optimizer feature selection meta-heuristics

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