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2022 International Conference on Data Analytics for Business and Industry, ICDABI 2022

作者： Ankita Rani, Shalli Bashir, Ali Kashif Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Computing and Mathematics Manchester Metropolitan University United Kingdom Woxsen University Adjunct Professor Woxsen School of Business India

ISBN: (纸本)9781665490580

As technology advances, more demands in various sectors rise, making everything smarter. The Internet of Things (IoT) connects everything through an interconnected nodes also bringing improvements to many industrial or manufacturing industries, healthcare sectors, smart retail, agriculture etc. by pushing many more applications to their limits but are vulnerable to threats and attacks. As a result, security and privacy are required to make IoT secure. This article discusses vulnerabilities in different layers of IoT architecture where security is critically required, the use of Intrusion Detection System in IoT networks and how machine and deep learning will help to overcome those assaults. The following paper also discusses the different types of Intrusion Detection datasets along with the issues and challenges in IoT. © 2022 IEEE.

关键词： Internet of things

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Effect of using silica fume as a partial replacement of cement in concrete

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Materials Today: Proceedings 2023年

作者： Tak, Sudhansu Gupta, Priyanshu Kumar, Alok Sofi, A. Yun, Chin Mei B.Tech Civil Engineering School of Civil Engineering Vellore Institute of Technology Vellore India Professor Department of Structural and Geotechnical Engineering School of Civil Engineering Vellore Institute of Technology Vellore India Engineering Computing and Science Swinburne University of Technology Sarawak Malaysia

Concrete, which acts as the basic structural material, is frequently used in building projects. Concrete uses Portland cement as a binder and the huge production of cement results in carbon dioxide emissions. To reduce CO2 emissions, a transition to alternate products is required. Our research examines the viability of substituting a portion of the cement in concrete with silica fume. On the specimen, tests were conducted utilizing 0%, 5%, 8%, 11%, and 15% silica fume to replace cement in the composition. Concrete specimens were casted and assessed after 7 days, 14 days, and 28 days of cure. The test samples were compared to a control sample of concrete, and statistical analysis was used to establish the ideal percentage that provides the maximum strength. The mechanical properties of concrete were enhanced when silica fume was being used as a binder;the resultant concrete was also cost-effective. The ideal percentage of silica fume for concrete was determined to be 11%. © 2024 Elsevier Ltd. All rights reserved.

关键词： Compressive strength

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Identification of Congenital Heart Defects in Ultrasound Images using U-Net Segmentation 1

Identification of Congenital Heart Defects in Ultrasound Ima...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Pandey, Saroj Kumar Diwan, Ritesh Rose, Anthony Singh, Kamred Udham Singh, Teekam Somasekar, J. Gla University Department of Computer Engineering & Apllications UP Mathura India Department of Ele. & Tele. Raipur Institute of Technology Raipur India Pune India School of Computing Graphic Era Hill University Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Professor of Cse Department Bangalore India

ISBN: (纸本)9798350330915

In this study, the use of a U-Net segmentation model is measured for the accurate detection of congenital heart abnormalities in newborn ultrasound pictures. The technique includes U-Net model training, sophisticated picture preprocessing, as well as exhaustive dataset gathering. As a result of the model's considerable accuracy, sensitivity, and specificity, it has the potential to become a crucial diagnostic tool. A thorough analysis found both advantages, such as reliable performance, and disadvantages, which include the requirement for a larger and more varied dataset. Enlarging the dataset, addressing equipment variability, real-time clinical application, multidisciplinary cooperation, and ethical issues, including model improvement are among the key recommendations. In order to promote newborn healthcare, future work will require ongoing model development, real-time clinical integration, and ethical adherence. The work advances the development of accurate diagnostics in newborn care. © 2023 IEEE.

关键词： Congenital heart defects diagnostic accuracy medical image analysis neonatal ultrasound pediatric cardiology U-Net segmentation

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Prediction of Alzheimer's Disease Progression Using Longitudinal Brain MRI Data and GANs 1

Prediction of Alzheimer's Disease Progression Using Longitud...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Singh, Kamred Udham More, Ajit Verma, Rajeshwar Jain, Dhananjay Kumar Somasekar, J. Pandey, Saroj Kumar School of Computing Graphic Era Hill University Dehradun India Pune India Raipur Institute of Technology Department of Mechanical Raipur India Kalinga University Chhattisgarh Naya raipur India Professor of Cse Department Bangalore India Gla University Department of Computer Engineering & Apllications UP Mathura India

ISBN: (纸本)9798350330915

This research introduces a new method for predicting the course of Alzheimer's disease by combining longitudinal brain MRI data with Generative Adversarial Networks (GANs). Using additional information from reputable repositories, we carried out a descriptive study by applying a deductive technique and an interpretivist mindset. The GAN exhibited remarkable efficacy in producing lifelike MRI pictures by accurately identifying minute structural alterations that signify the advancement of the disease. The predictive model outperformed previous techniques with its high sensitivity and specificity. Comparison with well-established methods demonstrated our GAN-based approach's greater accuracy. Clinical validation, ethical issues, and multi-modal data integration should be the main areas of future research. This novel approach has the potential to completely transform Alzheimer's disease early detection and treatment programs. © 2023 IEEE.

关键词： Alzheimer's Disease Disease Progression Generative Adversarial Networks Longitudinal Brain MRI Predictive Model

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Selecting of Pet Adopters using C4.5 Decision Tree Model Algorithm 2

Selecting of Pet Adopters using C4.5 Decision Tree Model Alg...

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2nd International Conference in Information and computing Research, iCORE 2022

作者： Albia, Criza Jean D. Origines, Domingo Davao Del sur State College Davao del Sur Philippines Institute of Computing Engineering Technology Davao Del sur State College Assistant Professor Information Technology Department Davao Del Sur Digos Philippines

ISBN: (纸本)9798350333909

This study aims to select pet adopters based from the model created from the C4.5 decision tree algorithm to address the proper way for adoption of a pet through online examination. This study uses the method of the C4.5 algorithm by finding the highest gain value to create a decision tree model and generate a decision rules that will apply to a website for decision support if the adopter is qualified or not qualified to adopt. A confusion matrix is used to calculate the accuracy of the C4.5 decision tree algorithm. The information in the confusion matrix is needed to calculate the classification model's performance. This can be done by using performance metrics for the C4.5 algorithm that is based on accuracy, sensitivity, and specificity. The total number of datasets is 1800 which consists of 15 attributes, 1500 for training which consists of 100 instances, and 300 for testing the accuracy is consist of 20 instances. The results on testing the accuracy of the C4.5 decision tree algorithm using confusion matrix is 85%, sensitivity is 84.6% and specificity is 100%. Based on the result of testing the accuracy of the algorithm using the 20 dataset that results with the accuracy value of 85%, sensitivity is 84.6% and specificity is 100%. These results prove that generated model using C4.5 decision tree algorithm is efficient in selecting of pet adopters. © 2022 IEEE.

关键词： Decision trees

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The Terms Estimation of S Robotics using MTRS as well as FEM

The Terms Estimation of S Robotics using MTRS as well as FEM

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Advance computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： R. Gopal Mustafa Mudhafar Amjad Hashem Venkadeshan Ramalingam Dibyahash Bordoloi Muhammad Numan Ali Khan Myasar Mundher Adnan Zahraa N. Abdulhussain Assistant Professor Information and communication Engineering College of Engineering University of Buraimi Sultanate of Oman Department of Medical Physics Faculty of Medical Applied Sciences University of Kerbala Karbala Iraq Computer Engineer Department Al-kunooze University College Basra Iraq Network Computing College of Computing and Information Sciences University of Technology and Applied Sciences– Shinas Sultanate of Oman Dept of CSE Graphic Era Hill University Adjunct professor Graphic Era Deemed to be University Dehradun Uttarakhand Faculty – Network Computing College of Computing and Information Sciences University of Technology and Applied Sciences – Shinas Sultanate of Oman Department of computers Techniques engineering College of technical engineering The Islamic university Najaf Iraq College of Technical Engineering National University of Science and TechnologyDhi Qar Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

This look at addresses the critical project of reaching dependable and precise proprioception in soft robots, it really is essential for his or her effective deployment in complicated environments. By integrating multi-tap resistive sensors in the robot’s form, our technique lets in for the distinct sensing of nearby deformations at various factors throughout the robotics’ frame, moving beyond traditional techniques that anticipate steady curvature. We beautify the decision of these deformations and couple the sensory facts with a strong finite detail technique (FEM) model. This included framework allows the correct estimation of the smooth robot’s form and the significance of outside forces applied to it, attaining a mean relative inaccuracy of about 4%. Additionally, our technique proves its software program in tender manipulation structures, in which it achieves thirteen% relative mistakes in external force estimation inside diverse zero to five N. The approach gives a promising direction for enhancing robotic interactions in sensitive and dynamic responsibilities, providing massive enhancements in robotic proprioception without reliance on outdoor monitoring generation.

关键词： Deformable models Deformation Force Estimation Soft robotics Robot sensing systems Software

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Optimizing Wireless Sensor Network Routing Through Memetic Algorithms: Enhancing Energy Efficiency and Data Reliability

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Procedia Computer Science 2023年 230卷 150-157页

作者： Aishwarya D Saranya S Sathiya A Samuel Manoharan J Asst. Professor/Dept. of Computer Science and Engineering School of Computing Sathyabama Institue of Science and Technology Chennai India Asst. Professor (SS)/ Dept. of Computer Science and Engineering Dr. N.G.P Institute of Technology Coimbatore India Research Scholar/Dept. of Electronics and Communication Engineering M. Kumarasamy College of Engineering Karur India Professsor/Dept. of Electronics and Communication Engineering Sir Issac Newton College of Engineering and Technology Nagapattinam India

Memetic Algorithm Based Routing in Wireless Sensor Networks (WSNs) is an innovative approach for optimizing data transmission routes within a network of interconnected sensors. Traditional routing algorithms often fail to consider the dynamic and resource-constrained nature of WSNs, resulting in inefficient energy utilization and decreased network lifetime. By incorporating principles of natural selection, crossover, and mutation from genetic algorithms, along with local search methods, memetic algorithms offer a more adaptive solution. This research aims to implement a memetic algorithm to find the optimal routing paths while minimizing energy consumption and maximizing data delivery ratio. Preliminary results indicate a significant improvement in the network's overall performance metrics, including a longer lifespan and higher data reliability, compared to traditional routing methods.

关键词： Wireless Sensor Networks Energy Efficient Routing Memetic computing Evolutionary algorihtms

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Bird Swarm Algorithm with Fuzzy Min-Max Neural Network for Financial Crisis Prediction

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Computers, Materials & Continua 2022年第10期73卷 1541-1555页

作者： K.Pradeep Mohan Kumar S.Dhanasekaran I.S.Hephzi Punithavathi P.Duraipandy Ashit Kumar Dutta Irina V.Pustokhina Denis A.Pustokhin Department of Computing Technologies Associate ProfessorSRM Institute of Science and TechnologyKattankulathur603203India Department of Information Technology Kalasalingam Academy of Research and Education626126India Department of Computer Science and Engineering Sphoorthy Engineering CollegeHyderabadTelangana501510India Department of Electrical and Electronics Engineering J B Institute of Engineering and TechnologyHyderabadTelangana500075India Department of Computer Science and Information System College of Applied SciencesAlMaarefa UniversityRiyadh11597Kingdom of Saudi Arabia Department of Entrepreneurship and Logistics Plekhanov Russian University of Economics117997MoscowRussia Department of Logistics State University of Management109542MoscowRussia

Financial crisis prediction(FCP)models are used for predicting or forecasting the financial status of a company or financial *** is considered a challenging issue in the financial *** and machine learning(ML)models can be employed for the design of accurate FCP *** numerous works have existed in the literature,it is needed to design effective FCP models adaptable to different *** study designs a new bird swarm algorithm(BSA)with fuzzy min-max neural network(FMM-NN)model,named BSA-FMMNN for *** major intention of the BSA-FMMNN model is to determine the financial status of a firm or *** presented BSA-FMMNN model primarily undergoes minmax normalization to transform the data into uniformity ***,k-medoid clustering approach is employed for the outlier removal ***,the classification process is carried out using the FMMNN model,and the parameters involved in it are tuned by the use of *** utilization of proficient parameter selection process using BSA demonstrate the novelty of the *** experimental result analysis of the BSA-FMMNN model is validated using benchmark dataset and the comparative outcomes highlighted the supremacy of the BSA-FMMNN model over the recent approaches.

关键词： Financial crisis predictive model machine learning outlier removal clustering metaheuristics

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On Abstract Sciences: From Data, Information, Knowledge to Intelligence Sciences 21

On Abstract Sciences: From Data, Information, Knowledge to I...

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21st IEEE International Conference on Cognitive Informatics and Cognitive computing, ICCI*CC 2022

作者： Wang, Yingxu Intl. Inst. of Cogn. Informatics and Cognitive Computing Visiting Professor: Stanford Univ. MIT School of Engineering and Hotchkiss Brain Institute University of Calgary Dept. of Electrical and Software Engineering Schulich CalgaryABT2N 1N4 Canada

ISBN: (纸本)9781665490849

The emergence of abstract sciences as a counterpart of classic concrete sciences is presented in this work. The framework of abstract sciences encompasses data, information, knowledge, and intelligence sciences from the bottom up. It is found that intelligence is the ultimate level of cognitive objects generated in human brains aggregated from data (sensory), information (cognition), and knowledge (comprehension). However, there is a lack of rigorous studies and coherent theories towards the theoretical framework of abstract sciences as the counterpart of classical concrete sciences. This paper explores the cognitive and mathematical models of abstract mental objects in the brain. The taxonomy and cognitive foundations of them are explored. A set of mathematical models of data, information, knowledge, and intelligence is formally created in intelligent mathematics. Based on the cognitive and mathematical models of the cognitive objects, formal properties and relationship of contemporary data, information, knowledge, and intelligence sciences are rigorously explained. © 2022 IEEE.

关键词： Concretes

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Tools for Analysis of Treatment Dynamics and Outcomes for Personalized Medicine in Asthma 17

Tools for Analysis of Treatment Dynamics and Outcomes for Pe...

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17th IEEE International Conference on Application of Information and Communication Technologies, AICT 2023

作者： Savvin, Nikita Vasenin, Dmitrii Podvalny, Semyen Pasetti, Marco Rinaldi, Stefano Lesina, Victoria Voronezh State Technical University Department of Innovation and Building Physics Named after Professor I.S. Surovtseva Voronezh Russia Università Degli Studi di Brescia Department of Information Engineering Brescia Italy Voronezh State Technical University Automated and Computing Systems Department Voronezh Russia Clinical Hospital №1 Voronezh Regional Voronezh Russia

ISBN: (纸本)9798350303568

This paper introduces a methodology for tracking the dynamic changes in parameters related to asthma treatment. Leveraging extensive data gathered from clinical trials, blood analysis, and patient records, this study has developed sophisticated tools for visualizing and evaluating the treatment dynamics among afflicted patients, as well as appraising the effectiveness of the treatments administered. To manage and process the copious amounts of data, advanced software tools were devised, thereby enabling precise and insightful analyses. Utilizing state-of-the-art statistical models, discernible patterns and trends associated with asthma have been identified, contributing to a deeper comprehension of the dynamics of treatment response and efficacy assessment. Through a thorough examination of longitudinal patient data, intricate insights into treatment patterns, disease progression, and long-term outcomes have been uncovered. In summary, this paper conducts a comprehensive analysis of patient parameters, employing a multidimensional strategy that encompasses clinical trials, blood parameter evaluations, and patient-year data assessments. The innovative software tools, models, and data analysis techniques employed in this study facilitate a meticulous evaluation of treatment dynamics and eventual outcomes. The implications of these findings are invaluable for enhancing clinical practices and ultimately enhancing the quality of life for individuals grappling with asthma. © 2023 IEEE.

关键词： Dynamics

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