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检索条件"机构=dept. of Computer Computer Systems Engineering"

共 66560 条记录，以下是411-420 订阅

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A Survey On Various Smart Car Parking systems 3

A Survey On Various Smart Car Parking Systems

引用

3rd International Conference for Innovation in Technology, INOCON 2024

作者： Naik, Vishal Borkar, Vijayan Kumar, K.M. Chaman Shetgaonkar, Pratiksha Srieit Goa University Dept. of Computer Engineering Goa India

ISBN: (纸本)9798350381931

The never-ending challenge of finding a place to park in cities with traffic jams and inefficiency is a daily cause of annoyance. Using cutting-edge algorithms, smart car parking systems show promise as a solution to reduce the stress involved with parking in cities. This survey research illuminates the ongoing difficulties experienced by city people by thoroughly examining the intricate and subtle aspects of modern parking concerns. The ultimate goal is to provide a succinct yet comprehensive comparison of the diverse algorithms employed in smart car parking systems, aiming for improvements in terms of smart car parking management. © 2024 IEEE.

关键词： Traffic congestion

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GnBERT: Graph Neural Networks over BERT for Knowledge Graph Representation Learning 15

GnBERT: Graph Neural Networks over BERT for Knowledge Graph ...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Vidhate, Hutesh Khobragade, Anish COEP Technological University Dept. of Computer Engineering Pune India

ISBN: (纸本)9798350370249

Many disciplines depend on knowledge graphs to represent and arrange organized data. Nevertheless, understanding knowledge graphs is still quite difficult because of their intricate relationships and great importance. The work develops a new framework named GnBERT by fusing Bidirectional Encoder Representations from Transformers (BERT) with Graph Neural Networks (GNNs). Knowledge graph representations are able to be obtained via this approach. Graph Neural Networks (GNNs) provide relational semantics;GnBERT improves the representation of entities and relationships in knowledge graphs by combining the hierarchical structure of BERT's pre-trained language model with it. We have shown, using benchmark datasets, that GnBERT achieves the best degree of performance in knowledge graph completion, entity linking, and connection extraction over earlier techniques. © 2024 IEEE.

关键词： Knowledge graph

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Automail AI: Intelligent Voice-Controlled Email Generator 3

Automail AI: Intelligent Voice-Controlled Email Generator

引用

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Jayaram, Kavitha Mandagere, Samarth Gopisetti, Sampriti Sahit, S. Bnm Institute of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331515911

The complexity of contemporary communication further emphasizes the need to automate monotonous work to increase efficiency and effectiveness. This paper introduces a new advance, voice-controlled Automail AI, in the form of an email generation tool that automatically sends an email according to end-user-specified keywords. Automail AI utilizes NLP, ML, and Speech Recognition to differentiate formal emails from informal ones and draft appropriate responses as the situation demands. It has been tuned with Naive Bayes Classifier that yields a better level of accuracy as compared to models such as Decision Tree, SVM, and Logistic Regression. Setting the benchmark for Automated Communication tools, Automail AI combines diverse technologies like SMTP to guarantee secure Email delivery, Google Text-to-Speech or GTTS for auditory feedback, and a module providing an interface for speech recognition that offers the possibility to use the tool with no hands. © 2025 IEEE.

关键词： Automail AI email generation GTTS machine learning Naive Bayes natural language processing SMTP speech recognition

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Iraqi Legal GPT 21

Iraqi Legal GPT

引用

21st International Multi-Conference on systems, Signals and Devices, SSD 2024

作者： Mustafa, Mustafa Samir Abdulfatah, Mustafa Basim Abdulkareem, Husain Alaa Ashir, Abubakar M. Tishk International University Dept. of Computer Engineering Erbil Iraq

ISBN: (纸本)9798350374131

This paper proposes and develops a small language model artificial intelligence (AI) system or chatbots capable of providing competent legal information to users within the Iraqi legal jurisprudence. One of the major contributions of the papers is addressing critical challenges related to the current Large Language Model (LLM) like ChatGPT of their enormous size and lack of localized knowledge of internal processes and lifestyles. The proposed model provides low latency time with limited economic resources and the availability of efficient legal professionals for understanding the legal and rights requirements of individuals within the Iraqi region which can be run on a local computer without an internet connection. The research leverages the open source h2ogpt as a backbone language model and was trained with aggregated and curated legal documents from the Iraqi legal system. This approach allows users to input questions, and through the aid of Embedding algorithms and Vector Store algorithms, the data is stored and converted into a machine-readable format for subsequent comprehension and processing by the computer. The findings indicate a promising foundation for the project, featuring a user-friendly interface (UI) and an updateable back-end to accommodate future enhancements. The system achieved a noteworthy 1-minute response time with an accuracy rate of 80%. Notably, the development objectives aimed to establish a locally deployable system that is easily accessible and modifiable to address evolving challenges in the current computational era of information dissemination. © 2024 IEEE.

关键词： Information dissemination

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Adaptive Kalman Filter Based LiDAR aided GNSS/IMU Integrated Navigation System for High-Speed Autonomous Vehicles in Challenging Environments

Adaptive Kalman Filter Based LiDAR aided GNSS/IMU Integrated...

引用

2024 International Technical Meeting of The Institute of Navigation, ITM 2024

作者： Lee, Jae-Un Won, Jong-Hoon Dept. of Electrical and Computer Engineering Inha University Korea Republic of

ISBN: (纸本)9780936406367

This paper presents an advanced localization method for autonomous vehicles using an adaptive Kalman filter integrated with LiDAR-aided GNSS/IMU systems, addressing the challenges of GNSS reliability and precision in urban high speed driving scenarios. This approach combines multiple sensors, including GNSS, IMU, and LiDAR, with adaptive estimation method to enhance the accuracy of position estimation. The adaptive Kalman filter effectively counters the limitations of GNSS by employing fault detection and exclusion and utilizing LiDAR-based localization method for real-time correction in case of GNSS errors. Experiments conducted with generated critical GNSS errors in a test vehicle driving in urban environments, demonstrate the improved reliability and accuracy in false alarm detection and position estimation of the system. This research contributes to autonomous driving technology, offering a robust solution for precise localization in dynamic urban environments, and is adaptable to a wide range of unmanned mobility systems, signifying a considerable advancement in the field of autonomous navigation. © 2024, Institute of Navigation

关键词： Autonomous vehicles

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A Comprehensive Survey of Face Recognition Advancements 8

A Comprehensive Survey of Face Recognition Advancements

引用

8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Mane, Sunil B. Shah, Nisarg Garje, Vaibhav Tejwani, Aman Coep Technological University Dept. of Computer Engineering Pune India

ISBN: (纸本)9798350391770

Face recognition technology has experienced significant advancements in recent years due to the rapid progress in deep learning techniques. The purpose of this comprehensive literature review is to examine the various applications and underlying methodologies of face recognition. With recent advancements in face recognition techniques, a wider range of scenarios and challenges can be addressed. In this survey, we explore the latest developments in face recognition, including pitch variations, lighting changes, occlusions, and varied environments. The survey provides a comprehensive review of face recognition technology, covering applications, methodologies, dataset usage, model accuracy, and workings. Additionally, it analyzes three main approaches to face recognition for static images: traditional (or classical), deep learning-based, and hybrid. Hence, providing an overview of and comparing some of the popular face recognition approaches and techniques is the main objective of this paper. © 2024 IEEE.

关键词： Contrastive Learning

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Decomposition Algorithm for Security-Constrained Unit Commitment with AC Optimal Power Flows

Decomposition Algorithm for Security-Constrained Unit Commit...

引用

2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Renl, Weihang Li, Mingze Fan, Lei Guan, Yongpei University of Florida Dept. of Industrial and Systems Engineering FL United States University of Houston Dept. of Electrical and Computer Engineering TX United States University of Houston Engineering Technology TX United States

ISBN: (纸本)9798331541125

This paper presents a comprehensive approach to solving the security-constrained unit commitment with alternating current power flows (SCUC-ACPF) problem in contemporary power systems. We introduce algorithms that decompose the problem into subproblems suitable for specialized solvers, so that the large-scale mixed-integer nonlinear program-ming SCUC-ACPF problem can be solved. In case studies, we validate the efficiency and effectiveness of our algorithms on synthetic and industry-scale power system networks. © 2025 IEEE.

关键词： Lagrange multipliers

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A Secure method of transferring confidential documents by leveraging Zero Trust Principles and Blockchain Technology 4

A Secure method of transferring confidential documents by le...

引用

4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Alex, Hannah Thankam Alex, Sarah Swathi, C.G. Chavan, Chandrashekhar Pomu Pes University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331518981

Ensuring regulatory compliance and maintaining client trust in the legal industry depend on the safe transfer and preservation of sensitive data. Maintaining the safety and security of confidential information is essential in a law business. The suggested concept combines zero-trust concepts with blockchain technology to develop a decentralized application (dApp) that facilitates secure document sharing between clients and law firms. To guarantee the safe transfer of private legal documents, the platform makes use of IPFS for decentralized file storage and MetaMask for authentication. OTP verification, document encryption using cryptographic methods, and MetaMask user authentication are some of its key features. Only authorized users are able to view or manage documents in the DApp thanks to smart contract access management. The requirements for security, immutability, and transparency are maintained by this method. © 2024 IEEE.

关键词： Smart contract

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A Computationally-efficient Semi-supervised Learning Model for the Estimation of State Degradation of a Milling Tool 22

A Computationally-efficient Semi-supervised Learning Model f...

引用

2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics, SAMI 2024

作者： Sharifirad, Iman Boudjadar, Jalil Aarhus University Dept. of Electrical and Computer Engineering Aarhus Denmark

ISBN: (纸本)9798350317206

This paper proposes a computation-efficient semi-supervised machine learning model for the near-to-real-time state of health estimation for a Milling tool. To secure high reliability of the health state estimation, we have adopted the two-stage classification Beta Variational Auto-Encoder (β-VAE) architecture. The computation efficiency is achieved through the correlation between the latent space and input space classification processes of β-VAE for healthy states, where the input space decoder classification is triggered only when the latent space classifies the state to be unhealthy. This can be seen as a double-check process due to the high cost related to processing the false-positive maintenance decisions. We have implemented the proposed model and tested it on the UC Berkeley milling data set. The experiment results show that our state of health estimation model can reduce the computation cost by up to 15% while achieving high classification accuracy. © 2024 IEEE.

关键词： Signal encoding

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Latency Analysis of In-Vehicle Network for Advanced Driver Assistance System 100

Latency Analysis of In-Vehicle Network for Advanced Driver A...

引用

100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Park, Hanyoung Cho, Minji Jang, Yongjae Choi, Ji-Woong Dept. of Electrical Engineering & Computer Science Daegu Korea Republic of

ISBN: (纸本)9798331517786

Considering the advancements in autonomous driving technologies, the necessity for an advanced driver assistance system (ADAS) to incorporate a multitude of sensors for enhanced precision has become paramount. Consequently, the increase of sensors correlates directly with the escalation of autonomous driving capabilities. However, this escalation causes a larger volume of data traffic and an increase in the latency within the in-vehicle network (IVN). As the IVN latency increases, the overall latency of ADAS from the sensor to the actuator increases. This increased latency can affect the safety of ADAS. Hence, latency analysis for various sensors is required. In this paper, we struct Ethernet-based zonal architecture considered for future automotive architecture and analyze the factor of end-to-end latency for the safety-related ADAS with multi-type sensors, including IVN latency. © 2024 IEEE.

关键词： Advanced driver assistance systems

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