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Recent Trends in EV Technologies, Charging Process and Standards: A Comprehensive Review

Recent Trends in EV Technologies, Charging Process and Stand...

Cognitive Computing in engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Pramod Kumar M.A. Ansari Rajeev Agrawal Department of EEE Lloyd Institute of Engineering and Technology Greater Noida India Department of Electrical Engineering Gautam Buddha University Greater Noida India Department of CSE Lloyd Institute of Engineering and Technology Greater Noida India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

In this era, the depletion of fossil fuels and rising concerns about the emission of greenhouse gases (GHGs), which has contribution 30-40% of green-house-gas (GHG) emission by fossil-fuel operated transportation systems only and creating serious issues to environmental and eco-systems. So, there is a rapid transition toward electric vehicles (EVs) transportation system and it is providing a significant role in ongoing and coming electric vehicle transportation system. It has a significant scope for new research and advancements. Electric vehicles do not produce any kind of pollution i.e. emission of gases, noise pollution and running economically. The electric vehicles (EVs) have exponential growth and recognized worldwide. The rapid growth of electric vehicles are facing different challenges i.e. technical advancement, charging infrastructures, distribution network bidirectional power flow and charging time. This paper comprises a vital review on infrastructure of EV, latest scenario in technical development, different electric vehicles, AC-DC chargers with different charging standards, AC-DC isolated and non-isolated converters details. Slow and fast chargers and their levels of charging power and connectors are to be analysed for improving charging methods. There will be some challenges and future scopes for further advancements in modern electric vehicle technology.

关键词： Connectors Pollution Reviews Transportation Electric vehicles Topology Vehicle dynamics Standards Smart charging Resilience

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Designing Multifunctional Materials for Sustainable Construction: A Review 7th

Designing Multifunctional Materials for Sustainable Construc...

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7th International Conference on Construction, Real Estate, Infrastructure, and Project Management, ICCRIP 2023

作者： Kumari, Soni Krishna, Gude Rama Abhishek, Kumar Pathak, B.N. Khayoon, Ali Talib Dutt, Amit Anandhi, R.J. Chandra, Pradeep Kumar Department of Mechanical Engineering GLA University UP Mathura India Department of Civil Engineering Institute of Aeronautical Engineering Hyderabad500043 India Gujarat Ahmedabad380026 India Department of Mechanical Engineering IMS Engineering College Ghaziabad India College of Engineering Technology National University of Science and Technology DhiQar Iraq Lovely Professional University Panjab Phagwara India Department of Information Science Engineering New Horizon College of Engineering Bangalore India Lloyd Institute of Engineering and Technology Knowledge Park II Greater Noida Uttar Pradesh201306 India

ISBN: (纸本)9789819649013

This review paper focuses on the design of multifunctional materials for sustainable construction. The paper presents an overview of the key concepts and principles of sustainable construction and highlights the importance of using multifunctional materials to achieve sustainability. The paper discusses the various types of multifunctional materials, including phase change materials, shape memory alloys, and self-healing materials, and their applications in sustainable construction. The review also covers the recent advances in the design and development of multifunctional materials, including the use of nanotechnology and biomimicry. The paper concludes by identifying the challenges and opportunities associated with the design and implementation of multifunctional materials for sustainable construction. Overall, this review provides a comprehensive overview of the current state of the art in the design of multifunctional materials for sustainable construction and highlights the potential for further research and development in this area. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sustainable building

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Innovative Approaches to the Use of Multifunctional Materials in Building Envelopes 7th

Innovative Approaches to the Use of Multifunctional Material...

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7th International Conference on Construction, Real Estate, Infrastructure, and Project Management, ICCRIP 2023

作者： Kumari, Soni Suresh Kumar, R. Abhishek, Kumar Pathak, B.N. Nijhawan, Ginni Khayoon, Ali Talib Rajalakshmi, B. Kalra, Ravi Department of Mechanical Engineering GLA University UP Mathura India Department of Civil Engineering Institute of Aeronautical Engineering Hyderabad500043 India Gujarat Ahmedabad380026 India Department of Mechanical Engineering IMS Engineering College Ghaziabad India Lovely Professional University Panjab Phagwara India College of Engineering Technology National University of Science and Technology Dhi Qar Iraq Department of Computer Science New Horizon College of Engineering Bangalore India Lloyd Institute of Engineering and Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India

ISBN: (纸本)9789819649013

Multifunctional materials have become a hot topic in building envelope design due to their ability to simultaneously perform several functions such as structural support, insulation, energy harvesting, and storage. This paper reviews recent developments in the use of multifunctional materials in building envelopes, including their composition, properties, and potential applications. The paper also examines innovative approaches to integrating these materials into building envelopes to enhance their performance and sustainability. The potential benefits and challenges of using multifunctional materials in building envelopes are discussed, along with future directions for research in this field. However, there are also challenges associated with the use of these materials, including their high cost, complexity of integration, and potential durability issues, which require further research and development. Overall, this review provides insights into the current state and potential of multifunctional materials in building envelopes, highlighting opportunities for future research and application. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Thermal comfort

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Big Data Analytics for Healthcare Resource Allocation

Big Data Analytics for Healthcare Resource Allocation

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Sharma, Brijesh Kumar Jayant, Khel Prakash Pujari, Purvi Vikram, Devendra Saraswat, Manish Kathuria, Kajol Srm Institute of Science and Technology Department of Computer Applications UP Modinagar India Raj Kumar Goel Institute of Technology Computer Science & Engieering UP Ghaziabad India Dy Patil University Vijay Patil School of Management Department of Management Navi Mumbai India Abes Institute of Technology Computer Science & Engieering UP Ghaziabad India Lloyd Institute of Engineering & Technology Department of Mechanical Engineering UP Greater Noida India Gla University UP Mathura India Dronacharya Group of Institutions Dept Computer Science and Information Technology UP Greater Noida India

ISBN: (纸本)9798331508685

Big Data Analytics for Healthcare Resource Allocation is the new mantra as it integrates vast amounts of complementary data to allocate healthcare resources efficiently. There is an increasing demand for healthcare services, and resources are in limited supply, so doing something as simple as allocating resources can ensure that care quality remains high. The process includes gathering and organizing large datasets from several resources, including electronic health records, patient demographics, service utilization and detailed analysis to generate meaningful findings. Utilizing advanced statistical and analytical techniques, by definition, amongst others, Big Data Analytics can help you decipher the data to show you patterns in resource utilization (how resources are being used), areas where inefficiencies occur which have gone unnoticed long enough that cause them become ripe for incremental year over year cost savings targets or staff reactions if not corrected as then gain media attention likely) some even assembled through different techniques to predict future needs based on past use cases. The advantages of this are manifold. It will help identify high-risk patients, enhance clinical decision-making, and facilitate evidence-based resource allocation. It can also help quantify how well-existing resource distribution strategies work and influence resource planning. Big Data Analytics for Healthcare Resource Allocation: Better Outcome, Cutting Cost and Effective Utilization of Resources This have the potential to revolutionize healthcare resource allocation and improve national healthcare systems' efficiency and effectiveness. © 2025 IEEE.

关键词： Electronic health record

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Study of Oxide Material Variation on Electrical Characteristics and Linearity Parameters Induced in Vertical Nanowire TFET

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Semiconductors 2025年第5期59卷 474-482页

作者： Bhardwaj, Anjana Das, Amit Rai, Amrita Krishna, Ram Upadhyay, A.K. Department of ECE GLA University Uttar Pradesh Mathura India Lloyd Institute of Engineering and Technology Uttar Pradesh Greater Noida India G.L. Bajaj Institute of Technology and Management Uttar Pradesh Greater Noida India GL Bajaj Group of Institutions Mathura U.P. India

Abstract: The oxide material in a tunnel FET (TFET) plays an important role in the electrical characteristics of the device. As the device dimensions are diminishing and moving to high-k oxide materials, it is essential to maintain the linearity and reliability of the devices with varying manufacturing and environmental conditions. Therefore, this paper investigates the impact of variation in the material used for the oxide region. The effect is analyzed on analog/RF, structural, and linearity parameters. In this manuscript, the oxide materials are varied, including Al₂O₃, SiO₂, HfO₂, Si₃N₄, and ZnO₂. The proposed device achieves higher ON-current and steeper characteristics, a vertical nanowire TFET with high-k oxide (HKO-VNW-TFET) as the oxide material. Due to its high transconductance and cut-off frequency, the device’s suitability for analog applications has been verified by simulated RF analysis results. In addition, linearity analysis is performed in terms of several FOMs, such as higher-order gm, third-order intermodulation distortion (IMD3), second-order voltage intercept point (VIP2), third-order input intercept point (IIP3), and third-order voltage intercept point (VIP3). This manuscript aims to benefit the semiconductor industry by finding the effect of various oxides and to get a new opportunity by making highly reliable devices using high-k oxide material in devices. © Pleiades Publishing, Ltd. 2025.

关键词： HfO2 high-k linearity parameters Silvaco TCAD tunnel FET

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A Study on the Integration of Haptic Feedback for Optimizing Telerobotic Surgery

A Study on the Integration of Haptic Feedback for Optimizing...

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Cognitive Computing in engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Jayasheel Kumar Kalagatoori Archakam D Shobha Rani Ginni Nijhawan Tamam Ali Abd Ulabbas Abedi P. Subhashini Navya Gupta New Horizon College of Engineering Bangalore India Department of Electrical and Electronics Engineering Institute of Aeronautical Engineering Hyderabad Telangana Lovely Professional University Phagwara India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Lloyd Law College Greater Noida Uttar Pradesh

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

This paper aimed at conducting a comprehensive discussion on haptic feedback and force based teleoperation in the domain of surgical robots similar far-reaching significance of haptic feedback based operation in eradicating telerobotic surgery problems of sensory feel and motor skills for surgeons. Nonetheless, although the utilization of haptic feedback in the field of telesurgery has been demonstrated to have a plethora of benefits including enhanced realism during the interaction of tissue as well as the over-proportionate enhancement of surgical results, haptic feedback's adoption into commercial telesurgical systems remains limited. This paper categorizes the common technical barriers that have prevented broader use of haptic devices, such issues to do with fidelity, stability, and force feedback. Moreover, it also investigates strategies that are being investigated to address these problems, including the improved control algorithms, the use of machine learning techniques as well as combination of force reflection techniques. The paper also aims to review the ergonomics of haptic systems and their contribution to medical education particularly in surgery, the implications of haptic systems on patient outcomes is also considered. In concert with this, this study aims at presenting a research and development agenda for haptic integration in telesurgical operations through an elaborate review and synthesis.

关键词： Medical robotics Reviews Force Surgery Robot sensing systems Stability analysis Reflection Haptic interfaces Telerobotics Research and development

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Transfer Learning-Driven CNN Architectures for Automated Defect Detection in Printed Circuit Boards

Transfer Learning-Driven CNN Architectures for Automated Def...

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Cognitive Computing in engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Rajesh Gundlapalle Amandeep Nagpal Yagateela Pandu Rangaiah P Chandini Ali Albawi Susmita Kalyani Priyanka Agrawal Department of Electronics and Communication Engineering New Horizon College of Engineering Bangalore India Lovely Professional University Phagwara India Department of Electronics and Communication Enfineering Institute of Aeronautical Engineering Dundigal Hyderabad India Department of Information Technology MLR Institute of Technology Hyderabad Telangana India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Lloyd Law College Greater Noida Uttar Pradesh Department of Electrical & Electronics Engineering IILM University Greater Noida

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

Recent innovations in electronics manufacturing have created demands for timely an accurate defect during production of printed circuit board (PCB). The following paper gives a solid approach to PCBA defect detection using CNN, especially by transfer learning. In this method, the experts used pre-trained models like ResNet and EfficientNet besides retraining them on PCB defect datasets that are available to the public; this boosted the defect recognition process greatly. The method involves using TensorFlow/Keras based frameworks in the implementation and optimization of the CNN models and use OpenCV for a broad image preprocessing. Said integration of transfer learning with current most advanced neural architectures enables the achievement of very high detection rates even where domain-specific information is scarce. This study reveals the promising idea of using open datasets and developing practical CNN approaches to detect the defects for scaled electronics manufacturing.

关键词： Image edge detection Printed circuits Transfer learning Inspection Manufacturing Convolutional neural networks Integrated circuit reliability Integrated circuit modeling Defect detection Load modeling

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Advanced AI Techniques for Restoring Historical Documents and Photographs with Generative Adversarial and Diffusion Models for Cultural Heritage Preservation

Advanced AI Techniques for Restoring Historical Documents an...

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Cognitive Computing in engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Manjunatha Pendyala Shamili Srimani Manish Gupta Bashetty Suman Mohammed Wael Mohammed Kanan Divetia V Arun Department of Mechanical Engineering New Horizon College of Engineering Bangalore India Department of Electronics and Communication Engineering Institute of Aeronautical Engineering Hyderabad Telangana India Lovely Professional University Phagwara India Department of Information Technology MLR Institute of Technology Hyderabad Telangana India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Lloyd Law College Greater Noida Uttar Pradesh India Department of Electrical & Electronics Engineering IILM University Greater Noida India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

It is becoming the leading solution for bringing back the lost or damaged digital images, which are crucial for keeping history and culture alive. In this work, the state-of-art Generative Adversarial Networks (GANs), including CycleGAN and Pix2Pix, as well as diffusion models, have been explored for the first time in the area of historical image enhancement. The datasets are collected from the public domain; they are the Library of Congress and Old Picture repositories for training and testing the models. As illustrated by the framework under consideration, the fine details are reconstructed and noise is minimized when compared to other major approaches, thus the legibility and aesthetic quality of historical items are improved. The approach combines up-to-date machine learning algorithms with conventional image processing techniques thus maximizing the amount of the original content to be restored while at the same time maximizing the restoration quality. TensorFlow and PyTorch significantly help in the building of complex network structures and shorten the time for restoration. Thus, this work is relevant in this context as it discusses a professionally oriented scalable and robust realisation of digital archiving and restoration and opens up future ways to develop an integration of AI-based methodologies into the preservation of cultural heritage.

关键词： Training Machine learning algorithms Noise Diffusion models Generative adversarial networks Libraries Image restoration Cultural differences Image reconstruction Testing

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AI-Assisted Fine-Grained Plant Disease Diagnosis from Smartphone Images

AI-Assisted Fine-Grained Plant Disease Diagnosis from Smartp...

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Cognitive Computing in engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Anandhi R J D Sreenivasulu Alok Jain V Arun Fatimah Dhari Jabbar Bhasker Boddu Kanan Divetia Department of Information Science Engineering New Horizon College of Engineering Bangalore India Computer Science and Engineering (Data Science) Institute of Aeronautical Engineering Hyderabad India Lovely Professional University Phagwara India Department of Electrical & Electronics Engineering IILM University Greater Noida India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Lloyd Law College Greater Noida Uttar Pradesh India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

Disease detection at an early stage in plants is very important in order to check serious losses to crop production. This research presents novel, lightweight, and easily portable AI model that is best suited for real-time plant disease detection through mobile technology. The model is a combination of MobileNet and EfficientNet, and the Model is trained from the PlantVillage Dataset. One of the main objectives of the study is to enhance the ability to distinguish between visually similar diseases, a universal problem of plant pathology. Lack of data is then solved by using transfer learning from pre-trained networks as well as further image augmentation. Further, optimization techniques are employed in work to get faster inference and minimal device usage on mobile platform but keeping the diagnostic accuracy high. Thus, the proposed approach helps to bring ideas of AI to practicle field usage and supports further progress in such industries as precision farming and food safety.

关键词： Precision agriculture Plant diseases Accuracy Quantization (signal) Computational modeling Plants (biology) Transfer learning Production Real-time systems Image augmentation

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Federated Learning for Secure and Collaborative Power System Data ANALYSIS: Balancing Accuracy and Privacy in Decentralized Environments

Federated Learning for Secure and Collaborative Power System...

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Cognitive Computing in engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Priyanka Agrawal Yagateela Pandu Rangaiah Amandeep Nagpal Asha V P Laxmaiah Saurabh Sharma Baydaa Fathil Mohammed Department of Electronics & Electrical Engineering IILM University Greater Noida Department of Electronics and Communication Enfineering Institute of Aeronautical Engineering Dundigal Hyderabad India Lovely Professional University Phagwara India Department of Computer Applications New Horizon College of Engineering Bangalore India Department of Information Technology MLR Institute of Technology Hyderabad Telangana India Lloyd Law College Greater Noida Uttar Pradesh Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

The level of digitization in the current power systems has seen the generation of large volumes of data which provide a customer more options for enhanced visualization. Nevertheless, the proposed data is highly sensitive, which triggers multiple privacy issues to share this information among various utilities and stakeholders. This research aims at exploring the use of federated learning, a decentralized machine learning model, to overcome these in power system data analysis. Due to its ability to train machine learning models on several data sources co-operatively, federated learning helps to manage privacy by keeping data localized. They pointed out that the proposed method uses the properties of power system data, in particular temporal and spatial dependencies, also does not violate strict privacy requirements. The study shows that federated learning can improve the efficiency of utilities' cooperation and advance the power system operation and planning while preserving the data privacy. Such work is a remarkable progress in the integration of ML with power systems, providing a solid solution to the privacy issues that challenge this important area.

关键词： Data privacy Privacy Data analysis Accuracy Federated learning Collaboration Data models Power systems Stakeholders Protection

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