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Multithreaded Haplotype Block Partitioning of Rheumatoid Arthritis Genomic Data

Multithreaded Haplotype Block Partitioning of Rheumatoid Art...

2023 IEEE EMBS Special Topic Conference on Data science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Al-Khalifa, Azza M. Saad, Mohamed N. Rushdi, Muhammad A. Eldeib, Ayman M. Minia University Faculty of Engineering Biomedical Engineering Department Egypt Cairo University Faculty of Engineering Department of Biomedical Engineering and Systems Giza12613 Egypt Southern New Hampshire University School of Engineering Technology and Aeronautics Computer Science Department ManchesterNH United States

ISBN: (纸本)9798350383386

Haplotype block partitioning methods have been widely employed in the analysis of genetic patterns of common and complex diseases. The existing methods suffer from high time and memory complexities due to the key bottleneck of computing the linkage disequilibrium (LD) for all or most pairs of single-nucleotide polymorphisms (SNPs). In this work, we propose a multithreaded variant of the confidence internal test (CIT) method for haplotype block partitioning implementations. The usefulness of the proposed method in reducing the time and memory costs is demonstrated through experiments on the North American Rheumatoid Arthritis Consortium (NARAC) dataset. Our simulation results show 11-35% savings in time and 8-36% savings in memory requirements with only 3-6% increase in CPU *** Relevance: This work seeks time and memory savings in genetic analysis for the prediction of diseases with complex factors (e.g., rheumatoid arthritis in our case). These savings can streamline and accelerate relevant clinical workflows and reduce demand for computational resources. © 2023 IEEE.

关键词： Diseases

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ShieldSMS Sentinel: Guardian of Your Digital Communication Bastion 2

ShieldSMS Sentinel: Guardian of Your Digital Communication B...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Gourshettiwar, Palash Thakare, Rajesh D. Duddalwar, Prapti Shete, Rushikesh Gundewar, Swapnil Verma, Prateek Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Maharashtra Wardha442001 India Yashavantrao Chavan College of Engineering Department of Electronics Engineering Maharashtra Nagpur440002 India Vishwakarma Institute of Technology Department of Electronics Engineering Maharashtra Pune411037 India St. Vincent Pallotti College of Engineering and Technology Department of Computer Science and Business Systems Maharashtra Nagpur440002 India Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha442001 India

ISBN: (纸本)9798331528713

The SMS spam detection Project provides a comprehensive framework for reliably identifying and classifying spam messages sent over SMS communication channels by fusing ML algorithms with NLP techniques. Using EDA, a dataset of labelled SMS messages identified as spam or ham is thoroughly studied to reveal patterns in the word count, sentence count, and message length distributions. Then, unstructured text is transformed into structured data that may be utilized with ML models through tokenization, punctuation and stop word removal, stemming, and other text preprocessing techniques. Feature engineering, which numerically represents text data using vectorization techniques like BoW and TF-IDF, plays a significant role. Various ML algorithms, including Gaussian Naive Bayes, Multinomial Naive Bayes, SVM, and ensemble approaches, are trained and evaluated. Performance metrics, including accuracy and precision, serve as standards for model selection. © 2024 IEEE.

关键词： Text messaging

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Real-Time Testing of Microgrid Control Algorithms: Development of Experimental Setup 29

Real-Time Testing of Microgrid Control Algorithms: Developme...

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29th International Conference on Information Technology, IT 2025

作者： Forcan, Miodrag Dobrić, Goran Abed, Amir Žarković, Mileta Ikić, Marko Forcan, Jovana Barragán-Villarejo, Manuel Maza-Ortega, José María De Paula Garcia-López, Francisco University of East Sarajevo Faculty of Electrical Engineering East Sarajevo71123 Bosnia and Herzegovina University of Belgrade School of Electrical Engineering Belgrade11120 Serbia University of East Sarajevo Faculty of Philosophy Department of Computer Science and Systems East Sarajevo71420 Bosnia and Herzegovina University of Sevilla Department of Electrical Engineering Seville41004 Spain

ISBN: (纸本)9798331517649

This paper provides an overview of microgrid control strategies, examining differences between centralized and decentralized approaches, and focusing on classical hierarchical control schemes as well as the structure of three-layer microgrid control systems. It also explores Hardware-in-the-Loop modeling, a crucial approach for microgrid simulation, with particular emphasis on devices supporting microgrid modeling. The paper primarily focuses on the design and implementation requirements of an experimental setup for real-time testing of microgrid control algorithms. The setup incorporates Hardware-in-the-Loop device, a power amplifier, a power converter, a battery energy storage system, and a digital controller. It is specifically designed to handle both power and information (control) signals, facilitating a comprehensive approach to evaluating and validating microgrid control strategies in real-world conditions. A detailed analysis of the setup elements and their interactions is also provided. © 2025 IEEE.

关键词： Hardware-in-the-loop simulation

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Human Emotions Classification Using EEG via Audiovisual Stimuli and AI

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computers, Materials & Continua 2022年第12期73卷 5075-5089页

作者： Abdullah A Asiri Akhtar Badshah Fazal Muhammad Hassan A Alshamrani Khalil Ullah Khalaf A Alshamrani Samar Alqhtani Muhammad Irfan Hanan Talal Halawani Khlood M Mehdar Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Software Engineering University of MalakandDir LowerPakistan Department of Computer Science and Information Systems College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia

Electroencephalogram(EEG)is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain,measured and recorded chronologically the surface of the scalp from the *** recorded signals from the brain are rich with useful *** inference of this useful information is a challenging *** paper aims to process the EEG signals for the recognition of human emotions specifically happiness,anger,fear,sadness,and surprise in response to audiovisual *** EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp,in response to audiovisual stimuli for the mentioned *** a bandpass filter with a bandwidth of 1-100 Hz,recorded raw EEG signals are *** preprocessed signals then further analyzed and twelve selected features in different domains are *** Random forest(RF)and multilayer perceptron(MLP)algorithms are then used for the classification of the emotions through extracted *** proposed audiovisual stimuli based EEG emotion classification system shows an average classification accuracy of 80%and 88%usingMLP and RF classifiers respectively on hybrid features for experimental signals of different *** proposed model outperforms in terms of cost and accuracy.

关键词： Electroencephalography emotion classification signal processing multilayer perceptron random forest

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A Lumped Element Method for Acoustoelectric Imaging Reconstruction: A Numerical Study

A Lumped Element Method for Acoustoelectric Imaging Reconstr...

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2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Tan, Rick Hao McDermott, Conor Rossa, Carlos Ontario Tech University Faculty of Engineering and Applied Science Oshawa Canada Carelton University Systems and Computer Engineering OttawaON Canada

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Acoustoelectric impedance tomography (AET) is a new non-invasive medical imaging procedure used to map the electrical properties of biological tissues with higher spatial resolution than traditional electrical impedance tomography (EIT). It exploits the acoustoelectric effect where modulated ultrasonic pressure changes the local tissue conductivity. This provides additional information to reconstruct a tomographic image, and has a stabilizing effect on an otherwise highly unstable inverse *** this paper, a novel approach to solving the AET inverse problem for image reconstruction is proposed. In the algorithm, the acoustoelectric effect is assumed to create small perturbations in the local resistance of the medium under observation. A lumped model consisting of a finite mesh of resistors approximates the medium under observation, through which boundary voltage differences between the excited and unexcited medium are calculated. A variation of the Modified Newton Raphson (MNR) algorithm is then proposed, where each pattern in the algorithm is created from small perturbations of the tissue conductivity. A total of eight simulation scenarios are evaluated, where the conductivity perturbations are in the order of 1%, 2.5% to 5% of the nominal tissue conductivity. The algorithm can successfully reconstruct the images in the presence of random noise. The obtained images are compared against traditional EIT where the percentage error is calculated for each simulated tomographic image. The simulation results indicate that the proposed approach is superior to traditional EIT as it constructs more distinct and high contrasting images with less percentage error. © 2022 IEEE.

关键词： Inverse problems

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Game-Theoretic Sectoral Demand Response Procurement in Multi-Energy Microgrid Planning

Game-Theoretic Sectoral Demand Response Procurement in Multi...

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2022 IEEE Power and Energy Society General Meeting, PESGM 2022

作者： Mohseni, Soheil Brent, Alan C Sustainable Energy Systems School of Engineering and Computer Science Faculty of Engineering Victoria University of Wellington Wellington6140 New Zealand

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408233

Multi-energy community microgrids (MGs) have been recognized as key enablers for harnessing distributed demand-side flexibility resources, especially when integrating storage. However, the literature on demand response-integrated community energy system design and dispatch optimization has, thus far, failed to concurrently maximize the flexibility potential in several energy carriers, thereby neglecting the potentially significant improvement opportunities of the associated business cases. In response, this paper introduces a novel Nash bargaining-based cooperative game approach for the optimal aggregator-mediated demand response scheduling of multi-energy community MGs serving electricity and thermal loads, as well as hydrogen as a transportation fuel. More specifically, the proposed approach systematically and effectively characterizes how the players share the resulting surplus from demand-side management in an equitable manner under the assumption that the interests of the players - the MG operator, sectoral demand response aggregators, and small-scale end-users - are neither completely opposed nor completely coincident. The proposed approach is then integrated into a meta-heuristic-based long-term MG planning method. A case study for a community-based residential users' aggregation scheme in Aotearoa-New Zealand demonstrates the effectiveness of the method in reducing the total discounted system cost of a multi-energy MG by 14% (equating to US1.9m) and 31% (US5.4m) respectively compared to the cases where: (i) the actors' behaviors are characterized using non-cooperative game theory under self-interestedness assumptions;and (ii) no demand response programs are implemented. © 2022 IEEE.

关键词： Heuristic methods

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Automated Detection and Consistency Analysis of Tajweed Recitation Rules in the Holy Quran 4

Automated Detection and Consistency Analysis of Tajweed Reci...

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4th Novel Intelligent and Leading Emerging sciences Conference, NILES 2022

作者： Mohammad, Karim Aly Kandil, Ahmed H. El-Bialy, Ahmed M. Fawzi, Sahar Ali Cairo University Systems and Biomedical Engineering Faculty of Engineering Giza Egypt El-Shorouk Academy Systems and Biomedical Engineering Faculty of Engineering Cairo Egypt Information Technology & Computer Science Nile University Giza Egypt

ISBN: (数字)9781665452410

ISBN: (纸本)9781665452410

Precise Recitation of Holy Quran is a religious duty that must be performed with great care. Tajweed rules are constructed to guide the reader to utter the Holy Quran text as it was originally uttered by prophet Muhammad. An automatic pattern detection algorithm is implemented to allocate basic Tajweed rules. The rules addressed in this paper, are Madd, Noon Sakinah, Tanween and Meem Sakinah rules. These rules are characterized by well-defined uttered style. The rules studied in this paper, were allocated at 487 positions in forty verses of Surat El-Anfal of Sheikh El-Hosary's recitation. Data related to each detected rule was saved in a script file for further processing. The consistency analysis of the rules' uttered durations is performed to evaluate the performance of the reader. The results obtained Natural Madd and Noon Sakinah and Tanween rules achieved a consistency range of (0.71 to 0.90) and (0.89 to 1.17) respectively of the detected patterns. © 2022 IEEE.

关键词： Pattern recognition

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Al-Biruni Earth Radius(BER)Metaheuristic Search Optimization Algorithm

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computer systems science & engineering 2023年第5期45卷 1917-1934页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Seyedali Mirjalili Nima Khodadad Mona A.Al duailij Amel Ali Alhussan Doaa Sami Khafaga 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 Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Centre for Artificial Intelligence Research and Optimization Torrens University AustraliaFortitude ValleyQLD 4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722Korea Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and *** metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention,such as particle swarm optimization(PSO),whale optimization algorithm(WOA),grey wolf optimization algorithm(GWO),genetic algorithm(GA),and gravitational search algorithm(GSA).According to the literature,no one metaheuristic optimization algorithm can handle all present optimization *** novel optimization methodologies are still *** Al-Biruni earth radius(BER)search optimization algorithm is proposed in this *** proposed algorithm was motivated by the behavior of swarm members in achieving their global *** search space around local solutions to be explored is determined by Al-Biruni earth radius calculation method.A comparative analysis with existing state-of-the-art optimization algorithms corroborated the findings of BER’s validation and testing against seven mathematical optimization *** results show that BER can both explore and avoid local *** has also been tested on an engineering design optimization *** results reveal that,in terms of performance and capability,BER outperforms the performance of state-of-the-art metaheuristic optimization algorithms.

关键词： Metaheuristics evolutionary optimization exploration exploitation mutation Al-biruni earth radius

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A Review of Satellite Image Analysis Tools 4th

A Review of Satellite Image Analysis Tools

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4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2023

作者： Pawar, Bhushan Prakash, Vijay Garg, Lalit Galdies, Charles Buttigieg, Sandra Calleja, Neville Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta MSD Msida2080 Malta Department of Computer Science and Engineering Graphics Era Hill University Dehradun India Environmental Management and Plan Division Institute of Earth Systems University of Malta Msida Malta Faculty of Health Sciences University of Malta Msida Malta Faculty of Medicine and Surgery University of Malta Msida Malta

ISBN: (纸本)9789819994410

The rapid growth of urban areas, population, and pollution presents a significant environmental challenge. Addressing these challenges requires innovative analytical approaches and data sources. This study focuses on the three-scale phenomena of the environmental system, physical environment, and regional surroundings, considering their implications on a global network scale. Remote sensing data, with its easy accessibility, offers new toolkits and methods to improve the global environment. It provides self-consistent measurements of vital physical attributes and surpasses traditional data sources regarding accuracy, efficiency, and coverage of larger geographical areas. This study aims to identify and analyze appropriate satellite image analysis tools for healthcare. The study objectives include studying available tools, analyzing their features, categorizing tools into open-source and commercial categories, and providing recommendations. This study emphasizes feature extraction and image enhancement parameters, which are crucial for image analysis. Further, this study provides a functional overview of various commercial and open-source satellite image analysis tools and suggests suitable tools for healthcare applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Geographic information systems

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Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

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computers, Materials & Continua 2022年第9期72卷 4249-4265页

作者： Muhammad Irfan Ali Raza Faisal Althobiani Nasir Ayub Muhammad Idrees Zain Ali Kashif Rizwan Abdullah Saeed Alwadie Saleh Mohammed Ghonaim Hesham Abdushkour Saifur Rahman Omar Alshorman Samar Alqhtani Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadWah Campus22060Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Federal Urdu University of ArtsScience and TechnologyIslamabad44000Pakistan School of Electrical Engineering and Computer Science National University of Science and TechnologyIslamabad44000Pakistan Department of Computer Science and Engineering University of Engineering and TechnologyNarowal CampusLahore54000Pakistan Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia

In the Smart Grid(SG)residential environment,consumers change their power consumption routine according to the price and incentives announced by the utility,which causes the prices to deviate from the initial ***,electricity demand and price forecasting play a significant role and can help in terms of reliability and *** to the massive amount of data,big data analytics for forecasting becomes a hot topic in the SG *** this paper,the changing and non-linearity of consumer consumption pattern complex data is taken as *** minimize the computational cost and complexity of the data,the average of the feature engineering approaches includes:Recursive Feature Eliminator(RFE),Extreme Gradient Boosting(XGboost),Random Forest(RF),and are upgraded to extract the most relevant and significant *** this end,we have proposed the DensetNet-121 network and Support Vector Machine(SVM)ensemble with Aquila Optimizer(AO)to ensure adaptability and handle the complexity of data in the ***,the AO method helps to tune the parameters of DensNet(121 layers)and SVM,which achieves less training loss,computational time,minimized overfitting problems and more training/test *** evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark *** proposed method has achieved a minimal value of the Mean Average Percentage Error(MAPE)rate i.e.,8%by DenseNet-AO and 6%by SVM-AO and the maximum accurateness rate of 92%and 95%,respectively.

关键词： Smart grid deep neural networks consumer demand big data analytics load forecasting price forecasting

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