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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 65 Documents
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Search results for , issue "Vol 25, No 1: January 2022" : 65 Documents clear
A new function of stereo matching algorithm based on hybrid convolutional neural network Mohd Saad Hamid; Nurulfajar Abd Manap; Rostam Affendi Hamzah; Ahmad Fauzan Kadmin; Shamsul Fakhar Abd Gani; Adi Irwan Herman
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.pp223-231

Abstract

This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. The main purpose of the stereo matching algorithm is to produce a disparity map. This map is essential for many applications, including three-dimensional (3D) reconstruction. The raw disparity map computed by a convolutional neural network (CNN) is still prone to errors in the low texture region. The algorithm is set to improve the matching cost computation stage with hybrid CNN-based combined with truncated directional intensity computation. The difference in truncated directional intensity value is employed to decrease radiometric errors. The proposed method’s raw matching cost went through the cost aggregation step using the bilateral filter (BF) to improve accuracy. The winner-take-all (WTA) optimization uses the aggregated cost volume to produce an initial disparity map. Finally, a series of refinement processes enhance the initial disparity map for a more accurate final disparity map. This paper verified the performance of the algorithm using the Middlebury online stereo benchmarking system. The proposed algorithm achieves the objective of generating a more accurate and smooth disparity map with different depths at low texture regions through better matching cost quality.
An approach for slow distributed denial of service attack detection and alleviation in software defined networks Prathima Mabel John; Rama Mohan Babu Kasturi Nagappasetty
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.pp404-413

Abstract

Over the last few years, the need for programmable networks has captured the interest of industrialists and academicians. It has led to the development of a paradigm called software defined network (SDN). It separates the network intelligence into the control plane and forwarding logic into the data plane. This architecture gives scope to various security issues of which denial of service (DoS) is the most common and challenging to detect. This paper focuses on the detection and mitigation of a slow DoS attack called Slowloris on Apache2 server in SDN based networks. The proposed solution is called Slowloris detection and mitigation mechanism (SDMM). Mininet, an emulator, and SimpleHTTPServer are used for simulation and the same is implemented using Zodiac FX OpenFlow switch, Ryu controller and Apache2 server. SDMM algorithm detects and mitigates prolonged Slowloris attack in typical networks as well as in slow networks with low bandwidth and high delay in 240-280s with an accuracy of 100% and 98% respectively. It uses expectation of burst size as a key factor for detection.
Exploring the performance of feature selection method using breast cancer dataset Tsehay Admassu Assegie; Ravulapalli Lakshmi Tulasi; Vadivel Elanangai; Napa Komal Kumar
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.pp232-237

Abstract

Breast cancer is the most common type of cancer occurring mostly in females. In recent years, many researchers have devoted to automate diagnosis of breast cancer by developing different machine learning model. However, the quality and quantity of feature in breast cancer diagnostic dataset have significant effect on the accuracy and efficiency of predictive model. Feature selection is effective method for reducing the dimensionality and improving the accuracy of predictive model. The use of feature selection is to determine feature required for training model and to remove irrelevant and duplicate feature. Duplicate feature is a feature that is highly correlated to another feature. The objective of this study is to conduct experimental research on three different feature selection methods for breast cancer prediction. Sequential, embedded and chi-square feature selection are implemented using breast cancer diagnostic dataset. The study compares the performance of sequential embedded and chi-square feature selection on test set. The experimental result evidently shows that sequential feature selection outperforms as compared to chi-square (X2) statistics and embedded feature selection. Overall, sequential feature selection achieves better accuracy of 98.3% as compared to chi-square (X2) statistics and embedded feature selection.
Design and simulation double Ku-band Vivaldi antenna Huda Ibrahim Hamd; Israa Hazem Ali; Ahmed Mohammed Ahmed
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.pp396-403

Abstract

Due to the tremendous development in the field of wireless communication and its use in several fields, whether military or commercial was proposed. A novel tapered slot Vivaldi antenna is designed and simulated at double band frequency (Ku-band) using computer simulation technology (CST) software 2020. The dimensions of the antenna are 2.3 × 1 × 0.4 mm3 with a microstrip feed of 0.5 mm. The proposed antenna is improved by cutting a number of circle shapes on the patch layer in different positions. The simulation results are divided into more sections according to the number of circle shapes cutting. The results are good acceptance and make the improved Vivaldi antenna valuable in many future wireless communication applications.
An internet of things-based automatic brain tumor detection system Md. Lizur Rahman; Ahmed Wasif Reza; Shaiful Islam Shabuj
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.pp214-222

Abstract

Due to the advances in information and communication technologies, the usage of the internet of things (IoT) has reached an evolutionary process in the development of the modern health care environment. In the recent human health care analysis system, the amount of brain tumor patients has increased severely and placed in the 10th position of the leading cause of death. Previous state-of-the-art techniques based on magnetic resonance imaging (MRI) faces challenges in brain tumor detection as it requires accurate image segmentation. A wide variety of algorithms were developed earlier to classify MRI images which are computationally very complex and expensive. In this paper, a cost-effective stochastic method for the automatic detection of brain tumors using the IoT is proposed. The proposed system uses the physical activities of the brain to detect brain tumors. To track the daily brain activities, a portable wrist band named Mi Band 2, temperature, and blood pressure monitoring sensors embedded with Arduino-Uno are used and the system achieved an accuracy of 99.3%. Experimental results show the effectiveness of the designed method in detecting brain tumors automatically and produce better accuracy in comparison to previous approaches.

Page 7 of 7 | Total Record : 65

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