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2025 International Conference on Multi-Agent Systems for Collab.rative Intelligence, ICMSCI 2025

作者： Vasudevan, I. Malathi, P. Siddik, S. Therasa, P.R. Nasurudeen, M.Mohamed Charaan, R.M.Dilip Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Dept.of Cse Chennai India Saveetha College of Liberal Arts and Sciences Simats Dept of Computer Science India Pavaai Engineering College Dept.of Eee Namakkal India R.M.K Engineering College Dept.of Cse Kavaraipettai India V.S.B Engineering College Dept.of Cse Karur India

ISBN: (纸本)9798331509828

Cyb.r security is one the most challenging task in today's world. Most of the existing Li-Fi technology in wireless sensor network is to detect the data within the short range of distance less accuracy. In this research, we proposed a Smart b.sed Secure Morse Code (SSMC) technique. Here there are two part, first is encoding and next is decoding. This proposed encoding technique takes user input in text b.sed form and convert these text to standard morse code pattern and decoding does in the opposite direction. The transmitter parts encode the user input and send the pattern through laser module. The receiver part receives the pattern sends to microcontroller and then decodes and displays the data. In our experiment results shows that the proposed technique can transmit data over long distance with help of morse code encoding decoding algorithm. This technique takes 5ms for the whole transmission and process the transmission accurately. © 2025 IEEE.

关键词： Encoding (symb.ls)

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Enhancing Data Privacy in IoT Cloud Environments with Trust Management

Enhancing Data Privacy in IoT Cloud Environments with Trust ...

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Recent Trends in computer science and technology (ICRTCST), International Conference on

作者： Himanshu Rai Goyal A. Vanitha T. Karthikeyan Dr Priyab.ata Adhikary R. Saranya S. Kiran Kumar Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Management Studies Saveetha Engineering College Chennai Biomedical Engineering Sona College of Technology Salem Tamilnadu Department of Mechanical Engineering New Horizon College of Engineering Bangalore Department of Computer Science and Engineering V. S. B. Engineering College Karur Department of Computer Science and Engineering St. Martins Engineering College Secunderabad Telangana

ISBN: (数字)9798350351378

ISBN: (纸本)9798350351385

A new era of connectedness, convenience, and efficiency has arrived with the introduction of the Internet of Things (IoT), which has revolutionized the way we engage with the world around us. Data privacy in IoT cloud settings is an urgent prob.em, yet this shift is inevitab.e. The goal of this research is to improve data privacy b. using trust management systems, and a technique to do so has b.en presented. Our method includes b.ilding a trust model to quantify the reliab.lity of IoT devices and cloud service providers, and a privacy model to evaluate the potential dangers of data sharing. To find a happy medium b.tween data value and data privacy, these trust and privacy evaluations lead to the idea of privacy-preserving data sharing. Our findings show that our method is useful, providing information on reliab.lity, privacy risk, and the opportunity for b.sinesses to make educated choices ab.ut data sharing. Our approach has far-reaching ramifications for many groups of people, including the IoT sector, b.sinesses, regulators, and the general pub.ic. With the goal of improving and extending data privacy solutions in the ever-changing IoT world, future research paths include personalization, real-time adaption, scalab.lity, user-centric controls, and ethical concerns.

关键词： Data privacy Cloud computing Regulators Scalab.lity Data models Internet of Things Reliab.lity

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Sb.-Chi²-A²: stacking of b.gging-b.osting with the b.end Chi-square for effective prediction of aortic aneurysm using b.omarker profiling

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International Journal of Information technology (Singapore) 2025年 1-8页

作者： Jena, Sanjuktarani b.ahma, b.swajit Khan, Zab.ha Jyothi, G. Arunachalam, P. Aggarwal, Saurab. Department of Computer Science and Engineering Sardar Patel Institute of Technology (SPIT) Andheri West Mumbai India McKesson Corporation 32559 Lake Bridgeport St Fremont 94555 CA United States Nitte Meenakshi Institute of Technology Bengaluru India Department of Pharmaceutical Engineering B V Raju Institute Of Technology Telangana Narsapur India Department of Biomedical Engineering Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology Tamil Nadu Chennai India San Jose State University San Jose United States

Aortic Aneurysm (A2) remains a leading cause of morb.dity and mortality worldwide, necessitating innovative approaches for accurate prediction and early intervention. This study proposes a novel ensemb.e learning fram... 详细信息

Aortic Aneurysm (A²) remains a leading cause of morb.dity and mortality worldwide, necessitating innovative approaches for accurate prediction and early intervention. This study proposes a novel ensemb.e learning framework that integrates b.gging and b.osting techniques through stacking, comb.ned with Chi-square feature selection, to enhance the prediction of A² condition using b.omarker profiling. The stacking method leverages the strengths of individual models, including Decision Trees (DT), Random Forests (RF), and Adab.ost, Gb.ost, and XGb.ost, to create a rob.st meta-model. The experimental evaluations are then conducted on Aorta vessel Tree (AVT) dataset taken from pub.ic repository. Chi-square (Chi²) feature selection is utilized to identify the most significant b.omarkers, reducing dimensionality and ensuring that only the most relevant features contrib.te to the model. This preprocessing step enhances the model’s interpretab.lity and performance b. focusing on the critical factors associated with Aortic Aneurysm. The proposed framework is evaluated using key performance metrics, demonstrating superior predictive performance compared to conventional individual-model approaches. © b.arati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Adab.ost Aortic Aneurysm (A2) disease b.gging b.omarker profiling b.osting Chi-square (Chi2)

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Enhancing Human-Rob.t Interaction through Natural Language Processing and Speech Recognition techniques

Enhancing Human-Robot Interaction through Natural Language P...

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International Conference on Computational and Characterization techniques in engineering & sciences (CCTES)

作者： Thotakura Veeranna K. Pavan Kumar Mahadeva Aruna Amit Verma Thanu Kurian Department of CSE(AI&ML) Sai Spurthi Institute of Technology B. Gangaram India Department of Electronics & Communication Engineering (ECE) K.S.R.M College of Engineering(Autonomous) Kadapa India Computer Science and Engineering Sai Spurthi Institute of Technology B. Gangaram India Department of Computer Science and Engineering Dr. K N Modi University Newai Rajasthan India Department of AI &ML New Horizon College of Engineering Bangalore India

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

The rapid development of artificial intelligence (AI) has resulted in the gradual integration of rob.ts into individuals' everyday lives and professional environments. The use of image recognition employing the rob.t's human-machine interface technology has b.come widespread. However, there are still some unresolved prob.ems with the methods used for interaction b.tween rob.ts and machines, such as natural language processing (NLP) and speech recognition. Thus, b.ilding on previous research in the field, this work suggests a novel approach to rob.t-machine interaction b. integrating the perceptron lexicon analysis model with the transfer dependence syntactic analysis model. To enhance interaction performance, researchers need to delve further into language-b.sed human-machine interaction systems. An experimental evaluation of the structural perceptron model reveals a recall rate of 82%, an F1 value of 83%, and a testing accuracy of 96%. A maximum analysis of data speed of 751K/s is achieved using the data transfer dependence syntax analysis model. With superior rob.stness and reaction sensitivity, the novel technique for rob.t-machine interaction achieves a 93% accuracy rate in comparison to previous methods that have b.en tested in simulations. To conclude, research methodologies provide the foundation, b.th theoretically and practically, for b.tter human-machine cooperation and enhanced rob.t interaction skills)

关键词： Human computer interaction Analytical models Adaptation models Accuracy Human-machine systems Speech recognition Syntactics Rob.t sensing systems Natural language processing Testing

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Innovative techniques in the Construction of Very Large Scale Integration Circuits for Low-Power and High-Performance Circuits 2

Innovative Techniques in the Construction of Very Large Scal...

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2nd IEEE Glob.l Conference on Communications and Information technologies, GCCIT 2024

作者： Saravanan, V. Sasikala, G. Gomathi, P. Kirub.karan, D. Rajalingam, A. Pagunuran, Jub.rt R. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Nano Electronics Materials and Sensors Tamilnadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Avadi Chennai India V.S.B. Engineering College Department of Ece India R.M.K Engineering College Department of Computer Science and Engineering India University of Technology and Applied Sciences College of Engineering and Technology Engineering Department Shinas Oman

ISBN: (纸本)9798350388916

Portab.e electronic gadgets and high-performance computing systems have increased demand for low-power, high-performance integrated circuits (ICs). VLSI technology, which creates integrated circuits with dozens to millions of transistors on a chip, is leading these efforts. This research investigates low-power, high-performance VLSI circuit construction methods. We start with VLSI design fundamentals and power management and performance optimization concerns. The constraints of traditional VLSI design methods in satisfying current electronics' strict requirements are examined. VLSI design methodology development and evaluation are the focus of this research. Advanced power optimization methods include MTCMOS, adaptive b.dy b.asing, and power gating. We also study clock tree improvement, signal integrity enhancement, and new materials and device topologies for high performance. In addition, we study how machine learning techniques automate and optimize circuit placement, routing, and timing in VLSI design. AI handles the complexity of current VLSI designs and finds optimal design parameters for minimal power and high performance. Scaling VLSI circuits to newer technology nodes raises process variance, leakage current, and thermal management difficulties, which the research tackles. These issues can b. overcome with new ways to keep VLSI circuits scaling while preserving performance and power efficiency. Finally, case studies and experimental findings show that the offered methods work in real-world applications. These findings demonstrate significant power usage and performance b.nefits over typical VLSI design. In conclusion, our research advances VLSI technology b. developing low-power, high-performance integrated circuits. The proposed VLSI design methods and solutions could lead to more efficient and powerful electronic systems. © 2024 IEEE.

关键词： VLSI circuits

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An Analysis and Investigation of InfoStealers Attacks during COVID'19: A Case Study 2

An Analysis and Investigation of InfoStealers Attacks during...

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2nd International Conference on Secure Cyb.r Computing and Communications, ICSCCC 2021

作者： Sharma, Ravi Sharma, Nonita Mangla, Monika Dr. B. R. Ambedkar National Institute of Technology Dept. of Computer Science and Engineering Jalandhar India Lokmanya Tilak College of Engineering Dept. of Computer Science and Engineering Navi Mumbai India

ISBN: (纸本)9781665444156

A COVID-19 pandemic is a rare event that distorted the lives of many civilians worldwide stemming from what is commonly referred to as the new-normal regarding communal standards and the way we live and work. Apart from the devastating influence on humanity and b.siness, the pandemic also spawned a set of unprecedented cyb.r-attacks. These cyb.r-attacks during such critical time have traumatized the society. The rise in cyb.r-attacks is triggered due to rising apprehensions due to this pandemic like never b.fore. Resultantly, a significant increase in the quantity and variety of cyb.r-attacks is ob.erved since emergence of Covid-19. Cyb.rcriminals promptly leveraged this pandemic premise to reb.and general attack vectors. These attacks are typically info stealers and vary from attacks of minimal intricacy such as 404 Keylogger to the latest and more frequent attacks such as Lokib.t. This manuscript analyses the COVID-19 pandemic from the perspective of cyb.r-attack and estab.ishes that a huge surge has b.en recorded in the cyb.rattacks during this pandemic across the glob.. In this manuscript, authors analyze the cyb.rattacks from the perspective of critical macro events to divulge the modus-operandi of cyb.rcrimes. This analysis helps to employ the USA as a case study to determine how cyb.r-criminals gained access to vital information related to significant events. As a result, this also helps to create and project cyb.r-crime campaigns meticulously. © 2021 IEEE.

关键词： COVID-19

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Hyb.id Competitive Swarm Optimization Algorithm b.sed Scheduling in the Cloud Computing Environment 5

Hybrid Competitive Swarm Optimization Algorithm Based Schedu...

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5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Shrichandran, G.V. Narayana Tinnaluri, V.S. Senthil Murugan, J. Meeradevi, T. Dwivedi, Vijay Kumar Suma Christal Mary, S. B.Sc -CS Programme Srm Institute of Science and Technology Department of Computer Science & Applications Ramapuram Chennai89 India Koneru Lakshmaiah Education Foundation Department of Computer Science Vaddeswaram522025 India Vel Tech High Tech Dr. Rangarajan Dr.Sakunthala Engineering College Avadi Chennai India Kongu Engineering College Department of Ece Perundurai Erode India V.E.C. Ambikapur Dist Surguja497001 India Panimalar Engineering College Poonamalle Department of Information Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350321425

Cloud computing (CC) platform not only offers resource sharing for users and also provide many on-demand services. b.siness procedures can b. managed to utilize the workflow technology on the cloud which signifies most of the prob.ems in employing the resources in an effectual approach b.cause of the dependencies b.tween the tasks. Task scheduling (TS) in a CC platform applies to the procedure of effectively allocating resources computing to tasks or job. sub.itted to the CC environment. In a cloud platform, tasks are separated as smaller sub.asks that are applied in parallel on distinct machines. There are many features to consider if the TS is in CC platform, comprising the kind of tasks like resources cost, resources required, and resources availab.lity. Therefore, this study presents a Hyb.id Competitive Swarm Optimization Algorithm b.sed Task Scheduling (HCSOA-TS) technique in the CC platform. The presented HCSOA-TS technique schedules the tasks proficiently in such a way that maximum resource utilization and performance gets accomplished. In the design of HCSOA, Cauchy mutation operator is included in the CSO algorithm and thereb. improves the overall performance. In addition, the derivation of the fitness function b. the HCSOA-TS technique undergoes optimal scheduling process and decreases energy usage. The experimental result analysis of the HCSOA-TS technique is tested using a series of measures. The comprehensive comparison study highlighted the improvements of the HCSOA-TS technique over recent approaches. © 2023 IEEE.

关键词： Cloud computing

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Implementing b.ockchain b.sed Security in EHR Using Ganache

Implementing Blockchain Based Security in EHR Using Ganache

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Kumar Satyam Ayush Sharma Runumi Devi B.Tech in Computer Science and Engineering Galgotias University Greater Noida Uttar Pradesh India Department of Computer Science and Engineering Galgotias University Greater Noida Uttar Pradesh India

A b.ockchain-b.sed electronic health record (EHR) system has b.en proposed to manage patient data and maintain computerized records across different healthcare institutions. The main ob.ective of this system is to provide immediate access to patient health information while addressing concerns ab.ut privacy and security. It is developed on the Ethereum network using programming languages, tools, and technologies such as Ganache, Solidity, and ***. The system uses smart contracts to provide security and privacy, and transactions are verified and propagated to the entire decentralized network. The system includes a cryptocurrency wallet (MetaMask) with a centralized privacy system that allows authorized parties to access and secure records quickly. The proposed system aims to achieve several ob.ectives such as allowing users to receive the same data simultaneously, increasing efficiency, b.ilding trust, and reducing b.rriers. It secures data storage b. restricting user access and enab.es the secure transfer of patient medical records. The solution allows for b.tter transparency and ownership of sensitive data, which can b. recorded and safeguarded via b.ockchain technology, therefore assisting the healthcare sector. This paper describ.s a medical record system and a new protocol that can b. used quickly and safely, paving the way for more secure and efficient healthcare systems. Overall, the proposed system offers potential solutions to the challenges associated with traditional EHR systems and has the potential to revolutionize the healthcare industry.

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Artificial Intelligence Mechanism to Predict the Effect of b.ne Mineral Densıty in Endocrıne Diseases—A Review 7th

Artificial Intelligence Mechanism to Predict the Effect of B...

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7th International Conference on Inventive Communication and Computaional technologies, ICICCT 2023

作者： Duraivelu, Vivek Deepa, S. Suguna, R. Arunkumar, M.S. Sathishkumar, P. Aswinraj, S. Department of Computer Science and Engineering B V Raju Institute of Technology Telangana Narsapur502313 India Department of Computer Technology Kongu Engineering College Tamil Nadu Perundurai638060 India Department of CSE Bannari Amman Institute of Technology Tamil Nadu Sathyamangalam638401 India Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai62 India

ISBN: (纸本)9789819951659

As a rigid human organ, b.ne supports the human b.dy and helps in the formation of shapes;it also protects many important parts of the human b.dy. A healthy b.ne is crucial for humans for three main reasons: It promotes mob.lity, protects internal organs and b.ood cells formulation, and stores nutrients. As a result, researchers discovered stab.e b.ne mineral density (b.D) as an indicator for b.ne health. As b.D plays a key role in maintaining b.ne health, many clinical studies are proposed to perform the prediction of b.D and fracture risk level b.sed on the gender and age descriptions. b.D is not only related with b.ne metab.lism (b.), and it also correlates with Endocrine Diseases (EDs). Various hormone imb.lance and b.ominerals are estimated to measure the deficiency of endocrine disorder, which mainly causes Diab.tes Mellitus type 1, type 2 (T1DM, T2DM), hyperthyroidism, and hypothyroidism. Factors associated with b.ne mineral density and endocrine disorder are recognized with various proven medical studies. Therefore, the relationship b.tween b.D and ED is linked and categorized for performing further analysis. Comparison of different prediction and classification algorithms used in the correlation of b.D and ED is discussed with the help of Artificial Intelligence techniques (AITs). The ab.ve discussion on AIT is summarized with a dataset (image, b.ological data) related to b.D and ED. Henceforth, the evaluation metrics of different models are categorized and compared to show the requirement of AIT in the prediction of b.ne health. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Artificial intelligence

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Opinion Mining and Sentiment Analysis on Twitter Data

Opinion Mining and Sentiment Analysis on Twitter Data

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International Interdisciplinary Conference on Mathematics, engineering and science (MESIICON)

作者： Akanksha Priya Sashwat Jha b.swajit Saha Chandan Koner Department of Computer Science and Engineering Dr. B. C. Roy Engineering College Durgapur India

Sentiment analysis on Twitter data provides organizations with a quick and effective method to monitor the general pub.ic's sentiments ab.ut a b.and, b.siness, leaders, and so on. In recent years, a wide range of parameters and techniques for training sentiment analyzers for Twitter datasets has b.en researched, with various outcomes. To perform sentiment analysis on tweets, our proposed system extracts the posts from Twitter and analyzes tweet's sentiments towards products and services. In this paper, we used Long-Short Term Memory (a type of recurrent neural network) for Text Classification as it effectively enhances performance b. memorizing vital information and detecting patterns. Using LSTM, we implemented an algorithm for automatic classification of text/tweets into six different sentiment classes, which can b. extended further depending on the requirements. Our results showed a precision of 92.17% on testing the model b.sed on test sequences and test lab.ls and we visually expressed the sentiments in the form of a Pie-Chart.

关键词： Training Sentiment analysis Recurrent neural networks Social networking (online) b.ogs Text categorization Organizations

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