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2nd International Conference on Advance Computing and Innovative technologies in Engineering, ICACITE 2022

作者： Johri, Shiva Mehta, Kamakshi Suhashini, J. Shukla, Prashant Kumar Podile, Venkateswararao Singh, Devesh Pratap Bhopal India Amity College of Commerce Amity University Haryana India Psna College of Engineering and Technology Department of Management Studies Dindigul India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vaddeswaram Andhra Pradesh Guntur522502 India K.L. Business School K.L. University Andhra Pradesh Vaddeswaram India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9781665437899

Digital archive management solutions have become increasingly popular in archive management as information technology and wireless technology have advanced. Unlike traditional paper archives, which have inherent distinctiveness and strong tamper-proof modification, electronic files and data are stored in centralized databases, which are more vulnerable to network attacks, data loss, or attempting to steal through malicious software, and are more likely to be crafted and tampered with by internal managers but rather external attackers. Accounting system digitization is still very much in infancy in comparison to other businesses, which have also been severely affected by technological breakthroughs. Some of the explanations may be discovered in the very stringent regulatory standards for authenticity and integrity. The whole accounting system is designed in such a way that counterfeiting is either impossible or prohibitively expensive. This is accomplished through the use of mutual control mechanisms, as well as checks and balances. This will certainly have an impact on day-to-day operations. There is systematic duplication of work, detailed documentation, and periodic controls, among other things. The majority of them that are manual, labor-intensive operations that are far from mechanized. To date, it seems to be the cost of telling the truth As a result, electronic information management is required for its capacity to properly store and retrieve huge amounts of data while ensuring computer system performance integrity. © 2022 IEEE.

关键词： Transparency

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Banana fibre: A golden revolution

Asian Textile Journal

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Asian Textile Journal 2021年第9期30卷 51-59页

作者： Kannigadevi, R. Muthukannan, M. Dhesinghraja, J. Murali, M. Mayandi, K. Elango, Dinesh Department of Computer Science Engineering School of Computing Kalasalingam Academy of Research and Education Tamil Nadu Virudhunagar India Department of Civil Engineering School of environmental and construction technology Kalasalingam Academy of Research and Education India DST-STI hub project Kalasalingam Academy of Research and Education Department of Mechanical Engineering Kalasalingam Academy of Research and Education India Martin de tours school of management & economics Assumption university Bangkok Thailand

The climatic condition of India will be suitable for banana/plantain cultivations. Even we are the leading producers in the world. This has so many applications. This tree fruit is a healthy and hygienic diet. It is available everywhere even in the local markets. The free waste especially banana stem is able to be utilized to produce as some bioproducts and bio-fibres which will contribute directly to our country's and state's economy.

关键词： Fruits

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Improving Energy Efficiency in Three-Tier IoT Sensor Networks Through NDFT-based Power Optimization

Improving Energy Efficiency in Three-Tier IoT Sensor Network...

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Intelligent & Innovative Practices in Engineering & management (IIPEM), International Conference on

作者： Pallavi Joshi Anamika Kumari Navodit Bhardwaj Hitesh Tekchandani Praveen Kumar Shukla Department of Computer Science Amrita Vishwa Vidyapeetham Mysuru India MIT College of Management MIT Art Design & Technology University Pune India Bosch Global Software Technologies Private Limited Bengaluru India Artificial Intelligence & Data Science Koneru Lakshmaiah Education Foundation Hyderabad India Department of IoT & Intelligent Systems Manipal University Jaipur Jaipur India

ISBN: (数字)9798350390049

ISBN: (纸本)9798350390056

The data transmission process in the Internet of Things based sensor network is crucial as many applications require data movement from one device to another. As the network size grows, the volume of data transmission increases, reducing the overall energy efficiency of the network and leading to higher communication costs. Additionally, The execution time also increases as a result of this problem. Some researchers work on reducing the communication cost by using the clustering approach but these methods have not fully achieved the desired improvements. This paper explores the implementation of the discrete Fourier transform (DFT) on nonequidistant sensor nodes within a clustered sensor network to address these challenges. The method produces Fourier coefficients with estimation in error limits. Once the clusters become communication cost-efficient, the data routing is performed using the power constraints of the nodes, cluster leaders, and the base station. The nodes in every cluster transmit their measurements to a CL. CLs fuse the signals received by sensor nodes and send them to a base station on orthogonal fading channels. The channel estimation can be done by sending pilot signals to BS from CL. The Bayesian Cramér-Rao bound is obtained from mean square error and linear minimum mean square error estimator at BS. The proposed system demonstrates effective performance across various constraint parameters and proves to be power efficient. It has reduced the transmission cost by 35.2% and execution time by 24.13%.

关键词： Constraint optimization Base stations Costs Discrete Fourier transforms Channel estimation Mean square error methods Energy efficiency Bayes methods Data communication Optimization

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Automated Forest Fire Detection using Atom Search Optimizer with Deep Transfer Learning Model 2

Automated Forest Fire Detection using Atom Search Optimizer ...

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2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Alice, K. Thillaivanan, Alagu Koteswara Rao, Ganga Rama Rajalakshmi, S. Singh, Kamlesh Rastogi, Ravi Kani School of Computing Srmist Department of Computing Technologies Tamilnadu Chengalpet India College of Engineering and Technology Telangana Hyderabad India Koneru Lakshmaiah Education Foundation Department of Csit Andhra Pradesh Guntur India Rmk College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Thiruvallur India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India Nielit Uttar Pradesh Gorakhpur India

ISBN: (纸本)9781665456302

Automated Forest Fire Detection (AFFD) contains the technology used to recognize and alert authorities on latent wildfires in a forested region. AFFD methods are latent to enhance response times and decrease the damage led by wildfires. But, these systems are utilized in conjunction with typical fire management practices like fire prevention and suppression measures, to provide the best achievable outcomes. There are several algorithms to AFFD, comprising computer vision (CV), remote sensing, and machine learning (ML). This article develops an Automated Forest Fire Detection using Atom Search Optimizer with Deep Transfer Learning (AFFD-ASODTL) model. The goal of the AFFD-ASODTL technique lies in the effectual recognition of forest fires accurately and promptly. In the presented AFFD-ASODTL technique, residual network (ResNet50) model is applied for feature vector generation. Besides, the ASO technique is exploited for the optimal hyperparameter tuning of the ResNet model. Meanwhile, Quasi-Recurrent Neural Network (QRNN) model is used for forest fire classification. To exhibit the optimum resultant of the AFFD-AS ODTL system, a comprehensive set of simulations is carried out. The comparative study highlighted the improvised results of the AFFD-ASODTL method over other models. © 2023 IEEE.

关键词： Atoms

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Examining 6G Infrastructure Capabilities: Paving the Way for Future Connectivity

Examining 6G Infrastructure Capabilities: Paving the Way for...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Devyani Rawat Anurag Chaubey Prashant Kumar S. HEMELATHA P. GAJENDRAN D.S. Wankhede Department of Management Studies Graphic Era Deemed to be University Dehradun Uttarakhand India School of Commerce and Management IIMT University Meerut Department of ECE TMU Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore Department of Electrical and Electronics Engineering Karpagam College of Engineering Coimbatore Computer Engineering Vishwakarma Institute of Information Technology Pune

6G structures are anticipated to be a major driver for the smart data society, providing functionality that is better to 5G and satisfying innovative features and apps. In this piece, we outline utilization situations and specifications for non - linear and non per third and sophisticated 6G networks as well as our view of what 6G will be. That can provide all-encompassing and limitless wireless communication, we show a massive and independent structured cabling that combines land, air, sea, and space communications. For network interfaces and creative vapour style, we also address artificial intelligence and machine learning. The Internet of Graphene, microwave frequency connectivity, very highly directional arrays myriad, numerous different, large erudite textures and holograms directional antennas, orbital rotational frequency - division, laser and that can be seen comms, nanotech, genomic messaging, and Ethereum - based frequency hopping are a few of the systems we identify as enticing for the 6F I environment.

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Cloud-Integrated Clean Fuel Generation for Solar-Hydrogen Production with Wireless Sensor Networks 7

Cloud-Integrated Clean Fuel Generation for Solar-Hydrogen Pr...

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7th International Conference on Inventive Computation technologies, ICICT 2024

作者： Naveenkumar, N. Sridevi, V. Bharathi, R. Mishra, Nilamadhab Murugan, S. Velmurugan, S. Department of Computer Science And Engineering Namakkal Tamil Nadu Rasipuram India Academy of Maritime Education And Training Deemed To Be University Electrical And Electronics Engineering Tamil Nadu Chennai India Srm Institute of Science And Technology Faculty of Management Chennai Tamil Nadu Kattankulathur India Vit Bhopal University School of Computing Science And Engineering Madhya Pradesh India Saveetha Institute of Medical And Technical Sciences Saveetha University Saveetha School of Engineering Department of Biomedical Engineering Tamil Nadu Chennai India T.J.S. Engineering College Department of Electronics And Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350359299

This research study proposes a novel system that integrates Wireless Sensor Networks (WSNs) with cloud-based platforms to efficiently generate renewable energy and produce clean fuel. By enhancing the safety, efficiency, and reliability of solar power and hydrogen generation, the system integrates optimization strategies, data analysis, and real-time monitoring. Critical parameters such as temperature, sun irradiance, electrolysis efficiency, and hydrogen purity are monitored using WSNs, with data transmitted and processed via cloud techniques to identify patterns, outliers, and areas for improvement. Proactive decision-making and rapid adjustments are facilitated through remote monitoring and control capabilities, leading to maximized energy production and clean fuel output. Security measures including encryption, access controls, and regular audits safeguard data privacy and integrity, while multiple sensor deployments, robust communication protocols, and a resilient cloud infrastructure ensure system reliability. This integrated approach offers an effective solution for advancing renewable energy generation and clean fuel production, contributing to environmental sustainability and a greener future. © 2024 IEEE.

关键词： Energy efficiency

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Digital Signature for Content Authentication

Digital Signature for Content Authentication

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： Ashutosh Kumar Rai Manmohan Singh H C Sudheendramouli Varij Panwar N. Alangudi Balaji Ravish Kukreti Department of Computer Science and Engineering IES College of Technology Bhopal Madhya Pradesh India Department of Computer Science GSSS Simha SubbaMahalakshmi First Grade College Mysuru Karnataka India Department of Electronics & Communication Engineering Graphic Era Deemed to be University Dehradun Uttarakhand Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of Hospitality Management Graphic Era Deemed to be University Dehradun Uttarakhand India

A digital signature is a mathematical method used to confirm the genuineness and safety of a digitally transmitted message or file. content, such as electronic documents, emails, software, and multimedia files. It is a form of electronic signature that uses encryption and public-key cryptography to sign and verify digital content. In order to generate a digital signature, one must first several steps. First, the sender of the content results in unique hash of the message that has been content utilizing a secure hashing algorithm. The message digest is a sequence of bits that is set in length and specific to the content and cannot be reversed to reveal the original content. Finally, the sender encrypts the message digest using their secret code to create online signature. When The Present Recipient Acquires content and digital signature, they use digital signature decryption using the sender's public key and obtain summary of communications. The recipient then generates a new Briefing Notes of the content in the same way cryptographic hash function sender's role. If the two message digests match, the content is considered authentic and has not been tampered with in transit. Digital signatures provide several benefits for content authentication. They provide non-repudiation, meaning that the sender cannot deny having sent the content since their secret code is used to Construct the electronic signature. They also provide integrity, as any changes to the content will result in a different message digest and therefore an invalid digital signature. Lastly, they provide confidentiality, as only the intended recipient with the corresponding digital signature using a publicly available key pair message digest. Overall, digital signatures are an essential tool for ensuring the authenticity and integrity of digital content and are commonly employed in many fields, finance, healthcare and public administration.

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Automatic Topic Classification And Document Clustering Using Lda Based Machine Learning Techniques

Automatic Topic Classification And Document Clustering Using...

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Communications and Information technologies (GCCIT), Global Conference on

作者： K. Yuvaraj Nipun Setia Sangeetha S Prakhar Goyal Thomas P K Vishal A. Meshram Department of Computer Science Karpagam Academy of Higher Education Coimbatore Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Science and Humanities Prince Shri Venkateshwara Padmavathy Engineering College Chennai Quantum University Research Center Quantum University Roorkee Uttarakhand India Adjunct Faculty School of Management - PG Management JAIN (Deemed to be University) Bangalore Karnataka Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

Since more and more information is being stored in digital formats (such as databases, journals, libraries, and papers), it is crucial that this information be put to good use. However, it might be challenging to extract meaningful insights from the data because of its poor organisation, ambiguity, and lack of precision. Data may be correctly categorised to allow for separate research on different types of data, which will help with this problem. Because of this, researchers in disciplines like mathematics and computer science have been trying to figure out how to fix the issue. Material mining is a branch of machine learning that helps cope with unstructured and disorganised data by sifting through it for useful insights. Text mining is a subfield of data mining that focuses on discovering patterns and extracting structured attributes from unstructured text. To successfully analyse such data, supervised learning is combined with unsupervised learning. It has become common practise to employ Latent Dirichlet Allocation (LDA), a probabilistic approach to topic modelling, when classifying documents. As an unsupervised method, however, traditional LDA's findings may shift depending on which articles come first in the analysis. In this study, we provide a comprehensive strategy for avoiding the order effect as well as the unsupervised probabilistic character of the problem. The proposed framework achieved a success rate of 95.56% & 95.23% when evaluated on two separate datasets, demonstrating its better classification capabilities. Furthermore, the subjects that were extracted from the classified clusters are highly relevant to the domain classifications.

关键词： Text mining Machine learning algorithms Databases Machine learning Feature extraction Probabilistic logic Mathematics Libraries Data mining Unsupervised learning

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Revolutionizing Urban Mobility: An Overview of Intelligent Transportation Systems in Smart Cities

Revolutionizing Urban Mobility: An Overview of Intelligent T...

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International Conference on Inventive Research in Computing Applications (ICIRCA)

作者： A. Maria Nancy N. A. S. Vinoth K. Sargunan A. Alex Rajesh Kamal Alaskar V Raviteja Kanakala Department of Computing Technologies SRM Institute of Science and Technology Chennai India Department of Civil Engineering Vidya Academy of Science and Technology Technical Kilimanoor Kerala India Department of Civil Engineering K.S.R. College of Engineering Tiruchengode Tamil Nadu India Department of Computer Application BharatiVidyapeeth (Deemed To Be University) Institute of Management Kolhapur Maharashtra India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

In the present days, starting from phones to regularly utilized technologies all are getting smart. During this smart technological era, intelligent transportation system is one of the most expected project for developing a smart city. It is possible to assess the efficiency of Intelligent Transportation Systems (ITS) in a variety of urban environments by using statistical methods such as Analysis of Variance (ANOVA) and Regression Analysis in order to single out the factors that are most important. The primary objective of this study is to get an understanding of the impact that ITS has on travel times, congestion, and other metrics. According to the statistics, the population density of an area and the accessibility of road infrastructure are two of the most essential elements that must be present for an ITS to be effective. In light of these results, it is abundantly evident that prior to making any choice whatsoever, serious thought has to be given to both the advantages and the negatives of implementing ITS. The results of the research might be utilized by legislators and city planners in other nations to create transportation systems that are beneficial to the economic as well as the environment.

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Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data

arXiv

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arXiv 2024年

作者： Liu, Ji Jia, Juncheng Zhang, Hong Yun, Yuhui Wang, Leye Zhou, Yang Dai, Huaiyu Dou, Dejing Hithink RoyalFlush Information Network Co. Ltd. Hangzhou China School of Computer Science and Technology Soochow University Collaborative Innovation Center of Novel Software Technology and Industrialization Suzhou China School of Computer Science and Technology Soochow University Suzhou China Baidu Research Beijing China Key Lab of High Confidence Software Technologies Ministry of Education Software Institute Peking University Beijing China Department of Computer Science and Software Engineering Auburn University Auburn United States Department of Electrical and Computer Engineering North Carolina State University NC United States BEDI Cloud and School of Computer Science Fudan University Beijing China

Despite achieving remarkable performance, Federated Learning (FL) encounters two important problems, i.e., low training efficiency and limited computational resources. In this paper, we propose a new FL framework, i.e., FedDUMAP, with three original contributions, to leverage the shared insensitive data on the server in addition to the distributed data in edge devices so as to efficiently train a global model. First, we propose a simple dynamic server update algorithm, which takes advantage of the shared insensitive data on the server while dynamically adjusting the update steps on the server in order to speed up the convergence and improve the accuracy. Second, we propose an adaptive optimization method with the dynamic server update algorithm to exploit the global momentum on the server and each local device for superior accuracy. Third, we develop a layer-adaptive model pruning method to carry out specific pruning operations, which is adapted to the diverse features of each layer so as to attain an excellent trade-off between effectiveness and efficiency. Our proposed FL model, FedDUMAP, combines the three original techniques and has a significantly better performance compared with baseline approaches in terms of efficiency (up to 16.9 times faster), accuracy (up to 20.4% higher), and computational cost (up to 62.6% smaller). © 2024, CC BY.

关键词： Federated learning

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