Pub Date : 2020-05-01DOI: 10.1109/ICCCS49078.2020.9118579
Farhan Amin, G. Choi
Social Internet of Things (SIoT) is a new model that has integrated into two technologies, Internet of Things (IoT) and Social Networks. The SIoT defines as a social network of objects that are not only smarter but also socially conscious. The major issues related to IoT are; communication between the objects, service composition and service discovery. To address the after-mentioned needs, this paper proposes a possible approach named social pal. The social pal collects and provides the information to the IoT, and hence our proposed social network provides glue to allow the human to device interaction. This study leverages the social relationships among the participants (devices and users) in the system for delivering the required services to the users. By using this platform the capability to select and find the devices, discover the services in the IoT paradigm is augmented. Briefly, the main features of social pal are; create an object, define the relationship, find and discover the pairs of objects that can offer services, etc.
社交物联网(Social Internet of Things, SIoT)是一种融合了物联网(Internet of Things, IoT)和社交网络(Social Networks)两种技术的新模式。SIoT将其定义为一个不仅更智能而且具有社会意识的物体的社交网络。与物联网相关的主要问题有:对象之间的通信、服务组合和服务发现。为了解决上述需求，本文提出了一种可能的方法，称为社交伙伴。社交伙伴收集并提供信息给物联网，因此我们提出的社交网络提供了胶水，允许人与设备交互。本研究利用系统中参与者(设备和用户)之间的社会关系为用户提供所需的服务。通过使用该平台，增强了在物联网范式中选择和查找设备、发现服务的能力。简而言之，社交伙伴的主要特征有:创建对象，定义关系，查找和发现可以提供服务的对象对，等等。
{"title":"Social Pal: A Combined Platform for Internet of Things and Social Networks","authors":"Farhan Amin, G. Choi","doi":"10.1109/ICCCS49078.2020.9118579","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118579","url":null,"abstract":"Social Internet of Things (SIoT) is a new model that has integrated into two technologies, Internet of Things (IoT) and Social Networks. The SIoT defines as a social network of objects that are not only smarter but also socially conscious. The major issues related to IoT are; communication between the objects, service composition and service discovery. To address the after-mentioned needs, this paper proposes a possible approach named social pal. The social pal collects and provides the information to the IoT, and hence our proposed social network provides glue to allow the human to device interaction. This study leverages the social relationships among the participants (devices and users) in the system for delivering the required services to the users. By using this platform the capability to select and find the devices, discover the services in the IoT paradigm is augmented. Briefly, the main features of social pal are; create an object, define the relationship, find and discover the pairs of objects that can offer services, etc.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"40 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":"115444441","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/ICCCS49078.2020.9118487
R. Zhao, Yan Wang, Qiong Liu, Daheng Dong, Cuiling Li
In recent years, people’s demand for data analysis and knowledge acquisition from big data is becoming more urgent. Large-scale crowd evacuation also requires a wealth of decision-making knowledge to provide emergency solution guidance. This paper corresponds the crowd size to the granularity of knowledge objects, and proposes a variablegrained knowledge acquisition model for the evolution mechanism of crowd evacuation stability. The rough set matrix calculation model is used to generate the meta-rules. Through the rigorous discretization of the reversible process analysis logic, the meta-rules are automatically simplified into generalized rules with evacuation guiding significance. The explicit knowledge of stability situation in crowd evacuation is discovered. This study provides a scientific decision-making method for timely and accuratejudgment of the crowd stability, rational organization and guidance of safe evacuation, and also provides scientific basis for the prevention of malignant crowding and trampling events with important theoretical and social significance.
{"title":"Knowledge Acquisition Model for Stability Situation Judgement Used in Crowd Evacuation","authors":"R. Zhao, Yan Wang, Qiong Liu, Daheng Dong, Cuiling Li","doi":"10.1109/ICCCS49078.2020.9118487","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118487","url":null,"abstract":"In recent years, people’s demand for data analysis and knowledge acquisition from big data is becoming more urgent. Large-scale crowd evacuation also requires a wealth of decision-making knowledge to provide emergency solution guidance. This paper corresponds the crowd size to the granularity of knowledge objects, and proposes a variablegrained knowledge acquisition model for the evolution mechanism of crowd evacuation stability. The rough set matrix calculation model is used to generate the meta-rules. Through the rigorous discretization of the reversible process analysis logic, the meta-rules are automatically simplified into generalized rules with evacuation guiding significance. The explicit knowledge of stability situation in crowd evacuation is discovered. This study provides a scientific decision-making method for timely and accuratejudgment of the crowd stability, rational organization and guidance of safe evacuation, and also provides scientific basis for the prevention of malignant crowding and trampling events with important theoretical and social significance.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"47 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":"125815852","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/icccs49078.2020.9118565
{"title":"ICCCS 2020 Table of Contents","authors":"","doi":"10.1109/icccs49078.2020.9118565","DOIUrl":"https://doi.org/10.1109/icccs49078.2020.9118565","url":null,"abstract":"","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"11 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":"126825020","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/ICCCS49078.2020.9118597
Yunhe Cui, Qing Qian
Distributed Denial of Service (DDoS) is quite a serious security issue existing in Software-Defined Networking (SDN). In order to mitigate DDoS attack, we present MIND, a message classification based controller scheduling method, where how to store and process messages is designed based on analyzing and classifying the OpenFlow messages received by SDN controller. The experiment results validate that the proposed controller scheduling method can significantly improve the availability of SDN controller under DDoS attack.
{"title":"MIND: Message Classification Based Controller Scheduling Method for Resisting DDoS Attack in Software-Defined Networking","authors":"Yunhe Cui, Qing Qian","doi":"10.1109/ICCCS49078.2020.9118597","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118597","url":null,"abstract":"Distributed Denial of Service (DDoS) is quite a serious security issue existing in Software-Defined Networking (SDN). In order to mitigate DDoS attack, we present MIND, a message classification based controller scheduling method, where how to store and process messages is designed based on analyzing and classifying the OpenFlow messages received by SDN controller. The experiment results validate that the proposed controller scheduling method can significantly improve the availability of SDN controller under DDoS attack.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"37 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":"115328831","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/ICCCS49078.2020.9118547
Thomas Gabor, Sebastian Zieliński, Christoph Roch, Sebastian Feld, Claudia Linnhoff-Popien
Quantum Annealing is an algorithm for solving instances of quadratic unconstrained binary optimization (QUBO) that is implemented in hardware utilizing quantum effects to quickly find approximate solutions. However, QUBO can obviously also be solved by any classical optimization technique, for which various implementations exist. The UQ platform provides a unified interface to various means of solving QUBO that allows for a seamless switch between classical and quantum methods while implementing features such as load and user management.
{"title":"The U Q Platform: A U nifed Approach To Q uantum Annealing","authors":"Thomas Gabor, Sebastian Zieliński, Christoph Roch, Sebastian Feld, Claudia Linnhoff-Popien","doi":"10.1109/ICCCS49078.2020.9118547","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118547","url":null,"abstract":"Quantum Annealing is an algorithm for solving instances of quadratic unconstrained binary optimization (QUBO) that is implemented in hardware utilizing quantum effects to quickly find approximate solutions. However, QUBO can obviously also be solved by any classical optimization technique, for which various implementations exist. The UQ platform provides a unified interface to various means of solving QUBO that allows for a seamless switch between classical and quantum methods while implementing features such as load and user management.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"94 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":"116454534","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/ICCCS49078.2020.9118508
Siying Wu, Huilin Zhou
Since the dimension of the measured scattering field is usually much smaller than the dimension of the unknown parameter, this makes the electromagnetic field integral equation ill-conditioned, and the solution of the equation can be obtained using sparse constraint regularization. For this reason, this paper introduced a nonlinear electromagnetic field inverse scattering imaging algorithm under sparse domain, namely: sparse constraints subspace optimization method (SP-SOM) algorithm, the algorithm is used to reconstruct the spatial distribution information of electrical performance parameters of multi-media targets. To use the inexact Newton method, it can be handled that the scattered field equations is reconstructed using the SP-SOM algorithm. The simulation results show that SP-SOM algorithm can effectively reconstruct the spatial distribution information of electrical performance parameters.
{"title":"Research on Scatter Imaging Method for Electromagnetic Field Inverse Problem Based on Sparse Constraints","authors":"Siying Wu, Huilin Zhou","doi":"10.1109/ICCCS49078.2020.9118508","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118508","url":null,"abstract":"Since the dimension of the measured scattering field is usually much smaller than the dimension of the unknown parameter, this makes the electromagnetic field integral equation ill-conditioned, and the solution of the equation can be obtained using sparse constraint regularization. For this reason, this paper introduced a nonlinear electromagnetic field inverse scattering imaging algorithm under sparse domain, namely: sparse constraints subspace optimization method (SP-SOM) algorithm, the algorithm is used to reconstruct the spatial distribution information of electrical performance parameters of multi-media targets. To use the inexact Newton method, it can be handled that the scattered field equations is reconstructed using the SP-SOM algorithm. The simulation results show that SP-SOM algorithm can effectively reconstruct the spatial distribution information of electrical performance parameters.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"73 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":"114036160","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/ICCCS49078.2020.9118572
Xingchuan Liu, Lin Han, Jiang Zhu, Zhiwei Xu
Sparse Bayesian learning (SBL) has been a popular method for sparse signal recovery under the standard linear model (SLM). Since SBL involves a matrix inversion in each iteration, the computation complexity is usually very high when applied to problems with large data set. Consequently, an inversefree sparse Bayesian learning (IF-SBL) algorithm has been proposed to achieve lower reconstruction errors than other state-of-the-art fast sparse recovery methods in low signal-to-noise ratio (SNR) scenarios. In practice, many problems can be formulated as a generalized linear model (GLM) where measurements are obtained in a nonlinear way such as image classification and estimation from quantized data. This work develops inverse-free generalized sparse Bayesian learning (IF-Gr-SBL), which can be viewed as performing iterations between two modules, where one module performs the standard IF-SBL algorithm, the other module performs the minimum mean squared error (MMSE) estimation. Finally, numerical experiments show the effectiveness
{"title":"Fast Inverse-Free Generalized Sparse Bayesian Iearning Algorithm","authors":"Xingchuan Liu, Lin Han, Jiang Zhu, Zhiwei Xu","doi":"10.1109/ICCCS49078.2020.9118572","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118572","url":null,"abstract":"Sparse Bayesian learning (SBL) has been a popular method for sparse signal recovery under the standard linear model (SLM). Since SBL involves a matrix inversion in each iteration, the computation complexity is usually very high when applied to problems with large data set. Consequently, an inversefree sparse Bayesian learning (IF-SBL) algorithm has been proposed to achieve lower reconstruction errors than other state-of-the-art fast sparse recovery methods in low signal-to-noise ratio (SNR) scenarios. In practice, many problems can be formulated as a generalized linear model (GLM) where measurements are obtained in a nonlinear way such as image classification and estimation from quantized data. This work develops inverse-free generalized sparse Bayesian learning (IF-Gr-SBL), which can be viewed as performing iterations between two modules, where one module performs the standard IF-SBL algorithm, the other module performs the minimum mean squared error (MMSE) estimation. Finally, numerical experiments show the effectiveness","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"12 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":"116730510","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/ICCCS49078.2020.9118475
Guodong Li, Jinyi Sun, Xin Guo
Due to the increasing complexity of power grid, SGCC hopes to have a computer-aided decision-making scheme for ICT system fault identification. This paper proposes an ICT fault analysis technology which integrates text classification and image recognition. It aims to solve the problem that only relying on the knowledge reserve and personal experience of a single staff member is often unable to analyze and judge the fault of power grid system. In this paper, the main work is as follows: first, preprocess the ICT fault report data to get more easily recognized structured data by computer; second, build a text recognition model to classify the text content; then build an image recognition model to classify the image content; finally, integrating the text and image classification based on the above content, linear regression is applied to the weight parameters to improve the accuracy and reliability of the classification results. According to the test results of comprehensive test data, the accuracy of the method is good and it can be used as a reliable scheme test.
{"title":"An ICT System Fault Analysis Technology Based on Text Classification and Image Recognition","authors":"Guodong Li, Jinyi Sun, Xin Guo","doi":"10.1109/ICCCS49078.2020.9118475","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118475","url":null,"abstract":"Due to the increasing complexity of power grid, SGCC hopes to have a computer-aided decision-making scheme for ICT system fault identification. This paper proposes an ICT fault analysis technology which integrates text classification and image recognition. It aims to solve the problem that only relying on the knowledge reserve and personal experience of a single staff member is often unable to analyze and judge the fault of power grid system. In this paper, the main work is as follows: first, preprocess the ICT fault report data to get more easily recognized structured data by computer; second, build a text recognition model to classify the text content; then build an image recognition model to classify the image content; finally, integrating the text and image classification based on the above content, linear regression is applied to the weight parameters to improve the accuracy and reliability of the classification results. According to the test results of comprehensive test data, the accuracy of the method is good and it can be used as a reliable scheme test.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"224 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":"116855230","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}
Autonomous vehicle technology will make possibility of significant benefits to social welfare such as reducing traffic casualties, assisting the mobility of the elderly, and reducing the burden of driving. Among them, collision prediction and avoidance system are especially important topics in real road scenes. In order to realize a collision avoidance system, it is necessary to accurately grasp the surrounding environment of the self-location and predict the behavior of the target. Camera information or Light Detection and Ranging (LiDAR) information are used for behavior prediction. However, LiDAR is impractical due to its high cost. For camera information, the accuracy is lower than that of LiDAR, however there is a possibility that the accuracy can be compensated by introducing machine learning that has been developing in recent years. In this study, we investigate the usefulness of 3D box estimation in behavior prediction using camera information. In 3D box estimation, the dimensions and orientation of the target in the 2D box are regressed using a CNN model. We use MultiBin loss when we regress orientation. And we estimate final 3Dbox parameters based on regression values. Finally, we predict the trajectory using the center of the box and four vertices as inputs, and we verify its usefulness.
{"title":"Behavior Prediction Using 3D Box Estimation in Road Environment","authors":"Shinnosuke Kaida, Pornprom Kiawjak, Kousuke Matsushima","doi":"10.1109/ICCCS49078.2020.9118531","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118531","url":null,"abstract":"Autonomous vehicle technology will make possibility of significant benefits to social welfare such as reducing traffic casualties, assisting the mobility of the elderly, and reducing the burden of driving. Among them, collision prediction and avoidance system are especially important topics in real road scenes. In order to realize a collision avoidance system, it is necessary to accurately grasp the surrounding environment of the self-location and predict the behavior of the target. Camera information or Light Detection and Ranging (LiDAR) information are used for behavior prediction. However, LiDAR is impractical due to its high cost. For camera information, the accuracy is lower than that of LiDAR, however there is a possibility that the accuracy can be compensated by introducing machine learning that has been developing in recent years. In this study, we investigate the usefulness of 3D box estimation in behavior prediction using camera information. In 3D box estimation, the dimensions and orientation of the target in the 2D box are regressed using a CNN model. We use MultiBin loss when we regress orientation. And we estimate final 3Dbox parameters based on regression values. Finally, we predict the trajectory using the center of the box and four vertices as inputs, and we verify its usefulness.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"54 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":"129841690","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/ICCCS49078.2020.9118571
Meelis Kitsing
This paper explores the role of digital platforms and their potential future developments. It makes three contributions. First, the concept of digital platform ecosystem is introduced instead of platform economy. The development of digital platforms depends on a number of political and social factors in addition to economic and technological drivers. Particularly, the role of governance and institutions is emphasized for structuring platform ecosystems. Second, the future of digital platform ecosystems is explored on the basis of scenario planning. This approach allows to consider alternative future trajectories rather than rely on extrapolation of current trends. Last but not least, paper discusses different scenarios developed by international and national organizations which highlight potential futures for digital platform ecosystems.
{"title":"Scenarios for Digital Platform Ecosystems","authors":"Meelis Kitsing","doi":"10.1109/ICCCS49078.2020.9118571","DOIUrl":"https://doi.org/10.1109/ICCCS49078.2020.9118571","url":null,"abstract":"This paper explores the role of digital platforms and their potential future developments. It makes three contributions. First, the concept of digital platform ecosystem is introduced instead of platform economy. The development of digital platforms depends on a number of political and social factors in addition to economic and technological drivers. Particularly, the role of governance and institutions is emphasized for structuring platform ecosystems. Second, the future of digital platform ecosystems is explored on the basis of scenario planning. This approach allows to consider alternative future trajectories rather than rely on extrapolation of current trends. Last but not least, paper discusses different scenarios developed by international and national organizations which highlight potential futures for digital platform ecosystems.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"72 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":"114531418","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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