cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 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. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 64 Documents
 3   4   5   6   7 
Search results for , issue "Vol 11, No 3: June 2022" : 64 Documents clear
Fast and accurate classifying model for denial-of-service attacks by using machine learning Mohammed Ibrahim Kareem; Mahdi Nsaif Jasim
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3688

Abstract

A denial of service (DoS) attack is one of the dangerous threats to networks that Internet resources and services will be less available, as they are easily operated and difficult to detect. As a result, identifying these intrusions is a hot issue in cybersecurity. Intrusion detection systems that use classic machine learning algorithms have a long testing period and high computational complexity. Therefore, it is critical to develop or improve techniques for detecting such an attack as quickly as possible to reduce the impact of the attack. As a result, we evaluate the effectiveness of rapid machine learning methods for model testing and generation in communication networks to identify denial of service attacks. In WEKA tools, the CICIDS2017 dataset is used to train and test multiple machine learning algorithms. The wide learning system and its expansions and the REP tree (REPT), random tree (RT), random forest (RF), decision stump (DS), and J48 were all evaluated. Experiments have shown that J48 takes less testing time and performs better, whereases it is performed by using 4-8 features. An accuracy result of 99.51% and 99.96% was achieved using 4 and 8 features, respectively.
Design and realization of low-cost solenoid valve remotely controlled, application in irrigation network Abdelhamid Benbatouche; Boufeldja Kadri
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.4123

Abstract

The remote and automated irrigation system of farmlands can avoid and minimize the waste of water and energy resources. This can be done with the remote-control of the solenoid-valves. A new solenoid-valve was designed and built from a simple valve with a motor and switches. The remote and automated irrigation system can monitor and receive requests via short message service (SMS) or web interface for controlling pump or solenoid-valves connected to the system. After each operation performed by the system, users receive notifications via SMS messages that contain the real-time status of the solenoid-valves controlled or temperature and humidity value. This system was created using Raspberry-Pi as the system control center. It has been connected to several sensors, and raspicam is used to take photo or video capture in real-time after the users’ request, and the global system mobile (GSM) module is a communication interface used to receive requests for controlling the irrigation system or to send notifications to users. A website is also developed for consultation and control of all that it contains in the system remotely. The result of this research aims to build a secure remote and automated irrigation system including low-cost solenoid-valve with Raspberry-Pi based on control and notification via SMS and web-page.
Chattering reduction in step down converter using robust reaching law Sridhara Somaguddu Ningappa; Siddesh Kondapur Basavarajan; Sudharashan Mungasavalli Katappa; Sandeep Velur Ramareddy; Lavakumar Tavane Basavarajappa
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3790

Abstract

The proposed robust reaching law for sliding mode control is used for chattering suppression, minimization of steady state error and reaching speed kept fast. With fine tuning parameters of robust reaching law, the system state reaches the sliding mode at the earliest. The mathematical analysis of the proposed reaching law is verifed. In one hand, they guarantee the system states reaches the sliding surface quickly and remain on it, in another way it deteriorate the chattering effectively, even unmatched certainties and disturbances. Such that the system response can better realize the unification of rapidity. A proposed reaching law applied to SMC DC-DC step down converter to analyse the chattering, it reduces the switching losses in the switching devices of the step down converter. In turn efficiency of the buck converter increases. MATLAB/Simulink results gives significant turn down of chattering and dynamic response of the system. This research work effectively improves the performance of the system.
Chest radiographs images retrieval using deep learning networks Sawsan M. Mahmoud; Hanan A. S. Al-Jubouri; Tawfeeq E. Abdoulabbas
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3478

Abstract

Chest diseases are among the most common diseases today. More than one million people with pneumonia enter the hospital, and about 50,000 people die annually in the U.S. alone. Also, Coronavirus disease (COVID-19) is a risky disease that threatens the health by affecting the lungs of many people around the world. Chest X-ray and CT-scan images are the radiological imaging that can be helpful to detect COVID-19. A radiologist would need to compare a patient's image with the most similar images. Content-based image retrieval in terms of medical images offers such a facility based on visual feature descriptor and similarity measurements. In this paper, a retrieval algorithm was developed to tackle such challenges based on deep convolutional neural networks (e.g., ResNet-50, AlexNet, and GoogleNet) to produce an effective feature descriptor. Also, similarity measures such as City block and Cosine were employed to compare two images. Chest X-ray and CT-scan datasets used to evaluate the proposed algorithms with a highest performance applying ResNet -50 (99% COVID-19 (+) and 98% COVID-19 (–)) and GoogleNet (84% COVID-19 (+) and 81% COVID-19 (–)) for X-ray and CT-scan respectively. The percentage increased about 1-4% when voting was used by a k-nearest neighbor classifier

Page 7 of 7 | Total Record : 64

 3   4   5   6   7 

Filter by Year

2022 2022


Reset
Filter By Issues
All Issue Vol 14, No 6: December 2025 Vol 14, No 5: October 2025 Vol 14, No 4: August 2025 Vol 14, No 3: June 2025 Vol 14, No 2: April 2025 Vol 14, No 1: February 2025 Vol 13, No 6: December 2024 Vol 13, No 5: October 2024 Vol 13, No 4: August 2024 Vol 13, No 3: June 2024 Vol 13, No 2: April 2024 Vol 13, No 1: February 2024 Vol 12, No 6: December 2023 Vol 12, No 5: October 2023 Vol 12, No 4: August 2023 Vol 12, No 3: June 2023 Vol 12, No 2: April 2023 Vol 12, No 1: February 2023 Vol 11, No 6: December 2022 Vol 11, No 5: October 2022 Vol 11, No 4: August 2022 Vol 11, No 3: June 2022 Vol 11, No 2: April 2022 Vol 11, No 1: February 2022 Vol 10, No 6: December 2021 Vol 10, No 5: October 2021 Vol 10, No 4: August 2021 Vol 10, No 3: June 2021 Vol 10, No 2: April 2021 Vol 10, No 1: February 2021 Vol 9, No 6: December 2020 Vol 9, No 5: October 2020 Vol 9, No 4: August 2020 Vol 9, No 3: June 2020 Vol 9, No 2: April 2020 Vol 9, No 1: February 2020 Vol 8, No 4: December 2019 Vol 8, No 3: September 2019 Vol 8, No 2: June 2019 Vol 8, No 1: March 2019 Vol 7, No 4: December 2018 Vol 7, No 3: September 2018 Vol 7, No 2: June 2018 Vol 7, No 1: March 2018 Vol 6, No 4: December 2017 Vol 6, No 3: September 2017 Vol 6, No 2: June 2017 Vol 6, No 1: March 2017 Vol 5, No 4: December 2016 Vol 5, No 3: September 2016 Vol 5, No 2: June 2016 Vol 5, No 1: March 2016 Vol 4, No 4: December 2015 Vol 4, No 3: September 2015 Vol 4, No 2: June 2015 Vol 4, No 1: March 2015 Vol 3, No 4: December 2014 Vol 3, No 3: September 2014 Vol 3, No 2: June 2014 Vol 3, No 1: March 2014 Vol 2, No 4: December 2013 Vol 2, No 3: September 2013 Vol 2, No 2: June 2013 Vol 2, No 1: March 2013 Vol 1, No 4: December 2012 Vol 1, No 3: September 2012 Vol 1, No 2: June 2012 Vol 1, No 1: March 2012 List of Accepted Papers (with minor revisions) More Issue