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Evolution of electric vehicle and its future scope

Materials Today: Proceedings 2020年 33卷 3930-3936页

作者： P.M. Sneha Angeline M. Newlin Rajkumar Research Scholar Department of Computer Science Engineering Anna University Regional Campus Coimbatore 641 046 India Assistant Professor Department of Computer Science Engineering Anna University Regional Campus Coimbatore 641 046 India

Electrification is one of the appropriate way to establish a clean and energy efficient transportation. The impact of electric vehicle on the environment is considered as a serious issue. The locomotive industry as well as power sector gets benefitted by the reliable technology provided by the electric vehicle. This green vehicle also helps in creating an alternative power source for household applications and provide ancillary services to the grid. It also helps in integrating the intermittent resources for vehicle charging. As this vehicle generates prominent feature of less maintenance and ease of charge at residential premises. The electric vehicle creates a significant role in power sector mainly in the application of smart grid and act as a smart vehicle through grid communication. The challenges imposed by the electric vehicle and its effects in the transportation and energy sector are elaborately addressed in this paper.

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Statistical analysis of online learning through cloud environment in higher education institutions using R Programming during COVID-19

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AIP Conference Proceedings 2022年第1期2516卷

作者： Ananthi Claral Mary T. Arul Leena Rose P. J. Armstrong Doss D. 1Research Scholar Associate Professor Department of Computer Science College of Science & Humanities SRM Institute of Science & Technology Chengalpattu India 2Research Scholar Associate Professor Department of Computer Science College of Science & Humanities SRM Institute of Science & Technology Chengalpattu India 3Head Department of Business Administration Madras Christian College Chennai India

Online learning through cloud platforms takes place on the cloud – a virtual space that is not tied to any computer. The cloud-based learning management systems bring vast benefits at all educational levels. These systems provide a powerful teaching tool. More educators are adopting them as their main learning management system, and students find them very intuitive to use. An online learning system based on cloud computing infrastructure is possible and it can significantly progress the effectiveness of investment that can make this system into a righteous path and accomplish a win-win situation for students and teachers. This online study comprises of several segments, namely, demographic details of the students, their usage of smart devices, device ownership, device connectivity and number of hours the device is connected in online. It consists of approximately 360 respondents. The statistical analysis was performed using R programming. The results indicated that most of the respondents utilize smartphones to access online classes through cloud platform. During pandemic circumstances the smart devices facilitated faculties and students of higher education sectors to teach and learn their subjects.

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IMPROVED RESOURCE MANAGEMENT AND UTILIZATION BASED ON A FOG-CLOUD COMPUTING SYSTEM WITH IOT INCORPORATED WITH CLASSIFIER SYSTEMS

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Microprocessors and Microsystems 2021年

作者： M. Buvana K. Loheswaran Karanam Madhavi Sivakumar Ponnusamy Aradhana Behura R. Jayavadivel Assistant Professor Department of Computer Science and Engineering PSNA College of Engineering and Technology Dindigul India Associate Professor Department of Computer Science and Engineering CMR College of Engineering &Technology Kandlakoya Medchal Road Hyderabad - 501 401 Telangana India Professor Computer Science and Engineering Department Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad 500090 Telangana state India Associate Professor Department of Computer Science and Engineering SRM Institute of Science &Technology Delhi NCR Campus Modinagar Ghaziabad Uttar Pradesh-201204 India Assistant Professor Department of Computer Science and Engineering GITA Engineering College Road Badaraghunathpur Janla Bhubaneswar Odisha-752054 India Associate Professor Department Computer Science and Engineering Vivekanandha College of Engineering for Women Tiruchengode Namakkal Tamilnadu-– 637205 India

With the rapid rise of computing devices-linked networks, the Internet of Things (IoT) has increased proportionally and speedily. After that, the size of the data generated and significantly increased computational effort. A solution for a very large workload is cloud computing significantly slowed and continues to be a problem in a distributed computer network. Addressing the workload at the network edge can enchase time feedback, and delaying the data load management task imposes performance constraints from the power source to the edge of the network, which does not support only limited battery power. Therefore, the workload must be distributed equally to the clouds and across the network. This document presents the XCS Classification System (LCS), by XCS and BCM-XCS, to ensure energy consumption at the end of the project which decreases the workloads of the processing time. Our test outcome showed the dominance of BCM-XCS XCS according to standard methods. A distributed method of allocating responsibility for reducing the processing time between node cloud and fog. In addition to the significant benefits of handling fluctuating turnaround times, the proposed procedures can simultaneously decrease 42% response times utilizing an average consumption of energy in the grid edge. With the propounded method, rechargeable batteries are used on the edge of the grid also can load approximately 18% more than the best method of the prior art.

关键词： Learning classification systems (LCS) Extended Classification System (XCS) Internet of Things (IoT) fog computing best classifier memory (BCM)

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Detect the Replication Attack on Wireless sensor network by Using Intrusion Detection System

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Journal of Physics: Conference Series 2021年第1期1717卷

作者： P. Manju Bala S. Usharani V. Abarna Associate Professor Department of Computer Science and Engineering IFET College of Engineering Villupuram. UG Scholar Department of Computer Science and Engineering IFET College of Engineering Villupuram.

Remote sensor systems are conveyed in dense regions wherever the sensor nodes are physically seized by intruders. As several nodes take care of the entire group area, the captured nodes are repeated. To rectify this attack, a response was provided. Be that as it may, because of the absence of improvements in the device size, these structures have low efficiency to recognize the clone hubs quickly. In order to quickly locate the clone hubs, an expansion calculation is generated in this paper with the improved LEACH called NI-LEACH convention which is utilized to limit the group by taking the vitality of every hub and the minimum range of clusters. In addition to this protocol, an IDS (Intrusion Detection System) calculation is designed and generated by doling out screen hubs in the remote sensor organization to identify replication assaults. Reenactment findings show that in remote sensor networks the new calculation is straightforward and powerful to implement. With a high probability proportion, a harmful centre can be reliably detected and established and ideal throughput can also be achieved all the *** limit of the method is expanded definitely byconsuming this calculation against the clone hub assault byintruders.

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Real-time energy-efficient framework for multi-source harvesting and adaptive communication IIoT networks

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Sustainable Computing: Informatics and Systems 2025年 47卷

作者： Kumari Priyanka Sinha Hosam Alden Riyadh Y.Mohana Roopa Saiyed Faiayaz waris Hatem S.A. Hamatta L. Bhagyalakshmi Shadab Alam Ali Algahtani Dept. of CSE Nalanda College of Engineering Chandi Bihar Engineering University Patna India Accounting and Finance department Faculty of Business Curtin University Malaysia Miri 98009 Malaysia Professor of Computer science and Engineering Institute of Aeronautical Engineering Hyderabad Telangana India Department of Computer Science and Engineering Koneru Lakshmiah Education Foundation Vaddeswaram Andhra pradesh India Department of Applied Sciences Aqaba University College Al Balqa Applied University Aqaba Jordan Faculty of Information Technology Aqaba University of Technology Aqaba Jordan Professor and Head Dept. of ECE Rajalakshmi Engineering College Chennai TN India Department of Computer Science College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Mechanical Engineering Department College of Engineering King Khalid University Abha Asir 61421 Saudi Arabia Research Center for Advanced Materials Science (RCAMS) King Khalid University Guraiger Abha Asir 61413 Saudi Arabia

Over the past few years, Industrial Internet of Things (IIoT) devices have proliferated across modern manufacturing ecosystems, facilitating real-time monitoring, predictive analytics, and autonomous control. Nevertheless, maintaining these devices in low-resource contexts, especially in situations where the use of wired power is impossible and battery management is not feasible, is a significant challenge. Here, we introduce a new hybrid system that combines multi-source ambient energy harvesting (vibration, heat, and RF) with a lightweight adaptive communication protocol specifically designed for energy-limited industrial settings. Harnessing real-time energy buffer levels and environmental feedback, the architecture utilizes a central middleware engine to adapt transmission behaviors, routing decisions, and node activity states. We design and test detailed models to measure the performance of the framework on major metrics such as energy usage, communication delay, packet delivery ratio, and network sustainability. We utilize a synthetic industrial case scenario with 45 IoT nodes out-deployed across three zones we show the framework's strong benefits over baseline and partial methods, reaching as high as 40 % improvement in node life, 28 % improvement in sustained throughput, and substantial improvements in node availability and energy fairness. This study provides a basis for the installation of self-sustained, resilient IoT systems in realistic industrial environments, connecting the state of the art for energy autonomy design with the state of the art in the field of communication intelligence.

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Survey for Dependent on Neuro Fuzzy Algorithm for Framework ID

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Journal of Physics: Conference Series 2021年第1期1717卷

作者： S. Umadevi B.V.K. Namratha Associate Professor Department of Computer Science and Engineering IFET College of Engineering Villupuram. UG Scholar Department of Computer Science and Engineering IFET College of Engineering Villupuram.

This article focuses on hybrid neuro-fuzzy techniques, its advantages and disadvantages. The techniques of fuzzy logic and neural networks are commonly used for artificial intelligence. At the point when they are utilized in a joined manner, they are called Neuro-Fuzzy Systems. In the Neuro-Fuzzy Systems fuzzy sets and fuzzy rules are adjusted using input output patterns. The Neuro-fuzzy systems are implemented by different authors in different models. The Neuro-Fuzzy frameworks have the accompanying attributes: quick learning, versatility on-line, to modify itself with the point of getting the little worldwide blunder conceivable and little computational multifaceted nature. The obtaining of information, the pre-handling of information and preparing information are additionally significant for the achievement of the use of the neuro-fuzzy models

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Optimizing the fluidity in thin-section investment casting for vacuum induction molten AZ91D-1 %wt. CaO

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Journal of Magnesium and Alloys 2025年

作者： Carneiro, V.H. Lopes, V. Duarte, I. Puga, H. INESC TEC - Institute for Systems and Computer Engineering Technology and Science R. Dr. Roberto Frias Porto4200-465 Portugal Department of Engineering School of Science and Technology - Universidade de Trás-os-Montes e Alto Douro Quinta de Prados Vila Real5001-801 Portugal INL – International Iberian Nanotechnology Laboratory Avenida Mestre José Veiga Braga4715-330 Portugal CMEMS-UMinho Department of Mechanical Engineering University of Minho Campus de Azurém Guimarães4800-058 Portugal TEMA - Centre for Mechanical Technology and Automation Department of Mechanical Engineering University of Aveiro Campus Universitário de Santiago Aveiro3810-193 Portugal LASI - Intelligent Systems Associate Laboratory Campus Azurém Guimarães4800-058 Portugal

This paper discusses an experimental investigation into the fluidity of AZ91D-1 %wt. CaO magnesium melt via induction for thin-section investment casting. Plaster molds with thin spiral cavities (0.5 to 1.5 mm square sections) were designed and manufactured to assess the impact of casting conditions on filling length, as magnesium alloys cause severe melting and melt-mold exothermic reactions, making investment casting challenging. Combinations of traditional Mg-mold reaction mitigation techniques, such as applying a protective mold coating (Yttria) and vacuum, were examined to determine their role in the filling process. The results suggest that when induction is employed to melt reactive alloys, these methods are not always beneficial, as initially thought. Particularly at higher melt temperatures, the combination of Yttria-coated molds with low-pressure vacuum induction significantly reduce fluidity: vacuum induced melt levitation which promotes oxidation with the residual atmosphere;and Yttria-coating cracking due to thermal stress during the mold fabrication slows filling and promotes significant melt-mold reaction. This study shows that best results to investment cast thin-sections are obtained by avoiding both vacuum and protective coatings, providing a viable route for the precision manufacturing of stent biomedical devices. © 2025 Chongqing University

关键词： Investment casting

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SAMS: Smart Agriculture Management System Using Emerging Technologies IoT, AI -A Study

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IOP Conference Series: Materials science and engineering 2021年第1期1074卷

作者： B. Srinivas Kumar S.G. Santhi K. Kranthi Kumar Research Scholar Department of Computer Science and Engineering Annamalai University. Associate Professor Department of Computer Science and Engineering Annamalai University. Assistant Professor Department of Information Technology Gudlavalleru Engineering College Gudlavalleru

Farming or Agriculture is the science and art of cultivating plants. It is the vital enrichment in the growth of human living. It creates food and the other related things by farming with domestic animals and will enable people to live long and healthy life. There are two agricultural categories, one is traditional Agriculture and the second one is Modern Agriculture. In Traditional Agriculture Farmers had faced many difficulties to Farm, but with the modern Agriculture Farmers can be able to see many improvements in Framing due to the agronomy, use of agricultural chemicals such as pesticides and fertilizers, Plant breeding and technological growth, these enrichments in Farming would yield good crop.(IoT)Internet of Things very often called as a system it can able to connect real physical Things, Implanted sensors, Embedded software's along with different technologies to connect and to transfer data amongst various diverse devices over the Internet. It is the hopeful expertise or technology which gives accurate and most reliable solutions on the way to too many domains. There is an extensive set of wide range of real time applications of IoT devices such as Industrial, Consumer, Commercial, Infrastructure may made IoT is the one of the best Technology to see enhancements in many domains. Solutions which are given by IoT would reduce human efforts in Farming and may provide sound of crop. In this paper a small survey will be presented to see how Internet of Things and its equivalent or other represent technologies AI, Cloud Computing would be useful to provide SMART AGRICULTURE along with Modern agricultural improvements will also be presented.

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Critical evaluation of YouTube videos regarding the all-on-4 dental implant treatment concept: A content-quality analysis

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Journal of Prosthetic Dentistry 2024年

作者： Gaikwad, Amit Rachh, Pranidhipurnima Raut, Kaustubh Associate Professor Department of Prosthodontics and Crown & Bridge MGM Dental College and Hospital Navi-Mumbai India and Doctoral Researcher Lower Saxony Centre for Biomedical Engineering Implant Research and Development (NIFE) Hannover Medical School Hanover Germany Department of Prosthetic Dentistry and Biomedical Materials Science Hannover Medical School Hanover Germany Graduate student Department of Prosthodontics and Crown & Bridge MGM Dental College and Hospital Maharashtra Navi-Mumbai India Graduate student Department of Prosthodontics and Crown & Bridge MGM Dental College and Hospital Kamothe Maharashtra Navi-Mumbai India

Statement of problem: Rehabilitation of complete edentulous arches by using the all-on-4 dental implant treatment concept is a well-established procedure. Considering the popularity of YouTube as a source for health-related information, a thorough investigation of the content-quality and reliability of videos regarding the all-on-4 concept is lacking. Purpose: The purpose of this cross-sectional analysis was to critically appraise the content-quality and reliability of YouTube videos regarding the all-on-4 dental implant treatment concept as a source of information for patients, students, and dentists. Material and methods: A comprehensive search was performed on the YouTube website using the specific keyword “All-on-4,” which was identified as the most appropriate search term by the Google Trends website. Only English language videos regarding the all-on-4 dental implant treatment concept were included for systematic analyses. Following the eligibility criteria, the included videos were assessed for their demographic characteristics and quality-content. Based on the content score, the videos were categorized as low content (LC) and moderate + high content (MHC) groups. Further, qualitative analyses were performed by using the DISCERN tool and a global quality (GQ) scale. Statistical analyses were conducted by using the Mann-Whitney U test and the Spearman correlation analysis (α=.05). Results: Of 250 screened videos, only 73 were eligible for final analyses. The included videos presented an average 123 846 (range, 4 to 3 182 404) views with a mean duration of 528 (range, 12 to 1699) seconds. In addition, the average number of likes was 1122 (range, 0 to 3300), but, remarkably, none of the included videos received any dislikes. Overall, the mean content-quality score was 6.2 ±3.8, thus indicating low-quality content. The average DISCERN and GQ scores were 47.73 ±9.94 and 3.41 ±0.95, with the Spearman rank correlation test showing a strong positive correlation (r=.73

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Machine learning approach for detection of keratoconus

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IOP Conference Series: Materials science and engineering 2021年第1期1055卷

作者： S Shanthi K Nirmaladevi M Pyingkodi K Dharanesh T Gowthaman B Harsavardan Associate Professor Department of Computer Science and Engineering Kongu Engineering College Erode India Assistant Professor Department of Computer Applications Kongu Engineering College Erode India UG Student Department of Computer Science and Engineering Kongu Engineering College Erode India

Keratoconus is a progressive eye disease and it should be detected in early stage, to avert probable refractive surgery that could develop ecstasies. In this the authors proposes a new computer aided diagnosis model based on Support Vector Machine (SVM) learning to detect the early stage of keratoconus using the available topographic, pachymetric and aberrometry parameters of patients with keratoconus, subclinical keratoconus and normal corneas. The proposed SVM produces 91.8% accuracy with 94.2% sensitivity, 97.5% specificity for classification of early keratoconus from normal; 100% accuracy with 100%, 100% of sensitivity and specificity respectively for classification of early keratoconus from subclinical keratoconus.

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