Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118573
Yiran Liu, Wanjiang Han, Xiaoxiang Wang, Qi Li
Imbalance problem is widespread in machine learning. Most learning algorithms can’t get satisfied performance when they are applied on imbalance data sets, because they can be deteriorated by this problem easily. This paper proposed SDSMOTE method which captures the spatial distribution of imbalance data sets, and changes the tendency of learning algorithm by over sampling by oversampling according to the recognition difficulty. Experiments on 5 UCI data sets validate the effectiveness of this oversampling algorithm.
{"title":"Oversampling Algorithm Based on Spatial Distribution of Data Sets for Imbalance Learning","authors":"Yiran Liu, Wanjiang Han, Xiaoxiang Wang, Qi Li","doi":"10.1109/ICCCS49078.2020.9118573","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118573","url":null,"abstract":"Imbalance problem is widespread in machine learning. Most learning algorithms can’t get satisfied performance when they are applied on imbalance data sets, because they can be deteriorated by this problem easily. This paper proposed SDSMOTE method which captures the spatial distribution of imbalance data sets, and changes the tendency of learning algorithm by over sampling by oversampling according to the recognition difficulty. Experiments on 5 UCI data sets validate the effectiveness of this oversampling algorithm.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133010002","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118504
Mingwan Zhu, Linlin Zhu, Yu Han, Xiaoqi Xi, Lei Li, Bin Yan
Computed Tomography (CT) has been used in many fields. Practical misalignment of the actual CT system causes geometric artifacts in the reconstructed images, which severely degrades image quality. Geometric artifact evaluation provides a reliable basis for subsequent geometric artifact correction. Some characteristics of images, such as entropy and sharpness, are often used to measure the severity of geometric artifacts, but they are limited in generality and accuracy. Convolutional neural network (CNN) has excellent image feature learning capabilities and is well used in image processing. This paper explores the network structure suitable for the evaluation of geometric artifacts in CT images. We select three commonly used networks LeNet-5, VGG16 and AlexNet. The datasets of three kinds of phantoms are constructed using simulation and actual scanning results. The three networks are trained and tested separately on the three kinds of datasets. Experimental results show that all three CNN models can evaluate the existence of geometric artifacts in CT images. The AlexNet network achieves the best classification evaluation performance with an average classification accuracy of 0.961, with the smallest average loss and the shortest training time.
{"title":"Geometric Artifact Evaluation of X-ray Computed Tomography Images Based on Convolutional Neural Network","authors":"Mingwan Zhu, Linlin Zhu, Yu Han, Xiaoqi Xi, Lei Li, Bin Yan","doi":"10.1109/ICCCS49078.2020.9118504","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118504","url":null,"abstract":"Computed Tomography (CT) has been used in many fields. Practical misalignment of the actual CT system causes geometric artifacts in the reconstructed images, which severely degrades image quality. Geometric artifact evaluation provides a reliable basis for subsequent geometric artifact correction. Some characteristics of images, such as entropy and sharpness, are often used to measure the severity of geometric artifacts, but they are limited in generality and accuracy. Convolutional neural network (CNN) has excellent image feature learning capabilities and is well used in image processing. This paper explores the network structure suitable for the evaluation of geometric artifacts in CT images. We select three commonly used networks LeNet-5, VGG16 and AlexNet. The datasets of three kinds of phantoms are constructed using simulation and actual scanning results. The three networks are trained and tested separately on the three kinds of datasets. Experimental results show that all three CNN models can evaluate the existence of geometric artifacts in CT images. The AlexNet network achieves the best classification evaluation performance with an average classification accuracy of 0.961, with the smallest average loss and the shortest training time.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131416998","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118515
Wei Wang, Jianhua Chen
In a distributed video coding (DVC) system, side information(SI) is the estimated frame of the original Wyner-Ziv(WZ) frame, which has an important impact on the performance of the whole system. High quality SI is helpful for the decoder to restore Wyner-Ziv frames. For this reason, based on the analysis of the existing methods of generating SI, we propose a new SI generation method. Two categories of SI are generated by motion compensation frame interpolation(MCFI) and optical flow interpolation, and then they are fused based on a probability fusion method to obtain more accurate SI. The experiment results indicate that the Hybrid SI generation algorithm proposed in this work can effectively improve the quality of SI.
{"title":"Hybrid Side Information Generation Algorithm Based on Probability Fusion for Distributed Video Coding","authors":"Wei Wang, Jianhua Chen","doi":"10.1109/ICCCS49078.2020.9118515","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118515","url":null,"abstract":"In a distributed video coding (DVC) system, side information(SI) is the estimated frame of the original Wyner-Ziv(WZ) frame, which has an important impact on the performance of the whole system. High quality SI is helpful for the decoder to restore Wyner-Ziv frames. For this reason, based on the analysis of the existing methods of generating SI, we propose a new SI generation method. Two categories of SI are generated by motion compensation frame interpolation(MCFI) and optical flow interpolation, and then they are fused based on a probability fusion method to obtain more accurate SI. The experiment results indicate that the Hybrid SI generation algorithm proposed in this work can effectively improve the quality of SI.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127223418","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118603
Huazhi Dong, Yushan Qian, Linlin Wang, Pei Lu
Generative Adversarial Network (GAN) is a kind of deep learning model and one of the most promising methods for unsupervised learning in complex distribution in recent years. Due to the need for higher hardware support, it has certain limitations in practical application. Therefore, how to use the fast-developing Web technology and Cloud technology to promote and share it is a difficult problem. To address this issue, the theme is based on the hot model of GAN, combined with the thinkPHP framework, using python and php language, then, by means of the Cloud computing technology and bootstrap technology, the interactive response system for image style transformation between the mobile terminal and the server terminal is subsequently realized, which conforms to the development trend and expansion characteristics of the mobile terminal. This scheme can be promoted to art creators or the general public to meet their needs for artistic inspiration or image style transformation and ultimately to achieve a complete chain of resource collection, information processing and service feedback.
{"title":"The Application of Image Style Transformation Based on GAN in the Intelligent Mobile Terminal","authors":"Huazhi Dong, Yushan Qian, Linlin Wang, Pei Lu","doi":"10.1109/ICCCS49078.2020.9118603","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118603","url":null,"abstract":"Generative Adversarial Network (GAN) is a kind of deep learning model and one of the most promising methods for unsupervised learning in complex distribution in recent years. Due to the need for higher hardware support, it has certain limitations in practical application. Therefore, how to use the fast-developing Web technology and Cloud technology to promote and share it is a difficult problem. To address this issue, the theme is based on the hot model of GAN, combined with the thinkPHP framework, using python and php language, then, by means of the Cloud computing technology and bootstrap technology, the interactive response system for image style transformation between the mobile terminal and the server terminal is subsequently realized, which conforms to the development trend and expansion characteristics of the mobile terminal. This scheme can be promoted to art creators or the general public to meet their needs for artistic inspiration or image style transformation and ultimately to achieve a complete chain of resource collection, information processing and service feedback.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"486 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124419668","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118466
Chen Chen, Ping Lu, Siqi Wang, Zijie Li
In allusion to the current common acupoint recognition is based on the edge extraction of neural network, which is affected by too many factors of human, there are certain interferences and errors in finding acupoints. This paper put forward a novel method combining posture tracking algorithm with proportional bone measurement, which can fully fit the skeleton of human body to provide a new idea for acupoint recognition of massage robot, and improve its accuracy and efficiency. The above method is simulated in Python to realize the function of massage robot to find acupoints automatically. The result shows that it takes less time to find more accurate and more quantities acupoints.
{"title":"PoseNet Based Acupoint Recognition of Blind Massage Robot","authors":"Chen Chen, Ping Lu, Siqi Wang, Zijie Li","doi":"10.1109/ICCCS49078.2020.9118466","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118466","url":null,"abstract":"In allusion to the current common acupoint recognition is based on the edge extraction of neural network, which is affected by too many factors of human, there are certain interferences and errors in finding acupoints. This paper put forward a novel method combining posture tracking algorithm with proportional bone measurement, which can fully fit the skeleton of human body to provide a new idea for acupoint recognition of massage robot, and improve its accuracy and efficiency. The above method is simulated in Python to realize the function of massage robot to find acupoints automatically. The result shows that it takes less time to find more accurate and more quantities acupoints.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117354462","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118413
J. Sa, Zhihao Li, Qijun Yang, Xuan Chen
Detecting packaging defection with high accuracy and efficiency is of great significance in product quality. We use OpenCV to preprocess images which come from damaged package according to characteristics of the image. The processed data is combined with deep learning and based on neural network model ResNet. Meanwhile the processed image data is sent to a convolutional neural network (CNN) for model training. We establish a detection system for product packaging. The detection system provides a solution for automatic detection of package defection, which realizes rapid and accurate detection of product packaging.
{"title":"Packaging Defect Detection System Based on Machine Vision and Deep Learning","authors":"J. Sa, Zhihao Li, Qijun Yang, Xuan Chen","doi":"10.1109/ICCCS49078.2020.9118413","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118413","url":null,"abstract":"Detecting packaging defection with high accuracy and efficiency is of great significance in product quality. We use OpenCV to preprocess images which come from damaged package according to characteristics of the image. The processed data is combined with deep learning and based on neural network model ResNet. Meanwhile the processed image data is sent to a convolutional neural network (CNN) for model training. We establish a detection system for product packaging. The detection system provides a solution for automatic detection of package defection, which realizes rapid and accurate detection of product packaging.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"50 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123696640","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118538
Yonglin Ju, Zhiwen Liu, Yougen Xu
Subspace-based methods are attractive solutions to localization problems due to their satisfactory performance and super-resolution property. In large-scale MIMO systems, the prohibitive computational complexity induced by direct eigenvalue decomposition of the high-dimensional covariance matrix severely limits their practical application. In this paper, a Nyström-based method is proposed to solve the complexity problem. A randomized SVD procedure embedded with orthogonal iteration is introduced into the proposed method which releases the computational burden to a big extent. To address the degradation problem of the proposed method in low SNR scenario, an approximate noiseless covariance matrix is devised based on Nyström approximation. Numerical experiments indicate that the proposed method can obtain adequate performance compared with the standard Nyström method as well as the classical subspace-based method, while the complexity of the proposed method is further reduced which makes it a more practical option in large-scale MIMO systems.
{"title":"A Nyström-Based Method for Incoherently Distributed Source Localization","authors":"Yonglin Ju, Zhiwen Liu, Yougen Xu","doi":"10.1109/ICCCS49078.2020.9118538","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118538","url":null,"abstract":"Subspace-based methods are attractive solutions to localization problems due to their satisfactory performance and super-resolution property. In large-scale MIMO systems, the prohibitive computational complexity induced by direct eigenvalue decomposition of the high-dimensional covariance matrix severely limits their practical application. In this paper, a Nyström-based method is proposed to solve the complexity problem. A randomized SVD procedure embedded with orthogonal iteration is introduced into the proposed method which releases the computational burden to a big extent. To address the degradation problem of the proposed method in low SNR scenario, an approximate noiseless covariance matrix is devised based on Nyström approximation. Numerical experiments indicate that the proposed method can obtain adequate performance compared with the standard Nyström method as well as the classical subspace-based method, while the complexity of the proposed method is further reduced which makes it a more practical option in large-scale MIMO systems.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129792768","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118546
Qing Qian, Yunhe Cui
Speech content is often faced with malicious forgery and tampering in transit. Therefore, we introduce a novel fragile watermarking algorithm by modifying the least significant digits for speech content authentication and tampering recovery. In this letter, the proposed authentication scheme consists of two processes: the first one is watermark generation and embedding, the second one is content authentication and recovery. In the former process, the compressed speech signal, frame number and check information are generated based on speech content to form a watermark. Subsequently, the generated watermark is embedded into the least significant digits of speech sampling points using the proposed watermarking algorithm. In the latter process, the embedded watermark is utilized to locate the tampered area and recover that tampered content synchronously. Experimental results show that the proposed watermarking algorithm is fragile to common signal processing. Additionally, it has favorable inaudibility, accurate location ability and high recovery quality.
{"title":"A Fragile Watermarking Algorithm for Speech Authentication by Modifying Least Significant Digits","authors":"Qing Qian, Yunhe Cui","doi":"10.1109/ICCCS49078.2020.9118546","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118546","url":null,"abstract":"Speech content is often faced with malicious forgery and tampering in transit. Therefore, we introduce a novel fragile watermarking algorithm by modifying the least significant digits for speech content authentication and tampering recovery. In this letter, the proposed authentication scheme consists of two processes: the first one is watermark generation and embedding, the second one is content authentication and recovery. In the former process, the compressed speech signal, frame number and check information are generated based on speech content to form a watermark. Subsequently, the generated watermark is embedded into the least significant digits of speech sampling points using the proposed watermarking algorithm. In the latter process, the embedded watermark is utilized to locate the tampered area and recover that tampered content synchronously. Experimental results show that the proposed watermarking algorithm is fragile to common signal processing. Additionally, it has favorable inaudibility, accurate location ability and high recovery quality.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128600867","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118595
Zijie Li, Kun Zhang, Jiangguo Wu, Ping Lu
There are many methods of thread measurement. In addition, these thread measurement methods require manual segmentation of regions of interest (threaded area) and These methods are easily disturbed by the environment (e.g. dust, iron filings, oil stains, etc.), resulting in inaccurate measurement results. This paper proposes an external thread measurement method based on ResUnet and hidden Markov model (HMM). First, we propose a ResUnet-based thread edge recognition method that omits the process of calibrating the threaded area and identify the thread edge in a complex environment. Secondly, we use HMM to classify the thread edge points so that the threaded parts can be placed at any angle during the measurement, simplifying the measurement steps and calculating the thread parameters based on the classification results. Finally, we evaluated our method using our own dataset, and the results showed that the difference between the measured value and the standard value is within 0.01 mm.
{"title":"External Thread Measurement Based on ResUnet and HMM","authors":"Zijie Li, Kun Zhang, Jiangguo Wu, Ping Lu","doi":"10.1109/ICCCS49078.2020.9118595","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118595","url":null,"abstract":"There are many methods of thread measurement. In addition, these thread measurement methods require manual segmentation of regions of interest (threaded area) and These methods are easily disturbed by the environment (e.g. dust, iron filings, oil stains, etc.), resulting in inaccurate measurement results. This paper proposes an external thread measurement method based on ResUnet and hidden Markov model (HMM). First, we propose a ResUnet-based thread edge recognition method that omits the process of calibrating the threaded area and identify the thread edge in a complex environment. Secondly, we use HMM to classify the thread edge points so that the threaded parts can be placed at any angle during the measurement, simplifying the measurement steps and calculating the thread parameters based on the classification results. Finally, we evaluated our method using our own dataset, and the results showed that the difference between the measured value and the standard value is within 0.01 mm.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129563269","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}
Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118430
Shuangyin Ren, Gaigai Tang
Software Defined Networks paradigm decouples network control from switches and is directly programmable. A relatively centralized control plane together with developed APIs between control and data plane allows it to retrieve a global view of network traffic. Traffic estimation algorithm, which aims to generate a realtime and precise traffic flow undergoing with acceptable overhead, is fundamental for traffic engineering and QoS guarantee. A few traffic estimation algorithms is proposed based on Software Defined Networks paradigm, such as Flowsense and Payless. We propose a reactive traffic estimation algorithm to retrieve network traffic information. This reactive traffic estimation algorithm sends two query messages after a flow table is installed, and estimates upper bound bandwidth. We run a simulation on Mininet with Ryu as controller and OVS as data plane switch to test proposed algorithm. Simulation shows that this algorithm shows a better comprehensive performance in aspect of realtime and bandwidth overhead.
{"title":"A Reactive Traffic Flow Estimation in Software Defined Networks","authors":"Shuangyin Ren, Gaigai Tang","doi":"10.1109/ICCCS49078.2020.9118430","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118430","url":null,"abstract":"Software Defined Networks paradigm decouples network control from switches and is directly programmable. A relatively centralized control plane together with developed APIs between control and data plane allows it to retrieve a global view of network traffic. Traffic estimation algorithm, which aims to generate a realtime and precise traffic flow undergoing with acceptable overhead, is fundamental for traffic engineering and QoS guarantee. A few traffic estimation algorithms is proposed based on Software Defined Networks paradigm, such as Flowsense and Payless. We propose a reactive traffic estimation algorithm to retrieve network traffic information. This reactive traffic estimation algorithm sends two query messages after a flow table is installed, and estimates upper bound bandwidth. We run a simulation on Mininet with Ryu as controller and OVS as data plane switch to test proposed algorithm. Simulation shows that this algorithm shows a better comprehensive performance in aspect of realtime and bandwidth overhead.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129621004","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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