Pub Date : 2016-12-01DOI: 10.7763/IJCTE.2016.V8.1098
Li Zu, A. Yin, Yanyang Sun, Yulin Wang, Y. Ou, Yi Liang
{"title":"Deformation Analysis and Simulation of the Cup-Shaped Flexspline for Harmonic Drive Using in Aerocrafts","authors":"Li Zu, A. Yin, Yanyang Sun, Yulin Wang, Y. Ou, Yi Liang","doi":"10.7763/IJCTE.2016.V8.1098","DOIUrl":"https://doi.org/10.7763/IJCTE.2016.V8.1098","url":null,"abstract":"","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121551165","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 : 2016-12-01DOI: 10.7763/IJCTE.2016.V8.1096
Qiantu Zhang, Liqing Fang, Leilei Ma, Yulong Zhao
—The performance of the support vector machine (SVM) is determined to a great extent by the parameter selection. In order to improve the learning and generalization ability of SVM, in this paper, an improved fruit fly optimization algorithm (IFOA) was proposed to optimize kernel parameter and penalty factor of SVM. In IFOA, the fruit fly group is dynamically divided into advanced subgroup and drawback subgroup according to its own evolutionary level. A global search is made for the drawback subgroup under the guidance of the best individual and a finely local search is made for the advanced subgroup in which the fruit flies do Levy flight around the best individual. Two subgroups exchange information by updating the overall optimum and recombining the subgroups. Getting rid of local optimum and improve search ability are ensured by making those changes in basic FOA. The performance of the IFOA and classification accuracy of optimized SVM based on IFOA are respectively examined through several typical benchmark functions and classical data sets from UCI benchmark. The experiment results show that the performance of the new algorithm is obviously more successful than FOA and it is also an effective SVM parameter optimization method which has better performance than some other methods.
{"title":"Research on Parameters Optimization of SVM Based on Improved Fruit Fly Optimization Algorithm","authors":"Qiantu Zhang, Liqing Fang, Leilei Ma, Yulong Zhao","doi":"10.7763/IJCTE.2016.V8.1096","DOIUrl":"https://doi.org/10.7763/IJCTE.2016.V8.1096","url":null,"abstract":"—The performance of the support vector machine (SVM) is determined to a great extent by the parameter selection. In order to improve the learning and generalization ability of SVM, in this paper, an improved fruit fly optimization algorithm (IFOA) was proposed to optimize kernel parameter and penalty factor of SVM. In IFOA, the fruit fly group is dynamically divided into advanced subgroup and drawback subgroup according to its own evolutionary level. A global search is made for the drawback subgroup under the guidance of the best individual and a finely local search is made for the advanced subgroup in which the fruit flies do Levy flight around the best individual. Two subgroups exchange information by updating the overall optimum and recombining the subgroups. Getting rid of local optimum and improve search ability are ensured by making those changes in basic FOA. The performance of the IFOA and classification accuracy of optimized SVM based on IFOA are respectively examined through several typical benchmark functions and classical data sets from UCI benchmark. The experiment results show that the performance of the new algorithm is obviously more successful than FOA and it is also an effective SVM parameter optimization method which has better performance than some other methods.","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128661209","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 : 2016-10-01DOI: 10.7763/ijcte.2016.v8.1072
Zulfiqar Haider, Shuwen Chen, Muhammad Bux Burdey
{"title":"E-Government Project Obstacles in Pakistan","authors":"Zulfiqar Haider, Shuwen Chen, Muhammad Bux Burdey","doi":"10.7763/ijcte.2016.v8.1072","DOIUrl":"https://doi.org/10.7763/ijcte.2016.v8.1072","url":null,"abstract":"","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114747731","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 : 2016-10-01DOI: 10.7763/IJCTE.2016.V8.1085
Tawunrat Chalothorn, J. Ellman
This paper reports on the use of ensemble learning to classify as either positive or negative the sentiment of Tweets. Tweets were chosen as Twitter is a popular tool and a public, human annotated dataset was made available as part of the SemEval 2013 competition. We report on a classification approach that contrasts single machine learning algorithms with a combination of algorithms in an ensemble learning approach. The single machine learning algorithms used were support vector machine (SVM) and Naive Bayes (NB), while the methods of ensemble learning include the arbiter tree and the combiner tree. Our system achieved an F-score using Tweets and SMS with the arbiter tree at 83.57% and 93.55%, respectively, which was better than base classifiers; meanwhile, the results from the combiner tree achieved lower scores than base classifiers.
{"title":"Using Arbiter and Combiner Tree to Classify Contexts of Data","authors":"Tawunrat Chalothorn, J. Ellman","doi":"10.7763/IJCTE.2016.V8.1085","DOIUrl":"https://doi.org/10.7763/IJCTE.2016.V8.1085","url":null,"abstract":"This paper reports on the use of ensemble learning to classify as either positive or negative the sentiment of Tweets. Tweets were chosen as Twitter is a popular tool and a public, human annotated dataset was made available as part of the SemEval 2013 competition. We report on a classification approach that contrasts single machine learning algorithms with a combination of algorithms in an ensemble learning approach. The single machine learning algorithms used were support vector machine (SVM) and Naive Bayes (NB), while the methods of ensemble learning include the arbiter tree and the combiner tree. Our system achieved an F-score using Tweets and SMS with the arbiter tree at 83.57% and 93.55%, respectively, which was better than base classifiers; meanwhile, the results from the combiner tree achieved lower scores than base classifiers.","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121645943","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 : 2016-10-01DOI: 10.7763/ijcte.2016.v8.1083
M. Abid
Big data and Cloud computing are emerging as new promising technologies, gaining noticeable momentum in nowadays IT. Nowadays, and unprecedentedly, the amount of produced data exceeds all what has been generated since the dawn of computing; a fact which is mainly due to the pervasiveness of IT usage and to the ubiquity of Internet access. Nevertheless, this generated big data is only valuable if processed and mined. To process and mine big data, substantial HPC (high-performance computing) power is needed; a faculty which is not that affordable for most, unless we adopt for a convenient venue, e.g., cloud computing. In this paper, we propose a blue print for deploying a real-world HPC testbed. This will help simulating and evaluating HPC relevant concerns with minimum cost. Indeed, cloud computing provides the unique opportunity for circumventing the initial cost of owning private HPC platforms for big data processing, and this by providing HPC as a service (HPCaaS). In this paper, we present the subtleties of a synergetic “fitting” between big data and cloud computing. We delineate opportunities and address relevant challenges. To concretize, we advocate using private clouds instead of public ones, and propose using Hadoop along with MapReduce, on top of Openstack, as a promising venue for scientific communities to own research-oriented private clouds meant to provide HPCaaS for Big data mining.
{"title":"HPC (High-Performance the Computing) for Big Data on Cloud: Opportunities and Challenges","authors":"M. Abid","doi":"10.7763/ijcte.2016.v8.1083","DOIUrl":"https://doi.org/10.7763/ijcte.2016.v8.1083","url":null,"abstract":"Big data and Cloud computing are emerging as new promising technologies, gaining noticeable momentum in nowadays IT. Nowadays, and unprecedentedly, the amount of produced data exceeds all what has been generated since the dawn of computing; a fact which is mainly due to the pervasiveness of IT usage and to the ubiquity of Internet access. Nevertheless, this generated big data is only valuable if processed and mined. To process and mine big data, substantial HPC (high-performance computing) power is needed; a faculty which is not that affordable for most, unless we adopt for a convenient venue, e.g., cloud computing. In this paper, we propose a blue print for deploying a real-world HPC testbed. This will help simulating and evaluating HPC relevant concerns with minimum cost. Indeed, cloud computing provides the unique opportunity for circumventing the initial cost of owning private HPC platforms for big data processing, and this by providing HPC as a service (HPCaaS). In this paper, we present the subtleties of a synergetic “fitting” between big data and cloud computing. We delineate opportunities and address relevant challenges. To concretize, we advocate using private clouds instead of public ones, and propose using Hadoop along with MapReduce, on top of Openstack, as a promising venue for scientific communities to own research-oriented private clouds meant to provide HPCaaS for Big data mining.","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123386200","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 : 2016-10-01DOI: 10.7763/ijcte.2016.v8.1080
P. S. A. Devi, M. G. Mini
{"title":"PET Image Segmentation Based on Gabor Annulus Filtering and Region Growing","authors":"P. S. A. Devi, M. G. Mini","doi":"10.7763/ijcte.2016.v8.1080","DOIUrl":"https://doi.org/10.7763/ijcte.2016.v8.1080","url":null,"abstract":"","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123692315","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 : 2016-10-01DOI: 10.7763/IJCTE.2016.V8.1071
Islam Elgedawy
—To ensure reliable delivery for composite web services, we argue that Byzantine fault tolerance (BFT) must be guaranteed for the service delivery modules (such as BPEL execution engines and dispatchers) as well as for the realizing components of the composite web service. Existing BFT service delivery approaches are mainly focused on atomic web services. However, there are few approaches discussed BFT for composite web services delivery. Unfortunately, such approaches either ensured BFT for the service delivery modules alone or for the service realizing components alone; but not for both. To overcome such limitation, this paper proposes GEMINI; a hybrid BFT protocol for reliable composite web services orchestrated delivery. GEMINI uses a lightweight replication-based BFT protocol to ensure the BFT for service delivery modules, and uses a speculative quorum-based BFT protocol to ensure components BFT. Unlike existing quorum-based BFT approaches that ensure components redundancy via component replication; GEMINI ensures components redundancy via components parallel provisioning. Experimental results show that GEMINI increases the reliability and throughput of composite web service delivery when compared with existing composite web services delivery approaches.
{"title":"GEMINI: A Hybrid Byzantine Fault Tolerant Protocol for Reliable Composite Web Services Orchestrated Delivery","authors":"Islam Elgedawy","doi":"10.7763/IJCTE.2016.V8.1071","DOIUrl":"https://doi.org/10.7763/IJCTE.2016.V8.1071","url":null,"abstract":"—To ensure reliable delivery for composite web services, we argue that Byzantine fault tolerance (BFT) must be guaranteed for the service delivery modules (such as BPEL execution engines and dispatchers) as well as for the realizing components of the composite web service. Existing BFT service delivery approaches are mainly focused on atomic web services. However, there are few approaches discussed BFT for composite web services delivery. Unfortunately, such approaches either ensured BFT for the service delivery modules alone or for the service realizing components alone; but not for both. To overcome such limitation, this paper proposes GEMINI; a hybrid BFT protocol for reliable composite web services orchestrated delivery. GEMINI uses a lightweight replication-based BFT protocol to ensure the BFT for service delivery modules, and uses a speculative quorum-based BFT protocol to ensure components BFT. Unlike existing quorum-based BFT approaches that ensure components redundancy via component replication; GEMINI ensures components redundancy via components parallel provisioning. Experimental results show that GEMINI increases the reliability and throughput of composite web service delivery when compared with existing composite web services delivery approaches.","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129438627","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 : 2016-08-01DOI: 10.7763/IJCTE.2016.V8.1068
Gil-Ja So, S. H. Kim, Jeong-Yeop Kim
{"title":"Evaluation Model of the Visual Fatigue on the 3D Stereoscopic Video","authors":"Gil-Ja So, S. H. Kim, Jeong-Yeop Kim","doi":"10.7763/IJCTE.2016.V8.1068","DOIUrl":"https://doi.org/10.7763/IJCTE.2016.V8.1068","url":null,"abstract":"","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125819497","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 : 2016-08-01DOI: 10.7763/IJCTE.2016.V8.1057
Roghayeh Mojarad, H. Zarandi
In this paper, an anomaly correction method is proposed which is based on Markov anomaly detection method. The proposed method employs the probability of transitions between events to evaluate the behavior of a system. This method consists of three steps: 1) Construction of transition matrix by probability of transitions between events and list of known events are generated in training phase; 2) Detection of anomaly based on Markov detection method will be done. In test data when the probability of transition previous event to current event does not reach a predefined threshold, an anomaly is detected. Threshold is determined based on constructed transition matrix in step 1; 3) Check the defined constraints for each anomalous event to find source of anomaly and the suitable way to correct the anomalous event. Next, an event with the highest compliance with the constraints is selected. Evaluation of the proposed method is done using a total of 7000 data sets. The operational scope of corrector and the number of injected anomalies varied between 3 and 5, 1 and 7, respectively. The simulation experiments have been done to measure the correction coverage rate which is between 53.5% and 97.2% with average of 77.66%. For evaluation of hardware consumptions of the proposed method, this method is implemented by VHDL. Power, area and time consumptions are on average 87.43 w, 415.48 m, and 4.12ns, respectively.
{"title":"Markov-Based Anomaly Correction in Embedded Systems","authors":"Roghayeh Mojarad, H. Zarandi","doi":"10.7763/IJCTE.2016.V8.1057","DOIUrl":"https://doi.org/10.7763/IJCTE.2016.V8.1057","url":null,"abstract":"In this paper, an anomaly correction method is proposed which is based on Markov anomaly detection method. The proposed method employs the probability of transitions between events to evaluate the behavior of a system. This method consists of three steps: 1) Construction of transition matrix by probability of transitions between events and list of known events are generated in training phase; 2) Detection of anomaly based on Markov detection method will be done. In test data when the probability of transition previous event to current event does not reach a predefined threshold, an anomaly is detected. Threshold is determined based on constructed transition matrix in step 1; 3) Check the defined constraints for each anomalous event to find source of anomaly and the suitable way to correct the anomalous event. Next, an event with the highest compliance with the constraints is selected. Evaluation of the proposed method is done using a total of 7000 data sets. The operational scope of corrector and the number of injected anomalies varied between 3 and 5, 1 and 7, respectively. The simulation experiments have been done to measure the correction coverage rate which is between 53.5% and 97.2% with average of 77.66%. For evaluation of hardware consumptions of the proposed method, this method is implemented by VHDL. Power, area and time consumptions are on average 87.43 w, 415.48 m, and 4.12ns, respectively.","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127897091","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 : 2016-08-01DOI: 10.7763/ijcte.2016.v8.1066
M. Uysal
Technical innovations and trends have been changing from time to time as a major driving force for Software Engineering (SE). Although it can be regarded as a relatively young discipline usually driven by industrial needs or practices, fundamental problems of SE still continue to exist. It is thought that the problem may be not only in adopting a domain specific technology or method, but also in understanding the foundations and use of theories in SE. Therefore, investigating the trans-disciplinary aspects of SE may pave the way of some solutions while it may shed light on building the theoretical background of possible empirical studies. However, the review of SE literature shows the little effort given to this research gap, and thus, this paper attempts to offer a conceptual framework and brings a different perspective for understanding the theoretical and trans-disciplinary foundations of SE as a discipline.
{"title":"In Search of Software Engineering Foundations: A Theoretical and Trans-disciplinary Perspective","authors":"M. Uysal","doi":"10.7763/ijcte.2016.v8.1066","DOIUrl":"https://doi.org/10.7763/ijcte.2016.v8.1066","url":null,"abstract":"Technical innovations and trends have been changing from time to time as a major driving force for Software Engineering (SE). Although it can be regarded as a relatively young discipline usually driven by industrial needs or practices, fundamental problems of SE still continue to exist. It is thought that the problem may be not only in adopting a domain specific technology or method, but also in understanding the foundations and use of theories in SE. Therefore, investigating the trans-disciplinary aspects of SE may pave the way of some solutions while it may shed light on building the theoretical background of possible empirical studies. However, the review of SE literature shows the little effort given to this research gap, and thus, this paper attempts to offer a conceptual framework and brings a different perspective for understanding the theoretical and trans-disciplinary foundations of SE as a discipline.","PeriodicalId":306280,"journal":{"name":"International Journal of Computer Theory and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115919542","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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