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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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A Smart Management Approach Investigation for Hybrid Autonomous Power System Nasri Sihem; Ben Slama Sami; Cherif Adnane
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 6: December 2015
Publisher : Institute of Advanced Engineering and Science

A novel design of system management based on multi-agents approach applied to an autonomous hybrid power system is proposed and investigated. The system under study integrates few elements, some serve to provide power requirements, while the others used to store energy. Among these items, we can mention a Solar Power Source namely (SPS) which works as primary source to feed a DC electric load. The system integrates also a secondary power source namely Power Recovery Source (PRS) based on a fuel cell technology used to compensate the power deficit if required. More than two kinds of energy storage, the first called Hydrogen Generation Element (HGE) including a water electrolyzer to store the energy in hydrogen form, while the second uses an Ultracapacitor Element (UE) to store the energy in its electrical form. To reach the well functioning of the system in order to satisfy the load requirements whatever the facts, an intelligent energy management approach based on multi-agent modeling is implemented and verified. Hence, the reliability and the effectiveness of the applied management strategy, which allows the coordination between the different energy sources and protects the system against any fluctuation, are proved by the obtained results from Matlab/Simulink.

Soybean leaf disease detection and severity measurement using multiclass SVM and KNN classifier Sachin B. Jadhav; Vishwanath R. Udup; Sanjay B. Patil
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Soybean fungal diseases such as Blight, Frogeye leaf spot and Brown Spot are a significant threat to soybean plant due to the severe symptoms and lack of treatments. Traditional diagnosis of the thease diseases relies on disease symptom identification based on neaked eye observation by pathalogiest, which can lead to a high rate of false-recognition. This work present a novel system, utilizing multiclass support vector machine and KNN classifiers, for detection and classification of soybean diseases using color images of diseased leaf samples. Images of healthy and diseased leaves affected by Blight, Frogeye leaf spot and Brown Spot were acquired by a digital camera. The acquired images are preprocessed using image enhancement techniques. The background of each image was removed by a thresholding method and the Region of Interest (ROI) is obtained. Color-based segmentation technique based on K-means clustering is applied to the region of interest for partitioning the diseased region. The severity of disease is estimated by quantifying a number of pixels in the diseased region and in total leaf region. Different color features of segmented diseased leaf region were extracted using RGB color space and texture features were extracted using Gray Level Co-occurrence Matrix (GLCM) to compose a feature database. Finally, the support vector machine (SVM) and K-Nearest Negbiour (KNN) classifiers are used for classifying the disease. This proposed classifers system is capable to classify the types of blight, brown spot, frogeye leaf spot diseases and Healthy samples with an accuracy of 87.3% and 83.6 % are achieved.

A Proposal for End-to-End QoS Provisioning in Software-Defined Networks Francesco Lucrezia; Guido Marchetto; Fulvio Risso; Michele Santuari; Matteo Gerola
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 4: August 2017
Publisher : Institute of Advanced Engineering and Science

This paper describes a framework application for the control plane of a network infrastructure; the objective is to feature end-user applications with the capability of requesting at any time a customised end-to-end Quality-of-Service profile in the context of dynamic Service-Level-Agreements. Our solution targets current and future real-time applications that require tight QoS parameters, such as a guaranteed end-to-end delay bound. These applications include, but are not limited to, health-care, mobility, education, manufacturing, smart grids, gaming and much more. We discuss the issues related to the previous Integrated Service and the reason why the RSVP protocol for guaranteed QoS did not take off. Then we present a new signaling and resource reservation framework based on the cutting-edge network controller ONOS. Moreover, the presented system foresees the need of considering the edges of the network, where terminal applications are connected to, to be piloted by distinct logically centralised controllers. We discuss a possible inter-domain communication mechanism to achieve the end-to-end QoS guarantee.

Spam image email filtering using K-NN and SVM Yasmine Khalid Zamil; Suhad A. Ali; Mohammed Abdullah Naser
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

The developing utilization of web has advanced a simple and quick method for e-correspondence. The outstanding case for this is e-mail. Presently days sending and accepting email as a method for correspondence is prominently utilized. Be that as it may, at that point there stand up an issue in particular, Spam mails. Spam sends are the messages send by some obscure sender just to hamper the improvement of Internet e.g. Advertisement and many more. Spammers introduced the new technique of embedding the spam mails in the attached image in the mail. In this paper, we proposed a method based on combination of SVM and KNN. SVM tend to set aside a long opportunity to prepare with an expansive information set. On the off chance that "excess" examples are recognized and erased in pre-handling, the preparation time could be diminished fundamentally. We propose a k-nearest neighbor (k-NN) based example determination strategy. The strategy tries to select the examples that are close to the choice limit and that are effectively named. The fundamental thought is to discover close neighbors to a question test and prepare a nearby SVM that jelly the separation work on the gathering of neighbors. Our experimental studies based on a public available dataset (Dredze) show that results are improved to approximately 98%.

A secure image steganography based on JND model Tuan Duc Nguyen; Dung Huu Le
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Minimizing distortion produced by embedding process is very important to improve the security of hidden message and maintain the high visual quality of stego images. To achieve these objectives, an effective strategy is to perform pixel selection which is well-known as a channel selection rule. In this approach, a pixel associated with the smallest image degradation is chosen to carry secret bits. From these facts, in this paper, a new secure channel selection rule for digital images in spatial domain is designed and proposed. In this new approach, the modified matrix embedding method is utilized as data hiding method because it introduces more than one embedding change to be performed. This enables us to select a suitable pixel to embed message bits with less degradation yielded in a stego-image. In pixel selection of the proposed method, a just noticeable difference value and gradient value of a considering pixel are employed together. The experimental results (which were conducted on 10,000 uncompressed images) indicate that stego images of the proposed approach achieve a higher perceptual quality and security than those of the stego-images created by the previous approaches.

Exploration of Corpus Augmentation Approach for English-Hindi Bidirectional Statistical Machine Translation System K. Jaya; Deepa Gupta
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 3: June 2016
Publisher : Institute of Advanced Engineering and Science

Even though lot of Statistical Machine Translation(SMT) research work is happening for English-Hindi language pair, there is no effort done to standardize the dataset. Each of the research work uses different dataset, different parameters and different number of sentences during various phases of translation resulting in varied translation output. So comparing these models, understand the result of these models, to get insight into corpus behavior for these models, regenerating the result of these research work becomes tedious. This necessitates the need for standardization of dataset and to identify the common parameter for the development of model. The main contribution of this paper is to discuss an approach to standardize the dataset and to identify the best parameter which in combination gives best performance. It also investigates a novel corpus augmentation approach to improve the translation quality of English-Hindi bidirectional statistical machine translation system. This model works well for the scarce resource without incorporating the external parallel data corpus of the underlying language. This experiment is carried out using Open Source phrase-based toolkit Moses. Indian Languages Corpora Initiative (ILCI) Hindi-English tourism corpus is used. With limited dataset, considerable improvement is achieved using the corpus augmentation approach for the English-Hindi bidirectional SMT system.

An Effiecient Approach for Resource Auto-Scaling in Cloud Environments Bahar Asgari; Mostafa Ghobaei Arani; Sam Jabbehdari
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 5: October 2016
Publisher : Institute of Advanced Engineering and Science

Cloud services have become more popular among users these days. Automatic resource provisioning for cloud services is one of the important challenges in cloud environments. In the cloud computing environment, resource providers shall offer required resources to users automatically without any limitations. It means whenever a user needs more resources, the required resources should be dedicated to the users without any problems. On the other hand, if resources are more than user’s needs extra resources should be turn off temporarily and turn back on whenever they needed. In this paper, we propose an automatic resource provisioning approach based on reinforcement learning for auto-scaling resources according to Markov Decision Process (MDP). Simulation Results show that the rate of Service Level Agreement (SLA) violation and stability that the proposed approach better performance compared to the similar approaches.

PID Controller Design for Two Tanks Liquid Level Control System Using Matlab Mostafa Abdul Fellani; Aboubaker M. Gabaj
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 3: June 2015
Publisher : Institute of Advanced Engineering and Science

The industrial application of Coupled Tank System (CTS) is widely used especially in chemical process industries. The control of liquid level in tanks and flow between tanks is a problem in the process technologies. The process technologies require liquids to be pumped, stored in tanks, and then pumped to another tank systematically. This paper presents development of Proportional-Integral-Derivative (PID) controller for controlling the desired liquid level of the CTS. Various conventional techniques of PID tuning method will be tested in order to obtain the PID controller parameters. Simulation is conducted within MATLAB environment to verify the performances of the system in terms of Rise Time (Ts), Settling Time (Ts), Steady State Error (SSE) and Overshoot (OS). The trial and error method of tunning will be implemented and all the performance results will be analyzed using MATLAB. It has been demonstrated that performances of CTS can be improved with appropriate technique of PID tuning methods.

Statistical analysis of spinal cord injury severity detection on high dimensional MRI data Sk HasaneAhammad; V Rajesh; K Saikumar; Sridevi Jalakam; G.N.S. Kumar
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Staggered Segmenting on the programmed spinal rope form is a vital advance for evaluating spinal line decay in different infections. Outlining dark issue (GM) and white issue (WM) is additionally helpful for measuring GM decay or for extricating multiparametric MRI measurements into WMs tracts. Spinal line division in clinical research isn't as created as cerebrum division, anyway with the considerable change of MR groupings adjusted to spinal line MR examinations, the field of spinal rope MR division has progressed extraordinarily inside the most recent decade. Division strategies with variable exactness and level of multifaceted nature have been produced. In this paper, we talked about a portion of the current strategies for line and WM/GM division, including power based, surface-based, and picture based and staggered based techniques. We likewise give suggestions to approving spinal rope division systems, as it is essential to comprehend the inborn qualities of the strategies and to assess their execution and constraints. In conclusion, we represent a few applications in the solid and neurotic spinal string. In this task, an Automatic Spinal Cord Injury (SCI) is identified utilizing a staggered division technique.

Improvement of Fading Channel Modeling Performance for Wireless Channel Inaam Abbas Heider
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Fading channel modeling is generally defined as the variation of the attenuation of a signal with various variables. Time, geographical position, and radio frequency which is included. Fading is often modeled as a random process. Thus, a fading channel is a communication channel that experiences fading. In this paper, the proposed system presents a new design and simulate a wireless channel using Rayleigh channels. Rayleigh channels using two approaches (flat and frequency-selective fading channels) in order to calculate some path space loss efforts and analysis the performance of different wireless fading channel modeling. The results show that the bite error rate (BER) performance is dramatically improved in the value of signal to noise ratio (SNR) is equal to 45dB. Finally, the experimental results show that the proposed method enhances the performance of fading channel modeling by reducing the error of BER when the SNR is reduced also. Moreover, the more accurate model is Rayleigh model which can be considered for developing fading channel model.

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Home Page

OAI Link

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

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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