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Developed Z-Source H-Bridge Multilevel Inverter with Reduced Components for Speed Control of Induction Motor

10.11591/ijra.v7i3.pp205-214
C. L.Kuppuswamy , T. A. Raghavendiran
This paper introduces a new developed H-bridge based cascaded multilevel inverter with reduced components. This topology has a low complexity thereby reducing the overall cost of an inverter. The proposed circuit is connected with a PI controller and switches are controlled by pulse width modulation technique to control the speed of an induction motor. The simulation was carried out using Matlab / Simulink. The simulation of the same was made and performance of various PWM techniques such as Phase disposition (PD), Phase opposite disposition (POD) and phase shifted (PS) and there results were compared on different quantitative measures such as Voltage, current stator Total harmonic Distortion, Voltage stress and rise time. It was observed that that the proposed power circuit with Phase disposition pulse width modulation (PDPWM) that offers reduced total harmonic Detection in terms of voltage, current and phase was found to be very less when compared to other Pulse width modulation techniques. The simulation results will have a fast and quick rise time thereby making this inverter a choice for speed control of induction motor.
Volume: 7
Issue: 3
Page: 205-214
Publish at: 2018-09-01

The Factors Affecting on Managing Sensitive Data in Cloud Computing

10.11591/ijeecs.v11.i3.pp1168-1175
Haifaa Jassim Muhasin , Rodziah Atan , Marzanah A. Jabar , Salfarina Abdullah
Cloud computing represents the most important shift in computing and information technology (IT). However, security and privacy remain the main obstacles to its widespread adoption. In this research we will review the security and privacy challenges that affect critical data in cloud computing and identify solutions that are used to address these challenges. Some questions that need answers are: (a) User access management, (b) Protect privacy of sensitive data, (c) Identity anonymity to protect the Identity of user and data file. To answer these questions, a systematic literature review was conducted and structured interview with several security experts working on cloud computing security to investigate the main objectives of proposed framework, a pilot study by using a structured questionnaire was conducted. Framework using multilevel to enhance management information system on sensitive data in cloud environment.
Volume: 11
Issue: 3
Page: 1168-1175
Publish at: 2018-09-01

Key Escrow with Elliptic Curve Cryptography – Conceptual Framework for Distributed Mobile Networks

10.11591/ijeecs.v11.i3.pp1060-1067
B. Sugumar , M. Ramakrishnan
In the large scale distributive environment involving mobile network, metadata server and storage applications, the data access and the security measures are of paramount importance. In parallel application processing, data is distributed across multiple servers and storage location. Ensuring confidentiality and availability of the data to the authorised users at the appropriate time involves high level of encryption algorithms, key management schemes and security algorithms. In this paper, key escrow scheme is implemented with the light weighted symmetric algorithm, elliptic curve cryptography in the distributed environment. Key escrow centre is established along with the metadata server and the encryption keys are segmented and shared among the multiple sub agents using Shamir threshold sharing scheme. The implementation of Key Escrow mechanism with Elliptical Curve Cryptography provides wide range of flexibility and confidentiality in the distributed environment. It also eliminates private secret sub key problem and thereby ensuring better security.
Volume: 11
Issue: 3
Page: 1060-1067
Publish at: 2018-09-01

An Effective Pre-Processing Phase for Gene Expression Classification

10.11591/ijeecs.v11.i3.pp1223-1227
Choon Sen Seah , Shahreen Kasim , Mohd Farhan Md Fudzee , Mohd Saberi Mohamad , Rd Rohmat Saedudin , Rohayanti Hassan , Mohd Arfian Ismail , Rodziah Atan
A raw dataset prepared by researchers comes with a lot of information. Whether the information is usefull or not, completely depends on the requirement and purposes. In machine learning, data pre-processing is the very initial stage. It is a must to make sure the dataset is totally suitable for the requirement. In significant directed random walk (sDRW), there are three steps in data pre-processing stage. First, we remove unwanted attributes, missing value and proper arrangement, followed by normalization of the expression value and lastly, filtering method is applied. The first two steps are completed by Bioconductor package while the last step is works in sDRW.
Volume: 11
Issue: 3
Page: 1223-1227
Publish at: 2018-09-01

Kinect-Based Physiotherapy and Assessment: A Comprehensive Review

10.11591/ijeecs.v11.i3.pp1176-1187
Fadilla ‘Atyka Nor Rashid , Nor Surayahani Suriani , Ain Nazari
Kinect-based physical rehabilitation grows significantly as a mechanism for clinical assessment and rehabilitation due to its flexibility, low-cost and markerless system for human action capture. It is also an approach to provide convenience for for patients’ exercises continuation at home.  In this paper, we discuss a review of the present Kinect-based physiotherapy and assessment for rehabilitation patients to provide an outline of the state of art, limitation and issues of concern as well as suggestion for future work in this approach. The paper is constructed into three main parts. The introduction was discussed on physiotherapy exercises and the limitation of current Kinect-based applications. Next, we also discuss on Kinect Skeleton Joint and Kinect Depth Map features that being used widely nowadays. A concise summary with significant findings of each paper had been tabulate for each feature; Skeleton Joints and Depth Map. Afterwards, we assemble a quite number of classification method that being implemented for activity recognition in past few years.
Volume: 11
Issue: 3
Page: 1176-1187
Publish at: 2018-09-01

Automated Detection of Microaneurysmsusing Probabilistic Cascaded Neural Network

10.11591/ijeecs.v11.i3.pp1083-1093
Jeyapriya J , K S Umadevi , R Jagadeesh Kannan
The diagnosing features for Diabetic Retinopathy (DR) comprises of features occurring in and around the regions of blood vessel zone which will result into exudes, hemorrhages, microaneurysms and generation of textures on the albumen region of eye balls. In this study we presenta probabilistic convolution neural network based algorithms, utilized for the extraction of such features from the retinal images of patient’s eyeballs. The classifications proficiency of various DR systems is tabulated and examined. The majority of the reported systems are profoundly advanced regarding the analyzed fundus images is catching up to the human ophthalmologist’s characterization capacities.
Volume: 11
Issue: 3
Page: 1083-1093
Publish at: 2018-09-01

Application of Multi Layer Artificial Neural Network in the Diagnosis System: A Systematic Review

10.11591/ijai.v7.i3.pp138-142
Arvind Singh Rawat , Arti Rana , Adesh Kumar , Ashish Bagwari
Basic hardware comprehension of an artificial neural network (ANN), to a major scale depends on the proficientrealization of a distinctneuron. For hardware execution of NNs, mostly FPGA-designed reconfigurable computing systems are favorable .FPGA comprehension of ANNs through a hugeamount of neurons is mainlyan exigentassignment. This workconverses the reviews on various research articles of neural networks whose concernsfocused in execution of more than one input neuron and multilayer with or without linearity property by using FPGA. An execution technique through reserve substitution isprojected to adjust signed decimal facts. A detailed review of many research papers have been done for the proposed work.
Volume: 7
Issue: 3
Page: 138-142
Publish at: 2018-09-01

A Review of Crude Oil Prices Forecasting using Hybrid Method

10.11591/ijeecs.v11.i3.pp1114-1120
Nurull Qurraisya Nadiyya Md-Khair , Ruhaidah Samsudin
Crude oil is considered as a crucial energy source in modern days. Consequently, the fluctuation of crude oil prices can cause a significant impact on economic activities. Researchers have proposed many hybrid forecasting models on top of single forecasting methods which are utilized to predict crude oil prices movement more accurately. Nevertheless, many limitations still existed in hybrid forecasting models and models that can predict crude oil prices as accurate as possible is required. The motivations of this review paper are to identify and assess the mostly used crude oil prices forecasting methods and to analyse their current limitations. 12 studies that used “decomposition-and-ensemble” framework was selected for review. Wavelet transform is identified as the mostly used data decomposition method while some limitations have been recognized. Future researches should include more studies to further elucidate the limitations in existing forecasting method so that subsequent forecasting methods can be improved.
Volume: 11
Issue: 3
Page: 1114-1120
Publish at: 2018-09-01

Design Process to Reduce Production Cycle Time in Product Development

10.11591/ijai.v7.i3.pp125-129
Mahesh Mallampati , Kolla Srivinivas , Tirumala Krishna. M
In today’s business climate, the old adage “time is money” has been expanded to mean that time is competitive weapon. Today customer’s demands are quick delivery and good quality at reasonable price. When entering the global market the companies encounter several difficulties, the most important one being excessive time for new product development. Thus to perform in a global market, short lead times are essential to provide customer satisfaction. Lead time in manufacturer point of view is the time elapse between placing of an order and the receipt of goods ordered. There are various components of lead time such as setup time, process time, move time and waiting time. This paper deals with review of various tools and techniques to reduce lead time. This problem can be solved by transition from sequential engineering to concurrent engineering, A survey of published works in the field of designing teams in big companies has revealed that in big companies a three-level team structure is recommended, as well as a workgroup, consisting of four basic teams. Method study techniques use to examine current way of work and develop effective method base on elimination, combining, changing and simplification of activities. Various lean tools such as Single Minute Exchange of Dies (SMED), 5S, Poka-yoke, Kanban, Just-in-time (JIT), Value Stream Mapping (VSM), Jidoka, Cellular manufacturing etc. helps in reducing lead time. Also Manufacturing Resource Planning (MRPII), Theory of Constraints (TOC) classic approaches of Production Planning and Control (PPC) are use to reduce Work in Process (WIP) and flow time.
Volume: 7
Issue: 3
Page: 125-129
Publish at: 2018-09-01

Identification of Rainfall Patterns on Hydrological Simulation Using Robust Principal Component Analysis

10.11591/ijeecs.v11.i3.pp1162-1167
S.M. Shaharudin , N. Ahmad , N.H. Zainuddin , N.S. Mohamed
A robust dimension reduction method in Principal Component Analysis (PCA) was used to rectify the issue of unbalanced clusters in rainfall patterns due to the skewed nature of rainfall data. A robust measure in PCA using Tukey’s biweight correlation to downweigh observations was introduced and the optimum breakdown point to extract the number of components in PCA using this approach is proposed. A set of simulated data matrix that mimicked the real data set was used to determine an appropriate breakdown point for robust PCA and  compare the performance of the both approaches. The simulated data indicated a breakdown point of 70% cumulative percentage of variance gave a good balance in extracting the number of components .The results showed a  more significant and substantial improvement with the robust PCA than the PCA based Pearson correlation in terms of the average number of clusters obtained and its cluster quality.
Volume: 11
Issue: 3
Page: 1162-1167
Publish at: 2018-09-01

Signal Processing in Telecommunications with Forward Correction of Errors

10.11591/ijeecs.v11.i3.pp868-877
Juliy Boiko , Oleksander Eromenko
The development of mechanisms of increase efficiency of frequency-shift keying signals processing in telecommunications using algorithms of noise immunity channel coding in obstacle effect conditions is held in the article. The synthesis of the frequency-shift keying signal processing unit accounting intersymbol communication which is inherent for such signals with continuous phase is held. The conditions of the compromise implementation in the telecommunication information transmission channel with frequency shift keying and error correction coding for setting the optimal encoding rate in the range of the bandwidth of the information transmission system are explored. Linear cyclic codes Bose-Chaudhuri-Hocquenghem (BCH) are used for studying. By means of Matlab the article focuses on the definition of energetic benefit compared to uncoded system in case of equality of the bandwidth of the information transmission system with coding and without coding.
Volume: 11
Issue: 3
Page: 868-877
Publish at: 2018-09-01

Homotopy Analysis Method for the First Order Fuzzy Volterra-Fredholm Integro-differential Equations

10.11591/ijeecs.v11.i3.pp857-867
Ahmed A. Hamoud , Kirtiwant P. Ghadle
A fuzzy Volterra-Fredholm integro-differential equation (FVFIDE) in a parametric case is converted to its related crisp case.  We use homotopy analysis method to find the approximate solution of this system and hence obtain an approximation for the fuzzy solution of the  FVFIDE. This paper discusses existence and uniqueness results and convergence of the proposed method.
Volume: 11
Issue: 3
Page: 857-867
Publish at: 2018-09-01

The Fuzzy Inference System with Least Square Optimization for Time Series Forecasting

10.11591/ijeecs.v11.i3.pp1015-1026
Samingun Handoyo , Marji Marji
The rule base on the fuzzy inference system (FIS) has a major role since the output generated by the system is highly dependent on it. The rule base is usually obtained from an expert but in this study proposed the rule base generated based on input-output data pairs with generating rule bases using lookup table scheme, then consequent part of each rule optimized with ordinary least square(OLS), so finally formed rule base from model FIS Takagi-Sugeno orde zero. The exchange rate dataset of EURO to USD is used for the development and validation of the system. In this study, 12 FISs were developed from a combination of linguistic values of n = 3,5,7, 9 with the number of lag (k) assumed to have an effect on output for k = 2,3,5. In training data, values R2 ranged between 0.989 and 0.993, MAPE values ranged between 0.381% and 0.473% where the FIS with the combination of n = 9 and k = 5 has the best performance. In the testing data, values R2 ranged between 0.203 and 0.7858, MAPE values ranged between 0.5136% and 0.9457% where FIS n = 3 and k = 2 perform best.
Volume: 11
Issue: 3
Page: 1015-1026
Publish at: 2018-09-01

A Novel Approach for Efficient Training of Deep Neural Networks

10.11591/ijeecs.v11.i3.pp954-961
D.T.V. Dharmajee Rao , K.V. Ramana
Deep Neural Network training algorithms consumes long training time, especially when the number of hidden layers and nodes is large. Matrix multiplication is the key operation carried out at every node of each layer for several hundreds of thousands of times during the training of Deep Neural Network. Blocking is a well-proven optimization technique to improve the performance of matrix multiplication. Blocked Matrix multiplication algorithms can easily be parallelized to accelerate the performance further. This paper proposes a novel approach of implementing Parallel Blocked Matrix multiplication algorithms to reduce the long training time. The proposed approach was implemented using a parallel programming model OpenMP with collapse() clause for the multiplication of input and weight matrices of Backpropagation and Boltzmann Machine Algorithms for training Deep Neural Network and tested on multi-core processor system. Experimental results showed that the proposed approach achieved approximately two times speedup than classic algorithms.
Volume: 11
Issue: 3
Page: 954-961
Publish at: 2018-09-01

Modified SHA-1 Algorithm

10.11591/ijeecs.v11.i3.pp1027-1034
Rogel Ladia Quilala , Ariel M Sison , Ruji P Medina
Hashes are used to check the integrity of data. This paper modified SHA-1 by incorporating mixing method in every round for better diffusion. The modification increased the hash output to 192-bits. Increasing the output increases the strength because breaking the hash takes longer. Based on the different message types, avalanche percentage of modified SHA-1 showed better diffusion at 51.64%, higher than the target 50%, while SHA-1 achieved 46.61%. The average execution time noted for modified SHA-1 is 0.33 seconds while SHA-1 is 0.08 seconds. Time increases as the number of messages hashed increases; the difference is negligible in fewer messages. On character hits, that is - no same character in the same position, modified SHA-1 achieved lower hit rate because of the mixing method added. The modifications’ effectiveness was also evaluated using a hash test program. After inputting 1000 hashes from random strings, the result shows no duplicate hash.
Volume: 11
Issue: 3
Page: 1027-1034
Publish at: 2018-09-01
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