Pub Date : 2015-08-18DOI: 10.1109/CSICSSE.2015.7369244
Najme Yaghouti, M. Kahani, Behshid Behkamal
In recent years the web has evolved from a global information space of linked documents to one where both documents and data are linked. What supports this evolution is a set of best practices in publishing and connecting structured data on the web that is called linked data. The usefulness of linked data relies on how much related concepts are linked together. The aim of this research is to propose a metric-driven approach for interlinking assessment of a single dataset. The proposed metrics are categorized into three groups called internal linking, external linking and link-ability from other datasets. These metrics consider both graph structure (topology) and schema of datasets (semantic information) to evaluate interlinking with appropriate accuracy.
{"title":"A metric-driven approach for interlinking assessment of RDF graphs","authors":"Najme Yaghouti, M. Kahani, Behshid Behkamal","doi":"10.1109/CSICSSE.2015.7369244","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369244","url":null,"abstract":"In recent years the web has evolved from a global information space of linked documents to one where both documents and data are linked. What supports this evolution is a set of best practices in publishing and connecting structured data on the web that is called linked data. The usefulness of linked data relies on how much related concepts are linked together. The aim of this research is to propose a metric-driven approach for interlinking assessment of a single dataset. The proposed metrics are categorized into three groups called internal linking, external linking and link-ability from other datasets. These metrics consider both graph structure (topology) and schema of datasets (semantic information) to evaluate interlinking with appropriate accuracy.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126998689","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369235
Ayub Mamandi, S. Yousefi, Reza Ebrahimi Atani
Increasing the population of cites has led to several problems in using the spatial sources of cities. One of these sources which imposes high expenses on city mates are car parks. To solve such problems many parking guidance systems have been developed, but unfortunately in most of them the efficiency has not been evaluated. In order to analyze efficiency of parking guidance systems, in this paper two models of parking selection systems are provided, using two concepts: game theory and priority heuristic. In the games theory model, drivers are considered as being rational entity that are seeking to maximize their payoffs. On the other hand, in the priority heuristic model, characteristics of drivers are taken into account for choosing a car park. We compared our model to the similar existing models based on three factors: the total number of drivers, the number of on-street car parks space, costs difference between private and on-street car parks and the influences of each factor on the efficiency of the parking guidance system. The results of comparison represent far higher efficiency compared to previous models.
{"title":"Game theory-based and heuristic algorithms for parking-lot search","authors":"Ayub Mamandi, S. Yousefi, Reza Ebrahimi Atani","doi":"10.1109/CSICSSE.2015.7369235","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369235","url":null,"abstract":"Increasing the population of cites has led to several problems in using the spatial sources of cities. One of these sources which imposes high expenses on city mates are car parks. To solve such problems many parking guidance systems have been developed, but unfortunately in most of them the efficiency has not been evaluated. In order to analyze efficiency of parking guidance systems, in this paper two models of parking selection systems are provided, using two concepts: game theory and priority heuristic. In the games theory model, drivers are considered as being rational entity that are seeking to maximize their payoffs. On the other hand, in the priority heuristic model, characteristics of drivers are taken into account for choosing a car park. We compared our model to the similar existing models based on three factors: the total number of drivers, the number of on-street car parks space, costs difference between private and on-street car parks and the influences of each factor on the efficiency of the parking guidance system. The results of comparison represent far higher efficiency compared to previous models.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114779908","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369239
Elham Darbanian, Gh Dastghaiby Fard
Users may have various login ids that will be hard to remember their passwords and alphanumeric passwords are difficult to remember. One solution is to use graphical passwords that are more secure. Some threats of Internet security are spyware and shoulder-surfing attacks. This paper presents a new scheme for graphical password that uses images that are unexplainable and have larger password space. The proposed scheme is also resistant to spyware and shoulder-surfing attacks.
{"title":"A graphical password against spyware and shoulder-surfing attacks","authors":"Elham Darbanian, Gh Dastghaiby Fard","doi":"10.1109/CSICSSE.2015.7369239","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369239","url":null,"abstract":"Users may have various login ids that will be hard to remember their passwords and alphanumeric passwords are difficult to remember. One solution is to use graphical passwords that are more secure. Some threats of Internet security are spyware and shoulder-surfing attacks. This paper presents a new scheme for graphical password that uses images that are unexplainable and have larger password space. The proposed scheme is also resistant to spyware and shoulder-surfing attacks.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125987988","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369247
V. Riahi, Morteza Kazemi
The no-wait flowshop scheduling problem (NWFSP) that needs jobs to be processed without interruption between consecutive machines is a NP-hard combinatorial optimization problem, and embodies a significant area in production scheduling. The objective is set to find the scheduling which minimizes the makespan. In this paper, a new hybrid ant colony optimization (ACO) and Simulated Annealing (SA) algorithm is presented to solve NWFSP. The computational results on 29 benchmark instances provided by Carlier and Reeves and comparison with other reported results in the literature approves the efficiency of the proposed algorithm.
{"title":"A hybrid heuristic algorithm for the no-wait flowshop scheduling problem","authors":"V. Riahi, Morteza Kazemi","doi":"10.1109/CSICSSE.2015.7369247","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369247","url":null,"abstract":"The no-wait flowshop scheduling problem (NWFSP) that needs jobs to be processed without interruption between consecutive machines is a NP-hard combinatorial optimization problem, and embodies a significant area in production scheduling. The objective is set to find the scheduling which minimizes the makespan. In this paper, a new hybrid ant colony optimization (ACO) and Simulated Annealing (SA) algorithm is presented to solve NWFSP. The computational results on 29 benchmark instances provided by Carlier and Reeves and comparison with other reported results in the literature approves the efficiency of the proposed algorithm.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124698364","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369248
Sara Behjat-Jamal, R. Demirci, Taymaz Rahkar-Farshi
A variety of methods for images noise reduction has been developed so far. Most of them successfully remove noise but their edge preserving capabilities are weak. Therefore bilateral image filter is helpful to deal with this problem. Nevertheless, their performances depend on spatial and photometric parameters which are chosen by user. Conventionally, the geometric weight is calculated by means of distance of neighboring pixels and the photometric weight is calculated by means of color components of neighboring pixels. The range of weights is between zero and one. In this paper, geometric weights are estimated by fuzzy metrics and photometric weights are estimated by using fuzzy rule based system which does not require any predefined parameter. Experimental results of conventional, fuzzy bilateral filter and proposed approach have been included.
{"title":"Hybrid bilateral filter","authors":"Sara Behjat-Jamal, R. Demirci, Taymaz Rahkar-Farshi","doi":"10.1109/CSICSSE.2015.7369248","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369248","url":null,"abstract":"A variety of methods for images noise reduction has been developed so far. Most of them successfully remove noise but their edge preserving capabilities are weak. Therefore bilateral image filter is helpful to deal with this problem. Nevertheless, their performances depend on spatial and photometric parameters which are chosen by user. Conventionally, the geometric weight is calculated by means of distance of neighboring pixels and the photometric weight is calculated by means of color components of neighboring pixels. The range of weights is between zero and one. In this paper, geometric weights are estimated by fuzzy metrics and photometric weights are estimated by using fuzzy rule based system which does not require any predefined parameter. Experimental results of conventional, fuzzy bilateral filter and proposed approach have been included.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128046948","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369236
Ardavan Afshar, Bahareh Ashenagar, Negar Foroutan Eghlidi, M. Z. Jahromi, A. Hamzeh
Community detection has recently turned to be one of the most popular research topics in social networks analysis. Majority of community detection methods already considered in the literature try to optimize a global metric through a centralized decision maker. These approaches are too time-consuming in huge networks. Several of methods need initial parameters such as number and size of communities in order to find out the problems; however, they are not always reachable. In this paper, we propose a local utility maximization approach for community identification as a distributed framework in which each community acts as a selfish agent to maximize its utility function based on some predefined actions. Our framework has some crucial characteristic features. The first feature is the local approach that is easily implemented through parallel computing concepts, while the second is an economical interpretation of utility measurement. Experimental results on output benchmark datasets show that our proposed method can perform as well as the existing centralized approaches that already exist in the literature to detect non-overlapping communities.
{"title":"Using local utility maximization to detect social networks communities","authors":"Ardavan Afshar, Bahareh Ashenagar, Negar Foroutan Eghlidi, M. Z. Jahromi, A. Hamzeh","doi":"10.1109/CSICSSE.2015.7369236","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369236","url":null,"abstract":"Community detection has recently turned to be one of the most popular research topics in social networks analysis. Majority of community detection methods already considered in the literature try to optimize a global metric through a centralized decision maker. These approaches are too time-consuming in huge networks. Several of methods need initial parameters such as number and size of communities in order to find out the problems; however, they are not always reachable. In this paper, we propose a local utility maximization approach for community identification as a distributed framework in which each community acts as a selfish agent to maximize its utility function based on some predefined actions. Our framework has some crucial characteristic features. The first feature is the local approach that is easily implemented through parallel computing concepts, while the second is an economical interpretation of utility measurement. Experimental results on output benchmark datasets show that our proposed method can perform as well as the existing centralized approaches that already exist in the literature to detect non-overlapping communities.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"404 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127201691","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369245
Seyyed Hamid Aboutorabi, Mehdi Rezapour, M. Moradi, Nasser Ghadiri
With the advent of big data phenomenon in the world of data and its related technologies, the developments on the NoSQL databases are highly regarded. It has been claimed that these databases outperform their SQL counterparts. The aim of this study is to investigate the claim by evaluating the document-oriented MongoDB database with SQL in terms of the performance of common aggregated and non-aggregate queries. We designed a set of experiments with a huge number of operations such as read, write, delete, and select from various aspects in the two databases and on the same data for a typical e-commerce schema. The results show that MongoDB performs better for most operations excluding some aggregate functions. The results can be a good source for commercial and non-commercial companies eager to change the structure of the database used to provide their line-of-business services.
{"title":"Performance evaluation of SQL and MongoDB databases for big e-commerce data","authors":"Seyyed Hamid Aboutorabi, Mehdi Rezapour, M. Moradi, Nasser Ghadiri","doi":"10.1109/CSICSSE.2015.7369245","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369245","url":null,"abstract":"With the advent of big data phenomenon in the world of data and its related technologies, the developments on the NoSQL databases are highly regarded. It has been claimed that these databases outperform their SQL counterparts. The aim of this study is to investigate the claim by evaluating the document-oriented MongoDB database with SQL in terms of the performance of common aggregated and non-aggregate queries. We designed a set of experiments with a huge number of operations such as read, write, delete, and select from various aspects in the two databases and on the same data for a typical e-commerce schema. The results show that MongoDB performs better for most operations excluding some aggregate functions. The results can be a good source for commercial and non-commercial companies eager to change the structure of the database used to provide their line-of-business services.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128499236","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369240
Mohsen Gavahi, Reza Mirzaei, Abolfazl Nazarbeygi, Armin Ahmadzadeh, S. Gorgin
The k-nearest neighbor (k-NN) is a widely used classification technique and has significant applications in various domains. The most challenging issues in the k-nearest neighbor algorithm are high dimensional data, the reasonable accuracy of results and suitable computation time. Nowadays, using parallel processing and deploying many-core platforms like GPUs is considered as one of the popular approaches to improving these issues. In this paper, we present a novel and accurate parallel implementation of k-NN based on Mahalanobis distance metric in GPU platform. We design and implement k-NN for GPU architecture and utilize mathematic and algorithmic techniques to eliminate repetitive computations. Moreover, in addition, to taking advantage of different parallelism techniques, we improve warp management to gain maximum speed up in this implementation. Via Compute Unified Device Architecture (CUDA)-enabled GPUs, the acceleration is considerable as experimental results show the 110X speedup with respect to the single core CPU implementation. Furthermore, we measure the energy and power consumption of this algorithm for both CPU and GPU platforms, where GPU is more energy efficient regarding this application.
{"title":"High performance GPU implementation of k-NN based on Mahalanobis distance","authors":"Mohsen Gavahi, Reza Mirzaei, Abolfazl Nazarbeygi, Armin Ahmadzadeh, S. Gorgin","doi":"10.1109/CSICSSE.2015.7369240","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369240","url":null,"abstract":"The k-nearest neighbor (k-NN) is a widely used classification technique and has significant applications in various domains. The most challenging issues in the k-nearest neighbor algorithm are high dimensional data, the reasonable accuracy of results and suitable computation time. Nowadays, using parallel processing and deploying many-core platforms like GPUs is considered as one of the popular approaches to improving these issues. In this paper, we present a novel and accurate parallel implementation of k-NN based on Mahalanobis distance metric in GPU platform. We design and implement k-NN for GPU architecture and utilize mathematic and algorithmic techniques to eliminate repetitive computations. Moreover, in addition, to taking advantage of different parallelism techniques, we improve warp management to gain maximum speed up in this implementation. Via Compute Unified Device Architecture (CUDA)-enabled GPUs, the acceleration is considerable as experimental results show the 110X speedup with respect to the single core CPU implementation. Furthermore, we measure the energy and power consumption of this algorithm for both CPU and GPU platforms, where GPU is more energy efficient regarding this application.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114533684","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369237
Behnaz Aghabalaee Bonab, O. Bushehrian
in migration of the legacy software to the cloud, the software architecture has to be changed according to the cloud infrastructure and requirements. To achieve this purpose, the software is decomposed (if possible) in to a set of collaborating loosely coupled services to be deployed on the virtual machines. The main rationale behind this decomposition is to provide easy and fast recovery from failed components or replacing the required functionality of the legacy software with the reliable cloud services. In this paper a semi-automated reverse engineering method based on the clustering algorithms is proposed to recommend the best migration-to-cloud strategy. The recommendation is based on four defined metrics: the extent of effort required for reengineering, maintenance costs, achieved availability and the number of cloud services that are used. The proposed method is applied two case studies and the effectiveness of this method is discussed.
{"title":"A semi-automated reverse engineering method to recommend the best migration-to-cloud strategy","authors":"Behnaz Aghabalaee Bonab, O. Bushehrian","doi":"10.1109/CSICSSE.2015.7369237","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369237","url":null,"abstract":"in migration of the legacy software to the cloud, the software architecture has to be changed according to the cloud infrastructure and requirements. To achieve this purpose, the software is decomposed (if possible) in to a set of collaborating loosely coupled services to be deployed on the virtual machines. The main rationale behind this decomposition is to provide easy and fast recovery from failed components or replacing the required functionality of the legacy software with the reliable cloud services. In this paper a semi-automated reverse engineering method based on the clustering algorithms is proposed to recommend the best migration-to-cloud strategy. The recommendation is based on four defined metrics: the extent of effort required for reengineering, maintenance costs, achieved availability and the number of cloud services that are used. The proposed method is applied two case studies and the effectiveness of this method is discussed.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134193494","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 : 2015-08-01DOI: 10.1109/CSICSSE.2015.7369249
Fatemeh Taheri Dezaki, A. Ghaffari, E. Fatemizadeh
Graph Matching (GM) plays an essential role in computer vision and machine learning. The ability of using pairwise agreement in GM makes it a powerful approach in feature matching. In this paper, a new formulation is proposed which is more robust when it faces with outlier points. We add weights to the one-to-one constraints, and modify them in the process of optimization in order to diminish the effect of outlier points in the matching procedure. We execute our proposed method on different real and synthetic databases to show both robustness and accuracy in contrast to several conventional GM methods.
{"title":"GMWASC: Graph matching with weighted affine and sparse constraints","authors":"Fatemeh Taheri Dezaki, A. Ghaffari, E. Fatemizadeh","doi":"10.1109/CSICSSE.2015.7369249","DOIUrl":"https://doi.org/10.1109/CSICSSE.2015.7369249","url":null,"abstract":"Graph Matching (GM) plays an essential role in computer vision and machine learning. The ability of using pairwise agreement in GM makes it a powerful approach in feature matching. In this paper, a new formulation is proposed which is more robust when it faces with outlier points. We add weights to the one-to-one constraints, and modify them in the process of optimization in order to diminish the effect of outlier points in the matching procedure. We execute our proposed method on different real and synthetic databases to show both robustness and accuracy in contrast to several conventional GM methods.","PeriodicalId":115653,"journal":{"name":"2015 International Symposium on Computer Science and Software Engineering (CSSE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125065701","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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