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31,456 Article Results

Automatic segmentation of ceramic materials with relaxed possibilistic C-Means clustering for defect detection

10.11591/ijeecs.v19.i3.pp1505-1511
Kwang Baek Kim , Doo Heon Song , Hyun Jun Park
Auromatic inspection system is necessary for reliable quality control if ceramic materials to avoid operator subjectivity and fatigue in visual inspection. Automatic segmentation from material’s image is then the most important process to develop such an inspection system. In this paper, we propose a Possibilistic C-Means pixel clustering algorithm with fuzzy stretching to form the defect object in segmentation. In experiment using 50 images containing a certain amount of defects, the proposed method was successful in 49 cases or 98% of opportunities. That performance is roughly twice better than that of standard K-means clustering in defect object formation Auromatic inspection system is necessary for reliable quality control if ceramic materials to avoid operator subjectivity and fatigue in visual inspection. Automatic segmentation from material’s image is then the most important process to develop such an inspection system. In this paper, we propose a Possibilistic C-Means pixel clustering algorithm with fuzzy stretching to form the defect object in segmentation. In experiment using 50 images containing a certain amount of defects, the proposed method was successful in 49 cases or 98% of opportunities. That performance is roughly twice better than that of standard K-means clustering in defect object formation.
Volume: 19
Issue: 3
Page: 1505-1511
Publish at: 2020-09-01

Quality and texture analysis of biometric images compressed with second-generation wavelet transforms and SPIHT-Z encoder

10.11591/ijeecs.v19.i3.pp1325-1339
Ahmed Bouida , Mohammed Beladgham , Abdesselam Bassou , Ismahane Benyahia
In biometric systems, compression takes important place especially in order to reduce the size of the information stored or transmitted through the distributed biometric systems. It is also noted that the compression techniques induce loss of information in the compressed images that can affect the effectiveness of biometric systems. The main objective of our contribution is to examine the efficacy of the used method to offer an optimal compression quality in these kind of images without considerable distortion. In order to evaluate the efficacy of the compression process, we use two kinds of evaluation, full-reference image quality assessment and a new proposed textural quality analysis of the compressed images. In this paper, we use a second-generation wavelet transform to improve the compression study in biometric images. The basic idea of this algorithm is the quincunx wavelet transform coupled to a modified progressive encoder called SPIHT-Z encoding.
Volume: 19
Issue: 3
Page: 1325-1339
Publish at: 2020-09-01

Systematic review on event prediction models

10.11591/ijeecs.v19.i3.pp1490-1496
Fakhruzy Shakirin Jamaludin , R Kanesaraj Ramasamy
Predicting an event can comes as a huge advantage for a lot of people, especially if it involves profits that a company can make. In this paper, matters that were discussed were the algorithms used for the event prediction systems, the type of algorithms and the comparison between different types of algorithm. Two main categories that were compared was the single algorithm for the prediction model and hybrid algorithms which is a combination of two or more algorithms in the model. Hybrid algorithm shows signs of better efficiency when data used were complex and large but a smaller dataset is more suitable with a single algorithm as the base as it is easier to apply with satisfactory results.
Volume: 19
Issue: 3
Page: 1490-1496
Publish at: 2020-09-01

Comparison of CNNs and SVM for voice control wheelchair

10.11591/ijai.v9.i3.pp387-393
Mohammad Shahrul Izham Sharifuddin , Sharifalillah Nordin , Azliza Mohd Ali
In this paper, we develop an intelligent wheelchair using CNNs and SVM voice recognition methods. The data is collected from Google and some of them are self-recorded. There are four types of data to be recognized which are go, left, right, and stop. Voice data are extracted using MFCC feature extraction technique. CNNs and SVM are then used to classify and recognize the voice data. The motor driver is embedded in Raspberry PI 3B+  to control the movement of the wheelchair prototype. CNNs produced higher accuracy i.e. 95.30% compared to SVM which is only 72.39%. On the other hand, SVM only took 8.21 seconds while CNNs took 250.03 seconds to execute. Therefore, CNNs produce better result because noise are filtered in the feature extraction layer before classified in the classification layer. However, CNNs took longer time due to the complexity of the networks and the less complexity implementation in SVM give shorter processing time.
Volume: 9
Issue: 3
Page: 387-393
Publish at: 2020-09-01

Lighting control network based on KNX protocol, for the reduction of energy consumption

10.11591/ijeecs.v19.i3.pp1186-1193
Omar Chamorro Atalaya , Angel Quesquen-Porras , Dora Arce Santillan
This article presents the development of a lighting control network to reduce the energy consumption of a commercial building, using the KNX protocol; because of the high rates of electricity consumption, the same that are reflected in the payment of the electricity supply. For this, the design of the network architecture is carried out, the tree type quality and it has KNX, DALI components and LED luminaires, which are interconnected by means of an Ethernet type BUS; The KNX protocol configuration is then performed using the ETS version 5 software; carries out the implementation of KNX technology, determines the reduction of energy consumption by 82.33%. Likewise, emissions of carbon dioxide (CO2), one of the main gases involved in climate change, were reduced by 85%. With these results we obtain economic and environmental benefits; Reason why it is proposed to perform the same procedure for the control of air conditioning systems, since their operation represents 32.8% of the energy consumption of an establishment.
Volume: 19
Issue: 3
Page: 1186-1193
Publish at: 2020-09-01

Modelling of time-to collision for unmanned aerial vehicle using particles swarm optimization

10.11591/ijai.v9.i3.pp488-496
Sulaiman bin Sabikan , Nawawi. S. W , NAA Aziz
A method for the development of Time-to-Collision (TTC) mathematical model for outdoor Unmanned Aerial Vehicle (UAV) using Particles Swarm Optimization (PSO), are presented. TTC is the time required for a UAV either to collide with any static obstacle or completely stop without applying any braking control system when the throttle is fully released. This model provides predictions of time before UAV will collide with the obstacle in the same path based on their parameter, for instance, current speed and payload. However, this paper focus on the methodology of the implementation of PSO to develop the TTC model for 5 different set of payloads. This work utilizes a quadcopter as our testbed system, that equipped with a Global Positioning System (GPS) receiver unit, a flight controller with data recording capability and ground control station for real-time monitoring. The recorded onboard flight mission data for 5 different set of payloads has been analyzed to develop a mathematical model of TTC through the PSO approach. The horizontal ground speed, throttle magnitudes and flight time stamp are extracted from the on-board quadcopter flight mission. PSO algorithm is used to find the optimal linear TTC model function, while the mean square error is used to evaluate the best fitness of the solution. The results of the TTC mathematical model for each payload are described.
Volume: 9
Issue: 3
Page: 488-496
Publish at: 2020-09-01

Performance comparison of field oriented control based permanent magnet synchronous motor fed by matrix converter using PI and IP speed controllers

10.11591/ijeecs.v19.i3.pp1156-1168
Mohamed Bouazdia , Mohamed Bouhamida , Rachid Taleb , Mouloud Denai
This paper focuses on modeling and closed-loop speed control of a three-phase Permanent Magnet Synchronous Motor (PMSM) fed by a Matrix Converter (MC) based on Field-Oriented Control (FOC). The model considers a set of a small input filter with supply impedance or cable effect, to improve the quality of the input current. A simplified form of the Venturini modulation algorithm is used for switching the matrix converter and a comparative study of two types of speed controllers is presented, namely a proportional integral (PI) and a proportional integral (PI) to improve performances of the drive system in transient and stable conditions. The overall drive system is simulated using Matlab/Simulink environment. The motor performance is evaluated under different operating conditions such as sudden changes in the load or changes in the angular speed reference. The results of the converter MC gives unlimited output frequency, sinusoidal input current and output voltage waveforms and unity input displacement factor. The IP controller is shown to achieve better performance of the speed control loop, with or without the load torque as compared to the PI classic controller.
Volume: 19
Issue: 3
Page: 1156-1168
Publish at: 2020-09-01

IoT blood pressure monitoring system

10.11591/ijeecs.v19.i3.pp1384-1390
Norlezah Hashim , Nurbahirah Norddin , Fakrulradzi Idris , Siti Nur Ilmani Mohd Yusoff , Madiha Zahari
The number of patients in hospital keep increasing every year and, some patients’s blood pressure must be measured by medical staff regularly. This means that the medical staff need to attend to the patient routinely and several readings are required in each session to make sure the results are accurate. Therefore, there is a need to simplify the monitoring process inside hospital in Malaysia. In this work, IoT blood pressure monitoring system (IBPMS) is designed to monitor patient’s blood pressure remotely. This project use Raspberry Pi as a gateway to view the value of blood pressure online. Result showed that the design is capable to transfer data from blood pressure detector through the network using USB TTL serial cable which is directly attached to the Raspberry Pi. User can also view the blood pressure reading continuously from Telegram application and email service. Furthermore, the system can measure the value of blood pressure accurately when user is in sitting position.
Volume: 19
Issue: 3
Page: 1384-1390
Publish at: 2020-09-01

Design of a contactless body temperature measurement system using Arduino

10.11591/ijeecs.v19.i3.pp1251-1258
Asif A. Rahimoon , Mohd Noor Abdullah , Ishkrizat Taib
The recent advances in electronics and microelectronics devices allow the development of newly low-cost monitoring tools used by peoples for health preventive purposes. Sensors used in medical equipments convert various forms of human body vital signs into electrical signals. Therefore, the healthcare monitoring systems considering non-invasive and wearable sensors with integrated communication mediums allow an efficient solution to live a comfortable home life.  This paper presents the remote monitoring of human body temperature (HBT) wirelessly by means of Arduino controller with different sensors and open source internet connection. The proposed monitoring system uses an internet network via wireless fieldity (wifi) connection to be linked with online portal on smart phone or computer. The proposed system is comprised of an Arduino controller, LM-35 (S1), MLX-90614 (S2) temperature sensors and ESP-wifi shield module. The obtained result has shown that real time temperature monitoring data can be transferred to authentic observer by utilizing internet of things (IoT) applications. The findings from this research indicates that the difference of average temperature in between Sensor S1 and S2 is about 15 0C
Volume: 19
Issue: 3
Page: 1251-1258
Publish at: 2020-09-01

Differential evolution algorithm of soft island model based on K-means clustering

10.11591/ijeecs.v19.i3.pp1548-1555
Xujie Tan , Seong-Yoon Shin
Differential evolution (DE) is a highly effective evolutionary algorithm. However, the performance of DE depends on strategies and control parameters. The combination of many strategies helps balance the exploitation and exploration of DE. In this study, a multi-population based on k-means clustering is proposed to realize an ensemble of multiple strategies, thereby resulting in a new DE variant, namely KSDE, where similar individuals in the population implement the same mutation strategies, and dissimilar subpopulations migrate information through the soft island model (SIM). Firstly, the population is virtually divided into k subpopulations by the k-means clustering algorithm. Secondly, the individual specific mutation scheme is selected from a strategy pool by random method. Finally, the migration of subpopulation information is done using soft island model. The performance of the KSDE algorithm is evaluated on 13 benchmark problems. The experiments show that KSDE algorithm improves the performance of the DE algorithm.
Volume: 19
Issue: 3
Page: 1548-1555
Publish at: 2020-09-01

Investigation of voltage regulation in grid–connected PV system

10.11591/ijeecs.v19.i3.pp1131-1139
Soumen Gorai , Sattianadan D , V. Shanmugasundaram , S. Vidyasagar , G. R. Prudhvi Kumar , M. Sudhakaran
In the present scenario the power demand on the load side is increasing day by day, so to balance the power demand and power supply various renewable energy comes to picture as the additional source of electricity generation. The power generated by various renewable resources such as solar, wind, tidal energy and geothermal sources is environmentally clean and have a less emission impact. Out of which PV system draws more attention because it generates energy with a much lower level of carbon dioxide emissions. In the proposed work the objective is to investigate the synchronisation of the grid-connected PV system in terms of voltage and frequency. It includes the P-V characteristics under the circumstances of MPPT technique such as perturb & observe (P&O) method can able to track the local maximum point. The proposed inverter is a voltage source H-Bridge inverter which is controlled using a Clarke and Park transformation to drive a controlled current into the grid to maintain the THD value within the standards. As the grid frequency is fluctuating between SRF-PLL is generally used to fix the output frequency and phase of the grid. It also includes with the design of a three-phase H-bridge inverter as an interface between PV system and grid system. The proposed work is designed and simulated in MATLAB SIMULINK 2017b environment.
Volume: 19
Issue: 3
Page: 1131-1139
Publish at: 2020-09-01

Coaxial treatment chamber for liquid food treatment through pulsed electric field

10.11591/ijeecs.v19.i3.pp1169-1176
Rai Naveed Arshad , Zulkurnain Abdul Malek , Mohd. Hafizi Ahmad , Zolkafle Buntat , C L G Pavan Kumara , Asaad Zuhair Abdulameer
Over the last couple of decades, pulsed electric field (PEF) attained substantial consideration in the food industry with an effort to generate replacements to conventional thermal treatment. It is recognised to produce secure and chill-stable liquid food samples with fresh and nutritional qualities. The uniform electric field in the treatment zone has been recognised as the main handling parameter. The design of the treatment chamber shows an essential impact on the effectiveness of the procedure by controlling homogenous treatment. This study revealed the homogeneity of the electric field strength of the different existing treatment chambers through COMSOL Multiphysics. It adopted a study to design a co-axial treatment chamber for continuous treatment of liquid samples. This research helps to take some fundamental designing steps for a new treatment chamber with a uniform distribution of the electric field.
Volume: 19
Issue: 3
Page: 1169-1176
Publish at: 2020-09-01

A self-rectifying memristor model for simulation and ReRAM applications

10.11591/ijeecs.v19.i3.pp1204-1209
Sinan Sabah , Nasri Bin Sulaiman
In this paper, a self-rectifying memristor (SRM) model is proposed for memristive circuit simulations. This model is based on the behavior of voltage controlled, bipolar memristors that exhibit diode-like rectification behavior when reverse biased. Such unique feature can solve the sneak path problem in crossbar memristive memory structures without requiring additional cell selectors. The results show that the proposed model satisfies the basic memristor’s i-v characteristics and fits many different memristor devices adequately. The proposed model is implemented in Verilog-A so that it is conveniently incorporated into various memristor applications with different circuit simulators
Volume: 19
Issue: 3
Page: 1204-1209
Publish at: 2020-09-01

Increasing the efficiency of information transmission in communication channels

10.11591/ijeecs.v19.i3.pp1306-1315
Bohdan Zhurakovskyi , Juliy Boiko , Vladymir Druzhynin , Irina Zeniv , Oleksander Eromenko
This paper discusses compression methods focused on data transmission over communication channels. The characteristics of different algorithms for different types of incoming data are analyzed. The purpose of this study is to evaluate the speed of operation of each of the compression algorithms for different types of information and different compression parameters, on the basis of the obtained results to make recommendations for the application of compression methods in systems critical to the performance of the algorithm. Based on the results of the analysis, the methods of compression that can be used in communication channels are selected: LZW, LZH, Vitter and matrix. The practical research of the selected methods on different information flows (text, graphics, measurement data, combined data) was carried out, their comparative analysis was performed. Research has highlighted compression methods that give the most optimal results in each case. Comparative evaluation of algorithms for different parameters is made, the possibility of data compression implementation in systems running in real time is analyzed. Based on the results of the study, recommendations are made for the application of particular compression methods in specific conditions.
Volume: 19
Issue: 3
Page: 1306-1315
Publish at: 2020-09-01

Dynamic spectrum access using markov chain technique for regional area network

10.11591/ijeecs.v19.i3.pp1420-1427
Jayant P Pawar , Prashant V. Ingole
Cognitive Radio Network is the effective solution to the spectrum scarcity.  Dynamic spectrum access is a paradigm used to access the spectrum dynamically. A Markov Chain is a stochastic model describing a sequence of possible events in which probability of each event depends only on the state attained in the previous event. We model the dynamics of cognitive user with 2-D Markov chain. The resource distribution probability (RDP) verses addition/ elimination rate of the channels in the network is also plotted. The RDP verses utilization factor of the queue, which is the secondary user in the network, is also plotted. This plot helps to maintain the total arrival and departure rate based on the RDP. The base station of the network will use this relation to maintain the proper RDP for the devices. The dynamics of each cognitive user and its correlation with Markov Chain is an interesting approach. Here we considered the DSA at Base Station as a Markov chain and analyzed it. This analysis helps us to determine the behavior of the cognitive radio and also helps to find the fault in the cognitive devices. 
Volume: 19
Issue: 3
Page: 1420-1427
Publish at: 2020-09-01
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