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
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 9,138 Documents
 816   817   818   819   820 
Optimization of re-configurable multi-core processors and security based on field programmable gate arrays Bachanna, Prashant; Hari Sankar, Palla; Kumar Tripath, Mukesh; Shivendra, Shivendra; Ravi Kumar, Kadali; Bhosle, Nilesh

Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp568-580

Abstract

In system-on-a-chip based complex processors has the problem of multithreading and miss-functionality due to their complexity and high-speed operations. In order to minimize these problems, the proposed design has machine learning based algorithms and cryptography systems for security has been incorporated. In the proposed work, the security level has been taken care of in three different stages such as data integrity, data authentication, and private and public keys encryption and decryption. In order to increase throughput with minimal latency, the proposed architecture with advanced high-performance protocol and advanced high-performance and advanced peripheral bus bridge is incorporated between the fabric dynamically re configurable multi-processor and peripherals along with security algorithms using secure hash algorithm (SHA-256) bits and advanced encryption standard (AES). In order to perform machine learning based applications, the proposed system is incorporated double-precision floating point arithmetic operations. The overall proposed architecture is developed in verilog hybrid deep learning (HDL) and quality checking using the LINT tool. The entire design is interfaced with the Zynq processor and software development kit (SDK) tool to verify data transfer between hardware and software. The obtained results are compared with existing state-of-art results and found that 18% improvement in throughput, a 21% improvement in power consumption savings, and a 34% reduction in latency.
Design of an enhanced dual-band microstrip patch antenna with defected ground structures for WLAN and WiMax El Issawi, Mohamed Lemine; Onyango Konditi, Dominic Bernard; Usman, Aliyu Danjuma
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp165-174

Abstract

This research presents an innovative dual-band microstrip patch antenna design enhanced with defected ground structures (DGS) and barium strontium titanate (BST) thin film, tailored for wireless local area network (WLAN) and WiMax applications. The first design phase involved the development of an microstrip patch antenna (MPA) using an flame retardant (FR4) substrate with a permittivity (εr1) of 4.3 and a thickness of 1.524 mm, enhanced with DGS. This configuration achieved a single-band resonance at 4.1 GHz, with a bandwidth of 0.82 GHz and a return loss (S11) of -32 dB. The second phase involved the integration of a BST thin film, with a high permittivity(εr2) of 250 and a thickoness of 0.1 mm, into the DGS-enhanced microstrip patch antenna (MPA). This mdification led to a transformation in the antenna's performance, enabling dual-band operation at resonance frequencies of 2.8 GHz and 5.8 GHz. Further, there was a corresponding substantial increase in bandwidth to 1.34 GHz and 1.25 GHz, respectively, an improvement in S11 values to -16.3 dB and -21.4 dB. Moreover, and antenna’s size of 14×10×1.524 mm3 . The study underscores the critical role of innovative material use and design optimization in advancing antenna technology, offering significant enhancements in bandwidth, and miniaturization, for wireless communication systems.
Development of cloud visualization a machining manufacturing system shop floor Joko Sulistyo; Angga Tegar Setiawan; Isa Setiyasah Toha
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp1005-1015

Abstract

The industry is currently experiencing the fourth industrial revolution, characterized by the automation of cyber physical systems and advanced connectivity through the internet of things (IoT). This revolution enables real-time monitoring of machines status on the shop floor by leveraging cyber-physical and IoT technologies. This paper describes the results of research that develops IoT and cloud-based visualization for a machining manufacturing system shop floor. Our proposed solution involves an internet of things device equipped with two current sensors to detect machine and spindle current. The sensor connected to an Arduino Nano, which is then connected to Wemos D1 for wireless transmission of data to the cloud. The cloud has been developed to store data and provide visualization applications, in the form of machines layout map to monitor machines conditions in the form of machines ON, machines OFF, spindles ON and spindles OFF in real time.
5G handover issues and techniques for vehicular communications Muhamad Ali Zuhdi Rosli; Siti Fatimah Abdul Razak; Sumendra Yogarayan
Indonesian Journal of Electrical Engineering and Computer Science Vol 32, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v32.i3.pp1442-1450

Abstract

Vehicular communication is gaining popularity, and seamless handover is critical to maintaining a stable and uninterrupted network connection between vehicles and roadside units. This paper investigates the advancements in handover approaches in vehicular networks, with a specific focus on 5G technology. Vehicular Ad-hoc Networks (VANETs) face challenges due to high mobility, dynamic network topology, and frequent information exchange. The paper discusses handover issues in 5G VANET environments, such as too-late and too-early handovers, wrong handover decisions, and unnecessary handovers. It also explores key performance indicators (KPIs) used in handover evaluation. The advancements in handover approaches presented in this paper pave the way for enhanced connectivity and communication management in 5G VANETs, contributing to the development of safer and more efficient intelligent transportation systems.
Uncovering botnets in IoT sensor networks: a hybrid self-organizing maps approach Mwaffaq Abu AlHija; Hamza Jehad Alqudah; Hiba Dar-Othman
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1840-1857

Abstract

The integration of the internet of things (IoT) has revolutionized diverse industries, introducing interconnected devices and IoT sensor networks for improved data acquisition. However, this connectivity exposes IoT ecosystems to emerging threats, with botnets posing significant risks to security. This research aims to develop an innovative solution for detecting botnets in IoT sensor networks. Leveraging insights from existing research, the study focuses on designing a hybrid self-organization map (SOM) Approach that integrates lightweight deep learning (DL) techniques. The objective is to enhance detection accuracy by exploring various DL architectures. Proposed methodology aims to balance computational efficiency for resource-constrained IoT devices while improving the discriminatory power of the detection system. The study advancing IoT cybersecurity and addresses critical challenges in botnet detection within IoT sensor networks. The testing of the artificial neural networks (ANN) classifier involves three models, each represented based on parameters related to the construction of the training models. The most effective ANN achieves 86%, works on anomaly intrusion detection systems (AIDS).
Uplink-downlink resource optimization for provisioning 5G application considering SUI fading channel models Vanita Kaba; Rajendra R. Patil
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp350-361

Abstract

Recently, superposition coding (SC), Stanford University Interim (SUI) fading channel, user clustering, successive interference cancellation (SIC) mechanism has been incorporated into the power allocation design for attaining good performance. Nonetheless, the existing model works with cluster size up to 4 user per cluster and induce higher control channel overhead. In addressing this paper introduce an effective resource allocation (ERA) design for power domain non-orthogonal multiple access (PD-NOMA) system. The ERA, first employ Zadoff Chu (ZC) coding, then power is allocated according to the distance considering 5 user per cluster. Finally, multi-level SIC is done at the receiver end. The ERA performance is studied by varying signal-to-noise ratio (SNR) in terms of bit error rate (BER) considering a maximum of five users per cluster. Further, the ERA performance in terms of BER is tested under different scenario defined in SUI propagation scenario such as higher pathloss, moderate path loss, and low path loss. The throughput performance under varied density and speed is also studied; the ERA achieves much better performance in terms of ERA, SNR and throughput than standard multi-user downlink resource allocation (MUDRA) model.
Multi-layer perceptron hyperparameter optimization using Jaya algorithm for disease classification Novika, Andien Dwi; Girsang, Abba Suganda
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp620-630

Abstract

This study introduces an innovative hyperparameter optimization approach for enhancing multilayer perceptrons (MLP) using the Jaya algorithm. Addressing the crucial role of hyperparameter tuning in MLP’s performance, the Jaya algorithm, inspired by social behavior, emerges as a promising optimization technique without algorithm-specific parameters. Systematic application of Jaya dynamically adjusts hyperparameter values, leading to notable improvements in convergence speeds and model generalization. Quantitatively, the Jaya algorithm consistently achieves convergences at first iteration, faster convergence compared to conventional methods, resulting in 7% higher accuracy levels on several datasets. This research contributes to hyperparameter optimization, offering a practical and effective solution for optimizing MLP in diverse applications, with implications for improved computational efficiency and model performance.
The effect of technological context on smart home adoption in Jordan Adai Al-Momani; Mohd Nordin Abdul Rahman; Mohammed N. Al-Refai; Suhaila Abuowaida; Mohammad Arabiat; Nawaf Alshdaifat
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp1186-1195

Abstract

This research examines the use of internet of things (IoT) smart home technologies in Jordan, using the technologies-organization-environment (TOE) framework and social exchange theory (SET). This study investigates the influence of security and privacy considerations on the behavioral intention to embrace IoT smart home solutions. The research examines the function of trust (TR) in service providers as a mediator and investigates how information technology (IT) knowledge acts as a moderator between technological elements and behavioral intention. Analyzed using smart partial least squares (PLS), data from 315 responses of executives in both listed and non-listed businesses were examined. The results highlight the need of giving priority to technological factors and building TR in service providers to ensure the effective implementation of IoT smart home technology in Jordan.
Optimal chest position of auscultation for chronic obstructive pulmonary disease diagnosis using machine learning John Amose; Manimegalai Vairavan
Indonesian Journal of Electrical Engineering and Computer Science Vol 32, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v32.i3.pp1417-1425

Abstract

Digital Stethoscopes over recent years have gained acceptance among pulmonologists to perform auscultations due to their advantages over traditional stethoscopes. During the previous decade, researchers have prominently contributed to the development of algorithms aimed at enabling objective diagnosis of respiratory sounds and conditions, thereby affording individuals lacking medical expertise the capability to auscultate themselves. However, auscultation requires the personnel to be aware of the optimal chest position to place the device for a reliable diagnosis as well. This study aims to identify the optimal chest position to place a digital stethoscope's diaphragm to objectively diagnose Chronic Obstructive Pulmonary Disease (COPD). Lung sound recordings from seven chest positions with data available in the ICBHI 2017 database namely, Anterior left (Al), Anterior right (Ar), Lateral left (Ll), Lateral right (Lr), Posterior left (Pl), Posterior right (Pr) and Trachea (Tc), were analyzed in this study. COPD+ and COPD- at diagnosis, each chest position was done objectively using Mel-Frequency Cepstral Coefficients (MFCC) features and machine learning models namely Support Vector Machine and Decision Tree. The results indicate that the Posterior right (Pr) chest position offers superior precision, recall, and F1 score, with a recognition accuracy of 99.7% in COPD screening.
Deep learning based COVID and Pneumonia detection using chest X-ray Praveen Kumar; Mira Rakhimzhanova; Seema Rawat; Alibek Orynbek; Vikas Kamra
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1944-1952

Abstract

Since the outbreak, the novel coronavirus (COVID-19) has infected more than 180 million people and has taken a toll of 3.91 million lives globally as of June 2021. This virus causes symptoms like fever, cold, and fatigue, and can develop into Pneumonia which can be detected using chest X-rays (CXRs). Therefore, early detection of COVID-19 can help get early medical attention. However, a sudden rise in the number of cases in many countries caused by COVID waves increases the burden on their testing facilities. As a result, they sometimes fail to perform enough testing to contain the spread. This work proposes a deep learning model to detect COVID-19 and Pneumonia based on CXRs. The dataset for our COVID model contains a total of 3,400 CXRs images of COVID-19 patients and 3,400 normal CXRs. The dataset for our Pneumonia model contains 1,300 CXR images of Pneumonia patients and 1,300 normal CXRs. We use convolutional neural network provided by TensorFlow to build our model, which gave 94.17% and 93.55% accuracy for COVID model and Pneumonia model, respectively. Finally, we deployed our model on the web and added a web tracker, which gives us the cases, deaths, and recoveries state-wise and nationwide.

Page 818 of 914 | Total Record : 9138

 816   817   818   819   820 

Filter by Year

2012 2026


Reset
Filter By Issues
All Issue Vol 41, No 1: January 2026 Vol 40, No 3: December 2025 Vol 40, No 2: November 2025 Vol 40, No 1: October 2025 Vol 39, No 3: September 2025 Vol 39, No 2: August 2025 Vol 39, No 1: July 2025 Vol 38, No 3: June 2025 Vol 38, No 2: May 2025 Vol 38, No 1: April 2025 Vol 37, No 3: March 2025 Vol 37, No 2: February 2025 Vol 37, No 1: January 2025 Vol 36, No 3: December 2024 Vol 36, No 2: November 2024 Vol 36, No 1: October 2024 Vol 35, No 3: September 2024 Vol 35, No 2: August 2024 Vol 35, No 1: July 2024 Vol 34, No 3: June 2024 Vol 34, No 2: May 2024 Vol 34, No 1: April 2024 Vol 33, No 3: March 2024 Vol 33, No 2: February 2024 Vol 33, No 1: January 2024 Vol 32, No 3: December 2023 Vol 32, No 1: October 2023 Vol 31, No 3: September 2023 Vol 31, No 2: August 2023 Vol 31, No 1: July 2023 Vol 30, No 3: June 2023 Vol 30, No 2: May 2023 Vol 30, No 1: April 2023 Vol 29, No 3: March 2023 Vol 29, No 2: February 2023 Vol 29, No 1: January 2023 Vol 28, No 3: December 2022 Vol 28, No 2: November 2022 Vol 28, No 1: October 2022 Vol 27, No 3: September 2022 Vol 27, No 2: August 2022 Vol 27, No 1: July 2022 Vol 26, No 3: June 2022 Vol 26, No 2: May 2022 Vol 26, No 1: April 2022 Vol 25, No 3: March 2022 Vol 25, No 2: February 2022 Vol 25, No 1: January 2022 Vol 24, No 3: December 2021 Vol 24, No 2: November 2021 Vol 24, No 1: October 2021 Vol 23, No 3: September 2021 Vol 23, No 2: August 2021 Vol 23, No 1: July 2021 Vol 22, No 3: June 2021 Vol 22, No 2: May 2021 Vol 22, No 1: April 2021 Vol 21, No 3: March 2021 Vol 21, No 2: February 2021 Vol 21, No 1: January 2021 Vol 20, No 3: December 2020 Vol 20, No 2: November 2020 Vol 20, No 1: October 2020 Vol 19, No 3: September 2020 Vol 19, No 2: August 2020 Vol 19, No 1: July 2020 Vol 18, No 3: June 2020 Vol 18, No 2: May 2020 Vol 18, No 1: April 2020 Vol 17, No 3: March 2020 Vol 17, No 2: February 2020 Vol 17, No 1: January 2020 Vol 16, No 3: December 2019 Vol 16, No 2: November 2019 Vol 16, No 1: October 2019 Vol 15, No 3: September 2019 Vol 15, No 2: August 2019 Vol 15, No 1: July 2019 Vol 14, No 3: June 2019 Vol 14, No 2: May 2019 Vol 14, No 1: April 2019 Vol 13, No 3: March 2019 Vol 13, No 2: February 2019 Vol 13, No 1: January 2019 Vol 12, No 3: December 2018 Vol 12, No 2: November 2018 Vol 12, No 1: October 2018 Vol 11, No 3: September 2018 Vol 11, No 2: August 2018 Vol 11, No 1: July 2018 Vol 10, No 3: June 2018 Vol 10, No 2: May 2018 Vol 10, No 1: April 2018 Vol 9, No 3: March 2018 Vol 9, No 2: February 2018 Vol 9, No 1: January 2018 Vol 8, No 3: December 2017 Vol 8, No 2: November 2017 Vol 8, No 1: October 2017 Vol 7, No 3: September 2017 Vol 7, No 2: August 2017 Vol 7, No 1: July 2017 Vol 6, No 3: June 2017 Vol 6, No 2: May 2017 Vol 6, No 1: April 2017 Vol 5, No 3: March 2017 Vol 5, No 2: February 2017 Vol 5, No 1: January 2017 Vol 4, No 3: December 2016 Vol 4, No 2: November 2016 Vol 4, No 1: October 2016 Vol 3, No 3: September 2016 Vol 3, No 2: August 2016 Vol 3, No 1: July 2016 Vol 2, No 3: June 2016 Vol 2, No 2: May 2016 Vol 2, No 1: April 2016 Vol 1, No 3: March 2016 Vol 1, No 2: February 2016 Vol 1, No 1: January 2016 Vol 16, No 3: December 2015 Vol 16, No 2: November 2015 Vol 16, No 1: October 2015 Vol 15, No 3: September 2015 Vol 15, No 2: August 2015 Vol 15, No 1: July 2015 Vol 14, No 3: June 2015 Vol 14, No 2: May 2015 Vol 14, No 1: April 2015 Vol 13, No 3: March 2015 Vol 13, No 2: February 2015 Vol 13, No 1: January 2015 Vol 12, No 12: December 2014 Vol 12, No 11: November 2014 Vol 12, No 10: October 2014 Vol 12, No 9: September 2014 Vol 12, No 8: August 2014 Vol 12, No 7: July 2014 Vol 12, No 6: June 2014 Vol 12, No 5: May 2014 Vol 12, No 4: April 2014 Vol 12, No 3: March 2014 Vol 12, No 2: February 2014 Vol 12, No 1: January 2014 Vol 11, No 12: December 2013 Vol 11, No 11: November 2013 Vol 11, No 10: October 2013 Vol 11, No 9: September 2013 Vol 11, No 8: August 2013 Vol 11, No 7: July 2013 Vol 11, No 6: June 2013 Vol 11, No 5: May 2013 Vol 11, No 4: April 2013 Vol 11, No 3: March 2013 Vol 11, No 2: February 2013 Vol 11, No 1: January 2013 Vol 10, No 8: December 2012 Vol 10, No 7: November 2012 Vol 10, No 6: October 2012 Vol 10, No 5: September 2012 Vol 10, No 4: August 2012 Vol 10, No 3: July 2012 More Issue