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International Journal of Electrical and Computer Engineering
ISSN : 20888708     EISSN : 27222578     DOI : -
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.
Articles 88 Documents
Search results for , issue "Vol 15, No 6: December 2025" : 88 Documents clear
Low-power and reduced delay in inverter and universal logic gates using Hvt-FinFET technology Chikkagoudar, Veerappa; Indumathi, G.
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5193-5204

Abstract

The rapid scaling of conventional complementary metal–oxide– semiconductor (CMOS) metal–oxide–semiconductor field-effect transistors (MOSFETs) led to significantly increasing power dissipation, delay, and short channel effects (SCEs). Fin field-effect transistor (FinFET) technology is a better alternative to MOSFETs with superior electrostatic control, low power, and reduced leakage current. FinFETs have been chosen for their efficiency in overcoming these issues. This work focuses on the design of high-threshold voltage fin field-effect transistor (Hvt-FinFET) 18 nm technology-based inverter with optimized parameters and implementing universal gates NAND and NOR in Cadence Virtuoso tool. These three gates are basic building blocks for any complex digital system design. The results demonstrate significant improvement in power and reduced propagation delay in comparison with conventional CMOS technology. The Hvt-FinFET inverter obtained power dissipation and delay reduction of 13.63% and 33.33%, respectively. Power and delay optimization of 29.10% and 11.8% have been obtained in the NAND gate and 31.28% and 29.08% in the NOR gate when compared to conventional CMOS circuits. The results demonstrate significant improvements in power savings, reduced propagation delay, and superior energy efficiency, validating the effectiveness of Hvt-FinFET technology for next-generation very large scale integration (VLSI) applications.
Geometrical determination of the focal point of parabolic solar concentrators Maxmudov, Bekzod; Korabayev, Sherzod A.; Sharibaev, Nosir Yu.; Abdulkhaev, Abror; Mahmudova, Xulkarxon; Mahsudov, Sh A.
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5055-5066

Abstract

Parabolic solar concentrators play a crucial role in harnessing solar energy by focusing sunlight onto a single focal point, enhancing efficiency in solar thermal applications. However, accurately determining the focal point remains a significant challenge, affecting energy efficiency, stability, and operational costs. This study presents a novel approach to determining the focal point of parabolic solar concentrators using two distinct geometric and mathematical methods. The first method applies standard parabolic equations to derive the focal point, while the second method introduces a geometric approach based on the properties of straight-line tangents and angular measurements. Experimental validation was conducted by comparing the proposed method against laser-based focal point determination. The results demonstrate that the proposed method enhances heat collection efficiency and stability, leading to improved energy output. The findings of this study contribute to optimizing solar concentrator designs, reducing energy losses, and promoting sustainable energy applications.
Improving time-domain winner-take-all circuit for neuromorphic computing systems Truong, Son Ngoc; Ngo, Tu Tien
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5173-5182

Abstract

With the rapid advancements of information processing systems, winner- take-all (WTA) circuits have emerged as essential components in a wide range of cognitive functions and decision-making applications. Neuromorphic computing systems, inspired by the biological brain, utilize WTA circuits as selective mechanisms that identify and retain the strongest signal while suppressing all others. In this study, we present an effective time-domain WTA circuit with optimized multiple-input NOT AND (NAND) gate and delay circuit for neuromorphic computing applications. The circuit is evaluated using sinusoidal current inputs with varying phase delays, which successfully demonstrating precise winner selection. When applied to neuromorphic image recognition task, the enhanced time-domain WTA achieves an improvement of 0.2% in precision while significantly reducing power consumption, yielding a low figure of merit (FoM) of 0.03 µW/MHz, compared to the previous study with FoM of 0.25 µW/MHz. The optimized WTA circuit is highly promising for large-scale neuromorphic applications.
Enhanced matrix pencil method for robust and efficient direction of arrival estimation in sparse and multi-frequency environments N., Ashraya A.; B., Punithkumar M.
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5380-5387

Abstract

Accurate direction of arrival (DOA) estimation is vital for applications in radar, sonar, wireless communication, and localization. This paper proposes an enhanced matrix pencil method (MPM) framework to overcome limitations of traditional methods such as noise sensitivity, computational inefficiency, and challenges with sparse arrays. The framework incorporates wavelet-based denoising for improved robustness in low signal-to-noise ratio (SNR) environments and employs particle swarm optimization (PSO) to optimize key parameters, achieving a balance between accuracy and efficiency. Extending MPM to two-dimensional (2D) DOA estimation, the method precisely determines azimuth and elevation angles. Comprehensive mathematical formulations and eigenvalue computations underlie the proposed enhancements. Simulation results validate its superiority over state-of-the-art techniques like MUSIC and ES-PRIT, achieving up to 30% improvement in root mean square error (RMSE) and reducing computational time by 20%–30%. Sensitivity analysis demonstrates robustness across varying noise levels, array geometries, and multi-frequency scenarios. This scalable and efficient framework addresses critical challenges in DOA estimation and offers promising directions for future advancements in real-time and resource-constrained environments.
Design and implementation of a modern modulation technique for modular multilevel converters Parapelly, Kishore; C., Mahalakshmi; Gopala, Venu Madhav
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5249-5257

Abstract

The phase opposition disposition (POD) modulation technique is a sophisticated control strategy employed in modular multilevel converters (MMCs) to achieve high-quality output waveforms with minimized harmonic distortion. POD modulation employs numerous triangular carrier signals, positioned such that carriers above the zero-reference point are in phase, while those below are 180 degrees out of phase. This unique arrangement reduces even-order harmonics and enhances the overall power quality. By comparing a common sinusoidal reference signal with these phase-opposed carriers, pulse width modulation (PWM) signals are generated to control the insertion and bypassing of sub modules within the MMC. The modular structure and balanced switching pattern of POD modulation ensure efficient thermal management and reduced electrical stress on the components, significantly improving the reliability and lifespan of the converter. The technique’s inherent scalability and flexibility make it particularly suitable for renewable energy integration, HVDC systems, and industrial motor drives. This paper explores the principles, implementation, and advantages of the POD modulation technique in enhancing the performance and efficiency of MMCs in modern power electronics.
Prediction of peripheral arterial disease through non-invasive diagnostic approach Mummaneni, Sobhana; Katakam, Lalitha Devi; Sri, Pali Ramya; Lingamallu, Mounika; Ch, Smitha Chowdary; Indira, D.N.V.S.L.S
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5782-5791

Abstract

Peripheral arterial disease (PAD) is a cardiovascular condition caused by arterial blockages and poor blood circulation, increasing the risk of severe complications such as stroke, heart attack, and limb ischemia. Early and accurate detection is essential to prevent disease progression and improve patient outcomes. This study introduces a non-invasive diagnostic method using laser doppler flowmetry (LDF), electrocardiography (ECG), and photoplethysmography (PPG) to assess vascular health. LDF measures microvascular blood flow, ECG evaluates heart rate variability, and PPG captures pulse waveform characteristics. Key physiological features such as blood flow variability, pulse transit time, and hemodynamic responses are extracted and analyzed using machine learning. Random forest and XGBoost models are employed and combined using ensemble learning to classify individuals into non-PAD, moderate PAD, and severe PAD categories. A comparative evaluation shows that the ensemble model delivers superior classification accuracy. This integrated system offers a fast, reliable screening tool that supports early PAD detection and intervention. By combining multimodal signal analysis with machine learning, the approach enhances diagnostic precision and provides a scalable solution for preventive cardiovascular care.
Synergetic synthesis of a neural network controller for an adaptive control of a nonlinear dynamic plant Siddikov, Isamidin; Khalmatov, Davronbek; Iskandarov, Zokhid; Khushnazarova, Dilnoza
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5258-5265

Abstract

The paper considered issues the development of a self-organizing controller (SC) based on a neuro-fuzzy network that can approximate a nonlinear function with arbitrary accuracy. The SC in the form of neuro-fuzzy networks, possesses the nonlinear property that allows for an increased range of control over the plant, which imparts adaptive properties to the control systems. To reduce the dimensionality of the plant, it is proposed to split the model of the system into sub models with smaller dimensionality, due to which the duration of training of the neuro-fuzzy network is reduced and asymptotic stability is ensured as a whole. The proposed approach is also applicable to multidimensional control systems of the nonlinear dynamic plants. The simulation results showed that the synthesized SC provides good tracking characteristics, the tracking efficiency is no more than 10%, which meets the requirement of the control system.
Solar powered internet of things-based heart rate monitoring system employing electrocardiogram signal analysis Ahmad, Suziana; Aina, Ahmad Alif Ahmad; Marwan, Shahrul Hisyam; Hashim, Rosziana; Shari, Nurul Syuhada
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5942-5953

Abstract

Electrocardiogram (ECG) test is used to record the electrical activity of a human heart for determining any problems with irregular heartbeat patterns and other cardiovascular conditions. This project deals with the implementation of an Internet of things (IoT) enabled ECG monitoring system with solar supply that can identify heart rate deviations from normal values (40 BPM, 80 BPM and 120 BMP) utilizing simulated ECG signals. The ECG data acquisition is done by using KL-76001 biomedical measurement training system, KL-75001 ECG module and multiparameter simulator MS400. The acquired ECG signals are processed through Python software to detect R-peaks and R-R interval. The counts of these R-R peaks are utilized in conjunction with the Blynk IoT platform, employing an ESP8266 module for monitoring via a mobile application and LCD display. The system was tested for detecting and monitoring three heart conditions which are bradycardia, normal, and tachycardia and successfully demonstrated alert capabilities for these conditions.
Robotic product-based manipulation in simulated environment Guacheta-Alba, Juan Camilo; Espitia-Cubillos, Anny Astrid; Jimenez-Moreno, Robinson
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5894-5903

Abstract

Before deploying algorithms in industrial settings, it is essential to validate them in virtual environments to anticipate real-world performance, identify potential limitations, and guide necessary optimizations. This study presents the development and integration of artificial intelligence algorithms for detecting labels and container formats of cleaning products using computer vision, enabling robotic manipulation via a UR5 arm. Label identification is performed using the speeded-up robust features (SURF) algorithm, ensuring robustness to scale and orientation changes. For container recognition, multiple methods were explored: edge detection using Sobel and Canny filters, Hopfield networks trained on filtered images, 2D cross-correlation, and finally, a you only look once (YOLO) deep learning model. Among these, the custom-trained YOLO detector provided the highest accuracy. For robotic control, smooth joint trajectories were computed using polynomial interpolation, allowing the UR5 robot to execute pick-and-place operations. The entire process was validated in the CoppeliaSim simulation environment, where the robot successfully identified, classified, and manipulated products, demonstrating the feasibility of the proposed pipeline for future applications in semi-structured industrial contexts.
Optimal design, decoding, and minimum distance analysis of Goppa codes using heuristic method Aylaj, Bouchaib; Nouh, Said; Belkasmi, Mostafa
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5411-5421

Abstract

Error-correcting codes are crucial to ensure data reliability in communication systems often affected by transmission noise. Building on previous successful applications of our heuristic method degenerate quantum simulated annealing (DQSA) to Bose–Chaudhuri–Hocquenghem (BCH) and quadratic residue (QR) codes. This paper proposes two algorithms designed to address two coding problems for Goppa codes. DQSA-dmin computes the minimum distance (dmin) while DQSA-Dec, serves as a hard decoder optimized for additive white gaussian noise (AWGN) channels. We validate DQSA-dmin comparing its computed minimum distances with theoretical estimates for algebraically constructed Goppa codes, showing accuracy and efficiency. DQSA-dmin further used to find the optimal Goppa codes that reach the lower bound of dmin for linear codes known in the literature and stored in Marcus Grassl's online database. Indeed, we discovered 12 Goppa codes reaching this lower bound. For DQSA-Dec, experimental results show that it obtains a bit error rate (BER) of 10-5 when SNR=7.5 for codes with lengths less than 65, which is very interesting for a hard decoder. Additionally, a comparison with the Paterson algebraic decoder specific to this code family shows that DQSA-Dec outperforms it with a 0.6 dB coding gain at BER=10-4. These findings highlight the effectiveness of DQSA-based algorithms in designing and decoding Goppa codes.

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