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检索条件"机构=Be in Computer Engineering L D College of Engineering"

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Smart Web Application for Efficient Management of Hospital Appointments

Smart Web Application for Efficient Management of Hospital A...

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2022 IEEE International Conference on Current development in engineering and Technology, CCET 2022

作者： Patil, Siddheshwar V. Patil, Shobha B. Terdalkar, Omarsharif A. Yelure, Bhushan S. D. Y. Patil College of Engineering and Technology Dept. of Computer Science and Engineering Kolhapur India Government College of Engineering Dept. of Computer Science and Engineering Karad India

ISBN: (纸本)9781665454155

The interest in medical care administrations is expanding as the populace develops, and the number of patients looking for care at clinics, clinical foundations, all-encompassing gatherings, and doctors' workplaces has significantly expanded. These present new hindrances for the office's laborers and directors. The most pervasive trouble that clinics, their administration, and their staff face are bringing down functional costs and accomplishing productivity objectives. In the interim, most clinics are working on a careful financial plan. Patients have generally been not able to move openly all through their visits and return because of their endeavors to smooth out the association. due to the shortcomings of existing appointment monitoring and management systems, this paper proposes an alternative and efficient approach for appointment monitoring. In this work, a smart-appointment booking system for patients to book appointments with storage facilities for medical reports and emergency service is proposed. A Health-Buddy BooknMeet system with online taking appointments to a specific hospital enables patients to check directly in without interacting with staff. © 2022 IEEE.

关键词： Emergency services

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Improving data Integrity for Gray Hole Attack detection by using a Hash Signature Algorithm in WSN 5

Improving Data Integrity for Gray Hole Attack Detection by u...

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5th International Conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Radhika, S. Srikanth, M.S. Anand, K. Saravanan, K. Southry, S. Sree Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Reva University School Computer Science and Engineering Karnataka Bangalore India Rajalakshmi Engineering College Department of Computer Science and Engineering Rajalakshmi NagarThandalam Chennai India R.M.D Engineering College Department of Information Technology Kavaraipettai Chennai India Sona College of Technology Department of Electronics and Communication Engineering Tamil Nadu Salem India

ISBN: (纸本)9781665474672

Nowadays, Sensor nodes are utilized in widespread distribution. Thus, security issues are a significant apprehension in the Wireless Sensor Networks (WSN). The gray hole attack is a particularly damaging kind of assault that, in addition to bringing down WSNs, brings down whole networks and interferes with the flow of data. A hash signature algorithm (IGdH) is proposed to solve these problems to improve data integrity for Gray hole attack detection. during the process of route discovery in the network, this strategy makes use of an algorithm that generates a hash signature to detect the Gray hole attack. The recipient node gets the message from any sensor and verifies the sensor node hash signature. during data transmission, the recipient node checks the principal communication count (PCC) and size of the data packet;if the packet size is equal Accept the message;otherwise, the recipient node decides some packets are dropped and isolates that node is a grayhole attacker. The simulation results explain the proposed method has better packet delivery and minimizes the packet loss and miss detection ratio in the WSN. © 2023 IEEE.

关键词： Sensor nodes

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Mission Concept development for the TERP RAPTOR (Terrapin Engineered Rideshare Probe for Rapid-response Asteroid Apophis Profiling, Tracking, Observing, and Reconnaissance)

Mission Concept Development for the TERP RAPTOR (Terrapin En...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Barbee, Brent W. Rudolph, Adrienne Storey, Cameron Prasad, Chinthan Bhingradiya, Kruti Vishnoi, Rahul Mahon, Ryan Philips, Sean Akin, david A. Bowden, Mary Young, Jarred Department of Aerospace Engineering The University of Maryland 3181 Glenn L. Martin Hall College ParkMD20742 United States Department of Computer Science The University of Maryland 1309 Kim Engineering Building College ParkMD20742 United States Space Systems Laboratory Department of Aerospace Engineering The University of Maryland 3181 Glenn L. Martin Hall College ParkMD20742 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The ∼350-meter diameter Potentially Hazardous Asteroid (PHA) designated 99942 Apophis 2004 MN4 will make an historic close approach of Earth on April 13th, 2029, passing within ∼31,634 km of Earth’s surface, ∼4,152 km closer than our geosynchronous satellites. Current asteroid population models suggest that this is a 1 in 7500 years event, so this is an extraordinarily rare and unique opportunity for an Earth-orbiting spacecraft mission to collect data relevant to planetary science and planetary defense on a several hundred-meter size asteroid while it experiences the effects of close proximity to Earth’s gravitational field. Our Terrapin Engineered Rideshare Probe for Rapid-response asteroid Apophis Profiling, Tracking, Observing, and Reconnaissance (TERP-RAPTOR) is an Earth-orbiting mission concept in which a 12U CubeSat built by University of Maryland students would perform a flyby of Apophis during its 2029 perigee. We present several design reference mission cases, including an orbit potentially reachable from a typical Geosynchronous Transfer Orbit (GTO) rideshare launch. TERPRAPTOR is an innovative design for a small and affordable University-built spacecraft capable of providing a higher ratio of scientific return to mission cost than any previous mission to an asteroid or comet. The world will be watching during Apophis’s historic Earth close approach, and TERP-RAPTOR will be our eyes in space, alongside any other spacecraft that the nations of the world might dispatch to study this extraordinary natural event. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Orbits

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Robust AI-Enabled Electronic Components Authentication and Anti -Counterfeiting 9

Robust AI-Enabled Electronic Components Authentication and A...

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9th International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Banu, E. Afreen Priyanka, R. Thiruramanathan, P. Senthilnathan, T. Vithya, V.T. Vinoth, K. Saveetha School of Engineering Simats Department of Computer Science Engineering Tamil Nadu Chennai602105 India S.A Engineering College Department of Computer Science Engineering Tamil Nadu Chennai600077 India Ramco Institute of Technology Department of Physics Tamil Nadu Rajapalayam626117 India Sri Venkateswara College of Engineering Department of Applied Physics Tamil Nadu Sriperumbudur602117 India Rmk College of Engineering And Technology Department of Computer Science Engineering Tamil Nadu Puduvoyal601206 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science And Technology Department of Electrical And Electronics Engineering Tamil Nadu Chennai600062 India

ISBN: (纸本)9798350365092

In consumer electronics, aircraft, health care, and defense, fake electronic parts compromise system security and reliability. This study presents an AI-powered electrical component authentication and anti-counterfeiting system for efficiency and robustness. To prevent counterfeit electronic components, a multi-layered defense uses cutting-edge authentication and AI algorithms. deep learning models for picture identification, spectroscopic analysis, and other cutting-edge component physical attribute evaluation. A decentralized blockchain platform can record the whole supply chain from producers to consumers. Smart contracts automate and enforce quality standards, eliminating many counterfeiting layers. An Integrated sensors and triggers detect physical tampering, alarm, and authenticate. Tracking and reporting component movements in real time permits quick response to suspicious activity. Stakeholders can easily validate components with AI algorithms via web or mobile apps. NFC, RFId, and QR code authentication is simple. To prevent counterfeiting, the framework specifies a stringent electrical component validation method. Advanced AI and physical and digital security measures provide comprehensive electrical component security throughout their lifespan. © 2024 IEEE.

关键词： Authentication

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An Experimental Evaluation of an Effective QR Code Based duplicate Product detection Using Blockchain Technology

An Experimental Evaluation of an Effective QR Code Based Dup...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Geetha, R. Jayakumar, d. Prabakaran, P. Nivedha, S. Sindhu, M. Thivyarathi, R.C. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electrical and Electronics Engineering Tamil Nadu Chennai India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India St.Joseph's Institute of Technology Department of Management Studies Tamil Nadu Chennai India Jeppiaar Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Rmk College of Engineering and Technology Department of Science and Humanities Tamil Nadu Chennai India

ISBN: (纸本)9798350375237

Over the span of the last few years, innovations in blockchain technology have received a great deal of attention. Currency exchange, which has a variety of applications in addition to digital money, is the subject that receives the most attention. Because of this, it may have an effect on multiple industries. large-scale financial transactions have become more transparent and straightforward as a result of the implementation of blockchain technology. Through the utilization of blockchain technology, we are able to recognize counterfeit merchandise. When it comes to making a purchase of any kind in this day and age, the question of authenticity frequently makes an appearance. In addition, studies have shown that these aspects are essential for the expansion of the economy. In light of this, it is of the utmost importance to educate consumers about the transparency of the items in order to decrease the number of counterfeit goods. With blockchain technology, we have taken a step closer to eliminating the ever-increasing presence of false and hazardous items from the global market. This is a cause for concern. Each and every person ought to be made aware of the fact that the utilization of technology will result in a reduction in the production of merchandise that is counterfeit. Every item must be given a one-of-a-kind digital code in order to guarantee that the production and packaging processes are carried out correctly. In this research, a novel method for detecting counterfeit goods is presented. This method is referred to as the Blockchain and QR based Product Analyzer (BQRPA). It undergoes cross-validation with the traditional Classical Fake Product Identifier (CFPI) in order to determine whether or not it is effective. Within the context of the software installation process, this programme performs a scan of the product code in order to ascertain whether or not the product in question is a counterfeit. © 2024 IEEE.

关键词： Blockchain

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An Accurate Stock Prediction Using Ensemble deep learning Model

An Accurate Stock Prediction Using Ensemble Deep Learning Mo...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Baswaraj, d. Rekha, Ravula Shashi divya, V. Natchadalingam, R. Sahni, Nancy Reddy, Pundru Chandra Shaker Computer Science and Engineering Vasavi College of Engineering Telanagana Hyderabad India Computer Science and Engineering Malla Reddy College of Engineering and Technology Hyderabad India CSE-Data Science R.L.Jalappa Institute of Technology Karnataka Bengaluru India Mittal School of Business Management Lovely Professional University Punjab Phagwara India School of Computer Science and Engineering Lovely Professional University Punjab Phagwara India

ISBN: (纸本)9798350305708

Financial textual, statistical, and graphical data have all seen increased interest in machine learning and deep learning as analytical tools in recent years. Anticipating the trend of a stock price in the future is challenging applications of deep-learning(dl) in economics. Several factors influence the amplitde &incidence of ascend and descend of stocks at the alike time, making it difficult to predict their future movement. In addition, these are merely company-level considerations;industry-performance, investor-mood, and economic-factors also have a role in determining the direction of equities in the future. In this research, we offer a unique deep learning method for forecasting stock price behavior in the future. The model combines two recurrent-neural-networks(RNN) with a fully connected NN using a mixing ensemble learning technique. The Standard & Poor's 500 Index serves as a case study for our investigation. Our blending ensemble-dl strategy significantly outperforms the best existing anticipation desgn on the same dataset by decreasing the mean-squared-error(MSE) by 58%, growing the precision by 41%, the recall by 52%, the F1-score by 45%, and the movement-direction-accuracy by 35%. The goal study is to detail our intend ethos and demonstrate how Edl may more correctly anticipate upcoming stock price patterns and help investors make sound financial decisions than more conventional approaches. © 2023 IEEE.

关键词： deep-learning Ensemble-learning Statistical-finance Stock-prediction

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Hybrid Blockchain and IoT driven Framework for Supply Chain Optimization by Enhancing Transparency, Efficiency and Cost Reduction 3

Hybrid Blockchain and IoT Driven Framework for Supply Chain ...

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Pradeep Kumar, S. Basha, C.H. Hussaian Prasath, C. Arun Amirthayogam, G. lathif, Syed Ismail Abdul leelavathi, R. Rajalakshmi Engineering College Computer Science Design Department Thandalam Chennai602105 India Sr University Department of Electrical and Electronics Engineering Warangal506371 India Mahendra Engineering College Department of Ece Namakkal637503 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai600062 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India Velalar College of Engineering and Technology Department of Biomedical Engineering Erode638012 India

ISBN: (纸本)9798331509675

Blockchain technology represents a modern supply chain management revolution which fixes operational challenges while providing enhanced transparency at reduced costs. The research develops HB-SCOF (Hybrid Blockchain-Enabled Supply Chain Optimization Framework) which combines blockchain self-verification databases with automatic smart contracts to maintain continuous supply chain observation and evaluate data credibility. The framework integrates tamper-proof transaction tracking mechanisms with unified supply chain network connectivity for securing data transmission as a trust delivery method through unbreakable shared databases. The retail-industry case study demonstrated a 25% decrease in expenses stemming from agency elimination alongside enhanced flow management and better stock distribution. The system demonstrates its effectiveness through assessments of key performance indicators including transaction speed and data accuracy together with business cost efficiency. This part looks at implementation methods through training stakeholders in addition to transforming organizational policies which produce successful outcomes. Blockchain technology labs verify its capability to enhance supply chain management efficiency while showing realistic deployment methods. © 2025 IEEE.

关键词： Smart contract

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Blockchain Enabled Intelligent Surveillance System Model with AI and IoT 8

Blockchain Enabled Intelligent Surveillance System Model wit...

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8th IEEE International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2023

作者： Sathyaseelan, K. Vyas, Tushar Madala, Ravikiran Chamundeeswari, Vijaya Rai Goyal, Himanshu Jayaraman, Raja Department of Information Technology Mallasamudram India Jecrc University Department of Computer Science and Engineering Rajasthan Jaipur India University of Cumberlands Ph.D Information Technology DurhamNC United States Saveetha Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Graphic Era Deemed to Be University Department of Computer Science Engineering Uttrakhand Dehradun India St. Martin's Engineering College Department of Computer Science and Engineering Secunderabad India

ISBN: (纸本)9798350347791

In the New Year, Internet of Things (IoT) is industrializing in a few certifiable applications, for example, clever transportation, brilliant city to make human existence reliable. Extreme amounts of detecting information are being delivered from various sensors devices in the Modern IoT as a result of the growing industrialization of IoT. Understanding the constraints of flow innovations and the potential for future exploration techniques is necessary to the establishment of a secure and dependable information environment. A dishonest individual can connect with a trusted person through the blockchain, a decentralized digital ledger that tracks the conversation from start to finish. This report urges the medical care industry to deploy blockchain-coordinated digital protection in order to preserve clinically relevant things in light of the use of artificial intelligence in clinical settings. Applications based on blockchain may be able to precisely pinpoint the most serious, potentially dangerous mistakes in the medical sector. Blockchain-based decentralized information insurance safeguards patient health records from data theft. © 2023 IEEE.

关键词： Blockchain

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Cognizant Care Machine learning-Assisted Smart Records for Improved Healthcare 2

Cognizant Care Machine Learning-Assisted Smart Records for I...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Mageshwari, G. latha, J. Naveen, G. Murugan, S. Karthick Joseph Gilbert Andrews, Allen R.M.K.College of Engineering and Technology Department of Artificial Intelligence and Data Science Tiruvallur Dist Puduvayal India R.M.K.College of Engineering and Technology Department of Computer Science and Engineering Tiruvallur Dist Kavaraipettai India Madha Institute of Engineering and Technology Department of Electronics and Communication Engineering Tiruvallur Dist Kavaraipettai India R. M. D. Engineering College Department of Computer Science and Engineering Tiruvallur Dist Kavaraipettai India Deloitte Consulting LLP 200 Sterling Road MechanicsburgPA United States

ISBN: (纸本)9798350317558

In the era of evolving healthcare demands, the requirement for innovation in record-keeping systems is undeniable. Traditional methods of documenting have difficulties in terms of efficiency, accuracy, and flexibility. The paper addresses an urgent need for a revolutionary solution by proposing "Cognizant Care,"a unique system that employs machine learning to build Smart Records, therefore revolutionizing healthcare documentation and decision-making processes. The inefficiencies of legacy systems, which include time-consuming manual data entry and limited predictive capabilities, highlight the need for a novel concept. Cognizant Care's architecture can be incorporated with existing Electronic Health Record systems, providing intelligent data extraction, predictive analytics, decision support, and automated reporting. The results and analysis show a significant improvement demonstrates superior performance with accuracy at 94%, precision of 92%, recall of 88%, and an F1 score of 90%, proving the system's ability to mitigate the drawbacks of existing systems. Cognizant Care emerges as an essential method signifying an evolving era in which the combination of human knowledge and artificial intelligence drives healthcare into a realm of unparalleled achievements. © 2024 IEEE.

关键词： Cognizant Care Cost Savings decision Support Electronic Health Records Healthcare Innovation Personalized Patient Care

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Methodical Tamil Character Recognition Using Fabricated CNN Model

Methodical Tamil Character Recognition Using Fabricated CNN ...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Bhavani, M. Ravikumar, S. Prithi, S. Arockia Raj, Y. Rajendiran, Babu Rajalakshmi Engineering College Department of Computer Science and Engineering Tamilnadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Chennai India School of Computing Department of Computational Intelligence SRM Institute of Science and Technology Chennai India PSNA College of Engineering and Technology Department of Computer Science and Engineering Dindigul India

ISBN: (纸本)9798350348217

Recognizing text is one of the most challenging problems in computer vision. To put it simply, handwritten character recognition is the process of recognising text in photographs, papers, and other media and converting it into a form that a computer can read. You can solve this issue by employing the image classification method. We will be able to recognise the user's typed Tamil characters in this paper. We designed a brand new model, MVGG16, to handle character recognition and classification. Its basic structure is analogous to that of VGG16, but we added a few more layers to improve accuracy. So far, 156 Tamil characters have been learnt, with 350 images each class. In experimental settings, this model achieves an accuracy of 91.8%. As an input method, this work makes use of a whiteboard where the user can scribble the Tamil character to be recognised. The character will be sent for verification after the user has written it and the image has been exported. Once the model identifies the character, it will show it to the user. © 2023 IEEE.

关键词： Character recognition

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