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automation Through Machine Learning: Reinvigorating Cyber Security 15

Automation Through Machine Learning: Reinvigorating Cyber Se...

引用

15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Bagade, Jayashree V. Dari, Sukhvinder Singh Dhivrani, Rekha Chowhan, Santosh Ravivarman, G. Janakiraman, V. Vishwakarma Institute of Technology Department of Information Technology Pune India Symbiosis International Symbiosis Law School Nagpur Pune India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Data Analytics and Mathematical Sciences Karnataka Bangalore India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India

ISBN: (纸本)9798350370249

Cyber security is predicated heavily on manual efforts to fight malicious assaults, but such processes are increasingly turning into overwhelmed by means of the quantity of threats - a hassle worsened in the course of the global COVID-19 pandemic. This has highlighted the importance of leveraging device studying (ML) to automate cyber protection methods. In this article, we speak how ML may be used to optimize the detection, prevention, and remediations of malicious assaults in an extensive kind of applications and offerings. We discover the various procedures being evolved that may assist make the identity of threats greater accurate and greater effortlessly to be had. We additionally recollect the capacity challenges associated with the software of ML strategies, along with the potential for unfair bias in opposition to positive instructions of customers, and become aware of methods for addressing those issues. Our end emphasizes the significance of leveraging ML in order to enable automation in cyber safety, as well as to make sure the detection of state-of-the-art new threats. © 2024 IEEE.

关键词： Cyber Instructions Malicious Procedures Threats

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GCC-YOLOv7: Accelerate printed circuit board small target detection

GCC-YOLOv7: Accelerate printed circuit board small target de...

引用

2023 international conference on computer Application and Information Security, ICCAIS 2023

作者： Liang, Jianwei Yuan, Xuchang Li, Hui School of Electrical Engineering and Automation Jiangxi University of Science and Technology Jiangxi Ganzhou China School of Information Engineering Gannan University of Science and Technology Jiangxi Ganzhou China

ISBN: (纸本)9781510675032

Given the low detection accuracy, slow speed, and impoverished comprehensiveness of existing Printed Circuit Board (PCB) surface defect detection in small target detection, a lightweight YOLOv7 improved algorithm is proposed. First, the ordinary convolution operation is replaced by Ghost, the model parameters are significantly reduced, the accuracy is almost no loss, and then the Convolutional Block Attention Module (CBAM) is added. Finally, the Contextual Transformer module is added to the detection header to increase the model's focus on defect features, which can combine contextual feature information to improve the representation of small target features. Ablation experiments were performed on the PCB datasets provided by the Intelligent Robot Open Laboratory of Peking University, combined with the datasets of 10,000 different PCB defect images collected by ourselves. The experimental results showed that the enhanced model reduced the number of parameters by 54% compared with the previous model, and the detection precision mAP was 97.02%. The running speed is 53.4 FPS, which suits the need for high detection precision and speed in industrial. © 2024 SPIE.

关键词： Surface defects

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Integrating Supply Chain Finance into Blockchain-Based Supply Chain Management Systems 2

Integrating Supply Chain Finance into Blockchain-Based Suppl...

引用

2nd IEEE international conference on IoT, Communication and automation Technology, ICICAT 2024

作者： Vijayakumari, G. Siri, Dharmapuri Sharma, Ashish Hussein, Ramy Riad Maneiah, D. Uganya, G. New Prince Shri Bhavani College of Engineering and Technology Department of ECE Tamil Nadu Chennai600073 India GRIET Bachupally Department of CSE Telangana Hyderabad India GLA University Department of Computer Engineering & Applications Mathura India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Department of Mechanical CMR Technical Campus Telangana Hyderabad India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of ECE Chennai600062 India

ISBN: (纸本)9798350368109

On that consideration, this investigation examines SCF as a concept and how it can be implemented within blockchain-enabled supply chain systems to increase effectiveness, minimize risk, and provide greater visibility into supply chain transactions. This study reveals the practical advantages of applying a decentralized and tamper-proof ledger of blockchain in the spheres of transaction processing, specifically, times of completing basic transactions, times of the payments' cycles, and decreasing the number of errors and discrepancies. Notable results among them include cutting the business's transaction processing time by half, payment cycle time by 71% in addition to reporting an 87% reduction in data entry mistakes. They concur with previous research supporting the disruptive prospect of blockchain technology in SCM and SCP, adding more research effort and investment in this area is warranted in order to fully exploit its advantages. © 2024 IEEE.

关键词： Decentralized finance

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Harvesting Renewable Energy from Foot Pedal Using Rotational Electromagnetic Induction Flywheel 15

Harvesting Renewable Energy from Foot Pedal Using Rotational...

引用

15th international conference on computer and automation engineering, ICCAE 2023

作者： Montalban, Patricia Angelica R. Pizarra, Nyxzel S. Magwili, Glenn V. Mapua University Department of Electrical Electronics and Computer Engineering Manila City Philippines

ISBN: (纸本)9798350396225

Philippines is one of the highest electricity prices in the ASEAN where harnessing renewable energy using wasted human effort is necessary. The global pandemic COVID-19 is spreading and because of this, establishments have required sanitation. The study's main objective is to Develop a Rotational Electromagnetic Induction Flywheel using Foot Pedal as Actuation to Harvest Renewable Energy. T-test was used to validate the results using the battery percentage of a power bank as the parameter, where there is a significant difference between single and multiple actuations with an attached mechanical dispenser and without. The system was able to harness an average of 0.30992 Watt-hour and 6.11476 Watt-hour in 5 daily trials for single and multiple controlled set-ups without mechanical dispenser respectively. An average of 0.2441 Watt-hour and 5.0027 Watt-hour for single and multiple controlled set-ups with mechanical dispenser correspondingly. Lastly, an average of 3.2924 Watt-hour in 5 daily trials for uncontrolled set-up. © 2023 IEEE.

关键词： Electromagnetic induction

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Target Distance Estimation Model Based on Deformable Convolution and Attention Mechanism

Target Distance Estimation Model Based on Deformable Convolu...

引用

2023 IEEE international conference on Electrical, automation and computer engineering, ICEACE 2023

作者： Lin, Tao Shi, Yu Zhang, Yabo Jiang, Zeping Yi, Shiming Wang, Rong School of Computer Science and Information Engineering Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350309614

Environment perception tasks, including target detection, distance estimation, and other charges, are essential components of autonomous driving systems or automation systems. Among them, target distance value estimation is used to achieve tasks such as collision avoidance in automated systems. Although the target distance estimation task is indispensable, few related studies exist. This paper proposes a model combined with a deformable convolution kernel attention mechanism for monocular ranging tasks. Compared with previous distance estimation deep learning models, introducing the attention mechanism can better grasp the relationship between the target and the global situation. At the same time, deformable convolution can better capture the characteristics of different targets and reduce the impact of the background on the results. Experiments have proven that distance estimation and other models based on attention mechanisms perform better. Based on the basic model, we introduce a multi-task tool and conduct joint training through joint pixel-level tasks, which can better combine the global information of the target and allow the model to obtain better expressive capabilities. Through ablation experiment comparison, we can find that multi-task joint is after training, and the performance of the basic model can be significantly improved. © 2023 IEEE.

关键词： attention mechanism convolutional neural network dense prediction depth estimation image segmentation Monocular ranging multi-task model

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Convolution Pyramid Attention: An Efficient Channel Attention Mechanism 4

Convolution Pyramid Attention: An Efficient Channel Attentio...

引用

4th international conference on computer Vision and Data Mining, ICCVDM 2023

作者： Wang, Ruitong Jiang, Xiangju School of automation & electrical engineering Lanzhou Jiaotong University GANSU Lanzhou730070 China

ISBN: (纸本)9781510674448

Many studies show that convolutional neural networks can improve performance after embedding attention mechanism. However, the existing related research either develops more complex attention modules in pursuit of ultimate performance improvement;Or the performance improvement is not obvious in pursuit of ultra-lightweight In order to balance the contradiction between the performance and complexity of attention mechanism, this paper proposes a simple convolution pyramid attention module (CPA). Firstly, the module constructs a convolution pyramid which can be used for multi-scale feature extraction by stacking two-dimensional convolution with convolution kernel size of 1, and then counts the global information of feature mapping in the channel dimension. Then, the feature fusion is carried out with the exclusion block, and the output weight vector is multiplied with the original feature mapping in the channel dimension, thus realizing the adaptive correction of feature mapping in the channel dimension. Finally, the performance superiority of the proposed attention mechanism is proved by image classification and target detection tasks, and then its structural rationality is proved by ablation experiments. © 2024 SPIE.

关键词： Convolution

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Research on Physical Intelligent Health Test System of Students in computer Digital Intelligent Campus

Research on Physical Intelligent Health Test System of Stude...

引用

2023 IEEE international conference on Electrical, automation and computer engineering, ICEACE 2023

作者： Fang, Qingbo Jilin University of Finance and Economics Jilin Changchun130117 China

ISBN: (纸本)9798350309614

Starting from the backbone service module and information interaction module of the system, a complete system of information interaction and transmission functions including system management operation, data testing, student management and data analysis is gradually formed. Then a decision tree classification method based on C4.5 is presented. By embedding the decision tree algorithm into the system for data mining and processing, the purpose of planning processing and internal contact of college sports test data is achieved. This method can evaluate the physical condition of college students scientifically and efficiently, and can better reflect the change of physical condition of college students. The results show that lung capacity is the most important factor in college students. © 2023 IEEE.

关键词： C4.5 decision tree data mining MySQL Students physical health test testing and management

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Study on Evaluation of Herbicide Removal of Invasive Plant Micrantha Using Big Data Remote Sensing Images from computer Beidou Navigation

Study on Evaluation of Herbicide Removal of Invasive Plant M...

引用

2023 IEEE international conference on Electrical, automation and computer engineering, ICEACE 2023

作者： Shuqiang, Li Wei, Chen University of Electronic Science and Technology of China Department of Mechanical and Electrical Engineering Zhongshan Institute Zhongshan China Industry Research Center Wonders Information Co. Ltd. Beijing China

ISBN: (纸本)9798350309614

The surface spectral data of Mikania micrantha were studied by using satellite hyperspectral images. A hierarchical extraction algorithm based on MSMEAP algorithm was proposed to identify and extract Mikania micrantha invasion on a large scale. A color image is divided into several uniform small blocks, and then the average value of each pixel color vector is obtained. The results show that the recognition accuracy of spatial distribution map of Micrantha based on OHS remote sensing image reaches 82.6%, which can be well adapted to the current monitoring requirements. In the use of herbicides, 2, 4-D sodium salt, 2, 4-D butyl ester two phenoxy carboxylic acid herbicides are relatively ideal drugs, they can effectively inhibit the growth and harm of harmful plants. The best treatment effect is applied to the middle and top of the plant. © 2023 IEEE.

关键词： Beidou navigation herbicide mikania micrantha satellite hyperspectral remote sensing spectrum

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FabricSense: A Tactile-Based Fabric Structure Detection Methodology for Automatic Temperature Adjustment

FabricSense: A Tactile-Based Fabric Structure Detection Meth...

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2023 international conference on IoT, Communication and automation Technology, ICICAT 2023

作者： Dayananda, Chaithanya Hemashree, P. Harshini, M. Sai Guruprasad, N. Global Academy of Technology Department of Computer Science and Engineering Karnataka Bangalore India Annamcharya Institute of Technology & Sciences Department of Computer Science and Engineering Andhra Pradesh Tirupati India

ISBN: (纸本)9798350302820

Based on tactile information and content-based image retrieval (CBIR), this methodology proposes a novel way for fabric structure detection and automatic temperature control. The technology accurately identifies fabric structures and establishes the ideal ironing temperature by combining tactile qualities, visual elements retrieved from fabric photographs, and programmed thermostat sensors. Unlike standard visual-based methods, this approach analyses colour, texture, and shape properties of fabric samples using tactile information and CBIR algorithms, enabling reliable fabric structure detection. Through testing and improvement, the system's performance is confirmed, providing exact temperature adjustment and improving the ironing experience. © 2023 IEEE.

关键词： Iron

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Research on Multilevel Degradater Model under Unsupervised Learning 6

Research on Multilevel Degradater Model under Unsupervised L...

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6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Lv, Jieyi Wang, Zhongsheng Xi'an Technological University School of Computer Science and Engineering Xi'an China Xi'an Technological University State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control Xi'an China

ISBN: (纸本)9798350305388

In most super-resolution experiments, because the data set in the real scene cannot meet the quantity requirements, it is necessary to downsample the high-resolution images using the degradation method to obtain the same proportion of low-resolution images. However, because the same degradation method is used to process images, the processing process of low-resolution images is relatively simple, which is easy to cause model solidification in the subsequent training process. After the training is completed, the generalization ability will be generally low due to the single underlying degradation method. This paper uses the SRMD method to build an unsupervised multilevel degradation, and takes advantage of the adduction network generated in unsupervised learning. After extracting image features, it adopts anisotropic Gaussian fuzzy kernel, bi-cubic subsampling and additive Gaussian noise to compose the degradation training data set. Compared with the traditional bi-cubic PNSR, the performance is improved by 5%. The SSIM value is increased by 3%, and the running speed is increased by 7% on average. © 2023 IEEE.

关键词： Gaussian distribution

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