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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
A non-negative matrix factorization based clustering to identify potential tuna fishing zones Devi Fitrianah; Hisyam Fahmi; Achmad Nizar Hidayanto; Pang Ning-Tan; Aniati Murni Arymurthy
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.pp5458-5466

Abstract

Many nonnegative matrix factorization based clusterings are employed in discovering pattern and knowledge. Considering the sparseness nature of our data set about the daily tuna fishing data, we attempted to utilize a clustering approach, which is based on non-negative matrix factorization. Adding sparseness constraint and assigning good initial value in the modified NMF method, a proposed algorithm Direct-NMFSC yielded better result cluster compared to other methods which are also utilizing sparse constraint to their approaches, SNMF and NMFSC. The result of this study shows that Direct-NMFSC has 5.376 times of iteration number less than NMFSC in average with 531.97 as the CH index result. The determination of potential fishing zones is one of the essential efforts in the potential fishing zone mapping system for tuna fishing. By means of this novel data-driven study to construct the information and to identify the potential tuna fishing zones is done. We also showed that utilizing the Direct-NMFSC can spot and identify the potential tuna fishing zones presented in red cluster that covers both the spatial and temporal information.
Disturbance observer-based controller for inverted pendulum with uncertainties: Linear matrix inequality approach Van-Phong Vu; Minh-Tam Nguyen; Anh-Vu Nguyen; Vi-Do Tran; Tran Minh Nguyet Nguyen
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.pp4907-4921

Abstract

A new approach based on linear matrix inequality (LMI) technique for stabilizing the inverted pendulum is developed in this article. The unknown states are estimated as well as the system is stabilized simultaneously by employing the observer-based controller. In addition, the impacts of the uncertainties are taken into consideration in this paper. Unlike the previous studies, the uncertainties in this study are unnecessary to satisfy the bounded constraints. These uncertainties will be converted into the unknown input disturbances, and then a disturbance observer-based controller will be synthesized to estimate the information of the unknown states, eliminate completely the effects of the uncertainties, and stabilize inverted pendulum system. With the support of lyapunov methodology, the conditions for constructing the observer and controller under the framework of linear matrix inequalities (LMIs) are derived in main theorems. Finally, the simulations for system with and without uncertainties are exhibited to show the merit and effectiveness of the proposed methods.
Design and analysis of multiple read port techniques using bank division with XOR method for multi-ported-memory on FPGA platform Druva Kumar S.; Roopa M.
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.pp4785-4793

Abstract

The multiple read and write operations are performed simultaneously by multi-ported memories and are used in advanced digital design applications on reprogrammable field-programmable gate arrays (FPGAs) to achieve higher bandwidth. The Memory modules are configured by block RAM (BRAMs), which utilizes more area and power on FPGA. In this manuscript, the techniques to increase the read ports for multi-ported memory modules are designed using the bank division with XOR (BDX) approach. The read port techniques like two read-one write (2R1W) memory, hybrid mode approach either 2R1W or 4R memory, and hierarchical BDX (HBDX) Approach using 2R1W/4R memory are designed on FPGA platform. The Proposed work utilizes only slices and look-up table (LUT's) rather than BRAMs while designing the memory modules on FPGA, which reduces the computational complexity and improves the system performance.  The experimental results are analyzed on Artix-7 FPGA. The performance parameters like slices, LUT utilization, maximum frequency (Fmax), and hardware efficiency are analyzed by concerning different memory depths. The 4R1W memory design using the HBDX approach utilizes 4% slices and works at 449.697 MHz operating frequency on Artix-7 FPGA. The proposed work provides a better platform to choose the proper read port technique to design an efficient modular multiport memory architecture.
A new method for vehicles detection and tracking using information and image processing Mazouzi Amine; Kerfa Djoudi; Ismail Rakip Karas
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.pp4942-4949

Abstract

In this article, a new method of vehicles detecting and tracking is presented: A thresholding followed by a mathematical morphology treatment are used. The tracking phase uses the information about a vehicle. An original labeling is proposed in this article. It helps to reduce some artefacts that occur at the detection level. The main contribution of this article lies in the possibility of merging information of low level (detection) and high level (tracking). In other words, it is shown that many artefacts resulting from image processing (low level) can be detected, and eliminated thanks to the information contained in the labeling (high level). The proposed method has been tested on many video sequences and examples are given illustrating the merits of our approach.
Mining knowledge graphs to map heterogeneous relations between the internet of things patterns Vusi Sithole; Linda Marshall
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.pp5066-5080

Abstract

Patterns for the internet of things (IoT) which represent proven solutions used to solve design problems in the IoT are numerous. Similar to object-oriented design patterns, these IoT patterns contain multiple mutual heterogeneous relationships. However, these pattern relationships are hidden and virtually unidentified in most documents. In this paper, we use machine learning techniques to automatically mine knowledge graphs to map these relationships between several IoT patterns. The end result is a semantic knowledge graph database which outlines patterns as vertices and their relations as edges. We have identified four main relationships between the IoT patterns-a pattern is similar to another pattern if it addresses the same use case problem, a large-scale pattern uses a small- scale pattern in a lower level layer, a large pattern is composed of multiple smaller scale patterns underneath it, and patterns complement and combine with each other to resolve a given use case problem. Our results show some promising prospects towards the use of machine learning techniques to generate an automated repository to organise the IoT patterns, which are usually extracted at various levels of abstraction and granularity.
Using the modified k-mean algorithm with an improved teaching-learning-based optimization algorithm for feedforward neural network training Morteza Jouyban; Mahdieh Khorashadizade
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.pp5277-5285

Abstract

In this paper we proposed a novel procedure for training a feedforward neural network. The accuracy of artificial neural network outputs after determining the proper structure for each problem depends on choosing the appropriate method for determining the best weights, which is the appropriate training algorithm. If the training algorithm starts from a good starting point, it is several steps closer to achieving global optimization. In this paper, we present an optimization strategy for selecting the initial population and determining the optimal weights with the aim of minimizing neural network error. Teaching-learning-based optimization (TLBO) is a less parametric algorithm rather than other evolutionary algorithms, so it is easier to implement. We have improved this algorithm to increase efficiency and balance between global and local search. The improved teaching-learning-based optimization (ITLBO) algorithm has added the concept of neighborhood to the basic algorithm, which improves the ability of global search. Using an initial population that includes the best cluster centers after clustering with the modified k-mean algorithm also helps the algorithm to achieve global optimum. The results are promising, close to optimal, and better than other approach which we compared our proposed algorithm with them.
Smart information desk system with voice assistant for universities Dabiah Alboaneen; Dalia Alsaffar; Amani Alqahtani; Lama Alamri; Amjad Alfahhad; Bashaier Alqahtani; Alyah Alateeq; Rahaf Alamri; Fatimah Almohammedsaleh
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.pp5206-5215

Abstract

This article aims to develop a smart information desk system through a smart mirror for universities. It is a mirror with extra capabilities of displaying answers for academic inquiries such as asking about the lecturers’ office numbers and hours, exams dates and times on the mirror surface. In addition, the voice recognition feature was used to answer spoken inquiries in audio responds to serve all types of users including disabled ones. Furthermore, the system showed general information such as date, weather, time and the university map. The smart mirror was connected to an outdoor camera to monitor the traffics at the university entrance gate. The system was implemented on a Raspberry Pi 4 model B connected to a two-way mirror and an infrared (IR) touch frame. The results of this study helped to overcome the problem of the information desk absence in the university. Therefore, it helped users to save their time and effort in making requests for important academic information.
A novel optimal small cells deployment for next-generation cellular networks Nael A. Al-Shareefi; Ammar AbdRaba Sakran
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.pp5259-5265

Abstract

Small-cell-deployments have pulled cellular operators to boost coverage and capacity in high-demand areas (for example, downtown hot spots). The location of these small cells (SCs) should be determined in order to achieve successful deployments. In this paper, we propose a new approach that optimizes small cells deployment in cellular networks to achieve three objectives: reduce the total cost of network installation, balancing the allocation of resources, i.e. placement of each SC and their transmitted power, and providing optimal coverage area with a lower amount of interference between adjacent stations. An accurate formula was obtained to determine the optimum number of SC deployment (NSC). Finally, we derive a mathematical expression to calculate the critical-handoff-point (CHP) for neighboring wireless stations.
A fuzzy rule based approach for islanding detection in grid connected inverter systems Naima Ikken; Nour-Eddine Tariba; Abdelhadi Bouknadel; Ahmed Haddou; Hafsa El Omari; Hamid El Omari
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.pp4759-4766

Abstract

Islanding is when an area of the electrical distribution system is isolated from the electrical system while being powered by distributed generators. An important condition for the interconnection of power plants and distribution systems is the ability of the power plant to detect islands. The presented and proposed method is a combination of best active sandia frequency shift (SFS) method with the intelligent fuzzy logic controller, which has been tested in distributed production using the island detection function. And the choice to improve the method by fuzzy logic control (FLC) is retained, as this process is more effective in decreasing the non-detection zone (NDZ) and in further improving the efficiency of the islanding detection system. This paper proposes a new active islanding detection technique controlled by a fuzzy logic controller, for grid connected photovoltaic (PV) inverters. In addition, the efficiency and performance of the proposed method strategy for islanding detection has been analyzed and tested in the various situations of the network. In addition, the results of the simulations with the power simulation (PSIM) software will be provided to illustrate the main conclusions and the development of the control. Thus, will be used to show the feasibility and validity of the proposed new algorithm.
Image retrieval based on swarm intelligence Shahbaa I. Khaleel; Ragad W. Khaled
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.pp5390-5401

Abstract

To keep pace with the development of modern technology in this information technology era, and the immense image databases, whether personal or commercial, are increasing, is requiring the management of these databases to strong and accurate systems to retrieve images with high efficiency. Because of the swarm intelligence algorithms are great importance in solving difficult problems and obtaining the best solutions. Here in this research, a proposed system is designed to retrieve color images based on swarm intelligence algorithms. Where the algorithm of the ant colony optimization (ACOM) and the intelligent water drop (IWDM) was used to improve the system's work by conducting the clustering process in these two methods on the features extracted by annular color moment method (ACM) to obtain clustered data, the amount of similarity between them and the query image, is calculated to retrieve images from the database, efficiently and in a short time. In addition, improving the work of these two methods by hybridizing them with fuzzy method, fuzzy gath geva clustering algorithm (FGCA) and obtaining two new high efficiency hybrid algorithms fuzzy ant colony optimization method (FACOM) and fuzzy intelligent water drop method (FIWDM) by retrieving images whose performance values are calculated by calculating the values of precision, recall and the f-measure. It proved its efficiency by comparing it with fuzzy method, FGCA and by methods of swarm intelligence without hybridization, and its work was excellent.

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