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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

共 1532 条记录，以下是271-280 订阅

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Audio Based Music Genre Classification using Convolutional Neural Networks Sequential Model 8

Audio Based Music Genre Classification using Convolutional N...

引用

8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Pasrija, Simran Sahu, Shubham Meena, Shweta Delhi Technological University Department of Software Engineering Delhi India

ISBN: (纸本)9798350334012

Music recommendation system has high demand in the modern world, and these types of systems recommend music according to music genres. the music combines lyrics and beautiful sounds, and lyrics can be in any language. thus, sound plays an essential role in defining the genres of all music written in different. therefore, the recognition of music genres is a challenging task. However, various studies have been found in this area that performed well. However, the performance of the system can be further increased. thus, the proposed research aims to identify the music genres with good performance. this study used GTZAN Dataset, which is a publicly available dataset. this dataset has ten classes and around 1000 samples for each category. this system used the Convolutional neural network (CNN) model to recognize the performance of the music genres recognition system. the CNN model has ten layers, eight dense and two dropout layers. the achieved accuracy by the proposed model is 98.30%. © 2023 ieee.

关键词： Music

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Review of Machine Learning Algorithms for Predictive Maintenance in Industrial Applications 8

Review of Machine Learning Algorithms for Predictive Mainten...

引用

8th international conference on Electrical, Mechanical and computer engineering, ICEMCE 2024

作者： Wu, Xiaohua He, Qingfei Zuo, Zhaoyang Xijing University School of Mechanical Engineering Shaanxi Xi'an China

ISBN: (纸本)9798331506230

Predictive maintenance (PdM) has gained increasing importance in modern industries due to its ability to anticipate equipment failures and extend asset life. By leveraging machine learning (ML) techniques, PdM systems can analyze large volumes of operational data, identify early signs of wear, and predict remaining useful life (RUL) more accurately than traditional methods. this review delves into the application of various ML algorithms in PdM, including artificial neural networks, support vector machines, clustering algorithms, and random forests. We discuss how these algorithms enhance the ability to detect anomalies, optimize maintenance schedules, and reduce unnecessary maintenance costs. Additionally, we evaluate the challenges associated with data quality, feature selection, and model interpretability in real-world PdM implementations. the paper also provides insights into future trends, such as the integration of deep learning and IoT technologies to enable real-time monitoring and dynamic maintenance strategies that can adapt to complex industrial environments. Overall, this review underscores the transformative potential of ML-driven predictive maintenance in achieving more efficient, cost-effective, and reliable industrial operations. © 2024 ieee.

关键词： Predictive maintenance

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SDN Enabled Big Data Analytics and Framework for Sensor Data of Vehicle Health, Safety and Monitoring System

SDN Enabled Big Data Analytics and Framework for Sensor Data...

引用

international conference on software engineering and computer systems (icsecs)

作者： Tanvir Ahmad Nor Syahidatul Nadiah Binti Ismail Abdullah Mat Safri Md. Arafatur Rahman Mohammad Sojon Beg M. Taher Bin Bakhtiar Faculty of Computing University Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia Faculty of Science and Engineering Unversity of Wolverhampton Wolverhampton UK Faculty of Mechanical and Automotive Engineering University Malaysia Pahang Al-Sultan Abdullah Kulliyyah of Pharmacy IIUM Kuantan Campus Kuantan Malaysia

Vehicular network enabled vehicle health, safety and monitoring system is gaining attention for its potential application while software defined network (SDN) is supporting vehicular communication for designing core of the network. Vehicular network emits enormous amount of data where most of them are sensor data and that amount of data required to undergo analyzed for productive output. there are two types of sensor data are used in vehicular network, vehicle sensor data (VSD) and infrastructure sensor data (ISD). Flow based SDN controller examines every packet of the network which is responsible of engagement of resources gravely. For vehicular health monitoring and safety applications, SDN doesn't required to check and analyze ISD. In this paper, a framework is proposed that promises to ignore ISD and only consider VSD for vehicle health, safety and monitoring applications. With this connections, this paper proposes big data module along with SDN controller and inside the big data module, a partitioner program is designed. the partitioner program categorize VSD and ISD on the basis of certain parameters like data payload, technology used, packet header and restrict RSD to be processed by SDN controller. A combiner program is designed that bind both VSD and ISD to fed to the application plane of system. Additionally, a big data analytics for vehicle health, safety and monitoring application is derived.

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Compact S-Band Low-Pass Filter with Enhanced Suppression using Inductive Compensated Resonators and BSF Feed Line 8

Compact S-Band Low-Pass Filter with Enhanced Suppression usi...

引用

8th international conference on Information Technology, InCIT 2024

作者： Phromloungsri, Ravee Chiawchanwattana, thanapat Srisawat, Somkuan Boonsivanon, Krittachai Sonasang, Somchat Chongcheawchamnan, Mitchai Udon Thani Rajabhat University Faculty of Technology Udon Thani Thailand Faculty Industrial Technology Nakhon Phanom Thailand Prince of Songkla University Department of Electrical Engineering Songkhla Thailand

ISBN: (纸本)9798350366303

this paper presents an innovative technique for designing a compact L-band and S-band microstrip low-pass filter (LPF) utilizing cascaded resonators with doubly inductive compensated coupled lines. the proposed design significantly enhances signal suppression in the transition and stopbands compared to conventional stub-based LPFs. A closed-form design equation is provided for ease of implementation. Simulation and experimental results for a 2.75 GHz cut-off frequency LPF demonstrate an insertion loss of less than 0.1 dB, return loss exceeding 24 dB, and suppression performance over 52 dB at 5.5 GHz. the compact size and superior suppression performance make this filter ideal for modern microwave systems. © 2024 ieee.

关键词： Low pass filters

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Edge Intelligence in IoT: Architecture and Applications 8

Edge Intelligence in IoT: Architecture and Applications

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Jewani, Kajal Abimannan, Satheesh Department of Computer Science and Engineering Maharashtra Mumbai India

ISBN: (纸本)9798350396638

this research survey presents a comprehensive analysis of IoT architectures that incorporate edge computing, examining their classifications, applications, and the challenges and limitations associated with their implementation. the survey also explores future directions and trends in IoT architectures that leverage edge computing, including 5G integration, artificial intelligence (AI), and machine learning (ML) advancements, edge virtualization, edge security, and improved interoperability. the research study highlights the potential of IoT architectures that utilize edge computing to address the challenges posed by traditional cloud-centric architectures while also acknowledging the key challenges and limitations that need to be overcome. By examining the current state of the field and emerging trends and technologies, this survey aims to provide a valuable reference for researchers, practitioners, and industry stakeholders working on the development and implementation of IoT solutions incorporating edge computing. © 2023 ieee.

关键词： Internet of things

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PyTPU: Migration of Python Code for Heterogenous Acceleration with Automated Test Generation 8

PyTPU: Migration of Python Code for Heterogenous Acceleratio...

引用

8th ieee/ACIS international conference on Big Data, Cloud Computing, and Data Science, BCD 2023

作者： Kundu, Arghya Nguyen, Uyen Trang York University Electrical and Computer Engineering Toronto Canada

ISBN: (纸本)9798350373615

software applications are increasingly built to take advantage of heterogeneous architectures as specialised hardware accelerators take centre stage in today's computing environment. Tensor processing units (TPUs), the latest hardware addition, have demonstrated orders of magnitude improvement in computing efficiency over CPUs and GPUs for heterogeneous deep learning applications. However, despite the trend of incorporating heterogeneity and specialization in hardware, the creation of heterogeneous applications is confined to a handful of engineers. We propose a framework called PyTPU that takes Python code written in the PyTorch framework as input and automatically migrates it to its TPU compatible counterpart with test behaviour preservation and increased performance. First, PyTPU generates unit test cases to ensure test behavior compatibility. Second, using the abstract syntax tree and a manually curated exhaustive knowledge base, PyTPU migrates the original code to its TPU compatible version. Finally, PyTPU ensures the migrated code is readable and maintainable by adding necessary comments and conforming to PEP8 standard if needed. We evaluated PyTPU on four real-world Python applications with TPU v2 kernels. On average the migrated heterogeneous code is 19.103% faster than the original code while safeguarding test behavior preservation. © 2023 ieee.

关键词： Python

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A Multi-view Fusion Method for Finger Vein Recognition 8

A Multi-view Fusion Method for Finger Vein Recognition

引用

8th international conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Li, Weishi Xu, Sihang Zhang, Miao Peng, Yong National University of Defense Technology College of Systems Engineering Changsha China Hunan First Normal University School of Computer Science Changsha China

ISBN: (纸本)9798350302455

With the wide application of biometrics and the development of multi-mode fusion, how to obtain more accurate recognition technology by combining multiple characteristic information needs to be solved. Based on the finger vein recognition technique, this paper proposes a multi-view method of high-dimensional feature layer fusion at the feature level by canonical correlation analysis, which can improve the accuracy of recognition results. the fusion method of finger veins and fingerprint was demonstrated in the experiment of two-stream network. the effectiveness of the multi-view fusion method has also been demonstrated on several common baseline data sets. the results presented are competitive with the most advanced results in the literature. © 2023 ieee.

关键词： Biometrics

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Fine-Tuned Convolutional Neural Networks for Tamil Handwritten Text Recognition 8

Fine-Tuned Convolutional Neural Networks for Tamil Handwritt...

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Dhivyaa, C.R. Nithya, K. Dharshini, R. Sudhakar, R. Kumar, K. Sathis Janani, T. Kongu Engineering College Computer Science and Engineering Erode India Kongu Engineering College Computer Technology Erode India Nandha College of Technology Computer Science and Engineering Erode India Bannari Amman Institute of Technology Computer Science and Engineering Sathyamangalam India Bannari Amman Institute of Technology Information Technology Sathyamangalam India

ISBN: (纸本)9798350396638

Tamil Handwritten Text Recognition is the process of identifying and transcribing handwritten Tamil characters into machine-encoded text. Due to variations in the style, stroke, and shape of characters, identifying handwritten text is a critical task. the recognition of Tamil handwritten characters is an essential step in many applications, such as digitizing historical Tamil documents, handwriting recognition in education, and Tamil language translation systems. the development of accurate and efficient recognition systems for Tamil handwritten characters can greatly benefit these applications and contribute to the preservation and dissemination of Tamil literature and culture. the fine-tuned Convolutional Neural Network (CNN) is proposed for the identification of Tamil handwritten text. the proposed approach involves the use of pre-trained CNN models and fine-tuning them on a dataset of Tamil handwritten characters. the dataset consists of a large number of images of individual Tamil characters, including various styles of handwriting. To assess the efficacy of the suggested method, various experiments are performed on optimizing the CNN model's hyper parameters, utilizing both grid search and random search approaches. the results proved that the grid search with CNN model yields better result to recognize the Tamil text from the images. © 2023 ieee.

关键词： Convolutional neural networks

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Response Time Analysis of An Automotive Use-Case Based Two-Level Mixed Criticality System 8

Response Time Analysis of An Automotive Use-Case Based Two-L...

引用

8th international conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Wang, Tianyu Zou, Yuan Zhang, Xudong Wu, Ziyan Cai, Zhijia Zhang, Yiwei Beijing Institute of Technology Department of Automotive Engineering Beijing China

ISBN: (纸本)9798350302455

the evolution of information technology and the tendency of more functionality-centralized controllers has made it possible to schedule tasks with different criticality within the same computing platform on automotives. Unfortunately, a huge gap still remains between academic study of the mixed criticality system and automotive practice. To address the issues when applying the traditionally popular mixed criticality models to practice, an automotive use-case mixed criticality model is proposed. By adopting response time analysis of fixed priority scheduling technique, an implementation of AUB-MCS is accomplished and effectiveness are proved with schedulability test evaluation. © 2023 ieee.

关键词： Response time (computer systems)

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Blockchain-Enabled Secure Communication for Autonomous Vehicles 8

Blockchain-Enabled Secure Communication for Autonomous Vehic...

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8th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Khanpara, Pimal Kathiria, Preeti Patel, Usha Athreya, Deekshita Nirma University Department of Computer Science and Engineering Ahmedabad India

ISBN: (纸本)9798350376425

this research study introduces an innovative Vehicle-to-Everything (V2X) communication system utilizing Ethereum blockchain and Solidity smart contracts. the proposed approach transcends conventional vehicular communication systems by integrating the inherent security and transparency of blockchain technology. this integration aims to revolutionize V2X interactions, encompassing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, ensuring enhanced security, reliability, and immutability of data exchanged in urban traffic environments. the foundation of our system is a strong Solidity smart contract deployed on the Ethereum blockchain. this contract orchestrates the V2X communication, providing a decentralized and tamper-proof platform for transmitting and receiving data across various urban traffic entities. the practical application of this system is demonstrated through simulations in an urban environment created in Netedit, with various traffic scenarios evaluated using the Simulation of Urban Mobility (SUMO) software. © 2024 ieee.

关键词： Ethereum

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