International Journal on Electrical Engineering and Informatics最新文献

{"title":"A Process Framework for Applying Situational Method Engineering (SME) on OMG's Essence","authors":"Yani Widyani, Muhammad Zuhri Catur Candra, E. K. Budiardjo, B. Sitohang","doi":"10.15676/ijeei.2021.13.4.1","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.4.1","url":null,"abstract":": Situational method engineering (SME) is an engineering process used to construct context-specific software development methods. The advantage of SMEs is to allow software development teams to work using a context-specific or situational method, that is, a method that suits their project characteristics. A situational method comprises method parts; each part has a context description that details the appropriate situation for applying that particular method. There are several types of method parts, such as method fragment, method chunk, method component, and method service. In this research, we adopt the concept of method chunk. We also use the modified metamodel from our previous study. Although there are advantages to applying SMEs, it does require extra effort. Method chunks are not easy to find, and a different notation decreases the method chunk's interoperability. This research proposes a process framework for applying SMEs. The framework's benefits are to guide method engineers in applying SMEs and provide a reference for software engineers to develop the supporting system. This framework use Essence language as a standard for method modeling to improve the interoperability of method chunks. We also apply the concept of service-oriented in the SME process to enhance the accessibility of method chunks by providing method chunk description as a service. Following the proposed framework, method engineers can extract method chunks from existing methods, publish them at a centralized publishing system to make them available as a service, and construct situational methods from selected method chunks. Software engineers can use the proposed framework to develop the supporting system. Our framework defines the complete processes for applying SMEs in a software project. The proposed framework has been validated by using the framework in a case study and building a prototype of the supporting system. Our objective is to validate the applicability of the proposed framework as a guideline. We conclude that the proposed framework is applicable, and in the end, it can support method engineers in applying SMEs in their software projects with less effort.","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73315975","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}

{"title":"Single Document Summarization Using BertSum and Pointer Generator Network","authors":"Rini Wijayanti, M. L. Khodra, D. H. Widyantoro","doi":"10.15676/ijeei.2021.13.4.10","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.4.10","url":null,"abstract":": The rapid development of textual data requires an automated text summarization system to obtain shortened versions of documents quickly and accurately. This paper investigates the performances of BertSum and Pointer Generator Network (PGN) on the IndoSum corpus containing Indonesian news articles. We compare these methods to NeuralSum, which is claimed to outperform other methods when working with the IndoSum dataset. In our experiment, BertSum with Indonesian's pre-trained model outperformed NeuralSum in extractive summarization. NeuralSum, on the other hand, tends to select the leading sentences as a summary and occasionally produces a blank summary. Meanwhile, PGN effectively prevents word repetition by using a coverage mechanism, although the summary results are sometimes out of context.","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83052396","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}

{"title":"Evaluation of The Deep Learning Techniques to Identify Plant Diseases Using Leaf Images","authors":"Harry Yuliansyah, Rudy Hartanto, I. Soesanti","doi":"10.15676/ijeei.2021.13.4.5","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.4.5","url":null,"abstract":": Successful farming is influenced by various techniques conducted by farmers in identifying the types of diseases that affect plant yields to avoid greater losses. Therefore, this study aims to evaluate the deep learning techniques in identifying plant diseases using leaf images. Furthermore, an artificial intelligence approach was used to identify types of plant diseases. During the deep learning training, about 11 deep learning architectural models and consisting of 38 classes in the dataset were used. The results showed that the highest minimum accuracy value obtained was 87.10%, with only one class having an accuracy value below 90%.","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76278892","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}

{"title":"Real-time Human Tracking System using Histogram Intersection Distance in Firefly Optimization Based Particle Filter","authors":"D. Maharani, C. Machbub, L. Yulianti","doi":"10.15676/ijeei.2021.13.4.7","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.4.7","url":null,"abstract":": Real-time human tracking in a video have numerous applications. For security and surveillance application, the tracking system with PTZ (Pan, Tilt, and Zoom) camera is expected to track an object correctly regardless of the object orientation. Numerous studies reported that Particle Filter (PF) is reliable for color object tracking. However, the PF algorithm still suffers from impoverishment and degeneration in the resampling process. These problems can be resolved by combining the PF with Firefly Optimization (FO) in the resampling process. This research proposes the use of Histogram Intersection distance to build a likelihood function in PF to achieve real-time implementation. The Firefly Optimization Algorithm-based Particle Filter (FOAPF) with Histogram Intersection distance was compared to FOAPF with Bhattacharyya distance, resulting in lower RMSE (Root Mean Square Error) in tracking TB datasets. The result shows that when the Histogram Intersection distance was implemented, a faster average time of 1.8 ms was achieved than 1.9 ms when using Bhattacharyya distance. It shows the time result slightly different. The FOAPF with Histogram Intersection distance results in the TB datasets perform a low RMSE of 4.96 and 12.07, and private datasets show a low RMSE of 16.92 and 8.80, with the real-time implementation of 30 FPS and 50 particles. The comparison presents the successful implementation of the proposed method as a tracker to enhance human movement tracking with real-time implementation.","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80438330","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}

{"title":"Real Time Tracking Trajectory and Obstacle Avoidance for Two Mobile Robots by FLC and NMPC","authors":"H. Merabti, Ibrahim Aliouche, Abdelkadir Bouhallit, K. Belarbi, H. Nezzari, A. Benammar","doi":"10.15676/ijeei.2021.13.4.12","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.4.12","url":null,"abstract":"Fast solution procedures are still persist as a challenge for autonomous mobile robot control for tracking trajectory, while simultaneously detecting and avoiding static and dynamic obstacles. In this work, two fast controllers are investigated: the Fuzzy Logic Controller (FLC) and the NMPC based on the Knowledge Particle Swarm Optimization (KPSO). Theses controllers are used to control two mobile robots at the same time for trajectory tracking and obstacle avoidance in a dynamical environment. Simulation and experimental results are presented for the studied controllers. The results show that the FLC has the fastest computation time with an acceptable accuracy in tracking trajectory and obstacle avoidance while the control signals smoothness and robots navigation accuracy are very good with the NMPC-KPSO. In this latter case, the computation of the control signal needs to be shortened.","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"122 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88071128","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}

{"title":"Study of Thermallay accelerated aging of Transformer Insulation Paper in Mineral Oil and Gas-to-Liquid Dielectrics using Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA) and X-ray Diffraction (XRD)","authors":"A. Ritonga, S. Suwarno","doi":"10.15676/ijeei.2021.13.3.12","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.3.12","url":null,"abstract":"","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76136556","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}

{"title":"Fuzzy Logic Speed Control and Adaptation Mechanism-Based Twelve Sectors DTC to Improve the Performance of a Sensorless Induction Motor Drive","authors":"Yassine Zahraoui, M. Akherraz, Sara Elbadaoui","doi":"10.15676/ijeei.2021.13.3.1","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.3.1","url":null,"abstract":"","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76619042","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}

{"title":"A Hybrid SVM NAÏVE-BAYES Classifier for Bright Lesions Recognition in Eye Fundus Images","authors":"Nasr Y. Gharaibeh, Obaida M. Al-hazaimeh, Ashraf A. Abu-Ein, K. Nahar","doi":"10.15676/ijeei.2021.13.3.2","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.3.2","url":null,"abstract":"","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84530297","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}

{"title":"Review on Effective Disease Prediction through Data Mining Techniques","authors":"Muhammad Nabeel, Shumaila Majeed, Mazhar Javed Awan, Hooria Muslih ud-Din, Mashal Wasique, R. Nasir","doi":"10.15676/ijeei.2021.13.3.13","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.3.13","url":null,"abstract":"","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90166936","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}

{"title":"Frequency Control in Dispersed Power System Using Partially Decentralized Combined Fuzzy-PID (PD-CFPID) Regulator","authors":"P. Dash, S. K. Mohapatra, A. Baliarsingh","doi":"10.15676/ijeei.2021.13.3.14","DOIUrl":"https://doi.org/10.15676/ijeei.2021.13.3.14","url":null,"abstract":"","PeriodicalId":38705,"journal":{"name":"International Journal on Electrical Engineering and Informatics","volume":"127 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79550874","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}