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Design and Numerical Investigation of FTO/TiO2/FA0.85Cs0.15Pb(I0.85br0.15)3/MoO3/Au Perovskite solar Cell

Design and Numerical Investigation of FTO/TiO2/FA0.85Cs0.15P...

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2023 IEEE International Conference on Modelling, simulation and Intelligent Computing, MosICom 2023

作者： sarkar, Paramita srivastava, Ashutosh Narmada, G. Nithin, E.N. Naidu, J. B.M.S. Institute of Technology and Management Department of ECE Bangalore560064 India Bennett University School of Computer Science Engineering and Technology Greater Noida India B v Raju Institute of Technology Department of ECE Narsapur India

ISBN: (纸本)9798350393415

The primary aim of the present work is to design a perovskite photovoltaic cell with higher efficacy that is suitable for practical applications. Therefore, a mixed perovskite layer composed of FA0.85Cs0.15Pb(I0.85br0.15)3 was used as the active layer. Along with this perovskite, TiO2 and MoO3 have been used as electron and hole transport layer, respectively. The cell was optimized by varying the working temperature between 280K to 325K, absorber layer thickness between 100nm to 700nm, and bulk defect density between 1011/Cm-3 to 1016/Cm-3. The final Optimized cell shows 1.53v open circuit voltage, 23.67mA/Cm2 short circuit current, 85.63% of fill factor and 30.84% of efficiency at optimized temperature of 280K, optimized perovskite layer thickness of 700nm and bulk defect density of 1011 Cm3. The present modeling technique is compared with the reported theoretical as well as experimental data that confirm the accuracy of the conclusions we have obtained for the proposed cell. © 2023 IEEE.

关键词： Perovskite

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Construction of Low-carbon Economic Development Level Model based on bP Neural Network Algorithm 2

Construction of Low-carbon Economic Development Level Model ...

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2nd International Conference on smart Technologies for smart Nation, smartTechCon 2023

作者： Nurullayevna, Nigmatullayeva Gulchekhra Parvin begum, I. Alzubaidi, Laith H. Gnana soundari, A. santhosh, s. Naqvi, Aiman Tashkent State University of Economics Uzbekistan Department of Computer applications B.S.Abdur Rahman Crescent Institute of Science and Technology Tamil Nadu Vandalur600048 India College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Tamil Nadu Chennai India New Prince Shri Bhavani College Of Engineering And Technology Tamilnadu India M S Ramaiah Institute Of Technology Msr Nagar Msrit Post Bangalore India

ISBN: (纸本)9798350305418

The Low-Carbon Economy (LCE) is an all-encompassing topic that combines economic, social, and environmental concerns with technological ones. It encompasses the ideas of low-carbon industry, low-carbon technology, low-carbon energy, low-carbon consumption, and carbon sinks. The expansion of LCE in India is hampered by a number of causes, one of which is India's illogical industrial structure, which is also an important component. As a result, the bPNN (bP neural network) technique is utilized in this study in order to construct the LCE development level model. First, an index system for controlling total carbon emissions should be created for LCE development. Next, an evaluation method that is based on the bPNN model should be developed. Examine the precision of the second generation prediction model by applying the test sample set to it, and continue this process until you have gotten the final prediction model that satisfies the convergence conditions. The findings of the research indicate that the maximum error that can occur between the actual output value of bPNN and the expected output value of bPNN is 8.36%, and the error is less than 10%, which indicates that the training results of the bPNN evaluation model constructed in this paper are good, and the evaluation results obtained are quite satisfactory. © 2023 IEEE.

关键词： bP neural network Index system Low carbon economy

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LoRaWAN and biosensor-Assisted smart City Framework to Mitigate the Effects of Lung Diseases

LoRaWAN and Biosensor-Assisted Smart City Framework to Mitig...

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Modeling, simulation & Intelligent Computing (MosICom), International Conference on

作者： K M Abubeker Michaelraj Kingston Roberts C Prajitha s Rinesh A shafeena Karim s. Jeevanandham Department of Electronics and Communication Engineering Amal Jyothi College of Engineering (Autonomous) Kerala India Department of Electronics and Communication Engineering Centre for Advances in Signal Processing and Wireless Sensor Networks Sri Eshwar College of Engineering Coimbatore India Department of Electronics and Communication Engineering Centre for Interdisciplinary Research Karpagam Academy of Higher Education Coimbatore India Department of Computer Science and Engineering V.S.B College of Engineering Technical Campus Coimbatore India Department of Information Technology Sri Ramakrishna Engineering College Coimbatore India

ISBN: (数字)9798331533311

ISBN: (纸本)9798331533328

Urbanization and industrialization in cities present substantial obstacles to air quality, resulting in detrimental effects on public health, including respiratory health. This research introduces an Internet of Things (IoT) framework for a smart city environment using LoRaWAN and sensor networks. The framework utilizes the EsP32 LoRaWAN module to provide real-time monitoring of essential air quality metrics, such as carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, and humidity. Integrating biosensors enhances accuracy by identifying distinct biological indicators linked to respiratory well-being. The proposed work aims to use the framework in an urban setting within a global context, demonstrating its capacity to reduce the effects of lung disorders. The EsP32 LoRaWAN module enables effective communication within the sensor network up to 20 kilometers, guaranteeing a robust and adaptable solution for smart city applications. The developed framework provides a scalable and novel method for developing healthier and more sustainable cities, decreasing respiratory disorders as urban settings develop.

关键词： Temperature sensors smart cities Pulmonary diseases LoRaWAN Air quality Real-time systems biosensors Internet of Things Public healthcare Organic compounds

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Wireless Charging Technologies for Electric vehicles: state of the Art and Future Outlook

Wireless Charging Technologies for Electric Vehicles: State ...

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IEEE students' Conference on Electrical, Electronics and computer science (sCEECs)

作者： sarathkumar D b.K. Parrthipan Murugesan Manivel T. Jayakumar R subramani Rao s. sambooranalaxmi Department of Electrical and Electronics Engineering Tamil Nadu India Department of Mechanical Engineering Kamaraj College of Engineering and Technology Vellakulam Tamil Nadu India Department of Electrical and Electronics Engineering Karpagam Institute of Technology Coimbatore Tamilnadu India Department of Electrical and Electronics Engineering Nandha Engineering College Tamilnadu India Department of Electrical and Electronics Engineering V.S.B Engineering College Karur Department of Electronics and Communication Engineering PSR Engineering College Sivakasi Tamil Nadu India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

Wireless charging technology for electric vehicles (Evs) represents a significant advancement in the transition to sustainable transportation, offering a convenient and efficient alternative to traditional plug-in charging systems. This paper provides a comprehensive review of the state-of-the-art wireless charging techniques, with a focus on inductive power transfer (IPT), resonant inductive coupling, and emerging capacitive and magnetic resonance methods. Key components of wireless charging systems, including power electronics, coil design, alignment techniques, and communication protocols, are discussed. We also address the challenges related to efficiency, safety, standardization, and scalability, particularly in dynamic charging systems designed for highway applications. The paper further explores the integration of wireless charging into smart grids, considering the potential for vehicle-to-grid (v2G) applications and renewable energy sources. A comparative analysis of existing technologies and their readiness for widespread adoption is provided, alongside an outlook on future trends, including high-power charging, autonomous charging infrastructure, and advances in materials and control algorithms. The paper concludes by identifying research gaps and potential directions for innovation in wireless charging for Evs.

关键词： vehicle-to-grid Electric potential Technological innovation Inductive charging Dynamics Magnetic resonance Transportation Power electronics Inductive coupling vehicle dynamics

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Enhancing Wireless sensor Network Longevity and security: A Quad-LEACH Approach

Enhancing Wireless Sensor Network Longevity and Security: A ...

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Emerging Technologies in computer science for Interdisciplinary Applications (ICETCs), International Conference on

作者： J J Lohith s shreya J L Hamsa Priya Dept. of Computer Science and Engineering B.M.S. College of Engineering Bangalore India Dept. of Information Science and Engineering D.S.C.E. Bangalore India Dept. of Electronics and Telecommunications B.M.S. College of Engineering Bangalore India

ISBN: (数字)9798350372502

ISBN: (纸本)9798350372519

Researchers have increasingly focused on Wireless sensor Networks (WsNs) in recent years, recognizing their versatile applications. The primary focus within WsNs is enhancing network longevity for efficient resource utilization, coupled with a strong emphasis on security and authentication. This paper specifically delves into the implementation of Quad LEACH for homogeneous networks, aiming to substantially improve network lifetime, stability, and throughput. The proposed protocol achieves this by employing a cluster head selection process and integrating security and authentication measures between cluster heads in the Quad-LEACH routing protocol. The research addresses the integration of a security agent within WsNs using the Ns-2 tool, contributing to enhanced authentication. The implementation is carried out through the simulation software Ns 2, where the security agent is seamlessly combined with the WsN infrastructure. The objective of this research is to incorporate a reliable authentication and security agent into Ns-2 in conjunction with the LEACH protocol, which is the standard for wireless sensors networks (WsNs). The efficacy of the suggested methodology will be validated through simulated outcomes.

关键词： Wireless sensor networks Authentication Throughput stability analysis software Routing protocols software reliability

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An Advanced Learning based Diabetes Mellitus Prediction Using KNN 5

An Advanced Learning Based Diabetes Mellitus Prediction Usin...

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5th International Conference on IoT based Control Networks and Intelligent systems, ICICNIs 2024

作者： vikruthi, sriharsha Reddy singasani, Tejesh Ram Pavan Kumar M, v.T. spandana, K. Narasimha Raju, M. Raghavendra, Ch B v Raju Institute of Technology Narsapur Dept of CSE Telangana Medak502313 India Kakaraparti Bhavanarayana College Dept of Computer Science Andhrapradesh Vijayawada India Hyderabad Ghatkesar India Shri Vishnu Engineering College for Woman Dept of CSE Bhimavaram India Andhra Pradesh Guntur India

ISBN: (纸本)9798331518097

Diabetes Mellitus (DM) is one of the chronic diseases that variations in blood sugars may cause. If it is not identified in the early stages, this may lead to severe issues over health. Diabetes may cause many side effects to the human body. Thus, detecting and diagnosing in the early stages is very important. This paper uses the advanced learning model to detect diabetes mellitus using K-Nearest Neighbours (KNN) combined with other hybrid techniques. The quality and relevance of the input were improved by using various data preprocessing techniques and feature selection methods to solve missing value issues. The KNN in this scenario performed better because of its intelligibility and efficiency in classifying the DM to obtain predictive results. The performance of the proposed approach was analyzed using confusion matrix metrics, which show actual values and predicted values. The results show that the proposed approach outperforms the results based on the given dataset. © 2024 IEEE.

关键词： k-nearest neighbors

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Unlocking Efficiency in Agricultural supply Chains: A secure and Transparent Approach through blockchain Technology

Unlocking Efficiency in Agricultural Supply Chains: A Secure...

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Emerging Technologies in computer science for Interdisciplinary Applications (ICETCs), International Conference on

作者： J J Lohith s shreya J L Hamsa Priya Dept. of Computer Science and Engineering B.M.S. College of Engineering Bangalore India Dept. of Information Science and Engineering D.S.C.E Bangalore India Dept. of Electronics and Telecommunications B.M.S. College of Engineering Bangalore India

ISBN: (数字)9798350372502

ISBN: (纸本)9798350372519

supply Chain Management (sCM) involves orchestrating various processes that extend from acquiring raw materials to delivering finished products to end consumers. The key objectives of a proposed supply chain in agriculture, emphasizes information-driven processes, cost reduction, and customer impact. It creates a versatile system capable of managing the supply chain for diverse commodities within a country, while also addressing the crucial need for increased transparency and traceability in data throughout the chain of activities. In our proposed approach to agricultural supply chain management (sCM), the focus is on creating a secure, transparent, and traceable sCM. To achieve this, we leverage cutting-edge technologies like the Ethereum blockchain and the Interplanetary File system (IPFs). The resulting software is a Decentralized Application (DApp) that orchestrates a series of activities within the agricultural industry, using cryptocurrencies to establish a seamless and efficient supply chain management system. This software platform is fortified by the secure algorithms of blockchain, providing an added layer of reliability. Additionally, our application incorporates transparency and traceability, ensuring user-friendly functionality and making it more accessible for users.

关键词： supply chain management Costs supply chains software algorithms Decentralized applications software blockchains

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Machine Learning Algorithms for Robust software vulnerability Detection

Machine Learning Algorithms for Robust Software Vulnerabilit...

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2024 IEEE International Conference on Innovation and Novelty in engineering and Technology, INNOvA 2024

作者： bajantri, Gayatri Noorullah shariff, C. Department of Computer Science & Engineering BLDEA’s V.P. Dr. P.G. Halakatti College of Engineering Vijayapura Ashram Road Karnataka Vijayapur586103 India Department of AIML Ballari Institute of Technology and Management BallariJnana Gangotri Campus Near Allipur Karnataka Bellary583104 India

ISBN: (纸本)9798331505134

software flaws pose a serious risk to the dependability and security of computer systems and applications in a variety of industries. because they take a long time and are prone to errors, traditional techniques of finding these vulnerabilities—like human code reviews and static analysis tools—are frequently insufficient. In order to improve the precision, effectiveness, and scalability of vulnerability detection, this paper presents a thorough technique for creating a software vulnerability detection tool that uses machine learning (ML) methods. The tool uses machine learning (ML) to automatically evaluate code samples, find possible security holes, and give developers useful information. The suggested approach consists of multiple phases, such as gathering and preprocessing data, extracting features, training and assessing models, and integrating and deploying tools. To maximise detection performance, a variety of machine learning (ML) algorithms are investigated, such as logistic regression, decision trees, random forests, support vector machines, and deep learning models. The tool's ability to adjust to new threats is guaranteed by its feedback mechanisms and ongoing monitoring. With the help of this cutting-edge technique, software engineers and security experts will be able to detect and address flaws more effectively and automatically, strengthening software systems' defences against ever-changing cyberattacks. © 2024 IEEE.

关键词： Application programs

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LegalDb: Long distilbert for legal document classification 1

LegalDB: Long distilbert for legal document classification

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1st IEEE International Conference on Advances in Electrical, Computing, Communications and sustainable Technologies, ICAECT 2021

作者： bambroo, Purbid Awasthi, Aditi Department of Computer Science and Engineering B.M.S. College of Engineering Bengaluru India

ISBN: (纸本)9781728157900

Transformers have caused a paradigm shift in tasks related to natural language. From text summarization to classification, these models have established new state-of-the-art results on various general and closed domain tasks. Having said that, most of the popular transformer based models (bERT - bidirectional Encoder Representations from Transformers, DistilbERT, and RobERTa) face a limitation in terms of the content length they can accept. This is because the self-attention used by these models scales quadratically with the context sequence length. While this works well for short passages and questions, for longer documents this method fails to effectively capture both the local and global contexts. This shortcoming is underscored further for closed domain tasks like Legal Document classification, where the length of the documents can extend up to a couple of pages and which differ in their vocabulary from general English substantially. In this paper, a new architecture is proposed, where the concept of "long" attention is applied to a distilled bERT and then the model is pre-trained on legal-domain specific corpora. This helps combine a local windowed attention with task-motivated global attention, making the model contextually-aware for longer sequences. The proposed model is also able to outperform fine-tuned bERT and other transformer-based models at the task of legal document classification while also being faster. © 2021 IEEE

关键词： Text processing

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Non-Invasive Devices for Early Diagnosis of Oral Potentially Malignant Disorders: A Comparative Analysis 6

Non-Invasive Devices for Early Diagnosis of Oral Potentially...

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6th International Conference on Recent Trends on Electronics, Information, Communication and Technology, RTEICT 2021

作者： Hegde, Kratharth shenoy, Kedary Krishna, T. sooda, Kavitha Abhilash B.M.S. College of Engineering Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9781665435598

Oral potentially malignant disorders (OPMDs) combine an assortment of sores and conditions which show an increased danger for change to oral cancer. Early discovery and determination of such disorders are important to avoid malignant change. Globally, it was decreed to be the fifteenth most common cancer in 2012. Many advanced determination methods are used to detect, anticipate their progression, and to assess the risk of transformation. As a part of this study a detailed analysis of four non-invasive devices used to detect OPMDs has been conducted by analysing the studies performed by researchers and comparing their sensitivity and specificity. Despite the fact that the devices involved in this study have good sensitivity and specificity (as high as 80%) and are non-invasive in nature, they cannot replace the golden standard of biopsy. © 2021 IEEE.

关键词： Diseases

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