e Informatica Softw. Eng. J.最新文献_第5页

Empirical AI Transformation Research: A Systematic Mapping Study and Future Agenda 实证人工智能转型研究:系统映射研究与未来议程

e Informatica Softw. Eng. J. Pub Date : 2022-01-01 DOI: 10.37190/e-inf220108

Einav Peretz-Andersson, R. Torkar

引用次数: 1

Microservice-Oriented Workload Prediction Using Deep Learning 基于深度学习的微服务工作负载预测

e Informatica Softw. Eng. J. Pub Date : 2022-01-01 DOI: 10.37190/e-inf220107

Sebastian Ştefan, Virginia Niculescu

{"title":"Microservice-Oriented Workload Prediction Using Deep Learning","authors":"Sebastian Ştefan, Virginia Niculescu","doi":"10.37190/e-inf220107","DOIUrl":"https://doi.org/10.37190/e-inf220107","url":null,"abstract":"Background: Service oriented architectures are becoming increasingly popular due to their flexibility and scalability which makes them a good fit for cloud deployments. Aim: This research aims to study how an efficient workload prediction mechanism for a practical proactive scaler, could be provided. Such a prediction mechanism is necessary since in order to fully take advantage of on-demand resources and reduce manual tuning, an auto-scaling, preferable predictive, approach is required, which means increasing or decreasing the number of deployed services according to the incoming workloads. Method: In order to achieve the goal, a workload prediction methodology that takes into account microservice concerns is proposed. Since, this should be based on a performant model for prediction, several deep learning algorithms were chosen to be analysed against the classical approaches from the recent research. Experiments have been conducted in order to identify the most appropriate prediction model. Results: The analysis emphasises very good results obtained using the MLP (MultiLayer Perceptron) model, which are better than those obtained with classical time series approaches, with a reduction of the mean error prediction of 49%, when using as data, two Wikipedia traces for 12 days and with two different time windows: 10 and 15min. Conclusion: The tests and the comparison analysis lead to the conclusion that considering the accuracy, but also the computational overhead and the time duration for prediction, MLP model qualifies as a reliable foundation for the development of proactive microservice scaler applications.","PeriodicalId":11452,"journal":{"name":"e Informatica Softw. Eng. J.","volume":"13 1","pages":"220107"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86799892","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

Understanding Top Management Involvement in SDLC Phases 理解最高管理层在SDLC阶段的参与

e Informatica Softw. Eng. J. Pub Date : 2021-11-20 DOI: 10.5120/ijca2021921759

A. Alzayed, A. Khalfan

{"title":"Understanding Top Management Involvement in SDLC Phases","authors":"A. Alzayed, A. Khalfan","doi":"10.5120/ijca2021921759","DOIUrl":"https://doi.org/10.5120/ijca2021921759","url":null,"abstract":"One of the most essential factors in the success of system implementation has been recognized as top management support and involvement. Few research, however, have addressed the question of what sort of engagement is necessary through the various stages of the system development life cycle (SDLS). Given the many challenges to top management involvement and support in the various SDLC phases. The objective of this research was twofold. First, to examine the relationship between top management support and the phases of SDLC in order to give guidance for top management practices to ensure the success of information system projects. Second, this study sought to investigate approaches of motivating top management to participate in the SDLC as well as the barriers that hinder them from doing so. This study investigates the function of top management in various phases of system implementation, which will help us in understanding the support mechanism from top management in various SDLC stages. To achieve this goal, the author performed a qualitative study in five different firms in Kuwait, interviewing top management, project management, system analysts, and IT managers. The research established criteria for top management participation and indicated that top management should be involved primarily in the planning and implementation phases, as well as other phases as needed.","PeriodicalId":11452,"journal":{"name":"e Informatica Softw. Eng. J.","volume":"91 1","pages":"87-120"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79419871","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

Mining Weighted Periodic Patterns by a Weighted Direction Graph Based Approach for Time-Series Databases 基于加权方向图的时间序列数据库加权周期模式挖掘方法

e Informatica Softw. Eng. J. Pub Date : 2021-11-01 DOI: 10.17706/jsw.16.6.267-284

Ye-In Chang, Cheng Fu, Jialan Que

{"title":"Mining Weighted Periodic Patterns by a Weighted Direction Graph Based Approach for Time-Series Databases","authors":"Ye-In Chang, Cheng Fu, Jialan Que","doi":"10.17706/jsw.16.6.267-284","DOIUrl":"https://doi.org/10.17706/jsw.16.6.267-284","url":null,"abstract":"Periodic pattern mining in time series database plays an important part in data mining. However, most existing algorithms consider only the count of each item, but do not consider about the value of each item. To consider the value of each item on periodic pattern mining in time series databases, Chanda et al. proposed an algorithm called WPPM. In their algorithm, they construct the suffix trie to store the candidate pattern at first. However, the suffix trie would use too much storage space. In order to decrease the processing time for constructing the data structure, in this paper, we propose two data structures to store the candidates. The first data structure is Weighted Paired Matrix. After scanning the database, we will transform the database into the matrix type, and it is used for the second data structures. Therefore, our algorithm not only can decrease the usage of the memory space, but also the processing time. Because we do not need to use so much time to construct so many nodes and edges. Moreover, wealso consider the case of incremental mining for the increase of the data length. From the performance study, we show that our proposed algorithm based on the Weighted Direction Graphis more efficient than the WPPMalgorithm.","PeriodicalId":11452,"journal":{"name":"e Informatica Softw. Eng. J.","volume":"22 1","pages":"267-284"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79934496","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

Team Collaboration Assessment Method in Marine Engine Room Simulator 船舶机舱模拟器团队协作评估方法

e Informatica Softw. Eng. J. Pub Date : 2021-11-01 DOI: 10.17706/jsw.16.6.315-332

Hui Cao, You-Bing Cao, Jun-dong Zhang

{"title":"Team Collaboration Assessment Method in Marine Engine Room Simulator","authors":"Hui Cao, You-Bing Cao, Jun-dong Zhang","doi":"10.17706/jsw.16.6.315-332","DOIUrl":"https://doi.org/10.17706/jsw.16.6.315-332","url":null,"abstract":"Based on the fuzzy mathematics and set similarity theory an intelligent collaboration assessment method for engine room simulator was studied. First, an integrated weighting method using both subjective and objective information was designed to obtain the weight vector; second, the fuzzy comprehensive evaluation method was used to calculate the completion degree of team collaboration, then the Dice coefficient and the Tversky coefficient were adopted to quantify the sequence factor, interactivity factor, redundancy factor and unauthorized factor of team collaboration effectiveness; third, a comprehensive calculation was achieved by the completion degree and the four factors to get the team collaboration assessment result; finally, the influence of the collaboration factors on assessment result was analyzed by an example, and it was found that even if the team get a higher task completion degree, due to some factors, the score is still low. The research shows that the collaborative performance of a team can greatly influence the final assessment result, the quantitative analysis of team collaboration can more objectively reveal the impact on collaboration. It is an effective method to add the influence of team cooperation factors to the traditional individual evaluation.","PeriodicalId":11452,"journal":{"name":"e Informatica Softw. Eng. J.","volume":"10 1","pages":"315-332"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90754855","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

Research on an Improved MB-LBP 3D Face Recognition Method 一种改进的MB-LBP三维人脸识别方法研究

e Informatica Softw. Eng. J. Pub Date : 2021-11-01 DOI: 10.17706/jsw.16.6.306-314

Liangliang Shi, Xia Wang, Yongliang Shen

引用次数: 0

Object Metrics for Green Software 绿色软件的目标指标

e Informatica Softw. Eng. J. Pub Date : 2021-11-01 DOI: 10.17706/jsw.16.6.285-305

M. Oussalah, Romain Brohan, Ossama Moustafa

引用次数: 1

A Quality Assessment Instrument for Systematic Literature Reviews in Software Engineering 软件工程中系统文献综述的质量评价工具

e Informatica Softw. Eng. J. Pub Date : 2021-09-21 DOI: 10.37190/e-inf230105

M. Usman, N. Ali, C. Wohlin

{"title":"A Quality Assessment Instrument for Systematic Literature Reviews in Software Engineering","authors":"M. Usman, N. Ali, C. Wohlin","doi":"10.37190/e-inf230105","DOIUrl":"https://doi.org/10.37190/e-inf230105","url":null,"abstract":"Context: Systematic literature reviews (SLRs) have become standard practise as part of software engineering research, although their quality varies. To build on the reviews, both for future research and industry practice, they need to be of high quality. Objective: To assess the quality of SLRs in software engineering, we put forward an appraisal instrument for SLRs. The instrument is intended for use by appraisers of reviews, but authors may also use it as a checklist when designing and documenting their reviews. Method: A well-established appraisal instrument from research in healthcare was used as a starting point to develop a quality assessment instrument. It is adapted to software engineering using guidelines, checklists, and experiences from software engineering. As a validation step, the first version was reviewed by four external experts on SLRs in software engineering and updated based on their feedback. Results: The outcome of the research is an appraisal instrument for the quality assessment of SLRs in software engineering. The instrument intends to support the appraiser in assessing the quality of an SLR. The instrument includes 16 items with different options to capture the quality. The item is assessed on a two or three-grade scale, depending on the item. The instrument also supports consolidating the items into groups, which are then used to assess the overall quality of a systematic literature review. Conclusion: It is concluded that the presented instrument may be helpful support for an appraiser in assessing the quality of SLRs in software engineering.","PeriodicalId":11452,"journal":{"name":"e Informatica Softw. Eng. J.","volume":"20 1","pages":"230105"},"PeriodicalIF":0.0,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90441923","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: 3

Conceptualised Visualisation of Extended Agent Oriented Smart Factory (xAOSF) Framework with Associated AOSR-WMS System 扩展Agent - Oriented智能工厂(xAOSF)框架与相关AOSR-WMS系统的概念化可视化

e Informatica Softw. Eng. J. Pub Date : 2021-07-01 DOI: 10.17706/jsw.16.4.%20182-199

F. U. Din, David J. Paul, F. Henskens, M. Wallis

{"title":"Conceptualised Visualisation of Extended Agent Oriented Smart Factory (xAOSF) Framework with Associated AOSR-WMS System","authors":"F. U. Din, David J. Paul, F. Henskens, M. Wallis","doi":"10.17706/jsw.16.4.%20182-199","DOIUrl":"https://doi.org/10.17706/jsw.16.4.%20182-199","url":null,"abstract":"The emergence of the fourth industrial revolution (Industry 4.0) has sparked proliferation in thedomain of Cyber-Physical Systems (CPS), and extensive research has been conductedin this area since its beginning. However, recent literature claims that Smallto Medium Size Enterprises (SMEs) are not getting the benefits of Industry 4.0 (I4.0) in a full potential because of unresolved compatibility-mismatch issues and involvement of high infrastructuralcost. In order to help bridge this gap, the Extended Agent-Oriented Smart Factory (xAOSF) framework provides a high-level guideline solution, integrating the whole supply chain (SC), from supplier-end to customer-end with an objective to expose SMEs towards the benefits of I4.0. This paper, as part of a publication series, provides a conceptualised visualisation of the xAOSF framework as a customised CPS,which presents an elegant mediation mechanism between multiple xAOSF agents to uptake negotiation and coordination schemes at different enterprise levels. This paper also includes detail on howthe I4.0 based xAOSF framework caters to three-dimensional enterprise integration, in order to provide seamless connectivity and robustness in enterprise-wide operations. Furthermore, for the purpose of validation and to justify the claim, the experimentation is performed by applying a comprehensive test scenario onxAOSF's recommended AOSR WMS strategy in comparison with linear SC-based standard WMS system, which yields a substantial performance improvement in certain key-performance areas.","PeriodicalId":11452,"journal":{"name":"e Informatica Softw. Eng. J.","volume":"92 1","pages":"182-199"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83824076","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

Adversarial Semi-supervised Learning for Corporate Credit Ratings 企业信用评级的对抗性半监督学习

e Informatica Softw. Eng. J. Pub Date : 2021-04-04 DOI: 10.17706/jsw.16.6.259-266

Bojing Feng, Wenfang Xue

{"title":"Adversarial Semi-supervised Learning for Corporate Credit Ratings","authors":"Bojing Feng, Wenfang Xue","doi":"10.17706/jsw.16.6.259-266","DOIUrl":"https://doi.org/10.17706/jsw.16.6.259-266","url":null,"abstract":"Corporate credit rating is an analysis of credit risks withina corporation, which plays a vital role during the management of financial risk. Traditionally, the rating assessment process based on the historical profile of corporation is usually expensive and complicated, which often takes months. Therefore, most of the corporations, duetothelack in money and time, can’t get their own credit level. However, we believe that although these corporations haven’t their credit rating levels (unlabeled data), this big data contains useful knowledgeto improve credit system. In this work, its major challenge lies in how to effectively learn the knowledge from unlabeled data and help improve the performance of the credit rating system. Specifically, we consider the problem of adversarial semi-supervised learning (ASSL) for corporate credit rating which has been rarely researched before. A novel framework adversarial semi-supervised learning for corporate credit rating (ASSL4CCR) which includes two phases is proposed to address these problems. In the first phase, we train a normal rating system via a machine-learning algorithm to give unlabeled data pseudo rating level. Then in the second phase, adversarial semi-supervised learning is applied uniting labeled data and pseudo-labeleddatato build the final model. To demonstrate the effectiveness of the proposed ASSL4CCR, we conduct extensive experiments on the Chinese public-listed corporate rating dataset, which proves that ASSL4CCR outperforms the state-of-the-art methods consistently.","PeriodicalId":11452,"journal":{"name":"e Informatica Softw. Eng. J.","volume":"15 1","pages":"259-266"},"PeriodicalIF":0.0,"publicationDate":"2021-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81593979","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