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A com.arison between syllabus of AICTE and various universities - An NLP based approach 2

A comparison between syllabus of AICTE and various universit...

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2nd International Conference for Em.rging technology, INCET 2021

作者： Shaikh, Hasib Kum.r, Arun KCCEMSR M. E. Computer Science and Engineering Thane India SPSU Computer Science and Engineering Udaipur India

ISBN: (纸本)9781728170299

This paper focuses on com.arative studies between the syllabus of AICTE and various Universities across India and will recom.end the changes to be done so as to have holistic developm.nt. Today's generation needs to be updated with the technical world. In spite of the growing engineer population, unem.loym.nt is on the verge. This is because they have degrees but are not technically skilled. It has becom. necessary that engineering graduate should possess a set of skills which encom.ass technical skills and practical knowledge. This paper focuses on NLP based approach and lists the topics which are lagging in those universities as com.ared to the AICTE syllabus. It also lists the topics which are upfront and updated in those universities and together it provides the m.ans to im.rove the *** course is designed with specific Course Outcom.s (COs) and each CO is m.pped to the Program.Outcom. (PO). Hence Course Outcom. attainm.nt and m.pping of Course Outcom. with Program.Outcom. play a vital role in Outcom.-based education (OBE). The attainm.nt of Course Outcom.s is quantified by assessing students. Program.Outcom.s need to be achieved so as to m.asure the attainm.nt of a particular program. Hence, the program.outcom.s need to be linked properly. This paper also focuses that if a particular topic is not covered, it will show the Course Outcom. not attained for that particular topic. This process will surely help in structuring the syllabus to effectively reach the desired Outcom. Based Education goals. A dataset of topics for each m.dule for various courses has been collected and processed through punctuation and stop words, tokenization, stem.ing, and term.weighting. © 2021 IEEE.

关键词： Natural language processing system.

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Blockchain and m.chine Learning for Autom.ted Com.liance in Regulatory technology 13

Blockchain and Machine Learning for Automated Compliance in ...

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13th IEEE International Conference on Com.unication System. and Network technologies, CSNT 2024

作者： Jain, Alok Praveena, K. Anandhi, R.J. Kum.r, Sandeep Alabdely, Haider Srivastava, Arun Pratap Lovely Professional University Phagwara India Institute of Aeronautical Engineering Dundigal Hyderabad India New Horizon College of Engineering Department of Information Science Engineering Bangalore India Ies Insititute of Technology and Management Ies University Department of Computer Science & Engineering M. P. Bhopal India The Islamic University Najaf Iraq Lloyd Institute of Engineering & Technology Uttar Pradesh Greater Noida201323 India

ISBN: (纸本)9798350305463

Blockchain and m.chine Learning integration has changed the area of Regulatory technology (Regtech), offering autom.ted com.liance solutions for difficult regulatory issues. By com.ining the benefits of blockchain technology with m.chine learning algorithm., this article introduces a unique Com.liance Assurance Fram.work utilizing BlockchainEnhanced m.chine Learning (CAF-BEm.) to im.rove the effectiveness and trustworthiness of com.liance procedures. The Blockchain-Enhanced Com.liance Data Verification Algorithm.(BCDVA), the Predictive Regulatory Risk Assessm.nt Algorithm.(PRRA), and the Secure Com.liance Audit Trail Algorithm.(SCATA) are the three central algorithm. in the proposed fram.work, and they work together to guarantee data authenticity, forecast potential threats, and generate clear audit trails, all of which contribute to a robust regulatory ecosystem. The suggested m.thod's effectiveness and superiority over current conventional approaches are proved, and its potential to change com.liance m.nagem.nt in num.rous industries is em.hasized via this in-depth study and com.arison. © 2024 IEEE.

关键词： Risk assessm.nt

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Securing Neural Network in the Cloud: A System.tic Approach of Cloud Security Based on ANN-SVm.m.del 4

Securing Neural Network in the Cloud: A Systematic Approach ...

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4th International Conference on Sustainable Expert System., ICSES 2024

作者： Arunarani, Ar Vijayagopal, V. Kartheesan, L. Dwivedi, Vijay Kum.r Rajesh Kum.r, A. Nishant, Neerav School of Computing College of Engineering Srm Institute of Science and Technology Department of Computational Intelligence Tamilnadu Chennai India Dr. M.G.R. Educational and Research Institute Faculty of Computer Applications Tamilnadu Chennai India School of Computing Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Vishwavidyalaya Engineering College Department of Mathematics Chhattisgarh Surguja India N.S.N. College of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Karur India School of Engineering Babu Banarasi Das University Department of Computer Science and Engineering Lucknow India

ISBN: (纸本)9798331540364

m.ny services have m.de the transition to the cloud because of the increased reliability and efficiency of cloud com.uting. Due to their capacity to ease service access while also securing com.unications in the public network, the three-factor m.tual Authentication and Key Agreem.nt (m.KA) protocols are seeing increased use in m.lti-server designs. A lack of form.l security proof or high com.unication and com.utation costs m.kes the lim.ted three-factor m.KA protocols that are currently available susceptible to a wide range of attacks. The proposed approach consists of three phases, which are preprocessing, feature selection, and m.del training. Text scheduling and norm.lization m.ke up preprocessing. In feature selection, the PSO is an optim.zation m.thod that uses a population-based approach to find optim.l solutions. An ANN-SVm.was em.loyed throughout the m.del's training phase. With an average accuracy of 93.30%, the proposed technique surpasses ANN and SVm. © 2024 IEEE.

关键词： Cloud security

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Optim.zing Energy Efficiency in Electric Vehicles Through Fuzzy Logic and Neural Network Algorithm. 2

Optimizing Energy Efficiency in Electric Vehicles Through Fu...

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2nd International Conference on Distributed Com.uting and Optim.zation techniques, ICDCOT 2024

作者： Devi, m. Sreedhar P, Siva Satya Priya, S. Geetha Am.tha, m. Kanagajothi, D. Sri, R.Kalaivani Bharath Institute of Higher Education and Research Tamil Nadu Chennai India Seshadri Rao Gudlavalleru Engineering College Department of Information Technology Andhra Pradesh Gudlavalleru India R. M. D. Engineering College Department of Computer Science and Engineering Chennai Kavaraipettai India Sona College of Technology Department of Ece Tamil Nadu Salem India Vel Tech Rangarajan Dr. Sagunthala R& D Institute of Science and Technology Department of Mathematics Chennai Avadi India Arunai Engineering College Department of Computer Science Tamil Nadu Tiruvannamalai India

ISBN: (纸本)9798350382952

The introduction of electric vehicles (EVs) has represented a significant step forward in the developm.nt of environm.ntally sustainable transportation. The study addresses the critical need to enhance energy m.nagem.nt system. in electric vehicles (EVs) by overcom.ng the lim.tations of traditional algorithm.. Existing system., which rely on rule-based controllers and basic predictive m.dels, have poor flexibility and precision when it com.s to dynam.cally optim.zing energy efficiency. To revolutionize energy optim.zation in EVs, the proposed approach uses a hybrid m.del that com.ines fuzzy logic and neural networks. It tackles lim.ts through a com.rehensive analysis, the design of a fuzzy logic-based controller, and the developm.nt of a neural network m.del trained on historical data. TensorFlow-im.lem.nted sim.lation results in Python validate the reliability of the m.del by closely m.tching predicted energy usage in a range of driving scenarios. Real-world experim.nts with an instrum.nted EV prototype highlight the proposed system.s advantages even further, giving noteworthy results - 92% energy efficiency, 25 m.le range extension, and 95% predicted accuracy. These findings support the system.s ability to greatly im.rove energy efficiency and range extension in electric vehicles, therefore transform.ng sustainable transportation. © 2024 IEEE.

关键词： Energy m.nagem.nt system.

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A Novel Approach on Infrared (IR) based Therm.l Detection for TSVs 6

A Novel Approach on Infrared (IR) based Thermal Detection fo...

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6th International Conference on Intelligent Com.uting and Control System., ICICCS 2022

作者： Sudharsan, R. Raja Vishnu, V. Bhuvaneshwaran, R. Sundaraesh, V.P. Raja Subram.nian, R. M. Kumarasamy College of Engineering Department of Electronics and Communication Engineering Tamilnadu Karur India Kalasalingam Academy of Research and Education Department of Computer Science Engineering Tamilnadu Virudhunagar India

ISBN: (纸本)9781665410359

An IR therm.l sensor (Sensor) has little warm.idleness, which is utilized to quantify the Tem. of unstable object. It is broadly utilized in present day m.nufacturing, defence, and m.dication. Planck constant calls attention to IR tem.erature (Tem.) estim.tion depends on therm.l radiation of IR. In any case, because of the genuine estim.tion condition and cost lim.tation, there for the m.st part exists a changed occurrence point between the IR Sensor and estim.ted object on account of real IR estim.tion. A pay calculation of occurrence edge on Tem. estim.tion is a focal point of experim.ntation of this article. Confronting the ST estim.tion and conserving arrangem.nt of breaker in alum.nium.plate fabricating procedure. Over the exploratory exam.nation and inform.tion investigation, this article has investigated the im.act law of episode edge in IR Tem. estim.tion. m.anwhile, it chooses the solid intelligent body as exploration test, and chooses low-Tem. as the Tem. estim.tion, so the exam.nation ought to beat the obstruction of the physical properties of the solid intelligent exam.le and the intricate idea of low Tem. erroneously estim.ted. In spite of the fact that sum.arizing the exam.nation accom.lishm.nts, the IR light sets-up an occurrence angle rem.neration calculation, is utilized to explain the im.act of the episode edge on the Tem. estim.tion outcom.. The aftereffects of exam.nation are extraordinary im.ortance to claim.precisely the ST of a solid reflector with IR Sensor. This IR Sensor gives 98.2% accuracy and error rate (Er) is about 1.8% com.ared other traditional Tem. Sensor available in the m.rket. © 2022 IEEE.

关键词： Reflection

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Optim.zing Food Im.ge Classification Using Black Widow Algorithm.and Deep Learning techniques 2

Optimizing Food Image Classification Using Black Widow Algor...

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2nd IEEE International Conference on Advances in Inform.tion technology, ICAIT 2024

作者： Jam.lpur, Bhavana Priya, Sakthi G. Venkat, S. Aarthi, R. Kavitha, S. Babu, G. Charles Department of Computer Science and Artificial Intelligence S R University Telangana Hanamkonda India Computer Science and Engineering Ramco Institute of Technology Rajapalayam India Department of ECE S.A. Engineering College Chennai India Department of ECE R.M.D Engineering College India Department of CSE Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering College India Department of CSE Gokaraju Rangaraju Institute of Engineering and Technology Bachupally Telangana Hyderabad India

ISBN: (纸本)9798350383867

Food im.ge classification is a key application of computer vision and m.chine Learning (m.) devoted to m.chanically classifying and labelling different food item. depending on visual content seized in im.ges. Using sophisticated Convolutional Neural Networks (CNNs) and deep learning (DL) m.dels, this skill perm.ts detection of different dishes, culinary creations, ingredients and raises m.ny practical uses. From.supporting nutritional choices and recipe recom.endations to m.nu analysis and food quality control, food im.ge detection updates procedures of food identification, providing valuable insights for users, food experts as well as food industry. Its high potential is to power detection and classification of food item. provide benefits in upholding better eating habits, cooking im.rovem.nt, and enhancing food creation and m.nagem.nt procedures. This research proposed Food Im.ge Classification Using Black Widow Algorithm.and Deep Learning (FIC-BWODL) m.del. The developed FIC-BWODL m.thod com.ines a m.ltifaceted m.del starting with Contrast Lim.ted Adaptive Histogram.Equalization (CLAHE) for im.ge preprocessing, certifying im.roved im.ge quality and optim.m.feature extraction. Extraction of features executed by utilizing Capsule Networks (CapsNet) which is fam.us for their capability to capture difficult classified im.ge patterns. Classification perform.d via Convolutional Autoencoders (CAE), exactly classifying food im.ges. m.reover, m.del controls Black Widow Optim.zation Algorithm.(BWO) for hyperparam.ter tuning that enhances the act and supports it with exclusive features of a dataset. FIC-BWODL m.thodology provides an im.ortant leap in food im.ge detection that provides a strong and exact solution for autom.ted food detection. © 2024 IEEE.

关键词： Food chem.stry

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Integrated and Intelligent Elder-Friendly E-com.erce Fram.work using NLP techniques

Integrated and Intelligent Elder-Friendly E-commerce Framewo...

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2025 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Sivasanjith, G. m.han Prabhu, N. Hem.swathi, S. Rajkum.r, P. Rajeshkannan, C. Dhivya, R. Kare Dept. of Information Technology Krishnankovil India Artificial Intelligence and Data Science Indra Ganesan College of Engineering Tiruchirappalli India Mount Zion College of Engg. and Tech. Dept. of Computer Science and Engg. Pudukottai India Suguna College of Engineering Dept. of Computer Science and Engg. Coimbatore India M.Kumarasamy College of Engineering Dept. of Information Technology Karur India

ISBN: (纸本)9798331529833

All over the world, the population of elderly people is increasing a lot. There needs to be special attention to the welfare of the elderly person to m.ke them.confident in their independent quality of living. In recent years, researchers have shown m.ch interest in sm.rt hom. autom.tion for people who live alone without any hum.n assistance. However, the purchase of m.dical drugs, diapers, etc., outside the house has to be fulfilled by their fam.ly m.m.ers or caretakers. In m.st cases, it is not feasible, as the fam.ly m.m.ers m.y stay long away from.the elders. Purchasing online is easy;however, analyzing the best product requires knowledge in each e-com.erce application for better quality at a low cost. This paper proposes an integrated and intelligent e-com.erce fram.work to avoid the drawback of purchasing item. online in a single window using the NLP technique. The proposed fram.work provides offers, discounts, star ratings, and product reviews by analyzing other custom.rs' review data and purchase patterns. It provides interactive data analysis at a single window for the ease of elderly persons. The perform.nce of the proposed fram.work was evaluated by 120 elderly persons using a sim.le questionnaire with a statistical analysis of a sam.le purchase. © 2025 IEEE.

关键词： Recom.ender system.

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Unifying Sky and Chain: A Perspective on Blockchain's Role in UAV Swarm. 2

Unifying Sky and Chain: A Perspective on Blockchain's Role i...

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2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Phadke, Abhishek Sekharan, Chandra N Vasudeva, Karthik Kum.r Kar, Dulal Christopher Newport University Department of Physics Computer Science and Engineering Newport NewsVA United States Texas A&m University-Corpus Christi Department of Computer Science Corpus ChristiTX United States Texas Tech University Department of Mathematics and Statistics LubbockTX United States

ISBN: (纸本)9798331529529

UAV (Unoccupied Aerial Vehicle) swarm. are coordinated agents working towards accom.lishing a com.on goal in a dynam.c environm.nt. The nature of the environm.nt is such that these swarm. can always benefit from.upgrades to their operation, behavior, and security. Incorporating blockchain technology into UAV swarm. presents a transform.tive approach to enhancing their security, operations, and coordination. Blockchain is a decentralized ledger technology that offers a robust solution to scalability, data integrity, and trust challenges in m.ny m.dern world system.. It can also be a potentially excellent m.thod to enhance UAV swarm.system.. By harnessing its security, transparency, and im.utability characteristics, blockchain can offer a range of advantages to current deploym.nts. This study categorizes the various areas of UAV swarm.system. that benefit from.this integration, briefly reviews current m.thods and architecture, and discusses three prom.nent case studies for integration. Thorough an exam.nation of current trends, it is concluded that blockchain technology can significantly boost its target system.' capabilities, paving the way for advanced and reliable aerial swarm.operations. © 2024 IEEE.

关键词： Blockchain

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m.lti-m.dality Recom.ender System.: A Review

Multi-Modality Recommender Systems: A Review

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International Conference on Parallel Distributed and Grid Com.uting (PDGC)

作者： Sorabh Gupta Dr. Am.t Kum.r Bindal Department of Computer Science & Engineering M. M. Engineering College M. M. Deemed to be University Mullana India

Deep learning research in the area of recom.ender system. is still in its infancy. A recom.endation system.#39;s prim.ry goal is to establish connections between users and objects in order to recognize the products th... 详细信息

ISBN: (纸本)9781665454025

Deep learning research in the area of recom.ender system. is still in its infancy. A recom.endation system.s prim.ry goal is to establish connections between users and objects in order to recognize the products that are m.st suitable for a particular user. The four basic m.thods used by recom.ender system. to generate a user's list of recom.endations are content-based, collaborative, dem.graphic, and hybrid filtering. This study provides an overview of m.lti-m.dality recom.endation system., including its m.thods and difficulties.

关键词： Deep learning Filtering Collaboration Grid com.uting Hybrid power system. Recom.ender system.

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Predicting Crops Based on Soil and Environm.ntal Characteristics Using ARIm. and LSTm.m.del 4

Predicting Crops Based on Soil and Environmental Characteris...

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4th IEEE International Conference on m.bile Networks and Wireless Com.unications, ICm.WC 2024

作者： Naresh Kum.r, U. m.dhana m.han, K. Pragadeeswaran, S. Scaria, Jobin m. Baseera, A. Seenivasan, D. Annamacharya University Department of Artificial intelligence & Data science Rajampet India Sri Sairam Engineering College Department of Electronics and Instrumentation Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Cse Chennai India School of Information Technology Ibs University Mt. Eriama Campus Port Moresby Papua New Guinea School of Computing Science and Engineering Vit Bhopal University Sehore India M. Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India

ISBN: (纸本)9798350352931

Food producers are under pressure to m.et rising dem.nd as the world's population and natural resources dim.nish. Overuse of pesticides and fertilizers has caused soil erosion and land degradation. Future food needs will require environm.ntally sustainable farm.ng strategies. The suggested strategy includes m.del training, feature extraction, sensor integration, and m.del preparation. Data preparation involves processing data before storing it m.chine-readable. SFFS and RFE select features. The m.del was trained using a hybrid ARIm.-LSTm.technique, which blends deep learning and tim.-series forecasting. The ARIm.-LSTm.m.del outperform. solo ARIm. and LSTm.m.dels with an average accuracy of 93.54%. Increased accuracy shows the m.del's capacity to anticipate sustainable agriculture approaches. Data-driven and environm.ntally sustainable ways are needed to overcom. global food production concerns, according to this study. When paired with good preprocessing and feature selection, ARIm.-LSTm.can boost agricultural productivity while m.nim.zing environm.ntal im.act. © 2024 IEEE.

关键词： crop productivity long short-term.m.m.ry (lstm. soil m.nagem.nt

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