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

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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An Ensemble Model to Predict Network Traffic Prediction Model Using Rb Multicast Protocol 7

An Ensemble Model to Predict Network Traffic Prediction Mode...

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7th International Conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Deepa, S. Sathishkumar, P. Duraivelu, Vivek Suguna, R. Arunkumar, M.S. Myleshan, M.b. Kongu Engineering College Perundurai Department of Computer Technology - PG Tamilnadu Erode638060 India Bannari Amman Institute of Technology Department of Computer Science and Engineering Sathyamangalam India B v Raju Institute of Technology Department of Computer Science and Engineering Telangana Narsapur502313 India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamilnadu Chennai-62 India Kongu Engineering College Perundurai Tamilnadu Erode638 060 India

ISBN: (纸本)9798350340600

A Vehicular Ad Hoc Network (VANET) is an effective method for addressing group-oriented services. It is possible to support such services through multicast routing. As a result, packet delivery ratios must be improved, delays must be reduced, and overheads must be reduced. Consequently, multicast routing protocols for VANETs must be stable and reliable. A Receiver based Multicast protocol is proposed in our paper that determines how multicast traffic should be forwarded. In the packet header, Rb Multicast stores a list of destinations. Multicast members to whom this packet is addressed are listed in this destination list. Consequently, there is no need to store tree state at intermediate nodes and no multicast tree is required. According to this study, the objective of the study was to predict network traffic by using the V2R dataset, and to use the receiving packets sent by vehicles to the RSUs as a measure of network activity. Our analysis of network traffic flow resulted in the prediction of network flow. Using ensemble classification metrics, we evaluated the data. Simulated results indicate that the proposed model has a superior performance in terms of execution time and prediction accuracy compared to other algorithms. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Comparative Analysis of ResNet, EfficientNet, and MobileNetV2 for Detecting Skin Conditions in Deep Learning Models

Comparative Analysis of ResNet, EfficientNet, and MobileNetV...

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Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： M. Rajkumar Shreenath Raghunath Siriyala Ananya Sharma D. Naga Sujith Kumar Department of Smart Computing School of Information Technology & Engineering Vellore Institute of Technology VIT University Vellore Campus Tamil Nadu India B.Tech-Information Technology School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology VIT University Vellore Campus Tamil Nadu India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

Comparing the effectiveness of Skin Condition Detection using ResNet, EfficientNet and MobileNetV2 deep learning models. The 3 skin conditions that have been considered are Acrochordon, Lichenoid Keratosis and Vascular Lesions. The ResNet Model, EfficientNet Model and MobileNetV2 Model have been assessed against one another. ResNet and EfficientNet both predicted the skin condition with an accuracy of 92.1875% which is greater than MobileNetV2, which predicted the skin condition with 90.625% accuracy. Through this research, it has been concluded that ResNet and EfficientNet are significantly better than MobileNetV2 in terms of training models to accurately detect skin conditions.

关键词： Deep learning Training Analytical models Accuracy Quantization (signal) Green communications Skin Reliability Lesions Tuning

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Development of Secure IoT Ecosystems for Healthcare

Development of Secure IoT Ecosystems for Healthcare

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International Conference on Intelligent Communication and Computational techniques (ICCT)

作者： Pranav Shirgur Sandeep Chaurasia B. Tech Computer Science and Engineering Manipal University Jaipur Jaipur Rajasthan Department of Computer Science and Engineering Manipal University Jaipur Jaipur Rajasthan

The Internet of Things (IoT) is a rapidly developing field of technology which entails a network of smart devices connected to each other and the internet. The TATCRb2industry is anticipated to increase by 18% to 14.4 billion active connections in 2022. There will likely be about 27 billion linked IoT devices by 2025 as supply limitations, brought about by the current global semiconductor and chip shortage - loosen and demand quickens. IoT has quickly penetrated the healthcare industry, this paper defines a framework that enables the development of secure and scalable IoT healthcare platforms/applications. These platforms will also allow for secure cloud storage and analysis of patient data, helping professionals recognize latent parameters such as patient behavioral patterns that contribute to an ailment. This ultimately will enable the study of social and economic impact of a particular disease. This will greatly cull the survivorship bias in the health care industry - especially in testing times like a pandemic.

关键词： Industries Economics Cloud computing Ecosystems Medical services behavioral sciences Internet of Things

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Design and Development of Hybrid Feature Selection Method for Classification

Design and Development of Hybrid Feature Selection Method fo...

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2021 International Conference on Intelligent technologies, CONIT 2021

作者： Sreedevi, M. Manasa, Garikapati Apurva, Idupulapati Koneru Lakshmaiah Education FoundationVaddeswaram Dept of Computer Science and Engineering Andhra Pradesh India Koneru Lakshmaiah Education Foundation Vaddeswaram Jonnalagadda Mohana and Reddem Pravallika Final Year B.Tech CSE Andhra Pradesh India

ISBN: (纸本)9781728185835

To enhance the capability of the learning model in this research paper we have developed a hybrid feature selection method. To defeat the curse of dimensionality, to speed up the classification process, and to get more accurate results a hybrid feature selection model is developed which is a combination of multiple filter methods and a wrapper method. In this model, we employed two sets of Filter Methods-basic filter methods, a correlation filter method and two Statistical Ranking filter methods (ANOVA and ROC-AUC) to generate two different subsets of important features, and a Wrapper method (Recursive Feature Elimination with Cross-Validation) is applied on the combined subset to generate a final subset of important features for better prediction results. Five machine learning algorithms-Logistic Regression (LR), Decision Tree, Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbour are used to evaluate the classification accuracy. The proposed hybrid method is applied over four low and four microarray datasets. Outputs are compared to find out which algorithm works best with the proposed model as the results diverge with the machine learning algorithm. Precision, Sensitivity, and Specificity are calculated for each outcome and they demonstrate that the suggested method improved the accuracy of the algorithms. © 2021 IEEE.

关键词： Feature Selection

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Solar-Power Enabled Data-Driven IoT Smart Garbage Pail for Individuals and Disabled

Solar-Power Enabled Data-Driven IoT Smart Garbage Pail for I...

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science, technology, engineering and Management (ICSTEM), International Conference on

作者： S.Appavu alias balamurugan Preethi b Mohamed Ashik Sheriff R Vigneshwar b R Sumaiya V Computer Science and Engineering Periyar Maniammai Institute of Science & Technology (Deemed to be University) Thanjavur Tamilnadu India Final Year B Tech Computer Science and Engineering Periyar Maniammai Institute of Science & Technology (Deemed to be University) Thanjavur Tamilnadu India

ISBN: (数字)9798350376913

ISBN: (纸本)9798350388473

According to the increasing population, our disposal of waste has been increased. The main aim is to provide help for the physically challenged people in the disposal of waste. In this motive we have created one smart garbage pail based on loT. To provide convenience in this task, we have developed the bin to move on its own path to collect the dust. Main function of the smart bin is to deliver the trash bin close to a user who are physically challenged. by adding the ultrasonic sensor, it avoids the obstacles and deviates its path. In addition to that, it can automatically get opened when the user approaches the dustbin. Another purpose of the garbage pail is voice recognition accessed. by accessing the voice, the dustbin will move accordingly. Arduino UNO is act as a heart component of our smart garbage pail. A smart garbage pail comes the user and collects the dust, we can access it through voice reignition. It can also avoid obstacles.

关键词： Heart Sociology Speech recognition Robot sensing systems Acoustics Waste disposal Task analysis

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Introduction and Development of Cyber Physical Systems in Smart Grid with blockchain technology to Enhance Sustainability 2

Introduction and Development of Cyber Physical Systems in Sm...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Valarmathi, P. Manoj, G. Das, Sandip Kumar Oommen, Sujo Tiwari, Mohit B. S Abdur Rahman Crescent Institute Department of Computer Science & Engineering Tamil Nadu India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Management Studies Tamilnadu Chennai India School of Electrical Engineering Odisha Bhubaneswar751024 India Reva University School of Electrical and Electronics Engineering Karnataka Bangalore560064 India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350325799

The need for increased sustainability and efficiency in the energy industry has led to a major increase in interest in the development of cyber-physical systems (CPS) in the smart grid domain in recent years. In the context of the smart grid, the term "CPS"refers to a network of physical objects, sensors, and communication systems that are interconnected and allow for the smooth exchange of data and control signals to optimize the production, distribution, and use of electricity. Demand response, energy management, and grid optimization are just a few of the smart grid applications that can be successfully implemented by utilizing CPS's capabilities. On the other side, blockchain technology provides a decentralized and secure framework for logging and validating transactions among numerous organizations. Since it is distributed, there is no need for middlemen, transparency is improved, and data integrity and immutability are all guaranteed. These qualities make blockchain an excellent choice for tackling the issues that the smart grid is facing, such as data privacy, security, and stakeholder confidence. There are many advantages to integrating blockchain and CPS in the smart grid. First and foremost, a decentralized and democratized energy market is made possible by blockchain, which enables safe and effective peer-to-peer energy trade among prosumers. This increases sustainability by encouraging the use of renewable energy sources and reducing dependency on centralized power generation. In conclusion, there is enormous potential for improving sustainability through the smart grid's integration of blockchain technology with cyber-physical systems. © 2023 IEEE.

关键词： Cyber Physical System

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Cloud Computing-Enhanced and Raspberry Pi-powered Solution for Remote Ear, Nose, and Throat Consultations with AI-Driven Diagnostics 5

Cloud Computing-Enhanced and Raspberry Pi-powered Solution f...

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5th IEEE International Conference for Emerging technology, INCET 2024

作者： Giriprasad, S. Karpagam, T. Nalini, V. Mishra, Nilamadhab Mohankumar, N. Malathi, N. Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai India Department of Artificial Intelligence and Data Science R.M.K College of Engineering and Technology Tamil Nadu Chennai India Department of Mathematics Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Tamil Nadu Chennai India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India Department of Electronics and Communication Engineering B.V. Raju Institute of Technology Telangana 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)9798350361155

The cutting-edge telemedicine program presents a game-changing alternative for patients seeking ENT (ear, nose, and throat) consultations from a distant location. Utilizing the capabilities of Raspberry Pi devices, powerful artificial intelligence, and cloud computing, the system allows otoscopic tests to be performed without interruption while securely transmitting data to the cloud. On a web-based platform, interactive patient-professional consultations are made possible via real-time communication, which is made possible by WebRTC. Cloud services are very important because of their ability to provide scalable storage as well as AI-driven diagnostics for accurate evaluations. The system complies with the requirements for healthcare compliance, emphasizes security and privacy, and features encryption from beginning to finish. This integrated approach promises scalability, reliability, and advanced diagnostic capabilities, and it reshapes the landscape of remote ENT care with accessible and technologically advanced healthcare solutions. With a user-friendly interface for patients and a cloud-hosted application for healthcare professionals, this integrated approach provides patients with advanced healthcare solutions. © 2024 IEEE.

关键词： Artificial intelligence

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brain Tumor Detection using MRI Image Processing techniques

Brain Tumor Detection using MRI Image Processing Techniques

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2024 IEEE International Conference on Innovation and Novelty in engineering and technology, INNOVA 2024

作者： Jadhav, Ambaji S. Pawar, Rashmi Hattaraki, Sunilkumar M. bagali, Shwetha Patil, Rajeshwari S. Patil, bhagyashree Department of Elecrtical and Electronics Engineering B.L.D.E. A’s V.P. Dr. P.G.H. College of Engg. and Tech. Vijayapura India Department of Electronics and Communication Engineering B.L.D.E. A’s V.P. Dr. P.G.H. College of Engg. and Tech. Vijayapura India Department of Computer Science and Engineering Sri Krishna Institute of Technology Bengaluru India

ISBN: (纸本)9798331505134

Medical image processing is highly developed and critical in the medical field, encompassing methods like X-rays, MRI, and CT scans. These techniques help to identify minute defects in the human body. brain tumors, which disrupt normal brain function, are detected through MRI using segmentation, feature extraction, and classification, processes that are time-consuming and depend on the expertise of clinical professionals. computer-aided technology addresses these challenges. This work aims to diagnose brain tumors accurately and quickly using MRI images. Image preprocessing is done using CLAHE and median filter to enhance contrast and eliminate noise. Thresholding is used for segmentation and a lightweight U-net is used for tumor segmentation, achieving high accuracy and efficiency without extensive training data. Finally, an MSD-CNN classifies the tumor, capturing both local and global features for better image recognition. Our proposed model outperforms over existing methods in terms of accuracy, robustness, and efficiency in brain tumor detection. © 2024 IEEE.

关键词： Median filters

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Implying Fuzzy Set for Computing Agricultural Vulnerability 2

Implying Fuzzy Set for Computing Agricultural Vulnerability

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2nd International Conference on Computing and Information technology, ICCIT 2022

作者： Amudhavalli, P. Sherubha, P. Ponmani, S. Ahamed, S. Aarif Muthuraja, M. B S Abdur Rahman Crescent Institute of Science and Technology Department of Computer Applications Vandalur Chennai India Karpagam College of Engineering Department of Information Technology Coimbatore India Rajalakshmi Engineering College Tamilnadu Chennai India Vel Tech Rangarajan Dr. Sagunthala Rd Institute of Science and Technology Department of Computer Science and Engineering Chennai India Department of Computer Science and Engineering Erode India

ISBN: (纸本)9781665436052

Climatic variations may impacts the intensity and frequency of external weather events that may have stronger influence towards agriculture-based ecosystems. In some regional areas, this eco-system may vary due to farming practices, ecological environment, intrinsic factors that may influences event vulnerability. The connection among external events and vulnerabilities of eco-system are categorized by experts, farmers, researchers and various scientists. Moreover, the knowledge eco-system-based vulnerabilities should be considered. Some disciplinary modelling was constructed to map agricultural vulnerability based expert system with combination of geographical information system and fuzzy inference system. This approach was utilized to evaluate vulnerabilities of major eco-systems. Vulnerabilities in cultivation based on heavy rain and vulnerabilities due to drought. This approach is more flexible and may identify diverse factors based on vulnerabilities. This offers essential tools to identify potential source of adaptations with agricultural system. © 2022 IEEE.

关键词： Cultivation

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