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<![CDATA[Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization Technique ]]>
<![CDATA[Muhammad Murtadha Othman]]>;
<![CDATA[Mohd Affendi Ismail Salim]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Mohammad Lutfi Othman]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i3.1278
<![CDATA[This paper presents the application of particle swarm optimization (PSO) technique for solving the dynamic economic dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation of generating units at every predicted load demands over a certain period of time. The optimum operation of generating units is obtained by referring to the minimum total generation cost while the system is operating within its limits. The DED based PSO technique is tested on a 9-bus system containing of three generator bus, six load bus and twelve transmission lines.]]>
<![CDATA[Evaluation of Support Vector Machine and Decision Tree for Emotion Recognition of Malay Folklores ]]>
<![CDATA[Mastura Md Saad]]>;
<![CDATA[Nursuriati Jamil]]>;
<![CDATA[Raseeda Hamzah]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i3.1279
<![CDATA[In this paper, the performance of Support Vector Machine (SVM) and Decision Tree (DT) in classifying emotions from Malay folklores is presented. This work is the continuation of our storytelling speech synthesis work to add emotions for a more natural storytelling. A total of 100 documents from children short stories are collected and used as the datasets of the text-based emotion recognition experiment. Term Frequency-Inverse Document Frequency (TF-IDF) is extracted from the text documents and classified using SVM and DT. Four types of common emotions, which are happy, angry, fearful and sad are classified using the two classifiers. Results showed that DT outperformed SVM by more than 22.2% accuracy rate. However, the overall emotion recognition is only at moderate rate suggesting an improvement is needed in future work. The accuracy of the emotion recognition should be improved in future studies by using semantic feature extractors or by incorporating deep learning for classification.]]>
<![CDATA[Oscillatory Stability Prediction using PSO Based Synchronizing and Damping Torque Coefficients ]]>
<![CDATA[A. M. Kamari, N.]]>;
<![CDATA[Musirin, I.]]>;
<![CDATA[A. Hamid, Z.]]>;
<![CDATA[H. M. Zaman, M.]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i3.1288
<![CDATA[This paper presents the assessment of stability domains for the angle stability condition of the power system using particle swarm optimization (PSO) technique. An efficient optimization method using PSO for synchronizing torque coefficients Ks and damping torque coefficients Kd to identify the angle stability condition on multi-machine system. In order to accelerate the determination of angle stability, particle swarm optimization (PSO) is proposed to be implemented in this study. The application of the proposed algorithm has been justified as the most accurate with lower computation time as compared to other optimization techniques such as evolutionary programming (EP) and artificial immune system (AIS). Validation with respect to eigenvalues determination, Least Square (LS) method and minimum damping ratio ξmin confirmed that the proposed technique is feasible to solve the angle stability problems.]]>
<![CDATA[Wind Energy Fed UPQC System for Power Quality Improvement ]]>
<![CDATA[Sarita Samal]]>;
<![CDATA[Prakash Kumar Hota]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i3.945
<![CDATA[The extensive use of non-linear loads in domestic, industrialand commercial services origin harmonic complications.Harmonics make malfunctions in profound equipment, voltage drop across the network, conductor heat increases and overvoltage through resonance. All these problems can be remunerated by using Unified Power Quality Controller (UPQC) and the operation of UPQC depends upon the available voltage across capacitor present in dc link. If the capacitor voltage is maintained constant then it gives satisfactory performance. The proposed research is basically on designing of Wind energy fed to the dc link capacitor of UPQCso as to maintain propervoltageacross it and operate the UPQC for power quality analysis. The proposed technique is the grouping of shunt and series Active Power Filter (APF) to form UPQC which is fed wind energy system and connected to grid for better response in the output. In this paper, the simulation model of series APF, shunt APF, UPQC and Wind energy with UPQC are design in Matlab. The proposed Wind energy-UPQC is design in Matlab simulation for reduction of voltage sag, swell, harmonics in load current and compensation of active and reactive power.]]>
<![CDATA[Development of Respiratory Rate Estimation Technique Using Electrocardiogram and Photoplethysmogram for Continuous Health Monitoring ]]>
<![CDATA[Nazrul Anuar Nayan]]>;
<![CDATA[Rosmina Jaafar]]>;
<![CDATA[Nur Sabrina Risman]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i3.1244
<![CDATA[Abnormal vital signs often predict a serious condition of acutely ill hospital patients in 24 hours. The notable fluctuations of respiratory rate (RR) are highly predictive of deteriorations among the vital signs measured. Traditional methods of detecting RR are performed by directly measuring the air flow in or out of the lungs or indirectly measuring the changes of the chest volume. These methods require the use of cumbersome devices, which may interfere with natural breathing, are uncomfortable, have frequently moving artifacts, and are extremely expensive. This study aims to estimate the RR from electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which consist of passive and non-invasive acquisition modules. Algorithms have been validated by using PhysioNet’s Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II)’s patient datasets. RR estimation provides the value of mean absolute error (MAE) for ECG as 1.25 bpm (MIMIC-II) and 1.05 bpm for the acquired data. MAE for PPG is 1.15 bpm (MIMIC-II) and 0.90 bpm for the acquired data. By using 1-minute windows, this method reveals that the filtering method efficiently extracted respiratory information from the ECG and PPG signals. Smaller MAE for PPG signals results from fewer artifacts due to easy sensor attachment for the PPG because PPG recording requires only one-finger pulse oximeter sensor placement. However, ECG recording requires at least three electrode placements at three positions on the subject’s body surface for a single lead (lead II), thereby increasing the artifacts. A reliable technique has been proposed for RR estimation.]]>
<![CDATA[Efficient Implementation of Mean, Variance and Skewness Statistic Formula for Image Processing Using FPGA Device ]]>
<![CDATA[Aqwam Rosadi Kardian]]>;
<![CDATA[Sunny Arief Sudiro]]>;
<![CDATA[Sarifuddin Madenda]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i3.687
<![CDATA[Processing statistic formula in image processing and accessing data from memory is easy in software, the other hand for hardware implementation is more dificult considering a lot of constraint. This article proposes an implementation of optimum mean, variance and skewness formula in FGPA Device. The proposed circuit design for all formulas only need three additions component (in three accumulators) and two divisions using two shift-right-registers, two subtractors, one adder and six multipliers. For 8x8 image size need 64 clock cycles to finish the mean, variance and skewness calculations, comparing other approach that need more than 1024 additions component without skewness calculation. Implementation into FPGA needs 68 slices of flip-flops and 121 of 4 input LUTs.]]>
<![CDATA[Improving Classification Accuracy Using Clustering Technique ]]>
<![CDATA[Norsyela Muhammad Noor Mathivanan]]>;
<![CDATA[Nor Azura Md.Ghani]]>;
<![CDATA[Roziah Mohd Janor]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i3.1272
<![CDATA[Product classification is the key issue in e-commerce domains. Many products are released to the market rapidly and to select the correct category in taxonomy for each product has become a challenging task. The application of classification model is useful to precisely classify the products. The study proposed a method to apply clustering prior to classification. This study has used a large-scale real-world data set to identify the efficiency of clustering technique to improve the classification model. The conventional text classification procedures are used in the study such as preprocessing, feature extraction and feature selection before applying the clustering technique. Results show that clustering technique improves the accuracy of the classification model. The best classification model for all three approaches which are classification model only, classification with hierarchical clustering and classification with K-means clustering is K-Nearest Neighbor (KNN) model. Even though the accuracy of the KNN models are the same across different approaches but the KNN model with K-means clustering had the shortest time of execution. Hence, applying K-means clustering prior to KNN model helps in reducing the computation time.]]>
<![CDATA[A Simple Way to Maintain the Top 50 Ranking Scientists in the SINTA from Excessive Self-Citations ]]>
<![CDATA[Tole Sutikno]]>;
<![CDATA[Herman Yuliansyah]]>;
<![CDATA[Lina Handayani]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i4.674
<![CDATA[Top 50 authors in the Science and Technology Index (SINTA) is become popular as Indonesian top 50 ranking scientists to measure both the productivity and quality of the publications. Unfortunately, to get a high ranking in SINTA, some authors are strongly indicated that they do instant and unfair ways through citation cartels or self-citation. Based on manual investigation, excessive self-citations are conducted through publication in international conference. This paper proposed a simple way to drop abuse of excessive self-citations by categorized research articles as main publication and others as secondary publication based on Scopus database. This method is proposed to avoid perverse and unintended effects on the direction of research and publication in Indonesia.]]>
<![CDATA[Distribution Network Reconfiguration Using Binary Particle Swarm Optimization to Minimize Losses and Decrease Voltage Stability Index ]]>
<![CDATA[Aji Akbar Firdaus]]>;
<![CDATA[Ontoseno Penangsang]]>;
<![CDATA[Adi Soeprijanto]]>;
<![CDATA[Dimas Fajar U.P.]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i4.821
<![CDATA[Power losses and voltage drop are existing problems in radial distribution networks. This power losses and voltage drop affect the voltage stability level. Reconfiguring the network is a form of approach to improve the quality of electrical power. The network reconfiguration aims to minimize power losses and voltage drop as well as decreasing the Voltage Stability Index (VSI). In this research, network reconfiguration uses binary particle swarm optimization algorithm and Bus Injection to Branch Current-Branch Current to Bus Voltage (BIBC-BCBV) method to analyze the radial system power flow. This scheme was tested on the 33-bus IEEE radial distribution system 12.66 kV. The simulation results show that before reconfiguration, the active power loss is 202.7126 kW and the VSI is 0.20012. After reconfiguration, the active power loss and VSI decreased to 139.5697 kW and 0.14662, respectively. It has decreased the power loss for 31.3136% significantly while the VSI value is closer to zero.]]>
<![CDATA[Features for Cross Spectral Image Matching: A Survey ]]>
<![CDATA[Maulisa Oktiana]]>;
<![CDATA[Fitri Arnia]]>;
<![CDATA[Yuwaldi Away]]>;
<![CDATA[Khairul Munadi]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v7i4.843
<![CDATA[In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching.]]>
