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检索条件"机构=Department of Eng. and Tech. Computer Engineering"

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Advanced Particle Swarm Optimization: An Innovative Approach Towards Addressing Constrained Optimization Challeng.s

Advanced Particle Swarm Optimization: An Innovative Approach...

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2024 IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2024

作者： Hasan, Ashik Sarker, Sowmik Bhowmik, Angkita Ahmed, Pathik Chowdhury, Abdullahi Islam, Mohammad Manzurul Khulna University of Eng. and Tech. Dept. of Electrical and Electronic Eng. Khulna9203 Bangladesh Khulna University of Eng. and Tech. Dept. of Urban and Regional Planning Khulna9203 Bangladesh University of South Australia UniSA Online Adelaide Australia East West University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331535476

A refined version of the traditional particle swarm optimization (PSO) method for handling constraint-based optimization is described in this paper. Numerous academic fields, including economics, finance, a nd engineering, frequently encounter bounded optimization challeng.s. The presence of constraints that restrict the possible search area makes solving these problems particularly difficult. This study reviews various approaches to handling constraints in metaheuristic optimization algorithms, with a focus on particle swarm optimization (PSO). The proposed PSO approach incorporates a mutation operator to enhance the diversity of the search process and a penalty function to manage constraints effectively. Several benchmark problems from the literature are used to assess the performance of the proposed tech.ique. The outcomes are compared with those of various PSO variations and conventional optimization algorithms, demonstrating competitive performance by improving both convergence speed and solution quality. The analysis reveals that, in terms of convergence time and solution quality, the proposed method outperforms previous PSO variations and compares favorably with state-of-the-art optimization tech.iques. With potential applications across numerous fields, the proposed PSO method represents a promising approach to solving constraint-based optimization problems. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Post Quantum Digital Signature Change in IOTA to Reduce Latency in Internet of Vehicles (IoV) Environments

Post Quantum Digital Signature Change in IOTA to Reduce Late...

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2022 International Conference on IoT and Blockchain tech.ology, ICIBT 2022

作者： Verma, Nikhil Kumari, Swati Jain, Pranavi Electronics And Comm. Engineering Thapar Institute Of Eng. And Tech. Patiala India Computer Science And Engineering Thapar Institute Of Eng. And Tech. Patiala India

ISBN: (纸本)9781665424165

In the last decade, the Internet of Things has witnessed exponential growth in demand and development. The growth of IoT and the increasing need for automation have led to an exciting application in the transportation industry, namely the Internet of Vehicles (IoV). Simply put, IoV systems are vehicular ad-hoc networks (VANETs) enhanced by integrating them with automation over the internet. As briefly discussed in this paper, the IoV systems guarantee various advantages like a much safer and more efficient future. However, the primary challeng. at hand is implementing IoV at the end-user level. Of the varied building blocks present on the road to the development of IoV, secure data transfer is an essential requirement, especially with recent advances in quantum computing. IOTA is a Distributed Ledger tech.ology (DLT) specifically designed to secure IoT data transmissions. This paper discusses the advantages of implementing IOTA for secure and private IoV systems. The paper suggests replacing IOTA's current post-quantum signature scheme Winternitz One Time Signature (W-OTS) with CRYSTALS Dilithium. These two post-quantum signature schemes are evaluated against each other to establish that employing Dilithium reduces both latency and signature space required, bringing a significant improvement to IOTA. This improvisation is beneficial, especially for the fast-paced functioning of IoV environments. © 2022 IEEE.

关键词： Internet of things

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Optimizing Resource Allocation for Device to Device Communication in Cellular Networks 5

Optimizing Resource Allocation for Device to Device Communic...

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5th IEEE International Conference on Recent Trends in computer Science and tech.ology, ICRTCST 2024

作者： Salim, Abu Tiwari, Rajesh Kumar Siddiqui, Shams Tabrez Tahir, Ali Kamal, Mohammad Shahid Sarfaraz, Mohammad Jazan University College of Engineering and Computer Science Department of Computer Science Jazan Saudi Arabia RVS College of Eng. & Tech Department of Computer Science and Engineering Jamshedpur Jharkhand India

ISBN: (纸本)9798350351378

Device-to-device communication is a noteworthy tech.ology that can improve the efficiency and capacity of cellular networks. Efficient resource allocation is crucial in a cellular network that supports both device-to-device communication and traditional cellular users. To minimize interference and optimize the overall performance of the network, this allocation is necessary. The current study introduces a new framework aimed at improving the spectrum efficiency and quality of service in device-to-device interactions. The framework utilizes interference management tech.iques to achieve these enhancements. The research conducted encompasses a comprehensive examination of the subject matter, incorporating theoretical analysis, simulation results, and practical implications. This approach has been employed to effectively showcase the advantages and benefits associated with the proposed methodology. © 2024 IEEE.

关键词： Resource allocation

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An Improved Method to Find Location and Sizing of DG In IEEE-69 Bus Distribution System 2

An Improved Method to Find Location and Sizing of DG In IEEE...

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2nd IEEE International Conference on Advancements and Key Challeng.s in Green Energy and Computing, AKGEC 2024

作者： Saurabh, Kumar Prusty, B. Rajanarayan Kumar, Kanhaiya Galgotias University Department of Electrical Electronics and Communication Engineering Greater Noida India Galgotias College of Eng. and Tech. Department of Electrical and Electronics Engineering Greater Noida India

ISBN: (纸本)9798350390179

Getting more power is seen as one of the fastest effective means for nations to develop and one of the greatest challeng.s in the world at present. Countries have changed their strategies for utilizing renewable energies rather than nonrenewable sources of energy since there aren't many of them and utilizing them is terrible for the environment. Renewable energies are easy to get, never lose worth over time, and don't depend on fluctuations in price. This means they can be used more in energy systems today. The electrical grid will have to change because of the most suitable location to position these resources and the best way to utilizethem. There is an approach to sort through which and how large to put DG (distributed generation) in energy distribution networks so that there is as little energy reduction, voltage-age constraints, distributed generation loading constraints, current limits, and distributed generation in filtration constraints as possible. In the first step, you need to find the distributed generation feature that helps each bus the most. After that, pick the best spot for the distributed generation to ensure it helps every bus most effectively. This method is able to be used to figure out the number and location of both single and multiple DG. For determining the most suitable area for, size and power factor of distributed generation in the distributional structure, the Coot Bird Optimization tech.ique (CBOM) is proposed. The suggested method has been tested on Distributed Networking and IEEE 69-bus. The CBOM method that was mentioned is a good way to determine the best place, terms of sizes and power factors for distributed creation. It could also be used for other kinds of distribution structures. © 2024 IEEE.

关键词： Distributed energy

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WaveAttack: Asymmetric Frequency Obfuscation-based Backdoor Attacks Against Deep Neural Networks 38

WaveAttack: Asymmetric Frequency Obfuscation-based Backdoor ...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Xia, Jun Yue, Zhihao Zhou, Yingbo Ling, Zhiwei Shi, Yiyu Wei, Xian Chen, Mingsong MoE Eng. Research Center of SW/HW Co-design Tech. and App. East China Normal University China Department of Computer Science and Engineering University of Notre Dame United States

Due to the increasing popularity of Artificial Intelligence (AI), more and more backdoor attacks are designed to mislead Deep Neural Network (DNN) predictions by manipulating training samples or processes. Although backdoor attacks have been investigated in various scenarios, they still suffer from the problems of both low fidelity of poisoned samples and non-negligible transfer in latent space, which make them easily identified by existing backdoor detection algorithms. To overcome this weakness, this paper proposes a novel frequency-based backdoor attack method named WaveAttack, which obtains high-frequency image features through Discrete Wavelet Transform (DWT) to generate highly stealthy backdoor triggers. By introducing an asymmetric frequency obfuscation method, our approach adds an adaptive residual to the training and inference stages to improve the impact of triggers, thus further enhancing the effectiveness of WaveAttack. Comprehensive experimental results show that, WaveAttack can not only achieve higher effectiveness than state-of-the-art backdoor attack methods, but also outperform them in the fidelity of images (i.e., by up to 28.27% improvement in PSNR, 1.61% improvement in SSIM, and 70.59% reduction in IS). Our code is available at https://***/BililiCode/WaveAttack. © 2024 Neural information processing systems foundation. All rights reserved.

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Integrating Structural Information: Comparing Classification-Based and Segmentation-Based Predictors in Bioinformatics (case study: protein-peptide region residue-level interaction) using structural information 29

Integrating Structural Information: Comparing Classification...

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29th International computer Conference, computer Society of Iran, CSICC 2025

作者： Shafiee, Shima Fathi, Abdolhossein Safari, Faezeh Department of Computer Engineering and Information Technology Razi University Kermanshah Iran School of Electrical Eng. and Computer Science Faculty of Eng. Architecture and Info. Tech University of Queensland BrisbaneQLD Australia

ISBN: (纸本)9798331523114

Understanding the regions where proteins bind to peptides is vital for studying diseases like cancer, as it sheds light on various cellular processes and aids in drug discovery. Although researchers can experimentally investigate protein-peptide interactions at the region level by analyzing the structures of their complexes, only a limited number of these structures are known. Additionally, experiments to determine these interactions can be both costly and time-consuming. Computational methods provide an alternative and complementary approach to experimental tech.iques. As a result, using computational methods to predict peptide-binding regions can significantly enhance the efficiency and cost-effectiveness of experimental research. To leverage these advantages, this study introduces a new method named Structure-based Prediction of Residue-level Interaction of Peptides (SPRINT-Pep), designed to pinpoint the binding regions between proteins and peptides. This approach leverages two distinct predictive models: a classification-based model combining DeepResNet with a Support Vector Machine (SVM) and a segmentation-based model called DeepU-Net. Our predictions outperform other state-of-the-art methods in terms of F-measures (by at least 23%), precision (by at least 3.7%), and the balance between sensitivity and specificity (by about 7.7%). These findings demonstrate the proficiency of the proposed method. © 2025 IEEE.

关键词： Bioinformatics

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Nonlinear Sub-Optimal Control of SIR Infectious Disease Model 3

Nonlinear Sub-Optimal Control of SIR Infectious Disease Mode...

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3rd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Islam, Samiul Paul, Sudipta Pramanik, Md. Abu Hanif Bhattacharjee, Srijita Naidu, D. Subbaram Rajshahi University Of Eng. & Tech. Electrical & Computer Engineering Rajshahi Bangladesh Rensselaer Polytechnic Institute Electrical Engineering New York United States University Of Minnesota Duluth Electrical Engineering Duluth United States

ISBN: (纸本)9798350318609

The Susceptible-Infectious-Recovered (SIR) disease model is a basic epidemiological framework for analyzing the spread of infectious diseases using various control theories. It plays a vital role in assessing disease control strategies and minimizing the impact of an infectious disease. This paper employs a nonlinear closed-loop infinite-horizon optimal tracking control via state-dependent Riccati equation (IH-SDRE) to the nonlinear SIR model with vaccination, aiming to reduce the number of infected individuals within a desired timeframe. This method, by transforming the nonlinear SIR model into a state-dependent coefficient form, solves the Riccati equation and the vector equation at every time step to determine the control law. The results obtained via MATLAB/Simulink demonstrate that the IH-SDRE minimizes the number of infected populations, reducing it to nearly zero within 30 days of the desired timeframe with an effective vaccination strategy. The findings show the effectiveness of the IH-SDRE as a robust method in the control and mitigation of infectious diseases. © 2024 IEEE.

关键词： Riccati equations

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Beat-wise Classification of Arrhythmia Using Novel Combination of ECG Signal-Specific and Signal-Independent Features with ML Algorithms 26

Beat-wise Classification of Arrhythmia Using Novel Combinati...

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26th International Conference on computer and Information tech.ology, ICCIT 2023

作者： Showmik, Ishtiaque A. Sadik, Farhan Morshed, Bashir I. Farah Sanam, Tahsina Bangladesh Univ. of Engineering & Tech. Department of Electrical & Electronic Eng. Dhaka1205 Bangladesh Texas Tech University Department of Computer Science LubbockTX79409 United States Bangladesh Univ. of Engineering & Tech. Institute of Appropriate Technology Dhaka1205 Bangladesh

ISBN: (纸本)9798350359015

Cardiovascular diseases (CVDs) can be diagnosed using electrocardiogram (ECG/EKG) data, which depict the electrical activity of the heart and provide information on the leng.h, peaks, and forms of each waveform. The field of smart health (sHealth) may greatly benefit from the use of wearables in cyber-physical systems (CPS) and the ability to analyze this signal with artificial intelligence (AI) for continuous or remote cardiac monitoring. In this work, we present an AI method based on machine learning (ML) that can quickly and accurately classify ECG beats. First, we extract signal-specific features, then rank and choose the top features using several feature selection tech.iques (ROCAUC, RFE, CQCDF). Then, using discrete wavelet transformation to extract signal-independent characteristics, we get approximation coefficients. Next, we apply a subband selection tech.ique to the group and choose the optimal levels of approximation coefficient based on mutual information and signal energy. Finally, we combine the chosen subbands with the signal-specific features. Using the support vector machine (SVM), random forest (RF), K-nearest neighbor (KNN), and decision tree ML classifiers, we assessed the performance of the ECG beat classification at various stages and with various combinations of features. We used SVM to get 97 percent accuracy, precision, recall, and F1-score for each. For wearable devices, our beat-by-beat classification algorithm identifies ECG data instantly. Our proposed approach reduces the number of features needed and combines effective feature selection and subband selection methods. © 2023 IEEE.

关键词： ECG classification machine learning wavelet transformation

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A Novel Geometric Visualization of Dual-lead ECG Signals for Beat-by-beat Arrhythmia Detection with a 2D CNN Deep Learning Classifier 26

A Novel Geometric Visualization of Dual-lead ECG Signals for...

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26th International Conference on computer and Information tech.ology, ICCIT 2023

作者： Sadik, Farhan Showmik, Ishtiaque A. Morshed, Bashir I. Sanam, Tahsina Farah Bangladesh Univ. of Engineering & Tech. Department of Electrical & Electronic Eng. Dhaka1205 Bangladesh Texas Tech University Department of Computer Science LubbockTX79409 United States Bangladesh Univ. of Engineering & Tech. Institute of Appropriate Technology Dhaka1205 Bangladesh

ISBN: (纸本)9798350359015

Electrocardiogram (ECG) has become prevalent for identifying irregular heartbeats, known as arrhythmia. Thanks to the rapid advancements in deep learning (DL), the application of DL-based ECG classification has reached its highest level of effectiveness in detecting arrhythmia, leading current research in this area. However, the integration of the onedimensional (1D) nature of ECG signals into widely used deep learning networks while ensuring compatibility with medical practitioners' interpretability remains an unexplored domain. This paper presents a novel 2D depiction of dual-lead ECG signals to detect arrhythmia that maintains consistency with the 1D ECG signal's interpretability while also enhancing efficiency when incorporated into a deep learning network. Specifically, the method proposed in this work employs an innovative approach to transform the dual-lead ECG signals into a 2D image in the spatial domain. Subsequently, this transformed representation is integrated with ResNet-18 Convolutional Neural Network (CNN) to effectively identify four classes (AAMI EC57 standard) of arrhythmia from the MIT-BIH arrhythmia dataset following the inter-patient scheme. Our proposed method not only ensures interpretability but also exhibits superior performance compared to STFT-based transformations in accurately classifying four different categories of heart activity. It achieves an F1 score of 97.3% for normal heartbeats and overall accuracy of 94.2%, which showcases its effectiveness. © 2023 IEEE.

关键词： Arrhythmia beat-by-beat classification deep learning ECG geometric visualization

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Optimal Planning of Synchronous Condensers Considering the Impact of Inverter-Based Resources

Optimal Planning of Synchronous Condensers Considering the I...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Fouladi, Ehsan Mehrizi-Sani, Ali Bahrani, Behrooz Virginia Tech Bradley Department of Electrical & Computer Engineering BlacksburgVA United States Monash University Department of Electrical & Computer Systems Eng. ClaytonVIC3800 Australia

ISBN: (纸本)9798350376067

Power systems with a higher share of inverter-based resources (IBR) have less streng.h and inertia, which are otherwise provided by synchronous generators (SG). In the case of a contingency, lack of streng.h (measured by short-circuit ratio [SCR]) and inertia may cause subsynchronous resonance and undamped oscillations. Synchronous condensers (SynCon) can be used to tackle these challeng.s as they offer voltage regulation and physical inertia. The utilization of a new SynCon unit is an expensive solution due to its high total cost, including installation, operation, and maintenance costs. The total cost of a new SynCon can be minimized by finding its optimal size and location. This paper proposes an optimization method to find the optimal location and size of SynCons, aiming to minimize their total costs and keep SCR above a certain level. This work considers the fault current contribution of each IBR and incorporates them into SCR calculation for the SynCons planning problem. This is particularly important in weak grids dominated by IBRs. The results of simulation studies on a modified version of the IEEE 39-bus system show that the presented method installs smaller sizes of SynCons in comparison to two previously proposed methods. © 2024 IEEE.

关键词： Power system planning short-circuit ratio synchronous condenser weak power system

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