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31,456 Article Results

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

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

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

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

An Architecture for Simplified and Automated Machine Learning

10.11591/ijece.v8i5.pp2994-3002
Jittapoo Poolwan , Sucha Smanchat
learning has been adopted by businesses to analyze their vast data in order to make strategic decision. However, knowledge in machine learning and technical skill are usually required to prepare data and perform machine learning tasks. This obstacle prevents smaller businesses with no technical knowledge to utilize machine learning. In this paper, we propose an architecture for simplified and automated machine learning process currently supporting the data classification task. The architecture includes a method for characterizing datasets, which allows for simplifying and automating machine learning model and hyperparameter selection based on historical execution configurations. Users can simply upload their datasets via a web browser, and the system will determine the possible models and their hyperparameter configurations for the users to choose from. The prototype shows the feasibility of the proposed architecture. Although the accuracy is still limited by the small execution history and the cleanliness of the input datasets, the architecture can minimize user involvement in the machine learning process so that non-technical users can perform data classification through a web browser without installing any software.
Volume: 8
Issue: 5
Page: 2994-3002
Publish at: 2018-10-01

Probabilistic Performance Index based Contingency Screening for Composite Power System Reliability Evaluation

10.11591/ijece.v8i5.pp2661-2670
Venkata Satheesh Babu K , Madhusudan V , Ganesh V
Composite power system reliability involves assessing the adequacy of generation and transmission system to meet the demand at major system load points. Contingency selection was being the most tedious step in reliability evaluation of large electric systems. Contingency in power system might be a possible event in future which was not predicted with certainty in earlier research. Therefore, uncertainty may be inevitable in power system operation. Deterministic indices may not guarantee the randomness in reliability assessment. In order to account for volatility in contingencies, a new performance index proposed in the current research. Proposed method assimilates the uncertainty in computational procedure. Reliability test systems like Roy Billinton Test System-6 bus system and IEEE-24 bus reliability test systems were used to test the effectiveness of a proposed method.
Volume: 8
Issue: 5
Page: 2661-2670
Publish at: 2018-10-01
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