cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Tole Sutikno
Contact Email
ijece@iaesjournal.com
Phone
-
Journal Mail Official
ijece@iaesjournal.com
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 112 Documents
 1   2   3   4   5 
Search results for , issue "Vol 12, No 3: June 2022" : 112 Documents clear
A sensorless approach for tracking control problem of tubular linear synchronous motor Nguyen Hong Quang; Nguyen Phung Quang; Nguyen Van Lanh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2393-2404

Abstract

As well-known, linear motors are widely applied to various industrial applicationsdue to their abilities in providing directly straight movement without auxiliary mechanical transmissions. This paper addresses the sensorless control problem of tubular linear synchronous motors, which belong to a family of permanent magnet linear motor. To be specific, a novel velocity observer is proposed to deal with an unmeasurable velocity problem, and asymptotic convergence of the observer error is ensured. Unlike other studies on sensorless control methods for linear motors, our proposed observer is designed by regrading unknown disturbance load in the tracking control problem whereas considering theoretical demonstrations. By adjusting controller parameters properly, the position and velocity tracking error converge in arbitrary small values. Finally, the effectiveness of the proposed method is verified in two illustrative examples.
Design and performance analysis of human body communication digital transceiver for wireless body area network applications Sujaya Bangalore Lokanatha; Sompura Basavaraju Bhanu Prashanth
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2206-2213

Abstract

Wireless body area network (WBAN) is a prominent technology for resolving health-care concerns and providing high-speed continuous monitoring and real-time help. Human body communication (HBC) is an IEEE 802.15.6 physical layer standard for short-range communications that is not reliant on radio frequency (RF). Most WBAN applications can benefit from the HBC's low-latency and low-power architectural features. In this manuscript, an efficient digital HBC transceiver (TR) hardware architecture is designed as per IEEE 802.15.6 standard to overcome the drawbacks of the RF-wireless communication standards like signal leakage, on body antenna and power consumption. The design is created using a frequency selective digital transmission scheme for transmitter and receiver modules. The design resources are analyzed using different field programmable gate array (FPGA) families. The HBC TR utilizes <1% slices, consumes 101 mW power, and provides a throughput of 24.31 Mbps on Artix-7 FPGA with a latency of 10.5 clock cycles. In addition, the less than 10-4bit error rate of HBC is achieved with a 9.52 Mbps data rate. The proposed work is compared with existing architectures with significant improvement in performance parameters like chip area, power, and data rate.
Inappropriate machine learning application in real power industry cases Alexandra Khalyasmaa; Pavel Matrenin; Stanislav Eroshenko
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp3023-3032

Abstract

Global digital transformation of the energy sector has led to the emergence of multiple digital platform solutions, the implementation of which have revealed new problems associated with continuous growth of data volumes requiring new approaches to their processing and analysis. This article is devoted to the improper application of machine learning approaches and flawed interpretation of their output at various stages of decision support systems development: data collection; model development, training and testing as well as industrial implementation. As a real industrial case study, the article examines the power generation forecasting problem of photovoltaic power plants. The authors supplement the revealed problems with the corresponding recommendation for industrial specialists and software developers.
Promoting fractional frequency reuse performance for combating pilot contamination in massive multiple input multiple output Hany A. Atallah; Saad Almutairi; Adel Bedair Abdel-Rahman; Mohamed Elwekeil
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2681-2688

Abstract

Massive multiple-input multiple-output (MIMO) improves spectrum efficiency by increasing the capacity of the wireless structure. Therefore, massive MIMO is promising for fifth generation (5G) wireless communications. In massive MIMO, channel estimation is a crucial part that should achieve reliable performance. Pilots are sent from the end-users to be used for estimating the channel. However, the problem of interference in pilot contamination affects the performance for cell-edge users. Specifically, pilot contamination appears when the same pilot sequence is utilized at the same time by more than one terminal. This lead to an inaccurate estimation of the channel. Consequently, the decoded data will not be reliable. For mitigating these pilot contamination effects, an enhanced fractional frequency reuse (eFFR) scheme is proposed that uses an algorithm in the allocation of pilot sequences to end users’ devices based on the locations of the users from the target base station (BS). The simulation results exhibit that the proposed scenario outweighs the traditional FFR within both signal to interference, and noise ratio (SINR), and capacity. Consequently, the suggested scenario enhances the performance of more than 80% of the cell terminals and the other 20% of the terminals have a slightly lower performance compared to the FFR.
Effect of silica nanofiller in cross-linked polyethylene as electrical tree growth inhibitor Moh Nazar, Nazatul Shiema; Syazwani Mansor, Noor; Khayam, Umar; Asiah Muhamad, Nor; Jaafar Mustapha, Mariatti; Izzani Mohamed, Amir; Mohd Jamil, Mohamad Kamarol
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2256-2263

Abstract

One of the main phenomena that contributes to the non-success of cable insulation made of cross-linked polyethylene (XLPE) is electrical treeing. To improve the XPLE cable insulation, the use of nanofiller has been introduced. Adding the nanofiller in the based composite offers better cable lifetime and resistance to deal with the cable failure. One of the potential nanofillers that can increase the insulation performance of XLPE cable is silica nanofiller. To this extent, the studies on silica nanofiller in XLPE are focusing on the impulse breakdown strength, dielectric loss, permittivity, space charge, alternating current (AC), and partial discharge. The studies reveal that the dielectric properties of the XLPE nanocomposite have significant improvement. Therefore, this work investigates the effect of various concentrations of silica nanofiller in XLPE composite as electrical tree inhibitor. The concentrations of silica nanofiller in XLPE were 0.25 wt%, 0.5 wt%, 0.75 wt%, 1.0 wt%, 1.25 wt%, 1.5 wt%, and 1.75 wt%. The silica nanofillers have 96%-99% purity, 20-30 nm sizes and the shapes are spherical. As a result, the XLPE composite containing 1.5 wt% silica nanofiller demonstrate higher tree inception voltage and detaining the tree propagation speed, which could be considered as an inhibitor medium of electrical tree growth.
HapPart: partitioning algorithm for multiple haplotyping from haplotype conflict graph Abu-Bakar Muhammad Abdullah; Md. Monowar Hossain; Pintu Chandra Shill
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2856-2866

Abstract

Each chromosome in the human genome has two copies. The haplotype assembly challenge entails reconstructing two haplotypes (chromosomes) using aligned fragments genomic sequence. Plants viz. wheat, paddy and banana have more than two chromosomes. Multiple haplotype reconstruction has been a major research topic. For reconstructing multiple haplotypes for a polyploid organism, several approaches have been designed. The researchers are still fascinated to the computational challenge. This article introduces a partitioning algorithm, HapPart for dividing the fragments into k-groups focusing on reducing the computational time. HapPart uses minimum error correction curve to determine the value of k at which the growth of gain measures for two consecutive values of k-multiplied by its diversity is maximum. Haplotype conflict graph is used for constructing all possible number of groups. The dissimilarity between two haplotypes represents the distance between two nodes in graph. For merging two nodes with the minimum distance between them this algorithm ensures minimum error among fragments in same group. Experimental results on real and simulated data show that HapPart can partition fragments efficiently and with less computational time.
k-nearest neighbor modelling of agarwood oil samples available in capital of Malaysia market Erny Haslina Abd Latib; Nurlaila Ismail; Saiful Nizam Tajuddin; Jasmin Jamil; Zakiah Mohd Yusoff
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp3158-3165

Abstract

Agarwood oil is consumed during traditional ceremonies and even in medicinal purposes due to its effective therapeutic characteristic. As a part of ongoing research on agarwood oil, this paper presented a k-nearest neighbor (k-NN) modelling of agarwood oil samples available in the capital of Malaysia market. The work involved agarwood oil samples from three sources which are lab, local manufacturer and market. The inputs are the chemical compounds and the output is the oil’s resources. The input-output was divided into training and testing dataset with the ratio of 80% to 20%, respectively, before they were fed to the k-NN for model development as well as model validation. During the model development, the k-value was varied from 1 to 5, and their accuracy was observed. The result showed that the k=1 and k=2 shared the similar accuracy for training and testing datasets, which are 98.63% and 100.00%, respectively. This study revealed the capabilities of the k-NN model in classifying the agarwood oil samples to the three sources: lab, local manufacturer and market. It was a significant study and contributed to further work especially those related to agarwood oil research area.
Video captioning in Vietnamese using deep learning Dang Thi Phuc; Tran Quang Trieu; Nguyen Van Tinh; Dau Sy Hieu
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp3092-3103

Abstract

With the development of today's society, demand for applications using digital cameras jumps over year by year. However, analyzing large amounts of video data causes one of the most challenging issues. In addition to storing the data captured by the camera, intelligent systems are required to quickly analyze the data to correct important situations. In this paper, we use deep learning techniques to build automatic models that describe movements on video. To solve the problem, we use three deep learning models: sequence-to-sequence model based on recurrent neural network, sequence-to-sequence model with attention and transformer model. We evaluate the effectiveness of the approaches based on the results of three models. To train these models, we use microsoft research video description corpus (MSVD) dataset including 1970 videos and 85,550 captions translated into Vietnamese. In order to ensure the description of the content in Vietnamese, we also combine it with the natural language processing (NLP) model for Vietnamese.
English speaking proficiency assessment using speech and electroencephalography signals Abualsoud Hanani; Yanal Abusara; Bisan Maher; Inas Musleh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2501-2508

Abstract

In this paper, the English speaking proficiency level of non-native English speakerswas automatically estimated as high, medium, or low performance. For this purpose, the speech of 142 non-native English speakers was recorded and electroencephalography (EEG) signals of 58 of them were recorded while speaking in English. Two systems were proposed for estimating the English proficiency level of the speaker; one used 72 audio features, extracted from speech signals, and the other used 112 features extracted from EEG signals. Multi-class support vector machines (SVM) was used for training and testing both systems using a cross-validation strategy. The speech-based system outperformed the EEG system with 68% accuracy on 60 testing audio recordings, compared with 56% accuracy on 30 testing EEG recordings.
Optimizing the placement of cloud data center in virtualized environment Al-Karawi, Yassir; S. Alhumaima, Raad; Hussein Khudair, Khalid; Ahmed, Abdulmunem
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp3276-3286

Abstract

In cloud mobile networks, precise assessment for the position of the virtualization powered cloud center would improve the capacity limit, latency and energy efficiency (EEf). This paper utilized the Monte Carlo oriented particle swarm optimization (PSO) and genetic algorithm (GA) to first, obtain the optimal number of virtual machines (VMs) that maximize the EEf of the mobile cloud center, second, optimize the position of the mobile data center. To fulfil such examination, a power evaluation framework is proposed to shape the power utilization of a virtualized server while hosting an amount of VMs. In addition, the total power consumption of the network is examined, including data center and radio units (RUs). This evaluation is based on linear modelling of the network parameters, such as resource blocks, number of VMs, transmitted and received powers, and overhead power consumption. Finally, the EEf is constrained to many quality of service (QoS) metrics, including number of resource blocks, total latency and minimum user's data rate.

Page 2 of 12 | Total Record : 112

 1   2   3   4   5 

Filter by Year

2022 2022


Reset
Filter By Issues
All Issue Vol 15, No 6: December 2025 Vol 15, No 5: October 2025 Vol 15, No 4: August 2025 Vol 15, No 3: June 2025 Vol 15, No 2: April 2025 Vol 15, No 1: February 2025 Vol 14, No 6: December 2024 Vol 14, No 5: October 2024 Vol 14, No 4: August 2024 Vol 14, No 3: June 2024 Vol 14, No 2: April 2024 Vol 14, No 1: February 2024 Vol 13, No 6: December 2023 Vol 13, No 5: October 2023 Vol 13, No 4: August 2023 Vol 13, No 3: June 2023 Vol 13, No 2: April 2023 Vol 13, No 1: February 2023 Vol 12, No 6: December 2022 Vol 12, No 5: October 2022 Vol 12, No 4: August 2022 Vol 12, No 3: June 2022 Vol 12, No 2: April 2022 Vol 12, No 1: February 2022 Vol 11, No 6: December 2021 Vol 11, No 5: October 2021 Vol 11, No 4: August 2021 Vol 11, No 3: June 2021 Vol 11, No 2: April 2021 Vol 11, No 1: February 2021 Vol 10, No 6: December 2020 Vol 10, No 5: October 2020 Vol 10, No 4: August 2020 Vol 10, No 3: June 2020 Vol 10, No 2: April 2020 Vol 10, No 1: February 2020 Vol 9, No 6: December 2019 Vol 9, No 5: October 2019 Vol 9, No 4: August 2019 Vol 9, No 3: June 2019 Vol 9, No 2: April 2019 Vol 9, No 1: February 2019 Vol 8, No 6: December 2018 Vol 8, No 5: October 2018 Vol 8, No 4: August 2018 Vol 8, No 3: June 2018 Vol 8, No 2: April 2018 Vol 8, No 1: February 2018 Vol 7, No 6: December 2017 Vol 7, No 5: October 2017 Vol 7, No 4: August 2017 Vol 7, No 3: June 2017 Vol 7, No 2: April 2017 Vol 7, No 1: February 2017 Vol 6, No 6: December 2016 Vol 6, No 5: October 2016 Vol 6, No 4: August 2016 Vol 6, No 3: June 2016 Vol 6, No 2: April 2016 Vol 6, No 1: February 2016 Vol 5, No 6: December 2015 Vol 5, No 5: October 2015 Vol 5, No 4: August 2015 Vol 5, No 3: June 2015 Vol 5, No 2: April 2015 Vol 5, No 1: February 2015 Vol 4, No 6: December 2014 Vol 4, No 5: October 2014 Vol 4, No 4: August 2014 Vol 4, No 3: June 2014 Vol 4, No 2: April 2014 Vol 4, No 1: February 2014 Vol 3, No 6: December 2013 Vol 3, No 5: October 2013 Vol 3, No 4: August 2013 Vol 3, No 3: June 2013 Vol 3, No 2: April 2013 Vol 3, No 1: February 2013 Vol 2, No 6: December 2012 Vol 2, No 5: October 2012 Vol 2, No 4: August 2012 Vol 2, No 3: June 2012 Vol 2, No 2: April 2012 Vol 2, No 1: February 2012 Vol 1, No 2: December 2011 Vol 1, No 1: September 2011 More Issue