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Towards TDD for FPGAs

Towards TDD for FPGAs

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2024 IEEE international Multi-conference on engineering, computer and Information Sciences, SIBIRCON 2024

作者： Staroletov, Sergey Institute of Automation and Electrometry Cyber-physical lab Novosibirsk Russia

ISBN: (纸本)9798331532024

The TDD (Test-Driven Development) methodology suggests an alternative approach to software production, advising to start the development by writing not code but tests. The approach was proposed by Kent Beck back in 2003, but there are still disputes in software engineering community about the feasibility of developing using this way. In our opinion, the applicability of methodology is hampered by the lack of explicit support from IDEs. In 2018, Ron Wilson from Intel raised the question on the relevance of this methodology to FPGA-based hardware systems development. With the current progress in the field of IoT, the demand is growing for the evolution of signal processing co-processors, devices dedicated to various purposes, neural processors, which is most efficiently implemented using FPGAs. However, the threshold for entry into the development is still high here, including the unusualnesses of the development tools. In this paper, we assume that the support for TDD at the IDE level, especially in the combination of visualized tools, taking into account the specifics of hardware development, will radically increase both the development speed and quality. We pay attention to the drawbacks of the Quartus Prime' IDE from Intel and Altera. Having some background primarily in software development, we offer options for their elimination and demonstrate the approach both on toy examples and a real case study of playing music from an SD card. © 2024 IEEE.

关键词： Software testing

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A Novel Machine Learning-Based Approach for Analysis, Prediction and Prevention of Accidents on Indian National Highways 7

A Novel Machine Learning-Based Approach for Analysis, Predic...

引用

2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Deshpande, Anjali Tribhuvan, Vinit Pune Institute of Computer Technology Department of Computer Engineering Pune India Coep Technological University Department of Computer Engineering Pune India

ISBN: (纸本)9798350304268

Road traffic safety is a matter of crucial concern for the government as well as citizens. Despite all the measures taken to promote road traffic safety in India, there are a lot of regions of vulnerability. This leads to the need of an effective analysis to subdue alarming figures by significant amount. In an attempt to address this problem, we apply statistical analysis and data mining algorithms for analysis, prevention and prediction of road accidents on Indian national highways. To enhance the process of road risk analysis, proposed system puts forth an idea of analyzing the National Highways Authority of India (NHAI) datasets using Hidden Markov Model (HMM) and regression model supported by fuzzy classification. Our proposed system also has an alert module to provide an alarm and also some suggestions to the user through SMS depending upon the travel route. The implementation results indicate that the proposed method yields an accuracy of 84.55% approximately. © 2023 IEEE.

关键词： Baum-Welsh algorithm data mining fuzzy classification Hidden Markov Model (HMM) machine learning regression

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A multi-fault diagnosis method based on the fusion of time-space information 7

A multi-fault diagnosis method based on the fusion of time-s...

引用

7th international conference on computer Information Science and Application Technology, CISAT 2024

作者： Zhou, Bingjing Shanghai Maritime University Logistics Engineering College Electrical Engineering and Automation Pudong New Area Shanghai China

ISBN: (纸本)9798350375107

In industrial processes, equipment data are often characterized by dynamics, strong nonlinearity and strong coupling, which makes it difficult to achieve multi-fault diagnosis when multiple faults occur simultaneously. To solve this problem, this paper proposes a multi-fault diagnosis method based on time-space information fusion. The method is realized by designing a time-space information fusion model and combining it with the contribution graph method. Firstly, the Euclidean distance is used to mine the information of the samples in the time direction;then, the spatial features are extracted from the mined temporal information to achieve the time-space information fusion;and finally, the fault variables are identified by combining with the contribution graph method to achieve the multi-fault diagnosis. Verified by numerical cases and actual data from the equipment of an inlet lift pump room of a wastewater treatment plant in Shanghai, the time-space information fusion model can effectively extract and use time-space information to separate fault samples, and the subsequent diagnostic results can accurately locate the fault variables. © 2024 IEEE.

关键词： Information fusion

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Revealing security vulnerabilities of chinese local government websites through topology analysis and knowledge graph 3

Revealing security vulnerabilities of chinese local governme...

引用

3rd international conference on Electronic Information engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Xie, Jiagui Zuo, Ming Cheng, Yanan Zhang, Zhaoxin School of Automation Beijing Institute of Technology Beijing China Harbin Institute of Technology Harbin China

ISBN: (纸本)9781510680449

As the Internet evolves, governments worldwide, including China, are digitalizing their services. However, in China, the technical disparity among local government websites is significant due to the vast number of local governments, their geographic spread, and varying regional economies. This disparity leads to considerable security risks. Our study involved topological analysis and knowledge graph construction to evaluate these websites, uncovering numerous security vulnerabilities such as data leaks, unauthorized access, and code execution. These findings highlight critical gaps in security measures. Knowledge graphs were instrumental in visualizing and analyzing these vulnerabilities and devising resolution strategies. This approach not only facilitates prompt identification and rectification of issues but also supports the development of robust long-term security strategies. Moreover, it serves as an educational tool for local government technical teams to learn and implement security best practices. Our analysis offers valuable insights and guidance for enhancing the security of Chinese local government websites, aiming to strengthen data and information protection for citizens. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Knowledge graph

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Exploring Large Scale Docker Image Vulnerability and Storage Performance Analysis Using High Performance Container-Based Docker Environment

Exploring Large Scale Docker Image Vulnerability and Storage...

引用

2024 international conference on System, Computation, automation and Networking, ICSCAN 2024

作者： Kavya Sri, B. Mahalakshmi, K. Anna University Faculty of Information and Communication Engineering Chennai India Kit - Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798331510022

In modern cloud environments, Docker containers have become a cornerstone for efficient application deployment, enabling microservices architectures and seamless scalability. However, large-scale Docker environments present significant challenges, particularly in terms of security vulnerabilities and storage performance. This paper explores vulnerability analysis and storage performance optimization in high-performance, container-based Docker environments. Docker swarm is a container orchestration platform which could be very useful for maintaining the docker containers at scale even at distributed environment, these tools also provide us a great features for managing the rolling updates and health check in the lifecycle of containers. We perform a comprehensive evaluation of Docker image vulnerabilities using automated scanning tools, assessing common vulnerabilities and exposures (CVEs) across large image repositories. Additionally, we investigate storage performance bottlenecks and analyse the impact of various storage drivers on container efficiency. Our findings offer critical insights into balancing performance and security in high-scale Docker deployments, proposing strategies for mitigating risks and enhancing resource management. The results guide container orchestration decisions for enterprises aiming to deploy secure, high-performance systems. © 2024 IEEE.

关键词： Bottles

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引用

4th international conference on Consumer Electronics and computer engineering, ICCECE 2024

作者： Liu, Yajun Fan, Kefeng Wu, Dakui Zhou, Wenju School of Mechatronic Engineering and Automation Shanghai University Shanghai China China Electronics Standardization Institute Beijing China

ISBN: (纸本)9798350384062

Filter pruning has become one of the driving forces behind the deployment of convolutional neural networks (CNNs) in mobile devices due to its effective compressibility and software and hardware universality. Existing pruning methods are based on analyzing the inherent parameters of the network model in the spatial domain and searching for the redundant parameters present. This approach ignores the correlation of the model structure in the frequency domain. In this paper, filter pruning is performed with the help of discrete wavelet transform (DWT) and edge structure similarity of feature maps to realize the readability of the model structure in the frequency domain. The edge information is an important part of an image. In addition, the WT provides a multi-resolution representation of image edge and can analyze edge at a finer scale. In this paper, the frequency domain transformation of DWT is used to convert the spatial feature map to the frequency domain in order to accurately obtain the edge structural components of the feature map. The structural similarity (SSIM) is also used to calculate the similarity between feature map edges, which in turn prunes the filter based on the feature map importance score. Experiments on two image classification datasets demonstrate the feasibility of the method proposed in this paper. © 2024 IEEE.

关键词： Discrete wavelet transforms

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Advanced Automotive Quality Assurance: A Comprehensive Approach to Power Window Functionality Testing through Software Test automation 7

Advanced Automotive Quality Assurance: A Comprehensive Appro...

引用

7th international conference on computer Applications in Electrical engineering-Recent Advances, CERA 2023

作者： Rathod, Neha Kulkarni, Rohan Kakade, S.M. Ray, Asesh Coep Technological University Dept. of Electrical Engineering Pune India Kj College of Engineering and Management Research Dept. of Electrical Engineering Pune India Brose India Automotive Systems Private Limited Electronics Department Pune India

ISBN: (纸本)9798350305005

Continuous progress in control methodologies within the automotive industry harnesses electronic hardware and software to achieve heightened functionality. Ensuring the top-notch The effectiveness and endurance of power window operations in automobile systems requires the implementation of automated software testing. This study is dedicated to the automation of power window testing, with a focus on key capabilities, including obstacle detection, heat and voltage protection, and accurate position tracking. As a mechatronic application, the power window relies on software algorithms. The power window Electronic Control Unit (ECU), an external DC power supply, a PCB layout design, and software tools such as the vector CANoe tool and the Communication Access Programming Language (CAPL) browser comprise the experimental setting for this investigation. The proposed automated testing method significantly enhances efficiency and mitigates the risks associated with ECU malfunctions and potential human accidents. The manual completion of 400 scenario checks, taking six weeks, can be streamlined to just two weeks through automation. The automated process generates a detailed report encompassing specifics like start times, end times, and logged values. © 2023 IEEE.

关键词： Graphical user interfaces

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Speech Recognition for Power Dispatching Scenarios 4

Speech Recognition for Power Dispatching Scenarios

引用

4th international conference on Electronic Information engineering and computer Communication, EIECC 2024

作者： Han, Yaxu Gao, Lu Zhang, Fei Qin, Ling Inner Mongolia China Inner Mongolia University of Science and Technology School of Automation and Electrical Engineering Inner Mongolia China

ISBN: (纸本)9798331534622

In power dispatch speech recognition, the recognition scenario is different from quiet public domains, as it involves challenges such as noisy audio signals and an abundance of technical terms. Therefore, this paper proposes an acoustic model framework to enhance the attention mechanism, using the Conformer as the sound encoder and introducing the Deep Residual Shrinkage Network to process audio signals. In the decoder part, the decoding results of CTC are fed into the Attention network for scoring again, obtaining new score rankings to achieve the output with the highest probability. Finally, a shallow fusion acoustic model based on statistical language models n-gram is utilized to further improve the overall recognition capabilities of the model for power dispatch scenario audio. A comparison with baseline models on public Mandarin datasets and power dispatch scenario audio datasets showed a reduction in Character Error Rate (CER) by 2.3 and 4.1 respectively, validating the advanced nature of the model. © 2024 IEEE.

关键词： Speech enhancement

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Speed and Torque Optimization of Motor Drive Through Intelligent Control Approaches

Speed and Torque Optimization of Motor Drive Through Intelli...

引用

2024 IEEE international conference on automation and Computation, AUTOCOM 2024

作者： Kantari, Hanumaji Vadivel, M. Jagadeesan, Pavithra Nagalakshmi, T.J. Meenakshi, B. Velmurugan, S. Malla Reddy Institute of Engineering and Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Vidya Jyothi Institute of Technology Department of Electronics and Communication Engineering Telangana Hyderabad India Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India T.J.S. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350382723

The need for better control approaches in Permanent Magnet Synchronous Motors (PMSMs) has increased due to the increased usage of electric motors in many different areas. The unique characteristics of PMSM motors make it difficult to use conventional control techniques to dynamically adjust speed and torque. This research proposes a novel approach to real-time speed and torque optimization of PMSM motor drives by integrating Sliding Mode Control (SMC) in Reinforcement Learning (RL). This could alleviate these issues. This study introduces a dual-mode control approach for permanent magnet synchronous motors (PMSM) that leverages the robustness of SMC and the flexibility of RL. In order to improve the PMSM motor drive's overall efficiency, a synergistic effect is achieved by creating an RL-based Maximum Torque and Speed Tracking (MTST) algorithm. Incorporating SMC ensures precise and stable control of speed and torque. Results from both theoretical and practical investigations using a PMSM motor operating system model in Matlab/Simulink validate the proposed method. The results reveal improved control over speed and torque, proving the efficacy and adaptability of the proposed method for PMSM actuators to function in different environments. © 2024 IEEE.

关键词： Sliding mode control

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Optimizing Algorithm For Networks Robustness Under Limited Knowledge Attacks 8

Optimizing Algorithm For Networks Robustness Under Limited K...

引用

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

作者： Li, Nuohan Wuhan University of Technology School of Automation Wuhan China

ISBN: (纸本)9798331506230

Many realistic networks are found to have community structure, which plays an important role in realworld applications, therefore it is critical to maintain the functional integrity of communities when networks are subjected to attacks and errors. Plenty of previous studies have focused on the robustness of community structures against malicious attacks, in which the full information of all nodes in the network is wellknown. However, restricted by realistic conditions, the information obtained by observing networks is limited, so we adopt a novel attack strategy that only partial nodes are observed, and the most vulnerable nodes among these are targeted in each attack round, i.e., the limited knowledge attack. Based on this attack strategy, we designed an optimization algorithm MA-CRLA which improves the community robustness under limited knowledge attacks while keeping the initial community partition well-preserved. The results show that the algorithm can effectively enhance the community robustness under different attack strategies, and prove that even if only few numbers of nodes are observed in each round of attack, the limited knowledge attack can still achieve the destructive effect of an approximately malicious attack. © 2024 IEEE.

关键词： Consensus algorithm

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