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31,458 Article Results

An Automatic ROI of The Fundus Photography

10.11591/ijece.v8i6.pp4545-4553
Jufriadif Na'am , Johan Harlan , Irawadi Putra , Romi Hardianto , Mutiana Pratiwi
The Region of interest (ROI) of the fundus photography is an important task in medical image processing. It contains a lot of information related to the diagnosis of the retinal disease. So the determination of this ROI is a very influential first step in fundus image processing later. This research proposed a threshold method of segmentation to determine ROI of the fundus photography automatically. Data to be elaborated were the fundus photography’s of 13 patients, captured using Nonmyd7 camera of Kowa Company Ltd in Dr. M. Djamil Hospital, Padang. The results of this processing could determine ROI automatically. The automatic cropping successfully omits as much as possible the non-medical areas shown as darkbackground, while still maintaining the whole medical areas, comprised the posterior pole of retina captured through the pupil. Thus, this method is  helpful in further image processing of posterior areas. We hope that this research will be useful for researchers.
Volume: 8
Issue: 6
Page: 4545-4553
Publish at: 2018-12-01

Development of Regenerative Braking Concept for Electric Vehicle Enhanced with Bidirectional Converter

10.11591/ijpeds.v9.i4.pp1584-1590
M. Kavitha , V. Elanangai , S. Jayaprakash , V. Balasubramanian
Due to the increasing concern for environment protection and the uncertainty about oil reserves, nowadays electricity is playing a key role as an alternative energy source in the automotive sector. In this paper, non isolated bidirectional converter is used for electric vehicle application during regenerative braking process. During motoring operation, the converter supplies energy to motor through battery. In regenerative braking action, the converter supplies the available back emf to charge the battery. The recycled energy is effectively stored in the battery. The simulation is carried out in MATLAB/Simulink. The worthiness of simulation is illustrated experimentally by developing a prototype. The simulation and experimental results are presented in this paper.
Volume: 9
Issue: 4
Page: 1584-1590
Publish at: 2018-12-01

Analysing Tuberculosis Trends in South Asia

10.11591/ijece.v8i6.pp5245-5252
Kumar Abhishek , M. P Singh , Md. Sadik Hussain
Tuberculosis (TB) has been one of the top ten causes of death in the world. As per the World Health Organization (WHO) around 1.8 million people have died due to tuberculosis in 2015. This paper aims to investigate the spatial and temporal variations in TB incident in South Asia (India, Bangladesh, Pakistan, Maldives, Nepal, and Sri-Lanka). Asia had been counted for the largest number of new TB cases in 2015. The paper underlines and relates the relationship between various features like gender, age, location, occurrence, and mortality due to TB in these countries for the period 1993-2012.
Volume: 8
Issue: 6
Page: 5245-5252
Publish at: 2018-12-01

MetOp Satellites Data Processing for Air Pollution Monitoring in Morocco

10.11591/ijece.v8i6.pp4584-4592
Mohamed Akram Zaytar , Chaker El Amrani
This paper presents a data processing system based on an architecture comprised of multiple stacked layers of computational processes that transforms Raw Binary Pollution Data coming directly from Two EUMETSAT MetOp satellites to our servers, into ready to interpret and visualise continuous data stream in near real time using techniques varying from task automation, data preprocessing and data analysis to machine learning using feedforward artificial neural networks. The proposed system handles the acquisition, cleaning, processing, normalizing, and predicting of Pollution Data in our area of interest of Morocco.
Volume: 8
Issue: 6
Page: 4584-4592
Publish at: 2018-12-01

Post Event Investigation of Multi-stream Video Data Utilizing Hadoop Cluster

10.11591/ijece.v8i6.pp5089-5097
Jyoti Parsola , Durgaprasad Gangodkar , Ankush Mittal
Rapid advancement in technology and in-expensive camera has raised the necessity of monitoring systems for surveillance applications. As a result data acquired from numerous cameras deployed for surveillance is tremendous. When an event is triggered then, manually investigating such a massive data is a complex task. Thus it is essential to explore an approach that, can store massive multi-stream video data as well as, process them to find useful information. To address the challenge of storing and processing multi-stream video data, we have used Hadoop, which has grown into a leading computing model for data intensive applications. In this paper we propose a novel technique for performing post event investigation on stored surveillance video data. Our algorithm stores video data in HDFS in such a way that it efficiently identifies the location of data from HDFS based on the time of occurrence of event and perform further processing. To prove efficiency of our proposed work, we have performed event detection in the video based on the time period provided by the user. In order to estimate the performance of our approach, we evaluated the storage and processing of video data by varying (i) pixel resolution of video frame (ii) size of video data (iii) number of reducers (workers) executing the task (iv) the number of nodes in the cluster. The proposed framework efficiently achieve speed up of 5.9 for large files of 1024X1024 pixel resolution video frames thus makes it appropriate for the feasible practical deployment in any applications.
Volume: 8
Issue: 6
Page: 5089-5097
Publish at: 2018-12-01

Comparison of Z-Source EZ-Source and TZ-Source Inverter Systems for Wind Energy Conversion

10.11591/ijpeds.v9.i4.pp1693-1701
S. Bala Kumar , Samuel Kefale , Azath M
In this paper, three different impedance source inverters: Z-source inverter, EZ- source inverter, TZ-Source for wind energy conversion system (WECS) were investigated. Total output power and THD of each of these systems are calculated. The proposed system can boost the output voltage effectively when the low output voltage of the generator is available at low wind speed. This system has higher performance, less components, increased efficiency and reduced cost. These features make the proposed TZSI based system suitable for the wind conversion systems. MATLAB simulink model for wind generator system is developed and simulation studies are successfully performed. The simulation is done using MATLAB and the simulation results are presented. This comparison shows that the TZ-source inverter is very promising for wind energy conversion system.
Volume: 9
Issue: 4
Page: 1693-1701
Publish at: 2018-12-01

Elliptic Curve Cryptography Based Data Transmission against Blackhole Attack in MANET

10.11591/ijece.v8i6.pp4412-4422
Jeenat Sultana , Tasnuva Ahmed
Mobile nodes roaming around in the hostile environment of mobile adhoc network (MANET) play the role of router as well as terminal. While acting as a router, a node needs to choose a reliable routing protocol. Besides, an encryption algorithm is needed to secure data to be conveyed through the unfriendly atmosphere while acting as a terminal. We have implemented Elliptic Curve Cryptography (ECC) along with Adhoc On Demand Multipath Distance Vector (AOMDV) routing protocol to secure data transmission against blackhole attack in a MANET. ECC, a public key cryptography that works on discrete logarithm problem with a much smaller key size, has been used to encrypt data packets at source node before transmission. We have used AOMDV, a reliable routing protocol compared to its parent protocol, Adhoc On Demand Distance Vector (AODV), with a multipath extension, for routing. The encrypted packets transferring between nodes via AOMDV, has been proved secured against blackhole attack. The performance of the secured protocol has been analyzed in terms of different performance metrics and in terms of varying number of blackhole attacker nodes.
Volume: 8
Issue: 6
Page: 4412-4422
Publish at: 2018-12-01

Smart Microwave Oven with Image Classification and Temperature Recommendation Algorithm

10.11591/ijece.v8i6.pp4239-4252
Tareq Khan
When food is warmed in a microwave oven, the user guesses the estimated time for the heating. This cognitive process of guessing can be incorrect - resulting the final food temperature to be too hot or still cold. In this research, a novel closed-loop microwave oven is designed which automatically suggests the target temperature of a food by learning from previous experiences and the heating stops automatically when the food temperature reaches the target temperature. The proposed microwave captures and classifies the food image, and recommends the target temperature, thus the user does not need to remember the target food temperature each time the same food is warmed. The algorithm gradually learns the type of foods that are used in that household and becomes smarter in the recommendation. The proposed algorithm can recommend target temperature with an accuracy of 86.31% for solid food and 100% for liquid food. A prototype of the proposed microwave is developed using the embedded system and tested.
Volume: 8
Issue: 6
Page: 4239-4252
Publish at: 2018-12-01

An Analytical Approach for Design of Microstrip Patch (MsP)

10.11591/ijece.v8i6.pp4175-4183
R. J. Kavitha , H. S. Aravind
A reliable configuration of electromagnetic interactions for antenna design can yield an effective Microstrip patch (MsP) antenna. During its design, the antenna arrays involve issues with parameters (i.e., space, dimension, shape) adjustment. This problem can be tackled with an analytical approach which can help to bring better idea to design the antenna aaray. However, the realistic designs of antenna array are quite expensive while extracting computational accuracy. Thus, to have low cost computational accuracy various meta-heuristic (generic algorithm, partical swarm optimizarion) approaches are used and are considered as effective one in handling the pattern synthesis problems. Howeever, the use of meta-heuristic approaches demands thousands of functions to analyze the antenna design. This manuscript introduces an analytical approach for MsP antenna desing using MATLAB that brings optimization in handling the side lobes and optimizing the reflection as well as radiation responses. The outcomes of the design were analyzed with respect to reflection, radiation coefficients, side lobes and found effective at 10GHz as per computational cost is concern.
Volume: 8
Issue: 6
Page: 4175-4183
Publish at: 2018-12-01

Complaint Analysis in Indonesian Language Using WPKE and RAKE Algorithm

10.11591/ijece.v8i6.pp5311-5317
Rini Wongso , Novita Hanafiah , Jaka Hartanto , Alexander Kevin , Charles Sutanto , Fiona Kesuma
Social media provides convenience in communicating and can present two-way communication that allows companies to interact with their customer. Companies can use information obtained from social media to analyze how the communities respond to their services or products. The biggest challenge in processing information in social media like Twitter, is the unstructured sentences which could lead to incorrect text processing. However, this information is very important for companies’ survival. In this research, we proposed a method to extract keywords from tweets in Indonesian language, WPKE. We compared it with RAKE, an algorithm that is language independent and usually used for keyword extraction. Finally, we develop a method to do clustering to groups the topics of complaints with data set obtained from Twitter using the “komplain” hashtag. Our method can obtain the accuracy of 72.92% while RAKE can only obtain 35.42%.
Volume: 8
Issue: 6
Page: 5311-5317
Publish at: 2018-12-01

New Version of Adaptive Speed Observer based on Neural Network for SPIM

10.11591/ijpeds.v9.i4.pp1486-1502
Ngoc Thuy Pham , Diep Phu Nguyen , Khuong Huu Nguyen , Nho Van Nguyen
This paper presents a novel Stator Current based Model Reference Adaptive System (SC_MRAS) speed observer for high-performance Six Phases Induction Motor (SPIM) drives using linear neural network. The article aim is intended to improve performance of an SC_MRAS observer, which were presented in the literature. In this proposed scheme, the measured stator current components are used as the reference model of the MRAS observer to avoid the use of a pure integrator and reduce the influence of motor parameter variation. The adaptive model uses a two-layer Neural Network (NN) to estimate the stator current, which has been trained online by means of a Least Squares (LS) algorithm instead of uses a nonlinear Back Propagation Network (BPN) algorithm to reduce the complexity and computational burden, it also help to improve some disadvantages cause by the inherent nonlinearity of  the BPN algorithm as local minima, two heuristically chosen parameters, initialization, and convergence problems, paralysis of the neural network. The adaptive model of the proposed scheme is employed in prediction mode, not in simulation mode as is usually the case in the literature, this made the proposed observer operate better accuracy and stability. In the proposed observer, stator and rotor resistance values are estimated online, these values thereafter were updated for  the current observer and rotor flux identifier to enhance the accuracy, robustness and insensitivity to parameters variation for the proposed observer. The proposed LS SC_MRAS observer has been verified thought the simulation and compared with the BPN MRAS observer. The simulation results have proven that  the speed is estimated a consequent quicker convergence, do not need the estimated speed filter, lower estimation errors both in transient and steady state operation, better behavior in low and zero speed operation.
Volume: 9
Issue: 4
Page: 1486-1502
Publish at: 2018-12-01

Multi-Channel Preemptive Priority Model for Spectrum Mobility in Cognitive Radio Networks

10.11591/ijece.v8i6.pp5169-5177
S. E. Saad , I. F. Tarrad , A. A. Ammar
Cognitive Radio techniques have been proposed for improving utilization of the spectrum by exploiting the unoccupied bands of the licensed spectrum. This paper proposes a preemptive multi-channel access model for prioritized cognitive radio networks using an iterative method of queuing theory to solve the spectrum scarcity problem. The proposed model formulates accurate closed form of an expected waiting time in the queue, an expected number of users in the queue, an expected waiting time in the system, and an expected number of users in the system. The results compared to the basic model (without preemptive priority) show that, the waiting time in queue and the waiting time in the system compared to the basic model will be improved by 92.99% and 33.15% respectively for class one secondary user. The results also show that, the waiting time in queue and the waiting time in the system will be improved by 43.25% and 15.42% respectively for class two secondary users. The proposed model investigates the desirable schedules of primary and secondary users.
Volume: 8
Issue: 6
Page: 5169-5177
Publish at: 2018-12-01

A Multi-robot System Coordination Design and Analysis on Wall Follower Robot Group

10.11591/ijece.v8i6.pp5098-5106
Agung Nugroho Jati , Randy Erfa Saputra , M. Ghozy Nurcahyadi , Nasy'an Taufiq Al Ghifary
In this research, multi-robot formation can be established according to the environment or workspace. Group of robots will move sequently if there is no space for robots to stand side by side. Leader robot will be on the front of all robots and follow the right wall. On the other hand, robots will move side by side if there is a large space between them. Leader robot will be tracked the wall on its right side and follow on it while every follower moves side by side. The leader robot have to broadcast the information to all robots in the group in radius 9 meters. Nevertheless, every robot should be received information from leader robot to define their movements in the area. The error provided by fuzzy output process which is caused by read data from ultrasound sensor will drive to more time process. More sampling can reduce the error but it will drive more execution time. Furthermore, coordination time will need longer time and delay. Formation will not be establisehed if packet error happened in the communication process because robot will execute wrong command.
Volume: 8
Issue: 6
Page: 5098-5106
Publish at: 2018-12-01

Forecasting Short-term Wholesale Prices on the Irish Single Electricity Market

10.11591/ijece.v8i6.pp4060-4078
Francesco Arci , Jane Reilly , Pengfei Li , Kevin Curran , Ammar Belatreche
Electricity markets are different from other markets as electricity generation cannot be easily stored in substantial amounts and to avoid blackouts, the generation of electricity must be balanced with customer demand for it on a second-by-second basis. Customers tend to rely on electricity for day-to-day living and cannot replace it easily so when electricity prices increase, customer demand generally does not reduce significantly in the short-term. As electricity generation and customer demand must be matched perfectly second-by-second, and because generation cannot be stored to a considerable extent, cost bids from generators must be balanced with demand estimates in advance of real-time. This paper outlines a a forecasting algorithm built on artificial neural networks to predict short-term wholesale prices on the Irish Single Electricity Market so that market participants can make more informed trading decisions. Research studies have demonstrated that an adaptive or self-adaptive approach to forecasting would appear more suited to the task of predicting energy demands in territory such as Ireland. We have identified the features that such a model demands and outline it here.
Volume: 8
Issue: 6
Page: 4060-4078
Publish at: 2018-12-01

Credit Scoring Using Classification and Regression Tree (CART) Algorithm and Binary Particle Swarm Optimization

10.11591/ijece.v8i6.pp5425-5431
Reza Firsandaya Malik , Hermawan Hermawan
Credit scoring is a procedure that exists in every financial institution. A way to predict whether the debtor was qualified to be given the loan or not and has been a major concern in the overall steps of the loan process. Almost all banks and other financial institutions have their own credit scoring methods. Nowadays, data mining approach has been accepted to be one of the well-known methods. Certainly, accuracy was also a major issue in this approach. This research proposed a hybrid method using CART algorithm and Binary Particle Swarm Optimization. Performance indicators that are used in this research are classification accuracy, error rate, sensitivity, specificity, and precision. Experimental results based on the public dataset showed that the proposed method accuracy is 78 %. In compare to several popular algorithms, such as neural network, logistic regression and support vector machine, the proposed method showed an outstanding performance. 
Volume: 8
Issue: 6
Page: 5425-5431
Publish at: 2018-12-01
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