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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 65 Documents
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Search results for , issue "Vol 18, No 1: April 2020" : 65 Documents clear
Detection and recognition of brain tumor based on DWT, PCA and ANN Nidhal Khdhair El abbadi; Zahraa Faisal Shoman
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp56-63

Abstract

Brain tumor is one of more dangerous diesis that affected more than 100 persons every day. The challenge is how to detect and recognise benign and malignant tumor without surgery. In this paper, initially, brain images are filtered to remove unwanted particles, then a new method for automatic segmentation of lesion area is carried out based on mean and standard deviation. Combining both solidity property and morphological operation used to detect only the tumor from segmented image. Mathematical morphology such as close used to join narrow breaks regions in an object, fill the small holes and remove small objects. Features extracted from image by using wavelet transform, followed by applying principle component analysis (PCA) to reduce the dimensions of features. Classification of tumor based on neural network, where the inputs to the network are thirteen statistical features and textural features. The algorithm is trained with 20 of brain MRI images and tested with 45 brain MRI images. Accuracy for this method was encourage and reach near 100% in identifying normal and abnormal tissues from MRI images.
Diacritic segmentation technique for arabic handwritten using region-based Ahmed Abdalla Shiekh; Mohd Sanusi Azmi; Maslita Abd Aziz; Mohammed Nasser Al-Mhiqani; Salem Saleh Bafjaish
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp478-484

Abstract

Arabic is a broadly utilized alphabetic composition framework on the planet, and it has 28 essential letters. The letters in order was first used to compose messages in Arabic, most prominently the Qur'an the holy book of Islam. However, Arabic language has diacritics in the word or letters which are not something extra or discretionary to the language, rather they are a vital piece of it. By changing some diacritics may change both the syntax and semantics of a word by turning a word into another. However, the current researches address the foreground image and consider the diacritics as noises or secondary images. Thus, it is not suitable for Arabic handwritten. The diacritics will be removed from the image and this will lead to losing some good features.   Furthermore, to extract the diacritics, the region-based segmentation technique is used. The image will be measured based on the region properties by first finding the connected component in binary image, and then we will determine the best area range measurement in that region for each image. The proposed technique region based has been tested in nine different images with different handwritten style, and successfully extracted secondary foreground images (diacritics) for each image.
Clustering optimization in RFM analysis Based on k-Means Rendra Gustriansyah; Nazori Suhandi; Fery Antony
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp470-477

Abstract

RFM stands for Recency, Frequency, and Monetary. RFM is a simple but effective method that can be applied to market segmentation. RFM analysis is used to analyze customer’s behavior which consists of how recently the customers have purchased (recency), how often customer’s purchases (frequency), and how much money customers spend (monetary). In this study, RFM analysis has been used for product segmentation is to be arrayed in terms of recent sales (R), frequent sales (F), and the total money spent (M) using the data mining method. This study has proposed a new procedure for RFM analysis (in product segmentation) using the k-Means method and eight indexes of validity to determine the optimal number of clusters namely Elbow Method, Silhouette Index, Calinski-Harabasz Index, Davies-Bouldin Index, Ratkowski Index, Hubert Index, Ball-Hall Index, and Krzanowski-Lai Index, which can improve the objectivity and similarity of data in product segmentation so that it can improve the accuracy of the stock management process. The evaluation results showed that the optimal number of clusters for the k-Means method applied in the RFM analysis consists of three clusters (segmentation) with a variance value of 0.19113.
An edge detection mechanism using L*A*B color-based contrast enhancement for underwater images M Sudhakara; M Janaki Meena
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp41-48

Abstract

In Ocean investigations, particularly those deployed by the Autonomous Underwater Vehicles, underwater object detection and recognition is an essential task. Edge detection places a key role and considered one of the pre-processing techniques for several deep learning applications. In an underwater environment, the illumination of light, turbulence in the water, suspended particles present in the seafloor are challenging issues to acquire the quality image. The two major problems in underwater imaging are light scattering and color change. In the former case, the vision sensors connected to the underwater vehicles or dive lights used by the divers themselves cause light dispersion and shadows in the seafloor. In the latter case, the occurrence of color distortion is mainly due to the attenuation of the light, hence the images are having dominant colors in the latter case. The conventional techniques are failed to detect the quality edges in the case of underwater images. Our mechanism focused, instead of applying the edge detection algorithm on the input image directly, it is better to apply edge detection algorithm after color correction and contrast enhancement using L*A*B model. Qualitative and quantitative test results demonstrate that the proposed mechanism is giving better results compared with state-of-the-art methods.
Simulation and analysis of improved direct torque control of switched reluctance machine Alexander Krasovsky
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp251-260

Abstract

Direct torque control of electric machines widely used in modern electric drives. Switched reluctance machines (SRM) are different from traditional electric machines, so we cannot apply well-known technical solutions to them. Simulation can provide a powerful approach for investigating the control of switched reluctance machines, and Matlab / Simulink allows it successfully implemented. This paper presents a description of the model and the simulation results of the proposed new algorithms for direct control of the instantaneous torque of SRM in the motor and braking modes. In comparison with the known control algorithms, the proposed algorithm uses one common for all phases relay regulator with a smaller number of switching thresholds and, therefore, it has greater reliability and is easier to set up. 
Investigation of monthly variations in the efficiencies of photovoltaics due to sunrise and sunset times Armstrong O. Njok; Julie C. Ogbulezie; Manoj Kumar Panjwani; Raja Masood Larik
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp310-317

Abstract

The effect of time of day and month on the efficient conversion of solar energy to electrical energy using a polycrystalline (PV) module in calabar was studied. A KT-908 precision digital hygrometer and thermometer, and a M890C+ digital multimeter were used in the process. Results obtained shows that photovoltaic produce different levels of peak efficiencies at different times of the day for different months due to the difference in sunrise and sunset times for the months. The results also indicated that photovoltaics will be more efficient in months with low average relative humidity couple with low panel temperature. A peak efficiency of 77% at 12:30 in the month of April was observed before dropping to 73% at 12:00 in the month of May, indicating that there might be further drop in efficiency as we proceed further into the year. Results also show that photovoltaics are more efficient before noon in the month of May than in April while the reverse will be observed in the afternoon. 
Noncontact monitoring of heart rate responses to taste stimuli using a video camera Masnani Bt Mohamed; Makoto Yoshizawa; Norihiro Sugita; Shunsuke Yamaki; Kei Ichiji
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp293-300

Abstract

Pleasant or unpleasant feeling stimulated by taste usually expressed to describe the acceptance or rejection of food and beverages intake by a human. Since it stimulates the emotional reactions, therefore it also induces other response such as heart rate variations. Traditional sensory tools used only subjective measurement such as self-report, to estimate the feeling of tasting. This method sometimes failed to show some differences between the pleasant and unpleasant type of feelings unconsciously. Previous unconscious measurement methods used the intrusive technique by placing some sensors in contact with the body, which may affect the results of sensory analysis. This study was conducted to avoid the effects of using contact sensors and validate the contact-less method of monitoring heart rate due to emotional changes by extracting plethysmographic signal from the green component of the video images. The videos were recorded while the subject responded to pleasant, unpleasant and neutral stimuli. The findings indicated that the heart rate was significantly related to taste stimuli that also reflected the subjective feelings. The unpleasant-taste influenced heart rate to increase more compared to pleasant-taste and neutral-taste. This proposed approach can be used to remotely detect the feeling/emotion that not overtly express through facial expression, speech or gestures.
Grey wolf optimizer based fuzzy-PI active queue management design for network congestion avoidance Sana Sabah Sabry; Nada Mahdi Kaittan
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp199-208

Abstract

Congestion is one of the most important issues in communication networks which has attracted much research attention. To ensure a stable TCP network, we can use active queue management (AQM for early congestion detection and router queue length regulation. In this study, it was proposed to use the Grey Wolf Optimizer (GWO) algorithm in designing a fuzzy proportional integral (fuzzy-PI) controller as a novel AQM for internet routers congestion control and for achieving a low steady-state error and fast response. The suggested Fuzzy logic-based network traffic control strategy permit us to deploy linguistic knowledge for depicting the dynamics of probability marking functions and ensures a more accurate use of multiple inputs to depict the   the network’s state. The possibility of incorporating human knowledge into such a control strategy using Fuzzy logic control methodology was demonstrated. The postulated controller was compared to proportion integral (PI) through several MATLAB simulation scenarios. The results indicated the stability of the postulated controller and its ability to attain a faster response in a dynamic network with varying network load and target queue length.
Modification of speed and current limiting performance of BLDC motor based on harmony search optimization method Mohammed Qasim Abbas; Yaser Atta Yassin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp549-557

Abstract

The brushless DC (BLDC) motor is a multi-variable and non-linear system so that it's required more advanced explaining and controlling set. In this work, an algorithm is proposed based on the harmony search algorithm (HAS) method. HSA mimics music improvisation process to find the optimal solution. In BLDC motor, many constraints are required; speed performance and current limiting control are dominated. HAS is proposed to find the optimal PID parameters for the two speed and current-limiting controllers that are proposed in the drive. By Matlab/Simulink results, a good performance is shown compared with the classical method that absence current-limiting controller.
The performance of Gauss Markov’s mobility model in emulated software defined wireless mesh network Tsehay Admassu Assegie; Pramod Sekharan Nair
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp428-433

Abstract

Wireless mesh networks (WMNs) are a new trend in wireless communication promising greater flexibility, reliability, and performance over traditional wireless local area networks (WLANs).Test bed analysis and emulation plays an important role in evaluation of wireless networks and node mobility is the prominent feature of next generation wireless network. In this paper we will focus on the models of wireless station mobility and discuss their importance within the software defined wireless mesh network performance evaluation. The existing mobility models for the next generation software defined wireless network will be explored. Finlay, we will present the mobility models in the mininet-Wi-Fi test bed, and evaluate the performance of the models

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