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Achieving Seamless Semantic Interoperability and Enhancing Text Embedding in Healthcare IoT: A Deep Learning Approach with Survey

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SN Computer Science 2024年第1期5卷 99页

作者： Purushothaman, Sony Shanmugam, G. Siva Nagarajan, Sureshkumar School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Computer Science Govt. Model Engineering College Kerala Kochi India Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamil Nadu Krishnakovil India

Achieving semantic interoperability in healthcare is one of the significant challenges in the rapidly expanding healthcare sector. On the other hand, IoT in healthcare can provide patient-centric treatment mechanisms to help resolve these issues. When several healthcare organizations are generating heterogeneous medical information, semantic interoperability becomes essential to develop better treatment plans and better medical research. In this article, we discuss the applications of healthcare IoT, a comparative study of existing solution paradigms for achieving semantic interoperability and its enabling technologies. The comprehensive analysis of semantic interoperability has versatile dimensions to meet this, and it establishes deep learning-based directions. In continuing the background work, we proposed a new deep learning model called MedRelBERT with six embeddings to remove linguistic ambiguities in medical documents. The survey also examines the bibliographic evaluation of Web of Science articles discussing semantic interoperability solutions. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Deep learning Internet of medical things Privacy Semantic interoperability

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Church Sustainability: Exploring Online Technologies through the Lens of System Dynamics 28

Church Sustainability: Exploring Online Technologies through...

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28th Americas Conference on Information Systems, AMCIS 2022

作者： Matobobo, Courage Bankole, Felix University of South Africa School of Computing College of Science Engineering & Technology South Africa

ISBN: (纸本)9781958200001

Online technologies such as social media and videoconferencing platforms have changed the way church leaders access information and communicate with congregants. The paper investigates the value of online technologies in creating church sustainability using system dynamics. Exploring Seventh-day Adventist (SDA) as the case study, the researchers interviewed 12 religious leaders. The results showed that church leaders were using online technologies to create online communities within their congregations which were crucial for addressing the communication and informational needs of various church leaders as well as aiding the retention of church members. The study concludes that online technologies have the potential to sustain religious organisations. The study provides insight to the church leaders regarding the value of online technologies in church sustainability. © 2022 28th Americas Conference on Information Systems, AMCIS 2022. All Rights Reserved.

关键词： Social networking (online)

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Real Time Motion Capture for Physical Rehabilitation Using Kinect

Real Time Motion Capture for Physical Rehabilitation Using K...

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Smart Systems for applications in Electrical Sciences (ICSSES), International Conference on

作者： Singireddy Srijay Reddy Nagumalla Yasash P. Rama V. Angayarkanni J. Kalaivani Faculty of Engineering and Technology Computing Technologies College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur TN India Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Chennai Department of Computing Technologies Faculty of Engineering and Technology SRMIST Kattankulathur

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

This Project is a Kinect-based rehabilitation system designed to assist patients with movement disorders by performing targeted physical exercises at home. This system enables the evaluation of whether patients are correctly executing the prescribed rehabilitation exercises. By utilizing the skeletal tracking capabilities of the Microsoft Kinect sensor, each movement of the patient during the exercises is recognized and *** research introduces a real-time motion capture system designed for physical rehabilitation using Microsoft's Kinect sensor. The system addresses the growing demand for remote, data-driven healthcare solutions that assist in rehabilitation exercises by tracking and analysing skeletal movements. The Kinect's ability to track 25 joints in real time provides a unique opportunity to offer non-intrusive monitoring, real-time feedback, and data collection for therapists and patients. While Kinect offers several advantages, including cost-effectiveness and ease of use, our study identifies several limitations in precision, especially for complex movements and occlusion scenarios. This paper details the system's design, testing, and evaluation, highlighting areas where future improvements are necessary.

关键词： Accuracy Target tracking Tracking Smart systems Motors Real-time systems Motion capture Monitoring System analysis and design Testing

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Understanding Cybercrime: A Study of Malware Analysis, Phishing Attacks, and Sentiment Trends 3

Understanding Cybercrime: A Study of Malware Analysis, Phish...

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3rd International Conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Kumaran, U. Sreeraag, G. Narendran, Advik Meena, V.P. Gupta, Sushil Kumar Appaji, Abhishek Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bangalore India National Institute of Technology Department of Electrical Engineering Jharkhand Jamshedpur831014 India Bms College of Engineering Department of Medical Electronics Engineering Bangalore India

ISBN: (纸本)9798331515911

With the rapid evolution of computer systems and technologies, individuals face an increasing threat of cybercrime. This research explores the changing landscape of cybercrime by focusing on three key areas: malware analysis, phishing attack analysis, and sentiment analysis. The study aims to identify malware strategies for evading detection and analyze the prevalence of spyware by examining diverse malware samples. Additionally, trend analysis highlights the rising complexity and frequency of phishing attacks, with a notable shift toward targeting reputable platforms. Sentiment analysis of media headlines surrounding data breaches uncovers a paradox: while concerns about cybersecurity remain, there is a growing confidence in the ability to manage cybersecurity crises. These findings provide insights into emerging threats and evolving public perceptions, offering a comprehensive understanding of the current cyber- crime landscape. © 2025 IEEE.

关键词： Phishing

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Testing user Attitudes in IoT-load interface Based Healthcare attention management system 4

Testing user Attitudes in IoT-load interface Based Healthcar...

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4th IEEE International Conference on Advance computing and Innovative Technologies in engineering, ICACITE 2024

作者： Tewari, Ramanuj Alsalami, Zaid Alsailawi, H.A. Kirubanantham, P. Dhabalia, Dharmesh Saadoun, Osama Nazim Abdulhussain, Zahraa N. Alwan, Ali Saad Graphic Era Hill University School of Management Uttarakhand Bhimtal India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq University of Kerbala College of Medicine Department of Chemistry and Biochemistry Kerbala56001 Iraq Srm Institute of Science and Technology School of Computing College of Engineering and Technology Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur SRM Nagar Chennai India Vishwakarma Institute of Information Technology Information Technology Pune India Al-kunooze University College Law Department Basra Iraq National University of Science and Technology College of Technical Engineering Dhi Qar64001 Iraq Kut University College Business Administration Department wasit Al kut52001 Iraq

ISBN: (纸本)9798350360165

The study aims to analyze consumer perception toward adopting Internet of Things (IoT) technology in healthcare. In contrast to earlier studies that focused on the technical aspects, the proposed integrated paradigm measures how user trust is affected by the existence of security and privacy concerns, and knowledge of the Internet of Things. The proposed architecture presents a holistic system for health data management that is secure and efficient in modern health systems, designed and developed using four layers: hospital, remote IoT integrated medical device, distributed medical record, and AI-based smart contract. The system is supposed to enhance security of data and efficiency in its management with integration of the blockchain technology and the AI-based intelligence. The hospital layer is similar to the database that stores the data of the patient, and the distributed medical record layer makes the storage of the data and the access from it secure through blockchain. The data transfer of the health parameters of the patient through the IoT-enabled medical node can be done using the blockchain. The Al-based smart contract layer brings in the intelligence of the system for automatic decision-making and proactive breach detection. Evaluation was made on the system's performance under different conditions, such as transaction processing time, average delay, where it demonstrated scalability, reliability, and robustness in the management of health data and hence sounds quite promising for this domain of modern healthcare. © 2024 IEEE.

关键词： Electronic health record

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Snowfall Forecasting with Enhanced Accuracy: Leveraging Multi-Class SVM for Meteorological Predictions 7th

Snowfall Forecasting with Enhanced Accuracy: Leveraging Mult...

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7th IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Ranjith Kumar, M. Sudeesh Kumar, V. Tharun Kaarthik, G.K. Chatiyode, Veda Srinivasan Anusha, Janani Revathi, P. School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai600127 India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Department of Computer Science and Engineering C Abdul Hakeem College of Engineering and Technology Tamil Nadu Melvisharam India

ISBN: (纸本)9783031699856

The use of multi-class Support Vector Machines (SVM) for snowfall prediction is an advanced meteorological application. The study emphasizes how valuable snowfall forecasts are in various contexts, including agriculture, aviation, transportation management, and climate reporting. This approach presents a novel methodology for classifying snowfall types by analyzing various meteorological factors such as temperature range, wind dynamics, and precipitation. A 400-entries of datasets were pulled from GitHub to demonstrate the methodology. The sample is selected to reduce the complexity and to increase the performance. The dataset is split into a testing set (30%) and a training set (70%), which aids in assessing the model’s performance in a wide range of parameters. When the algorithm was first tested, it could distinguish different types of snowfall with a remarkable 83% accuracy rate based on indicators such as Temperature (min & max), Precipitation, Wind Speed, and Wind Gust. By optimizing the SVM configuration through hyper-parameter tuning approaches such as grid search, we were able to further refine our model’s accuracy to an astounding 91%. This improvement in forecast accuracy signifies a significant move away from older, more expensive instrument-based methods and towards data-driven snowfall analysis. Our results show how machine learning can revolutionize weather prediction systems, providing a more effective and economical method of comprehending and predicting snowfall patterns. © IFIP International Federation for Information Processing 2024

关键词： Snow

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Shortest Job First with Gateway-based Resource Management Strategy for Fog Enabled Cloud computing 4

Shortest Job First with Gateway-based Resource Management St...

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4th IEEE International Conference on Data engineering and Communication Systems, ICDECS 2024

作者： Anbazhagan, K. Kumar, Rotash Thilagavathy, R. Anuradha, D. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Government Engineering College Department of Electronics and Communication Engineering Rajasthan Jhalawar India College of Engineering and Technology Srm Institute of Science and Technology Kattankulathur Department of Computing Technologies Chennai India Panimalar Engineering College Department of Computer Science and Business Systems Chennai India

ISBN: (纸本)9798350393354

In recent years, fog computing has extended cloud services to the network edge, lowering network latency and congestion and overcoming cloud computing restrictions. Many hurdles, however, must be overcome before the benefits of the fog-IoT paradigm for low-latency applications can be completely realized. The most challenging difficulty in IoT applications is developing efficient resource management strategies that maximize throughput while minimizing delay. IoT and fog computing, rather than simply utilizing cloud computing technology, have brought intriguing new data management solutions. Fog computing makes real-time analytics applications conceivable. After combining fog computing technologies with Internet of Things (IoT) applications, the system can reply in milliseconds. Existing fog resource managers focus on a subset of fog resource management parameters such as system response time, network bandwidth, energy consumption, and latency. No Fog resource management takes multiple factors into account at the same time for decision-making, which will become increasingly crucial in intelligent homes. Gateway-based Fog computing pioneered the introduction of the shortest job (SJFGFC) to address these difficulties. The technique is validated in an IoT-based imaginative house automation scenario before being evaluated in a small-scale bright home experiment using the iFogSim toolbox and empirical models. © 2024 IEEE.

关键词： Fog computing

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Comparative Analysis of Machine Learning Algorithms in Thyroid Disease Prediction 23th

Comparative Analysis of Machine Learning Algorithms in Thyro...

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Preethiya, T. Tyagi, Amit Kumar Pandiarajan, T. Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Kanchipuram 603203 India Department of Fashion Technology National Institute of Fashion Technology New Delhi India Department of Computer Science Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9783031648120

Thyroid disease is estimated to be the most common illness in the twenty-first century. The thyroid hormones are produced by a butterfly-shaped gland in the throat. The crucial function these hormones play in bodily metabolism, mental health, and general well-being. In this study, we present a method for accurately analysing thyroid function in an unbalanced dataset using Machine Learning (ML) algorithms. This dataset's accuracy score is ambiguous because most target variable classes are 1. Performance measurements are accuracy and recall, but when class distribution is asymmetrical, the F1-score balances the other parameters. The performance is evaluated using the F1-score, which is one of the best output metrics for unbalanced classification tasks. Simulation results shows that the Decision Tree (DT) algorithm outperforms the other algorithms with an F1-score of 0.9957, the Area Under Curve (AUC) score of 0.9917 and the kappa coefficient of 0.978 in the disease prediction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Support vector machines

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Identification of Cyberbullying and Finding Target User's Intention on Public Forums 6

Identification of Cyberbullying and Finding Target User's In...

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6th International Conference on Contemporary computing and Informatics, IC3I 2023

作者： Krishnasamy, Lalitha Kiruthika, M. Manjunatha Swamy, C. Vigneshwaran, T. Sharon Roji Priya, C. Vijay Anand, D. School of Engineering and Technology Department of CSE Christ University Bengaluru India School of Computing Department of Computational Intelligence SRM Institute of Science and Technology Tamilnadu Kattankulathur India Kongu Engineering College Department of Information Technology Erode India

ISBN: (纸本)9798350304480

Numerous cybercriminals are active in the online realm, carrying out cyber-crimes according to predetermined and preplanned agendas. Cyberbullying, which was formerly limited to physical limits, has now expanded online as a result of technology advancements. One type of cyberbullying is denigration or insult. The cyberbullying cases are in exponential rise in social media as per the reports of Computer Emergency Team by Sri Lanka. Insulting words are changeable in dynamic and the same terminology may have numerous meanings depending on the context. Bullying cannot be defined just because a statement comprises such a term. As a result, when classifying comments, standard keyword detecting approaches are insufficient. Other languages also may have dealt with this issue by utilizing lexical databases like WordNet, which might give synonyms as well as homonyms for words. Because no adequate lexical database mainly for the English language has been built, recognizing a word like bullying is difficult. As a result, employed rules to solve the problem. Facebook comments containing profanity were gathered, outliers were eliminated, and the remaining messages were pre-processed. Five feature extraction rules were employed to assess insult in the text. Following that, used the Support Vector Machine (SVM) technique. Using an F1-score of 85%, the findings demonstrate that when compared to existing works, SVM performs better. The focus on English language cyberbully identification, which has never been addressed earlier, distinguishes this study. © 2023 IEEE.

关键词： bag of words cyberbullying feature extraction sentiment analysis SVM

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'User AR' - Leveraging AI Based Augmented Reality for User Manuals 15

'User AR' - Leveraging AI Based Augmented Reality for User M...

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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Shanmugam, Thirumurugan Chandrashekar, Chirag Bhati, Vipin Subburaj, Maheswari Sivaraman, Arun Kumar Sultana, Ajmery University of Technology and Applied Sciences College of Computing and Information Sciences Suhar Oman Vellore Institute of Technology School of Computer Science and Engineering Chennai India Photon Interactive Inc Digital Engineering Solution Center TorontoON Canada Algoma University School of Computer Science and Technology BramptonON Canada

ISBN: (纸本)9798350370249

The objective of this research is to propose an AI based novel augmented reality (AR) software to assist users in operating a wide range of technical and non-technical devices. The project's aim is to make this AR application, which provides detailed explanations of all the device's functions, more widely used than traditional user manuals. Augmented reality, which overlays digital information onto the real world, can be employed to develop an AR-based user manual for products or devices. Mobile applications that use a camera to recognize a product or device and display dynamic graphics, such as 3 D models, animations, or text, are one example of AR user manuals. These augmented reality user manuals enable consumers to quickly and easily learn how to operate, assemble, repair, or troubleshoot their purchased products. Experiments show that the proposed algorithm was able to recognize the object accurately with a percentage of 95.2%. © 2024 IEEE.

关键词： Artificial Intelligence Augmented reality (AR) Object Recognition

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