International Journal of Electrical and Computer 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.
Articles
117 Documents
Search results for
, issue
"Vol 10, No 2: April 2020"
:
117 Documents
clear
Area efficient parallel lfsr for cyclic redundancy check
Rita Mahajan;
Komal Devi;
Deepak Bagai
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (436.292 KB)
|
DOI: 10.11591/ijece.v10i2.pp1755-1763
Cyclic Redundancy Check (CRC), code for error detection finds many applications in the field of digital communication, data storage, control system and data compression. CRC encoding operation is carried out by using a Linear Feedback Shift Register (LFSR). Serial implementation of CRC requires more clock cycles which is equal to data message length plus generator polynomial degree but in parallel implementation of CRC one clock cycle is required if a whole data message is applied at a time. In previous work related to parallel LFSR, hardware complexity of the architecture reduced using a technique named state space transformation. This paper presents detailed explaination of search algorithm implementation and technique to find number of XOR gates required for different CRC algorithms. This paper presents a searching algorithm and new technique to find the number of XOR gates required for different CRC algorithms. The comparison between proposed and previous architectures shows that the number of XOR gates are reduced for CRC algorithms which improve the hardware efficiency. Searching algorithm and all the matrix computations have been performed using MATLAB simulations.
Advancement in infotainment system in automotive sector with vehicular cloud network and current state of art
Reshma S.;
Chetanaprakash Chetanaprakash
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (598.519 KB)
|
DOI: 10.11591/ijece.v10i2.pp2077-2087
The automotive industry has been incorporating various technological advancement on top-end versions of the vehicle order to improvise the degree of comfortability as well as enhancing the safer driving system. Infotainment system is one such pivotal system which not only makes the vehicle smart but also offers abundance of information as well as entertainment to the driver and passenger. The capability to offer extensive relay of service through infotainment system is highly dependent on vehicular adhoc network as well as back end support of cloud environment. However, it is know that such legacy system of vehicular adhoc network is also characterized by various problems associated with channel capacity, latency, heterogeneous network processing, and many more. Therefore, this paper offers a comprehensive insight to the research work being carried out towards leveraging the infotainment system in order to obtain the true picture of strength, limitation, and open end problems associated with infotainment system.
Improved predictive current model control based on adaptive PR controller for standalone system based DG set
Halima Ikaouassen;
Abderraouf Raddaoui;
Miloud Rezkallah;
Hussein Ibrahim
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1146.045 KB)
|
DOI: 10.11591/ijece.v10i2.pp1905-1914
This paper investigates an improved current predictive model control (PCMC) strategy with a prediction horizon of one sampling time for voltage regulation in standalone system based on diesel engine driven fixed speed of a synchronous generator. An adaptive PR controller with anti-windup scheme is employed to achieve high performance regulation without saturation issues. In addition, new method to obtain the optimal parameters of the adaptive PR controller to achieve high performance during the transition and in steady state is provided. To balance the power at the point of common coupling (PCC) as well as to feed a clean power to the connected loads, a three-phase voltage source inverter (VSI) with LRC filter is controlled using the developed improved PCMC strategy, where the output filter current is controlled using the predicting of the system behaviour model in the future step, at each sampling prediction time. The performances of the proposed configuration and the improved control strategy are verified using Matlab/Simulink interface.
Design and simulation of an analog beamforming phased array antenna
Mohamed Elhefnawy
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1002.73 KB)
|
DOI: 10.11591/ijece.v10i2.pp1398-1405
In this paper, a phased array antenna is designed and simulated. The antenna array consists of four circularly polarized slotted waveguide elements. The antenna array is simulated using CST MWS. The simulation results for the proposed antenna array at different values of progressive phase shift demonstrate that the S‒parameters for all four ports are less than ‒10 dB over at least 2% bandwidth, the simulated maximum gain is 13.95 dB, the simulated beamwidth can be 19˚ or narrower based on the value of the progressive phase shift. , the range of frequencies over which the simulated Axial Ratio (AR) is below 3 dB is not fixed and varied according to the selected progressive phase shift. The proposed four-element RF front-end is simulated using Advanced Design System (ADS) at operating frequency of 9.6 GHz. The obtained simulation results by ADS indicate the feasibility of implementing the proposed RF-front end for feeding the antenna array to realize analog beamforming.
Study and analysis of mobility, security, and caching issues in CCN
Rao Naveed Bin Rais;
Osman Khalid
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (957.732 KB)
|
DOI: 10.11591/ijece.v10i2.pp1438-1453
Existing architecture of Internet is IP-centric, having capability to cope with the needs of the Internet users. Due to the recent advancements and emerging technologies, a need to have ubiquitous connectivity has become the primary focus. Increasing demands for location-independent content raised the requirement of a new architecture and hence it became a research challenge. Content Centric Networking (CCN) paradigm emerges as an alternative to IP-centric model and is based on name-based forwarding and in-network data caching. It is likely to address certain challenges that have not been solved by IP-based protocols in wireless networks. Three important factors that require significant research related to CCN are mobility, security, and caching. While a number of studies have been conducted on CCN and its proposed technologies, none of the studies target all three significant research directions in a single article, to the best of our knowledge. This paper is an attempt to discuss the three factors together within context of each other. In this paper, we discuss and analyze basics of CCN principles with distributed properties of caching, mobility, and secure access control. Different comparisons are made to examine the strengths and weaknesses of each aforementioned aspect in detail. The final discussion aims to identify the open research challenges and some future trends for CCN deployment on a large scale.
Efficient power allocation method for non orthogonal multiple access 5G systems
Maan A. S Al-Adwany
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (740.817 KB)
|
DOI: 10.11591/ijece.v10i2.pp2139-2150
One of the hot research topics for the upcoming 5G (fifth-generation) wireless communication networks is the non orthogonal multiple access (NOMA) systems, where it have attracted both industrial and academic fields to improve the existing spectral efficiency. In fact, the multiuser detection process for NOMA systems is largely affected by the power distribution of the received signals. In this paper, a new method has been proposed to control the transmit power among active users in one of the promising NOMA systems; the interleave division multiple access (IDMA) which has been adopted here for consideration. Unlike conventional methods, where tedious mathematical computations are required; a simple and direct method has been derived. The proposed method has been applied to IDMA system with different FEC codes. The obtained results show that the proposed method outperforms the conventional one as compared to optimal results.
Online signature verification using hybrid wavelet transform
Manoj Chavan;
Ravish R. Singh;
Vinayak Bharadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (601.638 KB)
|
DOI: 10.11591/ijece.v10i2.pp1823-1832
Online signature verification is a prominent behavioral biometric trait. It offers many dynamic features along with static two dimensional signature image. In this paper, the Hybrid Wavelet Transform (HWT) was generated using Kronecker product of two orthogonal transform such as DCT, DHT, Haar, Hadamard and Kekre. HWT has the ability to analyze the signal at global as well as local level like wavelet transform. HWT-1 and -2 was applied on the first 128 samples of the pressure parameter and first 16 samples of the output were used as feature vector for signature verification. This feature vector is given to Left to Right HMM classifier to identify the genuine and forged signature. For HWT-1, DCT HAAR offers best FAR and FRR. . For HWT-2, KEKRE 128 offers best FAR and FRR. HWT-1 offers better performance than HWT- 2 in terms of FAR and FRR. As the number of states increase, the performance of the system improves. For HWT - 1, KEKRE 128 offers best performance at 275 symbols whereas for HWT - 2, best performance is at 475 symbols by KEKRE 128.
Novel modelling of clustering for enhanced classification performance on gene expression data
Sudha V.;
Girijamma H. A.
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (534.264 KB)
|
DOI: 10.11591/ijece.v10i2.pp2060-2068
Gene expression data is popularized for its capability to disclose various disease conditions. However, the conventional procedure to extract gene expression data itself incorporates various artifacts that offer challenges in diagnosis a complex disease indication and classification like cancer. Review of existing research approaches indicates that classification approaches are few to proven to be standard with respect to higher accuracy and applicable to gene expression data apart from unaddresed problems of computational complexity. Therefore, the proposed manuscript introduces a novel and simplified model capable using Graph Fourier Transform, Eigen Value and vector for offering better classification performance considering case study of microarray database, which is one typical example of gene expression data. The study outcome shows that proposed system offers comparatively better accuracy and reduced computational complexity with the existing clustering approaches.
Power consumption prediction in cloud data center using machine learning
Deepika T.;
Prakash P.
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (640.138 KB)
|
DOI: 10.11591/ijece.v10i2.pp1524-1532
The flourishing development of the cloud computing paradigm provides several services in the industrial business world. Power consumption by cloud data centers is one of the crucial issues for service providers in the domain of cloud computing. Pursuant to the rapid technology enhancements in cloud environments and data centers augmentations, power utilization in data centers is expected to grow unabated. A diverse set of numerous connected devices, engaged with the ubiquitous cloud, results in unprecedented power utilization by the data centers, accompanied by increased carbon footprints. Nearly a million physical machines (PM) are running all over the data centers, along with (5 – 6) million virtual machines (VM). In the next five years, the power needs of this domain are expected to spiral up to 5% of global power production. The virtual machine power consumption reduction impacts the diminishing of the PM’s power, however further changing in power consumption of data center year by year, to aid the cloud vendors using prediction methods. The sudden fluctuation in power utilization will cause power outage in the cloud data centers. This paper aims to forecast the VM power consumption with the help of regressive predictive analysis, one of the Machine Learning (ML) techniques. The potency of this approach to make better predictions of future value, using Multi-layer Perceptron (MLP) regressor which provides 91% of accuracy during the prediction process.
Available techniques in hadoop small file issue
M. B. Masadeh;
M. S. Azmi;
S. S. S. Ahmad
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (276.972 KB)
|
DOI: 10.11591/ijece.v10i2.pp2097-2101
Hadoop is an optimal solution for big data processing and storing since being released in the late of 2006, hadoop data processing stands on master-slaves manner [1] that’s splits the large file job into several small files in order to process them separately, this technique was adopted instead of pushing one large file into a costly super machine to insights some useful information. Hadoop runs very good with large file of big data, but when it comes to big data in small files it could facing some problems in performance, processing slow down, data access delay, high latency and up to a completely cluster shutting down [2]. In this paper we will high light on one of hadoop’s limitations, that’s affects the data processing performance, one of these limits called “big data in small files” accrued when a massive number of small files pushed into a hadoop cluster which will rides the cluster to shut down totally. This paper also high light on some native and proposed solutions for big data in small files, how do they work to reduce the negative effects on hadoop cluster, and add extra performance on storing and accessing mechanism.