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Life cycle assessment of alternative building materials using idematlightlca mobile app

Materials Today: Proceedings 2022年 65卷 1243-1249页

作者： Saravanan, J. Sridhar, M. Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi Chennai 600052 India

In this paper, we have quantified the environmental impacts of different choices of conventional and alternative building materials for a 2BHK model residential building for above the plinth level construction using Life Cycle Assessment (LCA) standard procedures recommended by ISO 14040 – 2006 guidelines. The LCA was carried out using IdematLightLCA android app (Version 4.0) which is designed by delft University of technology, Netherlands. The comparisons were made between clay red bricks Vs sand lime bricks and reinforced cement concrete Vs bubble zoned light weight concrete with conventional and renewable energy resources inputs. The environmental impact categories analyzed were ranked on eco cost and on carbon footprint. The results confirmed that alternative materials along with renewable energy inputs proved to be more environment friendly and energy efficient than the conventional materials along with conventional energy inputs. © 2022

关键词： Energy efficiency

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Selecting the Suitable Waste to Energy technology for India Using MULTIMOOrA Method under Pythagorean Neutrosophic Fuzzy Logic

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Neutrosophic Sets and Systems 2023年 56卷 276-290页

作者： devi, r. Narmada Sowmiya, S. Anuja, A. Department of Mathematics Vel Tech Rangarajan Dr.Sanguthala R&D Institute of Science and Technology Tamil Nadu Chennai India Research Scholar Department of Mathematics Vel Tech Rangarajan Dr.Sanguthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Mathematics Arulmigu Palaniandavar Arts College for Women Tamil Nadu Dindigul India

Municipal solid waste (MSW) development has increased on a global scale, posing significant socio-economic and environmental challenges. Waste to energy conversion is strategic because it can determine the best waste-to-energy technology. recognizing the significance of waste in energy selection, this research aims to select the best technology based on its eco-friendliness. A two-phase methodology is used for presenting a framework for waste to energy technology selection. The first phase involves the selection of criteria for this problem and the perspectives of decision makers. ranking the selected criteria using a novel SWArA method, and ranking the technology of WtE with respect to selected criteria weights are obtained. In this paper, we investigate the WtE technology problem using the novel concept of the Pythagorean Neutrosophic fuzzy set (PNFS). This set is a hybrid of the Pythagorean and Neutrosophic fuzzy sets. In this paper, we propose the best WtE technology for India. We employ the MULTIMOOrA method in the Pythagorean Neutrosophic fuzzy environment for this purpose. Sensitivity and comparison analyses are also performed to ensure the framework's robustness. The findings of this study are useful in ranking the technology, and as a result, waste management can replicate the proposed framework for waste disposal for their new platform. © (2023). All rights reserved.

关键词： Fuzzy sets

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Performance Analysis of MAC Protocols for Node density in Wireless Sensor Networks 8

Performance Analysis of MAC Protocols for Node Density in Wi...

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Magar, Hanmant d. Srinivasan, r. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science & Engineering Avadi Chennai India

ISBN: (纸本)9798350391770

A wireless sensor network is a group of various forms of nodes that are arranged at random around the sensor area. In WSNs, certain nodes operate as source nodes, monitoring factors from the nearby area, while one node acts as a sink node, collecting information from source nodes. Clustering, sectoring, and sleep-active mechanism are just some of the different methods used in WSNs to provide reliable transmission of information between one point to another. The efficiency of wireless sensor networks is determined by their quality of services, or QoS, which includes factors like packet delivery ratio, energy, throughput, delay etc. Transferring information from one end to the other requires the use of mac protocols and routing. routing protocols are used to determine the shortest path between the sending and receiving nodes, while the MAC protocol ensures reliable data transfer via communication channels between nodes. In this paper, we analyzed the efficacy of multiple MAC protocols with various QoS for different node densities. This will assist inventors in the future with analysis. The CSMA protocol performs effectively for all network QoS standards. © 2024 IEEE.

关键词： Sensor nodes

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A KNN Algorithm Based Predictive Model for Heart disease Progression

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recent Advances in Computer science and Communications 2023年第5期16卷 76-81页

作者： Jaffrin, Lijetha C. Srikanth, G. Umarani Department of Information Technology Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science and Engineering Bharath Institute of Higher Education and Research Chennai India

Background: disease diagnosis is a useful phenomenon in healthcare. Machine learning classification methods would considerably improve the healthcare industry by providing a quick diagnosis of the disease. Thus, time could be saved for doctors. Nearly 17.9 million people expire due to heart disease every year. Objectives: World Health Organization (WHO) predicted that rate of death might increase by 24.5 million in 2030. Since heart illness was the major cause of death in comparison with other diseases today, it was the most challenging disease to diagnose. Methods: One of the reasons for death due to heart disease was due to the fact that risks were not identified in the earlier stage. Earlier diagnosis of disease was very much important. Machine Learning algorithms were used for predicting the prognosis of disease. results: Here K-NN algorithm was used to predict the presence of heart disease in an individual. Thus, patients were classified as either positive or negative for heart disease and this model enhanced medical care and reduced the cost. This gave us significant knowledge that helps us to predict the patients with heart disease. Conclusion: The Python sci-kit library was used to implement this in Anaconda Navigator's Spyder Integrated development Environment. Experiments revealed that technique worked well and was more accurate than before. © 2023 Bentham science Publishers.

关键词： diseases

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Phishing detection System Through Hybrid Machine Learning Based on UrL 3

Phishing Detection System Through Hybrid Machine Learning Ba...

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3rd International Conference on Electrical, Electronics, Information and Communication technologies, ICEEICT 2024

作者： Anandaraj, A. Peter Soosai ramesh, P.S. Arifulla, Shaik Madhuri, Chenna Geetha Malepati, Nikhil Yeshwanth Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai Avadi India

ISBN: (纸本)9798350369083

Phishing assaults rent fake UrLs to gather customers' confidence and retrieve touchy facts, threatening cyber security. Conventional machine learning and rule-based algorithms are often the simplest ones used by present day phishing UrL detection solution. Lacking the resilience needed to always classify harmful UrLs, those tactics may additionally war to evolve to newly-advanced phishing methods. The cause of this paper is to provide a novel Phishing detection System that employs Hybrid Machine Learning (PdS-HML) as a way of overcoming these deficiencies. Through the combination of several system studying strategies, including ensemble techniques and deep studying, PdS-HML enhances detection accuracy and resilience towards state-of-the-art phishing efforts. This provides the way for PdS-HML to make use of the strengths of other processes. By achieving higher detection prices and simultaneously decreasing the quantity of fake advantageous critiques, PdS-HML demonstrates superior overall performance in comparison to standard techniques. The provided technology can discover subtle phishing patterns and tendencies even when attackers make use of obfuscation or evasion approaches. The results show that the PdS-HML approach improves phishing detection skills. Furthermore, they show that this method may safeguard users against phishing efforts in an increasingly dangerous online environment and lessen the dangers of malicious UrLs. © 2024 IEEE.

关键词： Phishing

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Novel sandwich structure approach to develop lightweight concrete canoe

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Materials Today: Proceedings 2022年 65卷 1779-1784页

作者： Bharath, M. Saravanan, J. Kumar Sha, Aman ram Ghimire, Bal Bhagat, Kaushal Sherstha, Lekhnath Ghimire, Prabin Kasaudhan, rahul Sha, Sathis Madhu, Shilpa Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi Chennai 600052 India

Concrete canoe making is a prestigious multidisciplinary activity that relates the fields like concrete technology, hydrodynamics, material science, naval architecture, etc. Each year national and international level competitions are organized by various organizations. This work aimed to produce a lightweight single peddler concrete canoe. It was achieved by synergetic effects of the following activities: enhancing the floatability of hardened concrete;creating a maneuverable hull for a fresh paddler;enriching the structural performance of the canoe for the stress reversal for dealing with the curling effect in lightweight concrete and fabricating a canoe for a watertight environment. © 2022

关键词： Sandwich structures

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Proactive Preterm Labor Prediction Using Ptl-Simple rNN deep Learning 2

Proactive Preterm Labor Prediction Using Ptl-Simple RNN Deep...

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2nd IEEE Global Conference on Communications and Information technologies, GCCIT 2024

作者： Sivaranjani, S. Aruna, r. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai600062 India

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388916

Preterm labour presents a substantial obstacle in nature of obstetrics, requiring precise prediction models for prompt intervention. Utilizing deep learning, particularly simple rNN, presents encouraging opportunities for making such predictions. Simple rNN models are highly effective in capturing sequential dependencies, which is essential for studying temporal patterns in risk variables associated with premature labour. Simple rNN models may detect minor connections that indicate the start of premature labour by integrating several information sources, such as maternal health records, genetic predispositions, and environmental variables. Their ability to analyze time-series data allows for dynamic risk evaluation, resulting in improved early warning systems. In addition, Simple-rNN models can adjust to changing patient profiles, ensuring that customized risk assessment also provides higher accuracy. Simple rNN-based prediction models have great promise to reduce the effect of preterm labour by allowing preventative treatments and enhancing perinatal outcomes. This research realize this potential through ongoing improvement and integration with clinical practice. © 2024 IEEE.

关键词： Prediction models

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Virtual reality for real Estate: revolutionizing Property Visualization and Enhancing Client Engagement 4

Virtual Reality for Real Estate: Revolutionizing Property Vi...

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4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Prema, K. Chhetri, Abish Singh, Sowmya Pratap rao, d. Yaswanth Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India

ISBN: (纸本)9798331518981

Modern Virtual reality with a huge impact on the ever-diversifying branches of this new digital economy, Virtual reality is now such an integral part of our contemporary reality. Several factors - from decreasing component prices, fast technological market maturity to the easy availability of wide array of high-tech products that can leverage this new technology has made it a practical idea. In this article, we would like to address an investigation in the sense of what it is about establishing anything resembling a real estate management system using artificial intelligence and virtual reality technologies. At its core, this research centers around augmented reality and virtual reality applications and use cases for real estate. The panorama camera feature allows you to photograph an entire space in a 3d plane, which can then be stitched together resulting your viewer having the ability to look around within this room and view other events as they happen from his point of view. This allows for the option of presenting content in an entirely new light. Although 360-degree camera can shoot in better quality, not all of the people have it so scanning with smartphone is enough. This application indicates that virtual reality enriches the understanding and increases clients' intention to purchase, while the manipulation of virtual reality content remains as an important factor affecting both clients' satisfaction towards future housing sales, as well as developer's acceptance. © 2024 IEEE.

关键词： Augmented reality

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Emotion recognition in Speech: A Natural Language Processing Perspective

Emotion Recognition in Speech: A Natural Language Processing...

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2024 International Conference on Advances in Computing research on science Engineering and technology, ACrOSET 2024

作者： Suganya, V. Prema, K. Hari Krishna, Cherukuri Siva reddy, Ch. Jaswanth, E. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India

ISBN: (纸本)9798350388800

Speech emotion recognition is the process of accurately interpreting an individual's emotion from their speech. This paper introduces a python-based approach using natural language processing techniques for real-time emotion recognition in speech. The system utilizes a combination of feature extraction, acoustic modeling, and sentiment analysis to accurately identify and categorize different emotions expressed in spoken language. The feature extraction process involves extracting relevant acoustic features such as from the speech signal. These features are then used to train machine learning algorithms to classify emotions. sentiment analysis techniques are incorporated to capture additional emotional cues present in the text of the speech. The system demonstrates promising results in real-time emotion recognition, achieving high classification accuracies for a range of emotions. The system's efficacy and productivity are further enhanced by leveraging popular Python libraries such as NLTK, Scikit-learn, and Keras for natural language processing and machine learning tasks. The ultimate goal is to enhance emotion recognition accuracy significantly, with observed improvements ranging from 95% to 98%. Through this work experimental evaluation of the system on various emotion datasets shows its capability to recognize emotions in real-time speech with real- world applications © 2024 IEEE.

关键词： Modeling languages

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Comprehensive review for Big data-Based Sensitive Information Secure Sharing Using Blockchain techniques 5

Comprehensive Review for Big Data-Based Sensitive Informatio...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Murukanantham, K. Uma Nandhini, d. Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530013

Big data (Bd) has attracted much attention from science and industry. recent developments in Bd have raised significant security issues and increased the risk of Bd data privacy breaches. The novel reviews recent research and advancements in sensitive data security and privacy. This review explores various blockchain services for Bd, including blockchain for securing significant data acquisition, data storage, analytics, and privacy protection. It then discusses recent approaches to Blockchain based privacy preservation techniques and reviews consensus algorithms and various other cryptographic methods like Ciphertext-Policy Attribute-Based Encryption (CP-ABE), Elliptic Curve Cryptography (ECC) and Enhanced Privacy-Preserving data Perturbation Algorithm (EPPdPA). Finally, discuss the accomplishments and drawbacks of recent methods, as well as highlight investigation open issues associated to the incorporation of blockchain into Bd. © 2024 IEEE.

关键词： Encryption algorithms

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