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检索条件"机构=dept. of Computer Technology Engineering"

共 17317 条记录，以下是481-490 订阅

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Enhancing Power Grid Resilience: Advanced Strategies for Detecting and Analyzing Faults in Three-Phase Transmission Lines

Enhancing Power Grid Resilience: Advanced Strategies for Det...

引用

2024 IEEE International Conference on Information technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Ahmed, Khandakar Rabbi Shayer, Khandokar Shadman Shuvo, Jahidul Islam Haque, F.M. Mahmudul Salam, Towfika Miraz, Shafiun Noman, Abdullah Al Sobuj, Md. Shohanur Islam Arafat, Md. Yaqub Rial, Md Istiak Hasan Miyan Research Institute International University of Business Agriculture and Technology Uttara Model Town Dhaka Bangladesh Dept. of Mechatronics Engineering Kazla Rajshahi6204 Bangladesh American International University-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Dept. of Computer Science and Engineering Rajshahi Bangladesh Jahangirnagar University Dept. of Institute of Information Technology Saver Dhaka1342 Bangladesh Hajee Mohammad Danesh Science and Technology University Dept. of Electrical and Electronic Engineering Dhaka Bangladesh International University of Business Agriculture and Technology Dept. of Mechanical Engineering Dhaka Bangladesh Dept. of Computer Science and Engineering Andhra Pradesh Kakinada533291 India

ISBN: (纸本)9798350382693

Power system fault analysis is a process that establishes the bus voltages and line currents when various fault types occur. Three-phase balanced faults and unbalanced faults are two categories of power system faults. Single line-to-ground, line-to-line, and double line-to-ground faults are three different types of unbalanced faults that can occur on transmission lines for power systems. Fault analysis is used to choose and set the proper protective devices and switchgear. Determining the bus voltages and line currents is critical while investigating power system issues. Numerous mathematical calculation techniques are shown in the process, which is challenging to do by hand. The calculation can be performed quickly on a computer using a Simulink created using MATLAB. However, an error occurs when inverting an extensive bus system's Y-bus to Z-bus in the conventional short circuit study;this paper offers a solution that is solved using 'MATLAB SIMULINK' to reduce error. © 2024 IEEE.

关键词： Power system analysis

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Sensitive Content Detection in Social Networks Using Deep Learning Models and Explainability Techniques 9

Sensitive Content Detection in Social Networks Using Deep Le...

引用

9th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2024

作者： Perikos, Isidoros University of Patras Computer Engineering and Informatics Department Patras Greece University of Peloponnese Computer Technology Institute and Press 'Diophantus' Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350394191

In the dynamic landscape of online social networks, recognizing sensitive content is essential for safeguarding user privacy, fostering inclusivity, and enhancing diversity awareness. Building on prior research, this study explores new dimensions and methodologies for detecting sensitive content. We examine the temporal evolution of sensitive content, revealing how patterns shift over time, and address cross-linguistic challenges, emphasizing cultural and contextual nuances in detection. We employ advanced machine learning techniques, including deep learning models and BERT that improve the accuracy and robustness of the detection procedure. In the experimental study, BERT transformer reported the best performance in detecting sensitive content in text. Additionally, we incorporate explainability techniques such as LIME and SHAP to provide deeper insights into the model's decision-making processes, ensuring predictions are interpretable and reliable. Our work enhances the theoretical framework of sensitive content detection in social networks and provide methods that are accurate and scalable and can facilitate the creation of user-centric interaction that prioritize privacy and user experience. © 2024 IEEE.

关键词： Adversarial machine learning

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Towards an integration management maturity 49

Towards an integration management maturity

引用

49th Euromicro Conference on Software engineering and Advanced Applications, SEAA 2023

作者： Hyrynsalmi, Sonja M. Olsson, Helena Holmstrom Bosch, Jan Lut University Dept. Software Engineering Lahti Finland Malmö University Dept. Computer Science and Media Technology Malmö Sweden Chalmers University of Technology Dept. Computer Science and Engineering Göteborg Sweden

ISBN: (纸本)9798350342352

As industries continue to digitize at a rapid pace, the number of integrations, the connections between different digital systems, is increasing. As a consequence, integration management is becoming increasingly difficult, leading to scalability, stability, and system outage problems that directly affect company performance. For that reason the modern integration management platforms have emerged to offer efficient management of the growing number of integrations, as well as a new way to handle, enrich, and utilize data both inside and outside *** research involved interviews with 20 software vendor professionals and 20 clients who had recently undergone an integration platform project. The study identified key drivers behind integration management projects and recognized different maturity levels in integration management. The results revealed that more mature companies are utilizing modern integration platforms to support their digital transformation. The study also highlighted the growing importance of data management and utilization in integration *** address these findings, a maturity model was developed to help companies evaluate their current integration management status and find ways to progress in their integration management. © 2023 IEEE.

关键词： Integration

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Smart CropGuard: Innovating Disease Detection with Inception CNN and LSTM Peephole Networks

Smart CropGuard: Innovating Disease Detection with Inception...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Ahmed, Menna Ahmed, Hamed Walid, Mostafa Kazem, Mohamed El Gohary, Maryam Gawad, Shahd Ibrahim, Mohamed Ashraf, Ahmed Ibraheem, Mai Ramadan Galala University Faculty of Computer Engineering Artificial intelligence engineering Dept. Egypt Kafrelsheiksh University Faculty of Computers and Information Head of Information Technology Dept. Egypt

ISBN: (纸本)9798350351408

Detecting plant leaf diseases is a novel approach for automated plant leaf disease detection, integrating the Inception Convolutional Neural Network (CNN) with Long Short-Term Memory (LSTM) networks enhanced with peephole connections. By synergistically leveraging these advanced deep learning architectures, our research aims to develop a comprehensive framework for precise and efficient disease detection, addressing challenges in traditional methods and advancing agricultural sustainability. © 2024 IEEE.

关键词： Convolutional neural networks

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Implementation of a Secure Cellular Stream Cipher System for Multimedia Encryption 100

Implementation of a Secure Cellular Stream Cipher System for...

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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Peri, Priyanka Dutta, Jayati Malkuchi, Rohith Indian Institute of Technology Dept. of Electrical Engineering Hyderabad India Virginia Polytechnic Institute and State University Dept. of Electronics and Computer Engineering Blacksburg United States

ISBN: (纸本)9798331517786

In this paper, we explore the implementation and performance of cellular stream cipher algorithms for multimedia encryption, marking the first comprehensive assessment within the cellular standards. We evaluate these algorithms across the formats like text, audio, images, and video, using key metrics to gauge their efficiency and suitability for secure communication. This work addresses a significant gap in the literature on secure multimedia transmission over cellular networks. © 2024 IEEE.

关键词： Ciphertext

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Photoplethysmography Signal Quality Assessment Using Neighbour Edge Restricted Horizontal Visibility Graph and Machine Learning Classifiers 16

Photoplethysmography Signal Quality Assessment Using Neighbo...

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16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Khan, Zahir Manikandan, M. Sabarimalai Mahmud, Mufti Indian Institute of Technology Palakkad Dept. of Computer Science and Engineering Kerala Palakkad678623 India Indian Institute of Technology Palakkad Dept. of Electrical Engineering Kerala Palakkad678623 India Nottingham Trent University Dept. of Computer Science Nottingham Clifton Lane United Kingdom

ISBN: (纸本)9798350371154

Photoplethysmography (PPG) signals are vital for monitoring pulse rate, blood pressure, and more, but they are prone to motion artefacts and noise, leading to unreliable data. Assessing PPG signal quality is crucial for reliable healthcare and accurate medical diagnoses. By transferring the PPG time domain signal to a Horizontal Visibility Graph (HVG) network and combining extracted features from HVG with machine learning algorithms, we can classify the PPG signal into clean (or high quality) and noisy. We have proposed a new version of HVG called Neighbour Edge Restricted Horizontal Visibility Graph (NERHVG) by invoking some extra conditions for joining edges in HVG for PPG signal quality assessment (SQA). We have used the average degree (AD) of graphs extracted from HVG, and NERHVG algorithms as features in 3 different machine learning classifiers such as Random Forest (RF), Gaussian Naive Bayes (GNB), Decision Tree (DT) to classify 4 standard untrained PPG datasets (DS). The classifier models DT, RF, GNB associated with graph feature AD of HVG, NERHVG algorithms are named as: DT-HVG, DT-NERHVG, RF-HVG, RF-HVG, RF-NERHVG, GNB-HVG and GNB-NERHVG. After all the performance of HVG and NERHVG algorithms using AD feature are compared over the mentioned classifier models. It is observed that the NERHVG algorithm outperformed the HVG algorithm with the AD feature in all 4 datasets with a maximum accuracy of: 99.09%, 95.03%, 96.56 % and 84.63% using the GNB classifier. © 2024 IEEE.

关键词： Decision trees

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Optimization of New Radio Physical Uplink Shared Channel Resources Allocation with Efficient Demodulated Referenced Signals and PT-RE Deployment

Optimization of New Radio Physical Uplink Shared Channel Res...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Upadhyay, Deepak Gupta, Mridul Sharma, Kunj Bihari Upadhyay, Abhay Yadav, Satya Prakash Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India Bennett University School of Computer Science Engineering and Technology Greater Noida India

ISBN: (纸本)9798350378092

This paper explores the resource allocation optimisation of New Radio Physical Uplink Shared Channels with an emphasis on the effective implementation of Phase Tracking Reference Signals and Demodulation Reference Signals in 5G networks. Understanding how important these reference signals are to dependable communication, we created a Python framework to model and display their distribution on a time-frequency grid. By carefully modifying important factors including mapping type, PRB allocation, and symbol allocation, our method greatly increased resource efficiency, decreased overhead, and improved signal quality. The results show how sophisticated resource allocation techniques may be used to maximise system performance, providing important information for the creation of more reliable and effective 5G NR communication systems © 2024 IEEE.

关键词： 5G mobile communication systems

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A New S-Box Design Approach for SNOW 3G Using the POS of Power Functions 16

A New S-Box Design Approach for SNOW 3G Using the POS of Pow...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

ISBN: (纸本)9798350383119

In this paper, we propose 'S-POS', an 8× 8 S-box as a more secure alternative to Snow 3G's existing S2 S-box. By leveraging the product of the sum (POS) of power functions in GF28), S-POS demonstrates superior performance in key metrics such as differential uniformity (DU), non-linearity (NL), and algebraic immunity (AI) compared to the traditional S2-box. Additionally, differential and linear cryptanalysis reveals that S-POS enhances the keystream's randomness, supporting its potential as a replacement for the current S2-box in the Snow 3G stream cipher. © 2024 IEEE.

关键词： Cryptosystem POS of power functions Stream cipher Substitution box

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A Comparative Analysis for Stroke Risk Prediction Using Machine Learning Algorithms and Convolutional Neural Network Model 3

A Comparative Analysis for Stroke Risk Prediction Using Mach...

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3rd International Conference on Electrical, computer and Communication engineering, ECCE 2023

作者： Ferdous, Most. Jannatul Shahriyar, Rifat Bangladesh University of Business and Technology Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350345360

A critical, sometimes fatal medical disease called a stroke happens when the blood flow to a portion of the brain is broken off. In the case of stroke, urgent treatment is very essential. Nowadays, stroke is the main cause of death and impairment globally, according to WHO. In this situation, it will be very helpful if we predict the probability of stroke earlier depending on some most important features. Many researchers use different machine learning algorithms for prediction but very few researchers use stacking methods and CNN. The main contribution of this paper is to develop a stacking classifier of ensemble methods and the CNN model. In this paper, data-set is collected from Kaggle. Stroke data is imbalanced. Random oversampling is used for balancing data-set. Then most important features are find out using feature selection method, then applying different machine learning algorithms such as Logistic Regression, Decision Tree Classifier, Support vector machine, Random forest classifier, KNearest neighbour's classifier, Bernoulli Naïve Bayes, Gaussian Naïve Bayes, Stacking of six algorithms (Decision Tree Classifier, Support vector machine, Random forest classifier, KNearest neighbor's classifier, Bernoulli Naïve Bayes, Gaussian Naïve Bayes) and CNN. Then comparing the performances for predicting the probability of stroke during both the training and testing periods. Results show that the Stacking of six algorithms gives the highest accuracy, which is 99.89% for testing and 100% for training. © 2023 IEEE.

关键词： Convolutional neural networks

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Beamforming and Phased Arrays: Elevating MIMO-OFDM Systems for Next-Generation Wireless Networks

Beamforming and Phased Arrays: Elevating MIMO-OFDM Systems f...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Yadav, Satya Prakash Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Bennett University School of Computer Science Engineering and Technology Greater Noida India

ISBN: (纸本)9798350378092

This study explores the optimisation of Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems through the use of phased arrays and advanced beamforming methods. With a focus on overcoming the challenges that come with 5G wireless communication, like high data rate needs, interference resistance, and efficient spectrum usage, this work presents a novel approach that combines dynamic beam steering and adaptive precoding to significantly enhance system performance. Through thorough modelling, we demonstrate considerable improvements in bit error rates (BER), throughput, and spectrum efficiency compared to traditional MIMO-OFDM configurations. The results demonstrate a 25% improvement in throughput and a 40% reduction in BER in densely populated metropolitan environments, underscoring the potential of phased arrays and beamforming to further improve 5G network performance. This work not only validates the efficacy of the proposed enhancements but also establishes a foundation for future advancements in wireless communication systems by highlighting the critical roles that phased arrays and beamforming will play in achieving the maximum potential of 5G technology. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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