Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Filter Icon

Filters article

Years

FAQ Arrow
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

29,758 Article Results

Content an Insight to Security Paradigm for BigData on Cloud: Current Trend and Research

10.11591/ijece.v7i5.pp2873-2882
Chhaya S Dule , Girijamma H. A.
The sucesssive growth of collabrative applications prodcuing Bigdata on timeline leads new opprutinity to setup commodities on cloud infrastructure. Mnay organizations will have demand of an efficient data storage mechanism and also the efficient data analysis. The Big Data (BD) also faces some of the security issues for the important data or information which is shared or transferred over the cloud. These issues include the tampering, losing control over the data, etc. This survey work offers some of the interesting, important aspects of big data including the high security and privacy issue. In this, the survey of existing research works for the preservation of privacy and security mechanism and also the existing tools for it are stated. The discussions for upcoming tools which are needed to be focused on performance improvement are discussed. With the survey analysis, a research gap is illustrated, and a future research idea is presented
Volume: 7
Issue: 5
Page: 2873-2882
Publish at: 2017-10-01

Current Controller Based Power Management Strategy for Interfacing DG Units to Micro Grid

10.11591/ijece.v7i5.pp2300-2308
N. Chaitanya , P. Sujatha , K. Chandra Sekhar
This paper proposes a power management strategy of parallel inveters based system, to enhance the power generation capacity of the existing system with distributed energy sources one has to choose DG source based inverter connected in parallel with the existing system.Two DG sources PV, Fuel cells feeds the DC voltage to two parallel inverters connected to the grid. Fixed band hysteresis current control with Instantaneous p-q power theory is adopted to create an artificial environment. Two parallel inverters are able to deliver the harvested power from PV, FC to grid and able to balance the load Without communication between parallel inverters this controller having the capability of load following, the harmonic components of currents at output of inverter are also very low; this will automatically reduces the circulating currents between parallel inverters. Simulation studies are carried out to investigate the results of PV, FC systems connected to the utility grid.
Volume: 7
Issue: 5
Page: 2300-2308
Publish at: 2017-10-01

Inter-cell Interference Management Technique for Multi-Cell LTE-A Network

10.11591/ijece.v7i5.pp2696-2705
Iskandar Iskandar , I. Setyawan , H. Nuraini
In modern cellular system such as LTE Advanced (LTE-A), frequency reuse scheme is targeted to be applied to fulfill the requirement of high capacity broadband access and high spectrum efficiency. But this kind of frequency planning may lead to the worse inter-cell interference (ICI) level experienced especially by a user located at the cell edge. Soft Frequency Reuse (SFR) is considered as an effective way to mitigate inter-cell interference and maintain capacity. We propose a power division SFR, known as multi level SFR technique to minimize ICI in a designed LTE-A network for sub-urban environment. Service area of LTE-A network was first developed to deploy particular number of eNB by using LTE network planning tools in the frequency of 1800 MHz with the use of SISO (Single Input Single Output) antennas. Coverage dimensioning and propagation consideration determine LTE-A parameters which were used in the simulation. Monte carlo simulation is executed to examine the performance of SFR for LTE-A downlink transmission to address different power ratio and traffic loads problem. Both performance of cell edge users and overall cell performance are evaluated in terms of CINR, BLER, and throughput. Performance with SFR is also compared with the classical frequency reuse one and three.
Volume: 7
Issue: 5
Page: 2696-2705
Publish at: 2017-10-01

Converting UML Class Diagrams into Temporal Object Relational DataBase

10.11591/ijece.v7i5.pp2823-2832
Ain El Hayat Soumiya , Bahaj Mohamed
Number of active researchers and experts, are engaged to develop and implement new mechanism and features in time varying database management system (TVDBMS), to respond to the recommendation of modern business environment..Time-varying data management has been much taken into consideration with either the attribute or tuple time stamping schema. Our main approach here is to try to offer a better solution to all mentioned limitations of existing works in order to provide the non-procedural data definitions, queries of temporal data as complete as possible technical conversion that allow to easily realize and share all conceptual details of the UML class specifications, from conception and design point of view. This paper contributes to represent a logical design schema by UML class diagrams, which are handled by stereotypes to express a temporal object relational database with attribute timestamping.
Volume: 7
Issue: 5
Page: 2823-2832
Publish at: 2017-10-01

Parameter Extraction of PV Module using NLS Algorithm with Experimental Validation

10.11591/ijece.v7i5.pp2392-2400
Alivarani Mohapatra , Byamakesh Nayak , K.B. Mohanty
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.
Volume: 7
Issue: 5
Page: 2392-2400
Publish at: 2017-10-01

A Hybrid Digital Watermarking Approach Using Wavelets and LSB

10.11591/ijece.v7i5.pp2483-2495
V. Ashok Kumar , C. Dharmaraj , Ch. Srinivasa Rao
The present paper proposed a novel approach called Wavelet based Least Significant Bit Watermarking (WLSBWM) for high authentication, security and copyright protection. Alphabet Pattern (AP) approach is used to generate shuffled image in the first stage and Pell’s Cat Map (PCM) is used for providing more security and strong protection from attacks. PCM applied on each 5×5 sub images. A wavelet concept is used to reduce the dimensionality of the image until it equals to the size of the watermark image. Discrete Cosign Transform is applied in the first stage; later N level Discrete Wavelet Transform (DWT) is applied for reducing up to the size of the watermark image. The water mark image is inserted in LHn Sub band of the wavelet image using LSB concept. Simulation results show that the proposed technique produces better PSNR and similarity measure. The experimental results indicate that the present approach is more reliable and secure efficient.The robustness of the proposed scheme is evaluated against various image-processing attacks.
Volume: 7
Issue: 5
Page: 2483-2495
Publish at: 2017-10-01

LusRegTes: A Regression Testing Tool for Lustre Programs

10.11591/ijece.v7i5.pp2635-2644
Nguyen Thanh Binh , Trinh Cong Duy , Ioannis Parissis
Lustre is a synchronous data-flow declarative language widely used for safety-critical applications (avionics, energy, transport...). In such applications, the testing activity for detecting errors of the system plays a crucial role. During the development and maintenance processes, Lustre programs are often evolving, so regression testing should be performed to detect bugs. In this paper, we present a tool for automatic regression testing of Lustre programs. We have defined an approach to generate test cases in regression testing of Lustre programs.  In this approach, a Lustre program is represented by an operator network, then the set of paths is identified and the path activation conditions are symbolically computed for each version. Regression test cases are generated by comparing paths between versions. The approach was implemented in a tool, called LusRegTes, in order to automate the test process for Lustre programs.
Volume: 7
Issue: 5
Page: 2635-2644
Publish at: 2017-10-01

The Decision-making Model for the Stock Market under Uncertainty

10.11591/ijece.v7i5.pp2782-2790
Siham Abdulmalik Mohammed Almasani , Valery Ivanovich Finaev , Wadeea Ahmed Abdo Qaid , Alexander Vladimirovich Tychinsky
The main purpose of this research is developing methods and models of decision-making to assess the stock market state, and predict the possible changes in the RTS index value. This article shows that the analytical models for assessing the stock market state do not give reliable results. The absence of the reliable estimates associated with the high degree of uncertainty, random, nonlinear and non-stationary process with a significant degree of aftereffect. In this paper, to formalize the securities market parameters it’s proposed the fuzzy sets method. To assess the stock market current state and make decisions the fuzzy situational analysis model (situational model) is applied. The analytical prediction results of the stock market and graph of the RTS index expected return changes in 2014-2016 are showed. The model of calculating the fuzzy inference rules truth degree to predict the RTS index is developed. The market parameters linguistic definition is given and the expert’s rules construction to predict the RTS index growth is shown. The program in Matlab environment is designed to perform research. The study result showed that the model allows for the RTS index prediction in the condition of incomplete initial data with a confidence level about 90%.
Volume: 7
Issue: 5
Page: 2782-2790
Publish at: 2017-10-01

High-Performance Generator for a New Generation of Aircrafts

10.11591/ijece.v7i5.pp2338-2348
Flur Ismagilov , Irek Khayrullin , Vyacheslav Vavilov , Ruslan Karimov , Anton Gorbunov
The article describes multidisciplinary design process of high-performance electric generator for advanced aircrafts by analytical methods and computer modeling techniques (electromagnetic, thermal and mechanical calculations). New technical solutions used in its development are described. The main ideas are revealed of the method of EG voltage stabilization we used. To improve the heat dissipation efficiency, we have developed a new cooling system, and provide its study and description in this paper. The advantages of this cooling system include the fact that EG is made with dry, uncooled rotor. This allowed eliminating additional pumps, and significantly reducing the size of CSD. According to the results of our study, we created an experimental full capacity layout, and its studies are also provided in this paper.
Volume: 7
Issue: 5
Page: 2338-2348
Publish at: 2017-10-01

Intensity preserving cast removal in color images using particle swarm optimization

10.11591/ijece.v7i5.pp2581-2595
Om Prakash Verma , Nitin Sharma
In this paper, we present an optimal image enhancement technique for color cast images by preserving their intensity. There are methods which improves the appearance of the affected images under different cast like red, green, blue etc but up to some extent. The proposed color cast method is corrected by using transformation function based on gamma values. These optimal values of gamma are obtained through particle swarm optimization (PSO). This technique preserves the image intensity and maintains the originality of color by satisfying the modified gray world assumptions. For the performance analysis, the image distance metric criteria of CIELAB color space is used. The effectiveness of the proposed approach is illustrated by testing the proposed method on color cast images. It has been found that distance between the reference image and the corrected proposed image is negligible. The calculated value of image distance depicts that the enhanced image results of the proposed algorithm are closer to the reference images in comparison with other existing methods.
Volume: 7
Issue: 5
Page: 2581-2595
Publish at: 2017-10-01

Hybrid Spectrum Sensing Method for Cognitive Radio

10.11591/ijece.v7i5.pp2683-2695
A. S. Khobragade , R.D. Raut
With exponential rise in the internet applications and wireless communications, higher and efficient data transfer rates are required. Hence proper and effective spectrum is the need of the hour, As spectrum demand increases there are limited number of bands available to send and receive the data. Optimizing the use of these bands efficiently is one of the tedious tasks. Various techniques are used to send the data at same time, but for that we have to know which bands are free before sending the data. For this purpose various spectrum sensing approaches came with variety of solutions. In this paper the sensing problem is tackled with the use of hybrid spectrum sensing method, This new networking paradox uses the Centralized concept of spectrum sensing and creates one of the most trusted spectrums sensing mechanism. This proposed technique is simulated using MATLAB software.This paper also provides comparative study of various spectrum sensing methodologies
Volume: 7
Issue: 5
Page: 2683-2695
Publish at: 2017-10-01

Cursive Handwriting Segmentation using Ideal Distance Approach

10.11591/ijece.v7i5.pp2863-2872
Fitrianingsih Fitrianingsih , Sarifuddin Madenda , Ernastuti Ernastuti , Suryarini Widodo , Rodiah Rodiah
Offline cursive handwriting becomes a major challenge due to the huge amount of handwriting varieties such as slant handwriting, space between words, the size and direction of the letter, the style of writing the letter and handwriting with contour similarity on some letters. There are some steps for recursive handwriting recognition. The steps are preprocessing, morphology, segmentation, features of letter extraction and recognition. Segmentation is a crucial process in handwriting recognition since the success of segmentation step will determine the success level of recognition. This paper proposes a segmentation algorithm that segment recursive handwriting into letters. These letters will form words using a method that determine the intersection cutting point of image recursive handwriting with an ideal image distance. The ideal distance of recursive handwriting image is an ideal distance segmentation point in order to avoid the cutting of other letter’s section. The width and height of images are used to determine the accurate segmentation point. There were 999 recursive handwriting input images taken from 25 researchers used for this study. The images used are the images obtained from preprocessing step. Those are the images with slope correction. This study used Support Vector Machine (SVM) to recognize recursive handwriting. The experiments show the proposed segmentation algorithm able to segment the image precisely and have 97% success recognizing the recursive handwriting.
Volume: 7
Issue: 5
Page: 2863-2872
Publish at: 2017-10-01

Feasibility of Substitution of the Conventional Street Lighting Installation by the Photovoltaic Case Study on a Municipality in Agadir in Morocco

10.11591/ijece.v7i5.pp2287-2299
Fatima Outferdine , Lahoussine Bouhouch , Mustapha Kourchi , Mohamed Ajaamoum , Ali Moudden
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.
Volume: 7
Issue: 5
Page: 2287-2299
Publish at: 2017-10-01

PWM Dimming for High Brightness LED Based Automotive Lighting Applications

10.11591/ijece.v7i5.pp2434-2440
Muhammad Wasif Umar , Norzaihar Yahaya , Zuhairi Baharuddin
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.
Volume: 7
Issue: 5
Page: 2434-2440
Publish at: 2017-10-01

Indian Classical Dance Mudra Classification Using HOG Features and SVM Classifier

10.11591/ijece.v7i5.pp2537-2546
K.V.V. Kumar , P.V.V. Kishore
Digital understanding of Indian classical dance is least studied work, though it has been a part of Indian Culture from around 200BC. This work explores the possibilities of recognizing classical dance mudras in various dance forms in India. The images of hand mudras of various classical dances are collected form the internet and a database is created for this job.  Histogram of oriented (HOG) features of hand mudras input the classifier. Support vector machine (SVM) classifies the HOG features into mudras as text messages. The mudra recognition frequency (MRF) is calculated for each mudra using graphical user interface (GUI) developed from the model. Popular feature vectors such as SIFT, SURF, LBP and HAAR are tested against HOG for precision and swiftness. This work helps new learners and dance enthusiastic people to learn and understand dance forms and related information on their mobile devices.
Volume: 7
Issue: 5
Page: 2537-2546
Publish at: 2017-10-01
Show 1510 of 1984

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration