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2022 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2022

作者： Tsushima, Honami Sviridova, Nina Ikeguchi, Tohru Department of Information and Computer Technology Graduate School of Engineering Tokyo University of Science Katsushika-ku Tokyo Japan Department of Information and Computer Technology Faculty of Engineering Tokyo University of Science Katsushika-ku Tokyo Japan

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

The bicycle sharing system (BSS) is one of the eco-friendly transportation systems introduced in major cities world-wide. However, BSS faces one crucial challenge: an imbalance of bicycles among the ports, because users are free to rent and return bicycles freely. It is necessary to restore the bicycles among the ports using vehicles to overcome this issue. We have already proposed search strategies for finding the tours of the vehicles in a reasonable time frame. In our previously proposed method, we used the tabu search which harnesses executing two local searches: the CROSS-exchange and the Or-opt. In the numerical experiment, we used instances with uniformly distributed ports to evaluate the performance of our previous method;however, real BSS ports are not uniformly distributed. Thus, in this paper, we use instances with real port distributions from four BSSs (Boston, Washington D.C., New York, Chicago) to investigate whether our method is effective for non-randomly distributed ports of larger-size instances (200 ports). From the numerical experiments, our proposed method is also effective for instances based on real BSS port locations. © 2022 IEEE.

关键词： Tabu search

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Cardiovascular Health Risk Prediction Using Bayesian Predictive Analytics Approach 5th

Cardiovascular Health Risk Prediction Using Bayesian Predict...

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5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Shantanu, Kumar Singhal, Priya Mishra, Sushruta Sharma, Ruchi Obaid, Ahmed J. Kalinga Institute of Industrial Technology Deemed to be University Bhubaneswar India Department of ECE Bharati Vidyapeeth’s College of Engineering Delhi India Faculty of Computer Science and Mathematics University of Kufa Najaf Iraq

ISBN: (纸本)9789819763177

A correct CVD diagnosis and outcome, on the other hand, result in expedited patient care and highly accurate treatment, as well as good results. Medicine has turned to machine learning since it is capable of discerning intricate patterns from vast data set insights. This study seeks to reduce the risk of miscategorizing CVD events and subsequently decrease CVD death rates by using machine learning methods. As a result, a more sophisticated approach outlined: RF, Decision Tree, MP, and XGB as the best current computer program in the proposed system. To refine the sorting capability of the model, a revolutionary method produce, including a K-modes grouping and a Huang starting point technique to increase sorting the stuff more effectively. Using an actual data from Kaggle dataset which had 4240 examples, our models were trained and tested. After rigorous evaluation, the models demonstrated noteworthy accuracy rates: Decision Tree achieved 72.81%, XGBoost exhibited 83.33%, Random Forest attained 83.61%, Naive Bayes achieved 81.01%, and Multilayer Perceptron outperformed others with an accuracy of 77.32%. Moreover, effectiveness of the model was calculated by using the Area Under the Curve (AUC), which resulted in outstanding predictive capabilities. Specifically, XGBoost and Random Forest both achieved an AUC of 0.58, with support vector machine (SVM) model outperforming all, boasting an accuracy level of 83.33%, an AUC score of 0.58, highlighting their robustness in predicting CVD occurrences. An observation from this study tells the superiority of the brain-like network model (MPM), particularly at the time matched with cross-checking. It resulted in achieving an exceptional success rate of 87.28%. The research developed not only focuses on the area of predicting heart diseases but also lays emphasis on the potential of machine learning methods to transform medical diagnostics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Patient treatment

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Fitting’s Style Many-Valued Interval Temporal Logic Tableau System: Theory and Implementation 31

Fitting’s Style Many-Valued Interval Temporal Logic Tableau...

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31st International Symposium on Temporal Representation and Reasoning, TIME 2024

作者： Badia, Guillermo Noguera, Carles Paparella, Alberto Sciavicco, Guido Stan, Ionel Eduard School of Historical and Philosophical Inquiry University of Queensland Brisbane Australia Department of Information Engineering and Mathematics University of Siena Italy Department of Mathematics and Computer Science University of Ferrara Italy Faculty of Engineering Free University of Bozen-Bolzano Italy

ISBN: (纸本)9783959773492

Many-valued logics, often referred to as fuzzy logics, are a fundamental tool for reasoning about uncertainty, and are based on truth value algebras that generalize the Boolean one;the same logic can be interpreted on algebras from different varieties, for different purposes and pose different challenges. Although temporal many-valued logics, that is, the many-valued counterpart of popular temporal logics, have received little attention in the literature, the many-valued generalization of Halpern and Shoham’s interval temporal logic has been recently introduced and studied, and a sound and complete tableau system for it has been presented for the case in which it is interpreted on some finite Heyting algebra. In this paper, we take a step further in this inquiry by exploring a tableau system for Halpern and Shoham’s interval temporal logic interpreted on some finite FLew-algebra, therefore generalizing the Heyting case, and by providing its open-source implementation. © Guillermo Badia, Carles Noguera, Alberto Paparella, Guido Sciavicco, and Ionel Eduard Stan.

关键词： Temporal logic

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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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Price Prediction of Seasonal Items Using Time Series Analysis

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computer Systems science & engineering 2023年第7期46卷 445-460页

作者： Ahmed Salah Mahmoud Bekhit Esraa Eldesouky Ahmed Ali Ahmed Fathalla Faculty of Computers and Informatics Zagazig UniversitySharkeya44523Egypt Information Technology Department the University of Technology and Applied SciencesIbriOman School of Electrical and Data Engineering University of Technology SydneySydney2007Australia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Computer Science Department Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Higher Future Institute for Specialized Technological Studies Cairo3044Egypt Department of Mathematics Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

The price prediction task is a well-studied problem due to its impact on the business *** are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change,but there is very limited work to study the price prediction of seasonal goods(e.g.,Christmas gifts).Seasonal items’prices have different patterns than normal items;this can be linked to the offers and discounted prices of seasonal *** lack of research studies motivates the current work to investigate the problem of seasonal items’prices as a time series *** proposed utilizing two different approaches to address this problem,namely,1)machine learning(ML)-based models and 2)deep learning(DL)-based ***,this research tuned a set of well-known predictive models on a real-life *** models are ensemble learning-based models,random forest,Ridge,Lasso,and Linear ***,two new DL architectures based on gated recurrent unit(GRU)and long short-term memory(LSTM)models are ***,the performance of the utilized ensemble learning and classic ML models are compared against the proposed two DL architectures on different accuracy metrics,where the evaluation includes both numerical and visual comparisons of the examined *** obtained results show that the ensemble learning models outperformed the classic machine learning-based models(e.g.,linear regression and random forest)and the DL-based models.

关键词： Deep learning price prediction seasonal goods time series analysis

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Fundamental Limits of Doppler Shift-Based, ToA-Based,and TDoA-Based Underwater Localization

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1637-1639页

作者： Zijun Gong Cheng Li Ruoyu Su Hong Kong University of Science and Technology(Guangzhou) IOT ThrustGuangzhou 511400 Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong Kong 999077China Faculty of Engineering and Applied Science Memorial University of NewfoundlandNewfoundland A1B 3X5Canada School of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China

Dear Editor,This paper is concerned with the underwater localization based on acoustic signals. Specifically, we will focus on the search of an underwater target that can constantly broadcast a beacon signal, such as a black box. Common measurements for localization are Doppler shift [1], time of arrival(ToA) [2]–[4], time difference of arrival(TDoA) [5], [6], angle of arrival(AoA) [7], etc.

关键词： TDoA ToA underwater

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Service-the-Longest-Queue Among d Choices Policy for Quantum Entanglement Switching

Service-the-Longest-Queue Among d Choices Policy for Quantum...

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Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Guo Xian Yau Thirupathaiah Vasantam Gayane Vardoyan Faculty of Electrical Engineering Mathematics and Computer Science and QuTech TU Delft The Netherlands Department of Computer Science Durham University UK Manning College of Information and Computer Sciences University of Massachusetts Amherst USA

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

An Entanglement Generation Switch (EGS) is a quantum network hub that provides entangled states to a set of connected nodes by enabling them to share a limited number of hub resources. As entanglement requests arrive, they join dedicated queues corresponding to the nodes from which they originate. We propose a load-balancing policy wherein the EGS queries nodes for entanglement requests by randomly sampling d of all available request queues and choosing the longest of these to service. This policy is an instance of the well-known power-of-d-choices paradigm previously introduced for classical systems such as data-centers. In contrast to previous models, however, we place queues at nodes instead of directly at the EGS, which offers some practical advantages. Additionally, we incorporate a tunable back-off mechanism into our load-balancing scheme to reduce the classical communication load in the network. To study the policy, we consider a homogeneous star network topology that has the EGS at its center, and model it as a queueing system with requests that arrive according to a Poisson process and whose service times are exponentially distributed. We provide an asymptotic analysis of the system by deriving a set of differential equations that describe the dynamics of the mean-field limit and provide expressions for the corresponding unique equilibrium state. Consistent with analogous results from randomized load-balancing for classical systems, we observe a significant decrease in the average request processing time when the number of choices d increases from one to two during the sampling process, with diminishing returns for a higher number of choices. We also observe that our mean-field model provides a good approximation to study even moderately-sized systems.

关键词： Quantum entanglement Network topology Computational modeling Stars Switches Differential equations Mathematical models Quantum networks Load modeling

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Novel optimal region based robust watermarking using modified dragonfly optimization algorithm

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International Journal of Information Technology (Singapore) 2025年第2期17卷 851-858页

作者： Shamna, N.V. Kaur, Puneet Raghavendra Patil, G.E. Krishna, Nanditha P A College of Engineering Dept of CSE (IoT & amp Cyber Security including Blockchain Technology) Karnataka India EEE UIET Panjab University Chandigarh India Department of Computer Science and Engineering Faculty of Engineering and Technology Jain Deemed-to be University Karnataka Bengaluru 562112 India Department of Medical Electronics Engineering Dayananda Sagar College of Engineering Bengaluru India

The growing concern about unauthorized access and tampering with digital images requires the development of robust and secure watermarking methods. Traditional approaches frequently struggle with achieving a balance between security, image quality, and watermark strength, especially in high-resolution images. This study addresses these issues by proposing a new watermarking technique that combines the Blowfish encryption algorithm, the Discrete Wavelet Transform (DWT), and the Modified dragonfly optimization algorithm (MDFOA). The proposed approach begins with the Blowfish algorithm encrypting the secret image, providing increased security even if the watermark is detected. High-frequency features are preserved by embedding the encrypted watermark within the LL subband of the cover image, which is generated using DWT decomposition. MDFOA is used to identify the best embedding places inside the LL subband, which improves the watermark's concealment and resilience. The same methodology is used to repeat the extraction process, providing reliable and secure data transmission throughout the process. The proposed method is a highly effective solution for secure and high-quality image watermarking. It outperforms existing techniques in terms of Peak Signal-to-Noise ratio (PSNR), Normalized correlation (NC), Bit error rate (BER), and Normalized absolute error (NAE), according to extensive experiments conducted on a variety of high-resolution images. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Blowfish encryption algorithm Discrete wavelet transform Modified dragonfly optimization algorithm Watermarking technique

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Digital-Bracers: A Design Process for an Interactive Monitoring Generative System That Helps People with Hand Movements

Digital-Bracers: A Design Process for an Interactive Monitor...

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2023 International Symposium on World Ecological Design, ISWED 2023

作者： Yao, Yousheng Xie, Yuan Ying, Fangtian Wang, Haoran Huang, Zhihao Zheng, Junpeng Faculty of Humanities and Arts Macau University of Science and Technology China Hexiangning College of Art and Design Zhongkai University of Agriculture and Engineering China College of Computer and Cyber Security Fujian Normal University China

ISBN: (纸本)9781643685069

In the post-New Crown epidemic era, people need to face a period of physical recovery after being infected with New Crown, especially when there are frequent cases of deaths due to over-aggressive or excessive physical exercise after healing, or due to people's concerns about safety hazards, or loss of interest and adherence to fitness due to exercising alone, among other problems. In this paper, we design a complete interactive monitoring generation system for wrist brace components, Digital-Bracers, which consists of both hardware and software. The hardware has integrated textile heart rate monitoring and integrated sensors in a three-lead configuration for a textile-based digital wrist brace that conforms to human comfort. The software is a visualized app with pulse rate, speed, and frequency, oscillation rhythm, content generation social connectivity, etc. The software and hardware are connected via WI-FI or Bluetooth. Through exploration of materials, ergonomics, and textile wrist guard construction, we designed an experimental process and tested Digital-Bracers to determine the system's performance through peak heart rate detection and noise interference. The contribution of the Digital-Bracers Interactive Monitoring and Generation System is the ability to monitor one's own health in real-time during hand exercise to avoid potential risks, while at the same time, The Digital-Bracers Interactive Monitoring System contributes to the real-time monitoring of one's health during hand movements to avoid potential risks, and to the generation of a variety of different sounds to bring a sense of fulfillment and enjoyment to the hand movements. © 2024 The Authors.

关键词： Textiles

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A Distributed Framework for Large-scale Protein-protein Interaction Data Analysis and Prediction Using MapReduce

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 160-172页

作者： Lun Hu Shicheng Yang Xin Luo Huaqiang Yuan Khaled Sedraoui MengChu Zhou School of Computer Science and Technology Dongguan University of TechnologyDongguan 523808China School of Computer Science and Technology Wuhan University of TechnologyWuhan 430070China Chongqing Engineering Research Center of Big Data Application for Smart Cities and Chongqing Key Laboratory of Big Data and Intelligent ComputingChongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China Xinjiang Technical Institute of Physics and Chemistry Chinese Academy of SciencesUrumqi 830000China Center of Research Excellence in Renewable Energy and Power Systems and the Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA

Protein-protein interactions are of great significance for human to understand the functional mechanisms of *** the rapid development of high-throughput genomic technologies,massive protein-protein interaction(PPI)data have been generated,making it very difficult to analyze them *** address this problem,this paper presents a distributed framework by reimplementing one of state-of-the-art algorithms,i.e.,CoFex,using *** do so,an in-depth analysis of its limitations is conducted from the perspectives of efficiency and memory consumption when applying it for large-scale PPI data analysis and *** solutions are then devised to overcome these *** particular,we adopt a novel tree-based data structure to reduce the heavy memory consumption caused by the huge sequence information of *** that,its procedure is modified by following the MapReduce framework to take the prediction task distributively.A series of extensive experiments have been conducted to evaluate the performance of our framework in terms of both efficiency and *** results well demonstrate that the proposed framework can considerably improve its computational efficiency by more than two orders of magnitude while retaining the same high accuracy.

关键词： Distributed computing large-scale prediction machine learning MapReduce protein-protein interaction(PPI)

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