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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Singh, Vaishali Pandey, Pratik Aggarwal, Prateek Reena, R. Bhagwat, Suvarna R. Sunil, M.P. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Faculty of Engineering and Technology Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350319125

Statistics mining has emerged as a crucial device for agencies in the past two decades that significantly impact selection-making methods. It can be used to gain insights from massive datasets and might assist with an employer's marketing approach, operational performance, customer segmentation, etc. This paper will explore the impact information mining has on decision-making approaches, especially regarding coming across new styles and relationships. It will discuss the blessings of using records mining and how it may help decorate choice-making. It will also look at various methods used to extract statistics from massive datasets and how they facilitate the selection-making method. Finally, it will discuss a number of the constraints of information mining and the ability of answers to overcome them. Standard, this paper aims to pick out the effect of information mining on the choice-making system and how it may be leveraged as a practical device. © 2023 IEEE.

关键词： discuss extract information overcome relationships

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QoS-Aware High Throughput Scheduling for Wireless Networks 3

QoS-Aware High Throughput Scheduling for Wireless Networks

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Kar, Abhijeet Vashisht, Nitish Kumar, Ritesh Sharma, Sonal Indira, G. Kachhoria, Renu Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science Engineering Karnataka Bangalore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India

ISBN: (纸本)9798350319125

This paper seems on the challenge of providing first-class-of-provider (quality of service) conscious throughput scheduling for wireless networks. It starts by presenting an outline of the present-day scheduling techniques used to help wireless networks, where the point of interest is maximizing spectral efficiency. It then seems at a way to design scheduling algorithms to recall the quality of service constraints. Specifically, it looks at how strategies, price management, adaptive modulation coding, and channel and interference prediction may be utilized to make specific QoS-aware scheduling. Subsequently, how artificial intelligence may be used to aid in designing quality of service-conscious scheduling algorithms and how machines gain knowledge of-based strategies consisting of deep reinforcement getting to know may be used in this context. Sooner or later, the paper presents a QoS-conscious scheduling set of rules that combines present scheduling techniques and considers the restrictions earlier than presenting an evaluation of the efficacy of this technique. © 2023 IEEE.

关键词： Evaluation maximizing modulation reinforcement techniques

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Secure Channel Creation for Task Delivery in Vehicular Cloud Computing to Avoid Denial of Service (DoS)

Secure Channel Creation for Task Delivery in Vehicular Cloud...

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Automation, Computing and Renewable systems (ICACRS), International Conference on

作者： A. Meenambika S. Pavalarajan N. Anu Lavanya B. Ajith Jerom S. Divya Department of Computer Science and Business Systems PSNA College of Engineering and Technology Dindigul India Department of CSE (Cyber Security) PSNA College of Engineering and Technology Dindigul India Department of Artificial Intelligence and Data Science PSNA College of Engineering and Technology Dindigul India

ISBN: (数字)9798331532420

ISBN: (纸本)9798331532437

Vehicular Cloud Computing (VCC) offers a promising platform for supporting various automotive applications and services. However, its distributed and dynamic nature makes it susceptible to Denial-of-Service (DoS) attacks, particularly during channel establishment. This research proposes a comprehensive approach to mitigate these risks by integrating a suite of security mechanisms. These include rate-limiting, resource management, traffic analysis, access control, authentication, encryption, intrusion detection, behavioral analysis, and blacklisting/whitelisting techniques. By incorporating these measures, the proposed approach enhances the security and reliability of VCC, ensuring the availability of critical automotive services and protecting vehicles from the impact of DoS attacks.

关键词： Cloud computing Renewable energy sources Intrusion detection Transportation Computer architecture Organizations Denial-of-service attack Safety Resource management Vehicle dynamics

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Natural Language Processing to Improve Content Retrieval Performance 3

Natural Language Processing to Improve Content Retrieval Per...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Jadhav, Varsha D. Doda, Devendra Kumar Swarup, Lakshya Kumar, Ritesh Pandian, Rajesh Rufina, Princy Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Electrical Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science Engineering Karnataka Bangalore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India

ISBN: (纸本)9798350319125

Latest studies in herbal Language Processing (NLP) have targeted improving the accuracy of statistics retrieval through leveraging machines better to recognize the use and scope of human language. Employing NLP strategies makes it far more feasible to system massive units of files and better identify the applicable content in them. Content related to a user's query can then be taken care of and ranked based on the similarity of the language used in the file. NLP strategies permit a more accurate representation of content material and can help retrieve the maximum relevant statistics. Furthermore, NLP can be prolonged beyond traditional search engines like Google to research textual content-primarily based information, such as emails and social media posts, for areas that include sentiment analysis and customer support. This paper explores the capacity of NLP to enhance content material retrieval overall performance in more than a few situations. It additionally outlines valuable techniques for evaluating the effectiveness of such structures. Dialogue and conclusion refer to approaches by which the implementation of NLP can convey improved accuracy to content material retrieval. © 2023 IEEE.

关键词： Discussion effectiveness implementation representation similarity

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Relay-Assisted Connectivity Management for Underwater High Speed Communication Networks

Relay-Assisted Connectivity Management for Underwater High S...

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2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Sahoo, Girija Shankar Renuka, G. Shinde, Swapnil K. Batri, Krishnan Lone, Zeeshan Ahmad Faiz, Ayaan Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350329773

Relay-assisted connectivity control for underwater high-pace verbal exchange networks improves verbal exchange velocity and reliability by connecting Wi-Fi networks to relays. By allowing communication among unique networks, it enables higher insurance, higher air interface, higher interference immunity, and higher network resilience. With underwater excessive pace verbal exchange networks, relays are used to ensure reliable operation to increase the networks' transmission range. Such relay-assisted verbal exchange networks can offer higher records costs than a single factor-to-factor link should provide. They can help to reduce the effect of interference that affects the speed of conversation over lengthy distances. This generation offers some benefits: extended latency, stepped forward bandwidth usage, accelerated community topology, improved fault tolerance and robustness, better statistics synchronization, and quicker handover in multi-radio networks. Additionally, with the help of relay-assisted verbal exchange networks, such networks' deployment, and operation costs can be decreased substantially. © 2023 IEEE.

关键词： Wi-Fi

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A New Integrated Approach for Cloud Service Composition and Sharing Using a Hybrid Algorithm

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Mathematical Problems in engineering 2024年第1期2024卷

作者： Jayaudhaya, J. Jayaraj, R. Ramash Kumar, K. Department of Electronics and Communication Engineering Rmd Engineering College Chennai India Department of Data Science and Business Systems Srm Institute of Science and Technology Chennai India Department of Electrical and Electronics Engineering Dr. Ngp Institute of Technology Coimbatore India

The concept of a "Smart City"emphasizes the need to employ information and communication technologies to strengthen the quality, connectivity, and efficiency of various municipal services. Cloud computing and the Internet of Things are shaping future tech. Both ideas greatly impact smart city application and solution development. Cloud computing is amazing at managing and storing remote service access. Several companies have switched to cloud leasing to reduce local resource burden. Due to the intricacy and flexibility of cloud-maintained services, selecting jobs that best suit client needs should be optimized. Quality of service criteria for each cloud service are the best tools for choosing and optimizing cloud carriers. Genetic algorithms (GAs) and ant colony optimization (ACO) are combined to make cloud computing. It is discovered that the recommended ACO + GA obtains an accuracy of 82% when compared to existing methods of energy- and reliability-aware multiobjective optimization method and the hybrid cuckoo particles swarm, artificial bee colony optimization (CPS + ABCO) where accuracy is 68% and 75%, respectively. © 2024 Jayaudhaya J. et al.

关键词： Ant colony optimization

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Adaptive Bandwidth Optimization Techniques for Underwater Fiber Optic Networks 3

Adaptive Bandwidth Optimization Techniques for Underwater Fi...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Kale, Sunil D. Samrat, Bhavuk Varalakshmi, S. Tiwari, Mohit Singh, Vaishali Umamaheswari, B. Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Center for Management Studies Faculty of Engineering and Technology Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India

ISBN: (纸本)9798350319125

Underwater fiber optic networks provide hyperlinks that permit communiqué among offshore structures, deep-sea bases, and oil rigs. Despite the growing need for better facts costs, the constrained to be had bandwidth in such networks stays a major undertaking for their efficient use. To overcome this task, a variety of adaptive bandwidth optimization techniques were proposed in current years. A number of those strategies involve dynamic modulation and coding, whilst other techniques use adaptive scheduling algorithms. All tactics rely upon dynamic replace of bandwidth allocation to make the only use of the underlying fiber hyperlink. Within the case of dynamic modulation and coding, modifications are made to the physical layer configuration of the hyperlink to conform to converting conditions on the hyperlink. On the other hand, adaptive scheduling strategies use course optimization algorithms to select the maximum green route for records to tour, re-allocating bandwidth as had to accommodate heavy loads. Subsequently, new techniques such as EQUINOX are also being explored to further optimize bandwidth usage on underwater fiber optic networks by means of combining elements of each dynamic modulation and coding and adaptive scheduling. © 2023 IEEE.

关键词： Hyperlinks Modulation Optimization Scheduling Techniques

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Measuring COVID-19 Opinion in the Online Debate using an Unsupervised Model 1

Measuring COVID-19 Opinion in the Online Debate using an Uns...

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1st IEEE International Conference on Automation, Computing and Renewable systems, ICACRS 2022

作者： Priyadarsini, K. Jeba Sonia, J. Vijayalakshmi, K. Anbazhagu, U.V. Department of Data Science and Business Systems School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai603203 India Department of Computational Intelligence School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai603203 India Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai603203 India

ISBN: (纸本)9781665460842

A large quantity of potentially threatening COVID-19 false information is available online. In this article, machine learning approach is adopted to assess COVID-19 materials in online health advice adversaries, particularly those who oppose immunizations like (anti-vaccine). Pro-vaccination (pro-vaccine) group is emerging a more attentive conversation regarding COVID-19 above its corresponding portion, the anti-vaccine group. However, the anti-vaccine group presents a wide series of flavors of COVID-19-relatedtopics, andas a result, can demandto a wider cross-section of entities searching for COVID-19 assistance online, such as those who may be wary of receiving a COVID-19 vaccine as a condition of employment or those looking for alternative medications. Later, the anti-vaccine group appears to be better positioned than the pro-vaccine side to obtain complete support moving forward. This is important because if the COVID-19 vaccine is not widely used, the world will not be able to produce herd immunity, parting countries exposed to a COVID-19 comeback in the future. An automatic supervision machine learning model is provided that clarifies these results andcan be used to evaluate the efficacy of intervention efforts. Our method is adaptable and capable of addressing the crucial problem that social media platforms face when analyzing the vast amounts of online health misinformation. © 2022 IEEE

关键词： COVID-19

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Investigating the Feasibility of Using Machine Learning for Real-Time data Analysis

Investigating the Feasibility of Using Machine Learning for ...

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2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Latha, B. Ghule, Vijaykumar R. Geetha, G. Singh, Shweta Kharbas, Vikash Kumar Ahluwalia, Gunveen Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350329773

This paper seeks to determine the feasibility of the usage of device learning for actual-time facts evaluation. system gaining knowledge of can be used to research massive datasets and apprehend styles, in addition to automate selection-making methods. This may be utilized in studying the consequences of digital techniques in real-time and tracking adjustments in patron traits. numerous device studying algorithms, consisting of selection trees, Naïve Bayes, support Vector system (SVM), Logistic Regression, Random wooded area, and Neural Networks, are evaluated if you want to show their overall performance for real-time statistics assessment. A framework based on machine gaining knowledge of techniques is proposed for real-time facts evaluation. Open source datasets are used to evaluate and compare the overall performance of different algorithms. The assessment results show the practicality and effectiveness of the usage of device studying for actual-time records evaluation. In end, the feasibility of using device studying for real-time data analysis is affirmed via this research. © 2023 IEEE.

关键词： Support vector machines

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Quantifying the Impact of AI and Machine Learning on data Access Optimization

Quantifying the Impact of AI and Machine Learning on Data Ac...

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2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Khandari, Harsimrat Sahoo, Girija Shankar Tr, Mahesh Rajeswari, M. Jadhav, Prranjali Meena, Mansingh Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka 562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798350329773

Quantifying the impact of synthetic Intelligence (AI) and machine getting to know (ML) on information access Optimization (DAO) and its ability to enhance overall performance and performance inside organizations has been a topic of research for decades. This newsletter investigates how such technology is essential in optimizing records access and its effect on the rate and accuracy of operations. We speak about how cutting-edge advances in AI and ML can be utilized to detect patterns in facts, reduce latency, and improve the general quality of data. Furthermore, we discuss how that technology can reduce manual techniques and get rid of errors due to human mistakes, hence enhancing performance and productiveness. Sooner or later, we talk about the main challenges associated with enforcing AI and ML within a company and identify capacity areas of development. © 2023 IEEE.

关键词： Machine learning

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