Pub Date : 2021-11-09DOI: 10.15837/ijccc.2021.6.4519
Ioan Dumitrache, Simona Iuliana Caramihai, Dragos Constantin Popescu, Mihnea Alexandru Moisescu, Ioan Stefan Sacala
There are currently certain categories of manufacturing enterprises whose structure, organization and operating context have an extremely high degree of complexity, especially due to the way in which their various components interact and influence each other. For them, a series of paradigms have been developed, including intelligent manufacturing, smart manufacturing, cognitive manufacturing; which are based equally on information and knowledge management, management and interpretation of data flows and problem solving approaches. This work presents a new vision regarding the evolution of the future enterprise based on concepts and attributes acquired from the field of biology. Our approach addresses in a systemic manner the structural, functional, and behavioral aspects of the enterprise, seen as a complex dynamic system. In this article we are proposing an architecture and management methodology based on the human brain, where the problem solving is achieved by Perception – Memory – Learning and Behavior Generation mechanisms. In order to support the design of such an architecture and to allow a faster learning process, a software modeling and simulation platform was developed and is briefly presented.
{"title":"Neuro-inspired Framework for Cognitive Manufacturing Control","authors":"Ioan Dumitrache, Simona Iuliana Caramihai, Dragos Constantin Popescu, Mihnea Alexandru Moisescu, Ioan Stefan Sacala","doi":"10.15837/ijccc.2021.6.4519","DOIUrl":"https://doi.org/10.15837/ijccc.2021.6.4519","url":null,"abstract":"There are currently certain categories of manufacturing enterprises whose structure, organization and operating context have an extremely high degree of complexity, especially due to the way in which their various components interact and influence each other. For them, a series of paradigms have been developed, including intelligent manufacturing, smart manufacturing, cognitive manufacturing; which are based equally on information and knowledge management, management and interpretation of data flows and problem solving approaches. This work presents a new vision regarding the evolution of the future enterprise based on concepts and attributes acquired from the field of biology. Our approach addresses in a systemic manner the structural, functional, and behavioral aspects of the enterprise, seen as a complex dynamic system. In this article we are proposing an architecture and management methodology based on the human brain, where the problem solving is achieved by Perception – Memory – Learning and Behavior Generation mechanisms. In order to support the design of such an architecture and to allow a faster learning process, a software modeling and simulation platform was developed and is briefly presented.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"33 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138536635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-17DOI: 10.15837/IJCCC.2019.5.3629
Lin Tao, Wu Peng, Gao Fengmei, Wu Tianshu
The mobile ad hoc network (MANET) is more vulnerable to attacks than traditional networks, due to the high mobility of nodes, the weakness of transmission media and the absence of central node. To overcome the vulnerability, this paper mainly studies the way to detect selfish nodes in the MANET, and thus prevent network intrusion. Specifically, a data-driven reputation evaluation model was proposed to detect selfish nodes using a new reputation mechanism. The mechanism consists of a monitoring module, a reputation evaluation module, penalty module and a response module. The MANET integrated with our reputation mechanism was compared with the traditional MANET through simulation. The results show that the addition of reputation mechanism can suppress the selfish behavior of network nodes and enhance network security.
{"title":"Intrusion Detection for Mobile Ad Hoc Networks Based on Node Reputation","authors":"Lin Tao, Wu Peng, Gao Fengmei, Wu Tianshu","doi":"10.15837/IJCCC.2019.5.3629","DOIUrl":"https://doi.org/10.15837/IJCCC.2019.5.3629","url":null,"abstract":"The mobile ad hoc network (MANET) is more vulnerable to attacks than traditional networks, due to the high mobility of nodes, the weakness of transmission media and the absence of central node. To overcome the vulnerability, this paper mainly studies the way to detect selfish nodes in the MANET, and thus prevent network intrusion. Specifically, a data-driven reputation evaluation model was proposed to detect selfish nodes using a new reputation mechanism. The mechanism consists of a monitoring module, a reputation evaluation module, penalty module and a response module. The MANET integrated with our reputation mechanism was compared with the traditional MANET through simulation. The results show that the addition of reputation mechanism can suppress the selfish behavior of network nodes and enhance network security.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"14 1","pages":"660-671"},"PeriodicalIF":2.7,"publicationDate":"2019-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67604696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-12DOI: 10.15837/ijccc.2018.1.3176
Weidong Huang, Qian Wang, Jie Cao
Social network has become the main communication platform for public emergencies, and it has also made the public opinion influence spread more widely. How to effectively obtain public opinions from it to guide the healthy development of the society is an important issue that the government and other functional departments are concerned about. However, the interaction and evolution mechanism between the subject and the environment in the public opinion propagation is complicated, and the public and media attention and reaction to the incident are closely linked with the progress of the incident disposal. And public mining corpus has some shortcomings in the distribution of emotional classification. Only the timely update of artificial rules and emotional dictionary resources, it can handle new text data well. In fact, from the perspective of public opinion propagation, this paper built the network matrix between Internet users through the forwarding relationship, and used the social network analysis method and the emotion mining analysis technology to study the interaction and evolution mechanism between the subject and the environment in the public opinion propagation, and it studied the role of users in the emotional propagation of social networks. This paper proposed a sentiment analysis method on the micro-blog platform, which expanded the emotional dictionary and took sentence and emoticon and sentence patterns into account, which improved the accuracy of positive and negative classifications and emotional polarity analysis of the micro-blog.
{"title":"Tracing Public Opinion Propagation and Emotional Evolution Based on Public Emergencies in Social Networks","authors":"Weidong Huang, Qian Wang, Jie Cao","doi":"10.15837/ijccc.2018.1.3176","DOIUrl":"https://doi.org/10.15837/ijccc.2018.1.3176","url":null,"abstract":"Social network has become the main communication platform for public emergencies, and it has also made the public opinion influence spread more widely. How to effectively obtain public opinions from it to guide the healthy development of the society is an important issue that the government and other functional departments are concerned about. However, the interaction and evolution mechanism between the subject and the environment in the public opinion propagation is complicated, and the public and media attention and reaction to the incident are closely linked with the progress of the incident disposal. And public mining corpus has some shortcomings in the distribution of emotional classification. Only the timely update of artificial rules and emotional dictionary resources, it can handle new text data well. In fact, from the perspective of public opinion propagation, this paper built the network matrix between Internet users through the forwarding relationship, and used the social network analysis method and the emotion mining analysis technology to study the interaction and evolution mechanism between the subject and the environment in the public opinion propagation, and it studied the role of users in the emotional propagation of social networks. This paper proposed a sentiment analysis method on the micro-blog platform, which expanded the emotional dictionary and took sentence and emoticon and sentence patterns into account, which improved the accuracy of positive and negative classifications and emotional polarity analysis of the micro-blog.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"13 1","pages":"129-142"},"PeriodicalIF":2.7,"publicationDate":"2018-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67604285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.15837/ijccc.2018.1.3104
X Lin, Y Liang, L Wang, X Wang, M Yang, R Guan
Large-scale knowledge bases, as the foundations for promoting the development of artificial intelligence, have attracted increasing attention in recent years. These knowledge bases contain billions of facts in triple format; yet, they suffer from sparse relations between entities. Researchers proposed the path ranking algorithm (PRA) to solve this fatal problem. To improve the scalability of knowledge inference, PRA exploits random walks to find Horn clauses with chain structures to predict new relations given existing facts. This method can be regarded as a statistical classification issue for statistical relational learning (SRL). However, large-scale knowledge base completion demands superior accuracy and scalability. In this paper, we propose the path feature learning model (PFLM) to achieve this urgent task. More precisely, we define a two-stage model: the first stage aims to learn path features from the existing knowledge base and extra parsed corpus; the second stage uses these path features to predict new relations. The experimental results demonstrate that the PFLM can learn meaningful features and can achieve significant and consistent improvements compared with previous work.
{"title":"A Knowledge Base Completion Model Based on Path Feature Learning.","authors":"X Lin, Y Liang, L Wang, X Wang, M Yang, R Guan","doi":"10.15837/ijccc.2018.1.3104","DOIUrl":"https://doi.org/10.15837/ijccc.2018.1.3104","url":null,"abstract":"<p><p>Large-scale knowledge bases, as the foundations for promoting the development of artificial intelligence, have attracted increasing attention in recent years. These knowledge bases contain billions of facts in triple format; yet, they suffer from sparse relations between entities. Researchers proposed the path ranking algorithm (PRA) to solve this fatal problem. To improve the scalability of knowledge inference, PRA exploits random walks to find Horn clauses with chain structures to predict new relations given existing facts. This method can be regarded as a statistical classification issue for statistical relational learning (SRL). However, large-scale knowledge base completion demands superior accuracy and scalability. In this paper, we propose the path feature learning model (PFLM) to achieve this urgent task. More precisely, we define a two-stage model: the first stage aims to learn path features from the existing knowledge base and extra parsed corpus; the second stage uses these path features to predict new relations. The experimental results demonstrate that the PFLM can learn meaningful features and can achieve significant and consistent improvements compared with previous work.</p>","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"13 1","pages":"71-82"},"PeriodicalIF":2.7,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9275121/pdf/nihms-1767576.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40591768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.15837/ijccc.2018.3.3044
V. Phu
{"title":"Latent Semantic Analysis using a Dennis Coefficient for English Sentiment Classification in a Parallel System","authors":"V. Phu","doi":"10.15837/ijccc.2018.3.3044","DOIUrl":"https://doi.org/10.15837/ijccc.2018.3.3044","url":null,"abstract":"","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"73 1","pages":"408-428"},"PeriodicalIF":2.7,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67604991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-01DOI: 10.15837/ijccc.2017.3.2842
P. E. Mendez-Monroy
{"title":"Walking Motion Generation and Neuro-Fuzzy Control with Push Recovery for Humanoid Robot","authors":"P. E. Mendez-Monroy","doi":"10.15837/ijccc.2017.3.2842","DOIUrl":"https://doi.org/10.15837/ijccc.2017.3.2842","url":null,"abstract":"","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"12 1","pages":"330-346"},"PeriodicalIF":2.7,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67604671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-18DOI: 10.15837/ijccc.2012.3.1387
Feng Yin, Yaonan Wang, Yi-min Yang
Neural networks with their inherent learning ability have been widely applied to solve the robot manipulator inverse kinematics problems. However, there are still two open problems: (1) without knowing inverse kinematic expressions, these solutions have the difficulty of how to collect training sets, and (2) the gradient-based learning algorithms can cause a very slow training process, especially for a complex configuration, or a large set of training data. Unlike these traditional implementations, the proposed metho trains neural network in joint subspace which can be easily calculated with electromagnetism-like method. The kinematics equation and its inverse are one-to-one mapping within the subspace. Thus the constrained training sets can be easily collected by forward kinematics relations. For issue 2, this paper uses a novel learning algorithm called extreme learning machine (ELM) which randomly choose the input weights and analytically determines the output weights of the single hidden layer feedforward neural networks (SLFNs). In theory, this algorithm tends to provide the best generalization performance at extremely fast learning speed. The results show that the proposed approach has not only greatly reduced the computation time but also improved the precision.
{"title":"Inverse Kinematics Solution for Robot Manipulator based on Neural Network under Joint Subspace","authors":"Feng Yin, Yaonan Wang, Yi-min Yang","doi":"10.15837/ijccc.2012.3.1387","DOIUrl":"https://doi.org/10.15837/ijccc.2012.3.1387","url":null,"abstract":"Neural networks with their inherent learning ability have been widely applied to solve the robot manipulator inverse kinematics problems. However, there are still two open problems: (1) without knowing inverse kinematic expressions, these solutions have the difficulty of how to collect training sets, and (2) the gradient-based learning algorithms can cause a very slow training process, especially for a complex configuration, or a large set of training data. Unlike these traditional implementations, the proposed metho trains neural network in joint subspace which can be easily calculated with electromagnetism-like method. The kinematics equation and its inverse are one-to-one mapping within the subspace. Thus the constrained training sets can be easily collected by forward kinematics relations. For issue 2, this paper uses a novel learning algorithm called extreme learning machine (ELM) which randomly choose the input weights and analytically determines the output weights of the single hidden layer feedforward neural networks (SLFNs). In theory, this algorithm tends to provide the best generalization performance at extremely fast learning speed. The results show that the proposed approach has not only greatly reduced the computation time but also improved the precision.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"7 1","pages":"459-472"},"PeriodicalIF":2.7,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67604463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper states a novel, Evolutionary Metaheuristic Based on the Automata Theory (EMODS) for the multiobjective optimization of combinatorial problems. The proposed algorithm uses the natural selection theory in order to explore the feasible solutions space of a combinatorial problem. Due to this, local optimums are often avoided. Also, EMODS exploits the optimization process from the Metaheuristic of Deterministic Swapping to avoid finding unfeasible solutions. The proposed algorithm was tested using well known multi-objective TSP instances from the TSPLIB. Its results were compared against others Automata Theory inspired Algorithms using metrics from the specialized literature. In every case, the EMODS results on the metrics were always better and in some of those cases, the distance from the true solutions was 0.89%.
{"title":"Evolutionary Algorithm based on the Automata Theory for the Multi-objective Optimization of Combinatorial Problems","authors":"Elias D. Niño","doi":"10.5772/36101","DOIUrl":"https://doi.org/10.5772/36101","url":null,"abstract":"This paper states a novel, Evolutionary Metaheuristic Based on the Automata Theory (EMODS) for the multiobjective optimization of combinatorial problems. The proposed algorithm uses the natural selection theory in order to explore the feasible solutions space of a combinatorial problem. Due to this, local optimums are often avoided. Also, EMODS exploits the optimization process from the Metaheuristic of Deterministic Swapping to avoid finding unfeasible solutions. The proposed algorithm was tested using well known multi-objective TSP instances from the TSPLIB. Its results were compared against others Automata Theory inspired Algorithms using metrics from the specialized literature. In every case, the EMODS results on the metrics were always better and in some of those cases, the distance from the true solutions was 0.89%.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"7 1","pages":"916-923"},"PeriodicalIF":2.7,"publicationDate":"2014-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70923077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.15837/ijccc.2013.3.218
C. Dragos, R. Precup, Marius-Lucian Tomescu, S. Preitl, E. Petriu, M. Radac
{"title":"An Approach to Fuzzy Modeling of Electromagnetic Actuated Clutch Systems","authors":"C. Dragos, R. Precup, Marius-Lucian Tomescu, S. Preitl, E. Petriu, M. Radac","doi":"10.15837/ijccc.2013.3.218","DOIUrl":"https://doi.org/10.15837/ijccc.2013.3.218","url":null,"abstract":"","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"8 1","pages":"395-406"},"PeriodicalIF":2.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67604554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.15837/ijccc.2011.4.2095
M. Qu, Xianghu Wu, Xiao-Zong Yang
Creation of multi-copies accelerates data transmission and reduces network traffic, but it causes overhead storage and additional network traffic. A variety of parallel transmission algorithms based on GridFTP and multi-copy can be used to accelerate data transmission further, but they can not adapt to a wide range of network, and they can not be used to solve the problems of storage space and network traffic waste. GridTorrent combined with BitTorrent and GridFTP has compatibility with grid and has flexible scalability, but the speed is very slow when there are few peers, to solve this problem multicopy is needed also. To achieve multiple optimization objectives of storage space saving, suitable for two kinds of application modes(i.e. parallel transfer based on GridFTP and BitTorrent), adaptability for wide range of network and higher performance when there are fewer peers, based on the idea of GridTorrent, a distributed storage model, parallel transfer algorithm and virtual peer strategy are proposed. In experiments the performance is compared among the verification system VPG-Torrent and original parallel transfer algorithm (DCDA) only based on GridfTP & multi-copy and GridTorrent. When the same amount of data is deployed VPG-Torrent has better performance than DCDA, and when there are fewer peers VPG-Torrent also exceed GridTorrent, which prove the effectiveness of VPG-Torrent.
{"title":"A Novel Parallel Transmission Strategy for Data Grid","authors":"M. Qu, Xianghu Wu, Xiao-Zong Yang","doi":"10.15837/ijccc.2011.4.2095","DOIUrl":"https://doi.org/10.15837/ijccc.2011.4.2095","url":null,"abstract":"Creation of multi-copies accelerates data transmission and reduces network traffic, but it causes overhead storage and additional network traffic. A variety of parallel transmission algorithms based on GridFTP and multi-copy can be used to accelerate data transmission further, but they can not adapt to a wide range of network, and they can not be used to solve the problems of storage space and network traffic waste. GridTorrent combined with BitTorrent and GridFTP has compatibility with grid and has flexible scalability, but the speed is very slow when there are few peers, to solve this problem multicopy is needed also. To achieve multiple optimization objectives of storage space saving, suitable for two kinds of application modes(i.e. parallel transfer based on GridFTP and BitTorrent), adaptability for wide range of network and higher performance when there are fewer peers, based on the idea of GridTorrent, a distributed storage model, parallel transfer algorithm and virtual peer strategy are proposed. In experiments the performance is compared among the verification system VPG-Torrent and original parallel transfer algorithm (DCDA) only based on GridfTP & multi-copy and GridTorrent. When the same amount of data is deployed VPG-Torrent has better performance than DCDA, and when there are fewer peers VPG-Torrent also exceed GridTorrent, which prove the effectiveness of VPG-Torrent.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"6 1","pages":"681-700"},"PeriodicalIF":2.7,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67604255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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