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检索条件"任意字段=International Conference on Advances in Science, Engineering and Robotics Technology"

共 47866 条记录，以下是1451-1460 订阅

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Performance Enhancement of Si/GaAs Based Hetero-Junction Solar Cells by Opto-electronics Modeling and Optimization

Performance Enhancement of Si/GaAs Based Hetero-Junction Sol...

引用

2024 international conference on Recent advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence, RAEEUCCI 2024

作者： Roy, Arijit Bardhan Valiji, Navaid Hussain Rasulji Mohammad, Rehan Giridhar, P. Mondal, Pratik SRM Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350354539

When it comes to renewable energy sources, solar photovoltaic (PV) technology is the most popular and extensively utilized. Thus, one of the key challenges in acknowledging photovoltaic technology as an archaic source of energy is raising the solar cell's efficiency. Because of this, one of the best methods to achieve high efficiency through enhancing open circuit voltage and electron hole pair creation throughout a wide spectrum is through hetero-junction solar cells with suitable band gap tuning. This article focuses on the design and analysis of Si-GaAs based hetero-junction solar cells using PC1D software to optimize opto-electronics parameters such as material thickness and doping profile, resulting in an efficiency of over 20%. © 2024 IEEE.

关键词： Gallium arsenide

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OCTNet: Leveraging VGG16 for Automated Classification of Retina Health from OCT Scans 1

OCTNet: Leveraging VGG16 for Automated Classification of Ret...

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1st international conference on Pioneering Developments in Computer science and Digital Technologies, IC2SDT 2024

作者： Shourie, Poonam Anand, Vatsala Upadhyay, Deepak Devliyal, Swati Gupta, Sheifali Computer Science & Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Chitkara University Institute of Engineering and Technology Chitkara University Electronics and Communication Engineering Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to be University Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350365016

The healthy vision is seriously threatened by retinal diseases include drusen, diabetic macular edoema, and choroidal neovascularization (CNV). Immediate identification and treatment are essential to reducing their effects and retain healthy lives. In this work, model provide a deep learning method based on the VGG16 architecture for the automatic identification of retinal injury using a dataset of retinal OCT (optical coherence tomography) pictures. retinal OCT images into these four categories by preprocessing the images and training a VGG16 convolutional neural network (CNN) model. The retinal OCT dataset is used to fine-tune the pretrained VGG16 model, which is well-known for its efficiency in image classification tasks, so that it can adjust to the unique properties of retinal pictures. By means of comprehensive testing, the model assesses the accuracy performance of the proposed model across several epochs. The suggested model improves validation accuracy from 87.89% to 92.01% and training accuracy from 97.22% to 100%. The findings show that the VGG16-based method is helpful in accurately detecting retinal abnormalities, providing ophthalmologists with a possible tool to help them diagnose retinal illnesses quickly and reliably. By offering a dependable and automated technique for identifying retinal damage from OCT pictures, this work advances computer-aided diagnosis tools for retinal illnesses and eventually advances early intervention and better patient outcomes and hence improve quality of life. © 2024 IEEE.

关键词： Ophthalmology

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Detection of Thyroid Diseases Using Deep Learning 2

Detection of Thyroid Diseases Using Deep Learning

引用

2nd IEEE international conference on advances in Information technology, ICAIT 2024

作者： Archana, P. Suhana Anjum, S. Keerthana, S.M. Srusti, P.D. Department of Computer Science and Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India

ISBN: (纸本)9798350383867

Thyroid diseases, including hypothyroidism, hyperthyroidism, thyroiditis, nodules, cancer, and euthyroid disease, are serious health problems that require accurate and timely diagnosis and treatment. This article presents a new method that specifically uses deep learning in convolutional neural networks (CNN) to successfully classify thyroid disease based on X-ray and ultrasound images. Our method, which uses CNN principles and data such as x-ray and ultrasound containing multiple thyroid images, is effective in classifying diseases. Thanks to a careful pre-processing, optimization and elimination process, our CNN model achieved an accuracy of 97.92%, demonstrating its potential as an important diagnostic tool. Early diagnosis and treatment of thyroid disease. © 2024 IEEE.

关键词： Ultrasonic imaging

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Ensemble of Vision Transformers and CNNs for Accurate Diabetic Foot Ulcer Classification 1

Ensemble of Vision Transformers and CNNs for Accurate Diabet...

引用

1st IEEE international conference on Cognitive robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Pagadala, Arnold Anand Silas, Salaja Joy, Emmanuel Karunya Institute of Technology and Sciences Division of Computer Science Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Artificial Intelligence and Machine Learning Coimbatore India

ISBN: (纸本)9798350372748

Diabetic Foot Ulcers (DFU) are a significant diabetes complication that can lead to lower limb amputation. Currently, 537 million suffer from diabetes worldwide and it is anticipated to rise to 783 million by 2045. Given the speed at which DFU is developing, prompt action is necessary to avoid the serious consequences of amputation and associated various medical conditions. With the evolution of image-based ML algorithms, automated methods for identifying and assessing DFUs are becoming more common. Existing research works on visual computing techniques concerns tissue classification and detects the DFU's visual appearance. This research study combines ResNet50 with Vision Transformers (ViT) and MobileNet with Vision Transformers (ViT) to develop an ensemble model to classify the existence or absence of a Diabetic Foot Ulcer (DFU). Experimental results of the proposed model when tested on challenging datasets achieved a validation accuracy of 98.6%. © 2024 IEEE.

关键词： Neural networks

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An Efficient Prediction System for Heart Diseases Using Machine Learning Algorithms 2

An Efficient Prediction System for Heart Diseases Using Mach...

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2nd IEEE international conference on advances in Information technology, ICAIT 2024

作者： Archana, P. Shashikala, S.V. Department of Computer Science and Engineering BGS Institute of Technology Adichunchanagiri University BG Nagara Mandya India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383867

One of the most severe and demanding conditions that the arena is currently facing is heart illness. Forecasting cardiovascular illness is one among the most challenging pursuits in the world of medical facts analysis. Machine learning classification algorithms has been shown to be useful in making predictions and options that are solely dependent on substantial amounts of data. This study offers a technique to predict and classify if a person has coronary heart disease and to inform the affected individual about their risk through records or a diagnosis. The prediction version is built using a variety of options and numerous additional classification techniques. This is accomplished by comparing the accuracy of many algorithms to the outputs of each version independently, then choosing the method with the highest forecast accuracy. This paper's main goal is to use data analytics to predict whether or not contamination will persist for the foreseeable future. © 2024 IEEE.

关键词： Prediction models

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Artificial Intelligence in Next Generation IoT Infrastructure: Challenges and Opportunities 1

Artificial Intelligence in Next Generation IoT Infrastructur...

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1st international conference on advances in Computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Arabelli, Rajeshwarrao Chotaliya, Dhwanit K. Gadhave, Rajashree Tukaram Haritha, B. Kasireddy, Lakshmi Chandrakanth Soni, Mukesh School of Engineering SR University Department of Electronics and Communications Engineering Warangal India GEC-Rajkot Department of Instrumentation and Control Engineering Gujarat Rajkot360005 India Pillai HOC College of Engineering and Technology Rasayani Tal. Khalapur MH 410207 India St. martin's Engineering College Department of ECE Hyderabad India ThoughtSpot Inc Enterprise DevSecOps Architect R&D - Engineering FranklinTN United States Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Pune India

ISBN: (纸本)9798331518578

Numerous facets of the public realm could be revolutionised by the convergence of the Internet of Things (the Internet of Things) and Artificial Intelligence (AI). This project developed a based-on data predictive maintenance system for manufacturing production lines. One of these anticipated improvements that can be included into the factory's production system is 'AI of Things (AIoT),' which refers to the use of the IoT to carry out intelligent tasks with the aid of AI integration. By using the information created by IoT sensors progressively, the system utilizes machine learning (ML), a part of AI, to recognize expected blunders preceding they happen. The viability of the innovation was surveyed utilizing IoT information from genuine assembling frameworks, and the results of the appraisal demonstrated that the prescient support structure was effective in distinguishing potential failure indicators and could assist with forestalling some production stops. Comparing the performance of ML techniques revealed that frameworks of the bagging ensemble technique Random Forest and the boosting technique XGBoost appeared to outperform each of the techniques in the assessment. The factory's production system now uses the best-performing ML techniques from the present research. © 2025 IEEE.

关键词： Predictive maintenance

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Research on Vehicle Lane Change Prediction Considering Driver’s Behavior 3

Research on Vehicle Lane Change Prediction Considering Drive...

引用

3rd international conference on Control and Intelligent robotics, ICCIR 2023

作者： Lijiale, Su Jiangtian, Li School of Automotive Engineering Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781510671867

Accurate prediction of vehicle lane-change behaviour is beneficial for traffic efficiency and safety. This paper incorporates driver behavioural information indicators into the prediction of lane change behaviour. A driving simulator was used to collect driver behavioural characteristics and vehicle operating parameters during lane keeping and lane changing, and through theoretical analysis and data testing, seven indicators were obtained that could be used to predict lane changing behaviour: target area gaze time, head level turning angle, vehicle speed, lane drift angle, distance to the vehicle in front, and time to collision. Using the experimentally collected variable data, a logistic prediction model was developed and validated to have satisfactory prediction accuracy. © 2023 SPIE.

关键词： Eye movements

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Cross-Lingual Transfer Learning in RNNs for Enhancing Linguistic Diversity in Natural Language Processing

Cross-Lingual Transfer Learning in RNNs for Enhancing Lingui...

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2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Tiwari, Shikha Babu, Ch. Meher Shanker, P. Shahnaz, K.V. Roy, Vandana Kashyap, Ramgopal Amity University Raipur India Potti SriRamulu Chalavadi Mallikarkuna Rao College of Engineering and Technology Vijayawada India Cvr College of Engineering Dept. of Cse Hyderabad India Veltech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Dept. of Ece Chennai India Ggits DoEC Jabalpur India Amity University Chhattisgarh India

ISBN: (纸本)9798350388800

In addition to removing biases, these findings reveal a comprehensive method for improving cross-lingual transfer learning in NLP, which in turn makes language more diverse. This approach was created as a result of this effort. In order to construct the system utilizing these methodologies, five fundamental procedures are followed. One approach that falls under this category is MTI, which stands for Multilingual Embedding Adaptation and is used for Machine Translation-based Initialization. Ethical Bias Mitigation, Linguistic Feature Alignment, and Recurrent Neural Network Adaptation are some supplementary methods. Developing each strategy to address the wide variety of issues that may arise during cross-lingual transfer learning required considerable deliberation. Starting with translated data, the MTI algorithm aligns the source and target language embeddings, the RNA algorithm aligns RNN structures, the LFA algorithm aligns linguistic characteristics, and the EBM method lowers biases fairly. The desired outcomes are attained by employing all these techniques. The outcomes of ablation research demonstrated the significance of each approach and their interdependence in ensuring the system's functionality. The framework provides a comprehensive strategy for increasing the linguistic diversity of natural language processing (NLP) models to accommodate individuals from varying cultural backgrounds and language abilities. Issues of social justice and equity receive substantial consideration within the framework. © 2024 IEEE.

关键词： Contrastive Learning

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Blockchain in Higher Education: Key Research Themes and Future Directions

Blockchain in Higher Education: Key Research Themes and Futu...

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2023 international conference on Recent advances in science and engineering technology, ICRASET 2023

作者： Srivastava, Anugamini Priya Yadav, Mohit Khurana, Rahul Balodi, Arun Vihari, Nitin Simha Symbiosis International Deemed University Symbiosis Institute of Business Management Pune India Op Jindal Global University Jindal Global Business School Sonipat India Indian Institute of Technology Roorkee Department of Management Studies Roorkee India Dayananda Sagar University Department of e & C Engineering Bengaluru India Middlesex University Dubai Dubai United Arab Emirates

ISBN: (纸本)9798350306927

This research paper explores the applications of blockchain technology in higher education, focusing on areas where it can bring transformative changes. The study addresses research gaps by conducting a comprehensive bibliometric analysis to understand the overall research landscape, specific applications, and challenges of blockchain in higher education. The findings provide insights into publication trends, influential contributors, and emerging research directions. The study highlights the potential of blockchain in areas such as credentials and certificates, record-keeping, micro-credentials, payments, research, and data management. This research contributes to advancing knowledge by guiding future research directions and facilitating the integration of blockchain technology in higher education systems. © 2023 IEEE.

关键词： Blockchain

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Line Fitting-Based Corner-Like Detector for 2D Laser Scanners Data∗ 10

Line Fitting-Based Corner-Like Detector for 2D Laser Scanner...

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10th international conference on Automation, robotics, and Applications, ICARA 2024

作者： Sousa, Ricardo B. Sobreira, Heber Miguel Silva, Manuel F. Moreira, Antonio Paulo University of Porto Faculty of Engineering Porto4200-465 Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal ISEP Polytechnic of Porto R. Dr. António Bernardinode Almeida Porto4249-015 Portugal

ISBN: (纸本)9798350394245

The extraction of geometric information from the environment may be of interest to localisation and mapping algorithms. Existent literature on extracting geometric features from 2D laser data focuses mainly on detecting lines. Regarding corners, most methodologies use the intersection of line segment features. This paper presents a feature extraction algorithm for corner-like points in the 2D laser scan. The proposed methodol-ogy defines arrival and departure neighbourhoods around each scan point and performs local line fitting evaluated in multiple distance-based scales. Then, a set of indicators based on line fitting error, the angle between arrival and departure lines, and consecutive observation of the same keypoint across different scales determine the existence of a corner-like feature. The experiments evaluated the corner-like features regarding their relative position and observability, achieving standard deviations on the relative position lower than the sensor noise and visibility ratios higher than 75% with very low false positives rates. © 2024 IEEE.

关键词： Feature extraction

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