Ikram Dehmouch, B. E. Asri, Maryem Rhanoui, Mina Elmaallam
Feature modeling is used to express commonality and variability among a family of software products called the software product line. To offer customized products to their customers, organizations need to build packages of features taking into consideration customer needs and preferences. This paper presents a platform named SPLP (Software Product Line Profiling) which allows pre-configuring feature models through the restriction of the configuration space to meet the requirements of a specific market segment. Considering that concerns and preferences of this latter are a key criteria to achieve a tailored pre-configuration, authors propose the integration of user profiling in the SPLP platform through the definition of a user profile model describing information about the user and the products he is used to consume. This information is then exploited by the SPLP platform to perform an automated pre-configuration according to each user profile requirements and preferences.
{"title":"Feature Models Preconfiguration Based on User Profiling","authors":"Ikram Dehmouch, B. E. Asri, Maryem Rhanoui, Mina Elmaallam","doi":"10.5539/cis.v12n1p59","DOIUrl":"https://doi.org/10.5539/cis.v12n1p59","url":null,"abstract":"Feature modeling is used to express commonality and variability among a family of software products called the software product line. To offer customized products to their customers, organizations need to build packages of features taking into consideration customer needs and preferences. This paper presents a platform named SPLP (Software Product Line Profiling) which allows pre-configuring feature models through the restriction of the configuration space to meet the requirements of a specific market segment. Considering that concerns and preferences of this latter are a key criteria to achieve a tailored pre-configuration, authors propose the integration of user profiling in the SPLP platform through the definition of a user profile model describing information about the user and the products he is used to consume. This information is then exploited by the SPLP platform to perform an automated pre-configuration according to each user profile requirements and preferences.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"31 1","pages":"59-71"},"PeriodicalIF":0.0,"publicationDate":"2019-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81371031","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}
The research aims to examine critical factors that influence the acceptance and use of M-learning among Jordanian student. This study integrates technology acceptance model (TAM) with service quality factor. The primary data were collected from 487 valid questionnaires, which were distributed, to random Jordanian students in four cities. The analyses of the gathered data employed the (SPSS). The validity of the final overall model was evaluated using the statistics and acceptable fit of the measurement model to the data has been demonstrated. Based on the outcomes, the factors with the highest direct effect on Intention to use M-learning appeared to be Attitude toward using M-learning, while the factor with the highest indirect effect on Intention to use M-learning appeared to be Compatibility. The main findings of the study are: trust factor has a significant stronger impact on PEOU and PU. PEOU and PU have the stronger impact on customers' attitude, which in turn influences students’ intention to use M - learning services.
{"title":"Factor That Influence To Acceptance M-Learning among Jordanian Students","authors":"S. Zoubi, A. A. Zoubi, MohmmadIssa Al Zoubi","doi":"10.5539/cis.v12n1p53","DOIUrl":"https://doi.org/10.5539/cis.v12n1p53","url":null,"abstract":"The research aims to examine critical factors that influence the acceptance and use of M-learning among Jordanian student. This study integrates technology acceptance model (TAM) with service quality factor. The primary data were collected from 487 valid questionnaires, which were distributed, to random Jordanian students in four cities. The analyses of the gathered data employed the (SPSS). The validity of the final overall model was evaluated using the statistics and acceptable fit of the measurement model to the data has been demonstrated. Based on the outcomes, the factors with the highest direct effect on Intention to use M-learning appeared to be Attitude toward using M-learning, while the factor with the highest indirect effect on Intention to use M-learning appeared to be Compatibility. The main findings of the study are: trust factor has a significant stronger impact on PEOU and PU. PEOU and PU have the stronger impact on customers' attitude, which in turn influences students’ intention to use M - learning services.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"39 1","pages":"53-58"},"PeriodicalIF":0.0,"publicationDate":"2019-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73427155","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}
We study in this paper the performance of Hospitals in Lebanon. Using the nonparametric method Data Envelopment Analysis (DEA), we are able to measures relative efficiency of Hospitals in Lebanon. DEA is a technique that uses linear programming and it measures the relative efficiency of similar type of organizations termed as Decision Making Units (DMUs). In this study, due to the lack of individual data on hospital level, each DMU refers to a qada in Lebanon where the used data represent the aggregation of input and outputs of different hospitals within the qada. In DEA, the inclusion of more number of inputs and /or outputs results in getting a more number of efficient units. Therefore, selecting the appropriate inputs and outputs is a major factor of DEA results. Therefore, we use here the Principal Component Analysis (PCA) in order to reduce the data structure into certain principal components which are essential for identifying efficient DMUs. It is important to note that we have used the basic BCC-input model for the entire analysis. We considered 24 DMUs for the study, using DEA on original data; we got 17 DMUs out of 24 DMUs as efficient. Then we considered 1 PC for inputs and 1 PC for output with almost 80 percent variances, resulting in 3 DMUs as efficient and 21 as inefficient. Using 1 PC for input and 2 PCs for output with 90 percent variance for both input and output, we got 9 DMUs as efficient and 15 DMUs as inefficient. Finally, we have attempted to identify the efficient units with 2 PCs and for 2 PCs for input and outputs with variance more than 95 percent, resulting in 10 efficient DMUs and 14 inefficient DMUs. In Principal Component analysis, if the variance lies between 80 percent to-90 percent it is judged as a meaningful one. It is concluded that Principal Component Analysis plays an important role in the reduction of input output variables and helps in identifying the efficient DMUs and improves the discriminating power of DEA.
{"title":"Measuring the Performance of Hospitals in Lebanese qadas Using PCA- DEA Model","authors":"A. Nasser","doi":"10.5539/cis.v12n1p23","DOIUrl":"https://doi.org/10.5539/cis.v12n1p23","url":null,"abstract":"We study in this paper the performance of Hospitals in Lebanon. Using the nonparametric method Data Envelopment Analysis (DEA), we are able to measures relative efficiency of Hospitals in Lebanon. DEA is a technique that uses linear programming and it measures the relative efficiency of similar type of organizations termed as Decision Making Units (DMUs). In this study, due to the lack of individual data on hospital level, each DMU refers to a qada in Lebanon where the used data represent the aggregation of input and outputs of different hospitals within the qada. In DEA, the inclusion of more number of inputs and /or outputs results in getting a more number of efficient units. Therefore, selecting the appropriate inputs and outputs is a major factor of DEA results. Therefore, we use here the Principal Component Analysis (PCA) in order to reduce the data structure into certain principal components which are essential for identifying efficient DMUs. It is important to note that we have used the basic BCC-input model for the entire analysis. We considered 24 DMUs for the study, using DEA on original data; we got 17 DMUs out of 24 DMUs as efficient. Then we considered 1 PC for inputs and 1 PC for output with almost 80 percent variances, resulting in 3 DMUs as efficient and 21 as inefficient. Using 1 PC for input and 2 PCs for output with 90 percent variance for both input and output, we got 9 DMUs as efficient and 15 DMUs as inefficient. Finally, we have attempted to identify the efficient units with 2 PCs and for 2 PCs for input and outputs with variance more than 95 percent, resulting in 10 efficient DMUs and 14 inefficient DMUs. In Principal Component analysis, if the variance lies between 80 percent to-90 percent it is judged as a meaningful one. It is concluded that Principal Component Analysis plays an important role in the reduction of input output variables and helps in identifying the efficient DMUs and improves the discriminating power of DEA.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"6 1","pages":"23-32"},"PeriodicalIF":0.0,"publicationDate":"2019-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80176744","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}
In view of the sensitivity of the traditional mean algorithm to outliers and noise points, an improved mean algorithm is proposed in this paper, which is based on the density of the distribution of objects in space. In the measurement of density, the sensitivity of clustering effect to initial parameters is reduced. The improved algorithm can filter the "noise" data and discover the clustering of arbitrary shapes, which is obviously superior to the standard mean algorithm.
{"title":"Research and Improvement Method Based on k-mean Clustering Algorithm","authors":"Guohua Zhang, Kangting Zhao, Yi Li","doi":"10.5539/cis.v12n1p49","DOIUrl":"https://doi.org/10.5539/cis.v12n1p49","url":null,"abstract":"In view of the sensitivity of the traditional mean algorithm to outliers and noise points, an improved mean algorithm is proposed in this paper, which is based on the density of the distribution of objects in space. In the measurement of density, the sensitivity of clustering effect to initial parameters is reduced. The improved algorithm can filter the \"noise\" data and discover the clustering of arbitrary shapes, which is obviously superior to the standard mean algorithm.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"61 1","pages":"49-52"},"PeriodicalIF":0.0,"publicationDate":"2019-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81428218","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}
With the advent of the era of big data, it has become extremely easy for scientific users to have to access academic papers, which has enhanced their efficiency and capacity to search or browse papers. However, it also faces some problems such as the explosion of the literature or information overwhelming. Many researchers focus on academic paper recommendation service, hoping to help scientific users to find documents more efficiently and recommend interested or potentially interested papers which could assist academic users doing research. Through literature review, this paper make a comprehensive summary of the research on personalized academic papers recommendation, presenting the state-of-art of academic paper recommendation methodologies, pointing out its pros and cons and indicating primary evaluation metrics and popular datasets. Finnaly, we outlook the research trend of personalized academic paper recommendation as a reference for interested researchers.
{"title":"A Review on Personalized Academic Paper Recommendation","authors":"Zhi Li, Xiaozhu Zou","doi":"10.5539/cis.v12n1p33","DOIUrl":"https://doi.org/10.5539/cis.v12n1p33","url":null,"abstract":"With the advent of the era of big data, it has become extremely easy for scientific users to have to access academic papers, which has enhanced their efficiency and capacity to search or browse papers. However, it also faces some problems such as the explosion of the literature or information overwhelming. Many researchers focus on academic paper recommendation service, hoping to help scientific users to find documents more efficiently and recommend interested or potentially interested papers which could assist academic users doing research. Through literature review, this paper make a comprehensive summary of the research on personalized academic papers recommendation, presenting the state-of-art of academic paper recommendation methodologies, pointing out its pros and cons and indicating primary evaluation metrics and popular datasets. Finnaly, we outlook the research trend of personalized academic paper recommendation as a reference for interested researchers.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"11 1","pages":"33-43"},"PeriodicalIF":0.0,"publicationDate":"2019-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84312718","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}
Much of the adjunct technology developed for using among medical environments is targeted towards computers. Because the hospitals face increasing demands to participate in a very big selection of quality improvement activities, the role and influence of using mobile applications in these efforts is additionally increasing. The professionals of Healthcare pay abundant of their time wandering between offices and patients, whereas the validator technology stays stationary. This paper presents a study performed using the mobile application for storing and following up patients status. Therefore, mobile application for tracking patient progress is proposed to minimize such challenges and demands, by allowing physicians and nurses to trace the patients’ conditions a lot of expeditiously and simply. The experimental results conclude that the working environment would be improved by supporting the mobile workers with mobile technology.
{"title":"Developing Mobile Tracking Applications for Patient Treatment","authors":"H. Abu-Dalbouh","doi":"10.5539/cis.v12n1p12","DOIUrl":"https://doi.org/10.5539/cis.v12n1p12","url":null,"abstract":"Much of the adjunct technology developed for using among medical environments is targeted towards computers. Because the hospitals face increasing demands to participate in a very big selection of quality improvement activities, the role and influence of using mobile applications in these efforts is additionally increasing. The professionals of Healthcare pay abundant of their time wandering between offices and patients, whereas the validator technology stays stationary. This paper presents a study performed using the mobile application for storing and following up patients status. Therefore, mobile application for tracking patient progress is proposed to minimize such challenges and demands, by allowing physicians and nurses to trace the patients’ conditions a lot of expeditiously and simply. The experimental results conclude that the working environment would be improved by supporting the mobile workers with mobile technology.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"38 1","pages":"12-22"},"PeriodicalIF":0.0,"publicationDate":"2019-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78072303","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}
With the development of wireless network and the wide application of pervasive computing technology, the location-based service (LBS) needs more and more location information for mobile users. At present, the outdoor positioning system based on satellite signals has been very mature, but it can not be applied in the complex indoor environment. Therefore, indoor positioning technology has rapidly become a research hotspot. At the same time, the rapid development of wireless network technology, because of its fast communication speed, easy deployment and other characteristics, WiFi-based indoor positioning technology has been widely concerned and studied. Therefore, this paper takes an economic WiFi-based indoor positioning method as the research foundation, and studies the corresponding improved algorithm aiming at the existing problems.
{"title":"Research on an Economic Localization Approach","authors":"F. Yin, Jun Yin","doi":"10.5539/cis.v12n1p44","DOIUrl":"https://doi.org/10.5539/cis.v12n1p44","url":null,"abstract":"With the development of wireless network and the wide application of pervasive computing technology, the location-based service (LBS) needs more and more location information for mobile users. At present, the outdoor positioning system based on satellite signals has been very mature, but it can not be applied in the complex indoor environment. Therefore, indoor positioning technology has rapidly become a research hotspot. At the same time, the rapid development of wireless network technology, because of its fast communication speed, easy deployment and other characteristics, WiFi-based indoor positioning technology has been widely concerned and studied. Therefore, this paper takes an economic WiFi-based indoor positioning method as the research foundation, and studies the corresponding improved algorithm aiming at the existing problems.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"85 1","pages":"44-48"},"PeriodicalIF":0.0,"publicationDate":"2019-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84020058","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}
Software as a Service cloud computing model favorites the Multi-Tenancy as a key factor to exploit economies of scale. However Multi-Tenancy present several disadvantages. Therein, our approach comes to optimize instances assigned to multi-tenants with a solution using rich-variant components while ensuring more economies of scale and avoiding tenants hesitation to share resources. The paper present the theoretical and pragmatic cases of a user-aware multi-tenancy SaaS approach focused on graph-based algorithms. The theoretical case consists in having a set of tenants while the pragmatic case consists in adding a new tenants to a set of tenants.
{"title":"Theoretical and Pragmatic Cases of a Rich-Variant Approach for a User-Aware Multi-Tenant SaaS Applications","authors":"Houda Kriouile, B. E. Asri","doi":"10.5539/cis.v12n1p1","DOIUrl":"https://doi.org/10.5539/cis.v12n1p1","url":null,"abstract":"Software as a Service cloud computing model favorites the Multi-Tenancy as a key factor to exploit economies of scale. However Multi-Tenancy present several disadvantages. Therein, our approach comes to optimize instances assigned to multi-tenants with a solution using rich-variant components while ensuring more economies of scale and avoiding tenants hesitation to share resources. The paper present the theoretical and pragmatic cases of a user-aware multi-tenancy SaaS approach focused on graph-based algorithms. The theoretical case consists in having a set of tenants while the pragmatic case consists in adding a new tenants to a set of tenants.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"1 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2019-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83099962","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}
Topic modeling is a powerful technique for unsupervised analysis of large document collections. Topic models have a wide range of applications including tag recommendation, text categorization, keyword extraction and similarity search in the text mining, information retrieval and statistical language modeling. The research on topic modeling is gaining popularity day by day. There are various efficient topic modeling techniques available for the English language as it is one of the most spoken languages in the whole world but not for the other spoken languages. Bangla being the seventh most spoken native language in the world by population, it needs automation in different aspects. This paper deals with finding the core topics of Bangla news corpus and classifying news with similarity measures. The document models are built using LDA (Latent Dirichlet Allocation) with bigram.
{"title":"Topic Modelling in Bangla Language: An LDA Approach to Optimize Topics and News Classification","authors":"Malek Mouhoub, M. A. Helal","doi":"10.5539/cis.v11n4p77","DOIUrl":"https://doi.org/10.5539/cis.v11n4p77","url":null,"abstract":"Topic modeling is a powerful technique for unsupervised analysis of large document collections. Topic models have a wide range of applications including tag recommendation, text categorization, keyword extraction and similarity search in the text mining, information retrieval and statistical language modeling. The research on topic modeling is gaining popularity day by day. There are various efficient topic modeling techniques available for the English language as it is one of the most spoken languages in the whole world but not for the other spoken languages. Bangla being the seventh most spoken native language in the world by population, it needs automation in different aspects. This paper deals with finding the core topics of Bangla news corpus and classifying news with similarity measures. The document models are built using LDA (Latent Dirichlet Allocation) with bigram.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"66 1","pages":"77-83"},"PeriodicalIF":0.0,"publicationDate":"2018-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88962529","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}
Over the last decades, software development effort estimation has integrated new approaches dealing with uncertainty. However, effort estimates are still plagued with errors limiting their reliability. Thus, estimates error management at an organization level provides a promising alternative to the classical approaches dealing with single projects as a portfolio can afford more flexibility and opportunities in terms of risk management. The most widely used approaches in risk management were mainly based on the Gaussian approximation that shows its limits facing “ruin” risk associated to unusual events. The aim of this paper is to propose a Multi-Projects Error Modeling framework to characterize error at a portfolio level using bootstrapping, mixture of Gaussians and power law to emphasize the tail behavior respectively.
{"title":"Software Effort Estimation Risk Management over Projects Portfolio","authors":"Salma El Koutbi, A. Idri","doi":"10.5539/cis.v11n4p45","DOIUrl":"https://doi.org/10.5539/cis.v11n4p45","url":null,"abstract":"Over the last decades, software development effort estimation has integrated new approaches dealing with uncertainty. However, effort estimates are still plagued with errors limiting their reliability. Thus, estimates error management at an organization level provides a promising alternative to the classical approaches dealing with single projects as a portfolio can afford more flexibility and opportunities in terms of risk management. The most widely used approaches in risk management were mainly based on the Gaussian approximation that shows its limits facing “ruin” risk associated to unusual events. The aim of this paper is to propose a Multi-Projects Error Modeling framework to characterize error at a portfolio level using bootstrapping, mixture of Gaussians and power law to emphasize the tail behavior respectively.","PeriodicalId":14676,"journal":{"name":"J. Chem. Inf. Comput. Sci.","volume":"20 1","pages":"45-76"},"PeriodicalIF":0.0,"publicationDate":"2018-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88699207","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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