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International Journal of Electrical and Computer Engineering
ISSN : 20888708     EISSN : 27222578     DOI : -
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.
Articles 115 Documents
Search results for , issue "Vol 10, No 3: June 2020" : 115 Documents clear
User experience improvement of japanese language mobile learning application through mental model and A/B testing Komang Candra Brata; Adam Hendra Brata
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (584.235 KB) | DOI: 10.11591/ijece.v10i3.pp2659-2667

Abstract

Advances in smartphone technology have led to the strong emergence of mobile learning (m-learning) on the market to support foreign language learning purposes, especially for the Japanese language. No matter what kind of m-learning application, their goal should help learners to learn the Japanese language independently. However, popular Japanese m-learning applications only accommodate on enhancing reading, vocabulary and writing ability so that user experience issues are still prevalent and may affect the learning outcome. In the context of user experience, usability is one of the essential factors in mobile application development to determine the level of the application’s user experience. In this paper, we advocate for a user experience improvement by using the mental model and A/B testing. The mental model is used to reflect the user’s inner thinking mode. A comparative approach was used to investigate the performance of 20 high-grade students with homogenous backgrounds and coursework. User experience level was measured based on the usability approach on pragmatic quality and hedonic quality like effectiveness (success rate of task completion), efficiency (task completion time) and satisfaction. The results then compared with an existing Japanese m-learning to gather the insight of improvement of our proposed method. Experimental results show that both m-learning versions proved can enhance learner performance in pragmatic attributes. Nevertheless, the study also reveals that an m-learning that employs the conversational mental model in the learning process is more valued by participants in hedonic qualities. Mean that the proposed m-learning which is developed with the mental model consideration and designed using A/B testing is able to provide conversational learning experience intuitively.
Stateful library service system design and implementation in Saudi Arabia Arif Bramantoro
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (800.039 KB) | DOI: 10.11591/ijece.v10i3.pp2690-2700

Abstract

Service system has become one of the most challenging research issues in industry. Most of organizations in Saudi Arabia build their services with state-less technique to avoid many issues although there are some acknowledged advantages of using state-full technique. These issues are mainly related to the low number of visitors, low number of services, storage capacity and organization size. The purpose of this research is to create services that have capability in reading all required data from library management system, improving the service by applying state-full technique. Technology acceptance model is used to measure the acceptance of state-full service system through organizations and customers which gave some prediction to library high management to support them in decision making.
Fuzzy gain scheduling control apply to an RC Hovercraft Huu Khoa Tran; Pham Duc Lam; Tran Thanh Trang; Xuan Tien Nguyen; Hoang-Nam Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (643.518 KB) | DOI: 10.11591/ijece.v10i3.pp2434-2440

Abstract

The Fuzzy Gain Scheduling (FGS) methodology for tuning the Proportional – Integral – Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional – Integral – Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller.
An optimized approach for extensive segmentation and classification of brain MRI Harish S; G.F Ali Ahammed
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (387.617 KB) | DOI: 10.11591/ijece.v10i3.pp2392-2401

Abstract

With the significant contribution in medical image processing for an effective diagnosis of critical health condition in human, there has been evolution of various methods and techniques in abnormality detection and classification process. An insight to the existing approaches highlights that potential amount of work is being carried out in detection and segmentation process but less effective modelling towards classification problems. This manuscript discusses about a simple and robust modelling of a technique that offers comprehensive segmentation process as well as classification process using Artificial Neural Network. Different from any existing approach, the study offers more granularities towards foreground/background indexing with its comprehensive segmentation process while introducing a unique morphological operation along with graph-believe network for ensuring approximately 99% of accuracy of proposed system in contrast to existing learning scheme.
Evolutionary algorithms based tuning of PID controller for an AVR system Petchinathan Govindan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (869.631 KB) | DOI: 10.11591/ijece.v10i3.pp3047-3056

Abstract

In this paper, an evolutionary algorithm based optimization algorithm is proposed with new objective function to design a PID controller for the automatic voltage regulator (AVR) system. The new objective function is proposed to improve the transient response of the AVR control system and to obtain the optimal values of controller gain. In this paper, particle swarm optimization (PSO) and cuckoo search (CS) algorithms are proposed to tune the parameters of a PID controller for the control of AVR system. Simulation results are capable and illustrate the effectiveness of the proposed method. Numerical and simulation results based on the proposed tuning approach on PID control of an AVR system for servo and regulatory control show the excellent performance of PSO and CS optimization algorithms.
CPW fed SRR loaded monopole antenna for triple band operations Smitha K. M.; Aju John K. K.; Thomaskutty Mathew
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (548.74 KB) | DOI: 10.11591/ijece.v10i3.pp3145-3151

Abstract

A planar CPW fed SRR loaded monopole antenna based on split ring resonator with triple-band operations is reported for passive UHF RFID, Wireless Local Area Networks (WLAN) and World Interoperability for Microwave Access (WiMAX) applications. Measured and simulated results show the effect of tapering of the SRR layer on bandwidth improvement and gain enhancement in comparison to monopole with SRR antenna. The CPW fed SRR loaded monopole antenna has a bidirectional pattern with high gain for wireless communication applications.
Applying the big bang-big crunch metaheuristic to large-sized operational problems Yousef K. Qawqzeh; Ghaith Jaradat; Ali Al-Yousef; Anmar Abu-Hamdah; Ibrahim Almarashdeh; Mutasem Alsmadi; Mohammed Tayfour; Khalid Shaker; Firas Haddad
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (14.644 KB) | DOI: 10.11591/ijece.v10i3.pp2484-2502

Abstract

In this study, we present an investigation of comparing the capability of a big bang-big crunch metaheuristic (BBBC) for managing operational problems including combinatorial optimization problems. The BBBC is a product of the evolution theory of the universe in physics and astronomy. Two main phases of BBBC are the big bang and the big crunch. The big bang phase involves the creation of a population of random initial solutions, while in the big crunch phase these solutions are shrunk into one elite solution exhibited by a mass center. This study looks into the BBBC’s effectiveness in assignment and scheduling problems. Where it was enhanced by incorporating an elite pool of diverse and high quality solutions; a simple descent heuristic as a local search method; implicit recombination; Euclidean distance; dynamic population size; and elitism strategies. Those strategies provide a balanced search of diverse and good quality population. The investigation is conducted by comparing the proposed BBBC with similar metaheuristics. The BBBC is tested on three different classes of combinatorial optimization problems; namely, quadratic assignment, bin packing, and job shop scheduling problems. Where the incorporated strategies have a greater impact on the BBBC's performance. Experiments showed that the BBBC maintains a good balance between diversity and quality which produces high-quality solutions, and outperforms other identical metaheuristics (e.g. swarm intelligence and evolutionary algorithms) reported in the literature.
Prediction prices of basrah light oil using artificial neural networks Maysaa Abd Ulkareem Naser
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (822.9 KB) | DOI: 10.11591/ijece.v10i3.pp2682-2689

Abstract

The global economy is assured to be very sensitive to the volatility of the oil market. The beneficial from oil prices collapse are both consumers and developed countries. Iraq economy is a one-sided economy which is completely depends on oil revenue to charge the economic activity. Hence, the current decline in oil prices will produce serious concerns. Some factors stopped most investment projects, rationalize the recurrent outflow, and decrease the development of economic activity. The study of forecast oil prices is considered among the most complex studies because of the different dynamic variables that affects the strategic goods. Moreover, the laws of economics controlling the prices of oil such as the supply and demand law. Some other variables that control the oil prices are the political conditions when these conditions contribute to the world production. The subject of forecasting has been extremely developing during recent years and some modern methods have been appeared in this regards, for example, Artificial Neural Networks. In this study, an artificial neural network (FFNN) is adopted to extract the complex relationships among divergent parameters that have the abilities to predict oil prices serving as an inputs to the network data collected in this research represent monthly time series data are Oil prices series in (US dollars) over a period of 11 years (2008–2018) in Iraq
Combined cosine-linear regression model similarity with application to handwritten word spotting Youssef Elfakir; Ghizlane Khaissidi; Mostafa Mrabti; Driss Chenouni; Manal Boualam
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (642.954 KB) | DOI: 10.11591/ijece.v10i3.pp2367-2374

Abstract

The similarity or the distance measure have been used widely to calculate the similarity or dissimilarity between vector sequences, where the document images similarity is known as the domain that dealing with image information and both similarity/distance has been an important role for matching and pattern recognition. There are several types of similarity measure, we cover in this paper the survey of various distance measures used in the images matching and we explain the limitations associated with the existing distances. Then, we introduce the concept of the floating distance which describes the variation of the threshold’s selection for each word in decision making process, based on a combination of Linear Regression and cosine distance. Experiments are carried out on a handwritten Arabic image documents of Gallica library. These experiments show that the proposed floating distance outperforms the traditional distance in word spotting system.
Simulation, modelling and packet sniffing facilities for IoT: A systematic analysis Bimal Patel; Parth Shah
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (50.91 KB) | DOI: 10.11591/ijece.v10i3.pp2755-2762

Abstract

Man and Machine in terms of heterogeneous devices and sensors collaborate giving birth to the Internet of Things, Internet of future. Within a short span of time 30billions intelligent devices in form of smart applications will get connected making it difficult to test and debug in terms of time and cost.Simulators play vital role in verifying application and providing security before actually deploying it in real environment.Due to constraint environment in terms of memory, computation, and energy this review paper under a single umbrella will throw insight on comprehensive and in-depth analysis keeping in mind various barriers, critical design characteristics along with the comparison of candidate simulator and packet sniffing tool. Post simulated analysis play vital role in deciding behavior of data and helping research community to satisfy quality of service parameters.This review makes it feasible to make an appropriate choice for simulators and network analyzer tool easy fulfilling needs and making IoT a reality

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