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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 9,174 Documents
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Local stereo matching algorithm using modified dynamic cost computation A. F. Kadmin; R. A. Hamzah; M. N. Abd Manap; M. S. Hamid; T. F. Tg. Wook
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1312-1319

Abstract

Stereo matching is an essential subject in stereo vision architecture. Traditional framework composition consists of several constraints in stereo correspondences such as illumination variations in images and inadequate or non-uniform light due to uncontrollable environments. This work improves the local method stereo matching algorithm based on the dynamic cost computation method for depth measurement. This approach utilised modified dynamic cost computation in the matching cost. A modified census transform with dynamic histogram is used to provide the cost in the cost computation. The algorithm applied the fixed-window strategy with bilateral filtering to retain image depth information and edge in the cost aggregation stage. A winner takes all (WTA) optimisation and left-right check with adaptive bilateral median filtering are employed for disparity refinement. Based on the Middlebury benchmark dataset, the algorithm developed in this work has better accuracy and outperformed several other state-of-the-art algorithms.
The IoT and registration of MRI brain diagnosis based on genetic algorithm and convolutional neural network Ahmed Shihab Ahmed; Hussein Ali Salah
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp273-280

Abstract

The technology of the multimodal brain image registration is the key method for accurate and rapid diagnosis and treatment of brain diseases. For achieving high-resolution image registration, a fast sub pixel registration algorithm is used based on single-step discrete wavelet transform (DWT) combined with phase convolution neural network (CNN) to classify the registration of brain tumors. In this work apply the genetic algorithm and CNN clasifcation in registration of magnetic resonance imaging (MRI) image. This approach follows eight steps, reading the source of MRI brain image and loading the reference image, enhencment all MRI images by bilateral filter, transforming DWT image by applying the DWT2, evaluating (fitness function) each MRI image by using entropy, applying the genetic algorithm, by selecting the two images based on rollout wheel and crossover of the two images, the CNN classify the result of subtraction to normal or abnormal, “in the eighth one,” the Arduino and global system for mobile (GSM) 8080 are applied to send the message to patient. The proposed model is tested on MRI Medical City Hospital in Baghdad database consist 550 normal and 350 abnormal and split to 80% training and 20 testing, the proposed model result achieves the 98.8% accuracy.
Self-diagnostic approach for cell counting biosensor Qais Al-Gayem; Hussain F. Jaafar; Saad S. Hreshee
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp688-698

Abstract

In this research, a test monitoring strategy for an array of biosensors is proposed. The principle idea of this diagnostic technique is to measure and compare the impedance of each sensor in the array to achieve fully controlled online health monitoring technique at the system level. The work includes implementation of the diagnostic system, system architecture for analogue part, and SNR analysis. The technique has been applied on a cell coulter counting biochip where the design and fabrication of this sensing chip with electrodes make the coulter counter be an effective mean to count and analyses the cells in a blood sample. The experimental results show that the indication factor of the sensing electrodes has increased from 1 to 1.8 gradually depending on the fault level.
Trend of the spread of COVID-19 in Indonesia using the machine learning prophet algorithm Nur Hayati; Fauziah Fauziah; Dendi Rizka Poetra; Dede Wandi
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1780-1788

Abstract

Based on information on the BNPB website on 2 September 2020, the positive rate for coronavirus disease (COVID-19) in Indonesia reached 25.25% on 30 August 2020. This is a big challenge for the Indonesian government to reduce the positivity rate to meet the standards safe accepted by World Health Organization (WHO) is 5%. To ensure the accuracy of government policies, accurate data predictions are needed. Therefore, the prophet's machine learning algorithm can be used to see trends in the spread of COVID-19 in the next one year. This algorithm has a fairly high level of accuracy because the data contains time variables which are adjusted to the dataset. In several previous research, the dataset was vast uncertain and small. Meanwhile in this research, data was taken from 2 March 2020 to 12 February 2021 on the KawalCOVID19 website. This data is used to predict from 13 February 2021 to 12 February 2022. There are 3 data used; namely data confirmed, recovered and died. Based on the analysis, the confirmed patient was 22.60-42.11%, died amounted to 21.67%-39.00%, and recovered by 22.53-41.82%. The prediction percentage that the average cases died was 2.43% every day. The accuracy of data confirmed was 43.97%, died was 72.50% and recovered was 84.24%.
Improved cloud radio access network based fair network model in internet pricing Indrawati Indrawati; Fitri Maya Puspita; Desta Wahyuni; Evi Yuliza; Oki Dwipurwani
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp968-975

Abstract

In this study, the pricing scheme that will be formed is a model from the previous research model involving model of cloud-radio access network (C-RAN) and fair network management models. This model combines the benefits of internet service provider (ISP) and service quality (QoS) obtained by internet users, one of which is fair network factors. The model used is a nonlinear equation and is solved by the LINGO 13.0 program to get the optimal solution. The results show that the pricing scheme with regard to service quality generates maximum revenue for ISPs. Based on the improved C-RAN model that are classified into 2 cases, the optimal results in the improved model, the optimal value is found in the pricing scheme in case 1 of by conducting numerical computation using  hotspot traffic from local server.
Revealing and evaluating the influence of filters position in cascaded filter: application on the ECG de-noising performance disparity Abdenour Allali; Arres Bartil; Lahcene Ziet; Amar Hebibi
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp829-838

Abstract

In this paper, a new optimization on windowing technique based on finite impulse response (FIR) filters is proposed for revealing and evaluating the Influence of filters position in cascaded filter tested on the ECG signal de-noising. baseline wander (BLW), power line interference (PLI) and electromyography (EMG) noises are getting removed. The performance of the adopted method is evaluated on the PTB diagnostic database. Subsequently, the comparisons are based on signal to noise ratio (SNR) improvement and mean square error (MSE) minimization. Where the Rectangular, and Kaiser windows have been used for the more potent performances. The disparity average (DA) of SNR values is detected; in both Kaiser and Rectangular windows are assessed by ±0.38046dB and ±0.70278dB respectively, while the MSE values were constant. The excellent configuration or filters position (H-B-L) of the filtration system is selected according to high measurements of SNR and low MSE too, to de-noise the ECG signals. First of all, this applied approach has led to 31.30 dB SNR improvement with MSE minimization of 26. 43%. This means that there is a significant contribution to improving the field of filtration.
Comparative study of electrical test methods on detecting transformer faults Sharin Ab Ghani; Mohd Shahril Ahmad Khiar; Imran Sutan Chairul; Nor Hidayah Rahim; Mohd Hisamuddin Kamaruzaini
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 2: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i2.pp755-762

Abstract

Condition monitoring of distribution and power transformers is of utmost importance to utilities due to cost effectiveness concerns. The common faults that occur in transformers are short circuits and winding deformation. To date, there are many established test methods used to detect these faults. In this study, three test methods (insulation resistance (IR), transformer turn ratio (TTR), and frequency response analysis (FRA)) were compared to assess their effectiveness in detecting short circuit and winding deformation in a three-phase transformer. Based on the results, the three test methods were found to be capable of detecting short circuits. However, only TTR and FRA can detect winding deformation, and FRA can further indicate which phase is faulty. Therefore, it is concluded that FRA is more effective in detecting short circuit and winding deformation of a three-phase transformer.
Digital image processing methods for estimating leaf area of cucumber plants Uoc Quang Ngo; Duong Tri Ngo; Hoc Thai Nguyen; Thanh Dang Bui
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp317-328

Abstract

Increasingly emerging technologies in agriculture such as computer vision, artificial intelligence technology, not only make it possible to increase production. To minimize the negative impact on climate and the environment but also to conserve resources. A key task of these technologies is to monitor the growth of plants online with a high accuracy rate and in non-destructive manners. It is known that leaf area (LA) is one of the most important growth indexes in plant growth monitoring system. Unfortunately, to estimate the LA in natural outdoor scenes (the presence of occlusion or overlap area) with a high accuracy rate is not easy and it still remains a big challenge in eco-physiological studies. In this paper, two accurate and non-destructive approaches for estimating the LA were proposed with top-view and side-view images, respectively. The proposed approaches successfully extract the skeleton of cucumber plants in red, green, and blue (RGB) images and estimate the LA of cucumber plants with high precision. The results were validated by comparing with manual measurements. The experimental results of our proposed algorithms achieve 97.64% accuracy in leaf segmentation, and the relative error in LA estimation varies from 3.76% to 13.00%, which could meet the requirements of plant growth monitoring systems.
Increasing transmission control protocol speed by reducing the acknowledgement collision probability Suherman Suherman; Ali Hanafiah Rambe; Norshakila Haris; Anhar Anhar
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp121-128

Abstract

Transmission control protocol (TCP) employs acknowledgement (TCP-ACK) for every transmitted packets to ensure reliable transmission. As a result, it sends the next window packets after receiving the TCP-ACK packet of previous window. This means that the earlier the TCP-ACK packet arrives, the faster the TCP next window transmission and the better the TCP performances. To do so, there should be a special treatment to the transmitted TCP-ACK to fasten next window transmission. This paper proposes a collision probability reduction for the transmitted TCP-ACK packets so that the overall TCP delay reduces. Collision probability reduction can be implemented in many ways. Initially, mathematical analysis is provided to prove that method can work as expected. The mathematic analysis shows that when TCP-ACK collision probability is reduced, the overall TCP delay is also reduced. The proposed method is then implemented in 802.11, 802.16 and complex networks. The NS-2 simulations evaluations for the aforementioned networks and the proposed method proved that collision reductions on TCP-ACK exert average TCP delay reductions about 11.86%, 28.04% and 9.46% subsequently.The proposed method is also applicable for other TCP types.
Pythagorean fuzzy N-Soft groups M. Shazib Hameed; Salman Mukhtar; Haq Nawaz Khan; Shahbaz Ali; Muhammad Haris Mateen; Muhammad Gulzar
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1030-1038

Abstract

We elaborate in this paper a new structure pythagorean fuzzy $N$-soft groups which is the generalization of intuitionistic fuzzy soft group initiated by Karaaslan in 2013. In Pythagorean fuzzy N-soft sets concepts of fuzzy sets, soft sets, N-soft sets, fuzzy soft sets, intuitionistic fuzzy sets, intuitionistic fuzzy soft sets, Pythagorean fuzzy sets, Pythagorean fuzzy soft sets are generalized. We also talk about some elementary basic concepts and operations on Pythagorean fuzzy N-soft sets with the assistance of illusions. We additionally define three different sorts of complements for Pythagorean fuzzy N-soft sets and examined a few outcomes not hold in Pythagorean fuzzy N-soft sets complements as they hold in crisp set hypothesis with the assistance of counter examples. We further talked about {$(\alpha, \beta, \gamma)$-cut of Pythagorean fuzzy N-soft set and their properties}. We likewise talk about some essential properties of Pythagorean fuzzy N-soft groups like groupoid, normal group, left and right cosets, $(\alpha, \beta,\gamma)$-cut subgroups and some fundamental outcomes identified with these terms. Pythagorean fuzzy N-soft sets is increasingly efficient and adaptable model to manage uncertainties. The proposed models of Pythagorean fuzzy N-soft groups can defeat a few disadvantages of the existing statures.

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