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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 128 Documents
Search results for , issue "Vol 9, No 5: October 2019" : 128 Documents clear
Optimization of electronic sensors for detecting pollution due to organic gases using PARAFAC Shri Om Mishra; S Hasan Saeed
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (631.294 KB) | DOI: 10.11591/ijece.v9i5.pp3441-3449

Abstract

The principle point of this examination work is to recognize the butane, Acetone, Propane, ethane, LPG and other natural gases from the strong waste and do condition checking. Here the arrangement of sensors used to identify the poison gases from strong waste. Here our point is to build up a sensor cluster framework which will identify most extreme contamination gases and which is very responsive, minimal effort and low power devouring. We have assumed three sensors in position of six sensors and given the outcomes as fluctuation, score plot and stacking plot. Here we utilize the parallel factor analysis (PARAFAC) for identification of gases and contrast it and the key part investigation Principal component analysis (PCA). We confiscated three sensors in position of six sensors and given the outcomes as variance, score plot and loading plot. Electronic noses have given a plenty of advantages in different logical research fields. Here our point is to build up a sensor exhibit framework which will distinguish most extreme contamination gases and which is profoundly responsive, exact and minimal effort and low power expending. Here we utilize the parallel factor investigation method (PARAFAC) for discovery of gases and contrast it and the primary segment examination (PCA).
Estimation of regression-based model with bulk noisy data Chanintorn Jittawiriyanukoon
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (713.95 KB) | DOI: 10.11591/ijece.v9i5.pp3649-3656

Abstract

The bulk noise has been provoking a contributed data due to a communication network with a tremendously low signal to noise ratio. An appreciated method for revising massive noise of individuals through information theory is widely discussed. One of the practical applications of this approach for bulk noise estimation is analyzed using intelligent automation and machine learning tools, dealing the case of bulk noise existence or nonexistence. A regression-based model is employed for the investigation and experiment. Estimation for the practical case with bulk noisy datasets is proposed. The proposed method applies slice-and-dice technique to partition a body of datasets down into slighter portions so that it can be carried out. The average error, correlation, absolute error and mean square error are computed to validate the estimation. Results from massive online analysis will be verified with data collected in the following period. In many cases, the prediction with bulk noisy data through MOA simulation reveals Random Imputation minimizes the average error.
An adaptive wavelet transformation filtering algorithm for improving road anomaly detection and characterization in vehicular technology Habeeb Bello-Salau; A. J. Onumanyi; B. O. Sadiq; H. Ohize; A. T. Salawudeen; A. M. Aibinu
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (432.952 KB) | DOI: 10.11591/ijece.v9i5.pp3664-3670

Abstract

Accelerometers are widely used in modern vehicular technologies to automatically detect and characterize road anomalies such as potholes and bumps. However, measurements from an accelerometer are usually plagued by high noise levels, which typically increase the false alarm and misdetection rates of an anomaly detection system. To address this problem, we have developed in this paper an adaptive threshold estimation technique to filter accelerometer measurements effectively to improve road anomaly detection and characterization in vehicular technologies. Our algorithm decomposes the output signal of an accelerometer into multiple scales using wavelet transformation (WT). Then, it correlates the wavelet coefficients across adjacent scales and classifies them using a newly proposed adaptive threshold technique. Furthermore, our algorithm uses a spatial filter to smoothen further the correlated coefficients before using these coefficients to detect road anomalies. Our algorithm then characterizes the detected road anomalies using two unique features obtained from the filtered wavelet coefficients to differentiate potholes from bumps. The findings from several comparative tests suggest that our algorithm successfully detects and characterizes road anomalies with high levels of accuracy, precision and low false alarm rates as compared to other known methods.
Optimizing requirement analysis by the use of meta-heuristic in search based software engineering Rajesh Kumar; Rakesh Kumar
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (756.035 KB) | DOI: 10.11591/ijece.v9i5.pp4336-4343

Abstract

Requirements analysis is the first phase of software development process and it is one of the main concerns of software engineers. The selection of requirements is a complex problem caused by the heterogeneity of the users and their varied interests and demands. In this paper, it is justified that their is a strong need of optimization in requirement analysis. The paper argues that requirement selection can be viewed as an application area of Search-Based Software Engineering(SBSE). The aim is to justify the claim that requirement engineering can be re-formulated as search problem to which meta-heuristic technique can be applied.
A hyprid technique for human footprint recognition Yahya Ismail Ibrahim; Israa Mohammed Alhamdani
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (596.127 KB) | DOI: 10.11591/ijece.v9i5.pp4060-4068

Abstract

Biometrics has concerned a great care recently due to its important in the life that starts from civil applications to security and recently terrorism. A Footprint recognition is one of the personal identifications based on biometric measurements.  The aim of this research is to design a proper and reliable biometric system for human footprint recognition named (FRBS) that stands for Footprint Recognition Biometric System. In addition, to construct a human footprint database which it is very helpful for various use in scientific application e.g. for authentication. There exist many biometrics databases for other identity but very rare for footprint. As well as the existing one are very limited. This paper presents a robust hyprid techniques which merges between Image Processing with Artificial Intelligent technique via Ant Colony Optimization (ACO) to recognize human footprint.  (ACO) plays the essential role that rise the performance and the quality of the results in the biometric system via feature selection. The set of the selected features was treated as exploratory information, and selects the optimum feature set in standings of feature set size. Life RGB footprint images from nine persons with ten images per person constructed from life visual dataset. At first, the visual dataset was pre-processed operations. Each resultant image detects footprint that is cropped to portions represented by three blocks. The first block is for fingers, the second block refers to the center of the foot and the last one determines the heel. Then features were extracted from each image and stored in Excel file to be entered to Ant Colony Optimization Algorithm. The experimental outcomes of the system show that the proposed algorithm evaluates optimal results with smaller feature set comparing with other algorithms. Experimental outcomes show that our algorithm obtains an efficient and accurate result about 100% accuracy in comparison with other researches on the same field.
A Shortest Data Window Algorithm for Detecting the Power Factor in presence of non-sinusoidal load current Safaa S. Omran; Ali Sh. Al-Khalid; Amer Atta Yaseen
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (472.014 KB) | DOI: 10.11591/ijece.v9i5.pp3956-3966

Abstract

During recent years, nonlinear power electronic equipments introduce harmonic pollution on electric power systems. It makes the traditional power factor meter can not act accurately when it monitors unbalanced and harmonic loads. In this paper, a new algorithm for detecting the power factor in presence of non-sinusoidal load current is proposed. The proposed algorithm detects the true power factor exactly. By uses only two successive sampled data points of the voltage and the current for each displacement power factor value calculation and two sampled data points for each distortion power factor value calculation, the total/true power factor becomes easy to measure using these values directly. The proposed detector implemented using microcontroller as a main part and has been tested for single phase power system. The test results show that it can measure the true power factor of the loads quickly and accurately.
Implementation of AES using biometric Srividya R.; Ramesh B.
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (633.057 KB) | DOI: 10.11591/ijece.v9i5.pp4266-4276

Abstract

Mobile Adhoc network is the most advanced emerging technology in the field of wireless communication. MANETs mainly have the capacity of self-forming, self-healing, enabling peer to peer communication between the nodes, without relying on any centralized network architecture. MANETs are made applicable mainly to military applications, rescue operations and home networking. Practically, MANET could be attacked by several ways using multiple methods. Research on MANET emphasizes on data security issues, as the Adhoc network does not befit security mechanism associated with static networks. This paper focuses mainly on data security techniques incorporated in MANET. Also this paper proposes an implementation of Advanced Encryption Standard using biometric key for MANETs. AES implementation includes, the design of most robust Substitution-Box implementation which defines a nonlinear behavior and mitigates malicious attacks, with an extended security definition. The key for AES is generated using most reliable, robust and precise biometric processing. In this paper, the input message is encrypted by AES powered by secured nonlinear S-box using finger print biometric feature and is decrypted using the reverse process.
Short-term optimal hydro-thermal scheduling using clustered adaptive teaching learning based optimization Surender Reddy Salkuti
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.537 KB) | DOI: 10.11591/ijece.v9i5.pp3359-3365

Abstract

In this paper, Clustered Adaptive Teaching Learning Based Optimization (CATLBO) algorithm is proposed for determining the optimal hourly schedule of power generation in a hydro-thermal power system. In the proposed approach, a multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, net head and power generation is considered. Constraints such as power balance, water balance, reservoir volume limits and operation limits of hydro and thermal plants are considered. The feasibility and effectiveness of the proposed algorithm is demonstrated through a test system, and the results are compared with existing conventional and evolutionary algorithms. Simulation results reveals that the proposed CATLBO algorithm appears to be the best in terms of convergence speed and optimal cost compared with other techniques.
Outage probability analysis of EH relay-assisted non-orthogonal multiple access (NOMA) systems over Block Rayleigh Fading Channel Tan N. Nguyen; Minh Tran; Van-Duc Phan; Hoang-Nam Nguyen; Thanh-Long Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (648.472 KB) | DOI: 10.11591/ijece.v9i5.pp3607-3614

Abstract

Non-orthogonal multiple access (NOMA) has been identified as a promising multiple access technique for the fifth generation (5G) mobile networks due to its superior spectral efficiency. In this paper, we propose and investigate a Non-Orthogonal Multiple Access (NOMA) of energy harvesting (EH) relay assisted system over Block Rayleigh Fading Channel. In order to evaluate the performance of the proposed system, the integral expression of the outage probability is analyzed and derived. Numerical results confirm that our derived analytical results match well with the Monte Carlo simulations in connection with all possible system parameter.
Efficient error correcting scheme for chaos shift keying signals Hikmat N. Abdullah; Thamir R. Saeed; Asaad H. Sahar
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1037.079 KB) | DOI: 10.11591/ijece.v9i5.pp3550-3557

Abstract

An effective error-correction scheme based on normalized correlation for a non coherent chaos communication system with no redundancy bits is proposed in this paper. A modified logistic map is used in the proposed scheme for generating two sequences, one for every data bit value, in a manner that the initial value of the next chaotic sequence is set by the second value of the present chaotic sequence of the similar symbol. This arrangement, thus, has the creation of successive chaotic sequences with identical chaotic dynamics for error correction purpose. The detection symbol is performed prior to correction, on the basis of the suboptimal receiver which anchors on the computation of the shortest distance existing between the received sequence and the modified logistic map’s chaotic trajectory. The results of the simulation reveal noticeable Eb/No improvement by the proposed scheme over the prior to the error- correcting scheme with the improvement increasing whenever there is increase in the number of sequence N. Prior to the error-correcting scheme when N=8, a gain of 1.3 dB is accomplished in Eb/No at 10-3 bit error probability. On the basis of normalized correlation, the most efficient point in our proposed error correction scheme is the absence of any redundant bits needed with minimum delay procedure, in contrast to earlier method that was based on suboptimal method detection and correction. Such performance would render the scheme good candidate for applications requiring high rates of data transmission.

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