AUTOMATIC CONTROL AND COMPUTER SCIENCES最新文献_第3页

Financial Digital Images Compression Method Based on Discrete Cosine Transform 基于离散余弦变换的金融数字图像压缩方法

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-11-06 DOI: 10.3103/S014641162470069X

Wenjin Wang, Miaomiao Lu, Xuanling Dai, Ping Jiang

{"title":"Financial Digital Images Compression Method Based on Discrete Cosine Transform","authors":"Wenjin Wang, Miaomiao Lu, Xuanling Dai, Ping Jiang","doi":"10.3103/S014641162470069X","DOIUrl":"10.3103/S014641162470069X","url":null,"abstract":"In response to the characteristics of financial image data, this paper proposes an efficient digital image compression scheme. Firstly, discrete cosine transform (DCT) is applied to divide the financial image into DC and AC coefficients. Secondly, based on the characteristics of DCT coefficients, a fuzzy method is employed to categorize DCT subblocks into smooth, texture, and edge classes, enabling distinct quantization strategies. Subsequently, to eliminate spatial and statistical redundancies in financial images, common features and structures are utilized, and a specific scanning approach is employed to optimize the arrangement of important coefficients. Finally, differential prediction and entropy coding are employed for DCT coefficient scanning encoding, enhancing compression efficiency. The objective evaluation metrics of this algorithm are approximately 2 dB higher than existing algorithms at bit rates of 0.25 and 0.5. Even at bit rates of 0.75, 1.5, 2.5, and 3.5, the performance of this method still outperforms the comparative algorithms, demonstrating its capability to efficiently store and transmit massive financial image data, thereby providing robust support for data processing in the financial sector.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 5","pages":"592 - 601"},"PeriodicalIF":0.6,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Arabic Optical Character Recognition Approach Based on Levenshtein Distance 基于莱文斯坦距离的新型阿拉伯语光学字符识别方法

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-11-06 DOI: 10.3103/S0146411624700639

Walid Fakhet, Salim El Khediri, Salah Zidi

引用次数: 0

Advancing Driver Behavior Recognition: An Intelligent Approach Utilizing ResNet 推进驾驶员行为识别：利用 ResNet 的智能方法

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-11-06 DOI: 10.3103/S0146411624700664

Haiyan Kang, Congming Zhang, Hongling Jiang

{"title":"Advancing Driver Behavior Recognition: An Intelligent Approach Utilizing ResNet","authors":"Haiyan Kang, Congming Zhang, Hongling Jiang","doi":"10.3103/S0146411624700664","DOIUrl":"10.3103/S0146411624700664","url":null,"abstract":"In pursuit of enhancing public safety and addressing challenges in driver behavior recognition, an intelligent recognition and detection method of driver behavior based on ResNet (IRDMDB-ResNet) is proposed. The approach aims to identify instances of distracted driving resulting from abnormal behavior. Three models (IRDMDB-1, IRDMDB-2, and IRDMDB-3) are presented to implement this method, which is adapted to a deep learning behavior recognition in driving scenarios. Firstly, this study utilizes two well-tested real datasets: Driver Drowsiness Dataset and The State Farm. These datasets undergo preprocessing to meet the input requirements of the model. Secondly, a lightweight convolutional neural network model has been designed to extract features, aiding the warning system in delivering precise information and minimizing traffic collisions to the maximum extent possible. Finally, the model is evaluated based on the confusion metrics, accuracy, precision, recall, and F1-score criterion. As a result, the IRDMDB-3 model proposed in this paper can recognize and detect driver behavior effectively and stably. And it achieves 99.79% of accuracy in the classification of distracted drivers looking elsewhere in The State Farm dataset. Similarly, the detection at Driver Drowsiness Dataset is 99.68%. This advancement represents a significant improvement in traffic safety, showcasing adaptability to diverse behaviors and remarkable recognition and detection capabilities.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 5","pages":"555 - 568"},"PeriodicalIF":0.6,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fall Monitoring System Based on Wearable Device and Improved KNN 基于可穿戴设备和改进型 KNN 的跌倒监测系统

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-08-28 DOI: 10.3103/S0146411624700597

Shan Li, Diyuan Tan, Binbin Yao, Zhe Wang

{"title":"Fall Monitoring System Based on Wearable Device and Improved KNN","authors":"Shan Li, Diyuan Tan, Binbin Yao, Zhe Wang","doi":"10.3103/S0146411624700597","DOIUrl":"10.3103/S0146411624700597","url":null,"abstract":"For the elderly, falls can be extremely fatal. However, due to the physical decline of the elderly, it is difficult to avoid falls. Therefore, to the greatest extent feasible lessen the harm that falls on the elderly inflict, so that they can be found in the first time of falls, this study based on wearable devices, proposed a fall monitoring system using an improved K-nearest neighbor algorithm. The improved fuzzy K-nearest neighbor algorithm combined with support vector machine algorithm is applied to improve the efficiency and accuracy of the algorithm, and reduce the false positive rate and false negative rate as much as possible. The suggested model’s average precision in the simulation experiment is 97.5%. The specificity was 97.6%. The sensitivity was 97.5%. The convergence performance is also good, 24 iterations can reach the optimal. In the actual experiment, the average accuracy reached 98.7%; The false alarm rate is only 0.7%; The negative rate was 2.5%; Its performance is superior to other two algorithms. This shows that the proposed method has excellent accuracy, false positive rate and false negative rate in practical application, which has important significance for the health and safety of the elderly.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 4","pages":"366 - 378"},"PeriodicalIF":0.6,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RF Source Localization Method Based on a Single-Anchor and Map Using Reflection in an Improved Particle Filter 基于单锚定和地图的射频源定位方法，在改进粒子滤波器中使用反射法

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-08-28 DOI: 10.3103/S0146411624700500

Saeid Haidari, Alireza Hosseinpour

引用次数: 0

Fire Risk Monitoring of Tamarix chinensis Forest Based on Infrared Remote Sensing Technology 基于红外遥感技术的柽柳林火险监测

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-08-28 DOI: 10.3103/S0146411624700482

Jin Wang, Ruiting Liu, Liming Liu, Xiaoxiang Cheng, Feiyong Chen, Xue Shen

引用次数: 0

Research on Binocular Vision Image Calibration Method Based on Canny Operator 基于 Canny 运算器的双眼视觉图像校准方法研究

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-08-28 DOI: 10.3103/S0146411624700585

Lei Yan

引用次数: 0

Facial Expression Recognition Based on Multiscale Features and Attention Mechanism 基于多尺度特征和注意力机制的面部表情识别

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-08-28 DOI: 10.3103/S0146411624700548

Lisha Yao

引用次数: 0

Building a Production-Ready Keyword Detection System on a Real-World Audio 在真实世界音频上构建可用于生产的关键词检测系统

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-08-28 DOI: 10.3103/S0146411624700561

Eugene Zhmakin, Grach Mkrtchian

{"title":"Building a Production-Ready Keyword Detection System on a Real-World Audio","authors":"Eugene Zhmakin,  Grach Mkrtchian","doi":"10.3103/S0146411624700561","DOIUrl":"10.3103/S0146411624700561","url":null,"abstract":"This paper deals with the problem of creating a keyword spotting (KWS) system with real-world audio data. The paper describes the different methods used to build KWS systems, deep learning models such as convolutional neural networks (CNN), transformers, etc. The paper also discusses the mainstream dataset for training and testing KWS models, Google Speech Commands. We conduct experiments on Google Speech Commands dataset and propose our method of creating a KWS dataset and that helps neural networks achieve better results in training on relatively small amounts of data. We also introduce an idea of a hybrid KWS inference system architecture that uses voice detection and light-weight speech recognition framework in attempt to boost its computational performance and accuracy. We conclude by noting that KWS is an important challenge in the field of speech recognition, and suggest that their method can be used to improve the performance of KWS systems in the circumstances of low amounts of training data. We also note that future research could focus on bettering the process of evaluating the models and improving the overall performance of KWS systems.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 4","pages":"454 - 458"},"PeriodicalIF":0.6,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Research on Genetic Algorithm-Based Task Scheduling in Cloud-Fog Computing Systems 基于遗传算法的云雾计算系统任务调度研究

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-08-28 DOI: 10.3103/S0146411624700512

Wang Hao, Li Hui, Song Duanzheng, Zhu Jintao

{"title":"A Research on Genetic Algorithm-Based Task Scheduling in Cloud-Fog Computing Systems","authors":"Wang Hao, Li Hui, Song Duanzheng, Zhu Jintao","doi":"10.3103/S0146411624700512","DOIUrl":"10.3103/S0146411624700512","url":null,"abstract":"In recent years, the proliferating of IoT (Internet of things)-originated applications have generated huge amounts of data, which has put enormous pressure on infrastructures such as the network cloud. In this regard, scholars have proposed an architectural model for “cloud-fog” computing, where one of the obstacles to fog computing is how to allocate computing resources to minimize network resources. A heuristic-based TDCC (Time, distance, cost and computing-power) algorithm is proposed to optimize the task scheduling problem in this heterogeneous system for genetic algorithm-based “cloud-fog” computing, including execution time, operational cost, distance and total computing power resources. The algorithm uses evolutionary genetic algorithms as a research tool to combine the advantages of cloud computing, fog computing and genetic algorithms to achieve a balance between latency, cost, link length and computing power. In the hybrid computing task scheduling, this algorithm has a better balance than TCaS algorithm which only considers a single metric; this algorithm has a better adaptation value than traditional MPSO algorithm by 2.61%, BLA algorithm by 6.92% and RR algorithm by 33.39%, respectively. The algorithm is also flexible enough to match the user’s needs for high performance distance-cost-computing power, enhancing the effectiveness of the system.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 4","pages":"392 - 407"},"PeriodicalIF":0.6,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0