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International Journal of Electrical and Computer Engineering

IJECE
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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 6,301 Documents

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Optimal parameters of inverter-based microgrid to improve transient response Sergio Andrés Pizarro Pérez; John E. Candelo-Becerra; Fredy E. Hoyos Velasco
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

The inertia issues in a microgrid can be improved by modifying the inverter control strategies to represent a virtual inertia simulation. This method employs the droop control strategy commonly used to share the power of a load among different power sources in the microgrid. This paper utilizes a modified droop control that represents this virtual inertia and applies an optimization algorithm to determine the optimal parameters and improve transient response. The results show better control when different variations are presented in the loads, leading the microgrid to have a better control of the operation. The optimization method applied in this research allows improvement to the transient response, thus avoiding unnecessary blackouts in the microgrid.

Network Activity Monitoring Against Malware in Android Operating System Luis Miguel Acosta-Guzman; Gualberto Aguilar-Torres; Gina Gallegos-Garcia
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 1: February 2016
Publisher : Institute of Advanced Engineering and Science

Google’s Android is the most used Operating System in mobile devices but as its popularity has increased hackers have taken advantage of the momentum to plague Google Play (Android’s Application Store) with multipurpose Malware that is capable of stealing private information and give the hacker remote control of smartphone’s features in the worst cases. This work presents an innovative methodology that helps in the process of malware detection for Android Operating System, which addresses aforementioned problem from a different perspective that even popular Anti-Malware software has left aside. It is based on the analysis of a common characteristic to all different kinds of malware: the need of network communications, so the victim device can interact with the attacker. It is important to highlight that in order to improve the security level in Android, our methodology should be considered in the process of malware detection. As main characteristic, it does not need to install additional kernel modules or to root the Android device. And finally as additional characteristic, it is as simple as can be considered for non-experienced users.

Reversed-Trellis Tail-Biting Convolutional Code (RT-TBCC) Decoder Architecture Design for LTE Trio Adiono; Ahmad Zaky Ramdani; Rachmad Vidya Wicaksana Putra
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Tail-biting convolutional codes (TBCC) have been extensively applied in communication systems. This method is implemented by replacing the fixed-tail with tail-biting data. This concept is needed to achieve an effective decoding computation. Unfortunately, it makes the decoding computation becomes more complex. Hence, several algorithms have been developed to overcome this issue in which most of them are implemented iteratively with uncertain number of iteration. In this paper, we propose a VLSI architecture to implement our proposed reversed-trellis TBCC (RT-TBCC) algorithm. This algorithm is designed by modifying direct-terminating maximum-likelihood (ML) decoding process to achieve better correction rate. The purpose is to offer an alternative solution for tail-biting convolutional code decoding process with less number of computation compared to the existing solution. The proposed architecture has been evaluated for LTE standard and it significantly reduces the computational time and resources compared to the existing direct-terminating ML decoder. For evaluations on functionality and Bit Error Rate (BER) analysis, several simulations, System-on-Chip (SoC) implementation and synthesis in FPGA are performed.

Modeling and Simulation of Fuel cell (Dicks Larminie Model) based 3-Phase Voltage Source Inverter Gaurav Sachdeva
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 5: October 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (203.913 KB)

In the present work, performance of three phase voltage source inverter, while feeding different power factor loads, has been investigated. Fuel cells model namely Dicks Larminie model is used in input side as a DC source while dynamic load has been used at the output side. Dynamic load used is induction motor (IM). Performance of IM has been investigated under various loading conditions. ANN based control strategy has been proposed to find the conduction angle of a 3-Phase VSI and verified for IM load. Simulations have been performed using PSIM 7.0.5 and MATLAB 7.0.4.DOI:http://dx.doi.org/10.11591/ijece.v4i5.5508

Performance Evaluation of Fine-tuned Faster R-CNN on specific MS COCO Objects Garima Devnani; Ayush Jaiswal; Roshni John; Rajat Chaurasia; Neha Tirpude
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Fine-tuning of a model is a method that is most often required to cater to the users’ explicit requirements. But the question remains whether the model is accurate enough to be used for a certain application. This paper strives to present the metrics used for performance evaluation of a Convolutional Neural Network (CNN) model. The evaluation is based on the training process which provides us with intermediate models after every 1000 iterations. While 1000 iterations are not substantial enough over the range of 490k iterations, the groups are sized with 100k iterations each. Now, the intention was to compare the recorded metrics to evaluate the model in terms of accuracy. The training model used the set of specific categories chosen from the Microsoft Common Objects in Context (MS COCO) dataset while allowing the users to use their externally available images to test the model’s accuracy. Our trained model ensured that all the objects are detected that are present in the image to depict the effect of precision.

Organization Goal-Oriented Requirements Elicitation Process to Enhance Information System Fransiskus Adikara; Bayu Hendradjaya; Benhard Sitohang
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

This paper introduces and proposes an approach in goal-oriented requirements elicitation process that using Key Performance Indicators (KPIs), in information system enhancement process. KPIs can be used to control and reduce user requirements problems caused by personal interests of users in requirements elicitation process. An information system enhancement project for a distribution company has been used as a case study to demonstrate this approach. The case study shows that the requirements can be elicited from the organization goals and current information system condition rather than from user requirements. This approach also showed that KPIs have been able to control some user requirements that have difference point of view with high level stakeholder requirements. Compared with the previous research, IT goals and KPIs are more easily identified in the enhancement process rather than through development of a brand new information system.

Convolutional neural network-based model for web-based text classification Satyabrata Aich; Sabyasachi Chakraborty; Hee-Cheol Kim
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

There is an increasing amount of text data available on the web with multiple topical granularities; this necessitates proper categorization/classification of text to facilitate obtaining useful information as per the needs of users. Some traditional approaches such as bag-of-words and bag-of-ngrams models provide good results for text classification. However, texts available on the web in the current state contain high event-related granularity on different topics at different levels, which may adversely affect the accuracy of traditional approaches. With the invention of deep learning models, which already have the capability of providing good accuracy in the field of image processing and speech recognition, the problems inherent in the traditional text classification model can be overcome. Currently, there are several deep learning models such as a convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long-short term memory that are widely used for various text-related tasks; however, among them, the CNN model is popular because it is simple to use and has high accuracy for text classification. In this study, classification of random texts on the web into categories is attempted using a CNN-based model by changing the hyperparameters and sequence of text vectors. We attempt to tune every hyperparameter that is unique for the classification task along with the sequences of word vectors to obtain the desired accuracy; the accuracy is found to be in the range of 85–92%. This model can be considered as a reliable model and applied to solve real-world problem or extract useful information for various text mining applications.

Performance Investigation of OFDM-FSO System under Diverse Weather Conditions of Bangladesh Maliha Sultana; Agnila Barua; Jobaida Akhtar; Mohammad Istiaque Reja
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Free space optical (FSO) communication systems which are deployed for last mile access, being considered as a suitable alternative technology for optical fiber networks. It is one of the emerging technologies for broadband wireless connectivity which has also been receiving growing attention due to high data rate transmission capability with low installation cost and license free spectrum. However, the widespread use of FSO technology has been hampered by the randomly time varying characteristics of propagation path mainly due to atmospheric turbulence, sensitivity to diverse weather conditions and the nonlinear responsivity of laser diode. This paper presents the performance investigation of an OFDM-FSO system over atmospheric turbulence channels under diverse weather conditions of Bangladesh. The channel is modeled with gamma-gamma distribution using 16-QAM modulation format and 4×4 multiple transceiver FSO system. All possible challenges are imposed on the system performance such as atmospheric attenuation, turbulence, pointing error, geometric loss etc. The refractive index structure parameter and atmospheric attenuation coefficient for different weather conditions are calculated by using the data, collected from Bangladesh Meteorological Department. The acquired results can be fruitful for scheming, forecasting and assessing the OFDM-FSO system’s ability to transmit wireless services over turbulent FSO links under actual conditions of Bangladesh.

Proposed algorithm for image classification using regression-based pre-processing and recognition models Chanintorn Jittawiriyanukoon
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science

Image classification algorithms can categorise pixels regarding to image attributes with the pre-processing of learner’s trained samples. The precision and classification accuracy are complex to compute due to the variable size of pixels (different image width and height) and numerous characteristics of image per se. This research proposes an image classification algorithm based on regression-based pre-processing and the recognition models. The proposed algorithm focuses on an optimization of pre-processing results such as accuracy and precision. To evaluate and validate, recognition model is mapped in order to cluster the digital images which are developing the problem of a multidimensional state space. Simulation results show that compared to existing algorithms, the proposed method outperforms with the optimal number of precision and accuracy in classification as well as results higher matching percentage based upon image analytics.

Theoretical Analysis of a Two-stage Sagnac loop filter using Jones Matrices N. A. B. Ahmad; S. H. Dahlan; N. A. Cholan
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

In this work, a theoretical analysis of a Sagnac loop filter (SLF) with two-stage polarization maintaining fibers (PMFs) and polarization controllers (PCs) is presented. The transmission function of this two-stage SLF is calculated in detail by using Jones matrix. The calculation is performed in order to investigate the filtering characteristics. The theoretical results show that the wavelength interval is depending on the dynamic settings of the length of the PMFs and the polarization angle of the PCs. By changing the polarization angle of the PCs, a multiple of single, dual or triple wavelength in each channel can be achieved. Based on this study, a flat multiwavelength spectrum can be obtained by adjusting the PMFs and the PCs in the two-stage SLF. This finding significantly contributes to the generation of multiwavelength fiber laser (MWFL) that can be used for many optical applications.

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Tole Sutikno

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ijece@iaesjournal.com

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Location
Kota yogyakarta,

Daerah istimewa yogyakarta

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

Phone -

Journal Mail Official ijece@iaesjournal.com

Editorial Address -

Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA