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Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence最新文献

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A Searchable Encryption Scheme Over Facial Image 一种可搜索的面部图像加密方案
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523088
Yifang Gao, Wei Li
{"title":"A Searchable Encryption Scheme Over Facial Image","authors":"Yifang Gao, Wei Li","doi":"10.1145/3522749.3523088","DOIUrl":"https://doi.org/10.1145/3522749.3523088","url":null,"abstract":"In recent years, facial image search has been widely used. Although offering considerable convenience, facial image search also poses a severe threat to people’s privacy. How to conduct facial image search while protecting privacy has become a challenge. We design a scheme of searchable encryption facial image. The scheme is separated into two phases: uploading phase and retrieval phase. At the phase of uploading, the facial image is divided into two parts: the obfuscated features of the facial image and the encrypted facial image. In the retrieval phase, the facial image features are extracted and the similarity is calculated with the obfuscated facial features in the cloud after being obfuscated to obtain the closest obfuscated facial features and the corresponding encrypted facial image, then the encrypted facial image is decrypted in order to acquire the original facial image. Specifically, Facenet512 is used to collect facial image features while the obfuscation function is designed to obfuscate those facial image features and the Advanced Encryption Standard (AES) algorithm is used to encrypt facial images. Theoretical analysis and experimental results indicate that the scheme possesses favorable performance and high security.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123852675","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
Captcha Recognition Based on Attention Mechanism 基于注意机制的验证码识别
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523077
Yu Zheng
{"title":"Captcha Recognition Based on Attention Mechanism","authors":"Yu Zheng","doi":"10.1145/3522749.3523077","DOIUrl":"https://doi.org/10.1145/3522749.3523077","url":null,"abstract":"Captcha recognition is a worthful work to study, since it does help Internet security and also promotes the field of pattern recognition. In this work, we concentrate on the attention mechanism to this classification task for ameliorating the function of our baseline network. In our experiment, we arbitrarily combine the two modules in CBAM and the coordinate attention module that is considered to be efficient and novel. Then we add this combined attention to our baseline network. From the test results, we see that the better attention for this task is CBAM (spatial first, then channel attention), which improves the recognition accuracy to about 0.8% based on the mini-dataset generated by ourselves.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122953548","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
Arrhythmia Classification Using 2D-CNN Models 使用2D-CNN模型进行心律失常分类
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523080
Cuihua Tian, Yiping Zhang, Jingmin Gao, Zhigang Hu
{"title":"Arrhythmia Classification Using 2D-CNN Models","authors":"Cuihua Tian, Yiping Zhang, Jingmin Gao, Zhigang Hu","doi":"10.1145/3522749.3523080","DOIUrl":"https://doi.org/10.1145/3522749.3523080","url":null,"abstract":"Electrocardiogram (ECG) is one of the main tools to diagnose arrhythmia. The accurate identification of ECG signal can not only help doctors make better diagnosis, but also prevent the occurrence of cardiovascular disease. However, the current arrhythmia classification algorithms often need to be based on a large number of data sets, which reduces the scalability and practical significance of the classification algorithm. Our research proposes to use Siamese neural network based on 2D-CNN to extract the features of two-dimensional ECG signals. By calculating the Contrastive Loss and training the feature extraction model, we can judge the category of arrhythmia. The experimental results show that compared with other methods, this method not only has simple network structure, but also can be trained with fewer samples. For the five types of arrhythmias with fewer samples, the average accuracy is 97.13%.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126961724","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: 1
Fourier attack – a more efficient adversarial attack method 傅里叶攻击——一种更有效的对抗性攻击方法
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523078
Zerui Wen
{"title":"Fourier attack – a more efficient adversarial attack method","authors":"Zerui Wen","doi":"10.1145/3522749.3523078","DOIUrl":"https://doi.org/10.1145/3522749.3523078","url":null,"abstract":"As neural networks have made remarkable achievements in the field of image classification, a variety of adversarial attack methods have appeared to interfere with neural networks. Adversarial samples apply a tiny perturbation to the original image, which would not make much sense to the human eye, but would produce a massive error to the neural network. In recent years, many articles have made contributions to adversarial sample attack and defense, which aim to generate a maximum classification error while minimizing the perturbation. However, former attacks are focused on the spatial domain. We find that separated attacks based on different components in the frequency domain are more effective. The contribution of this article is: (1) compute the gradient of the neural network for image classification after the discrete Fourier transform. (2) design a stationary filter to generate the adversarial sample according to frequency component and gradient. (3) conduct experiments show that the adverasial samples generated by our method achieve the same attack effect on the premise that they are closer to the original picture.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132576522","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: 1
Single-site passenger flow forecast based on ga-lstm 基于ga-lstm的单站点客流预测
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523073
Xinyu Wen
{"title":"Single-site passenger flow forecast based on ga-lstm","authors":"Xinyu Wen","doi":"10.1145/3522749.3523073","DOIUrl":"https://doi.org/10.1145/3522749.3523073","url":null,"abstract":"In short-term passenger flow forecasting, thanks to big data analysis, we can obtain a large number of influencing factors describing the change of station passenger flow. Although this information provides a good basis for passenger flow forecasting, statistical use of passenger flow forecasting in the past are not accurate and stable because of the characteristics of timing, space and trend of passenger flow forecasting. In building an automated passenger flow forecasting system, accuracy and stability are the key points we need to pay attention to. this paper use the optimal parameter passenger flow prediction based on ga-lstm model. After selecting the optimal time step and the number of hidden units by using genetic algorithm (GA), LSTM is used for prediction. In the multi station boarding and alighting number prediction experiment on the real subway data provided by Hangzhou, It is proved that ga-lstm is better than the non optimized RNN model in prediction accuracy.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114054092","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
Vulnerability Analysis of Complex Network Important Nodes Based on Multi-attribute 基于多属性的复杂网络重要节点脆弱性分析
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523071
Jintao Yu, B. Xiao, Hao Li
{"title":"Vulnerability Analysis of Complex Network Important Nodes Based on Multi-attribute","authors":"Jintao Yu, B. Xiao, Hao Li","doi":"10.1145/3522749.3523071","DOIUrl":"https://doi.org/10.1145/3522749.3523071","url":null,"abstract":"∗ In order to predict the fragile nodes in complex networks more accurately, an important node mining method on the basis of multi-attributes is presented in the article. This method is suitable for both directed and undirected simple graph with no self-loops. The experiments based on ARPA-Net data show that the proposed method has better predictive ability on finding important nodes which can be applied to vulnerability analysis of complex network.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126256062","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 Many-objective Evolutionary Algorithm using Determinantal Point Process in Potential Region 一种基于势域确定性点过程的多目标进化算法
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523087
M. Wang, Fangzhen Ge, Debao Chen, Huaiyu Liu
{"title":"A Many-objective Evolutionary Algorithm using Determinantal Point Process in Potential Region","authors":"M. Wang, Fangzhen Ge, Debao Chen, Huaiyu Liu","doi":"10.1145/3522749.3523087","DOIUrl":"https://doi.org/10.1145/3522749.3523087","url":null,"abstract":"Most current many-objective optimization algorithms mainly attempt to construct various strategies to achieve convergence and maintain diversity. To simplify the complexity of algorithm design, we propose a many-objective optimization algorithm which introduces a ratio-based infinite norm indicator to find the optimal solutions in the current population and uses them to determine potential region where optimal solutions exist; then samples solutions with better convergence and diversity within the potential region using a determinantal point process. The results of comparing the algorithm with four algorithms on the WFG, MaF and DTLZ test sets show that our algorithm is competitive.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128088666","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
Offline reinforcement learning application in robotic manipulation with a COG method case 离线强化学习在机器人操作中的应用，以COG方法为例
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523075
Yanpeng Huo, Yuning Liang
{"title":"Offline reinforcement learning application in robotic manipulation with a COG method case","authors":"Yanpeng Huo, Yuning Liang","doi":"10.1145/3522749.3523075","DOIUrl":"https://doi.org/10.1145/3522749.3523075","url":null,"abstract":"Artificial intelligence now has different applications in various industrial fields. Reinforcement learning (RL) is one of the hot topics in the artificial intelligence, also in robotics. It is an important learning method in the field of robotic manipulation. The training policies of reinforcement learning can be divided into online learning policy and offline learning policy. Besides, the reinforcement learning algorithm of offline policy has great potential in transforming large data sets into powerful decision engine. To solve the problem that most of robot applications involve collecting data from scratch for each new task, offline learning combined with online learning is to make the training more efficient and convenient. The aim of this paper is to clearly introduce the application of offline reinforcement learning in the field of robotic manipulation. The basic formulation of reinforcement learning includes two points: First, it introduces Markov Decision Process and one of method of solution – policy gradients. Then through analyzing an application of offline learning in the field of robotic manipulation - COG algorithm, this paper analyzes the process of offline learning combining the prior data to learn new robotic skills and uses this method to solve specific tasks of robotic, such as the problems of sample efficiency. The results show that the offline learning policy has important research value in the field of robotic manipulation by reducing training time and make process efficient, and it fully embodies its advantages in solving the problems of robotic sample efficiency.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124800958","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 DQN-based workflow task assignment approach in cloud-fog cooperative considering terminal mobility 考虑终端移动性的云雾协作中基于dqn的工作流任务分配方法
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523083
Dongyue Huo, Hai-ya Wu, Baiyang Wang, Yuyun Kang, Dongping Chen
{"title":"A DQN-based workflow task assignment approach in cloud-fog cooperative considering terminal mobility","authors":"Dongyue Huo, Hai-ya Wu, Baiyang Wang, Yuyun Kang, Dongping Chen","doi":"10.1145/3522749.3523083","DOIUrl":"https://doi.org/10.1145/3522749.3523083","url":null,"abstract":"When the terminal device moves under the cloud-fog cooperative, reasonable task assignment between fog nodes and cloud servers is a difficult problem and uncompleted tasks migration to maintain the continuity of tasks is another difficult problem. To solve these two problems, a workflow task assignment and migration decision algorithm based on Deep Q Network(DQN) is proposed. Firstly, a workflow task assignment optimization model for the minimized latency is constructed. Secondly, a DQN-based algorithm is used to assign tasks reasonably. When the terminal device is moving, a task migration decision program is activated to execute task migration. Finally, a simulation experiment is proposed to verify the approach and the results indicated that the approach reduced the time latency reasonably and effectively by allocating the computing resources.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130302414","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: 1
The Power-Saving Elevator 节能电梯
Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence Pub Date : 2022-03-11 DOI: 10.1145/3522749.3523081
Tsung-Yen Kao, Hsiang-Chieh Chang, Yung-Cheng Wang, Po-Cheng Chiu, Chia-Cheng Li, Syuan-Cheng Chang
{"title":"The Power-Saving Elevator","authors":"Tsung-Yen Kao, Hsiang-Chieh Chang, Yung-Cheng Wang, Po-Cheng Chiu, Chia-Cheng Li, Syuan-Cheng Chang","doi":"10.1145/3522749.3523081","DOIUrl":"https://doi.org/10.1145/3522749.3523081","url":null,"abstract":"Under the energy-saving and carbon-reduction policy, the drive horsepower required for empty and full load is used to distinguish between large and small motors, which can avoid the use of the required rated horsepower when empty load is used to full load, resulting in unnecessary waste of electricity. According to the actual load capacity, the size of the motor can be automatically selected to drive the vertical lift. It can be driven by a small motor when descending, which has achieved the purpose of saving electricity. This power-saving hydraulic cargo elevator is used in large and heavy-duty lift, the greater the gap between the power required for empty and full load, the greater the power-saving benefits that can obtained. In this investigate, large and small motors are set up to meet the rated power required for vertical lifting when empty and full load, and the large and small motors can be automatically selected according to the weight of the load, so as to avoid the use of large motors and waste energy when there is no load.","PeriodicalId":361473,"journal":{"name":"Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133313208","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
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