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Heart Disease Risk Prediction Expending of Classification Algorithms

computers, Materials & Continua 2022年第12期73卷 6595-6616页

作者： Nisha Mary Bilal Khan Abdullah A.Asiri Fazal Muhammad Salman Khan Samar Alqhtani Khlood M.Mehdar Hanan Talal Halwani Muhammad Irfan Khalaf A.Alshamrani City University of Science and Information Technology Peshawar25000Pakistan Radiology Science Department College of Applied Medical Science Najran University Kingdom of Saudi Arabia Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia

Heart disease prognosis(HDP)is a difficult undertaking that requires knowledge and expertise to predict early *** failure is on the rise as a result of today’s *** healthcare business generates a vast volume of patient records,which are challenging to manage *** it comes to data mining and machine learning,having a huge volume of data is crucial for getting meaningful *** methods for predictingHDhave been used by researchers over the last few decades,but the fundamental concern remains the uncertainty factor in the output data,aswell as the need to decrease the error rate and enhance the accuracy of HDP assessment ***,in order to discover the optimal HDP solution,this study compares multiple classification algorithms utilizing two separate heart disease datasets from the Kaggle repository and the University of California,Irvine(UCI)machine learning *** a comparative analysis,Mean Absolute Error(MAE),Relative Absolute Error(RAE),precision,recall,fmeasure,and accuracy are used to evaluate Linear Regression(LR),Decision Tree(J48),Naive Bayes(NB),Artificial Neural Network(ANN),Simple Cart(SC),Bagging,Decision Stump(DS),AdaBoost,Rep Tree(REPT),and Support Vector Machine(SVM).Overall,the SVM classifier surpasses other classifiers in terms of increasing accuracy and decreasing error rate,with RAE of 33.2631 andMAEof 0.165,the precision of 0.841,recall of 0.835,f-measure of 0.833,and accuracy of 83.49 percent for the dataset gathered from *** SC improves accuracy and reduces the error rate for the Kaggle dataset,which is 3.30%for RAE,0.016 percent for MAE,0.984%for precision,0.984 percent for recall,0.984 percent for f-measure,and 98.44%for accuracy.

关键词： Heart disease heart disease datasets evaluation measures classification techniques

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A review of Communication and Data Networks Algorithms Shaping Modem Connectivity 7

A review of Communication and Data Networks Algorithms Shapi...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Srinath, M.K. Gatla, Anitha Lakhanpal, Sorabh Sharma, Saurabh Reddy, B.Ravali Al-Rubaye, Taqi Mohammed Khattab New Horizon College of Engineering Department of Mechanical Engineering Bangalore India Institute of Aeronautical Engineering Department of Information Technology Dundigal Hyderabad500043 India Lovely Professional University Phagwara India Lloyd Law College Plot No. 11 Knowledge Park II Uttar Pradesh Greater Noida201314 India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India The Islamic University College of Medical Technologies Department of Medical Laboratory Technology Najaf Iraq

ISBN: (纸本)9798350350067

The world of today is highly interconnected and undergoes rapid changes. Algorithms are essential for data networks and communication systems. This study looks at how the complexity of algorithms affects network design. It focusses on the GROA (Global Routing Optimisation Algorithm), LBEA (Load Balancing and Efficient Allocation), and QKD-NS systems in particular. We aim to educate individuals on the impact of various methods on security, route completion time, and resource constraints. Based on the results, GROA creates variable paths, QKD-NS boosts safety with quantum-based innovations, and LBEA efficiently divides up resources based on what the network requires. According to the study, putting these many technologies together could lead to strong partnerships that can handle security breaches, traffic jams, and changes in the network. This study focusses on how advances in technology have led to better computer design, which in turn has made the internet safer and easier to use. The paper elucidates the application of these novel mathematical discoveries to enhance the performance and durability of data networks. These new details help communication networks improve by ensuring that they are safe and can meet today's link standards. © 2024 IEEE.

关键词： Traffic congestion

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The rise of mobile development: a comparison between Ionic and Flutter 14

The rise of mobile development: a comparison between Ionic a...

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14th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2022

作者： Novac, Ovidiu Constantin Novac, Cornelia Mihaela Ciora, Bogdan Gordan, Cornelia Emilia Gordan, Mircea Ioan Bujdoso, Gyongyi University of Oradea Electrical Engineering and Information Technology Faculty Department of Computers and Information Technology Oradea Romania University of Oradea Electrical Electrical Engineering and Information Technology Faculty Department of Electrical Engineering Oradea Romania University of Oradea Management in Information Technology Engineering and Information Technology Faculty Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of of Electronics and Telecommunications Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Electrical Engineering Oradea Romania University of Debrecen Faculty of Informatics Department of Computer Science and Library and Information Science Debrecen Hungary

ISBN: (数字)9781665495356

ISBN: (纸本)9781665495356

A dive into the world of mobile development frameworks. An overview regarding the mobile technologies, in general but also a close look at two major mobile development frameworks, which are Ionic and Flutter. They are being analyzed at an individual level and furthermore, a comparison between these two technologies is taking place. © 2022 IEEE.

关键词： computers Games Software Marine vehicles Artificial intelligence

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The Evolution of Zero Trust Architecture (ZTA) from Concept to Implementation 29

The Evolution of Zero Trust Architecture (ZTA) from Concept ...

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29th International Conference on Information technology, IT 2025

作者： Nasiruzzaman, Md Ali, Maaruf Salam, Iftekhar Miraz, Mahdi H. Xiamen University Malaysia School of Computing and Data Science Malaysia Universiteti Metropolitan Tirana Faculty of Computer Science and IT Albania The Doctoral College United Kingdom Xiamen University Malaysia Mahdi H. Miraz Is with the School of Computing and Data Science Malaysia Wrexham University School of Computing Faculty of Arts Science and Technology United Kingdom University of South Wales Faculty of Computing Engineering and Science United Kingdom

ISBN: (纸本)9798331517649

Zero Trust Architecture (ZTA) is one of the paradigm changes in cybersecurity, from the traditional perimeter-based model to perimeterless. This article studies the core concepts of ZTA, its beginning, a few use cases and future trends. Emphasising the always-verify and least privilege access, some key tenets of ZTA have grown to be integration technologies like Identity Management, Multi-Factor Authentication (MFA) and real-time analytics. ZTA is expected to strengthen cloud environments, education, work environments (including from home) while controlling other risks like lateral movement and insider threats. Despite ZTA's benefits, it comes with challenges in the form of complexity, performance overhead and vulnerabilities in the control plane. These require phased implementation and continuous refinement to keep up with evolving organisational needs and threat landscapes. Emerging technologies, such as Artificial Intelligence (AI) and Machine Learning (ML) will further automate policy enforcement and threat detection in keeping up with dynamic cyber threats. © 2025 IEEE.

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Cloud Server Based Intelligent Health Care Kit using Body Sensor Network 2

Cloud Server Based Intelligent Health Care Kit using Body Se...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Arul Prasath, A. Ranganathan, Chitra Sabapathy Saravanan, K. Srinivasan, S. Latha, N. Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Mphasis Corporation ChandlerAZ United States Department of Information Technology R.M.D Engineering College Tamil Nadu Chennai India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350305418

In this study, the model investigates designing and deploying a Body Sensor Network (BSN)-based intelligent healthcare kit hosted on a cloud server. This study aims to determine whether and how well this technology can track and manage people's health. The study focuses on developing and implementing wearable sensors for continuously monitoring vital signs such as heart rate, blood pressure, temperature, and oxygen saturation. The data is sent wirelessly to a gateway device or central hub, which may be processed locally or analyzed in the cloud using sophisticated algorithms and machine learning methods. The cloud server is crucial for tracking users' vitals, spotting outliers, and alerting users and medical staff in real time. Based on an individual's health data, the system offers suggestions for changing one's lifestyle, taking medications as prescribed and engaging in physical activity. The cloud server ensures the privacy and security of stored data and complies with applicable data protection laws. In addition, methods are investigated for integrating the intelligent healthcare kit with preexisting healthcare systems and electronic health records to support the smooth exchange of data and the provision of all-encompassing medical treatment. This work aims to promote healthcare technology and patient care by conducting empirical research and assessing a cloud server-based intelligent healthcare kit employing a body sensor network. © 2023 IEEE.

关键词： Body Sensor Network Cloud Server Database Health Management Healthcare Kit

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An enhanced mechanism for detection of spam emails by deep learning technique with bio-inspired algorithm

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e-Prime - Advances in Electrical engineering, Electronics and Energy 2024年 8卷

作者： Nicholas, Neomi Nelin Nirmalrani, V. Faculty of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

This study aims to create a highly effective system for classifying email spam, with the key objective of improving performance and accuracy in classification. Rigorous pre-processing techniques, including lemmatization and tokenization, are applied to refine the dataset. The impact of optimal feature selection on deep learning algorithm stability with varying training datasets is investigated and to improve classifier performance, pre-stages such as feature extraction and selection using bag of words are utilized. The hybrid model is further enhanced by combining feature extraction and classification algorithms with optimization. The inclusion of multiple features, such as n-gram features, addresses the 'Curse of Dimensionality,' and optimal feature selection is employed to improve the spam detection process. The proposed system undergoes three main modifications: multiple feature extraction, feature selection, and an enhanced hybrid model, all aimed at improving spam detection accuracy. The e-mail classification phase involves mapping between training and testing sets, with deep learning algorithms utilized for feature extraction and classification. The recently introduced Sand Cat Swarm Optimization algorithm is employed to refine weights during each epoch, enhancing accuracy and minimizing loss. The proposed system extends its capabilities to identify phishing attacks within the network, offering a comprehensive approach to email security. © 2024

关键词： Bag of words Curse of dimensionality Email spam classification Optimization algorithm Sand Cat Swarm Tokenization

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Improving Explainability of the Attention Branch Network with CAM Fostering Techniques in the Context of Histological Images 26

Improving Explainability of the Attention Branch Network wit...

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26th International Conference on Enterprise Information Systems, ICEIS 2024

作者： Miguel, Pedro Lucas Lumini, Alessandra Medalha, Giuliano Cardozo Roberto, Guilherme F. Rozendo, Guilherme Botazzo Cansian, Adriano Mauro Tosta, Thaína A.A. do Nascimento, Marcelo Z. Neves, Leandro A. Department of Computer Science and Statistics São Paulo State University SP São José do Rio Preto Brazil Department of Computer Science and Engineering University of Bologna Italy 325 SP São José do Rio Preto15084-010 Brazil Faculty of Engineering University of Porto Porto Portugal Institute of Science and Technology Federal University of São Paulo SP São José dos Campos Brazil Faculty of Computer Science Federal University of Uberlândia MG Uberlândia Brazil

ISBN: (纸本)9789897586927

Convolutional neural networks have presented significant results in histological image classification. Despite their high accuracy, their limited interpretability hinders widespread adoption. Therefore, this work proposes an improvement to the attention branch network (ABN) in order to improve its explanatory power through the gradient-weighted class activation map technique. The proposed model creates attention maps and applies the CAM fostering strategy to them, making the network focus on the most important areas of the image. Two experiments were performed to compare the proposed model with the ABN approach, considering five datasets of histological images. The evaluation process was defined via quantitative metrics such as coherency, complexity, confidence drop, and the harmonic average of those metrics (ADCC). Among the results, the proposed model through the ResNet-50 was able to provide an improvement of 4.16% in the average ADCC metric and 3.88% in the coherence metric when compared to the respective ABN model. Considering the DesneNet-201 network as the explored backbone, the proposed model achieved an improvement of 14.87% in the average ADCC metric and 9.77% in the coherence metric compared to the corresponding ABN model. The contributions of this work are important to make the results via computer-aided diagnosis more comprehensible for clinical practice. Copyright © 2024 by SCITEPRESS – science and technology Publications, Lda.

关键词： Image enhancement

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Scrutinizing Domain-Specific Integrated Web Query Interfaces for Enhanced Security and Reliability in Storage Systems

Scrutinizing Domain-Specific Integrated Web Query Interfaces...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Kumar, Rajeev Kumar, Pradeep Elngar, Ahmed A. Moradabad Institute of Technology Department of Computer Science and Engineering Uttar Pradesh Moradabad India Kuala Lumpur Malaysia Beni-Suef University Faculty of Computers and Artificial Intelligence Beni-Suef City62511 Egypt

ISBN: (纸本)9798350369106

In this paper, the module is designed to possess an assortment of unique and meticulously retrieved query interfaces from multiple representative domains like travel, entertainment, and living. Using Integrated Web Query Interfaces (IWQI), which are entirely built on VDIS (View-based Data Integration System) and related to data from various data sources, we have presented a novel approach to online form integration. The essential processing of the proposed model starts from the wrapper module. This module is responsible for collecting data from various sources, extracting meaningful information from them, and identifying multiple web query interfaces. The proposed model follows and applies the rules that have been given and tested by researchers even before. In the given model two major mapping tasks have been done in the wrapper module. The organizational structure of all these elements in WQI along with the positional elements are also described and defined. © 2024 IEEE.

关键词： Structured Query Language

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Database Security: Current Challenges and Effective Protection Strategies

Database Security: Current Challenges and Effective Protecti...

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Computing and Informatics (ICCI), International Conference on

作者： Ahmed Naguib Khaled M. Fouad Faculty of Information Technology and Computer Science Nile University Faculty of Computers and Artificial Intelligence Benha University Faculty of Computer Science and Engineering New Mansoura University

Database security has grown to a necessary level of importance today, characterized by the escalating demand for data storage. The surge in data storage requirements, propelled by technological advancements, has led to increased attacks targeting database security vulnerabilities. While multiple storage and protection methods have emerged in tandem with evolving technologies, the discovery of security vulnerabilities has led to new attack vectors. This study aims to repair this gap by securing and fortifying the security of stored data within databases. Fundamental to information security, the study highlights integrity, confidentiality, and accessibility in addressing database security concerns. The study aims to spotlight these issues and increase awareness about security problems and potential solutions. An analysis of the most common security problems in databases forms a central part of the study, accompanied by a discussion of viable solutions for these challenges. Moreover, the study delves into international security standards and secure models to counteract cyber-attacks targeting databases.

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Development of a distributed embedded apogee prediction and control system with sensor fusion for sounding rockets

Development of a distributed embedded apogee prediction and ...

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AIAA SciTech Forum and Exposition, 2024

作者： Slawęcki, Piotr Slonka, Piotr Żebrowski, Wojciech Wesolowska, Zuzanna AGH University of Kraków AGH Space Technology Centre Kraków30-059 Poland AGH University of Kraków Faculty of Computer Science Electronics and Telecommunications Kraków30-059 Poland AGH University of Kraków Faculty of Applied Mathematics Kraków30-059 Poland AGH University of Kraków Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Kraków30-059 Poland

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This paper presents the development process of a distributed embedded system, designed by the members of AGH Space Systems student team with the aim of predicting the optimal engine cut-off time mid-flight to precisely reach a target apogee, with the use of a Pitot tube, inertial measurement units and barometric data. The authors evaluate various analytical approaches to determine the predicted apogee based on the vehicle’s momentary altitude and vertical velocity. © 2024 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Embedded systems

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