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30,411 Article Results

Feature Extraction of Chest X-ray Images and Analysis using PCA and kPCA

10.11591/ijece.v8i5.pp3392-3398
Roopa H , Asha T
Tuberculosis (TB) is an infectious disease caused by mycobacterium which can be diagnosed by its various symptoms like fever, cough, etc. Tuberculosis can also be analyzed by understanding the chest x-ray of the patient which is revealed by an expert physician .The chest x-ray image contains many features which cannot be directly used by any computer system for analyzing the disease. Features of chest x-ray images must be understood and extracted, so that it can be processed to a form to be fed to any computer system for disease analysis. This paper presents feature extraction of chest x-ray image which can be used as an input for any data mining algorithm for TB disease analysis. So texture and shape based features are extracted from x-ray image using image processing concepts. The features extracted are analyzed using principal component analysis (PCA) and kernel principal component analysis (kPCA) techniques. Filter and wrapper feature selection method using linear regression model were applied on these techniques. The performance of PCA and kPCA are analyzed and found that the accuracy of PCA using wrapper approach is 96.07%   when compared to the accuracy of kPCA which is 62.50%. PCA performs well than kPCA with a good accuracy.
Volume: 8
Issue: 5
Page: 3392-3398
Publish at: 2018-10-01

Performance Investigation of OFDM-FSO System under Diverse Weather Conditions of Bangladesh

10.11591/ijece.v8i5.pp3722-3731
Maliha Sultana , Agnila Barua , Jobaida Akhtar , Mohammad Istiaque Reja
Free space optical (FSO) communication systems which are deployed for last mile access, being considered as a suitable alternative technology for optical fiber networks. It is one of the emerging technologies for broadband wireless connectivity which has also been receiving growing attention due to high data rate transmission capability with low installation cost and license free spectrum. However, the widespread use of FSO technology has been hampered by the randomly time varying characteristics of propagation path mainly due to atmospheric turbulence, sensitivity to diverse weather conditions and the nonlinear responsivity of laser diode. This paper presents the performance investigation of an OFDM-FSO system over atmospheric turbulence channels under diverse weather conditions of Bangladesh. The channel is modeled with gamma-gamma distribution using 16-QAM modulation format and 4×4 multiple transceiver FSO system. All possible challenges are imposed on the system performance such as atmospheric attenuation, turbulence, pointing error, geometric loss etc. The refractive index structure parameter and atmospheric attenuation coefficient for different weather conditions are calculated by using the data, collected from Bangladesh Meteorological Department. The acquired results can be fruitful for scheming, forecasting and assessing the OFDM-FSO system’s ability to transmit wireless services over turbulent FSO links under actual conditions of Bangladesh.
Volume: 8
Issue: 5
Page: 3722-3731
Publish at: 2018-10-01

MICCS: A Novel Framework for Medical Image Compression Using Compressive Sensing

10.11591/ijece.v8i5.pp2818-2828
Lakshminarayana M , Mrinal Sarvagya
The vision of some particular applications such as robot-guided remote surgery where the image of a patient body will need to be captured by the smart visual sensor and to be sent on a real-time basis through a network of high bandwidth but yet limited. The particular problem considered for the study is to develop a mechanism of a hybrid approach of compression where the Region-of-Interest (ROI) should be compressed with lossless compression techniques and Non-ROI should be compressed with Compressive Sensing (CS) techniques. So the challenge is gaining equal image quality for both ROI and Non-ROI while overcoming optimized dimension reduction by sparsity into Non-ROI. It is essential to retain acceptable visual quality to Non-ROI compressed region to obtain a better reconstructed image. This step could bridge the trade-off between image quality and traffic load. The study outcomes were compared with traditional hybrid compression methods to find that proposed method achieves better compression performance as compared to conventional hybrid compression techniques on the performances parameters e.g. PSNR, MSE, and Compression Ratio.
Volume: 8
Issue: 5
Page: 2818-2828
Publish at: 2018-10-01

Robust Visual Multi Target Trackers: A Review

10.11591/ijeecs.v12.i1.pp7-16
Pavan Kumar E , Manojkumar Rajgopal
In this review paper, we address on the state-of-art process with visual object tracking in video surveillance, medical and military applications. In the present scenario number of algorithms and methods are used to track the object in the different scene, a robust visual object tracking remains a critical challenge. The challenges arise due to object motion from frame to frame with a change in appearance, structures, illumination, and occlusion. In this paper, at last, we outline the different algorithms, dataset, strength, and weakness of the different object tracker.
Volume: 12
Issue: 1
Page: 7-16
Publish at: 2018-10-01

Simplified Space Vector Pulse Width Modulation based on Switching Schemes with Reduced Switching Frequency and Harmonics for Five Level Cascaded H-Bridge Inverter

10.11591/ijece.v8i5.pp3417-3426
B. Sirisha , P. Satishkumar
This paper presents a simplified control strategy of spacevector pulse width modulation technique with a three segment switching sequence and seven segment switching sequence for high power applications of multilevel inverters. In the proposed method, the inverter switching sequences are optimized for minimization of device switching frequency and improvement of harmonic spectrum by using the three most desired switching states and one suitable redundant state for each space vector. The proposed three-segment sequence is compared with conventional seven-segment sequence for five level Cascaded H-Bridge inverter with various values of switching frequencies including very low frequency. The output spectrum of the proposed sequence design shows the reduction of device switching frequency, current and line voltage THD, thereby minimizing the filter size requirement of the inverter, employed in industrial applications, where sinusoidal output voltage is required.
Volume: 8
Issue: 5
Page: 3417-3426
Publish at: 2018-10-01

Faults Signature Extraction in Wind Farm Integrated Transmission Line Topology

10.11591/ijeecs.v12.i1.pp246-253
Osaji Emmanuel , Mohammad Lutfi Othman , Hashim Hizam , Muhammad M. Othman , Elhad Akar E. , Okeke Chidiebere A. , Nwagbara Samuel O.
The integration of Renewable Green Energy Sources (RGES) like Wind Farm Generators (WFG), and Photo Voltaic (PV) systems into convention power system as a future solution to the increase in global energy demands, generation cost reduction, and limited climate impact. The innovation introduced protection compromise challenges in power system due to in-feeds fault current penetration from RGES on existing system, leading to an undesired trip of the healthy section of TL, equipment damages, and safety failure. A comparison study of extracted faults signature from two proposed Transmission Line (TL) network topologies with and without WFG integration, for onward fault identification, and classification model design. Descrete wavelet multiresolution Analysis (DWMRA) of extracted one-cycle fault signal signatures from 11 faults type’s scenarios in Matlab. Result demonstrated a unique fault signatures across all simulated faults scenarios harness for future work of an adaptive unit protection model for this new area of DG integration.
Volume: 12
Issue: 1
Page: 246-253
Publish at: 2018-10-01

The Impact of Social Media Technologies on Adult Learning

10.11591/ijece.v8i5.pp3747-3755
Khalil Alsaadat
Technology and social media have presented significant tools for adult learners to learn and advance continually. Fast technological advancements have enabled development of technologies used for learning. Expansion of various tools has given professors, educaters, trainers, instructers, many alternatives towards the implementation of the technology supported learning. The use of social media can improve adult learning outcomes and academic accomplishment. Social media is increasingly proven to be beneficial in adult learning and has a huge potential for adult education. This paper sheds some lights on benefits of social media for adult learners, this is incorporated through the review of previous work and some barriers that encounters social media for learning purposes. Also some social media models are reviewed to show the growth and effect of social media in adult learning context, and suggestions and recommendations are provided.
Volume: 8
Issue: 5
Page: 3747-3755
Publish at: 2018-10-01

Load Balance in Data Center SDN Networks

10.11591/ijece.v8i5.pp3084-3091
Tariq Emad Ali , Ameer Hussein Morad , Mohammed A. Abdala
In the last two decades, networks had been changed according to the rapid changing in its requirements.  The current Data Center Networks have large number of hosts (tens or thousands) with special needs of bandwidth as the cloud network and the multimedia content computing is increased. The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations.  The current networking devices with its control and forwarding planes coupling result in network architectures are not suitable for dynamic computing and storage needs.  Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling control and forwarding planes. So, due to the rapid increase in the number of applications, websites, storage space, and some of the network resources are being underutilized due to static routing mechanisms. To overcome these limitations, a Software Defined Network based Openflow Data Center network architecture is used to obtain better performance parameters and implementing traffic load balancing function. The load balancing distributes the traffic requests over the connected servers, to diminish network congestions, and reduce underutilization problem of servers. As a result, SDN is developed to afford more effective configuration, enhanced performance, and more flexibility to deal with huge network designs
Volume: 8
Issue: 5
Page: 3084-3091
Publish at: 2018-10-01

Experimental Analysis of Web Browser Sessions Using Live Forensics Method

10.11591/ijece.v8i5.pp2951-2958
Rusydi Umar , Anton Yudhana , Muhammad Nur Faiz
In today's digital era almost every aspect of life requires the internet, one way to access the internet is through a web browser. For security reasons, one developed is private mode. Unfortunately, some users using this feature do it for cybercrime. The use of this feature is to minimize the discovery of digital evidence. The standard investigative techniques of NIST need to be developed to uncover an ever-varied cybercrime. Live Forensics is an investigative development model for obtaining evidence of computer usage. This research provides a solution in forensic investigation effectively and efficiently by using live forensics. This paper proposes a framework for web browser analysis. Live Forensics allows investigators to obtain data from RAM that contains computer usage sessions. 
Volume: 8
Issue: 5
Page: 2951-2958
Publish at: 2018-10-01

Optimal Economic Load Dispatch using Multiobjective Cuckoo Search Algorithm

10.11591/ijeecs.v12.i1.pp168-174
Z.M. Yasin , N.F.A. Aziz , N.A. Salim , N.A. Wahab , N.A. Rahmat
In this paper, Multiobjective Cuckoo Search Algorithm (MOCSA) is developed to solve Economic Load Dispatch (ELD) problem. The main goal of the ELD is to meet the load demand at minimum operating cost by determining the output of the committed generating unit while satisfying system equality and inequality constraints. The problem formulation is based on a multiobjective model in which the multiobjective are defined as fuel cost minimization and carbon emission minimization. MOCSA is based on the inspiration from the brooding parasitism of cuckoo species in nature. Three cases are considered to test the effectiveness of the proposed technique which are fuel cost minimization, carbon emission minimization and multiobjective function with fixed weighted sum. The effectiveness of the MOCSA’s performances are illustrated through comparative study with other techniques such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Particle Swarm Optimization (MOPSO) in terms of fitness functions. The proposed study was conducted on three generating unit system at various loading condition. The result proved that MOCSA provide better solution in minimizing fuel cost and carbon emission usage as compared to other techniques.
Volume: 12
Issue: 1
Page: 168-174
Publish at: 2018-10-01

Study on Breakdown Voltage for Vegetable Oils With Additive TiO2

10.11591/ijeecs.v12.i1.pp175-181
Muhammad Bin Yahya , Raja Muhammad Khidir Raja Chik
High voltage power transformers commonly used petroleum-based mineral oil for cooling and insulation purposes. Researchers are looking for suitable vegetable oils as alternatives to mineral oil to be used as transformer oil. The alternative vegetable oils are biodegradable, non-toxic and environmentally friendly. They may require some processing and modification to improve some of their properties to ascertain their safe use in power and distribution transformers as well as in high voltage equipment. This paper presents a study on the AC breakdown voltages of Palm Oil (PO) and Coconut Oil (CO) with presence of an additive. PO and CO are chosen as they are locally produced oils in Malaysia and easily obtained. The type of additive used in this study is Titanium dioxide TiO2. TiO2 nanoparticles was added into PO and CO at volume concentration of 0.1% to 0.5%. The effect of different gap distance of electrode 1.5mm, 2.5mm and 3.5mm was studied. The temperature of oil is controlled at 30oC. This paper provides a comparative assessment of breakdown properties through experimental investigation of PO and CO before and after the additive is added according to ASTM D1816 standard. From the experimental result, the PO have slightly higher breakdown voltage compared to CO. From all oil sample data recorded, it can be concluded that the breakdown voltage had increased to the increase in gap distance of electrode under presence of TiO2.
Volume: 12
Issue: 1
Page: 175-181
Publish at: 2018-10-01

A Modified Boltzmann Machine for Solving Distribution System Expansion Planning in Malaysia

10.11591/ijeecs.v12.i1.pp193-200
Siti Hajar Mohd Tahar , Shamshul Bahar Yaakob , Amran Ahmed
This paper proposes an effective technique to solve Distribution System Expansion Planning (DSEP) problem by using the artificial neural network. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer quadratic programming problem. It consists of two layers neural network which combine Hopfield network and Boltzmann machine (BM) in upper and lower layer respectively named as Modified BM. The originality of the proposed technique is it will delete the unit of the second layer, which is not selected in the first layer in its execution. Then, the second layer is restructured using the selected units. Due to this feature, the proposed technique will improve time consuming and accuracy of solution. Referring to the case study demonstrated in this paper, the significance outputs obtained are the improvement in computational time and accuracy of solution provided. As the solution provided various of options, the proposed technique will help decision makers in solving DSEP problem. As a result, the performance of strategic investment planning in DSEP certainly enhanced.
Volume: 12
Issue: 1
Page: 193-200
Publish at: 2018-10-01

Mining Fuzzy Time Interval Periodic Patterns in Smart Home Data

10.11591/ijece.v8i5.pp3374-3385
Imam Mukhlash , Desna Yuanda , Mohammad Iqbal
A convergence of technologies in data mining, machine learning, and a persuasive computer has led to an interest in the development of smart environment to help human with functions, such as monitoring and remote health interventions, activity recognition, energy saving. The need for technology development was confirmed again by the aging population and the importance of individual independent in their own homes. Pattern mining on sensor data from smart home is widely applied in research such as using data mining. In this paper, we proposed a periodic pattern mining in smart house data that is integrated between the FP-Growth PrefixSpan algorithm and a fuzzy approach, which is called as fuzzy-time interval periodic patterns mining. Our purpose is to obtain the periodic pattern of activity at various time intervals. The simulation results show that the resident activities can be recognized by analyzing the triggered sensor patterns, and the impacts of minimum support values to the number of fuzzy-time-interval periodic patterns generated. Moreover, fuzzy-time-interval periodic patterns that are generated encourages to find daily or anomalies resident’s habits.
Volume: 8
Issue: 5
Page: 3374-3385
Publish at: 2018-10-01

Structuring Elements of Hit or Miss to Identify Pattern of Benchmark Latin Alphabets Strokes

10.11591/ijeecs.v12.i1.pp356-362
Norzehan Sakamat , Noor Elaiza Abd Khalid , Inda Ishadah Nazrul Azha
Identification of features in correct alphabet stroke formation is a primary factor in acknowledging handwriting legibility. Hit–or-Miss transform is a morphology operator that is often applied to identify geometric features. Identifying the correct structuring elements (SEs) provides a good geometric feature extraction. Therefore this research proposes to identify generic SEs representing alphabet strokes. The handwriting font used is Syazalina83v3 which is  popularly use in teaching writing for lower primary school children in Malaysia. The methodology consists of four phases which are alphabet selection; image pre-processing; manual measurement and hit or miss algorithm with single and various combination of 2x2, 3x3 and 5x5 SE window size; and SEs performance using Pearson correlation.  The  combination of horizontal and vertical, right diagonal and left diagonal SEs performs well with very strong correlation in detecting  Simple Straight Line(SSL), Complex Straight Line(CSL) , Curve Line (CL) and Combination of Curve Line and Simple Straight Line(CLSSL) based on Evan’s correlation guide.
Volume: 12
Issue: 1
Page: 356-362
Publish at: 2018-10-01

An Enhancement Role and Attribute Based Access Control Mechanism in Big Data

10.11591/ijece.v8i5.pp3187-3193
M Meneka , K. Meenakshisundaram
To be able to leverage big data to achieve enhanced strategic insight and make informed decision, an efficient access control mechanism is needed for ensuring end to end security of such information asset. Attribute Based Access Control (ABAC), Role Based Access Control (RBAC) and Event Based Access Control (EBAC) are widely used access control mechanisms. The ABAC system is much more complex in terms of policy reviews, hence analyzing the policy and reviewing or changing user permission are quite complex task. RBAC system is labor intensive and time consuming to build a model instance and it lacks flexibility to efficiently adapt to changing user’s, objects and security policies. EBAC model considered only the events to allocate access controls. Yet these mechanisms have limitations and offer feature complimentary to each other. So in this paper, Event-Role-Attribute based fine grained Access Control mechanism is proposed, it provide a flexible boundary which effectively adapt to changing user’s, objects and security policies based on the event. The flexible boundary is achieved by using temporal and environment state of an event. It improves the big data security and overcomes the disadvantages of the ABAC and RBAC mechanisms. The experiments are conducted to prove the effectiveness of the proposed Event-Role-Attribute based Access Control mechanism over ABAC and RBAC in terms of computational overhead.
Volume: 8
Issue: 5
Page: 3187-3193
Publish at: 2018-10-01
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