Image segmentation is the basis of image understanding and analysis. Among the many image segmentation methods, the threshold segmentation method is simple and efficient, and is widely used in image segmentation. But how to find the right threshold is a tricky problem. Through the analysis of the traditional OTSU algorithm (maximum between-cluster variance), an improved OTSU algorithm is proposed for special images
{"title":"The application of the improved maximum between-cluster variance method in special images","authors":"Wang Na","doi":"10.1145/3411016.3411021","DOIUrl":"https://doi.org/10.1145/3411016.3411021","url":null,"abstract":"Image segmentation is the basis of image understanding and analysis. Among the many image segmentation methods, the threshold segmentation method is simple and efficient, and is widely used in image segmentation. But how to find the right threshold is a tricky problem. Through the analysis of the traditional OTSU algorithm (maximum between-cluster variance), an improved OTSU algorithm is proposed for special images","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127276126","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}
M. Sizov, A. Starostenko, A. Tsyganov, A. M. Medvedev
Budker Institute of Nuclear Physics produces electron beam welding facilities (EBWF), which are successfully utilized in experiments and low series production (e.g. manufacturing of vacuum chambers for the FAIR project). For the joint quality, it is crucial to deflect the electron beam in sync with the welded sample movement. We present the real-time control system architecture, that consists of a CPU-based high-level programmable interface, and real-time control logic implemented in FPGA. FPGA system consists of synchronized subsystems running simultaneously - execution of specialized programs to control electron beam deflection, coordinate table movement, and also processing image data gathered from secondary electron emission detector. To reduce the labor needed for implementation, the image processing subsystem is written in high-level domain-specific language Caph, thus the resulting image processing VHDL code is autogenerated.
{"title":"Real time control system architecture for industrial electron beam welding facility based on FPGA","authors":"M. Sizov, A. Starostenko, A. Tsyganov, A. M. Medvedev","doi":"10.1145/3411016.3411017","DOIUrl":"https://doi.org/10.1145/3411016.3411017","url":null,"abstract":"Budker Institute of Nuclear Physics produces electron beam welding facilities (EBWF), which are successfully utilized in experiments and low series production (e.g. manufacturing of vacuum chambers for the FAIR project). For the joint quality, it is crucial to deflect the electron beam in sync with the welded sample movement. We present the real-time control system architecture, that consists of a CPU-based high-level programmable interface, and real-time control logic implemented in FPGA. FPGA system consists of synchronized subsystems running simultaneously - execution of specialized programs to control electron beam deflection, coordinate table movement, and also processing image data gathered from secondary electron emission detector. To reduce the labor needed for implementation, the image processing subsystem is written in high-level domain-specific language Caph, thus the resulting image processing VHDL code is autogenerated.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128146285","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}
Xiao Li, Yu Yang, Yiming Xu, Chao Wang, Linyang Li
At present, the detection of crowd abnormal behavior has the problem of unclear definition of anomalies and mutual occlusion. Existing researches mostly detect the appearance and behavior characteristics of individuals, extract and analyze the movement characteristics of groups. Anomaly detection is achieved through comparison of parameters and thresholds. However, the context semantics cannot be effectively utilized and the definition of anomalies cannot be consistent with the actual situation. There is a problem of disconnection between behavior characteristics and behavior description. In this paper, we use the designed convolutional neural network to extract the spatiotemporal features of the crowd, combine the motion descriptors and emotional descriptors corresponding to the features, that is to say, to describe the features in multiple directions; with the help of unsupervised deep learning models, we train normal behaviors, and use crowd psychology knowledge to conduct research on crowd situation analysis; multi-class SVM training and using it to distinguish different types of features will help to achieve the description and prediction of crowd behavior. Furthermore, through the design of modular schemes to reduce the complexity of the calculation and improve the efficiency of the algorithm. The purpose of this article is to design a new method to achieve the effective extraction of various features of the crowd and the precise identification of abnormal behaviors in complex crowds. Experiments verify that the algorithm in this paper can accurately describe the behavior of complex people.
{"title":"Crowd Abnormal Behavior Detection Combining Movement and Emotion Descriptors","authors":"Xiao Li, Yu Yang, Yiming Xu, Chao Wang, Linyang Li","doi":"10.1145/3411016.3411166","DOIUrl":"https://doi.org/10.1145/3411016.3411166","url":null,"abstract":"At present, the detection of crowd abnormal behavior has the problem of unclear definition of anomalies and mutual occlusion. Existing researches mostly detect the appearance and behavior characteristics of individuals, extract and analyze the movement characteristics of groups. Anomaly detection is achieved through comparison of parameters and thresholds. However, the context semantics cannot be effectively utilized and the definition of anomalies cannot be consistent with the actual situation. There is a problem of disconnection between behavior characteristics and behavior description. In this paper, we use the designed convolutional neural network to extract the spatiotemporal features of the crowd, combine the motion descriptors and emotional descriptors corresponding to the features, that is to say, to describe the features in multiple directions; with the help of unsupervised deep learning models, we train normal behaviors, and use crowd psychology knowledge to conduct research on crowd situation analysis; multi-class SVM training and using it to distinguish different types of features will help to achieve the description and prediction of crowd behavior. Furthermore, through the design of modular schemes to reduce the complexity of the calculation and improve the efficiency of the algorithm. The purpose of this article is to design a new method to achieve the effective extraction of various features of the crowd and the precise identification of abnormal behaviors in complex crowds. Experiments verify that the algorithm in this paper can accurately describe the behavior of complex people.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133739944","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}
The propagation of light in water is affected by the absorption of water and the scattering of particles in water, which leads to the problems of low contrast, blur, color distortion and so on, the traditional underwater image enhancement algorithm is prone to over compensation of red component. In view of the above problems, an underwater color image enhancement method based on comprehensive processing is proposed. Firstly, the improved preprocessing method is used to equalize the color of the image through the bright channel and the blue-green channel of the underwater image, and stretch the hue and saturation components in the HSV color space to eliminate the color distortion of the underwater image and compensate the color attenuation; Secondly, contrast limited adaptive histogram equalization is used to improve image contrast; Then, sharpening is used to enhance image edge, improve the image clarity and visual effect; Finally, the sharpened image is smoothed by guided filtering. The experimental results show that the contrast and clarity of the underwater image are effectively improved and the problem of color distortion is solved.
{"title":"An Underwater Color Image Enhancement Model Based on Comprehensive Processing","authors":"Haoran Wang, Suping Yu","doi":"10.1145/3411016.3411165","DOIUrl":"https://doi.org/10.1145/3411016.3411165","url":null,"abstract":"The propagation of light in water is affected by the absorption of water and the scattering of particles in water, which leads to the problems of low contrast, blur, color distortion and so on, the traditional underwater image enhancement algorithm is prone to over compensation of red component. In view of the above problems, an underwater color image enhancement method based on comprehensive processing is proposed. Firstly, the improved preprocessing method is used to equalize the color of the image through the bright channel and the blue-green channel of the underwater image, and stretch the hue and saturation components in the HSV color space to eliminate the color distortion of the underwater image and compensate the color attenuation; Secondly, contrast limited adaptive histogram equalization is used to improve image contrast; Then, sharpening is used to enhance image edge, improve the image clarity and visual effect; Finally, the sharpened image is smoothed by guided filtering. The experimental results show that the contrast and clarity of the underwater image are effectively improved and the problem of color distortion is solved.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125942116","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}
The capability of Super Resolution Convolutional Neural Networks (SRCNN) has been proved to enhance resolution of images. We applied SRCNN to enhance digital rock core images that play an important role in analyzing rock core. In this process, we noticed that the bicubic interpolation algorithm that is the first step of SRCNN might improve the speed by adjusting the calculation strategy. We proposed an SRCNN based on accelerated bicubic interpolation and tested the performance with 2000 digital rock core images. The experiment demonstrated that the accelerated bicubic interpolation algorithm faster than improved region-based bicubic image interpolation algorithm and standard bicubic interpolation algorithm, and demonstrated the feasibility of SRCNN based on our proposed algorithm to produce higher resolution digital rock core images.
{"title":"Digital Rock Core Images Super Resolution via SRCNN Based on Accelerated Bicubic Interpolation","authors":"Yunfeng Bai, V. Berezovsky, V. Popov","doi":"10.1145/3411016.3411162","DOIUrl":"https://doi.org/10.1145/3411016.3411162","url":null,"abstract":"The capability of Super Resolution Convolutional Neural Networks (SRCNN) has been proved to enhance resolution of images. We applied SRCNN to enhance digital rock core images that play an important role in analyzing rock core. In this process, we noticed that the bicubic interpolation algorithm that is the first step of SRCNN might improve the speed by adjusting the calculation strategy. We proposed an SRCNN based on accelerated bicubic interpolation and tested the performance with 2000 digital rock core images. The experiment demonstrated that the accelerated bicubic interpolation algorithm faster than improved region-based bicubic image interpolation algorithm and standard bicubic interpolation algorithm, and demonstrated the feasibility of SRCNN based on our proposed algorithm to produce higher resolution digital rock core images.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129277166","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}
A security authentication method of QR code based on digital watermarking is proposed to improve the security of two-dimensional code. This method can be applied to verify the authenticity of QR code. Firstly, the host image is partitioned into blocks and then the Two-dimensional Discrete Cosine Transform(2D-DCT) is applied for each block. Secondly, a smaller block is selected from each block in the process above, and then the Singular Value Decomposition (SVD) is applied for the smaller block. At last, the 2D-DCT and SVD transforms are applied for the image of watermark, after that the watermark is embedded by modifying the characteristic value of the SVD. The process of extracting watermark image is opposite to the process of embedding watermark. Computer simulation and experimental results prove this method has the characteristics of strong robustness, invisibility, high security and low computational cost.
{"title":"A two-dimensional code security authentication method based on digital watermarking","authors":"Yang Yuwei, Yu Su","doi":"10.1145/3411016.3411164","DOIUrl":"https://doi.org/10.1145/3411016.3411164","url":null,"abstract":"A security authentication method of QR code based on digital watermarking is proposed to improve the security of two-dimensional code. This method can be applied to verify the authenticity of QR code. Firstly, the host image is partitioned into blocks and then the Two-dimensional Discrete Cosine Transform(2D-DCT) is applied for each block. Secondly, a smaller block is selected from each block in the process above, and then the Singular Value Decomposition (SVD) is applied for the smaller block. At last, the 2D-DCT and SVD transforms are applied for the image of watermark, after that the watermark is embedded by modifying the characteristic value of the SVD. The process of extracting watermark image is opposite to the process of embedding watermark. Computer simulation and experimental results prove this method has the characteristics of strong robustness, invisibility, high security and low computational cost.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116333032","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}
Chaodong Tan, D. Yu, Xiaoyong Gao, Wenrong Song, Chao Tan
Hydrate is one of the most common challenges in flow assurance. Mechanism model or empirical model is usually adopted to predict hydrate formation under a specific condition. However, the methods are difficult to operate in real-time change of actual situation. In this paper, a mechanism-based data-driven modeling method is built to predict hydrate formation. Based on the collected data, including temperature, pressure and components, a data-driven method is introduced to identify the unknown parameters in the mechanism model. 131 groups of experimental data were collected to make a correlation analysis to determine the main components affecting hydrate formation. Four different component systems were calculated using the mechanism model (P-P model), empirical model (Makogon model) and data-driven mechanism model for comparison. Results show that the average error of the data-driven model is as low as 0.0085 MPa, and this method can overcome the irrationality of prediction caused by only using historical data or mathematical formula.
{"title":"A Mechanism based Data-Driven Model for Prediction of Hydrate Formation","authors":"Chaodong Tan, D. Yu, Xiaoyong Gao, Wenrong Song, Chao Tan","doi":"10.1145/3411016.3411163","DOIUrl":"https://doi.org/10.1145/3411016.3411163","url":null,"abstract":"Hydrate is one of the most common challenges in flow assurance. Mechanism model or empirical model is usually adopted to predict hydrate formation under a specific condition. However, the methods are difficult to operate in real-time change of actual situation. In this paper, a mechanism-based data-driven modeling method is built to predict hydrate formation. Based on the collected data, including temperature, pressure and components, a data-driven method is introduced to identify the unknown parameters in the mechanism model. 131 groups of experimental data were collected to make a correlation analysis to determine the main components affecting hydrate formation. Four different component systems were calculated using the mechanism model (P-P model), empirical model (Makogon model) and data-driven mechanism model for comparison. Results show that the average error of the data-driven model is as low as 0.0085 MPa, and this method can overcome the irrationality of prediction caused by only using historical data or mathematical formula.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132486903","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}
The feature information of retinal vascular image is complex. There are some problems in the existing algorithms, such as poor segmentation effect of microvascular segmentation and pathological vascular misclassification. Therefore, a vascular segmentation model based on DenseNet-Attention-unet (DA-Unet) is proposed. Firstly, retinal blood vessels were enhanced by adaptive histogram equalization and gamma correction, and then the DA-Unet model was constructed by DenseNet, Convolutional Block Attention Module and U-Net for retinal blood vessel segmentation.The experimental results show that the average accuracy of retinal vascular segmentation is 97.01%, and the ROC is 98.65%, when it was tested on the DRIVE data set.
{"title":"Segmentation of Retinal Vessels Based on DenseNet-Attention-Unet Model Network","authors":"Zhen Liang, Huazhu Liu, Xiaofang Zhao, Li Yu","doi":"10.1145/3411016.3411167","DOIUrl":"https://doi.org/10.1145/3411016.3411167","url":null,"abstract":"The feature information of retinal vascular image is complex. There are some problems in the existing algorithms, such as poor segmentation effect of microvascular segmentation and pathological vascular misclassification. Therefore, a vascular segmentation model based on DenseNet-Attention-unet (DA-Unet) is proposed. Firstly, retinal blood vessels were enhanced by adaptive histogram equalization and gamma correction, and then the DA-Unet model was constructed by DenseNet, Convolutional Block Attention Module and U-Net for retinal blood vessel segmentation.The experimental results show that the average accuracy of retinal vascular segmentation is 97.01%, and the ROC is 98.65%, when it was tested on the DRIVE data set.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"91 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128773998","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}
Tan Chaodong, Zhang Ziqin, Wu Haoda, Feng Gang, Z. Qian, Wei Fangfang, Tan Tingzhuang, Lian Xiaomin
On-line measurement of oil well multi-phase flow split-phase content is of great significance to the analysis of oil well production dynamics. This paper proposes an online measurement model of oil-well multi-phase flow split-phase measurement based on multi-sensors of differential pressure device and radio frequency device, and conducts experiments. This paper explores the close relationship between the pressure fluctuation signal of the gas-liquid two-phase flow and the parameters of the two-phase flow, such as the flow pattern, gas phase content and other parameters, analyzes the characteristic values of the differential pressure fluctuation signal, and establishes a number of dimensionless parameters and gas phase The relationship model of the content rate; considering the influence of temperature, fluid state, salinity and other factors on the radio frequency moisture content measurement, an optimized support vector machine moisture content data fusion measurement model is established. A gas-liquid measurement sample is obtained through a laboratory multi-phase flow verification and calibration device, and multiple linear regression correction is performed on the differential pressure method flow test data to obtain a correlation with better measurement accuracy. Experimental research shows that the oil volume multi-phase flow split-phase metering model established in this paper has a liquid volume error of less than 5%, a water cut error of less than 2%, and a gas volume error of less than 10%, which improves the application range and measurement accuracy of oil well multi-phase flow measurement.
{"title":"Model and Experimental Study of Online measurement of multiphase flow in oil wells based on data fusion","authors":"Tan Chaodong, Zhang Ziqin, Wu Haoda, Feng Gang, Z. Qian, Wei Fangfang, Tan Tingzhuang, Lian Xiaomin","doi":"10.1145/3411016.3411023","DOIUrl":"https://doi.org/10.1145/3411016.3411023","url":null,"abstract":"On-line measurement of oil well multi-phase flow split-phase content is of great significance to the analysis of oil well production dynamics. This paper proposes an online measurement model of oil-well multi-phase flow split-phase measurement based on multi-sensors of differential pressure device and radio frequency device, and conducts experiments. This paper explores the close relationship between the pressure fluctuation signal of the gas-liquid two-phase flow and the parameters of the two-phase flow, such as the flow pattern, gas phase content and other parameters, analyzes the characteristic values of the differential pressure fluctuation signal, and establishes a number of dimensionless parameters and gas phase The relationship model of the content rate; considering the influence of temperature, fluid state, salinity and other factors on the radio frequency moisture content measurement, an optimized support vector machine moisture content data fusion measurement model is established. A gas-liquid measurement sample is obtained through a laboratory multi-phase flow verification and calibration device, and multiple linear regression correction is performed on the differential pressure method flow test data to obtain a correlation with better measurement accuracy. Experimental research shows that the oil volume multi-phase flow split-phase metering model established in this paper has a liquid volume error of less than 5%, a water cut error of less than 2%, and a gas volume error of less than 10%, which improves the application range and measurement accuracy of oil well multi-phase flow measurement.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130943704","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}
According to the characteristics of engineering software testing including development process self-testing, tripartite testing and identification /type testing, a engineering software testing method based on robust design is constructed, and the technical means of application of demand centered, system design and work breakdown structure in software engineering are proposed to achieve the purpose of engineering software testing process, we need to go through four stages: test requirement analysis and planning, test design and implementation, test execution and test summary, and apply different techniques and methods of robust design to ensure the application of engineering software test in software engineering. The experimental results show that the method is clear and can ensure the reliability of engineering software testing process and improve the quality of military software testing.
{"title":"Application of robust design in engineering software testing","authors":"Yingbei Niu","doi":"10.1145/3411016.3411025","DOIUrl":"https://doi.org/10.1145/3411016.3411025","url":null,"abstract":"According to the characteristics of engineering software testing including development process self-testing, tripartite testing and identification /type testing, a engineering software testing method based on robust design is constructed, and the technical means of application of demand centered, system design and work breakdown structure in software engineering are proposed to achieve the purpose of engineering software testing process, we need to go through four stages: test requirement analysis and planning, test design and implementation, test execution and test summary, and apply different techniques and methods of robust design to ensure the application of engineering software test in software engineering. The experimental results show that the method is clear and can ensure the reliability of engineering software testing process and improve the quality of military software testing.","PeriodicalId":251897,"journal":{"name":"Proceedings of the 2nd International Conference on Industrial Control Network And System Engineering Research","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131114067","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}
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