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5th International Conference on Innovative Product Design and Intelligent Manufacturing Systems, ICIPDIMS 2023

作者： Mogili, Umamaheswararao Mohamed, Aezeden Kasup, Collettah Department of Computer Science and Engineering Avanthi’s St Theressa Institute of Engineering and Technology Andhra Pradesh Chepurapally India Department of Mechanical Engineering PNG University Lae Papua New Guinea Department of Business Studies PNG University Lae Papua New Guinea

ISBN: (纸本)9789819767311

Cloud computing has revolutionized the ability to store and analyze vast quantities of data in a manner that is both economical and adaptable. Keyword search is an important mechanism for users to retrieve information from the cloud, but traditional keyword search techniques are vulnerable to attacks from cloud service providers or malicious users. The proposed mechanism uses a combination of encryption, data fragmentation, and user authentication to guarantee that only approved users can search for and retrieve the data, and user authentication is implemented. At the same time, the data remains confidential and secure. The results present a prototype implementation of the mechanism and evaluate its performance in a real-time scenario. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ciphertext

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Enhancing Cooperative Spectrum Sensing Performance with Fusion Rule in Cognitive Radio: Hybrid Techniques 2

Enhancing Cooperative Spectrum Sensing Performance with Fusi...

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2nd International Conference Computational and Characterization Techniques in engineering and Sciences, IC3TES 2024

作者： Deepthi, K. Sreevani, N. Raj, Vijilius Helena Sangeetha, A. Sobti, Rajeev Salman, Z. Avanthi Insistute of Engineering and Technology Department of Mechanical Engineering India Hyderabad India New Horizon College of Engineering Department of Applied Sciences Bangalore India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lovely Professional University Phagwara India Hilla University College Babylon Iraq

ISBN: (纸本)9798350364699

The issue of limited wireless spectrum may be addressed with the use of Cognitive Radio (CR). Without affecting the primary users (PU), or licenced users, it allows other users, known as secondary users or unlicensed users, to exploit spectrum gaps, improving spectrum efficiency. Energy detection, a matching filter, and cyclostationary detection make up the CR, which determines whether the spectrum is idle or not. Cognitive Radio Networks (CRNS) are hindered in their ability to improve performance by noise. No signal-to-noise ratio (SNR) may be efficiently achieved with a cooperative spectrum employing a set sensing time in terms of throughput performance. There are two ways that this research suggests they might improve the effectiveness of energy detectors in the wireless spectrum. At its core, the first method is an energy detector-based hybrid of the Additive Wavelet Transform as well as the Homomorphic (AWTH). Mixing the Haar Discrete Wavelet Transform with the Homomorphic technique (HDWTH) is the basis of the second approach. The Two Quality Metrics Used: False Alarm Probability (Pf) and Probability Detection (Pd). The efficiency of the energy detector is enhanced by implementing the two methods that have been suggested. Metrics for quality demonstrate that the first method improves the wireless spectrum's Pd point perspective. But from a throughput perspective, the second strategy succeeds in maximising. © 2024 IEEE.

关键词： Signal to noise ratio

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Enhancement of tribological properties of AA7075 aluminum alloy using nano-silicon carbide reinforcement: A detailed wear analysis and microhardness study 4

Enhancement of tribological properties of AA7075 aluminum al...

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4th Innovative Product Design and Intelligent Manufacturing Systems, IPDIMS 2022

作者： Phaneendra, Y. Mohan Rao, I. Kumar, P. Vijaya Santhoshi Kumari, Pilaka Suresh Babu, Koppula Avinash Ben, B. Dhanunjayarao, Borra N. Swamy Naidu, N.V. Hemalatha, S. Andhra Pradesh Visakhapatnam530049 India Andhra Pradesh Visakhapatnam531162 India Department of Mechanical Engineering Avanthi Institute of Engineering & Technology Andhra Pradesh Vizianagaram535006 India Department of Mechanical Engineering National Institute of Technology Raipur Chhattisgarh Raipur492010 India

Aluminum is used in engineering materials to produce components with a higher strength-to-weight ratio. The tribological properties of the aluminum alloy AA7075MMC were improved by using nano-silicon carbide (SiC) with a particle of 50 nm size material as a reinforcement in various proportions (1%, 2 %, 3%, and 4% wt. of SiC) synthesized using liquid metallurgy stir-casting technique. A comprehensive wear analysis was performed using an advanced computerized wear tester, employing an EN-32 steel disc and a round pin as the nanocomposite sample. The wear rate was determined through the friction coefficient, weight loss, and specific wear rate calculations. The results demonstrate that the nano-enhanced composites exhibit superior wear resistance compared to the base alloy (Al 7075). High-resolution field emission scanning electron microscopy (HR FESEM) was employed to examine the structural and microstructural characteristics of the materials, as well as the wear surfaces and debris. The weight loss of the composites was observed, and the relationship between wear loss and applied load was investigated, revealing similar trends for both the reinforced composites and the metal matrix. Furthermore, the nanocomposites exhibited reduced wear rates compared to conventional metals. An increase in the weight percentage of SiC resulted in a decrease in the wear rate and friction coefficient, especially with higher sliding speeds and SiC weight fractions. FESEM analysis confirmed the presence of SiC and other phases in the composites. Notably, the 4 wt% SiC composite demonstrated significantly improved friction coefficient, wear rate, and weight loss compared to the Al 7075 matrix metal. Copyright © 2023 Elsevier Ltd. All rights reserved.

关键词： Aluminum alloys

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Performance analysis of an Injera baking machine by using solar energy

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Materials Today: Proceedings 2022年 56卷 3285-3293页

作者： Suresh, P. Ali, M.D. Irfan Rao, P. Govind Rudrapati, Ramesh Mechanical Engineering Department Bharat Institute of Engineering and Technology Mangalpally Telangana Sagar road Ibrahimpatnam RR Dist India Thermal & Aerospace Program School of Mechanical Chemical and Materials Engineering Adama Science and Technology Ethiopia Mechanical Engineering Department Avanthi Research and Technology Bhogapuram India School of Mechanical Industrial Engineering Bulehora University Bulehora Ethiopia

The majority of Ethiopia's population, primarily women, is susceptible to smoke inhalation during cooking, and they spend the majority of their time striving to collect firewood. Biomass deforestation for cooking harms the rural household economy and contributes to national and global environmental change, such as pollution and health issues. The effort should aim to integrate the Scheffler concentrator with a thermal storage system via the secondary solar cooking reflector in order to stimulate indoor cooking while avoiding concerns associated by carbon inhalation and deforestation. As a result, the Injera bakery system powered by solar thermal energy is born. There is a primary (Scheffler), secondary (reflective), and thermal storage device incorporated, as well as a cooking (pan) mounts. Solid works software was utilized for Scheffler focus and secondary reflector modeling and simulation. The thermal retention capacity of a storage device is determined using heating and cooling curves generated by software modeling and simulation. The findings gained would aid in the development of any comfortable indoor cooking system specifically for rural areas without a grid connection, and as a result of this study, carbon inhalation and deforestation difficulties would be mitigated. Through automation, the output rate would also increase the amount and efficiency of injera. This analysis focuses on the Injera baker concept for domestic applications. © 2021

关键词： Solar energy

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Recognition of Indian Gestural Language Through Neural Networks: Narrative Approach 1

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8th International Conference on Computers, Management and Mathematical Sciences, ICCM 2022

作者： Budimure, Ramana Babu Lalitha, A.S. Rao, Golagani A. V. R. C. Mummana, Satyanarayana Sambana, Bosubabu Akula, Chandra Sekhar Jawaharlal Nehru Technological University-Gurajada Andhra Pradesh Vizianagaram India Andhra Pradesh Visakhapatnam India Department of Computer Science and Engineering Avanthi Institute of Engineering and Technology Vizianagaram Cherukupally India Jawaharlal Nehru Technological University-Gurajada Andhra Pradesh Vizianagaram India

ISBN: (数字)9783031511677

ISBN: (纸本)9783031511660

Gesture-based communication acknowledgment is useful in correspondence between marking individuals and non-marking individuals. Different research projects are underway on various communication via gesture acknowledgment frameworks around the world. The examination is restricted to specific countries as there are country-wide varieties accessible In this paper the hand signals compared to ISL English letters in order are caught through a webcam. In the caught outlines the hand is divided and the neural organizations are utilized to perceive the letters in order. The elements like points made between fingers, the number of fingers that are completely opened, completely shut, or semi-shut, and recognizable proof of each finger contribute to the neural organization. Trial and error were accomplished for single-hand letter sets and the results are summed up. In this paper, we have mentioned a comparison of various techniques for using recognition of gestural language like a neural network, CNN, deep learning, artificial neural network, and autoencoder work done to determine better results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Neural networks

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Weather Prediction(analysis) using Soft kind of Computing techniques 4

Weather Prediction(analysis) using Soft kind of Computing te...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Revathi, Pogiri Bhavani, Santhoshi Karthika Priya Dharshini, G. Rajaram, Gnanajeyaraman Siddhan, Saravanan Dwibedi, Rajat Kumar Gmr Institute of Technology Department of Ece Andhra Pradesh Rajam India Avanthi Institute of Engineering and Technology Department of Ece Andhra Pradesh Thagarapuvalasa India Saveetha Engineering College Thandalam Saveetha nagar Chennai602105 India Saveetha Institute of Medical and Technical Sciences Simats Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Department of Ece Tamil Nadu Chennai India

ISBN: (纸本)9798350360165

Identifying weather conditions is a prevalent issue across all industries. Autonomous vehicles must accurately assess meteorological conditions to adapt their driving behavior. Contemporary farming relies on analyzing present weather patterns. A potential approach could involve implementing a system that detects weather conditions from images. Since no specialized sensors are required, the entire setup should be quite affordable. Transfer learning (TL) enables the development of picture categorization methods with a limited database. This work introduces 3 weather detection systems. The designs are built using InceptionV3, MobileNetV2, & ResNet50 designs. Their effectiveness is evaluated and explained. © 2024 IEEE.

关键词： Neural networks

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Enhancement of tribological properties of AA7075 aluminum alloy using nano-silicon carbide reinforcement: A detailed wear analysis and microhardness study

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Materials Today: Proceedings 2024年 115卷 229-237页

作者： Y. Phaneendra I. Mohan Rao P.Vijaya Kumar Pilaka Santhoshi Kumari Koppula Suresh Babu B. Avinash Ben Borra N. Dhanunjayarao N.V. Swamy Naidu S. Hemalatha Department of Mechanical Engineering Vignan’s Institute of Information Technology (Autonomous) Visakhapatnam 530049 Andhra Pradesh India Department of Mechanical Engineering Raghu Institute of Technology (Autonomous) Visakhapatnam 531162 Andhra Pradesh India Department of Mechanical Engineering Avanthi Institute of Engineering & Technology Vizianagaram 535006 Andhra Pradesh India Department of Mechanical Engineering National Institute of Technology Raipur Raipur 492010 Chhattisgarh India

Aluminum is used in engineering materials to produce components with a higher strength-to-weight ratio. The tribological properties of the aluminum alloy AA7075MMC were improved by using nano-silicon carbide (SiC) with a particle of 50 nm size material as a reinforcement in various proportions (1%, 2 %, 3%, and 4% wt. of SiC) synthesized using liquid metallurgy stir-casting technique. A comprehensive wear analysis was performed using an advanced computerized wear tester, employing an EN-32 steel disc and a round pin as the nanocomposite sample. The wear rate was determined through the friction coefficient , weight loss, and specific wear rate calculations. The results demonstrate that the nano-enhanced composites exhibit superior wear resistance compared to the base alloy (Al 7075). High-resolution field emission scanning electron microscopy (HR FESEM) was employed to examine the structural and microstructural characteristics of the materials, as well as the wear surfaces and debris. The weight loss of the composites was observed, and the relationship between wear loss and applied load was investigated, revealing similar trends for both the reinforced composites and the metal matrix. Furthermore, the nanocomposites exhibited reduced wear rates compared to conventional metals. An increase in the weight percentage of SiC resulted in a decrease in the wear rate and friction coefficient, especially with higher sliding speeds and SiC weight fractions. FESEM analysis confirmed the presence of SiC and other phases in the composites. Notably, the 4 wt% SiC composite demonstrated significantly improved friction coefficient, wear rate, and weight loss compared to the Al 7075 matrix metal.

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A Microservice Architecture with Load Balancing Mechanism in Cloud Environment 1

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International Conference on Machine Learning and Big Data Analytics, ICMLBDA 2022

作者： Mummana, Satyanarayana Sambana, Bosubabu Ramanababu, Budimure Gandreti, Preethi Rani, P. Pratima Mishra, Priyanka Chandrasekhar, A. Narasimha Raju, K. Andhra Pradesh Vizianagaram India Jawaharlal Nehru Technological University Andhra Pradesh Kakinada India Department of Computer Science and Engineering Indian Institute of Information Technology Kota Rajasthan Jaipur India Andhra Pradesh Visakhapatnam India Department of Computer Science and Engineering Vignan’s Institute of Information Technology Visakhapatnam Andhra Pradesh India Department of Computer Science and Engineering Avanthi Institute of Engineering and Technology Vizianagaram Andhra Pradesh India Visakhapatnam Andhra University Andhra Pradesh India

ISBN: (数字)9783031151750

ISBN: (纸本)9783031151743

To solve the rising delay in responding to requests in Microservices Architecture (MSA), a load-balancing algorithm for requests is proposed based on microservice chain awareness. To formalize the request delay and microservice environment, the algorithm takes the average request delay and the host loads as the evaluation indicators. On this basis, the competition for shared microservices in microservice chain calling is studied. The simulation results show that the proposed rules can substantially reduce the put-off in requests in a complex microservice chain environment compared to the RR algorithm set of rules. In addition, it keeps excellent loading performance in an environment with unevenly distributed instances and balances loads of different hosts. In the more realistic tests of high-frequency requests, the proposed set of rules can drastically reduce the available reaction time of the system. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Scheduling algorithms

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Synergistic Integration of Photovoltaic and the Grid: An Intelligent ANFIS-Governed Interleaved Boost Converter Approach

Synergistic Integration of Photovoltaic and the Grid: An Int...

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2024 International Conference on Advancement in Renewable Energy and Intelligent Systems, AREIS 2024

作者： Balaji, V. Ganga, M. Barathi, K. Gouda, Pramod Kumar Prasad, Rajesh Venkatesh, Mammula MAI-NEFHI College of Engineering and Technology Department of Electrical and Computer Engineering Asmara Eritrea Hindusthan College of Engineering and Technology Department of Biomedical Engineering Coimbatore India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept. of Eee Tamil Nadu India Aditya Institute of Technology and Management Dept. of Eee Andhra Pradesh Srikakulam India Stella Mary's College of Engineering Dept. of Eee Tamil Nadu India Avanthi's Research and Technological Academy Dept. of Eee A. P Vizianagaram531162 India

ISBN: (纸本)9798350387230

The transition towards Renewable Energy Sources (RES), mainly solar power is crucial in addressing the depletion of fossil fuel-based energy supplies and mitigating environmental concerns. This paper proposes an innovative approach to enhance efficiency of PhotoVoltaic (PV) systems by integrating a two-phase Interleaved Boost (IB) converter with an Adaptive Neuro Fuzzy Inference System (ANFIS) controller. The ANFIS controller optimizes the operation of the IB converter by adjusting the duty cycle based on two key input parameters: solar irradiation and temperature. This adaptive control method effectively transforms solar energy into electrical power, maximizing the PV system's power production. By using the ANFIS mechanism, the suggested system improves total output power, decreases overshoot, and produces a higher voltage output than conventional techniques, all of which lead to increased performance and dependability. The IB converter operates with an efficiency of 96.15% and minimized settling time. © 2024 IEEE.

关键词： Adaptive control systems

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Mapping the Evolution of English language: Insights from Big Data Analysis

Mapping the Evolution of English language: Insights from Big...

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Cybernetics, Cognition and Machine Learning Applications (ICCCMLA), IEEE International Conference on

作者： Ranjit Kumar Elamadurthi Ayush Chakraborty Tamal Sau Satyanarayana Pukkalla G Suryanarayana Department of English Vardhaman College of Engineering Hyderabad India Department of Computer Science and Engineering Avanthi Institute of Engineering and Technology Vizianagaram India Department of Information Technology Vardhaman College of Engineering Hyderabad India

ISBN: (数字)9798331505790

ISBN: (纸本)9798331505806

This paper explores the transformative role of big data in studying language evolution, tracing historical linguistic shifts, and revealing contemporary trends. Traditional methods relied on manual analysis, but big data enables realtime, large-scale examinations through tools like NLP and social media analytics. Case studies, including “Quantitative Analysis of Culture Using Millions of Digitized Books” and analyses of Twitter language, demonstrate how big data uncovers new insights into cultural and linguistic dynamics. Despite challenges like data reliability and ethical concerns, integrating big data with conventional research methods offers a comprehensive approach to understanding language evolution and its broader implications.

关键词： Ethics Social networking (online) Statistical analysis Psychology Manuals Machine learning Big Data Linguistics Market research Reliability

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