2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)最新文献_第5页

Design of Control System of Epidemic Prevention Mobile Platform based on ASR 基于ASR的防疫移动平台控制系统设计

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930185

BaiHao Xing, Honghua Tan, Shuo Huang

{"title":"Design of Control System of Epidemic Prevention Mobile Platform based on ASR","authors":"BaiHao Xing, Honghua Tan, Shuo Huang","doi":"10.1109/AICIT55386.2022.9930185","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930185","url":null,"abstract":"The outbreak has spread all over the world, and the risk of medical work remains high. Traditional epidemic prevention methods have the risk of cross-infection. In order to reduce the contact rate of COVID-19 and strengthen the intelligence of epidemic prevention, this paper proposes an ASR-based mobile platform control system design for epidemic prevention. The system consists of an ASR control module, an epidemic prevention and disinfecting module, and a platform moving module. The system processes voice commands into text messages through ASR and transmits them in JSON format. The data is parsed by lexical analysis, keyword extraction and command parsing to complete the command parsing. The atomic instructions that can be recognized by the machine are solved by Iclingo and sent to the platform mobile module and the epidemic prevention and disinfection module, and the disinfection is completed at the designated place. Unity3D simulation experiments show that, compared with traditional Chinese speech recognition, the system responds faster under standard commands and has high recognition accuracy under language habit. And the operation is stable and the control is accurate, which can meet the task of epidemic prevention and disinfection in medical care places and reduce the infection rate of germs.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114677509","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

Improved Dark Channel Prior Dehazing Algorithm Combined with Sky Recognition 结合天空识别的改进暗通道先验去雾算法

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930227

Fan Yang, T. Zhang

引用次数: 0

Blind Additive Gaussian White Noise Level Estimation using Chi-square Distribution 基于卡方分布的盲加性高斯白噪声水平估计

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930155

Zhicheng Wang, Wenduo Xu, Zifan Zhu, Chen Huang, Yaozong Zhang, Zhenghua Huang

{"title":"Blind Additive Gaussian White Noise Level Estimation using Chi-square Distribution","authors":"Zhicheng Wang, Wenduo Xu, Zifan Zhu, Chen Huang, Yaozong Zhang, Zhenghua Huang","doi":"10.1109/AICIT55386.2022.9930155","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930155","url":null,"abstract":"It is important for image denoising methods with accurate noise level on real-world noisy images. Traditional noise level estimation methods either overestimate or underestimate the noise level. The former will make denoising methods smooth rich structures while the latter will make them reduce noise incompletely. To accurately estimate AGWN level, this paper proposes a novel blind additive Gaussian white noise level estimation method using Chi-square distribution, including the following key points: First, we select an initial flat patch set from the base image, which is decomposed from the noisy image by the relative total variation. And the initial noise level is estimated by mapping the patch set to the original noisy image. Then, we get the detail images by the usage of the directional gradient operations on the noisy image. Next, the initial flat patches are refined by a patch selection method with initial noise level and Chi-square distribution on the detail images. Finally, an iterative criterion is reemployed to generate a stable noise level. Experimental results validate that the proposed noise level estimation method is effective and is even superior to the state-of-the-arts.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130406993","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: 2

Research on Detection of Existing Defect Piles by Parallel Seismic Testing 平行地震试验检测既有缺陷桩的研究

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930278

Fan Yang, Ruyan Tang

引用次数: 0

Research on Fault Recovery and Reconstruction Algorithm of Distribution Network with Distributed Generation 分布式发电配电网故障恢复与重构算法研究

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930296

Qi Zhang, Xiaoling Wen, Junjie Lai

引用次数: 0

Research and Improvement of Dynamic Highly Available Load Balancing Algorithm for Microservices 微服务动态高可用负载均衡算法的研究与改进

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930161

Jianting Li, Guohong Yi, Bingqian Wu, Zhicao Cao, Xiaodong Xu

{"title":"Research and Improvement of Dynamic Highly Available Load Balancing Algorithm for Microservices","authors":"Jianting Li, Guohong Yi, Bingqian Wu, Zhicao Cao, Xiaodong Xu","doi":"10.1109/AICIT55386.2022.9930161","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930161","url":null,"abstract":"In microservices, in order to maintain the efficiency and reliability of the system under high concurrency and to solve the problem that the load balancer polling method in microservices cannot adapt to the high concurrency and high load situation, an algorithm DWLOAD (Dynamic Weight Loading Algorithm) is proposed for the dynamic weight server based on virtual nodes in conjunction with the actual application scenario. The algorithm introduces the concepts of virtual nodes and real-time weights based on a smooth polling load algorithm. The DWLOAD algorithm calculates the number of recent requests, response time, and throughput of the same microservice module deployed in different servers to obtain the real-time weights of each server and records them in the weights table, and uses the smooth polling loading algorithm to initialize virtual nodes in batches. The virtual nodes are initialized in batches using a smooth polling load algorithm. Through simulation experiments, the QPS processing capability of DWLOAD is improved by about 50% compared with the smooth polling algorithm in large-scale scenarios, which effectively improves the efficiency and reliability of load balancing in high-load situations in microservices and reduces the comprehensive response time of the system.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133810588","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

STATCOM compensation and control strategy of star cascade H-bridge under unbalanced conditions 不平衡条件下星型串级h桥的STATCOM补偿与控制策略

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930149

Zhang Chaofan, L. Jian, Chen Junfeng

引用次数: 0

Design and implementation of venue reservation based on React Native 基于React Native的场地预订的设计与实现

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930150

Huafeng Chen, Junqiao Xiong

引用次数: 1

Multi-target classification method based on the fusion of HOG and SURF features 基于HOG和SURF特征融合的多目标分类方法

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930309

Yun-Jiun Wang, Xiaoming Li

引用次数: 0

A Nonuniform Correction Algorithm Based on Regularization Constraints of Gaussian Surface Fitting 基于正则化约束的高斯曲面拟合非均匀校正算法

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930169

Ruzhou Li, Yu Shi, Zhigao Huang

{"title":"A Nonuniform Correction Algorithm Based on Regularization Constraints of Gaussian Surface Fitting","authors":"Ruzhou Li, Yu Shi, Zhigao Huang","doi":"10.1109/AICIT55386.2022.9930169","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930169","url":null,"abstract":"Due to the limitation of hardware, infrared optical systems often have thermal radiation noise effects on the acquired images. Although the effect of thermal radiation on image quality can be reduced with proper optical design, it is expensive and cannot completely eliminate the effect of thermal radiation. To solve this problem, for the purpose of improving the image quality after imaging, we propose a novel image non-uniformity correction method. The optical head cover of the imaging system is usually semi-circular, and the thermal radiation effect conforms to the Gaussian distribution. Therefore, this paper firstly preprocesses the degraded image, including Gaussian surface fitting and image layering, and then introduces the preprocessing results into In the correction model, frame wave regularization constraints are imposed on the potential clear images, and the Gaussian surface fitting regularization term is introduced into the thermal radiation correction model, and the clear images and thermal radiation effect maps are estimated by Split Bregman iterative optimization. The experimental results show that our proposed method can perform the non-uniform correction caused by thermal radiation noise well.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132049529","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