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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 98 Documents
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Search results for , issue "Vol 11, No 6: December 2021" : 98 Documents clear
Hybrid approach for disease comorbidity and disease gene prediction using heterogeneous dataset Lakshmi K. S.; Vadivu G.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5240-5250

Abstract

High throughput analysis and large scale integration of biological data led to leading researches in the field of bioinformatics. Recent years witnessed the development of various methods for disease associated gene prediction and disease comorbidity predictions. Most of the existing techniques use network-based approaches and similarity-based approaches for these predictions. Even though network-based approaches have better performance, these methods rely on text data from OMIM records and PubMed abstracts. In this method, a novel algorithm (HDCDGP) is proposed for disease comorbidity prediction and disease associated gene prediction. Disease comorbidity network and disease gene network were constructed using data from gene ontology (GO), human phenotype ontology (HPO), protein-protein interaction (PPI) and pathway dataset. Modified random walk restart algorithm was applied on these networks for extracting novel disease-gene associations. Experimental results showed that the hybrid approach has better performance compared to existing systems with an overall accuracy around 85%.
A case study of using the hybrid model of scrum and six sigma in software development Mona Najafi Sarpiri; Taghi Javdani Gandomani
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5342-5350

Abstract

The world of software engineering is constantly discovering new ways that lead to an increase in team performance in the production of software products and, at the same time, brings the customer's further satisfaction. With the advent of agile methodologies in software development, these objectives have been considered more seriously by software teams and companies. Due to their very nature, agile methodologies have the potential to be integrated with other methodologies or specific managerial approaches defined in line with agility objectives. One of the cases is Six Sigma, which is used in organizations by focusing on organizational change and process improvement. In the present study, attempts were made to present the hybrid software development approach, including Scrum, as the most common agile and Six Sigma methodology. This approach was practically used in a case study, and the obtained results were analyzed. The results of this evaluation showed that this hybrid method could lead to the increased team performance and customer satisfaction. However, besides these two achievements, an increase in the number of re-works, number of defects discovered, and the duration of the project implementation were also observed. These cases are in line with the main objectives of Scrum and Six Sigma and are justifiable and acceptable due to achieving those objectives.
Power system operation considering detailed modelling of the natural gas supply network Ricardo Moreno; Diego Larrahondo; Oscar Florez
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4740-4750

Abstract

The energy transition from fossil-fuel generators to renewable energies represents a paramount challenge. This is mainly due to the uncertainty and unpredictability associated with renewable resources. A greater flexibility is requested for power system operation to fulfill demand requirements considering security and economic restrictions. In particular, the use of gas-fired generators has increased to enhance system flexibility in response to the integration of renewable energy sources. This paper provides a comprehensive formulation for modeling a natural gas supply network to provide gas for thermal generators, considering the use of wind power sources for the operation of the electrical system over a 24-hour period. The results indicate the requirements of gas with different wind power level of integration. The model is evaluated on a network of 20 NG nodes and on a 24-bus IEEE RTS system with various operative settings during a 24-hour period.
Solving hybrid-vehicle routing problem using modified simulated annealing Nour Alsumairat; Mahmoud Alrefaei
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4922-4931

Abstract

In this paper, we consider the hybrid vehicle routing problem (HVRP) at which the vehicle consumes two types of power: fuel and electricity. The aim of this problem is to minimize the total cost of travelling between customers, provided that each customer is visited only once. The vehicle departs from the depot and returns after completing the whole route. This optimization problem is solved using a modified simulated annealing (SA) heuristic procedure with constant temperature. This approach is implemented on a numerical example and the results are compared with the SA algorithm with decreasing temperature. The obtained results show that using the SA with constant temperature overrides the SA with decreasing temperature. The results indicate that SA with decreasing temperature needs twice the number of iterations needed by the SA with constant temperature to reach a near optimum solution.
Impact analysis of actuator torque degradation on the IRB 120 robot performance using simscape-based model Le Ngoc Truc; Nguyen Phung Quang; Nguyen Hong Quang
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4850-4864

Abstract

Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
Real-time monitoring of the prototype design of electric system by the ubidots platform Noor Saleh Mohammed; Nasir Hussein Selman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5568-5577

Abstract

In this paper, a prototype DC electric system was practically designed. The idea of the proposed system was derived from the microgrid concept. The system contained two houses each have a DC generator and load that consists of four 12 V DC lamps. Each house is controlled fully by Arduino UNO microcontroller to work in Island mode or connected it with the second house or main electric network. House operating mode depends on the power generated by its source and the availability of the main network. Under all operating cases, the minimum price of electricity consumption should satisfy as possible. Information between the houses about the operating mode and the main network state was exchanging wirelessly with the help of the RF-HC12. This information uploaded to the Ubidots platform by the Wi-Fi-ESP8266 included in the node MCU microcontroller. This platform has several advantages such as capture, visualization, analysis, and management of data. The system was examined for different cases to verify its working by varying the load in each building. All tested states showed that the houses transfer from one mode to another automatically with high reliability and minimum energy cost. The information about the main grid states and the sources of the houses were monitored and stored at the Ubidots platform.
Single core configurations of saturated core fault current limiter performance of laboratory test models Vittesh Naphade; Vilas Ghate; Gajanan Dhole
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4667-4677

Abstract

Economic growth with industrialization and urbanization lead to an extensive increase in power demand. It forced the utilities to add power generating facilities to cause the necessary demand-generation balance. The bulk power generating stations, mostly interconnected, with the penetration of distributed generation result in an enormous rise in the fault level of power networks. It necessitates for electrical utilities to control the fault current so that the existing switchgear can continue its services without up-gradation or replacement for reliable supply. The deployment of fault current limiter (FCL) at the distribution and transmission networks has been under investigation as a potential solution to the problem. A saturated core fault current limiter (SCFCL) technology is a smart, scalable, efficient, reliable, and commercially viable option to manage fault levels in existing and future MV/HV supply systems. This paper presents the comparative performance analysis of two single-core SCFCL topologies impressed with different core saturations. It has demonstrated that the single AC winding configuration needs more bias power for affecting the same current limiting performance with an acceptable steady-state voltage drop contribution. The fault state impedance has a transient nature, and the optimum bias selection is a critical design parameter in realizing the SCFCL applications.
Green distributed algorithm for energy saving in IP wired networks using sleep scheduling Mohammed Hussein; Wisam Alabbasi; Ahmad Alsadeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5160-5169

Abstract

Energy saving has become a critical issue and a great challenge in the past few decades, and a great effort as well is being made to reduce consumed energy. The Internet forms a major source for energy consumption. Therefore, in this work we propose an algorithm for energy saving in distributed backbone networks, the reduced energy consumption (RedCon) algorithm. In this paper, we introduce a new version for saving energy on the Internet by switching off underutilized links and switching on idle links when the network is overloaded in a distributed manner over the network nodes based on LSA messages and without any knowledge of the traffic matrix. Our algorithm is more accurate and outperforms other algorithms with its time checks and advanced learning algorithm.
Analysis of electromagnetic pollution by means of geographic information system Vladimir Henao-Cespedes; Yeison Alberto Garcés-Gómez
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5099-5106

Abstract

Currently, telecommunications systems have become more widespread and there is still a discrepancy between whether or not non-ionizing radiation produces health problems in living beings at cellular level. From an experimental point of view, it is interesting to raise the correlation of high levels of electromagnetic pollution with health problems in urban populations which would make it possible to clearly determine the effects of this type of radiation on human health and the environment. By means of remote sensing, a geographic information system (GIS) has been developed for the analysis of electromagnetic pollution levels generated by emissions from non-ionizing radiation (NIR) sources in a city. A method for measuring electromagnetic pollution was applied, which allows the generation of a table of attributes of the GIS that is the input to generate by inverse distance weighting (IDW), the layer of electromagnetic pollution. The method, as a case study, was applied in the city of Manizales, located in Colombia, obtaining as a result a layer that allows evidence that the highest levels of electromagnetic pollution are concentrated in the most central area of the city. In this way, the effects of NIR on public health can be analyzed by means of correlations.
Company bankruptcy prediction framework based on the most influential features using XGBoost and stacking ensemble learning Much Aziz Muslim; Yosza Dasril
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5549-5557

Abstract

Company bankruptcy is often a very big problem for companies. The impact of bankruptcy can cause losses to elements of the company such as owners, investors, employees, and consumers. One way to prevent bankruptcy is to predict the possibility of bankruptcy based on the company's financial data. Therefore, this study aims to find the best predictive model or method to predict company bankruptcy using the dataset from Polish companies bankruptcy. The prediction analysis process uses the best feature selection and ensemble learning. The best feature selection is selected using feature importance to XGBoost with a weight value filter of 10. The ensemble learning method used is stacking. Stacking is composed of the base model and meta learner. The base model consists of K-nearest neighbor, decision tree, SVM, and random forest, while the meta learner used is LightGBM. The stacking model accuracy results can outperform the base model accuracy with an accuracy rate of 97%.

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