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Machine Learning-Based Big Data Analytics in Smart Cities: A Survey of current trends and Future Research Directions 11

Machine Learning-Based Big Data Analytics in Smart Cities: A...

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11th ieee/ACM international conference on Big Data computing, Applications and Technologies, BDCAT 2024

作者： Althabahi, Mariam Hassan Ahmad Jan, Mian Brik, Bouziane Foufou, Sebti University of Sharjah College of Computing and Informatics Department of Computer Science Sharjah27272 United Arab Emirates

ISBN: (纸本)9798350367300

Efficient utilization of Big data in smart cities is crucial for smooth operation of urban environments. Machine learning-enabled big data analytics is essential for optimizing city operations, improving resource management, and enhancing the quality of urban life. By leveraging machine learning (ML) algorithms to process and analyze the vast amounts of data generated in smart cities, authorities can gain insights and make real-time data-driven decisions. This article provides a comprehensive survey of how ML techniques are applied to analyze the large volumes of data generated by smart cities to improve urban living. Various ML algorithms, such as supervised, unsupervised, and reinforcement learning (RL) are discussed by highlighting their roles in numerous applications. Moreover, their distinguishing features are examined, enabling the selection of the most suitable algorithms for various applications in smart cities. Finally, the survey explores various challenges and suggests numerous research directions. © 2024 ieee.

关键词： Adversarial machine learning

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Resolving optimal power flow issue on ieee 57 bus system having renewable energies by MMKE algorithm 3

Resolving optimal power flow issue on IEEE 57 bus system hav...

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3rd international conference on Intelligent Systems, advanced computing, and Communication, ISACC 2025

作者： Sutradhar, Argha Sarkar, Tushnik Paul, Chandan Dutta, Susanta Roy, Provas Kumar Dr. B. C. Roy Engineering College Electrical Engineering Durgapur India Kalyani Government Engineering College Electrical Engineering Kalyani India

ISBN: (纸本)9798331523893

In the current paper, optimal power flow (OPF) issue has been addressed using Multi-trial vector based monkey king evolution (MMKE). The test system is standard ieee 57 bus network where renewable energy sources (RESs) like wind power (WP), solar photovoltaic power ( PV) and plugin electric vehicle (PEV) are being incorporated with traditional units. Objective of the study includes minimization of overall generation cost and emission. To deal with stochastic RESs, appropriate probability density functions (PDF) are utilized. The test results are contrasted with contemporary study. One way ANOVA has been conducted on the sample results to statistically validate the superior performance of MMKE. © 2025 ieee.

关键词： Solar fuels

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Exploring Computational Linguistics Techniques for Enhanced Outing Planning: A Comprehensive Review 4

Exploring Computational Linguistics Techniques for Enhanced ...

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4th international conference on advanced Research in computing, ICARC 2024

作者： Muthaliff, Faizan Sumanathilaka, T.G.D.K. School of Computing Informatics Institute of Technology Colombo06 Sri Lanka Swansea University Department of Computer Science Wales Swansea United Kingdom

ISBN: (纸本)9798350384864

In this day and age where convenience is king a new competitor in the form of chat-bots has appeared which requires users to only have prior knowledge on the language the chat-bot converses in. When it comes to planning outings there are a multitude of criteria to be wary of to determine the ideal solution. This review paper will address the common issues with extracting meaningful information from the user utilizing modern NLP techniques, the required criteria in addition to the user input such as, real time weather information and communicable diseases pertaining to the outing location, to determine an ideal suggestion and finally the method in which said ideal suggestion is determined after prioritizing criteria. The conclusion underscores that while NLP applications might not entirely replace existing menu-based systems for outing planning, they excel in certain scenarios. Notably, NLP's innate capacity to comprehend user preferences and context allows it to offer tailored outing suggestions. Furthermore, the application's unique feature of dynamically adapting to user requests without necessitating a return to the home page adds a distinctive advantage to its usability. © 2024 ieee.

关键词： Natural language processing systems

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Performance Evaluation of Clustering Algorithms for Enhancing Test Case Prioritization in Regression Testing 4

Performance Evaluation of Clustering Algorithms for Enhancin...

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4th international conference on advanced Research in computing, ICARC 2024

作者： Puviskar, S. Prabath Wasalthilaka, W.V.S.K. Kumara, B.T.G.S. Sabaragamuwa University of Sri Lanka Department of Computing & Information Systems Sri Lanka Sabaragamuwa University of Sri Lanka Department of Software Engineering Sri Lanka

ISBN: (纸本)9798350384864

Regression testing plays a crucial role in maintain software quality as applications evolving and getting more complex. Selection of a regression testing technique significantly influences overall software quality. In initial stages, this involves picking relevant test cases and remove unnecessary redundancies during minimization phase. Finally, prioritization of test cases phases most important ones is executed first which continue process iteratively or whole testing carried out which effect time and cost intensively. Test Case Prioritization method effective way to address the issue. In this study, we proposed approach to enhance Test Case Prioritization by integrating fault based methods and time of execution analysis. The study also evaluates the efficiency in proposed methodology through, employing APFD metric. The study aims to improve the precision and effectiveness of test case prioritization methods, advancing overall quality and reliability in dynamic software development environments. Notably, AHC outperforms in comparisons, showcasing its efficacy in improving outcomes. © 2024 ieee.

关键词： Software testing

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Enhancement of Containerization-based Cloud computing Performance using Hybrid Metaheuristic Optimization Algorithm: A Review 3

Enhancement of Containerization-based Cloud Computing Perfor...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Ramasamy, G. Kamalakkannan, S. Vels Institute of Science Technology & Advanced Studies Department of Computer Science School of Computing Sciences Pallavaram Chennai India Vels Institute of Science Technology & Advanced Studies Department of Information Technology School of Computing Sciences Pallavaram Chennai India

ISBN: (纸本)9798331509675

Container-based virtualisation has become a cornerstone of Cloud computing (CC) due to its lightweight and scalable properties when compared to traditional virtual machines. However, it is still difficult to optimising resource allocation in containerised systems, and current approaches frequently fall short in addressing problems like high computational costs, scalability, cold-start scenarios, and Graphics Processing Unit (GPU) management. Container resource allocation is critical for effectively managing computing workloads in cloud settings, enabling scalability, performance optimization, and cost effectiveness. It is extensively used in a various industry, including e-commerce, healthcare, and finance, where dynamic workloads call for efficient resource management. Traditional resource allocation techniques, while their importance, frequently face difficulties such as unequal load distribution and resource underutilization. To address these constraints, this paper suggests a hybrid metaheuristic optimization algorithm that addresses limitations such as network distance, execution time, and migration costs to provide balanced load distribution. This study attempts to analyse the efficiency, time consumption and latency of resource allocation in dynamic cloud systems by addressing existing limitations. © 2025 ieee.

关键词： Cloud platforms

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current Advancements in Radar Communication and its Future Research Directions

Current Advancements in Radar Communication and its Future R...

引用

2023 international conference on Circuit Power and computing Technologies, ICCPCT 2023

作者： Judice, Antony Livin, Joel James, Aaron Bharathi, Subha University of Technology and Applied Sciences Department of Engineering Ibri Oman University of Technology and Applied Sciences Department of Engineering Ibra Oman

ISBN: (纸本)9798350333244

Radars are playing a vital role in the field of electronic warfare, ground observation, different military applications, speed recognition of an objects, air traffic management, etc. It is an inescapable part for Tele-Communications. All of these systems must be capable of carrying out various jobs and have significant power gains, adaptive beamforming, faster scanning rates, low detection probabilities, high dependability, and low maintenance costs. Many of the updated radar systems and methods are taking the place of the outdated ones. This examination will deliver a thorough idea of the developments in radars, and current trends. current radar systems, such as sophisticated scanning methods, GPS-based landing systems, passive radars with multiliterate, 3D radars, Long and short-range Radars for Autonomous Vehicles, and satellite monitoring radars, are briefly discussed in this paper. The Radars being used in the advanced jet fighters also discussed. Certainly, all the secondary Radars would be replaced by Passive Radars and Satellites in near future. All the current research potential areas in modern Radar Communication are mentioned in this paper that would helpful for the early researchers in this vibrant field. © 2023 ieee.

关键词： Optical radar

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A Systematic Literature Review of XAI-based Approaches on Brain Disease Detection using Brain MRI Images 4

A Systematic Literature Review of XAI-based Approaches on Br...

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4th international conference on advanced Research in computing, ICARC 2024

作者： Madapatha, Savin Fernando, Pumudu University of Westminster Department of Computer Science and Engineering London United Kingdom School of Computing Informatics Institute of Technology Colombo Sri Lanka

ISBN: (纸本)9798350384864

Brain Magnetic Resonance Imaging (MRI) analysis is a widely used medical procedure for the early diagnosis of various brain diseases. Accurate pathology identification during the brain MRI analysis procedure is crucial as misdiagnoses or missed findings can greatly affect a patient's treatment and long-term prediction. With the recent advancement of Artificial Intelligence (AI) in the medical field, researchers have approached various techniques to detect brain diseases using AI. Although AI models exhibit high accuracy, they suffer from a lack of transparency and interpretability, paving the way for the development of eXplainable Artificial Intelligence (XAI) methods in brain disease diagnosis. Image segmentation, machine learning, deep learning and XAI are important for assisting the diagnostic procedure. In this paper, a comprehensive overview of various existing techniques in brain disease detection using MRI is presented, starting with image segmentation techniques, followed by classification techniques, and finally, XAI techniques. In conclusion, the paper identifies a critical need for further research on XAI integration to advance brain disease detection. © 2024 ieee.

关键词： Magnetic resonance imaging

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Overview of Security Approaches for Quantum computing in the current Era 3

Overview of Security Approaches for Quantum Computing in the...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Hansora, Pinal Prajapati, Viral Thakkar, Amit Rathod, Ajaysinh Mannanuddin, Khaja Alsarmi, Haitham Said Naseer Cspit Charusat Cse Department Changa388421 India Snpit It Department Umrakh India Department of Computer Science & Design Gujarat Vasad India Sr University School of Cs & Ai Department of Computer Science & Engineering Hasanparthy Warangal India Sohar International Bank Muscat Oman

ISBN: (纸本)9798331509675

Quantum computing are breakthroughs aimed to revolutionize several sectors, although they also present considerable cybersecurity threats. Quantum computers can manage quite greater quantities of information than the most powerful conventional supercomputers and has the capability to do complex computations. Despite being in the early stages of development, quantum computers have the potential to be regarded as cybersecurity concerns. Quantum computing is a phenomenon that should be seen as a technology primed to facilitate significant innovations in the future, while also presenting different concerns. The quantum cybersecurity threat encompasses data breaches of sensitive health and financial information, challenges to the integrity of digital assets, and vulnerabilities in the encryption supporting cryptocurrencies, among other possible risks. This review paper focuses on quantum computing and its effects on different security methods in the present generation. It covers the quantum computer threats to cryptography, post quantum cryptography and a comparison of different approaches to cryptography. This work also analyzes machine learning and AI in quantum security and its challenges and trends for the future. The literature review has incorporated references from more than 25 reputed Scopus-listed journal and conference proceeding. © 2025 ieee.

关键词： Cybersecurity

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Can current SDS Controllers Scale To Modern HPC Infrastructures?

Can Current SDS Controllers Scale To Modern HPC Infrastructu...

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2024 Workshops of the international conference for High Performance computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Miranda, Mariana Tanimura, Yusuke Haga, Jason Ruhela, Amit Harrell, Stephen Lien Cazes, John Macedo, Ricardo Pereira, Jose Paulo, Joao INESC TEC University of Minho Portugal AIST Japan TACC UTAustin United States

ISBN: (纸本)9798350355543

Modern supercomputers host numerous jobs that compete for shared storage resources, causing I/O interference and performance degradation. Solutions based on software- defined storage (SDS) emerged to address this issue by coordinating the storage environment through the enforcement of QoS policies. However, these often fail to consider the scale of modern HPC *** this work, we explore the advantages and shortcomings of state-of-the-art SDS solutions and highlight the scale of current production clusters and their rising trends. Furthermore, we conduct the first experimental study that sheds new insights into the performance and scalability of flat and hierarchical SDS control plane *** results, using the Frontera supercomputer, show that a flat design with a single controller can scale up to 2,500 nodes with an average control cycle latency of 41 ms, while hierarchical designs can handle up to 10,000 nodes with an average latency ranging between 69 and 103 ms. © 2024 ieee.

关键词： control plane QoS scalability Software-defined storage

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Digital Regimen for Parkinson Disease: An Informative Approach Using Mobile Application 2

Digital Regimen for Parkinson Disease: An Informative Approa...

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2nd international conference on Emerging trends in Information Technology and Engineering, ic-ETITE 2024

作者： Seya Prakash, P. Gunasekaran, G. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Vellore Institute Technology Department of Smart Computing Vellore India

ISBN: (纸本)9798350328202

Parkinson's disease (PD) is an advanced neuro-degenerative condition where a large number of people around the world are profoundly affected. The scarcity of precise data regarding the typical circumstances faced by humans with PD severely restricts ongoing research and therapeutic endeavours. This proposed work aims to investigate various innovations to address this issue comprehensively. Specifically, this proposed work intends to develop a versatile application tailored to help the PD patients and incorporating smart medication reminders. Moreover, this proposed work will focus on creating exercise/workout plans & diet plans based on continuous data collection and patient feedback to enhance prescription management while minimizing side effects. Simultaneously, initiatives aimed at reducing the stress level and improve mental health. The development and implementation of this versatile applications hold significant promise in improving patient outcomes. By addressing the dearth of accurate information and fostering a systematic support ecosystem, it aspires to enhance the lives of individuals grappling with PD on a global scale. © 2024 ieee.

关键词： Neurodegenerative diseases

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