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检索条件"机构=Computer Science And Engineering V.S.B Engineering College"

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A survey on Memory Assistive Technology for Elderly 5th

A Survey on Memory Assistive Technology for Elderly

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5th EAI International Conference on big Data Innovation for sustainable Cognitive Computing, bDCC 2022

作者： shikha, N. Choudhury, Antara Roy Department of Computer Science and Engineering B.M.S. College of Engineering Bangalore India

ISBN: (纸本)9783031283239

Technology cannot solve all age-related problems;however, they have the potential to relieve a significant amount of stress on elderly and their family. In this paper, existing memory assistive techniques for elderly are reviewed, and the idea of a smart memory companion is presented. The application leverages the personalized digital journal curated using historical and daily life experiences of the elderly to aid the aged in early stages of Alzheimer. The implementation proposed in this paper focuses on using automatic speech recognition and natural language processing techniques to build an intelligent conversational agent, retrieval engine, and an alerting module to help the elderly person in recalling and outdoor safe navigation. The smart application is meant to reduce the burden on the family to continuously monitor their aged loved ones and avoid caretakers unless necessary. The companion can be used to collect memories in visual and textual format from elderly, family, and caretakers to utilize it when needed. The companion can also be integrated with existing virtual assistants like Alexa and Google Home. © 2023, The Author(s), under exclusive license to springer Nature switzerland AG.

关键词： Location based services

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Enhancing Data Privacy in IoT Cloud Environments with Trust Management 5

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

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5th IEEE International Conference on Recent Trends in computer science and Technology, ICRTCsT 2024

作者： Goyal, Himanshu Rai vanitha, A. Karthikeyan, T. Adhikary, Priyabrata saranya, R. Kiran Kumar, s. Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha Engineering College Department of Management Studies Chennai India Sona College of Technology Biomedical Engineering Tamilnadu Salem India New Horizon College of Engineering Department of Mechanical Engineering Bangalore India V. S. B. Engineering College Department of Computer Science and Engineering Karur India St. Martins Engineering College Department of Computer Science and Engineering Telangana Secunderabad India

ISBN: (纸本)9798350351378

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 problem, yet this shift is inevitable. The goal of this research is to improve data privacy by using trust management systems, and a technique to do so has been presented. Our method includes building a trust model to quantify the reliability of IoT devices and cloud service providers, and a privacy model to evaluate the potential dangers of data sharing. To find a happy medium between 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 reliability, privacy risk, and the opportunity for businesses to make educated choices about data sharing. Our approach has far-reaching ramifications for many groups of people, including the IoT sector, businesses, regulators, and the general public. With the goal of improving and extending data privacy solutions in the ever-changing IoT world, future research paths include personalization, real-time adaption, scalability, user-centric controls, and ethical concerns. © 2024 IEEE.

关键词： Internet of things

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Facial skin Analysis for Detection of Dark Circles and Acne 3

Facial Skin Analysis for Detection of Dark Circles and Acne

引用

3rd International Conference on Artificial Intelligence and smart Energy, ICAIs 2023

作者： Kiran, M.K. Meda Ravi, Kusum Umadevi, v. B.M.S. College of Engineering Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9781665462167

The aim of this research is to analyze and detect the most commonly found facial skin conditions like acne vulgaris and dark circles. In the skin analysis algorithm, the occurrences of facial acne and dark circles are detected by using existing computer vision algorithms such as Otsu's thresholding algorithm and Deep Learning (DL) techniques. These techniques are further modified to suit the prepared dataset and achieve greater value of evaluation metrics. This article proposes two techniques for the detection of dark circles, which are the difference in skin Tone Pixel values and the Thresholding Technique and compare their performance. In the Thresholding Technique, the IoU obtained was 0.737, which provided better visualization of the affected region. Further, acne detection was carried out using two deep learning backbones viz, Inception ResNet 50 and MobileNet. The accuracy obtained for both the methods was 99%. © 2023 IEEE.

关键词： Deep learning

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Multimodal Misinformation Mitigation using Convolutional and Knowledge Transfer Learning Approach 3

Multimodal Misinformation Mitigation using Convolutional and...

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3rd International Conference on sentiment Analysis and Deep Learning, ICsADL 2024

作者： Rathod, Nachiket Ramteke, Prabhakar H.V.P.M 'S College of Engineering and Technology Deaprtment of Computer Science and Engineering Amravati Mahrashtra Amravati India

ISBN: (纸本)9798350396157

In the era of information proliferation and digital media, the battle against the spread of misinformation has evolved into a critical challenge. This work presents an inclusive exploration of the pinnacle in misinformation mitigation, employing a multimodal method that integrates textual and visual data. Advanced techniques in knowledge transfer learning are used to develop and evaluate models for Misinformation detection based on textual content, images, and their fusion. DistilFND, a distillation of diverse models specialized in different modalities, is a focal point of proposed research. The paper involves a systematic analysis of training and testing these models on a shared dataset, enabling a comparison of their performance and the provision of insightful evaluations. Cohen's Kappa scores and ROC-AUC scores are also computed to gauge the models' efficacy. This extensive study marks a significant advance in misinformation mitigation, with knowledge transfer learning and multimodal fusion serving as pivotal elements of progress. by means of a sequence of detailed experiments and evaluation metrics, this work enhances to an improved understanding of how knowledge transfer learning, multimodal fusion, and pinnacle models can boost the correctness of Misinformation detection. The results and insights in this work aid the ongoing efforts to combat the detrimental impacts of misinformation in the digital sphere. © 2024 IEEE.

关键词： Convolutional neural networks

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Exploring the Transformative Convergence of IoT and Fog Computing for Healthcare, Agriculture, Urbanization, and Transportation 6

Exploring the Transformative Convergence of IoT and Fog Comp...

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6th International Conference on Recent Trends in Advance Computing, ICRTAC 2023

作者： suresh, Kotari Humera Khanam, M. S. V. University College of Engineering Department of Computer Science and Engineering Tirupati India

ISBN: (纸本)9798350394702

The integration of IoT and fog computing technologies has the potential to revolutionize a number of sectors, including healthcare, agriculture, urbanization, and transportation. Real-time human health monitoring, sensor-generated bio-signals, and wireless communication protocols enable effective decision-making, medication management, and diagnostics in the healthcare industry while protecting sensitive medical data. Fog computing and Internet of Things solutions for agriculture improve production management and pest control using wireless sensor networks, giving farmers the most recent data on the state of the environment, the health of their crops, and pest activity. Fog computing and the IoT provide sustainable growth and better urban services, resource allocation, and citizen experiences in smart city efforts, solving difficulties brought on by expanding urban colonies. Fog computing and the IoT also benefit transportation systems, particularly through the use of vehicular ad hoc networks (vANETs), which improve driving experiences, traffic efficiency, and traffic forecasting, ultimately resulting in increased safety, fewer accidents, and better overall infrastructure for transportation. by utilizing real-time data analytics, connectivity, and intelligent decision-making, the convergence of fog computing and IoT presents a significant opportunity to address pressing issues in healthcare, agriculture, urbanization, and transportation. This will help to create a future that is more effective, sustainable, and interconnected across many industries. © 2023 IEEE.

关键词： Fog computing

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Text Transmission Through Li-Fi in WsN Using smart based secure Morse Code Algorithm

Text Transmission Through Li-Fi in WSN Using Smart Based Sec...

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2025 International Conference on Multi-Agent systems for Collaborative 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

Cyber 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 based 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 based 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 (symbols)

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Unveiling blockchain's Potential with Consensus Algorithms and Real-World Applications in supply Chain Management 2

Unveiling Blockchain's Potential with Consensus Algorithms a...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging business Technologies, TQCEbT 2024

作者： balasubramani, M. subathra, K. Agarwal, swathi bamini, J. Aeron, Anurag Gangadevi, E. V.S.B. Engineering College Department of Computer Science and Engineering Karur India Sri Sairam Engineering College Department of Mathematics Chennai India Cvr College of Engineering Department of It Hyderabad India Sri Ramakrishna College of Arts & Science Coimbatore India Miet Meerut Department of Cse Meerut India Loyola College Department of Computer Science Chennai India

ISBN: (纸本)9798350384277

blockchain technology in the supply chain is set to transform how businesses conduct and transact their businesses. This study explores the transformative potential of blockchain through an analysis of key results in four critical areas: transparency and traceability, efficiency and cost reduction, security and fraud prevention, and interoperability with novel technologies. The prospects of blockchain technology are enhanced transparency and traceability through real-time v.s.bility on the movement of products and exact tracing of product origins and histories. This high level of transparency creates trust among the participants in supply chain and smoothens the dispute resolution. Automation of blockchain has led to substantial efficiency gains as manual tasks and operational delays reduce. such improvements have reduced the operational costs by 15% making the supply chains more agile and efficient. Through an impressive 98% reduction in security incidents and 95% decrease in fraud incidents after blockchain implementation, security improvements are noticeable. The tamper-resistant properties of blockchain play a huge role in achieving these results and ensure the trust of the stakeholders. The integration of emerging technologies, including the IoT and AI, has only made supply chain capabilities broader. Integrating IoT devices effectively enables real-time data capture and surveillance;AI-powered data analytics give actionable intelligence for data-driven decision-support. © 2024 IEEE.

关键词： blockchain

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Prediction of Kidney Disease Utilizing a Hybrid Deep Learning Methodology 2

Prediction of Kidney Disease Utilizing a Hybrid Deep Learnin...

引用

2nd International Conference on computer, Communication and Control, IC4 2024

作者： Nallarasan, v. Ponnusamy, vijayakumar Lakshminarayanan, R. sona, K. vigneshwari, s. vinoth, R. Srm Institute of Science and Technology School of Computing Department of Networking and Communications Chengalpattu Kattankulathur India Srm Institute of Science and Technology Department of Electronics and Communications Chengalpattu Kattankulathur India Sri Ramakrishna Engineering College Department of Computer Science and Engineering India V.S.B College of Engineering Technical Campus India Gojan School of Business and Technology Department of Information Technology RedhillsTamilnadu Chennai600052 India

ISBN: (纸本)9798350387933

The kidney is an essential organ inside the human body, playing a crucial role in several physiological processes. One of its primary roles is the filtration of waste products and surplus fluids from the bloodstream, facilitating their subsequent elimination via urine production. In order to mitigate potential life-threatening complications, it is essential to identify and investigate chronic renal illnesses. The suggested method takes into account the limitations of early prediction and robust decision-making oscillations due to the presence of False Positive Rates in Kidney CT Images. The suggested system incorporates a hybrid method that combines machine learning and deep learning techniques. A prognostic method is developed by using the kidney dataset collected from TCIA, which involves the analysis of patients' past health information. The suggested system incorporates a hybrid approach of random forest regression and multinomial regression algorithms to identify the Explorer data analysis technique for the chronic kidney disease dataset. The secondary approach involves using a computer tomography image dataset obtained from the TCIA public data set. This dataset is processed using a deep convolutional neural network (DCNN) architecture that has many layers of deep convolution filters. The purpose of this architecture is to accurately detect and classify kidney abnormalities within the images. The integration of main and secondary outcomes is used to determine the presence or absence of renal disease in a patient. In this study, we examine a unique methodology known as Hybrid Deep K-Net (H-DKN). The accuracy reached by HDKN is reported to be 97%. Furthermore, we compare this approach with many state-of-the-art methods that have been established on the current platform. © 2024 IEEE.

关键词： Decision making

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bone Fracture Prediction Using Machine Learning and Deep Learning Techniques

Bone Fracture Prediction Using Machine Learning and Deep Lea...

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International Conference on Machine Learning and big Data Analytics, ICMLbDA 2023

作者： vamsi Kumar Appala, satya Jagadeesh, s.v.v.D. Durga satish, M. sridevi, b. Department of Computer Science B V Raju College Bhimavaram AP Vishnupur India Department of Computer Science & Engineering Vishnu Institute of Technology Bhimavaram Vishnupur India

ISBN: (纸本)9783031513374

bones play a significant role in human body support, allowing us to use our muscles to walk, ride a bike, and hold a child. A bone fracture is a medical condition that occurs when a bone is cracked or broken due to an accident or trauma. Fractures can range in severity from a small crack in the bone to a complete break, where the bone is broken into two or more pieces. Accidents are one of the most common causes of bone fractures, and they can occur in a variety of ways, such as falls, sports injuries, car accidents, and workplace accidents. The severity of the fracture depends on the amount of force applied to the bone, the location of the fracture, and the age and health of the person. To deal with this problem, it requires an essential need of prediction system for the detection of bone fractures in the human body. The artificial intelligence subfield of machine learning offers distinguished assistance in event prediction and trains its models using data from real-world occurrences. In this chapter, ML and DL algorithms for predicting bone fractures using support vector machine, decision tree, random forest, and convolutional neural network (CNN) algorithms are discussed. Out of these, svM outperformed with 86% accuracy. © The Author(s), under exclusive license to springer Nature switzerland AG 2025.

关键词： Convolutional neural networks

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smart Energy Management system Using IoT for Real-Time Monitoring and Theft Detection 9

Smart Energy Management System Using IoT for Real-Time Monit...

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9th International Conference on Information Technology and Digital Applications, ICITDA 2024

作者： Thinakaran, Rajermani Jalari, somasekar Neerugatti, vikram Cholla, Ravindra Raman Rao, K Nagendra Inti International University Faculty of Data Science and Information Technology Malaysia Faculty of Engineering and technology Department of Computer Science and Engineering Bangalore India S V College of Engineering Department of Computer Science and Engineering Andhra Pradesh Tirupati India

ISBN: (纸本)9798331510732

The internet of things technology has developed almost all the sectors including energy management. In traditional energy management system meters are used to recording the number of units and electricity used but they are unable to provide the real time information or updates or any theft of electricity. by focusing this problem, we have developed a system which is able to overcome all the problems in traditional electric management system. It monitors the energy usage and real time theft detection of electricity as it cost lot of money. In our system we have used a current sensor which continuously checks the electricity flow. The microcontroller measures the actual energy usage as well as expected values. It compares both the values. If a big difference found, then it could mean the theft of electricity. so, the GsM module is used to send the alert to the user hence they can take required action. The Wi-Fi module sends the data over the cloud for data analytics. Also, user can see the real time data from the cloud platform. Hence user can track the energy usage and get timely alerts so that user can be aware of energy consumption or energy theft. The system is developed by setting up hardware parts as well as integration with software. The system can be operated or monitored from remote place, as Wi-Fi module connects the system with the internet. system can detect the unusual activities like theft of electricity by analyzing the data. Using the IoT technology for energy management, it can become cost effective as well as smart solution of energy management to avoid any theft. Hence it can overcome the loss. © 2024 IEEE.

关键词： Energy utilization

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