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Predicting Chances of Cardiovascular Diseases Through Integration of Feature Selection and Ensemble Learning 1

11th International Conference on Recent Trends in Computing, ICRTC 2022

作者： Bhardwaj, Raghav Mishra, Shashvat Gupta, Isha Paliwal, Shweta Department of Computer Science and Engineering Meerut Institute of Engineering and Technology Meerut India

ISBN: (数字)9789811988257

ISBN: (纸本)9789811988240

Heart problems are among the top most notable problems in the field of medical science. The prediction of diseases related to heart is a peculiar challenge in the field of clinical analysis, and hence, it can be observed that heart problems have been the major death reason globally. The integration of different techniques of machine learning (ML) has proven to be an effective aid in decision making and helps in prediction from the diverse quantity of the data which is produced as a result of the observations in the field of health care. In this study, analysis of a real-time dataset has been performed using the integrated concept of feature selection. Different classifiers of ML are subject to parameter optimization, and values of classical performance measures are being observed. An interface has been designed to give user a pictorial view where the system will recommend what are the chances that an individual is suffering from heart disease. The identification of heart disease is based upon the proposed algorithm and identified features from the real-time dataset. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electrocardiography

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Real - Time AI and Machine Learning Applications in Healthcare Management 1

Real - Time AI and Machine Learning Applications in Healthca...

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1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Poornima, D. Premalatha, J. Sarojini Abirami, G. Triveni, K. Bobby, M.P. Sathyabama Institute of Science & Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350359756

Real-time Artificial Intelligence (AI) and Machine Learning (ML) programs have emerged as a number one motive force for considerably altering patient care and management inside the healthcare control area. Staff shortages and affected person document management are among the fundamental problems dealing with the healthcare industry. In an effort to fight those issues, actual-time AI and ML technology offer a demonstration of optimism with the aid of facilitating quick decisions and higher affected person care. Having those technologies work together ensures that time-sensitive healthcare statistics is processed quick, which improves both useful resource allocation and service shipping. However, there are challenges related to the implementation of real-time AI and ML packages in healthcare management. Interoperability, the mixing of disparate records sources, and privateness and security concerns all pose great difficulties. In addition, an intensive and powerful approach is needed to assure the processing of healthcare facts in real-time. To better manipulate patient facts inside electronic health information, an IoT-based totally Artificial Deep Neural Network (IoT-ADNN) is offered in this studies. There are a huge style of revolutionary uses for actual-time (AI-ML) in healthcare administration. These gear provide healthcare carriers with actual-time information, which in flip results in better resource allocation and a more gratifying affected person revel in. In addition, they enhance information security and accessibility, making sure privateness and ease of get entry to to touchy healthcare facts. Data transmission and shipping quotes, postpone estimation accuracy, energy performance, and throughput have all been dramatically improved. The importance and usefulness of actual-time AI and ML systems in healthcare management are emphasised by means of these measurements. © 2023 IEEE.

关键词： Deep neural networks

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Advance Kernel Rootkit Detection: Survey 7

Advance Kernel Rootkit Detection: Survey

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7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Suresh Kumar, S. Sudalaimuthu, T. Hindustan Institute of Technology and Science Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397253

Rootkits are a group of software tools that an attacker uses to break into a system, giving him the ability to access confidential information, hide his own existence, and install additional malicious software. A rootkit cannot be installed without administrative level access for the attacker. Due to their evasiveness, rootkits pose the greatest detection difficulty among malware. Attacks on rootkits today primarily target operating system kernel changes. In this work, a detailed investigation of rootkit detection technology is used to develop a novel typeof rootkit detection structure, a new technique (software), and a structured and comprehensive view of research on rootkit, process hiding, hook, and detection/prevention. © 2023 IEEE.

关键词： computer viruses

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A Novel Approach for Duty Cycle Optimization in Designing Scalable Wireless Sensor Networks 5th

A Novel Approach for Duty Cycle Optimization in Designing Sc...

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5th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： De, Sudip Kumar Banerjee, Avishek Majumder, Koushik Department of Information Technology Asansol Engineering College WB Asansol India Department of Computer Science and Engineering MAKAUT WB Kolkata India

ISBN: (纸本)9789819791118

This paper aims to enhance the efficiency of wireless sensor networks (WSNs) within an area of interest (AOI) by optimizing duty cycles. Focusing on a specific AOI divided into clusters, each with a dynamically selected cluster head, the study emphasizes establishing a time-synchronized duty cycle optimization protocol in the communication between cluster heads and the base stations. Unlike conventional approaches that randomly select nodes for duty cycle optimization, this paper introduces a method to identify the optimal cluster head (CH) of each cluster based on maximum remaining energy and a shorter distance from the Base Station (BS) to maximize the durability of the network. By introducing a time-synchronized Duty Schedule, the proposed methodology ensured that nodes that are not in use will enter a sleep mode, conserving energy. To ensure effective communication between the Data Centre and multiple Base Stations (BSs) of AOIs, the Particle Swarm Optimization (PSO) has been also used. Through simulation and analysis, the effectiveness of the proposed duty cycle optimization method is evaluated, demonstrating its potential to enhance WSN performance in terms of energy efficiency, network longevity, and communication. This research contributes to advancing the design and operation of WSNs, particularly in scenarios where energy conservation and data transmission are paramount concerns. The suggested duty cycle model assures a 20.44% increase in the network’s lifetime as compared to other available studies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Energy efficiency

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A Secure and Efficient Biometric Template Protection Scheme for Palmprint Recognition System

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1051-1063页

作者： Sardar, Alamgir Umer, Saiyed Rout, Ranjeet Kumar Khan, Muhammad Khurram Aliah University Department of Computer Science and Engineering Kolkata700156 India National Institute of Technology Department of Computer Science and Engineering Srinagar190006 India King Saud University Center of Excellence in Information Assurance Riyadh11451 Saudi Arabia

The accuracy and security of a biometric system are the two sides of a coin. A biometric system must be simple, flexible, efficient, and secure enough from unauthorized access. Concerning these requirements, this article presents an enhanced palmprint recognition system with superior performance and improved biometric template protection schemes. This method comprises five components: image preprocessing, feature extraction, cancelable biometrics, classification, and Bio-Cryptosystem. The palm texture region is extracted from the input hand image during preprocessing. A feature representation technique is then used to extract discriminant features from the palmprint texture patterns. The extracted features are then analyzed using an information coding scheme to compute a user-specific token. Here, the user-specific tokens along with the original palmprint features are used to calculate the feature vectors for the cancelable biometric system. A novel Bio-Cryptosystem has been proposed to protect templates with high security where there is no need to remember the users' tokens. Cancelable feature vectors are kept online in encrypted form using the proposed Bio-Cryptosystem, which is used to identify or verify the subjects after decryption. The original feature vectors are kept offline to prevent these from external attacks and misuse. Finally, the multiclass linear support vector machine has been used for user classification. For experimental purposes, two benchmark hand image databases: BOSPHORUS and CASIA-Palmprint, are employed, and the proposed system has achieved nearly 100% correct recognition rate in cancelable domain for both the employed databases. Finally, the performance comparison in terms of both verification and identification for the palmprint and the cancelable palmprint recognition systems with the existing state-of-the-art methods shows the superiority of the proposed system. © 2020 IEEE.

关键词： Palmprint recognition

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Voice Assistant with Emotion Recognition

Voice Assistant with Emotion Recognition

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2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： Srikanth, S. Sravana Manikantan, Sreenivasan Posonia, A. Mary Mary, S. Prince Revathy, S. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350333244

Voice assistants have become a essential part in our daily life, which helps to provide essential tasks in a hands free manner. Here the voice assistant helps the user with hands free experience that includes setting reminders, playing music, alarm, wishes etc. The voice assistant is powerful ones of cutting-edge speech recognition and natural language processing technique. The system will be intended to interpret and respond to a wide range of spoken instructions and enquiries in a natural and intuitive manner. Furthermore, the initiative intends to improve the user experience by giving tailored replies and suggestions depending on the user's preferences and history. For forecasting emotions, features such as emotion recognition, which detects a person's feelings through their face, are implemented. The goal of this project is to create a voice assistant that interacts with and shorten the burden of activities. © 2023 IEEE.

关键词： Emotion Recognition

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Interactive Learning using Mobile based Augmented Reality Application 2

Interactive Learning using Mobile based Augmented Reality Ap...

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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Nazeer, Shaik Somu, K.B. Roobini, M.S. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350315905

Augmented Reality has become a state-of-the-art technology that enhances the real-world environment with interactive and immersive virtual objects. This technology mixes the real and virtual worlds, enabling realtime interaction and accurate 3D registration of real and virtual objects. One of the most significant uses of Augmented Reality is in the educational system, especially for primary classes, where it brings imagination to life and increases children's interest and excitement in their studies. The technology can also be incorporated into mobile apps that are accessible and user-friendly. Software such as Unity and Vuforia are leading the development of Augmented Reality. In education, this technology has made a significant impact and made learning more engaging and interesting. The augmented reality application can be used to teach geometric figures, the solar system, wild animals, automobiles, and more. It uses target images and software that can detect special markers. 3D objects, animations, and other interactive elements come to life when the target image is placed in front of a mobile device's camera, making learning more enjoyable. The application has received positive feedback from both teachers and students in initial tests. © 2023 IEEE.

关键词： Augmented reality

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Newspaper Article Summarization Using Combinational Method

Newspaper Article Summarization Using Combinational Method

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2023 International Conference on Power, Instrumentation, Control and Computing, PICC 2023

作者： Ansary, Md. Siam Ahsanullah University of Science and Technology Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350334463

Text summarization produces a concise amount of data out of document which may represent the core information contained in the document. In this paper, a combinational approach has been used to generate summary from newspaper article that uses a number of features to rank sentences of the article. Graph based approach with minimal text sentiment analysis and the presence of category wise key phrases have been used. Sentences with the sentiment polarity of the overall document sentiment polarity can convey important information. Combination of multiple features can lead to the identification process of the significant sentences with which good summary can be formed. After the performance analysis of the approach, it has been observed that the technique can generate good summaries that are close to human written ones. © 2023 IEEE.

关键词： Sentiment analysis

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Enhancing Patient Well-Being in Healthcare Through the Integration of IoT and Neural Network

Enhancing Patient Well-Being in Healthcare Through the Integ...

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2024 International Conference on Emerging Innovations and Advanced Computing, INNOCOMP 2024

作者： Singh, Jagendra Shelke, Nitin Arvind Upreti, Kamal Divakaran, Prakash Lingareddy, Nagulapalli Deepika, Sheri School of Computer Science Engineering & Technology Bennett University Greater Noida India Department of Computer Science Ghaziabad India Himalayan University Itanagar India Vignan Institute of Technology and Science Department of CSE Deshmukhi India Sreyas Institute of Engineering and Technology Department of CSE Hyderabad India

ISBN: (纸本)9798350376470

This study analyses the revolutionary integration of Internet of Things (IoT) structures in healthcare through a complete examination of outstanding case research. The first case study focuses on real-time patient fitness monitoring in a clinic setting. The suggested device utilizes an Internet of Things-ready device that has many sensors, including oxygen, pressure, and temperature sensors. The issues of forecasting patient health in advance are handled with the deployment of machine learning models, notably Artificial Neural Networks (ANN), Decision Trees (DT), and Support Vector Machines (SVM). The second case study analyses IoT's effect on patient-precise medication identification and remote fitness monitoring, uncovering issues associated with accessibility, pricing, and human interfaces. Proposed alternatives, which incorporates greater education, increased accessibility, and user-pleasant interfaces with robust technical assistance, have been evaluated with 30 patients over a three-month duration. The results reveal a great growth in impacted person health, along with heightened attention of periodic health monitoring. The results highlight how IoT technologies may transform healthcare procedures by offering pro-active solutions for patients' well-being. This study offers insightful information that may be used to solve practical issues, promote patient-centered solutions, and broaden the scope of the healthcare period. A significant step towards a patient-centered and technologically advanced healthcare environment, the successful outcomes validate the capacity for sustained innovation, cooperation, and improvement in the integration of IoT systems for optimal patient care. © 2024 IEEE.

关键词： Support vector machines

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Makaton Sign Language Recognition

Makaton Sign Language Recognition

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2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： Prince, Nikhil R Thayil, Rohan Ousephachen Anto Praveena, M.D. Prince Mary, S. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350333244

Makaton is a widely used sign language system that is primarily used by individuals with communication difficulties, such as those with Autism, Down syndrome, and other developmental disorders. However, despite its widespread usage, there is a lack of technology for accurately recognizing and understanding Makaton signs. This paper proposes a model that combines MediaPipe Holistic with a neural network, such as SimpleRNN, LSTM, or GRU, to recognize Makaton sign language (MSL). The model is trained on a custom dataset of Makaton sign language videos using backpropagation and the Adam optimizer. The proposed network achieved a high accuracy on the test set, demonstrating its effectiveness in recognizing Makaton sign language. This study introduces an innovative method for advancing the development of systems that recognize sign language by utilizing MediaPipe Holistic in conjunction with a neural network. This can improve the way technology interacts with people who have hearing impairments. © 2023 IEEE.

关键词： Long short-term memory

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