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29,758 Article Results

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

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

Enhanced RSA Cryptosystem based on Multiplicity of Public and Private Keys

10.11591/ijece.v8i5.pp3949-3953
Ahmed Eskander Mezher
Security is one of the most important concern to the information and data sharing for companies, banks, organizations and government facilities. RSA is a public cryptographic algorithm that is designed specifically for authentication and data encryption. One of the most powerful reasons makes RSA more secure is that the avoidance of key exchange in the encryption and decryption processes. Standard RSA algorithm depends on the key length only to protect systems. However, RSA key is broken from time to another due to the development of computers hardware such as high speed processors and advanced technology. RSA developers have increased a key length or size of a key periodically to maintain a high security and privacy to systems that are protected by the RSA. In this paper, a method has been designed and implemented to strengthen the RSA algorithm by using multiple public and private keys. Therefore, in this method the security of RSA not only depends on the key size, but also relies on the multiplicity of public and private keys.
Volume: 8
Issue: 5
Page: 3949-3953
Publish at: 2018-10-01

Epidemic Alert System: A Web-based Grassroots Model

10.11591/ijece.v8i5.pp3809-3828
Etinosa Noma Osaghae , Kennedy Okokpujie , Charles Ndujiuba , Olatunji Okesola , Imhade P. Okokpujie
Most web-based disease surveillance systems that give epidemic alerts are based on very large and unstructured data from various news sources, social media and online queries that are parsed by complex algorithms. This has the tendency to generate results that are so diverse and non-specific. When considered along with the fact that there are no existing standards for mining and analyzing data from the internet, the results or decisions reached based on internet sources have been classified as low-quality. This paper proposes a web-based grassroots epidemic alert system that is based on data collected specifically from primary health centers, hospitals and registered laboratories. It takes a more traditional approach to indicator-based disease surveillance as a step towards standardizing web-based disease surveillance. It makes use of a threshold value that is based on the third quartile (75th percentile) to determine the need to trigger the alarm for the onset of an epidemic. It also includes, for deeper analysis, demographic information.
Volume: 8
Issue: 5
Page: 3809-3828
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

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
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