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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 70 Documents

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Search results for , issue "Vol 7, No 5: October 2017" : 70 Documents clear

SVM Classification of MRI Brain Images for Computer-Assisted Diagnosis Madina Hamiane; Fatema Saeed
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Magnetic Resonance Imaging is a powerful technique that helps in the diagnosis of various medical conditions. MRI Image pre-processing followed by detection of brain abnormalities, such as brain tumors, are considered in this work. These images are often corrupted by noise from various sources. The Discrete Wavelet Transforms (DWT) with details thresholding is used for efficient noise removal followed by edge detection and threshold segmentation of the denoised images. Segmented image features are then extracted using morphological operations. These features are finally used to train an improved Support Vector Machine classifier that uses a Gausssian radial basis function kernel. The performance of the classifier is evaluated and the results of the classification show that the proposed scheme accurately distinguishes normal brain images from the abnormal ones and benign lesions from malignant tumours. The accuracy of the classification is shown to be 100% which is superior to the results reported in the literature.

Parameter Extraction of PV Module using NLS Algorithm with Experimental Validation Alivarani Mohapatra; Byamakesh Nayak; K.B. Mohanty
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Photovoltaic (PV) module parameters act an important task in PV system design and simulation. Most popularly used single diode Rsh model has five unknown electrical parameters such as series resistance (Rse), shunt resistance (Rsh), diode quality factor (a), photo-generated current (Ipg) and dark saturation current (Is) in the mathematical model of PV module. The PV module output voltage and current relationship is represented by a transcendental equation and is not possible to solve analytically. This paper proposes nonlinear least square (NLS) technique to extract five unknown parameters. The proposed technique is compared with other two popular techniques available in the literature such as Villalva’s comprehensive technique and modified Newton-Raphson (N-R) technique. Only two parameters Rse and Rsh are estimated by Villalva’s technique, but all single diode unknown electrical parameters can be estimated by the NLS technique. The accuracy of different estimation techniques is compared in terms of absolute percentage errors at MPP and is found the minimum for the proposed technique. The elapsed time for parameter estimation for NLS technique is minimum and much less compared to other two techniques. Extracted parameters of polycrystalline ELDORA-40 PV panel by the proposed technique have been validated through simulation and experimental current-voltage (I-V) and power-voltage (P-V) characteristics.

Optimization of Fuzzy Tsukamoto Membership Function using Genetic Algorithm to Determine the River Water Qoirul Kotimah; Wayan Firdaus Mahmudy; Vivi Nur Wijayaningrum
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Some aquatic ecosystems in rivers depend on the river water, so it needs to be maintained by measuring and analyzing the river water quality. STORET is one of the methods used to measure the river water quality, but it takes a quite high of time and costs. Fuzzy Tsukamoto is an alternative method that works by grouping the river water data, but it is difficult to determine the membership function value. The solution offered in this study is the use of genetic algorithm to determine the membership function value of each criterion. Based on the test results, the optimization of fuzzy membership function using genetic algorithm provides higher accuracy value that is 95%, while the accuracy value without optimization process is 90%. The parameters used in genetic algorithm are as follows: population size is 80, generation number is 175, crossover rate (cr) is 0.6, and mutation rate (mr) is 0.4.

Enabling External Factors for Inflation Rate Forecasting Using Fuzzy Neural System Nadia Roosmalita Sari; Wayan Firdaus Mahmudy; Aji Prasetya Wibawa; Elta Sonalitha
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Inflation is the tendency of increasing prices of goods in general and happens continuously. Indonesia's economy will decline if inflation is not controlled properly. To control the inflation rate required an inflation rate forecasting in Indonesia. The forecasting result will be used as information to the government in order to keep the inflation rate stable. This study proposes Fuzzy Neural System (FNS) to forecast the inflation rate. This study uses historical data and external factors as the parameters. The external factor using in this study is very important, which inflation rate is not only affected by the historical data. External factor used are four external factors which each factor has two fuzzy set. While historical data is divided into three input variables with three fuzzy sets. The combination of three input variables and four external factors will generate too many rules. Generate of rules with too many amounts will less effective and have lower accuracy. The novelty is needed to minimalize the amount of rules by using two steps fuzzy. To evaluate the forecasting results, Root Means Square Error (RMSE) technique is used. Fuzzy Inference System Sugeno used as the comparison method. The study results show that FNS has a better performance than the comparison method with RMSE that is 1.81.

Inertial Navigation for Quadrotor Using Kalman Filter with Drift Compensation Lasmadi Lasmadi; Adha Imam Cahyadi; Samiadji Herdjunanto; Risanuri Hidayat
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

The main disadvantage of an Inertial Navigation System is a low accuracy due to noise, bias, and drift error in the inertial sensor. This research aims to develop the accelerometer and gyroscope sensor for quadrotor navigation system, bias compensation, and Zero Velocity Compensation (ZVC). Kalman Filter is designed to reduce the noise on the sensor while bias compensation and ZVC are designed to eliminate the bias and drift error in the sensor data. Test results showed the Kalman Filter design is acceptable to reduce the noise in the sensor data. Moreover, the bias compensation and ZVC can reduce the drift error due to integration process as well as improve the position estimation accuracy of the quadrotor. At the time of testing, the system provided the accuracy above 90 % when it tested indoor.

Insights on Research Techniques towards Cost Estimation in Software Design Praveen Naik; Shantaram Nayak
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Software cost estimation is of the most challenging task in project management in order to ensuring smoother development operation and target achievement. There has been evolution of various standards tools and techniques for cost estimation practiced in the industry at present times. However, it was never investigated about the overall picturization of effectiveness of such techniques till date. This paper initiates its contribution by presenting taxonomies of conventional cost-estimation techniques and then investigates the research trends towards frequently addressed problems in it. The paper also reviews the existing techniques in well-structured manner in order to highlight the problems addressed, techniques used, advantages associated and limitation explored from literatures. Finally, we also brief the explored open research issues as an added contribution to this manuscript.

PWM Dimming for High Brightness LED Based Automotive Lighting Applications Muhammad Wasif Umar; Norzaihar Yahaya; Zuhairi Baharuddin
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

In recent years, the use of high brightness LEDs has become increasingly accepted as light sources in mainstream vehicles. However, they are semiconductor devices and their electrical characteristics are completely different to the traditional lamps. The output luminous flux of an LED is determined by the forward current running through it. Hence they cannot be powered directly from the automotive battery using the conventional driving techniques. They require specialised driving circuits which can respond to the changing needs of the LEDs as their electrical properties change, while maintaining the uniform brightness. This paper discusses the importance of dimming for LED based automotive lighting applications. A boost type DC-DC switching converter with pulse width modulated (PWM) dimming control has been proposed. MATLAB/Simulink simulation package has been used to verify the theoretical predictions hence to provide a useful guide for design engineers and researchers.

Feasibility of Substitution of the Conventional Street Lighting Installation by the Photovoltaic Case Study on a Municipality in Agadir in Morocco Fatima Outferdine; Lahoussine Bouhouch; Mustapha Kourchi; Mohamed Ajaamoum; Ali Moudden
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

In this work, we present a technical and economic study of the solar powered street lighting system of a municipality in the south of Morocco. The state of the conventional street lighting system is first analyzed in a substation of street lighting. Then a sizing method is applied to the photovoltaic installation in the testing area. A financial study, by comparison between conventional and PV-based lighting, is carried out showing the feasibility of the PV street lighting.

Privacy Preserving Auction Based Virtual Machine Instances Allocation Scheme for Cloud Computing Environment Suneeta Mohanty; Prasant Kumar Pattnaik; G. B. Mund
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Cloud Computing Environment provides computing resources in the form of Virtual Machines (VMs), to the cloud users through Internet. Auction-based VM instances allocation allows different cloud users to participate in an auction for a bundle of Virtual Machine instances where the user with the highest bid value will be selected as the winner by the auctioneer (Cloud Service Provider) to gain more. In this auction mechanism, individual bid values are revealed to the auctioneer in order to select the winner as a result of which privacy of bid values are lost. In this paper, we proposed an auction scheme to select the winner without revealing the individual bid values to the auctioneer to maintain privacy of bid values. The winner will get the access to the bundle of VM instances. This scheme relies on a set of cryptographic protocols including Oblivious Transfer (OT) protocol and Yao’s protocol to maintain privacy of bid values.

A Novel Approach Based on Decreased Dimension and Reduced Gray Level Range Matrix Features for Stone Texture Classification G. S. N. Murthy; Srininvasa Rao. V; T. Veerraju
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

The human eye can easily identify the type of textures in flooring of the houses and in the digital images visually. In this work, the stone textures are grouped into four categories. They are bricks, marble, granite and mosaic. A novel approach is developed for decreasing the dimension of stone image and for reducing the gray level range of the image without any loss of significant feature information. This model is named as “Decreased Dimension and Reduced Gray level Range Matrix (DDRGRM)” model. The DDRGRM model consists of 3 stages. In stage 1, each 5×5 sub dimension of the stone image is reduced into 2×2 sub dimension without losing any important qualities, primitives, and any other local stuff. In stage 2, the gray level of the image is reduced from 0-255 to 0-4 by using fuzzy concepts. In stage 3, Co-occurrence Matrix (CM) features are derived from the DDRGRM model of the stone image for stone texture classification. Based on the feature set values, a user defined algorithm is developed to classify the stone texture image into one of the 4 categories i.e. Marble, Brick, Granite and Mosaic. The proposed method is tested by using the K-Nearest Neighbor Classification algorithm with the derived texture features. To prove the efficiency of the proposed method, it is tested on different stone texture image databases. The proposed method resulted in high classification rate when compared with the other existing methods.

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Tole Sutikno

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Location
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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

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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