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 6,301 Documents
 527   528   529   530   531 
Hybrid deep learning model for YouTube spam comment detection Sam'an, Muhammad; Imaddudin, Khrisna
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3313-3319

Abstract

Social media platforms, including YouTube and Facebook, allow users to interact through comments and videos. However, the openness of these platforms also makes them susceptible to spammers engaging in phishing, malware distribution, and advertisement dissemination. In response, our study introduces an innovative technique for detecting features indicative of spam within comments associated with shared videos. The initial phase involves data collection from the University of California, Irvine (UCI) machine learning repository and preprocessing using tokenization and lemmatization. Subsequently, a rigorous feature selection process is executed, and experiments are conducted with various proposed classification models. The performance evaluation demonstrates outstanding accuracy in identifying spam comments on YouTube: convolutional neural network with gated recurrent unit (CNN-GRU) at 95.92%, convolutional neural network with long short-term memory (CNN-LSTM) at 95.41%, convolutional neural network with bidirectional long short-term memory (CNN-biLSTM) at 96.43%, gated recurrent unit (GRU) at 95.41%, long short-term memory (LSTM) at 94.13%, and bidirectional long short-term memory (biLSTM) at 96.94% and convolutional neural network (CNN) at 94.64%. These results highlight the substantial contribution of our approach to spam detection and the fortification of online security.
Wideband trans-impedance amplifier with bandwidth tuning for near infra-red spectroscopy bio-medical applications Balasubramanian, Muthukumaran; Balasubramanian, Ramachandran
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6204-6213

Abstract

A wide band trans-impedance amplifier (WBTIA) with tunable bandwidth for near infra-red spectroscopy (NIRS) bio-medical applications is presented in this research article. The first stage of the proposed WBTIA is implemented by a modified inverter-cascode (InvCas) trans-impedance amplifier (TIA) with series and shunt inductive peaking for the bandwidth extension and a common-source amplifier as a second stage for gain boosting. Bandwidth tuning is achieved by a novel tuning mechanism with a fixed capacitor and tunable metal–oxide–semiconductor (MOS) capacitor with a control voltage. The fixed capacitor provides a coarse-grain bandwidth tuning whereas the tunable MOS capacitors are used for fine-grain bandwidth tuning. The WBTIA is designed in 45 nm technology and it achieved a maximum trans-impedance gain (TIG) of 84.91 dBΩ and 354.81 MHz bandwidth. The proposed WBTIA consumes 41.24 µW power from 1 V supply voltage. The input referred current noise at 100 MHz is 169 fA/sqrt (Hz) and the output noise voltage is 69.8 pV/sqrt (Hz).
An on-chip soft-start pseudo-current hysteresis-controlled buck converter for automotive applications Boutaghlaline, Anas; El Khadiri, Karim; Tahiri, Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1459-1472

Abstract

This paper introduces a novel direct current to direct current (DC-DC) buck converter that uses a pseudo-current hysteresis controller and an on-chip soft start circuit for improved transient performance in automotive applications. The proposed converter, implemented with Taiwan semiconductor manufacturing company (TSMC) 0.18 µm complementary metal oxide semiconductor (CMOS) one-poly-six-metal (1P6M) technology, includes a rail-to-rail current detection circuit and an on-chip soft start circuit to handle transient responses and improve efficiency. Transient response analysis shows fast settling times of 28 µs for both load current changes from 100 mA to 1 A and reversals with consistent transient voltages of approximately 190 mV and peak power efficiency of 99.32% at 5 V output voltage and 100 mA load current. Additionally, the converter maintains a constant output voltage of approximately 5 V across the entire load current range with an average accuracy of 90.41%. A comparative analysis with previous work shows superior performance in terms of figure of merit (FOM). Overall, the proposed pseudo-current hysteresis controlled buck converter exhibits remarkable transient response, load regulation and power efficiency, positioning it as a promising solution for demanding applications, particularly in automotive systems where precise voltage regulation is crucial.
A fuzzy logic scheme based on spread rate and population for pandemic vaccine allocation Kareem, Abdul; Kumara, Varuna
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5941-5948

Abstract

This paper deals with a novel decision-making scheme for inferring the allocation of vaccines to the provincial health care authorities by the central health care authority of a country in pandemic scenarios. This novel scheme utilizes a fuzzy logic-based inference scheme that utilizes the spread rate and population of a province as inputs to infer the vaccination rate. The proposed scheme is evaluated on the coronavirus disease (COVID-19) data from six southern states of India during the first week of October 2020, collected from the database maintained by the Government of India. The findings demonstrate that the suggested plan, which takes population and spread rate into account, makes sure that enough vaccination doses are distributed to the provinces with a larger spread rate with a higher priority, and that immunizations are not delayed in provinces with controlled spread rates. Also, in due course, all territories will appropriately distribute enough vaccine supply to control the spread. Therefore, this plan strengthens the efforts to control the pandemic outbreaks by ensuring the proper and balanced delivery of vaccines in a timely, efficient, and objective manner.
Impact of initialization of a modified particle swarm optimization on cooperative source searching Ab. Majid, Mad Helmi; Arshad, Mohd Rizal; Yahya, Mohd Faid; Ibrahim, Abu Bakar
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp218-229

Abstract

Swarm robotic is well known for its flexibility, scalability and robustness that make it suitable for solving many real-world problems. Source searching which is characterized by complex operation due to the spatial characteristic of the source intensity distribution, uncertain searching environments and rigid searching constraints is an example of application where swarm robotics can be applied. Particle swarm optimization (PSO) is one of the famous algorithms have been used for source searching where its effectiveness depends on several factors. Improper parameter selection may lead to a premature convergence and thus robots will fail (i.e., low success rate) to locate the source within the given searching constraints. Additionally, target overshooting and improper initialization strategies may lead to a nonoptimal (i.e., take longer time to converge) target searching. In this study, a modified PSO and three different initializations strategies (i.e., random, equidistant and centralized) were proposed. The findings shown that the proposed PSO model successfully reduce the target overshooting by choosing optimal PSO parameters and has better convergence rate and success rate compared to the benchmark algorithms. Additionally, the findings also indicate that the random initialization give better searching success compared to equidistant and centralize initialization.
Digital technologies evolution in swiftlet farming: a systematic literature review Markom, Arni Munira; Yusof, Yusrina; Markom, Marni Azira; Haris, Hazlihan; Muhammad, Ahmad Razif
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4456-4470

Abstract

The integration of cutting-edge technologies into swiftlet farming has greatly enhanced efficiency, productivity, and sustainability. The internet of things (IoT) provides farmers with up-to-date environmental data, enabling them to create and sustain ideal circumstances for swiftlets. Artificial intelligence (AI) enhances this process by analysing vast databases and providing farmers with well-informed choices to optimize yield. Biotechnology, by combining genetic selection and breeding programs, effectively connects with the IoT, enabling constant monitoring and control of the health and genetic traits of swiftlets. The integration of renewable energy technology seeks to diminish dependence on conventional energy sources, promoting sustainability. In this paper, a systematic review of the literature is examined the utilization of digital technology in the swiftlet farmhouse. The findings were classified into three main themes: smart monitoring and control systems, advanced bird detection techniques, and sustainable practices and innovative approaches, specifically in the manufacture of edible bird nest. This systematic literature review emphasizes the multidisciplinary nature of swiftlet farming's technological evolution, technology developers, challenges and recommendations that farmers and the industry face in their pursuit of sustainable growth.
Enhancing battery system identification: nonlinear autoregressive modeling for Li-ion batteries Mossaddek, Meriem; Laadissi, El Mehdi; Ennawaoui, Chouaib; Bouzaid, Sohaib; Hajjaji, Abdelowahed
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp2449-2456

Abstract

Precisely characterizing Li-ion batteries is essential for optimizing their performance, enhancing safety, and prolonging their lifespan across various applications, such as electric vehicles and renewable energy systems. This article introduces an innovative nonlinear methodology for system identification of a Li-ion battery, employing a nonlinear autoregressive with exogenous inputs (NARX) model. The proposed approach integrates the benefits of nonlinear modeling with the adaptability of the NARX structure, facilitating a more comprehensive representation of the intricate electrochemical processes within the battery. Experimental data collected from a Li-ion battery operating under diverse scenarios are employed to validate the effectiveness of the proposed methodology. The identified NARX model exhibits superior accuracy in predicting the battery's behavior compared to traditional linear models. This study underscores the importance of accounting for nonlinearities in battery modeling, providing insights into the intricate relationships between state-of-charge, voltage, and current under dynamic conditions.
Homomorphic technique for group data sharing in cloud computing environment Karemallaiah, Jayalakshmi; Revaiah, Prabha
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6612-6618

Abstract

The main aim of this research work is to make it easier for the same group to share and store anonymous data on the cloud securely and effectively. This research work presents verifiable privacy-aware enhanced homomorphic (VPEH) for multiple participants; moreover, the enhanced homomorphic encryption mechanism provides end-to-end encryption and allows the secure computation of data without revealing any data in the cloud. The proposed algorithm uses homomorphic multiplication to compute the hashes product of challenges blocks that make it more efficient, furthermore an additional security model is incorporated to verify the shared data integrity. The VPEH mechanism is evaluated considering parameters such as tag generation, proof generation, and verification; model efficiency is proved by observing the marginal improvisation over the other existing models by varying the number of blocks and number of challenge blocks.
Design and analysis of 7-stage MOS current mode logic power gated MOSFETs in current starved voltage-controlled oscillator for the phase locked loop application Madheswaran, Sivasakthi; Panneerselvam, Radhika
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1398-1405

Abstract

This paper presents a new process, voltage and temperature (PVT) tolerant 7-stage ring type current starved voltage-controlled oscillator (CS-VCO). In this, a 7-stage ring VCO is proposed using power gated technique for phase locked loop (PLL) application. PLL plays a major role in clock and data recovery, Global Positioning System (GPS) system and satellite communications. For the high-speed application of PLL it is designed using 7-stage inverter delay cell with MOS current mode logic (MCML) technique. The circuit undergoes process, voltage and temperature variations with different parameters such as average power, oscillation frequency, phase noise, tuning range and output noise. The Monte-Carlo analysis justifies the proposed design provides better results. The circuit is simulated under 45 nm CMOS technology using cadence virtuoso. The average power consumption of the proposed circuit is 29.368 µW with the oscillation frequency of 3.06 GHz. The output noise and the phase noise of the proposed VCO are -161.55 dB and -125.92 dBc/Hz respectively. It achieves the frequency tuning range (FTR) of 95.09%. The obtained simulation results are highly robust with PVT making the circuit suitable for PLL application.
Gaussian filter-based dark channel prior for image dehazing enhancement Nurhayati, Oky Dwi; Surarso, Bayu; Syafei, Wahyul Amien; Nugraheni, Dinar Mutiara Kusumo
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5765-5778

Abstract

The presence of haze in an image is one of the challenges in computer vision tasks, such as remote sensing, object monitoring, and traffic monitoring applications. The hazy image is considered to contain noise and it can interfere with the image analysis process. Thus, image dehazing becomes a necessity as part of image enhancement. Dark channel prior (DCP) is one of the images dehazing methods that works based on a physical degradation model and utilizes low-intensity values from outdoor image characteristics. The DCP method generally consists of some steps, which are finding the dark channel and gradient image, estimating the sky region, atmospherical light, and transmission map, and reconstructing the dehazed image. This study introduces image dehazing by utilizing the Gaussian filter combined with the DCP method to increase the sharpness and accentuate the details of hazy images. Experimental results show that the proposed method could produce dehazed images with a visual quality is 18.94 dB on average or an increase of 11.91% compared to the original hazy image with a similarity index is 66.71% on average or an increase of 8.10%. Therefore, it is expected that this study can contribute to the image dehazing method enrichment based on DCP.

Page 529 of 631 | Total Record : 6301

 527   528   529   530   531 

Filter by Year

2011 2026


Reset
Filter By Issues
All Issue Vol 16, No 1: February 2026 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