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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Sharma, Chetan Anooja, A. Kishore, Jaydeep Bhardwaj, Vivek UpGrad Education Private Limited Bangalore India School of Computer Application Jecrc University Rajasthan Jaipur India School of Computer Science and Engineering Manipal University Jaipur Jaipur India

ISBN: (纸本)9798331509828

Being a top cause of mortality and serious disability, stroke demands urgent diagnosis and impactful prevention. Current innovations in machine learning (ML) show a great capacity for predicting the likelihood of a stroke. This study reports on applying ML algorithms to improve the timely and early identification of stroke, leading to more effective interventions and lowering morbidity and mortality numbers. This work employs a complete dataset that integrates demographic information, medical history, data on lifestyle, and physical measurements. engineering techniques of a high level were utilized in pre-processing the data to reduce the assumptions that lay underneath. This research applied five machine learning models for the prompt identification of stroke: Decision Tree, Support Vector Machine (SVM), Gradient Boosting, K-Nearest Neighbours (KNN), and XG Boost. The number of datasets used for training was 80%, and 20% went to testing. The accuracy of the Gradient Boosting model stood at 96%, outperforming XG Boost at 92% and Decision Tree at 91%. The model with Support Vector Machines (SVM) gave 84% accuracy, but all three models illustrated high precision and recall. These results indicate that machine learning models could significantly augment stroke prediction and enhance clinical decision processes. © 2025 IEEE.

关键词： Support vector machines

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IOT-based Smart Ground water Recharge System 1

IOT-based Smart Ground water Recharge System

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Uniyal, Manas Bhatt, Chandradeep Mohd, Noor Kumar, Devendra Graphic Era Hill University Computer Science Department Dehradun India Abes Engineering College Computer Application Department Ghaziabad India

ISBN: (纸本)9798350338027

Water is the most important commodity for the existence of life. In India, the main sources of water are rainwater(monsoon) that fills the rivers with water and underground water. However, we have seen a steady decline in underground water levels across India at an alarming rate that affects the agriculture and daily water needs of the citizens. This paper suggests a smart ground water recharge system that automatically recharges the ground water after rain falls. The system uses smart IOT devices, solar panels, and a filter to filter out unwanted materials that come along the rainwater. In this paper a fully automatic rainwater harvesting is introduced that collects rainwater and filters out dirt and unwanted materials(trash) that comes along the rain. It also senses the acidic content of rain and filters it out when needed. Later on, the filtered water can be directly recharged in ground, or it can also be collected in artificial pools for irrigation purposes. Polluted water can be very harmful for our environment and food cycle. © 2023 IEEE.

关键词： Aquifers

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A Survey of Dynamic Exploration Symmetric Encryption with Backward & Forward Secrecy 3

A Survey of Dynamic Exploration Symmetric Encryption with Ba...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Singh, Satendra Bhagat, Samriti Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application India

ISBN: (纸本)9798350399264

A sophisticated type of symmetric encryption is called Multiuser Dynamic Searchable Symmetric Encryption. It expands the capabilities of conventional symmetric encryption to enable actions such as adding and removing encrypted data as well as the ability for a verified set of information users to access their preferred encrypted data within the dynamic database. The latter can use using erased data and search results to comprehend the content, while the former allows attackers to discover by performing file injection attacks, keywords from the injected data were exposed. can do. To our knowledge, the available literature has not completely addressed these privacy problems for M-DSSE. In light of this, our attention is directed toward multiuser dynamic searchable symmetric encryption that satisfies the requirements for forwarding and backward security. It uses Inverted indexes are created and updated using random number generator Functions (RNG) and Authenticator primitives search tokens to suggest specific solutions. In the accidental model, the suggested approach is shown to be secure. Additionally, the performance study demonstrates that the suggested approach provides increased security assurances at a fair cost to efficiency. © 2023 IEEE.

关键词： Cryptography

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An Edge Computing Algorithm Based on Multi-Level Star Sensor Cloud

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computer Modeling in engineering & sciences 2023年第8期136卷 1643-1659页

作者： Siyu Ren Shi Qiu Keyang Cheng The Open University of Chengdu Major in Computer ApplicationChengdu610000China Xi’an Institute of Optics and Precision Mechanics Chinese Academy of Sciences.Xi’an710119China School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang212013China

Star sensors are an important means of autonomous navigation and access to space information for *** have been widely deployed in the aerospace *** satisfy the requirements for high resolution,timeliness,and confidentiality of star images,we propose an edge computing algorithm based on the star sensor *** sensors cooperate with each other to forma sensor cloud,which in turn extends the performance of a single *** research on the data obtained by the star sensor has very important research and application ***,a star point extraction model is proposed based on the fuzzy set model by analyzing the star image composition,which can reduce the amount of data ***,a mappingmodel between content and space is constructed to achieve low-rank image representation and efficient ***,the data collected by the wireless sensor is delivered to the edge server,and a differentmethod is used to achieve privacy *** a small amount of core data is stored in edge servers and local servers,and other data is transmitted to the *** show that the proposed algorithm can effectively reduce the cost of communication and storage,and has strong privacy.

关键词： Star-sensing sensor cloud fuzzy set edge computing mapping

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ChatGPT Based Image Steganography (CGIS): A Novel Intelligent Information Hiding Approach to Achieve Secure Covert Communication 1

ChatGPT Based Image Steganography (CGIS): A Novel Intelligen...

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1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Mukherjee, Subhadip Mukhopadhyay, Somnath Sarkar, Sunita Assam University Department of Computer Science and Engineering Silchar788011 India Sikkim University Department of Computer Application Gangtok737102 India

ISBN: (纸本)9798350342796

Covert communication refers to the practice of exchanging information or messages in a discreet or secretive manner, with the intent of keeping the communication hidden from unintended or unauthorized recipients. Steganography is a widely used, strategy for establishing covert communication, for maintaining the privacy and security of sensitive information. Steganography ensures that the message remains concealed from surveillance or eavesdropping. Artificial Intelligence (AI) plays a crucial role in enhancing security across various domains of covert communication. ChatGPT is an AI model, specifically a natural language processing (NLP) model. It belongs to the broader category of AI models which can comprehend and produce language for humans. In this paper, a new image steganographic model named CGIS is developed for covert communication using ChatGPT. Proposed steganographic method has achieved 3.0 bpp of hiding capacity. In situations where confidentiality is critical, such as in military operations, intelligence agencies, or corporate strategies, proposed method ensures that the message cannot be detected and or extracted by any surveillance or eavesdropper. © 2023 IEEE.

关键词： Artificial Intelligence CGIS ChatGPT Covert Communication Image Steganography

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Comparative Evaluation of Machine Learning Algorithms for Detecting Credit Card Fraud 8

Comparative Evaluation of Machine Learning Algorithms for De...

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8th International Conference on Communication and Electronics Systems, ICCES 2023

作者： Prashanth, Banagani Gangadhar, Suddapalli Bhardwaj, Vivek Reddy, Kovvuru Diwakar Reddy, Puli Shiva Mehra, Manik Lovely Professional University Department of Computer Science and Engineering Phagwara India Manipal University Jaipur Department of Computer Science and Engineering Jaipur India Lovely Professional University School of Computer Application Phagwara India

ISBN: (纸本)9798350396638

Detecting credit card fraud is an extremely important issue in the financial sector, as it results in significant financial losses and negatively impacts customer trust. The main motive of CCFD is to develop methods to identify fraudulent transactions accurately and efficiently. This research typically involves the use of statistical and machine-learning algorithms to analyze large amounts of transaction data. Utilizing machine learning is a potential solution for addressing credit card fraud. Studies suggest that machine learning techniques can help overcome the challenges of identifying fraudulent transactions with high detection rates, both directly and indirectly. While supervised ML algorithm and unsupervised ML algorithms have been proposed, the limitations of each approach underscore the need for hybrid methods. From the results, it is evident that Logistic Regression has the highest accuracy of 94.86%, highest recall value of 98.97% and highest F1-score of 95.09%. © 2023 IEEE.

关键词： Feature extraction

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Prediction of Cardiac Arrest using Generalized Soft Computing Techniques 18

Prediction of Cardiac Arrest using Generalized Soft Computin...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Hota, Radhanath Dash, Sachikant Mishra, Sujogya Das, Subhalaxmi Lenka, S. Pradhan, G. Giet University Department of Computer Science Engineering Odisha Gunupur India Gandhi Institute for Education and Technology Department of Computer Science Engineering Odisha Gunupur India Odisha University of Technology and Research Department of Mathematics Bhubaneswar India Odisha University of Technology and Research Dept. of Computer Science and Engineering Bhubaneswar India Utkal University Department of Computer Science and Application Bhubaneswar India

ISBN: (纸本)9789380544519

Cardiac-related diseases always lead to fatal consequences around the globe. This research includes vague data analysis of the data related to cardiac anomalies. This study proposes a method to develop a dimension reduction model using vague data related to cardiac diseases using rough set theory (RST). The overall research is divided into two different sections. The first section of this study proposes analyses of the raw cardiac-related data using RST, and the second section calculates the performance accuracy using Principal Component Analysis (PCA) applied to the universal data set;the performance measures also include a combination of two Universal data sets. The above claims are verified using statistical tests © 2024 Bharati Vidyapeeth, New Delhi.

关键词： PCA Performance and accuracy Rough Set Theory Statistical method Vague data

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Next Generation Digital Health Monitoring System Using Artificial Neural Network 5

Next Generation Digital Health Monitoring System Using Artif...

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

作者： Kadayat, Yunika Sharma, Sachin Painuly, Sakshi Graphic Era Deemed to be University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Graphic Era Hill University Department of Computer Application Dehradun India

ISBN: (纸本)9798350351378

By empowering early identification and provoke reaction within the occasion of health irregularities, another era digital health monitoring systems are basic to guaranteeing people's prosperity. ANNs, or artificial neural networks, have become successful devices for making exact and successful health monitoring systems. This ponder offers a careful examination of how ANNs are utilized in health monitoring systems. It covers the standards of ANNs, considers how they fit into systems for health monitoring, gives case illustrations, and talks around the obstacles and up and coming advancements in this region. © 2024 IEEE.

关键词： Neural networks

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Personalized Confederation Training for Smart Iot Systems: A Cloud - Delivered Structure 3

Personalized Confederation Training for Smart Iot Systems: A...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Katariya, Jitendra Kumar Nivesh Vivekananda Global University Department of Computer Science Engineering India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

The Internet of Things (IoT) has significantly impacted many facets of contemporary life, and several sophisticated IoT applications and services are already being developed. Recently, the concept of federated learning has been proposed in order to train a globally shared model on IoT devices utilising a large number of user-generated data samples while stopping data leak. Due to the widespread heterogeneities in device, statistics, and model in complex IoT contexts, traditional federated learning is not suitable for instant implementation. In this paper, we present a cloud-edge architecture for intelligent IoT applications that includes a customised federated learning framework. To address the heterogeneity worries in IoT conditions, we examine imaginative altered united learning calculations that could diminish the unfortunate results brought about by heterogeneities in various aspects. The advantages of edge registering empower smart IoT applications to meet the models for high handling pace and low inertness. At long last, we give a contextual investigation of human movement recognition in light of Web of Things to show the advantages of customisable combined learning for intelligent IoT applications. © 2023 IEEE.

关键词： Internet of things

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Overcoming Spatial Constraints in VR:A Survey of Redirected Walking Techniques

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Journal of computer science & Technology 2024年第4期39卷 841-870页

作者： Jia-Hong Liu Yang-Fu Ren Qi Wen Gan Kui Huang Fiona Xiao Yu Chen Er-Xia Luo Khang Yeu Tang Yue-Yao Fu Cheng-Wei Fan Sen-Zhe Xu Song-Hai Zhang Academy of Arts and Design Tsinghua UniversityBeijing 100084China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China College of Computer Technology and Application Qinghai UniversityXining 810016China Zhili College Tsinghua UniversityBeijing 100084China School of Computer Beijing Information Science and Technology UniversityBeijing 100192China Department of Physics Tsinghua UniversityBeijing 100084China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China

As the virtual reality(VR)technology strives to provide immersive and natural user experiences,the challenge of aligning vast virtual environments with limited physical spaces remains *** survey comprehensively explores the advancements in redirected walking(RDW)techniques aimed at overcoming spatial constraints in *** addresses this by subtly manipulating users’physical movements to allow for seamless navigation within constrained *** survey delves into gain perception mechanisms,detailing how slight discrepancies between virtual and real-world movements can be utilized without user awareness,thus extending the effective navigable *** RDW control algorithms for gain-based RDW are analyzed,highlighting their implementation and effectiveness in maintaining immersion and minimizing perceptual ***,novel methods extending beyond traditional gain-based techniques are discussed,showcasing innovative approaches that further refine VR *** practical implications of RDW in enhancing safety and reducing physical collisions in VR environments are underscored,alongside its potential to improve user experience by aligning virtual exploration more closely with natural human behavior *** a thorough review of existing literature and recent advancements,this survey provides a systematic understanding for researchers,developers,and industry *** underscores the importance of RDW in the future of VR,emphasizing RDW's role in making VR more accessible and practical across various applications,from education and training to therapy and *** paper concludes with a forward-looking perspective on the continued evolution and potential of RDW in revolutionizing virtual reality experiences.

关键词： virtual reality(VR) redirected walking(RDW) redirection gain perception

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