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31,456 Article Results

Enhancing small-signal stability in high-voltage DC systems: supplementary controls for damping inter-area oscillations

10.11591/ijeecs.v40.i1.pp1-9
Siddharthsingh K. Chauhan , Vineeta S. Chauhan
High voltage direct current (HVDC) transmission systems have emerged as a leading technology for efficient and cost-effective long-distance power transmission, offering significant advantages over traditional high voltage alternating current (HVAC) systems. These benefits include seamless integration of asynchronous grids and renewable energy sources (RES), enhancing the reliability of power supply. However, the dynamic behavior of HVDC systems and their ability to maintain stability under small disturbances introduce challenges to overall system stability.To address these challenges, this study focuses on improving small-signal stability in HVDC systems by exploring supplementary control strategies for damping interarea power oscillations.The proposed strategy was tested using the kundur two-area four-machine (K-TAFM) system modeled in power systems computer-aided design (PSCAD), incorporating case study under a three phase-to-ground fault scenario.The active power imbalance and inter-area oscillations observed during fault conditions highlight the critical need for advanced stability enhancement techniques to effectively mitigate small signal disturbances. This approach significantly improved the small-signal stability of the HVDC system, underscoring its potential to enhance the reliability and resilience of modern power grids.
Volume: 40
Issue: 1
Page: 1-9
Publish at: 2025-10-01

Realization of Bernstein-Vazirani quantum algorithm in an interactive educational game

10.12928/telkomnika.v23i5.26929
David; Calvin Institute of Technology Gosal , Timothy Rudolf; Calvin Institute of Technology Tan , Yozef; Calvin Institute of Technology Tjandra , Hendrik Santoso; Calvin Institute of Technology Sugiarto
Quantum algorithms are celebrated for their computational superiority over classical counterparts, yet they pose significant learning challenges for non-physics audiences. Among these, the Bernstein-Vazirani (BV) algorithm stands out for its quantum speedup by efficiently identifying a secret binary string. However, the accessibility of such algorithms remains constrained by their inherent technical complexity. To address this educational gap, this paper introduces a gamified, web-based tool that innovatively reinterprets the BV algorithm’s complex mathematical settings through an into engaging scenario of identifying broken lamps. Players assume the role of an investigator, utilizing both classical and quantum solvers to identify faulty lamps with minimal queries. By transforming the BV algorithm into an intuitive gameplay experience, the tool helps reducing technical barriers, making quantum concepts much more comprehensible for educators and students than traditional methods that demand rigorous mathematical understanding. Developed using Qiskit, IBM’s Python package for quantum computation, and deployed via Flask, a popular Python microframework for building web applications, the game effectively simplifies complex quantum algorithms while demonstrating the practical applications of quantum speedup. This contribution advances quantum education by merging technical depth with interactive design, fostering a broader understanding of quantum principles and inspiring new innovations in gamified learning.
Volume: 23
Issue: 5
Page: 1247-1257
Publish at: 2025-10-01

Optimizing distance vector-hop localization in wireless sensor networks using the grasshopper optimization algorithm

10.11591/ijeecs.v40.i1.pp461-479
Janani Selvaraj , Hymlin Rose Sasijohn Gloryrajabai , Sivarathinabala Mariappan , Backia Abinaya Antony Samy , Sudhakar Kalairishi
In scenarios involving mobile sensors within distributed sensor systems, such as those often encountered in wireless sensor networks (WSNs) or the internet of things (IoT), the ability to ascertain the origin of sensor data holds significant importance. Range-free Monte Carlo Localization methods offer an energy-efficient solution that eliminates the need for extra hardware, as they solely rely on the radio hardware already present on sensor nodes. But there are certain disadvantages when implemented, as it occupies more amount of power and some inaccuracies might happen in accessing the data from the sensor node. In this paper, we suggest the grasshopper optimization algorithm (GOA) strategy, which incorporates the distance-vector hop (DVHop) and three-anchor methods. It displays its usefulness in terms of both overall localization accuracy and resistance to hostile attacks or malfunctioning nodes. Nonetheless, the incorporation of dead reckoning based on motion sensor data significantly enhances the precision of location estimates and bolsters the network's robustness against both faulty components and malicious agents.
Volume: 40
Issue: 1
Page: 461-479
Publish at: 2025-10-01

A comprehensive analysis of smartphones and tablets in graphic design and digital art

10.11591/ijeecs.v40.i1.pp146-155
Jirawat Sookkaew , Nakharet Chaikaew , Nakarin Chaikaew
This paper discusses how smartphones and tablets have changed creativity and graphic design. These portable tools and easy apps have transformed the creative process, allowing artists, designers, and students to create high-quality work anywhere. Mobile design apps promote creativity, accessibility, and skill development across broad user groups, according to the study. Unlike desktop tools, it addresses key constraints. Mobile apps sometimes struggle with smaller screens, restricted processing power, and reduced capabilities for complicated tasks like multi-layer editing and advanced graphics. These restrictions may inhibit expert designers working on complex, precise designs. Even Nevertheless, mobile technology like larger screens, stylus support, and cloud-based solutions are making mobile devices more feasible for creative work. The findings emphasise the relevance of integrating mobile technology into education and professional workflows and its complementarity to desktop solutions for resource-intensive jobs. In the developing digital landscape, our dual-platform approach maximizes creativity and flexibility.
Volume: 40
Issue: 1
Page: 146-155
Publish at: 2025-10-01

Optimal active disturbance rejection control with applications in electric vehicles

10.12928/telkomnika.v23i5.26867
Juan; Universidad Nacional de Colombia Quecan-Herrera , Sergio; Universidad Nacional de Colombia Rivera , Jorge; Purdue Univerity Neira-Garcia , John; Universidad Nacional de Colombia Cortés-Romero
This work proposes an optimal control strategy based on a modified active disturbance rejection control (ADRC) that considers disturbance weighting for a three-phase induction motor under rotor field-oriented control (FOC) to enhance energy efficiency. Induction motors (IMs) are widely used in electric vehicles (EVs) due to their cost-effectiveness and technological maturity. However, improving energy efficiency remains a key challenge, as it directly impacts vehicle range. The proposed approach employs ADRC, where part of the disturbance rejection task is handled offline by a hybrid optimization algorithm combining particle swarm optimization (PSO), tabu search (TS), and simulated annealing (SA) to tune a state-feedback controller. The controller parameters are optimized using a composite cost function that balances energy consumption and performance. Simulation and experimental results indicate that disturbance weighting has a significant impact on both problem complexity and performance. Optimal weighting improves the overall system response compared to conventional disturbance rejection methods. Energy and performance analyses show that disturbance weighting enhances energy usage compared to the traditional ADRC method, suggesting a novel efficiency control strategy for electric machines.
Volume: 23
Issue: 5
Page: 1427-1438
Publish at: 2025-10-01

A hybrid intelligent model for prediction of coronary artery diseases using TabNet and multiclass SVM

10.11591/ijeecs.v40.i1.pp156-163
Niveditha Honnemadu Rudreshgowda , Balakrishna Kempegowda , Anitha Sammilan
Cardiovascular disease is one of the significant fatality-causing diseases in this era by affecting the heart and blood vessels. Cardio diseases are classified into coronary heart disease (CHD), heart failure, valve disease, and arrhythmias. Medical diagnosis of heart disease and treating the patient is a challenging process, where early detection can lead to decreased fatality. In this research, hybrid model-based prediction of CHD detection is developed by TabNet and multiclass support vector machine (SVM). We created our datasets for experimentation by visiting the hospitals in the Mysore and Mandya regions of Karnataka, India. Datasets consist of 16 features; the features are pre-processed to normalize, encode, and handle missing values to extract the aggregate features using TabNet, and the multiclass SVM model is trained to classify the disease based on the classes. The proposed hybrid model prediction performance was evaluated using various metrics such as accuracy, recall, precision, and F1-score.
Volume: 40
Issue: 1
Page: 156-163
Publish at: 2025-10-01

Regulation of glucose insulin metabolism using feedback linearization

10.12928/telkomnika.v23i5.26408
Meriem; University of Sétif Samai , Ghedjati; University of Sétif Keltoum , Abdelaziz; University of Sétif Mourad
Diabetes is a chronic disease that occurs when the pancreas does not produce enough insulin, or when the body is not able to effectively use the insulin it produces. Insulin is a hormone that regulates blood sugar levels, this regulation is done by the pancreas. When this organ is damaged, the patient will have to regulate its blood sugar level themselves. This task is really painful and we will have to resort to an artificial pancreas or we will have to design a regulator which stabilizes blood sugar at its basal value. Several controls have been developed and the objective of this paper is to use input output linearization technique to regulate blood glucose levels by injecting an adequate quantity of insulin. The glucose insulin metabolism is a non-linear system whose input is the quantity of insulin to be injected and the output is the blood glucose measured in the blood. Simulations examples are given to demonstrate the usefulness of the command developed.
Volume: 23
Issue: 5
Page: 1385-1394
Publish at: 2025-10-01

Advanced image processing techniques for intelligent building environments using pattern recognition

10.12928/telkomnika.v23i5.26800
Mohanad A.; University of Anbar Al Askari , Iehab Abdul Jabbar; University of Anbar Kamil
The use of smart building environments, along with high-technology image processing and pattern recognition, is discussed within this paper. The study shows that the Canny edge detection algorithm is better than the Sobel operator in the edge clarity, continuity and accuracy in segmenting those edges, posting 92.7% of edge detection accuracy. Incorporating fuzzy logic, the hybrid Hough transform, and sophisticated segmentation techniques, like adaptive simple linear iterative clustering (SLIC) superpixel division, the study advances line detection and feature identification in the images of buildings. The variational autoencoder (VAE) and principal component analysis (PCA) help optimise the feature extraction substantially by retaining more than 93% variance at a lower dimension. In addition, adaptive Otsu thresholding and region-growing segmentation allow improving the segmentation accuracy, resulting in a significant increase in building detection F1 score from 77.3% to 89.6%. Irrespective of the Hough transform issues like noise sensitivity and over-joining, the results suggest computing process ideas that are computationally effective, scalable, and applicable in smart building systems. This study suggests extending the current advancement of hybrid models and incorporating them with the urban planning procedures, energy control, and building security systems.
Volume: 23
Issue: 5
Page: 1258-1270
Publish at: 2025-10-01

A proposed scheduling algorithm for real time application in 5G networks

10.12928/telkomnika.v23i5.26511
Moaath Saleh; University of Baghdad Abdulrahman , Buthaina Mosa; University of Baghdad Omran
The third-generation partnership developed the fifth-generation specifications to satisfy the expansion of mobile applications and the grown demand for extra data flow. As the real time services in 5G networks are widespread, professional scheduling algorithms are necessary to deal with the assignment of the scarce frequency resources among different categories of applications, ensuring the quality of service and improving the user experience. This paper proposes a real time flow scheduling algorithm by enhancing the scheduling metric to prioritize real time flows such as voice and video, particularly as the packet delay approaches its threshold time. The performance metrics of the proposed algorithm were evaluated and compared to three well-known algorithms, which are the modified largest weighted delay first, the exponential proportional fair, and the logarithmic rule. The simulation results, which was conducted by a dedicated software, showed that the proposed algorithm achieved up to 1.5 times the throughput of the other algorithms and resulted in less than half the video packets loss ratio compared to others, moreover, it offered a higher fairness index between users than other algorithms for video packets.
Volume: 23
Issue: 5
Page: 1155-1165
Publish at: 2025-10-01

DDoS attack detection using optimal scrutiny boosted graph convolutional and bidirectional long short-term memory

10.12928/telkomnika.v23i5.27046
Huda Mohammed; Urmia University Ibadi , Asghar Asgharian; Urmia University Sardroud
The distributed denial of service (DDoS) attack occurs when massive traffic from numerous computers is directed to a server or network, causing crashes and disrupting functionality. Such attacks often shut down websites or applications temporarily and remain among the most critical cybersecurity challenges. Detecting DDoS is difficult and must occur before mitigation. Recently, machine learning and deep learning (ML/DL) have been employed for detection; however, architectural limitations restrict their effectiveness against evolving attack methods. This paper presents a novel framework, scrutiny boosted graph convolutional–bidirectional long short-term memory and vision transformer (SBGC-BiLSTM-ViT), which integrates graph convolutional, BiLSTM, and ViT models with machine learning classifiers such as support vector machine (SVM), Naïve Bayes (NB), random forest (RF), and K-nearest neighbors (KNN). The integration enables autonomous extraction of critical features, enhancing precision in detecting and classifying DDoS attacks. To further boost performance, a Bayesian optimization algorithm (BOA) is applied for hyperparameter tuning of SBGC and ML methods. Evaluation on benchmark datasets UNSW-NB15 and CICDDoS2019 demonstrates that the proposed approach achieves higher accuracy and effectively identifies new DDoS variants, outperforming conventional methods.
Volume: 23
Issue: 5
Page: 1212-1227
Publish at: 2025-10-01

Cost-effective long-range secure speech communication system for internet of things-enabled applications

10.12928/telkomnika.v23i5.26884
Samer; German Jordanian University Alabed , Mohammad; American University of the Middle East Al-Rabayah , Bahaa; Yarmouk University Al-Sheikh , Lama Bou; Lebanese German University Farah
A new communication framework has been developed that allows voice transmission over long distances for internet of things (IoT) applications such as healthcare, smart cities, and remote monitoring in the least costly way and most secure manner. The system is based on long range (LoRa) technology and takes advantage of its spread spectrum technique, to provide long range transmission without the high-power requirements. The main limitation is LoRa’s bandwidth with a maximum throughput of 22 kbps for data. This presents a challenge for voice transmission communications. To address this shortened bandwidth issue, researchers developed an innovative compression solution that compresses voice data to less than 8 kbps to fit into LoRa’s capabilities. The compression allows for real practical voice communications and possibly can provide even greater distance than an uncompressed voice transmission update. The voice communications transmissions have cryptographic protection in place to protect the transmitted voice messages from unauthorized access.
Volume: 23
Issue: 5
Page: 1415-1426
Publish at: 2025-10-01

Lexicon-based comparison for suicide sentiment analysis on Twitter (X)

10.12928/telkomnika.v23i5.25711
Munawar; Esa Unggul University Munawar , Dwi; Universitas Esa Unggul Sartika , Fathinatul; Esa Unggul University Husnah
Suicidal individuals frequently share their desires on social media. As a result, it was determined that a learning machine for early detection of suicide issues on social media was required. This study aims to examine Twitter (X) users’ suicide-related sentiment expressions. The results of searching X for the keywords ‘suicide’, ‘wish to die’, and ‘want to commit suicide’ for 4 months yielded 5,535 tweets. Following the cleaning process, 2,425 tweets were collected. The findings of labeling with the lexicon-based valence aware dictionary and sentiment reasoner (VADER) and Indonesia sentiment (INSET) lexicon, which psychologists confirmed, revealed that VADER was more accurate (92.1%) than INSET (81.6%). Sentiment research reveals negative (86.4%), positive (11.1%), and neutral (2.5%) sentiment. Support vector machine (SVM), K-nearest neighbor (KNN), and Naïve Bayes modeling results show accuracy above 86%, with SVM having the best accuracy (87.65%). Because of its great accuracy, this model can be used to identify and analyze suspicious behavior relating to suicide on X. Further research is still required, despite the excellent identification of early indicators of suicide ideation from social media posts.
Volume: 23
Issue: 5
Page: 1314-1322
Publish at: 2025-10-01

Enhanced torque control for horizontal-axis wind turbines via disturbance observer assistance

10.12928/telkomnika.v23i5.26805
Edwin; Fundación Universitaria Los Libertadores Villarreal-Lopez , Horacio; Universidad de San Buenaventura Coral-Enriquez , Sergio; Samara National Research University Tamayo-Leon
This paper presents an enhanced control strategy for optimizing energy capture in horizontal axis wind turbines operating in the partial-load region (region 2). The proposed approach builds upon conventional standard torque control (STC) by incorporating a generalized extended state observer (GESO) that follows the active-disturbance-rejection paradigm. Although traditional torque control methods have proven effective under steady wind conditions, they often lack robustness against disturbances, system faults, and model uncertainties inherent in wind energy systems. The proposed observer-assisted control scheme addresses these limitations by estimating and compensating for total disturbance signals, including non-modeled dynamics, parameter uncertainties, and actuator faults. The effectiveness of the proposed control strategy is validated through comprehensive simulations using a 5 MW wind turbine model subjected to realistic operational conditions. Simulation scenarios include turbulent wind speed profiles and actuator degradation to assess controller performance. The results demonstrate improved robustness and energy capture efficiency compared to the conventional control approach, while maintaining the simplicity of the implementation. This work contributes to the development of more reliable wind energy conversion systems (WECSs) by offering a practical solution that improves both performance and fault tolerance in partial load operation.
Volume: 23
Issue: 5
Page: 1395-1403
Publish at: 2025-10-01

A dual-band modified-rectangular patch with parasitic antenna for 2.4/5 GHz wireless local area network applications

10.12928/telkomnika.v23i5.27055
Suthasinee; Rajamangala University of Technology Isan Khonkaen Campus Lamultree , Sakolkorn; Rajamangala University of Technology Isan Khonkaen Campus Ungprasutr , Charinsak; Rajamangala University of Technology Isan Khonkaen Campus Saetiaw , Chuwong; King Mongkut’s Institute of Technology Ladkrabang Phongcharoenpanich
This research presents the design and implementation of a dual-band patch antenna (DBPA) optimized for 2.4 GHz and 5 GHz wireless local area network (WLAN) applications. The antenna features a modified rectangular patch with a cut corner and two parasitic rectangular patches, enabling dual-band operation with enhanced gain. The DBPA is fed by a 50-Ohm coplanar waveguide and fabricated on a single-layer copper circuit board using a flame-retardant 4 substrate with a relative permittivity of 4.3 and a thickness of 1.6 mm. A prototype with compact dimensions of 0.040×0.040×0.0009 λ³ was constructed and experimentally evaluated. Measurements reveal a nearly omnidirectional radiation pattern, achieving peak gains of 2.92 dBi at 2.4 GHz and 4.25 dBi at 5 GHz. The antenna demonstrates a wide 10 dB return loss bandwidth of 67.7% (1.7–3.44 GHz) for the lower band and 56% (4.59–8.16 GHz) for the upper band. The strong agreement between simulated and measured results validates the design’s potential for practical and scalable implementation. This DBPA design offers a simpler, more compact, and wider-bandwidth alternative to conventional antennas, making it ideal for modern WLAN systems.
Volume: 23
Issue: 5
Page: 1177-1187
Publish at: 2025-10-01

A multi-path routing protocol for IoT-based sensor networks

10.11591/ijeecs.v40.i1.pp225-235
Udaya Suriya Rajkumar Dhamodharan , Krishna Prasad Karani , Saranya Pichandi , Kavitha Palani , Sathiyaraj Rajendran
Internet of things (IoT) based sensors are to link a big number of low-cost and power-integrated devices in a reliable manner. Numerous military and adventurous applications are regulated by communication among IoT sensors. The multi-path routing protocol (MRP) approach presented in this research to enhance secure routing in IoT sensors is significant. This technique makes use of data transfer routing and the relationships between network components. It finds the most efficient route between the nodes that minimizes communication overhead and is both reliable and economical in terms of shortest duration. The particle swarm optimization (PSO) technique is used to find the shortest path that is most cost-effective. To reach the target node, end-to-end data transmission must transit via intermediary nodes, which are provided by the routing path node history. The optimal path is chosen by MRP from PSO, and it traces the path to identify the intermediate nodes. In the unlikely event of a crisis, MRP offers the most affordable backup route for data transfer. When compared to earlier techniques, the outcomes of these current approaches enhance network efficiency, balance energy consumption among nodes, and routing attacks.
Volume: 40
Issue: 1
Page: 225-235
Publish at: 2025-10-01
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