Pub Date : 2020-06-08DOI: 10.1142/s2196888820500190
Tomasz Boinski, J. Szymański, Bartlomiej Dudek, Pawel Zalewski, Szymon Dompke, Maria Czarnecka
In this paper, we present results of employing DBpedia and YAGO as lexical databases for answering questions formulated in the natural language. The proposed solution has been evaluated for answeri...
{"title":"NLP Questions Answering Using DBpedia and YAGO","authors":"Tomasz Boinski, J. Szymański, Bartlomiej Dudek, Pawel Zalewski, Szymon Dompke, Maria Czarnecka","doi":"10.1142/s2196888820500190","DOIUrl":"https://doi.org/10.1142/s2196888820500190","url":null,"abstract":"In this paper, we present results of employing DBpedia and YAGO as lexical databases for answering questions formulated in the natural language. The proposed solution has been evaluated for answeri...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129422231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-14DOI: 10.1142/s2196888820500141
K. Zatwarnicki, Anna Zatwarnicka
Nowadays, a significant part of human activity is supported by information systems, especially Web systems, hosted in the Web clouds. The architectures of Web cloud systems are in most cases comple...
{"title":"An Architecture of a Two-Layer Cloud-Based Web System Using a Fuzzy-Neural Request Distribution","authors":"K. Zatwarnicki, Anna Zatwarnicka","doi":"10.1142/s2196888820500141","DOIUrl":"https://doi.org/10.1142/s2196888820500141","url":null,"abstract":"Nowadays, a significant part of human activity is supported by information systems, especially Web systems, hosted in the Web clouds. The architectures of Web cloud systems are in most cases comple...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127676521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.1142/s2196888820500104
S. Jaybhaye, V. Attar
Cloud services are used to achieve diverse computing needs such as cost, security, scalability, and availability. Acceleration evolution in the distributed and cloud domains is common for large and dynamic workflows deployment. Resources and task mapping depend on the user’s objectives such as reduction in cost or execution completion within the stipulated time in consideration with certain quality of services. Multiple virtual machine instances can be launched by defining different configurations such as operating system, server types, and applications. Though workflow scheduling is an NP-Hard problem, variety of decision-making techniques are available for optimum resource allocation. In this research paper, different algorithms are studied and compared with evolutionary approaches. Workflow scheduling using genetic algorithm is implemented and discussed. This paper aims to design a decision-making technique to optimize resources of cloud. It is an adaptive scheduling to maximize profit by reducing execution time. The approach implemented is useful to cloud service providers to maximize profit and resource efficiency in their services.
{"title":"Adaptive Workflow Scheduling Using Evolutionary Approach in Cloud Computing","authors":"S. Jaybhaye, V. Attar","doi":"10.1142/s2196888820500104","DOIUrl":"https://doi.org/10.1142/s2196888820500104","url":null,"abstract":"Cloud services are used to achieve diverse computing needs such as cost, security, scalability, and availability. Acceleration evolution in the distributed and cloud domains is common for large and dynamic workflows deployment. Resources and task mapping depend on the user’s objectives such as reduction in cost or execution completion within the stipulated time in consideration with certain quality of services. Multiple virtual machine instances can be launched by defining different configurations such as operating system, server types, and applications. Though workflow scheduling is an NP-Hard problem, variety of decision-making techniques are available for optimum resource allocation. In this research paper, different algorithms are studied and compared with evolutionary approaches. Workflow scheduling using genetic algorithm is implemented and discussed. This paper aims to design a decision-making technique to optimize resources of cloud. It is an adaptive scheduling to maximize profit by reducing execution time. The approach implemented is useful to cloud service providers to maximize profit and resource efficiency in their services.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128293726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-14DOI: 10.1142/s2196888820500153
R. Menéndez-Ferreira, J. Torregrosa, Á. Panizo-Lledot, A. González-Pardo, David Camacho
Radicalization, as a violent form of extremism, is a growing problem for Europe. Currently, it is possible to find extreme ideologies regarding almost every topic such as religion, politics or sports. This problem, which ranges from personal identity conflicts to complex societal issues, has an impact on several people everyday, especially on youngsters. To confront this situation, the European Union found several initiatives, as a way to face this problem from a scientific perspective. Some of these initiatives face the problem trying to reduce radicalization by working on personal and social skills through education, in such a way the youngster’s resilience is improved. This paper aims to present YoungRes, a European project whose goal is to improve the resilience of youngsters. To do so, it unifies an already created intervention — named Fortius — through the inclusion of video games in the learning process. This paper describes both: (1) how the Fortius program is modified to allow video games sessions and (2) the software architecture designed to allow students and educators to participate in YoungRes project. Finally, different suggestions to include in future versions of the game are discussed.
{"title":"Improving Youngsters' Resilience Through Video Game-Based Interventions","authors":"R. Menéndez-Ferreira, J. Torregrosa, Á. Panizo-Lledot, A. González-Pardo, David Camacho","doi":"10.1142/s2196888820500153","DOIUrl":"https://doi.org/10.1142/s2196888820500153","url":null,"abstract":"Radicalization, as a violent form of extremism, is a growing problem for Europe. Currently, it is possible to find extreme ideologies regarding almost every topic such as religion, politics or sports. This problem, which ranges from personal identity conflicts to complex societal issues, has an impact on several people everyday, especially on youngsters. To confront this situation, the European Union found several initiatives, as a way to face this problem from a scientific perspective. Some of these initiatives face the problem trying to reduce radicalization by working on personal and social skills through education, in such a way the youngster’s resilience is improved. This paper aims to present YoungRes, a European project whose goal is to improve the resilience of youngsters. To do so, it unifies an already created intervention — named Fortius — through the inclusion of video games in the learning process. This paper describes both: (1) how the Fortius program is modified to allow video games sessions and (2) the software architecture designed to allow students and educators to participate in YoungRes project. Finally, different suggestions to include in future versions of the game are discussed.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124043994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-14DOI: 10.1142/s2196888820500177
H. Drias, Hadjer Moulai, Y. Drias
In this paper, for the first time, a novel discretization scheme is proposed aiming at enabling scalability but also at least three other strong challenges. It is based on a Left-to-Right (LR) scanning process, which partitions the input stream into intervals. This task can be implemented by an algorithm or by using a generator that builds automatically the discretization program. We focus especially on unsupervised discretization and design a method called Usupervised Left to Right Discretization (ULR-Discr). Extensive experiments were conducted using various cut-point functions on small, large and medical public datasets. First, ULR-Discr variants under different statistics are compared between themselves with the aim at observing the impact of the cut-point functions on accuracy and runtime. Then the proposed method is compared to traditional and recent techniques for classification. The result is that the classification accuracy is highly improved when using our method for discretization.
在本文中，首次提出了一种新的离散化方案，旨在实现可扩展性，但也至少有三个其他强大的挑战。它基于从左到右(LR)扫描过程，该过程将输入流划分为间隔。这项任务可以通过算法或使用自动构建离散化程序的生成器来实现。我们特别关注无监督离散化，并设计了一种称为ussupervised Left to Right discreization (ULR-Discr)的方法。在小型、大型和医疗公共数据集上使用各种切点函数进行了广泛的实验。首先，对不同统计量下的ULR-Discr变量进行比较，观察截点函数对准确率和运行时间的影响。然后将该方法与传统和最新的分类技术进行了比较。结果表明，采用该方法进行离散化处理后，分类精度得到了很大的提高。
{"title":"An Automated Unsupervised Discretization Method: A Novel Approach","authors":"H. Drias, Hadjer Moulai, Y. Drias","doi":"10.1142/s2196888820500177","DOIUrl":"https://doi.org/10.1142/s2196888820500177","url":null,"abstract":"In this paper, for the first time, a novel discretization scheme is proposed aiming at enabling scalability but also at least three other strong challenges. It is based on a Left-to-Right (LR) scanning process, which partitions the input stream into intervals. This task can be implemented by an algorithm or by using a generator that builds automatically the discretization program. We focus especially on unsupervised discretization and design a method called Usupervised Left to Right Discretization (ULR-Discr). Extensive experiments were conducted using various cut-point functions on small, large and medical public datasets. First, ULR-Discr variants under different statistics are compared between themselves with the aim at observing the impact of the cut-point functions on accuracy and runtime. Then the proposed method is compared to traditional and recent techniques for classification. The result is that the classification accuracy is highly improved when using our method for discretization.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123862474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-20DOI: 10.1142/s2196888820500098
O. A. Alade, A. Selamat, R. Sallehuddin
One major characteristic of data is completeness. Missing data is a significant problem in medical datasets. It leads to incorrect classification of patients and is dangerous to the health manageme...
数据的一个主要特征是完整性。数据缺失是医学数据集中的一个重要问题。导致患者分类错误，危害健康管理。
{"title":"The Effects of Missing Data Characteristics on the Choice of Imputation Techniques","authors":"O. A. Alade, A. Selamat, R. Sallehuddin","doi":"10.1142/s2196888820500098","DOIUrl":"https://doi.org/10.1142/s2196888820500098","url":null,"abstract":"One major characteristic of data is completeness. Missing data is a significant problem in medical datasets. It leads to incorrect classification of patients and is dangerous to the health manageme...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132766948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-20DOI: 10.1142/s2196888820500128
Bálint Fazekas, A. Kiss
In classical artificial intelligence and machine learning fields, the aim is to teach a certain program to find the most convenient and efficient way of solving a particular problem. However, these...
{"title":"Simulation of Intelligence Evolution in Object-Oriented Systems","authors":"Bálint Fazekas, A. Kiss","doi":"10.1142/s2196888820500128","DOIUrl":"https://doi.org/10.1142/s2196888820500128","url":null,"abstract":"In classical artificial intelligence and machine learning fields, the aim is to teach a certain program to find the most convenient and efficient way of solving a particular problem. However, these...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131249326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-04DOI: 10.1142/s2196888820500116
H. Huynh, Q. Truong, Tan Kiet Nguyen Thanh, Q. Truong
The determination of plant species from field observation requires substantial botanical expertise, which puts it beyond the reach of most nature enthusiasts. Traditional plant species identification is almost impossible for the general public and challenging even for professionals who deal with botanical problems daily such as conservationists, farmers, foresters, and landscape architects. Even for botanists themselves, species identification is often a difficult task. This paper proposes a model deep learning with a new architecture Convolutional Neural Network (CNN) for leaves classifier based on leaf pre-processing extract vein shape data replaced for the red channel of colors. This replacement improves the accuracy of the model significantly. This model experimented on collector leaves data set Flavia leaf data set and the Swedish leaf data set. The classification results indicate that the proposed CNN model is effective for leaf recognition with the best accuracy greater than 98.22%.
{"title":"Plant Identification Using New Architecture Convolutional Neural Networks Combine with Replacing the Red of Color Channel Image by Vein Morphology Leaf","authors":"H. Huynh, Q. Truong, Tan Kiet Nguyen Thanh, Q. Truong","doi":"10.1142/s2196888820500116","DOIUrl":"https://doi.org/10.1142/s2196888820500116","url":null,"abstract":"The determination of plant species from field observation requires substantial botanical expertise, which puts it beyond the reach of most nature enthusiasts. Traditional plant species identification is almost impossible for the general public and challenging even for professionals who deal with botanical problems daily such as conservationists, farmers, foresters, and landscape architects. Even for botanists themselves, species identification is often a difficult task. This paper proposes a model deep learning with a new architecture Convolutional Neural Network (CNN) for leaves classifier based on leaf pre-processing extract vein shape data replaced for the red channel of colors. This replacement improves the accuracy of the model significantly. This model experimented on collector leaves data set Flavia leaf data set and the Swedish leaf data set. The classification results indicate that the proposed CNN model is effective for leaf recognition with the best accuracy greater than 98.22%.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126386858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-26DOI: 10.1142/s2196888820500062
Z. Murzabekov, M. Miłosz, K. Tussupova, G. Mirzakhmedova
For the mathematical model of a three-sector economic cluster, the problem of optimal control with fixed ends of trajectories is considered. An algorithm for solving the optimal control problem for...
对于三部门经济集群的数学模型，考虑了轨迹末端固定的最优控制问题。一种求解…最优控制问题的算法
{"title":"Problems of Optimal Control for a Class of Linear and Nonlinear Systems of the Economic Model of a Cluster","authors":"Z. Murzabekov, M. Miłosz, K. Tussupova, G. Mirzakhmedova","doi":"10.1142/s2196888820500062","DOIUrl":"https://doi.org/10.1142/s2196888820500062","url":null,"abstract":"For the mathematical model of a three-sector economic cluster, the problem of optimal control with fixed ends of trajectories is considered. An algorithm for solving the optimal control problem for...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128245568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-20DOI: 10.1142/s2196888820500086
M. Rana, A. Sung
Android is the most well-known portable working framework having billions of dynamic clients worldwide that pulled in promoters, programmers, and cybercriminals to create malware for different purp...
{"title":"Evaluation of Advanced Ensemble Learning Techniques for Android Malware Detection","authors":"M. Rana, A. Sung","doi":"10.1142/s2196888820500086","DOIUrl":"https://doi.org/10.1142/s2196888820500086","url":null,"abstract":"Android is the most well-known portable working framework having billions of dynamic clients worldwide that pulled in promoters, programmers, and cybercriminals to create malware for different purp...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117190790","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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