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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 64 Documents
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Search results for , issue "Vol 25, No 3: March 2022" : 64 Documents clear
The harmonic reduction techniques in shunt active power filter when integrated with non-conventional energy sources Rao, Kambhampati Venkata Govardhan; Kumar, Malligunta Kiran
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1236-1245

Abstract

The article covers the control techniques of shunt active filters using switching devices using artificial neural network (ANN) Theory. The basic idea is to achieve perfect disturbance minimization in both steady and transient states. The paper talks about a four-legged converter with a voltage source that can adjust for biased currents and harmonic elements caused by non-linear loads. A shunt connected active filter is used to minimise harmonic currents. The new proposed ANN controller for the improvement of percent total harmonic distortion (THD) is in comparison. The entire power filter concept is based on a MATLAB-modeled with ANN controller. The proposed circuit in this research is studied under various operating situations and simulated, demonstrating the system's potential.
Multi-feature based automatic facial expression recognition using deep convolutional neural network Dixit, Anjali; Kasbe, Tanmay
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1406-1419

Abstract

Deep multi-task learning is one of the most challenging research topics widely explored in the field of recognition of facial expression. Most deep learning models rely on the class labels details by eliminating the local information of the sample data which deteriorates the performance of the recognition system. This paper proposes multi-feature-based deep convolutional neural networks (D-CNN) that identify the facial expression of the human face. To enhance the accuracy of recognition systems, the multi-feature learning model is employed in this study. The input images are preprocessed and enhanced via three filtering methods i.e., Gaussian, Wiener, and adaptive mean filtering. The preprocessed image is then segmented using a face detection algorithm. The detected face is further applied with local binary pattern (LBP) that extracts the facial points of each facial expression. These are then fed into the D-CNN that effectively recognizes the facial expression using the features of facial points. The proposed D-CNN is implemented, and the results are compared to the existing support vector machine (SVM). The analysis of deep features helps to extract the local information from the data without incurring a higher computational effort.
Automatic construction of generic stop words list for hausa text Bichi, Abdulkadir Abubakar; Samsudin, Ruhaidah; Hassan, Rohayanti
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1501-1507

Abstract

Stop-words are words having the highest frequencies in a document without any significant information. They are characterized by having common relations within a cluster. They are the noise of the text that are evenly distributed over a document. Removal of stop words improve the performance and accuracy of information retrieval algorithms and machine learning at large. It saves the storage space by reducing the vector space dimension, and helps in effective documents indexing. This research generated a list of Hausa stop words automatically using aggregated method by combining frequency and statistics methods. The experiments are conducted using a primarily collected Hausa corpus consisting of 841 Hausa news articles of size 646862 words and finally a list of distinct 81 Hausa stop words is generated.
Combination of narrow bipolar pulses and attempted leaders in Melaka, Malaysia Isa, Nur Asyiqin Binti Mohd; Baharudin, Zikri Abadi; Daud, Izdihartun Najihah Binti Ahmad; Zainuddin, Hidayat
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1825-1830

Abstract

This paper presents the characteristic of the positive attempted leaders preceded by positive narrow bipolar pulses (NPBPs). Attempted leaders are the preliminary breakdown process with no subsequent event (return stroke). On the other hand, narrow bipolar pulse is the lightning event commonly isolated and produces a strong electromagnetic field (in a short period). Attempted leaders hardly occurred in the tropics, and the preceding of the NBP (the combination) should be considered unique. In this present study, we found four samples in which the arithmetic means of duration of NPBPs pulse was 32.19 µs, with separation between the positive attempted leader was 1.86 ms apart. For the positive attempted leader, the arithmetic means of the whole pulse train, individual pulse and interval pulse of positive attempted leaders were 3.47 ms, 29.66 µs and 486.53 µs, respectively. The pulse train in this study seems to fade out fast compared to the isolated positive attempted leader pulse train. Next, the NPBP's pulse duration in this study shows well in agreement with the type of isolated NPBPs indicates that the association does not affect its pulse duration characteristic already present in the title.

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