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International Journal of Software Science and Computational Intelligence-IJSSCI最新文献

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Machine Learning for Accurate Software Development Cost Estimation in Economically and Technically Limited Environments 机器学习在经济和技术有限的环境中进行准确的软件开发成本估算
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2023-10-10 DOI: 10.4018/ijssci.331753
Mohammad Alauthman, Ahmad al-Qerem, Someah Alangari, Ali Mohd Ali, Ahmad Nabo, Amjad Aldweesh, Issam Jebreen, Ammar Almoman, Brij B. Gupta
{"title":"Machine Learning for Accurate Software Development Cost Estimation in Economically and Technically Limited Environments","authors":"Mohammad Alauthman, Ahmad al-Qerem, Someah Alangari, Ali Mohd Ali, Ahmad Nabo, Amjad Aldweesh, Issam Jebreen, Ammar Almoman, Brij B. Gupta","doi":"10.4018/ijssci.331753","DOIUrl":"https://doi.org/10.4018/ijssci.331753","url":null,"abstract":"Cost estimation for software development is crucial for project planning and management. Several regression models have been developed to predict software development costs, using historical datasets of previous projects. Accurate cost estimation in software development is heavily influenced by the relevance and quality of the cost estimation dataset and its suitability to the software development environment. The currently available cost estimation datasets are limited to North American and European environments, leaving a gap in the representation of other economically and technically constrained software industries. In this article, the authors evaluate the performance of regression models using the SEERA dataset, which highly represents these constrained environments. This study provides insights into selecting regression models for cost estimation in software development. It highlights the importance of using appropriate models based on the specific software development model and dataset used in the estimation process. In the performance evaluations of eight regression models, including elastic net, lasso regression, linear regression, neural network, RANSACRegressor, random forest, ride regression, and SVM, for cost estimation in different software models, along with correlation coefficients and accuracy indicators, were reported. The results showed that SVM and random forest indicated superior performance. However, the elastic net, lasso regression, linear regression, neural network, and RANSACRegressor models also demonstrated exemplary performance in cost estimation.","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136294421","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}
引用次数: 0
Artificial Intelligence in Tongue Image Recognition 人工智能在舌头图像识别中的应用
IF 2.9
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2023-08-25 DOI: 10.4018/ijssci.328771
Hongli Chu, Y. Ji, Dingju Zhu, Zhanhao Ye, Jianbin Tan, Xianping Hou, Yujie Lin
{"title":"Artificial Intelligence in Tongue Image Recognition","authors":"Hongli Chu, Y. Ji, Dingju Zhu, Zhanhao Ye, Jianbin Tan, Xianping Hou, Yujie Lin","doi":"10.4018/ijssci.328771","DOIUrl":"https://doi.org/10.4018/ijssci.328771","url":null,"abstract":"Tongue image recognition is a traditional Chinese medicine diagnosis method, which uses the shape, color, and texture of the tongue to judge the health of the human body. With the rapid development of artificial intelligence technology, the application of artificial intelligence in the field of tongue recognition has been widely considered. Based on the intelligent analysis of tongue diagnosis in traditional Chinese medicine, this paper reviews the application progress of artificial intelligence in tongue image recognition in recent years and analyzes its potential and challenges in this field. Firstly, this paper introduces three steps of tongue image recognition, including tongue image acquisition, tongue image preprocessing, and tongue image feature analysis. The application of traditional methods and artificial intelligence methods in the whole process of tongue image recognition is reviewed, especially the tongue body segmentation, and the advantages and disadvantages of convolutional neural networks are analyzed and compared. Artificial intelligence can use technologies such as deep learning and computer vision to automatically analyze and extract features from tongue images. By constructing a tongue image recognition model, tongue shape, color, texture, and other features can be accurately recognized and quantitatively analyzed. Finally, this paper summarizes the problems existing in artificial intelligence in tongue image recognition and looks forward to the future developmental direction of this field. It can promote the modernization of TCM diagnostic methods, achieve early disease screening and prevention, personalized medicine and treatment optimization, and support medical research and knowledge accumulation. However, there is still a need for further validation and practice, with a focus on patient privacy and data security.","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47818249","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}
引用次数: 0
Software Architecture during Release Planning 发布计划期间的软件架构
IF 2.9
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2022-01-01 DOI: 10.4018/ijssci.300366
{"title":"Software Architecture during Release Planning","authors":"","doi":"10.4018/ijssci.300366","DOIUrl":"https://doi.org/10.4018/ijssci.300366","url":null,"abstract":"This research paper will throw light on the design and implementation of how software architects are involved in release planning of industry and how issues are tackled during this time. Release planning basically deals with the inclusion of products in future release. The intricacy of investors guarantees the application of results. The prescribed method of release planning is referred to redirect versatile categories and it will help in an organized way. Moreover, difficulties related to danger, personal controls, structures, money or technical needs can be easily implemented into the release planning. Release planning is also referred to as new embodiment of a growing product. Though, the idea of a release is not limited to this but can be functional to any kind of intruded progress where a release planning relates a time period. An experienced based planning procedure is not able to justify size, complication, ambiguity, problems and such plans leaves a customer with discontentment which can result in the loss of time, budget and market share.","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46736032","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}
引用次数: 0
Implementing web and mobile applications from linked open Data 从链接的开放数据实现web和移动应用程序
IF 2.9
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2022-01-01 DOI: 10.4018/ijssci.301567
{"title":"Implementing web and mobile applications from linked open Data","authors":"","doi":"10.4018/ijssci.301567","DOIUrl":"https://doi.org/10.4018/ijssci.301567","url":null,"abstract":"The Linked Data initiative has successfully attracted many data providers who agree to adhere to the linked data principles and W3C standards. This movement aims to adopt a unified format, understandable by machines and easily discoverable and exploitable. As a result of this success, there has been a continuous expansion of linked open data available on the cloud. However, a limited number of applications utilize this wealth of data. Therefore, several governmental initiatives were launched to encourage the exploitation and use of public utility data to create applications that improve citizens' lives. This work investigates how linked open data, including government data, can provide public utility applications. Furthermore, this paper proposes a generic approach for creating mobile and web apps based on linked open data.","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41702542","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}
引用次数: 2
A Formal Statistical Data Modeling for Knowledge Discovery and Prognostic Reasoning of Arecanut Crop using Data Analytics 基于数据分析的槟榔作物知识发现与预测推理的形式化统计数据建模
IF 2.9
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2022-01-01 DOI: 10.4018/ijssci.311447
Rithesh Pakkala Permanki Guthu, Shamantha Rai Bellipady
{"title":"A Formal Statistical Data Modeling for Knowledge Discovery and Prognostic Reasoning of Arecanut Crop using Data Analytics","authors":"Rithesh Pakkala Permanki Guthu, Shamantha Rai Bellipady","doi":"10.4018/ijssci.311447","DOIUrl":"https://doi.org/10.4018/ijssci.311447","url":null,"abstract":"","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70471495","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}
引用次数: 0
Multi-Authority Fine-Grained Data Sharing and Search Scheme for Cloud Banking Systems 云银行系统的多权限细粒度数据共享与搜索方案
IF 2.9
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2022-01-01 DOI: 10.4018/ijssci.300360
{"title":"Multi-Authority Fine-Grained Data Sharing and Search Scheme for Cloud Banking Systems","authors":"","doi":"10.4018/ijssci.300360","DOIUrl":"https://doi.org/10.4018/ijssci.300360","url":null,"abstract":"The migration of the banking system to the cloud seems inevitable in near future like any other industry. By leveraging cloud technology, the personal and financial data of any customer can be accessed and controlled by third-party service providers. However, in order to maintain confidentiality, this information should be kept in an encrypted format, which has an impact on the usefulness and flexibility of fundamental operations like search. Moreover, in a financial institution, a data owner may want to provide the searching capability to the users from diverse domains. Therefore, to provide such flexibility, a system of multi-authority fine-grained search is introduced where each authority manages a single but entirely disjoint domain of attributes. As a result, the proposed system is more scalable, it can handle a large number of users from diverse domains and manage their credentials effectively. While most of the schemes in the literature lack this feature, and have a performance bottleneck because of a single centralized trusted authority.","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46285641","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}
引用次数: 1
Enhancing Cloud Availability via Intelligent Monitoring using Time Series Database and Machine Learning 通过使用时间序列数据库和机器学习的智能监控增强云可用性
IF 2.9
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2022-01-01 DOI: 10.4018/ijssci.285591
{"title":"Enhancing Cloud Availability via Intelligent Monitoring using Time Series Database and Machine Learning","authors":"","doi":"10.4018/ijssci.285591","DOIUrl":"https://doi.org/10.4018/ijssci.285591","url":null,"abstract":"Every cloud provider, wishes to provide 99.9999% availabil- ity for the systems provisioned and operated by them for the customer i.e. may it be SaaS or PaaS or IaaS model, the availability of the system must be greater than 99.9999%.It becomes vital for the provider to mon- itor the systems and take proactive measures to reduce the downtime.In an ideal scenario, the support colleagues (24*7 technical support) must be aware of the on-going issues in the production systems before it is raised as an incident by the customer. But currently, there is no effective alert monitoring solutions for the same. The proposed solution presented in this paper is to have a central alert monitoring tool for all cloud so- lutions offered by the cloud provider. The central alert monitoring tool constantly observes the time series database which contains metric val- ues populated by HA and compares the incoming metric values with the defined thresholds. When a metric value exceeds the defined threshold, using machine learning techniques the monitoring tool decides & takes actions.","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48460802","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}
引用次数: 0
A Fast Two-objective Differential Evolutionary Algorithm based on Pareto-optimal Set 基于pareto最优集的快速双目标差分进化算法
IF 2.9
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2016-01-01 DOI: 10.4018/IJSSCI.2016010104
Xu Yulong, Zhao Ling-dong
{"title":"A Fast Two-objective Differential Evolutionary Algorithm based on Pareto-optimal Set","authors":"Xu Yulong, Zhao Ling-dong","doi":"10.4018/IJSSCI.2016010104","DOIUrl":"https://doi.org/10.4018/IJSSCI.2016010104","url":null,"abstract":"The two-objective differential evolution with Pareto-optimal set, which is researched in this paper. Firstly, it is found that there are some redundant computations in the classic multi-objective evolutionary algorithm, such as the NSGA-II. Then, based on the concept of Pareto-optimal set, the non-dominated solution sorted and its potential features, the authors propose a ranking method for solution that only handles the highest rank individuals in current population. The highlight of the proposed method is that during the ranking process, the individuals can be chosen into the next generation meanwhile. When the individuals of next generation population are obtained the algorithm is broken out. Both the number of individuals for sorting process and the time complexity are reduced. Furthermore, a method of uniform crowding distance calculation is provided in this work. Finally, the authors incorporate the introduced ranking method and uniform crowding distance method into differential evolution, a fast two-objective differential evolution algorithm is obtained. For verifying the proposed method, they use the classical optimal problems ZDTl~ZDT4 and ZDT6 for tesing. Simulation results show that the authors' method has greatly improved in terms of time complexity and performance than other algorithms.","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70471416","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}
引用次数: 0
A Rule Based Approach for Japanese-Uyghur Machine Translation System 基于规则的日维机器翻译系统研究
IF 2.9
International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2014-01-01 DOI: 10.4018/IJSSCI.2014010104
Maimitili Nimaiti, Y. Izumi
{"title":"A Rule Based Approach for Japanese-Uyghur Machine Translation System","authors":"Maimitili Nimaiti, Y. Izumi","doi":"10.4018/IJSSCI.2014010104","DOIUrl":"https://doi.org/10.4018/IJSSCI.2014010104","url":null,"abstract":"Japanese Uyghur machine translation system has been designed and developed using recent rule based approach. Even though Japanese and Uyghur language has many similarities, but there are also some linguistic differences cause serious problems to the word for word translation. In fact, as straightforward word-for-word Japanese-Uighur translation sometimes yields unnatural Uighur sentences. To raise the translation accuracy, the authors propose a word-for-word translation system using subject verb agreement in Uighur. After a brief introduction to the comparative study of Japanese-Uyghur grammars, morphology and syntax, the authors explain their developing of a word to word rule base system. The coverage of this rule base system, the rules for translation, comparison of experimental result between statistical machine translation system and rule base machine translation system are explained. Some practical suffix translation methods solving problems in Uyghur language are also proposed.","PeriodicalId":29913,"journal":{"name":"International Journal of Software Science and Computational Intelligence-IJSSCI","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70471404","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}
引用次数: 1
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