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30,033 Article Results

Star Coordinate Dimension Arrangement using Euclidean Distance and Pearson Correlation

10.11591/ijeecs.v12.i1.pp348-355
Noor Elaiza Abdul Khalid , Izyan Izzati Kamsani
Star Coordinate (SC) is a circular visualization technique that maps k-dimensional data. Its interactive features allow user to manipulate projections to search for hidden information. Without prior knowledge of relationship between dimensions users will be blindly searching for clusters. This paper proposes dimension rearrangement using Euclidean Distance and Pearson Correlations to reveal the clusters in SC. The methodology consists of four phases; Calculate the distance between individual attributes against a dependent attribute using Euclidean distance; Pearson correlation is used to obtain the correlation data attributes; Sort the correlation values in ascending order; finally, attributes table are reordered with the positive values to the right and negative values to the left according to the correlation value. The resulting tables are applied to produce the SC. This method is successful in producing clusters that makes it easier for the users to further manipulate the SC for their data analysis.
Volume: 12
Issue: 1
Page: 348-355
Publish at: 2018-10-01

Comparative Analysis of Various Testing Techniques used for Aspect-Oriented Software System

10.11591/ijeecs.v12.i1.pp51-60
Sandeep Dalal , Susheela Hooda
Nowadays, Aspect-Oriented Programming (AOP) paradigm is getting more popularity in the field of software development. But testing an Aspect-oriented software system (AOSS) is not well matured. Therefore, many researchers have been focusing on testing an AOSS. Moreover, the literature indicates that very few papers have devoted to literature survey but still there is need to study in depth of various testing techniques used for AOSS. Therefore, in this paper, a comprehensive study of existing various testing techniques for AOSS have been conducted and present a comparative analysis result of various testing techniques based on various parameters.
Volume: 12
Issue: 1
Page: 51-60
Publish at: 2018-10-01

A Comparative Analysis of Factor Effecting the Buying Judgement of Smart Phone

10.11591/ijece.v8i5.pp3057-3066
Rajni Bhalla , Amandeep Amandeep , Prateek Jain
Smart phone has various utilizations to various clients as per their necessities. With sensational rise in the usage of smart phone the individuals are considering different factors while purchasing a smart phone. This paper has put endeavor to reveal the fundamental factors which effect clients in picking up of the smart phone. A sample of 512 responses was taken through questionnaire. An organized questionnaire was planned with five point Likert scale was utilized to meeting respondent’s .Factor analysis and descriptive statistical tools were applied to extricate the basic variables influence cell phone acquiring choice. The result shows that the most important factors are physical attributes, apps and sounds while the less importance is given to other factors such as convenience, price which can also vary by age, service and gender. The future scope of this paper lies in the fact that whether age, occupation, gender makes any difference in purchasing decision of smart phone.
Volume: 8
Issue: 5
Page: 3057-3066
Publish at: 2018-10-01

Background Estimation Using Principal Component Analysis Based on Limited Memory Block Krylov Subspace Optimization

10.11591/ijece.v8i5.pp2847-2856
Ilmiyati Sari , Asep Juarna , Suryadi Harmanto , Djati Kerami
Given a video of 𝑀 frames of size ℎ × 𝑤. Background components of a video are the elements matrix which relative constant over 𝑀 frames. In PCA (principal component analysis) method these elements are referred as “principal components”. In video processing, background subtraction means excision of background component from the video. PCA method is used to get the background component. This method transforms 3 dimensions video (ℎ × 𝑤 × 𝑀) into 2 dimensions one (𝑁 × 𝑀), where 𝑁 is a linear array of size ℎ × 𝑤. The principal components are the dominant eigenvectors which are the basis of an eigenspace. The limited memory block Krylov subspace optimization then is proposed to improve performance the computation. Background estimation is obtained as the projection each input image (the first frame at each sequence image) onto space expanded principal component. The procedure was run for the standard dataset namely SBI (Scene Background Initialization) dataset consisting of 8 videos with interval resolution [146 150, 352 240], total frame [258,500]. The performances are shown with 8 metrics, especially (in average for 8 videos) percentage of error pixels (0.24%), the percentage of clustered error pixels (0.21%), multiscale structural similarity index (0.88 form maximum 1), and running time (61.68 seconds). 
Volume: 8
Issue: 5
Page: 2847-2856
Publish at: 2018-10-01

Two Level Disambiguation Model for Query Translation

10.11591/ijece.v8i5.pp3923-3932
Pratibha Bajpai , Parul Verma , Syed Q. Abbas
Selection of the most suitable translation among all translation candidates returned by bilingual dictionary has always been quiet challenging task for any cross language query translation. Researchers have frequently tried to use word co-occurrence statistics to determine the most probable translation for user query. Algorithms using such statistics have certain shortcomings, which are focused in this paper. We propose a novel method for ambiguity resolution, named ‘two level disambiguation model’. At first level disambiguation, the model properly weighs the importance of translation alternatives of query terms obtained from the dictionary. The importance factor measures the probability of a translation candidate of being selected as the final translation of a query term. This removes the problem of taking binary decision for translation candidates. At second level disambiguation, the model targets the user query as a single concept and deduces the translation of all query terms simultaneously, taking into account the weights of translation alternatives also. This is contrary to previous researches which select translation for each word in source language query independently. The experimental result with English-Hindi cross language information retrieval shows that the proposed two level disambiguation model achieved 79.53% and 83.50% of monolingual translation and 21.11% and 17.36% improvement compared to greedy disambiguation strategies in terms of MAP for short and long queries respectively.
Volume: 8
Issue: 5
Page: 3923-3932
Publish at: 2018-10-01

Bypass Diodes for Improving Solar Panel Performance

10.11591/ijece.v8i5.pp2703-2708
Fadliondi Fadliondi , Haris Isyanto , Budiyanto Budiyanto
The ouput power of solar panel that decreased due to shading has been improved using bypass diode method. The placement of bypass diodes increased the output current and power. New peaks and maximum powerpoints on the current-svoltage characteristics and power-voltage characteristics were observed. Without bypass diodes, the maximum output power was only around 50 W. After placing bypass diodes, the first peak around 115 W and second peak around 150 W appeared at voltage of around 31 V and 40 V, respectively.
Volume: 8
Issue: 5
Page: 2703-2708
Publish at: 2018-10-01

Fuel Station Monitoring and Automation based on WSN

10.11591/ijece.v8i5.pp3647-3656
Ehab AbdulRazzaq Hussein , Mahran Obaid Waheed
The Iraqi fuel station still now uses old technologies to control its activities from filling tanks to the filling cars. Automate the activity of fuel station is the objective of this work. The aims of fuel station automation are to save the fuel quantities and qualities supplied in fuel station, and to keep the fuel station, the worker and its main parts safe. This work uses the national instrument wireless sensor network (NI WSN). The NI WSN used to automate the protection system and level controlling system which makes the fuel station work under normal ambient temperature, and normal protection conditions. Automation based on a wireless sensor network gives excellent capabilities to automate and monitor fuel station. Through the user interface window the user monitor the status of actuators, protection system controller messages, fuel levels, water level, environment temperature, power source and its quality. The soft controller developed was built within The LABVIEW environment. The results of controller give the desired action through "on" and “off” states of the actuators.
Volume: 8
Issue: 5
Page: 3647-3656
Publish at: 2018-10-01

A New Approach to the Detection of Mammogram Boundary

10.11591/ijece.v8i5.pp3587-3593
Mohammed Rmili , Abdelmajid El Moutaouakkil , Mousatapha M. Saleck , Maksi Bouchaib , Fatiha Adnani , El Mehdi El Aroussi
Mammography is a method used for the detection of breast cancer. computer-aided diagnostic (CAD) systems help the radiologist in the detection and interpretation of mass in breast mammography. One of the important information of a mass is its contour and its form because it provides valuable information about the abnormality of a mass. The accuracy in the recognition of the shape of a mass is related to the accuracy of the detected mass contours. In this work we propose a new approach for detecting the boundaries of lesion in mammography images based on region growing algorithm without using the threshold, the proposed method requires an initial rectangle surrounding the lesion selected manually by the radiologist (Region Of Interest), where the region growing algorithm applies on lines segments that attach each pixel of this rectangle with the seed point, such as the ends (seeds) of each line segment grow in a direction towards one another. The proposed approach is evaluated on a set of data with 20 masses of the MIAS base whose contours are annotated manually by expert radiologists. The performance of the method is evaluated in terms of specificity, sensitivity, accuracy and overlap. All the findings and details of approach are presented in detail.
Volume: 8
Issue: 5
Page: 3587-3593
Publish at: 2018-10-01

Review on Security Aspects for Cloud Architecture

10.11591/ijece.v8i5.pp3129-3139
Shaz Alam , Mohd Muqeem , Suhel Ahmad Khan
Cloud computing is one of the fastest growing and popular technology in the field of computing. As the concept of cloud computing was introduced in 2006. Since then large number of IT industries join the queue to develop many cloud services and put sensitive information over cloud. In fact cloud computing is no doubt the great innovation in the field of computing but at the same time also poses many challenges. Since a large number of organizations migrate their business to cloud and hence it appears as an attractive target for the malicious attack. The purpose of the paper is to review the available literature for security concerns and highlight a relationship between vulnerabilities, attacks and threats in SaaS model. A mapping is being presented to highlight the impact of vulnerabilities and attacks.
Volume: 8
Issue: 5
Page: 3129-3139
Publish at: 2018-10-01

Galvanic Skin Response Data Classification for Emotion Detection

10.11591/ijece.v8i5.pp4004-4014
Djoko Budiyanto Setyohadi , Sri Kusrohmaniah , Sebastian Bagya Gunawan , Pranowo Pranowo , Anton Satria Prabuwono
Emotion detection is a very exhausting job and needs a complicated process; moreover, these processes also require the proper data training and appropriate algorithm. The process involves the experimental research in psychological experiment and classification methods. This paper describes a method on detection emotion using Galvanic Skin Response (GSR) data. We used the Positive and Negative Affect Schedule (PANAS) method to get a good data training. Furthermore, Support Vector Machine and a correct preprocessing are performed to classify the GSR data. To validate the proposed approach, Receiver Operating Characteristic (ROC) curve, and accuracy measurement are used. Our method shows that the accuracy is about 75.65% while ROC is about 0.8019. It means that the emotion detection can be done satisfactorily and well performed.
Volume: 8
Issue: 5
Page: 4004-4014
Publish at: 2018-10-01

High Voltage Durability of Bambusa Vulgaris as a Bio-composite Material

10.11591/ijece.v8i5.pp2643-2649
M. Y. Mat Zain , M.T. Ali , A. N. H. Hussin
This study is conducted in order to measure and identify the ability of a bio-composite material to the high voltage. According to it, the developed bio-composite material is tested to ensure the maximum voltage that the material can hold. The bio-composite material which made from a mixture of Bambusa Vulgaris and a selected polymer named as High Density Polyethylene (HDPE). The Bambusa Vulgarisis going through several processes before mixed together with HDPE using wood plastic composite (WPC) technique which also consists of several stages. There are several samples of bio-composite substance are fabricated. The difference among them is the composition of the raw materials (Bambusa Vulgaris and HDPE) used. In this research, the high voltage measurement which also called as breakdown voltage measurement of the bio-composite material is examined by using appropriate experiments. All the experimental results are presented and discussed in this paper.
Volume: 8
Issue: 5
Page: 2643-2649
Publish at: 2018-10-01

Multi-modal Asian Conversation Mobile Video Dataset for Recognition Task

10.11591/ijece.v8i5.pp4042-4046
Dewi Suryani , Valentino Ekaputra , Andry Chowanda
Images, audio, and videos have been used by researchers for a long time to develop several tasks regarding human facial recognition and emotion detection. Most of the available datasets usually focus on either static expression, a short video of changing emotion from neutral to peak emotion, or difference in sounds to detect the current emotion of a person. Moreover, the common datasets were collected and processed in the United States (US) or Europe, and only several datasets were originated from Asia. In this paper, we present our effort to create a unique dataset that can fill in the gap by currently available datasets. At the time of writing, our datasets contain 10 full HD (1920 1080) video clips with annotated JSON file, which is in total 100 minutes of duration and the total size of 13 GB. We believe this dataset will be useful as a training and benchmark data for a variety of research topics regarding human facial and emotion recognition.
Volume: 8
Issue: 5
Page: 4042-4046
Publish at: 2018-10-01

Challenges and Opportunities of Internet of Things in Healthcare

10.11591/ijece.v8i5.pp2753-2761
Amine Rghioui , Abdelmajid Oumnad
The Internet of  Things (IoT) relies on physical objects interconnected between each other’s, creating a mesh of devices producing information and services. In this context, sensors and actuators are being continuously embedded in everyday objects (e.g., cars, home appliances, and smartphones) thus pervading our living environment. Among the plethora of application contexts, smart Healthcare is gaining momentum. Indeed IoT can revolutionize the healthcare industry by improving operational efficiency and clinical trials’ quality of monitoring, and by optimizing healthcare costs. This paper provides an overview of IoT, its applicability in healthcare, some insights about current trends and an outlook on future developments of healthcare systems. 
Volume: 8
Issue: 5
Page: 2753-2761
Publish at: 2018-10-01

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

An Efficient Filtering Technique for Denoising Colour Images

10.11591/ijece.v8i5.pp3604-3608
K. Arun Sai , K. Ravi
Single-sensor digital cameras capture image with the aid of masking the sensor surface along a colour filter array(CFA) such that every sensor pixel solely samples certain of three primary colour values i.e., R (red)，G (green) and B (blue). To get a full-colour image, an interpolation method commonly referred in conformity with CFA demosaicking is required to estimate the other two contributions for producing a full-colour image. But, the clutter in imaging sensors not only corrupts the colour filter array but also introduces artifacts at some stage in the colour interpolation step and affects the characteristics of image. To acquire high quality full-colour image, a kind of viable and effective interpolation algorithm based over gradient is used. This technique can remove the noise effectively by retaining image border and detail data clearly.
Volume: 8
Issue: 5
Page: 3604-3608
Publish at: 2018-10-01
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