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29,082 Article Results

Low-power and reduced delay in inverter and universal logic gates using Hvt-FinFET technology

10.11591/ijece.v15i6.pp5193-5204
Veerappa Chikkagoudar , G. Indumathi
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.
Volume: 15
Issue: 6
Page: 5193-5204
Publish at: 2025-12-01

Design and performance analysis of an NSFET-based biosensor for the early detection of dengue

10.11591/ijece.v15i6.pp5183-5192
Tulasi Radhika Patnala , Madhavi Tatineni
Healthcare industry is changing due to technological breakthroughs that spur creative methods for diagnosing and treating illnesses. This study examines the development of nanowire-based stacked field-effect transistor (NSFET) biosensors for the early detection of dengue virus. Dengue fever is severe threat to public health and a flavivirus spread by mosquitoes. About half of the global population is at risk due to an endemic illness in tropical and subtropical regions, which affects approximately 100 million individuals annually in 130 countries. The virus has four antigenically distinct serotypes, and there may be a fifth. These serotypes induce variety of clinical symptoms. This can include benign infections that go away on their own or extremely serious, potentially fatal consequences like organ failure, plasma leakage, and bleeding. While many techniques are now used to diagnose dengue fever in the laboratory, no single technique satisfies the optimum standards for speed, economy, sensitivity, specificity. To close this gap in dengue diagnosis, newer detection technologies are desperately needed. This ultrasensitive label-free electrical device can detect the dengue virus (DENV) early on and prevent severe additional harm to humans. To detect various DENV concentrations in human blood and demonstrate potential for eventual point-of-care (POC) detection, NSFET constructed and simulated in this work.
Volume: 15
Issue: 6
Page: 5183-5192
Publish at: 2025-12-01

Impact of outlier detection techniques on time-series forecasting accuracy for multi-country energy demand prediction

10.11591/ijece.v15i6.pp5067-5079
Shreyas Karnick , Sanjay Lakshminarayanan , Madhu Palati , Prakash R
Accurate energy demand prediction is crucial for efficient grid management and resource optimization, particularly across multiple countries with varying consumption patterns. However, real-world energy demand data often contains outliers that can distort forecasting accuracy. This study evaluates the impact of five outlier detection techniques—Z-Score, density- based spatial clustering of applications with noise (DBSCAN), isolation forest (IF), local outlier factor (LOF), and one-class support vector machine (SVM)—on the performance of three time-series forecasting models: long short-term memory (LSTM) networks, convolutional neural network (CNN) Autoencoders, and LSTM with attention mechanisms. The models are tested using energy demand data from four European countries— Germany, France, Spain, and Italy—derived from real-time consumption records. A comparative analysis based on root mean squared error (RMSE) demonstrates that incorporating outlier detection significantly enhances model robustness, reducing forecasting errors caused by anomalous data. The findings emphasize the importance of selecting appropriate outlier detection strategies to improve the accuracy and reliability of energy demand forecasting. This research provides valuable insights into the trade-offs involved in outlier removal, with implications for policy and operational practices in energy management.
Volume: 15
Issue: 6
Page: 5067-5079
Publish at: 2025-12-01

SGcoSim: a co-simulation framework to explore smart grid applications

10.11591/ijece.v15i6.pp5106-5118
Abdalkarim Awad , Abdallatif Abu-Issa , Peter Bazan , Reinhard German
Under the smart grid concept, new novel applications are emerging. These applications make use of information and communication technology (ICT) to help the electrical grid run more smoothly. This paper introduces SGcoSim, a co-simulation framework that integrates power system modeling and data communication to enhance smart grid applications. The framework utilizes OpenDSS for simulating power distribution components and OMNeT++ for communication modeling, enabling real-time peer-to-peer interactions via wireless sensor network (WSN) techniques. Virtual cord protocol (VCP) is deployed for efficient routing and data management within the field area network. SGcoSim’s functionality is demonstrated through two case studies: a phasor measurement unit (PMU)-based wide-area monitoring system and an integrated volt/VAR optimization with demand response (IVVO-DR) application. Results indicate significant reductions in energy consumption and power losses, highlighting the capabilities of SGcoSim.
Volume: 15
Issue: 6
Page: 5106-5118
Publish at: 2025-12-01

Optimal design, decoding, and minimum distance analysis of Goppa codes using heuristic method

10.11591/ijece.v15i6.pp5411-5421
Bouchaib Aylaj , Said Nouh , Mostafa Belkasmi
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.
Volume: 15
Issue: 6
Page: 5411-5421
Publish at: 2025-12-01

The effect of dramatic play on early literacy: an experimental study

10.11591/ijere.v14i6.26607
Fatih Mehmet Aslan , Yasemin Yüzbaşıoğlu , Ayşe Alptekin , Ayşegül Sarıkaya
In line with the theories of Piaget and Vygotsky, the aim of the present study is to examine the effect of the dramatic play activities program on the early literacy skills of preschool children. The study is based on an experimental research design with pretest-posttest and control group. While the dependent variable of the study is children’s early literacy skills, the independent variable is dramatic play activity. Early literacy test (EROT) was used as data collection tool. The participants of the present study consist of 32 children divided equally as the participants of the experimental and control group. The age of the children is between 63-72 months. The children in the experimental group participated in a program of dramatic play activities over a period of 10 weeks, 5 days each week, 2 hours daily for 100 hours in total. Analysis of covariance (ANCOVA), t-test, and descriptive statistics were used in the analysis of the data. In line with the data obtained in the present study, dramatic play activity program positively affects the early literacy skills of preschool children in terms of receptive language and expressive language vocabulary acquisition, naming skills, functional knowledge, and listening comprehension skills.
Volume: 14
Issue: 6
Page: 5029-5037
Publish at: 2025-12-01

Exploring cookies vulnerabilities: awareness, privacy risks and exploitation

10.11591/ijece.v15i6.pp5792-5803
Nor Anisah Amir Hamzah , Anis Safiyyah Adnan , Norsaremah Salleh
This study investigates cookie vulnerabilities, focusing on awareness, privacy risks, and exploitation techniques. We used a mixed-method approach that combines insights from a survey study and a systematic mapping study of 27 papers from online databases to comprehensively address the research topic. The results show a moderate level of user awareness about cookie-related privacy risks, with significant concerns over user tracking and profiling, identified in 88% of the reviewed studies. Key risks include sensitive data exposure, privacy and consent issues, targeted advertising, ineffective mitigation measures, and cyberattacks. Tracking via cookies, and especially third-party cookies were found to pose the greatest risk to end-users. Their widespread use for cross-site tracking and extensive fingerprinting often occurred without users’ awareness or explicit consent. These insights suggest the need for stricter privacy laws, better practices on cookies, and improved user awareness to mitigate concerning risks.
Volume: 15
Issue: 6
Page: 5792-5803
Publish at: 2025-12-01

Enhanced matrix pencil method for robust and efficient direction of arrival estimation in sparse and multi-frequency environments

10.11591/ijece.v15i6.pp5380-5387
Ashraya A. N. , Punithkumar M. B.
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.
Volume: 15
Issue: 6
Page: 5380-5387
Publish at: 2025-12-01

Flow-guided long short-term memory with adaptive directional learning for robust distributed denial of service attack detection in software-defined networking

10.11591/ijece.v15i6.pp5484-5496
Huda Mohammed Ibadi , Asghar A. Asgharian Sardroud
A software-defined networking (SDN) architecture is designed to improve network agility by decoupling the control and data planes, but while much more flexible, also makes networks more vulnerable to threats, such as distributed denial of service (DDoS) attacks. In this study we present a novel detection model, the flow-guided long short-term memory (LSTM) network with adaptive directional learning (ADL), for the mitigation of DDoS attacks in software defined networking (SDN) environments. While the methodology is based on a flow direction algorithm (FDA), which analyzes traffic patterns and detects anomalies from directional flow behavior. The proposed method integrates FDA in LSTM-based threat detection frameworks within internet of things (IoT) networks, thereby yielding enhanced detection accuracy, as well as a real-time security threat response. The experimental evaluation on two benchmark datasets, namely the InSDN dataset and a real-time dataset utilizing a Mininet and POX controller setup, shows that a detection rate of 99.85% and 99.72%, respectively, thereby showcasing the proposed model’s ability to differentiate between legitimate and malicious network traffic.
Volume: 15
Issue: 6
Page: 5484-5496
Publish at: 2025-12-01

Enhancing system integrity with Merkle tree: efficient hybrid cryptography using RSA and AES in hash chain systems

10.11591/ijece.v15i6.pp5679-5689
Irza Nur Fauzi , Farikhin Farikhin , Ferry Jie
An analysis is conducted to address the growing threats of data theft and unauthorized manipulation in digital transactions by integrating \structures within hash chain systems using hybrid cryptography techniques, specifically Rivest-Shamir-Adleman (RSA) and advanced encryption standard (AES) algorithms. This approach leverages AES for efficient symmetric data encryption and RSA for secure key exchanges, while the hash chain framework ensures that each data block is cryptographically linked to its predecessor, reinforcing system integrity. The Merkle tree structure plays a crucial role by allowing precise and rapid detection of unauthorized data changes. Empirical analyses demonstrate notable improvements in both the efficiency of cryptographic processes and the robustness of data validation, underscoring the method’s applicability in high data throughput environments such as educational institutions. This research makes a substantive contribution to information security by offering a sophisticated solution that strengthens data protection practices, ensuring greater resilience against increasingly sophisticated data threats.
Volume: 15
Issue: 6
Page: 5679-5689
Publish at: 2025-12-01

Evaluating clustering algorithms with integrated electric vehicle chargers for demand-side management

10.11591/ijece.v15i6.pp5837-5846
Ayoub Abida , Redouane Majdoul , Mourad Zegrari
The integration of electric vehicles (EVs) and their effects on power grids pose several challenges for distribution operators. These challenges are due to uncertain and difficult-to-predict loads. Every electric vehicle charger (EVC) has its specific pattern. This challenge can be addressed by clustering methods to determine EVC energy consumption clusters. Demand side management (DSM) is an effective solution to manage the incoming load of EVs and the large number of EVCs. Considering the challenges of peak consumptions and valleys, the adoption of vehicle-to-grid (V2G) technology requires mastering load clusters to develop energy management systems for distributors. This work used clustering algorithms (K-means, DBSCAN, C-means, BIRCH, Mean-Shift, OPTICS) to identify load curve patterns, and for performance evaluation of algorithms, it worked on metrics like the Silhouette coefficient, Calinski-Harabasz index (CHI), and Davies-Bouldin index (DBI) to evaluate results. C-means achieves the best overall clustering performance, evidenced by the highest Silhouette coefficient (0.30) and a strong Calinski-Harabasz score (543). Mean-Shift excels in the Davies-Bouldin Index (1.13) but underperforms on other metrics. BIRCH provides a balanced approach, delivering moderate results across evaluated metrics.
Volume: 15
Issue: 6
Page: 5837-5846
Publish at: 2025-12-01

Enhanced ankle physiotherapy robot with electromyography - triggered ankle velocity control

10.11591/ijece.v15i6.pp5314-5326
Dimas Adiputra , Radithya Anjar Nismara , Muhammad Rafli Ramadhan Lubis , Nur Aliffah Rizkianingtyas , Kensora Bintang Panji Satrio , Rangga Roospratama Arif , Annisa Salsabila
Previous ankle physiotherapy robots, called picobot rely on predefined trajectories continuous passive movement without considering patient intent, limiting the encouragement of user-intent motion. This study then integrates electromyography (EMG) signals as triggers into picobot with an ankle velocity-based control system. The upgraded robot activates movement in specific gait phases based on muscle activity, synchronizing therapy with the patient’s intent. Functionality test on 7 young male healthy subjects investigates leg muscles, such as Tibialis Anterior, Soleus, and Gastrocnemius muscles for the most significantly contribute to ankle movements. Then, the muscle is tested to trigger picobot movements. Functionality tests revealed the Tibialis muscle significantly contributes to gait phases 2, the Soleus is prominent in phases 3 and 4, and gastrocnemius is active on phase 1. The robot successfully performs plantarflexion when EMG signals exceed a 1.58 V threshold, reaching a target position of -0.11 rad at a constant velocity of -0.62 rad/s. These findings establish a foundation for future trials since patient testing has not yet been conducted. By promoting active participation, this innovation has the potential to enhance rehabilitation outcomes. Incorporating user-intent triggers may accelerate recovery and improve healthcare accessibility in Indonesia, offering a significant advancement in physiotherapy technologies.
Volume: 15
Issue: 6
Page: 5314-5326
Publish at: 2025-12-01

Optimization of water resource management in crops using satellite technology and artificial intelligence techniques

10.11591/ijece.v15i6.pp5847-5853
Erick Salvador Reyes-Galván , Fredy Alexander Bolivar-Gomez , Yeison Alberto Garcés-Gómez
This study aims to optimize water consumption in avocado crops through the application of satellite technology, machine learning algorithms, and precise climate data from the climate hazards group infrared precipitation with stations (CHIRPS) system. Crop classification in satellite images is conducted using the random forest algorithm, enabling detailed categorization of cultivated areas, urban land, soil, and vegetation, with a specific focus on avocados due to their high-water demand. Given its economic importance and status as one of the most water-intensive crops, avocado cultivation presents a critical challenge for agricultural sustainability. To validate predictive models and ensure classification accuracy, advanced evaluation methodologies such as the confusion matrix and Cohen's kappa index are utilized, quantifying the precision and reliability of the results. This estimation of water consumption under deficit and surplus conditions offers key insights for efficient water management in avocado cultivation. The results generated can enhance agricultural efficiency by aligning water use with the crop’s actual requirements, thereby contributing to the reduction of its water footprint.
Volume: 15
Issue: 6
Page: 5847-5853
Publish at: 2025-12-01

Trends of unmanned aerial vehicles in smart farming: a bibliometric analysis

10.11591/ijece.v15i6.pp5746-5758
Alfred Thaga Kgopa , Sikhosonke Manyela , Bessie Baakanyang Monchusi
This paper presents a review of the trends of unmanned aerial vehicles (UAV) in agriculture using a bibliometric analysis. This bibliometric analysis shows that 1676 articles were accessed from the Elsevier Scopus database between 2013 and 2023. Our findings indicate research related to UAVs in agriculture has surged over the years, but the adoption and acceptance of smart farming technology in sub-Saharan Africa remains inert. This study employed VosViewer in data analysis and bibliometrics. Our findings show that China leads all countries and followed by the United States on UAV publications in smart farming research foci. Our findings indicate that UAVs are impactful in improving crop growth, crop health monitoring, and may be beneficial to small-holder farmers with increased yields. We recommend that sub-Saharan Africa nations accelerate collaboration with China and United States in advancing climate smart agriculture practices to mitigate food insecurity risks.
Volume: 15
Issue: 6
Page: 5746-5758
Publish at: 2025-12-01

Designing, developing and analyzing of a rectangular-shaped patch antenna at 3.5 GHz for 5G applications at S band

10.11591/ijece.v15i6.pp5422-5432
Sukanto Halder , Md. Sohel Rana , Md Abdul Ahad , Md. Shehab Uddin Shahriar , Md. Abdulla Al Mamun , Md. Mominur Rahaman , Omer Faruk , Md. Eftiar Ahmed
This research study focuses on the design and analysis of two distinct patch antennas for 5G applications at 3.5 GHz. Rogers RT5880 served as the foundational material for antenna designs I and II. A 50 Ω feed line is utilized to supply both antennas. According to the calculations, Design I exhibits a reflection coefficient (S11) of -32.98 dB, a voltage standing wave ratio of 1.045, a gain of 7.81 dBi, an efficiency of 89.2%, and a surface current of 66.82 A/V. Design II has a reflection coefficient (S11) of 34.98 dB, voltage standing wave ratio (VSWR) of 1.036, gain of 8.78 dBi, efficiency of 89.87%, and surface current of 62.7 A/V. Among the two antenna designs, design II outperformed design I, and the results indicate that the antenna fulfilled the designated purpose. The novelties of the proposed paper are to design two different patch antennas using same materials and highlight the performance of the design parameters. Design II is proficient in supporting 5G services owing to its advantageous performance. In addition, S11 of the antenna is reduced to bring the VSWR value is close to 1. Also, improve gain, directivity and efficiency by bringing the antenna impedance matching close to 50 Ω.
Volume: 15
Issue: 6
Page: 5422-5432
Publish at: 2025-12-01
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