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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 69 Documents
Search results for , issue "Vol 8, No 2: April 2018" : 69 Documents clear
An Internal Current Controlled BLDC Motor Drive Supplied with PV Fed High Voltage Gain DC-DC Converter G. G. Raja Sekhar; Basavaraja Banakara
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (436.662 KB) | DOI: 10.11591/ijece.v8i2.pp1262-1272

Abstract

The paper presents an efficient speed control of brushless DC (BLDC) motor drive for photo-voltaic (PV) system fed system. A high-gain DC-DC converter is employed in the system to boost the PV system low output voltage to a level required for the drive system. High-gain DC-DC converter is operated in closed-loop mode to attain accurate and steady output. The converter (VSI) for BLDC is switched at fundamental frequency and thus reducing high frequency switching losses. Internal current control method is developed and employed for the speed control of PV fed BLDC motor. The appropriateness of the internal current controller for the speed control of PV fed BLDC motor is verified for increamental speed with fixed torque and decreamental speed with fixed torque operating conditions. The system is developed and results are developed using MATLAB/SIMULINK software
Utilizing ECG Waveform Features as New Biometric Authentication Method Ahmed Younes Shdefat; Moon-Il Joo; Sung-Hoon Choi; Hee-Cheol Kim
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (587.527 KB) | DOI: 10.11591/ijece.v8i2.pp658-665

Abstract

In this study, we are proposing a practical way for human identification based on a new biometric method. The new method is built on the use of the electrocardiogram (ECG) signal waveform features, which are produced from the process of acquiring electrical activities of the heart by using electrodes placed on the body. This process is launched over a period of time by using a recording device to read and store the ECG signal. On the contrary of other biometrics method like voice, fingerprint and iris scan, ECG signal cannot be copied or manipulated. The first operation for our system is to record a portion of 30 seconds out of whole ECG signal of a certain user in order to register it as user template in the system. Then the system will take 7 to 9 seconds in authenticating the template using template matching techniques. 44 subjects‟ raw ECG data were downloaded from Physionet website repository. We used a template matching technique for the authentication process and Linear SVM algorithm for the classification task. The accuracy rate was 97.2% for the authentication process and 98.6% for the classification task; with false acceptance rate 1.21%.
An Investigation towards Effectiveness in Image Enhancement Process in MPSoC Archana H. R.; Vasundara Patel K. S.
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (265.905 KB) | DOI: 10.11591/ijece.v8i2.pp963-970

Abstract

Image enhancement has a primitive role in the vision-based applications. It involves the processing of the input image by boosting its visualization for various applications. The primary objective is to filter the unwanted noises, clutters, sharpening or blur. The characteristics such as resolution and contrast are constructively altered to obtain an outcome of an enhanced image in the bio-medical field. The paper highlights the different techniques proposed for the digital enhancement of images. After surveying these methods that utilize Multiprocessor System-on-Chip (MPSoC), it is concluded that these methodologies have little accuracy and hence none of them are efficiently capable of enhancing the digital biomedical images.
Neural Network based p-q-r Theory for Harmonic Reduction and Neutral Current Mitigation S. Malathi; J. Jayachandran
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (30.384 KB) | DOI: 10.11591/ijece.v8i2.pp825-836

Abstract

The power quality compensator chosen in this paper is a DSTATCOM which integrates a three phase four leg Voltage Source Converter (VSC) with a DC capacitor. The major role of the DSTATCOM is to mitigate the components of harmonic/reactive current present in the line current thereby shapes the grid current to be sinusoidal and improves the power factor nearly unity under varying conditions. In addition DSATATCOM mitigates neutral current (Isn) and balances the load currents under unbalanced conditions in three phase four wire (3P4W) distribution system. The control strategy proposed for the DSTATCOM is a Neural Network (NN) based p-q-r theory with two Artificial Neural Network (ANN) controllers for a 3P4W distribution system. The reference signal for 3P3W Shunt Active Power Filter (SAPF) is calculated by implementing an ANN controller. The alleviation of Isn under unbalanced condition is achieved by another ANN controller which produces reference signal for the 1Φ APF. The performance of the proposed DSTATCOM is analysed for various conditions through simulations in MATLAB SIMULINK and the simulation results justify the effectiveness of the propounded NN based control algorithm for DSTATCOM.
Simulation and Modeling of Silicon Based Single Electron Transistor Malik Ashter Mehdy; Mariagrazia Graziano; Gianluca Piccinini
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5091.252 KB) | DOI: 10.11591/ijece.v8i2.pp900-907

Abstract

In this work, we simulated and modeled silicon quantum dot based single electron transistor (SET). We simulated the device using non-equilibrium Green’s function (NEGF) formalism in transport direction coupled with Schrodinger equation in transverse directions. The characteristics of SET such as Coulomb blockade and Coulomb diamonds were observed. We also present a new efficient model to calculate the current voltage (IV) characteristics of the SET. The IV characteristic achieved from the model are very similar to those from simulations both in shape and magnitude. The proposed model is capable of reproducing the Coulomb diamond diagram in good agreement with the simulations. The model, which is based on transmission spectrum, is simple, efficient and provides insights on the physics of the device. The transmission spectrum at equilibrium is achieved from simulations and given as input to the model. The model then calculates the evolved transmission spectra at non-equilibrium conditions and evaluates the current using Landauers formula.
Gravitational-Search Algorithm for Optimal Controllers Design of Doubly-fed Induction Generator Saher Albatran; Muwaffaq I. Alomoush; Ahmed M. Koran
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (792.893 KB) | DOI: 10.11591/ijece.v8i2.pp780-792

Abstract

Recently, the Gravitational-Search Algorithm (GSA) has been presented as a promising physics-inspired stochastic global optimization technique. It takes its derivation and features from laws of gravitation. This paper applies the GSA to design optimal controllers of a nonlinear system consisting of a doubly-fed induction generator (DFIG) driven by a wind turbine. Both the active and the reactive power are controlled and processed through a back-to-back converter. The active power control loop consists of two cascaded proportional integral (PI) controllers. Another PI controller is used to set the q-component of the rotor voltage by compensating the generated reactive power. The GSA is used to simultaneously tune the parameters of the three PI controllers. A time-weighted absolute error (ITAE) is used in the objective function to stabilize the system and increase its damping when subjected to different disturbances. Simulation results will demonstrate that the optimal GSA-based coordinated controllers can efficiently damp system oscillations under severe disturbances. Moreover, simulation results will show that the designed optimal controllers obtained using the GSA perform better than the optimal controllers obtained using two commonly used global optimization techniques, which are the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).
A Systematic Review of Existing Data Mining Approaches Envisioned for Knowledge Discovery from Multimedia Benaka Santosha S; Chitra Kiran N
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.369 KB) | DOI: 10.11591/ijece.v8i2.pp908-916

Abstract

The extensive use of multimedia technologies extended the applicability of information technology to a large extent which results enormous generation of complex multimedia contents over the internet. Therefore the number of multimedia contents available to the user is also exponentially increasing. In this digital era of the cloud-enabled Internet of Things (IoT), analysis of complex video and image data plays a crucial role.It aims to extract meaningful information as the distributed storages and processing elements within a bandwidth constraint network seek optimal solutions to increase the throughput along with an optimal trade-off between computational complexity and power consumption. However, due to complex characteristics of visual patterns and variations in video frames, it is not a trivial task to discover meaningful information and correlation. Hence, data mining has emerged as a field which has diverse aspects presently in extracting meaningful hidden patterns from the complex image and video data considering different pattern classification approach. The study mostly investigates the existing data-mining tools and their performance metric for the purpose of reviewing this research track.It also highlights the relationship between frequent patterns and discriminativefeatures associated with a video object. Finally, the study addresses the existing research issues to strengthen up the future direction of research towards video analytics and pattern recognition.
Internet of Things: Low Cost and Wearable SpO2 Device for Health Monitoring R. R. Adiputra; S. Hadiyoso; Y. Sun Hariyani
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (709.164 KB) | DOI: 10.11591/ijece.v8i2.pp939-945

Abstract

This paper discusses a device for measuring oxygen saturation (SpO2) and heart rate as parameters of the representations of heart conditions. SpO2 device that have been made has a small dimension, wearable and high mobility with battery as the main power source. The device connects to a node MCU as a data processor and an internet network gateway to support internet of things applications. Data sent to the Internet cloud can be accessed online and real time via website for further analysis. The error rate at heart rate measurement is ± 2.8 BPM and for oxygen saturation (SpO2) is ± 1.5%. Testing data transmission delay until it can be displayed on website is 3 second that depends on internet traffic conditions.
Novel Scheme for Minimal Iterative PSO Algorithm for Extending Network Lifetime of Wireless Sensor Network Hemavathi P; Nandakumar A. N.
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (283.567 KB) | DOI: 10.11591/ijece.v8i2.pp1084-1091

Abstract

Clustering is one of the operations in the wireless sensor network that offers both streamlined data routing services as well as energy efficiency. In this viewpoint, Particle Swarm Optimization (PSO) has already proved its effectiveness in enhancing clustering operation, energy efficiency, etc. However, PSO also suffers from a higher degree of iteration and computational complexity when it comes to solving complex problems, e.g., allocating transmittance energy to the cluster head in a dynamic network. Therefore, we present a novel, simple, and yet a cost-effective method that performs enhancement of the conventional PSO approach for minimizing the iterative steps and maximizing the probability of selecting a better clustered. A significant research contribution of the proposed system is its assurance towards minimizing the transmittance energy as well as receiving energy of a cluster head. The study outcome proved proposed a system to be better than conventional system in the form of energy efficiency.
Towards an accurate Ground-Level Ozone Prediction Eiman Tamah Alshammari
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (586.166 KB) | DOI: 10.11591/ijece.v8i2.pp1131-1139

Abstract

This paper motivation is to find the most accurate technique to predict the ground level ozone at Al Jahra station, Kuwait. The data on the meteorological variables (air temperature, relative humidity, solar radiation, direction and speed of wind) and concentration of seven pollutants of environment (SO2, NO2, NO, CO2, CO, NMHC, and CH4) were applied to forecast the ozone concentration in atmosphere. In this report, three methods (PLS regression, support vector machine (SVM), and multiple least-square regression) were used to predict ground-level ozone. We used Fifteen parameters to evaluate the performance of methods. Multiple least-square regression, partial least square regression (PLS regression), and SVM using linear and radial kernels were the best performers with MAE (mean absolute error) of 9.17x 10-03, 9.72 x 10-03, 9.64 x 10-03, and 9.12 x 10-03, respectively. SVM with polynomial kernel had MAE of 5.46 x 10-02. These results show that these methods could be used to predict ground-level ozone concentrations at Al Jahra station in Kuwait.

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