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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
ISSN : 25024752     EISSN : 25024760     DOI : -
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Articles 9,174 Documents
Design analysis of moth-flame optimized fault tolerant technique for minimally buffered network-on-chip router Subramanian Sumithra; Nagaiyanallur Lakshminarayanan Venkatara; Subramani Suresh Kumar; Ramaiah Purushothaman; Kathiresan Kokulavani; Velankanni Gowri
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp179-189

Abstract

A network on a chip is a solitary silicon chip utilized to perform the communication characteristics of large-scale (LSI) to very large-scale integration (VLSI) systems. Network-on-chip (NoC) architecture includes links, network interfaces (NI), and routers to unite with external memories or processors. NoC is designed to flow messages from the source module to the destination module through several links involving routing decisions. The design of NoC is complex and the buffer section’s expensiveness creates problems while providing secured data service. Moreover, routers and links in NoC setups are liable to faults. This work introduces a minimal buffered router, and the faults in the network are optimized using moth flame optimized (MFO) fault-tolerant technique. The software named Xilinx ISE design suite 14.5 is employed for the minimum buffered router model. The suggested scheme is operated with less area, low power (0.241 mW), and high speed (965.261 Megahertz (MHz)) when matched with previous works.
A novel identifiable data sharing mechanism for multiple participants in cloud computing Jayalakshmi Karemallaiah; Prabha Revaiah
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.pp1444-1451

Abstract

Recent applications and growth on the internet have generated a lot of popularity and adoption of cloud computing which aims to assure the various computing resources. Data storage is one of the primary resources offered by the cloud; however, considering the multiple users in the particular cloud raises major concerns due to security. Recent researches shown great potential for providing efficient data sharing with multiple users. However, tracing of the data provider is still concerned to be a major issue. Hence, this research work proposes identifiable data sharing for multiple users (IDSMU) mechanism which aims to provide security for multiple users in a particular cloud group. At first, IDSMU creates the general participants (GP)-key for secure access to data. Further, IDSMU creates the trusted participants (TP) based on the reputation which further helps in creating the key generation. A novel signature scheme is used for identifying the participants; IDSMU is evaluated on computation count and efficiency is proved by comparing with an existing model considering computation count.
Depression recognition over fusion of visual and vocal expression using artificial intelligence Chandan Gautam; Aaradhya Raj; Bhargavee Nemade; Vinaya Gohokar
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.pp1753-1759

Abstract

Depression is a mental illness that usually goes untreated in people and can have catastrophic consequences, including suicidal thoughts. Counselling services are widely available, but because depression is a stigmatized illness, many people who are depressed decide not to seek help. Therefore, it is essential to develop an automated system that can recognize depression in individuals before it worsens. In this study, a novel approach is proposed for identifying depression using a combination of visual and vocal emotions. Long short-term memory (LSTM) is used to assess verbal expressions and convolutional neural networks (CNN) to analyze facial expressions. The proposed system is trained using features of depression from the distress analysis interview corpus (DAIC) dataset and tested on videos of college students with frontal faces. The proposed approach is effective in detecting depression in individuals, with high accuracy and reliability.
Development and modification Sobel edge detection in tuberculosis X-ray images Devita, Retno; Fitri, Iskandar; Yuhandri, Yuhandri; Yani, Finny Fitry
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp1191-1200

Abstract

Tuberculosis (TB), a major global health threat caused by mycobacterium tuberculosis, claims lives across all age groups, underscoring the urgent need for accurate diagnostic methods. Traditional TB diagnosis using X-ray images faces challenges in detection accuracy, highlighting a critical problem in medical imaging. Addressing this, our study investigates the use of image processing techniques-specifically, a dataset of 112 TB X-ray images-employing pre-processing, segmentation, edge detection, and feature extraction methods. Central to our method is the adoption of a modified Sobel edge detection technique, named modification and extended magnitude gradient (MEMG), designed to enhance TB identification from X-ray images. The effectiveness of MEMG is rigorously evaluated against the gray-level co-occurrence matrix (GLCM) parameters, contrast, and correlation, where it demonstrably surpasses the standard Sobel detection, amplifying the contrast value by over 50% and achieving a correlation value nearing 1. Consequently, the MEMG method significantly improves the clarity and detail of TB-related anomalies in X-ray images, facilitating more precise TB detection. This study concludes that leveraging the MEMG technique in TB diagnosis presents a substantial advancement over conventional methods, promising a more reliable tool for combating this global health menace.
Arnold’s cat map secure multiple-layer reversible watermarking Aulia Arham; Novia Lestari
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 3: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i3.pp1536-1545

Abstract

Reversible watermarking is a novel approach to digital copyright protection that allows the embedding of watermarks into digital data using multiple layers while retaining the ability to recover the original content without data loss. This method provides a unique solution for securing digital data while maintaining the integrity and quality of the content. Nonetheless, new challenges have emerged with the increase in attacks on this method, as reversible watermarking methods lack security keys, making it easy to extract and modify hidden data. In this paper, we present a method for multiple-layer reversible watermarking with security keys, with the goal of addressing the challenges posed by attacks and improving data protection within embedded content. The method uses arnold’s cat map to scramble images, and data embedding in predetermined iterations serves as the methods security key. We put the method through its paces with six grayscale images. With this method, the embedding capacity can reach 2.999 bpp across four layers of embedding, while the visual image quality can reach 22.01 dB. The outcomes from this approach are that the security of multiple-layer reversible watermarking can be enhanced while preserving the capacity to embed data in each layer.
Transforming image descriptions as a set of descriptors to construct classification features Volodymyr Gorokhovatskyi; Iryna Tvoroshenko; Olena Yakovleva
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp113-125

Abstract

The article develops methods to solve a fundamental problem in computer vision: image recognition of visual objects. The results of the research on the construction of modifications for the space of classification features based on the application of the transformation of the structural description through the decomposition in the orthogonal basis and the implementation of the distance matrix model between the components of the description are presented. The application of the system of orthogonal functions as an apparatus for the transformation of the description showed the possibility of a significant gain in the speed of processing while maintaining high indicators of classification accuracy and interference resistance. The synthesized feature systems’ effectiveness has been confirmed in terms of a significant increase in the rate of codes and a sufficient level of efficiency. An experimental example showed that the time spent calculating the relevance of descriptions according to their modified presentation is more than ten times shorter than for traditional metric approaches. The developed classification features can be used in applied tasks where the time of visual objects’ identification is critical.
Design and fabrication of S-band power amplifier for wireless sensor networks Hoi, Tran Van; Lanh, Ngo Thi; Duong, Bach Gia
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp979-986

Abstract

This paper discusses the process of designing and manufacturing a wideband power amplifier operating in the S-band. To amplify a low power and broadband radio frequency signals from 2.1 GHz to 2.5 GHz, the proposed power amplifier uses a diagram of a two-stages amplification with peak offset amplification frequency 2.3 GHz. The power amplifier is designed with a center frequency difference of 2.2 GHz and 2.4 GHz respectively to achieve a bandwidth of 400 MHz. The proposed power amplifier (PA) uses RF transistor SHF-0589 using gallium arsenide heterostructure field-effect transistor (GaAs HFET) technology for high gain and low power consumption. The complete amplifier achieves power gain 21.1 dB inband 2.1-2.5 GHz and achieve maximum power gain of 22.5 dB at the frequency of 2.4 GHz; the output power rise up to 33 dBm; input reflection coefficient (S11) reaches -19.2 dB and output reflection coefficient reaches -17.2 dB. The designed amplifier circuit can be used for wireless sensor networks operating at S-band.
Analysis of converter transformer pressboard insulation degradation under surge using mathematical morphology Shrikant S. Mopari; Dagadu Shankar More; Anjali S. Bhalchandra; Pannala Krishna Murthy; K. M. Jadhav
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.pp1434-1443

Abstract

Nowadays, with the significant expansion of industrial growth, the bulk power requirement can only be satisfied through high-voltage direct current HVDC transmission. The converter transformer is the utmost vital part of the HVDC transmission. Pressboard insulation is most commonly used as inter-disc insulation in converter transformers. During working conditions due to elevated temperature and different operational stresses, insulation material gets deteriorated. It may cause a risk to the life of the converter transformer. The effects of elevated temperatures as well as frequency on pressboard insulation of the converter transformer are examined in this study. The condition evaluation and morphological changes in pressboard insulation at elevated temperatures can evaluate with the help of frequency domain spectroscopy (FDS) and atomic force microscopy (AFM) techniques. The impact of elevated temperatures on insulation material can be analyzed based on surface roughness and dielectric parameters. In MATLAB Simulink environment, a dual winding single-phase converter transformers valve side star winding 60 discs model is constructed for impulse test. Based upon arrival time and velocity of traveling wave, insulation degradation location can be identified by using mathematical morphology. The simulation results demonstrate that the suggested method can notably located degradation across disc winding.
High-capacity steganography through audio fusion and fission Namitha Mangikuppe Venkateshaiah; Manjula Govinakovi Rudrappa
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp643-652

Abstract

Information security is required for two reasons, either to conceal the information completely or to prevent the misuse of the information by adding watermarks or metadata. Audio steganography uses audio signals to hide secret information. In the proposed audio steganography technique, cover audio files and secret audio files are transformed from time domain to wavelet domain using discrete wavelet transform, the secret audio file is transformed in two levels, leading to secure and high-capacity data hiding. 1% of the 2-level compressed secret is fused to 99% of the 1-level compressed cover. “Peak signal to noise ratio and mean squared error, Pearson’s correlation coefficient, spearman’s correlation coefficient, perceptual evaluation of speech quality and short-time objective intelligibility” are considered to assess the similarity of cover audio and stego audio and similarity of secret audio embedded, and secret audio retrieved. Results show that the stego audio signal is perceptually indistinguishable from the cover audio signal. The approach also passed the robustness test.
Reduced switch cascaded asymmetrical 27 level inverter-STATCOMwith fuzzy logic controller Sundar Ramesh; Vijayakumar Govindaraj; Raja Raman; Shanmugasundaram Venkatarajan; Kamatchi Kannan Vijayarangan
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.pp1288-1297

Abstract

In this study, a 27-levelinverter with a reduced switch asymmetrical cascaded H-bridge (CHB) with fuzzy logic controller (FLC) is proposed. With series connections, a low voltage converter, a middle level voltage converter, and a high voltage converter make up the static synchronous compensator (STATCOM). The configuration of the asymmetrical inverter uses trinary DCsources. To acquire switching signals for the trinary inverter-based STATCOM to compensate for real power, load voltage, reactive power, load current, and power factor under load changing conditions, FLC is constructed. With fewer switches, the suggested arrangement produces greater voltage levels. The performance of the reduced switch asymmetrical cascaded H-bridge inverter-STATCOM with FLCis simulated using the MATLAB Simulink platform under both static and dynamic load conditions. When compared to reduced switch asymmetrical cascaded H-bridge inverter-STATCOM with traditional proportional integral (PI) controller, the FLC result demonstrates efficient unbalanced load compensation. The FLC in the proposed inverter also lowers the total harmonic distortion.

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