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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Towards better performance: phase congruency based face recognition </text>
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                <text>Phase congruency is an edge detector and measurement of the significant feature in the image. It is a robust method against contrast and illumination variation. In this paper, two novel techniques are introduced for developing a low-cost human identification system based on face recognition. Firstly, the valuable phase congruency features, the gradient-edges and their associated angles are utilized separately for classifying 130 subjects taken from three face databases with the motivation of eliminating the feature extraction phase. By doing this, the complexity can be significantly reduced. Secondly, the training process is modified when a new technique, called averaging-vectors is developed to accelerate the training process and minimizes the matching time to the lowest value. However, for more comparison and accurate  valuation,&#13;
three competitive classifiers: Euclidean distance (ED), cosine distance (CD), and Manhattan distance (MD) are considered in this work. The system performance is very competitive and acceptable, where the experimental results show promising recognition rates with a reasonable matching time. </text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i6.17300</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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Authentication system for e-certificate by using RSA’s digital signature</text>
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                <text>Online learning and teaching become the popular channel for all participants, because they can access the courses everywhere with the high-speed internet. E-certificate is being prepared for everyone who has participated or passed the requirements of the courses. Because of many benefits from e-certificate, it may become the demand for intruders to counterfeit the certificate. In this paper, Rivest-Shamir-Adleman (RSA)’s digital signature is chosen to sign e-certificate in order&#13;
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                <text>Kritsanapong Somsuk, Mongkhon Thakong</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i6.17278</text>
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                <text>Sri Wahyuni</text>
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Co-simulation of self-adjusting fuzzy PI controller for the robot with two-axes system </text>
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                <text>FPGA, Fuzzy PI controller, Radial basis function neural network, Simulation, XY-axis</text>
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                <text>This paper presents the co-simulation of the self-adjusting fuzzy PI controller to control a two-axes system. Each axis was driven by a permanent magnet linear synchronous motor (PMLSM). The position and speed controller used the fuzzy PI algorithm with parameters adjusted by a radial basis function neural network (RBFNN). The vector control was applied to the decoupled effect of the PMLSM. The field programmable gate array (FPGA) was used to control both axes of the system. The very high-speed integrated circuit-hardware description language (VHDL) was developed in the Quartus II software environment, provided by Altera, to analyze and synthesize designs. Firstly, the mathematical model of PMLSM and fuzzy PI was introduced. Secondly, the RBFNN adjusted the knowledge base of the fuzzy PI. Thirdly, the motion trajectory was introduced for testing the control algorithm. Fourthly, the implementation of the controller based on FPGA with the FSM method and the structure of co-simulation between Matlab/Simulink and ModelSim were set up. Finally, discussion about the results proved the effectiveness of the control system, determining the exact position and trajectory of the XY axis system. This research was successful in implementing a two-motor controller within one chip. </text>
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                <text>Nguyen Vu Quynh, Pham Van Toan</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i1.17277</text>
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A robust maximum power point tracking control for PV panel using adaptive PI controller based on fuzzy logic </text>
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                <text>Most methods of maximum power point tracking (MPPT) for photovoltaic (PV) focus only on tracking performance while robustness against disturbances has rarely been addressed. This paper proposes a new MPPT control method that provides robustness against direct current (DC) link voltage disturbance as well as good tracking performance. The method uses indirect MPPT control topology which incorporates two controllers. For the external controller, we use an adaptive proportional-integral (PI) control which is real-time tuned by fuzzy logic (FL). New membership functions and rule base are proposed using only one fuzzy input variable and 10 fuzzy rules. The internal controller is a PI controller. The PV panel is connected to a boost DC-DC converter. The proposed MPPT control is compared with the fuzzy logic controller (FLC). Performance is evaluated under DC link voltage disturbance, steady-state condition, and rapid solar radiation changes. Simulation results indicate that the proposed method provides 41.2 %&#13;
better robustness against DC link voltage disturbance as compared to the direct FLC. Experimental results under natural climate conditions with real solar radiation validate that the proposed method works well in regulating the MPP at steady-state solar irradiance as well as in tracking the MPP towards rapid solar irradiance changes. It yields the PV power tracking speed of 95.75 W/s. </text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i6.17271</text>
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Offline signatures matching using haar wavelet subbands</text>
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                <text>The complexity of multimedia contents is significantly increasing in the current world. This leads to an exigent demand for developing highly effective systems to satisfy human needs. Until today, handwritten signature considered an important means that is used in banks and businesses to evidence identity, so there are many works tried to develop a method for recognition purpose. This paper introduced an&#13;
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performance in signature recognition. </text>
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                <text>Zinah S. Abduljabbar, Zainab J. Ahmed, Noor Khalid Ibrahim</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i6.17069</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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                  <text>VOL. 18, NO. 6 2020</text>
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A beamforming comparative study of least mean square, genetic algorithm and grey wolf optimization algorithms for multipath smart antenna system </text>
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                <text>Multipath environment is a limitation fact in optimized usage of wireless networks. Using smart antenna and beamforming algorithms contributed to that subscribers get a higher-gain signal and better directivity as well as reduce the consumed power for users and the mobile base stations by adjusting the appropriate weights for each element in the antenna array that leads to reducing interference and directing the main beam to wanted user. In this paper, the performance of three of beamforming algorithms in multipath environment in terms of Directivity and side lobe level reduction has been studied and compared, which are least mean square (LMS), genetic algorithm (GA) and grey wolf optimization (GWO) technique. The simulation result appears that LMS algorithm aids us to get the best directivity followed by the GWO, and we may get most sidelobe level reduction by using the GA algorithm, followed by LMS algorithm in second rank. </text>
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                <text>Asma Issa Mohsin, Asaad. S. Daghal, Adheed Hasan Sallomi</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i6.16970</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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                  <text>VOL. 18, NO. 6 2020</text>
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Average dynamical frequency behaviour for multi-area islanded micro-grid networks</text>
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                <text>Distributed generator, Frequency responses, Islanded micro-grid, State-space representation, Two area networks</text>
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                <text>A micro-grid is a part of power system which able to operates in grid or&#13;
islanding mode. The most important variable that able to give us information about the stability in islanded micro-grid network is the frequency dynamical responses. The frequency analysis for multi-area micro-grid network model may involve a complicated of mathematical equations. This makes the researcher intending to omit several unnecessary parameters in  order to simplify the equations. The purpose of this paper is to show an approach to derive the mathematical equations to represent the average behavior of frequency dynamical responses for two different micro-grid areas. Both of networks are assumed to have non-identical distributed generator behavior with different parameters. The prime mover and speed governor systems are&#13;
augmented with the general swing equation. The tie line model and the information of rotor angle was considered. Then, in the last section, the comparison between this technique with the conventional approach using centre of inertia (COI) technique was defined. </text>
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                <text>M. Saifuzam Jamri, Muhammad Nizam Kamarudin, Mohd Luqman Mohd Jamil</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i6.16805</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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Recognizing emotional state of user based on learning method and conceptual memories</text>
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accordance with the positive and negative experiences of users with different personalities. The end result of comparison of the testing methods demonstrated the superiority of memory-based learning in all three parameters of emotional control, enhancement of positive emotional states and reduction of negative emotional states. Moreover,</text>
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                <text>Sri Wahyuni</text>
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Harnessing deep learning algorithms to predict software refactoring</text>
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                <text>During software maintenance, software systems need to be modified by adding or modifying source code. These changes are required to fix errors or adopt new requirements raised by stakeholders or market place. Identifying the targeted piece of code for refactoring purposes is considered a real challenge for software developers. The whole process of refactoring mainly relies on software developers’ skills and intuition. In this paper, a deep learning algorithm is used to develop a refactoring prediction model for highlighting the classes that require refactoring. More specifically, the gated recurrent unit algorithm is used with proposed pre-processing steps for refactoring prediction at the class level. The effectiveness of the proposed model is evaluated using a very common dataset of 7 open source java projects. The experiments are&#13;
conducted before and after balancing the dataset to investigate the influence of data sampling on the performance of the prediction model. The experimental analysis reveals a promising result in the field of code refactoring prediction. </text>
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                <text>Mamdouh Alenezi, Mohammed Akour, Osama Al Qasem</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i6.16743</text>
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Modelling of solar micro gas turbine for parabolic dish based controller application </text>
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                <text>Dish-Stirling unit and photovoltaic panels are the premier technologies available to generate off-grid solar energy. The major issue for both systems is in terms of producing output power. Air-Brayton cycle was utilized as an engine by converting the thermal energy to electricity. Micro gas turbine (MGT) has been recognized as one of the viable alternatives compared to Stirling engines, where it represents a state-of-art parabolic dish engine specifically in turbine gas technology. Hence, the micro gas turbine is a technology that is capable of controlling low carbon while providing electricity in off-grid regions. MGT uses any gas as its input like natural gas, biogas and others. Micro gas turbine has&#13;
advantages for its high expansion ratio and less moving components. Compared to competing for diesel generators, the electricity costs from hybrid solar units were reduced between 10% and 43%, whereas specific CO2 emissions reduced by 20-35%. MGT provides advantages over photovoltaic systems such as the inherent ability to hybridize the systems with hydrocarbon fuels to produce electricity around the clock, and the ability to operate more effectively in very hot climates with photovoltaic performance degradation over the lifetime of the system. Hybrid solar micro gas-turbines are cost-effective, eco-friendly and&#13;
pollution free as they can work by burning any gas like natural gas, landfill gas and others. This paper presented the controls contained in the MGT-dish system consisted of temperature control, fuel flow control, speed and acceleration control. A conceptual design of the 25kW MGT-dish system was also covered. </text>
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                <text>Syariffah Othman, Mohd Ruddin Ab. Ghani, Zanariah Jano, Tole Sutikno</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v18i6.16676</text>
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                <text>Sri Wahyuni</text>
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