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AlGaN/GaN MSM UV photodetector without and with BGaN back-barrier layer comparison study by SILVACO-TCAD

10.11591/ijeecs.v40.i2.pp590-600
Aicha Benyettou , Abedelkader Hamdoune , Belkacem Benadda , Djamal Lachachi
Using DevEDIT and atlas under SILVCAO-TCAD, we were able to achieve high photodetector metal-semiconductor-metal (MSM) AlGaN/GaN/BGaN performance with high electronic mobility. Our device demonstrated a sensitivity of 286 (I illumination/I dark) at Vanode 20V with an illumination current of 26 mA, a photocurrent of 1.56e-7 A at a wavelength of 0.350 µm, and an appropriate efficiency value of 87% without BGaN, and we also studied the influence of the boron B0.03Ga0.97N back-barrier layer. As a result, we obtain a sensitivity of 293,4 at Vanode 20V with an illumination current of 27 mA, a photocurrent of 1,85e-7 A at a wavelength of 0.350 µm, and an appropriate efficiency value of 90%. Additionally, this type of photodetector has been effectively created to detect UV light in the 100–450 nm range, and it may find value in both medical and military settings. Astronomical, medical diagnostics, environmental sensing, remote sensing, thermal imaging, optical signal detection, night vision cameras, missiles, and target tracking.
Volume: 40
Issue: 2
Page: 590-600
Publish at: 2025-11-01

Interactive multimedia e-collaboration for innovative linguistics education

10.11591/ijeecs.v40.i2.pp1149-1157
Syarifa Rafiqa , Nofvia De Vega , Arifin Arifin
This study aims to investigate the needs of students and lecturers regarding interactive multimedia resources in linguistics at the Faculty of Teacher Training and Education, Universitas Borneo Tarakan, to facilitate further development. The findings reveal a significant gap between current instructional provisions and the specific needs of students and faculty, highlighting the necessity for pedagogical innovation to enhance interaction and understanding in linguistics. Utilizing a mixed-methods approach, the research included surveys and interviews with participants in linguistics courses. Results indicated that 86% of students sought in-depth knowledge of linguistics, and 73% felt that existing support was inadequate. It underscores a high demand for a focus on selected topics, simplified explanations, and multimedia interactivity. The findings demonstrate that instructional materials are poorly aligned with teaching needs, negatively impacting educational methodologies and failing to effectively address students' relevant needs. The implications of this study extend to practice and further research, urging faculty members to increasingly integrate multimedia elements into their teaching and develop tailored resources based on identified needs. Newly created materials should undergo practical evaluation to enhance student satisfaction and performance in linguistics studies.
Volume: 40
Issue: 2
Page: 1149-1157
Publish at: 2025-11-01

Interpretable federated deep learning models for predicting gait dynamics in biomechanics

10.11591/ijeecs.v40.i2.pp1087-1099
Shaik Sayeed Ahamed , Akram Pasha , Syed Ziaur Rahman , D. N. Puneeth Kumar
Accurate prediction of human joint angle dynamics and reliable gait classifica tion are essential for applications in rehabilitation, biomechanics, and clinical monitoring. Traditional machine learning (ML) models trained on centralized data raise concerns about privacy, scalability, and transparency. This study proposes a federated deep learning (DL) framework that integrates privacy preserving model training with interpretable predictions. Specifically, a gated recurrent unit- deep neural network (GRU-DNN) hybrid model is developed for regression of joint angles, while a Long short-term memory- convolutional neural network (LSTM-CNN) hybrid model is designed for binary and multi class gait classification. The framework is deployed using the federated av eraging (FedAvg) algorithm across simulated clients, with each client training locally on its data. To enhance interpretability, the local interpretable model agnostic explanations (LIME) algorithm is integrated at the client level to gener ate human-understandable explanations for model predictions. The experimen tal results demonstrate significant improvements, including a reduction in global mean squared error (GMSE) from 56.16 to 3.31 and an increase in R-squared score from 0.80 to 0.99 for regression, along with classification accuracies of 0.97 (binary) and 0.94 (multi-class). This scalable, privacy-preserving frame work bridges the gap between accuracy and transparency, offering impactful applications in biomechanics, healthcare, and personalized medicine.
Volume: 40
Issue: 2
Page: 1087-1099
Publish at: 2025-11-01

End-to-end system for translating bahasa isyarat Indonesia sign language gestures into Indonesian text

10.11591/ijeecs.v40.i2.pp719-734
Satria Putra , Erdefi Rakun
This study addresses critical challenges in developing an end-to-end bahasa isyarat Indonesia (BISINDO) SLT by integrating advanced deep learning techniques to overcome complex background interference, transitional gesture recognition, and limitations in dataset availability. While existing SLT systems struggle with isolated word recognition and manual preprocessing, our work introduces three key innovations: (1) implementation of YOLOv8 for optimized object detection, achieving 88% mAP and reducing WER to 11.40%, outperforming YOLOv5/v7 in handling complex backgrounds; (2) automated removal of transitional gestures using Threshold conditional random fields (TCRF), which attained 95.68% accuracy, significantly improving upon MobileNetV2’s performance (WER: 6.89% vs. 93.53%); and (3) end-to-end BISINDO SLT by expansion of the BISINDO dataset to 435 word labels, enabling comprehensive sentencelevel translation. Experimental results demonstrate the system’s robustness, with 8.31% of WER, 84.13% of SAcc, and 87.08% of SacreBLEU after dataset expansion and redundancy elimination through grouping methods. The proposed framework operates without manual intervention, marking a substantial advancement toward real-world applicability.
Volume: 40
Issue: 2
Page: 719-734
Publish at: 2025-11-01

Improving recommendations with implicit trust propagation from ratings and check-ins

10.11591/ijeecs.v40.i2.pp814-828
Sara Medjroud , Nassim Dennouni , Mourad Loukam
This paper investigates how the propagation of implicit trust between users affects the quality of point-of-interest (POI) recommendations in location-based social networks (LBSNs). Through the analysis of user interactions via ratings and check-ins, this work proposes a recommendation model known as propagation of rating/check-in for implicit trust (PRCT). This model relies on two primary approaches: Similarity trust rating (STR), which utilizes user ratings, and similarity trust check-in (STC), which focuses on check-ins data. Both approaches employ trust propagation to enhance their similarity matrices between users. An evaluation of the PRCT model using the Yelp dataset shows that the STR approach surpasses other variants in terms of PRECISION and RECALL, while the STC approach demonstrates superior performance in terms of RMSE. Furthermore, while trust propagation in the PRCT model increases the density of its similarity matrices, it does not consistently enhance its PRECISION parameter. Only the similarity Jaccard check-in (SJC) and similarity cosine check-in (SCC) approaches show a significant improvement of this parameter. 
Volume: 40
Issue: 2
Page: 814-828
Publish at: 2025-11-01

Automatic wildlife species identification on camera trap images using deep learning approaches: a systematic review

10.11591/ijeecs.v40.i2.pp968-977
Siyabonga Mamapule , Bukohwo Michael Esiefarienrhe , Ibidun Christiana Obagbuwa
The foundation of systematic research depends on precise species identification, functioning as a critical component in the processes of biological research. Wildlife biologists are prompting for more effective techniques to fulfill the expanding need for species identification. The rise in open source image data showing animal species, captured by digital cameras and other digital methods of collecting data, has been monumental. This rapid expansion of animal image data, integrated with state-of-the-art machine learning techniques such as deep learning which has shown significant capabilities for automating species identification. This paper focuses on the role of deep neural network architectures in furthering technological advancements in automating species identification in recent years. To advocate further investigation in this field, an examination of machine learning architectures for species identification was presented in this work. This examination focuses primarily on image analyses and discusses their significance in wildlife conservation. Fundamentally, the aim of this article is to offer insights into the present advancements in automating species identification and to act as a reference for scholars who are keen to integrate machine learning techniques into ecological studies. Systems designed through Artificial Intelligence are extensive in providing toolkits for systematic identification of species in the upcoming years.
Volume: 40
Issue: 2
Page: 968-977
Publish at: 2025-11-01

Generalized domain tutoring framework for AI agents with integrated explainable AI techniques

10.11591/ijeecs.v40.i2.pp860-870
László Csépányi-Fürjes , László Kovács
This paper proposes a novel approach to integrate tutoring functionality into AI systems to counteract the potential decline of human intelligence caused by AI-driven over-automation. Existing explainable AI methods primarily emphasize transparency while lacking inherent educational functionality. Consequently, users are essentially left as passive recipients of AI-driven decisions without any structured learning mechanism in place. To address this, this paper introduces the knowledge-sharing-bridge (KSB), a component designed to transform AI into an active tutor. Unlike traditional intelligent tutoring systems (ITS), which operate separately from AI decision-making processes, the KSB is embedded within AI frameworks, ensuring continuous and context-aware learning opportunities. The proposed framework uses structured knowledge representation tools, such as category maps and word-clouds, to improve the user’s understanding of the decisions made by the AI systems. Prototype implementation demonstrates how these elements work together to provide real-time, interactive learning experiences. The results indicate that integrating KSB into AI enhances both explainability and user learning. This approach promotes a more in-depth interaction with AI insights and enables AI systems to become lifelong learning companions, closing the gap between automation and education.
Volume: 40
Issue: 2
Page: 860-870
Publish at: 2025-11-01

Adoption of virtual tours for tourism promotion in Tegal Regency: a technology acceptance model analysis

10.11591/ijeecs.v40.i2.pp1109-1120
Dairoh Dairoh , Sharfina Febbi Handayani , Dwi Intan Af'idah
Tegal Regency has various tourist attractions that have the potential to be increased as a stimulus for the district's economy. So that this potential can have an optimal positive impact, the tourist destination should be promoted to the general public to increase tourism visits. This effort can be carried out by utilizing existing technological developments through virtual tour (VT), but their implementation requires careful consideration. This study explored how perceived usefulness (PU), perceived ease of use (PEU), attitude, behavioral intention (BI), and tourism promotion (TP) relate to each other within the context of virtual tourism. Data were collected from 126 participants via an an online survey developed using the technology acceptance model (TAM) framework. The partial least squares structural equation modeling (PLS-SEM) method was employed for analyzing the data. The result revealed significant relationships between PU and ease of use, user attitudes (AT), and BIs. Furthermore, BI, PU, and PEU were all considerable predictors of TP. However, no significant relationship was found between user AT and BIs.
Volume: 40
Issue: 2
Page: 1109-1120
Publish at: 2025-11-01

Enhancing cross-cutting concerns in the internet of things with applying aspect oriented programming

10.11591/ijres.v14.i3.pp745-753
Khalifa Fatiha , Guelta Bouchiba
Aspect oriented programming (AOP) is a new programming model that provides new concepts to handle cross-cutting concerns about code. The idea of introducing AOP in the internet of things (IoT) is inherited from the complexity of sensor operations involving data acquisition, processing, and communication, the need to support multiple simultaneous services for users particularly security services such as authentication, authorization, data traceability, and transaction management, and the challenges posed by the IoT deployments, the treatment of these data volumes lead to problematic code redundancy and cross-cutting concerns that compromise system maintainability. In this context, AOP enables the separation of core functionalities, data management, and cross-cutting concerns, allowing them to be developed and reused independently within the same codebase. To address these issues, this paper proposes an AOP model for IoT systems based on the Petri net representations. The model strategically integrates the core AOP advantages of modularity, reusability, and extensibility, microservices based architectural decomposition and specialized handling of sensor-specific requirements in IoT environments.
Volume: 14
Issue: 3
Page: 745-753
Publish at: 2025-11-01

Room energy management utilizing internet of things technology for decreasing electricity consumption

10.11591/ijres.v14.i3.pp734-744
Winasis Winasis , Suroso Suroso , Azis Wisnu Widhi Nugraha , Priswanto Priswanto
This paper proposes a novel internet of things (IoT)-based control system for energy management to reduce electricity consumption from the two most dominant loads in buildings: air conditioners (AC) and lighting. The proposed system provides a comprehensive operational control strategy that integrates scheduling, human detection, ambient temperature, and light intensity for optimal room-level energy management employed. The proposed system employs wireless fidelity (WiFi)-enabled temperature, presence, and light sensors for comprehensive room conditions monitoring. Additionally, a WiFi-connected infrared module serves as an actuator to regulate the AC unit. Testing results demonstrate compelling energy savings, achieving up to 36% for the AC and 72% for the lighting while maintaining a comfortable indoor environment. These results were obtained from an experimental test in a private room within a residence over an 8-hour daytime period with 50% occupancy time. The proposed IoT system offers a highly effective and easily deployable solution for sustainable energy reduction in residential settings.
Volume: 14
Issue: 3
Page: 734-744
Publish at: 2025-11-01

The impacts of optical display BaF2-Ce materials on solid-state lighting

10.11591/ijres.v14.i3.pp717-724
Luu Hong Quan , Nguyen Thi Phuong Loan
Transparent ceramic doped with barium fluorid cerium (BaF2-Ce) was created via a sintering method and its brightness and scintillation characteristics were examined. The luminescence is associated with the 5d-4f transitions in the Ce3+ ion and exhibits emitting maxima at 310 and 323 nm. For Na-22 radioisotopes, photo-maximum at 511 keV and 1274 keV were achieved using translucent ceramic BaF2-Ce. The translucent ceramic BaF2-Ce has been determined to have a power resolution of 13.5% at 662 keV. A luminescent production rate was measured for the BaF2-Ce (0.2%) ceramic, which is similar to sole crystal. Calculations of the scintillation degradation period beneath 662 keV gamma stimulation reveal a quick part of 58 ns and a somewhat sluggish part of 434 ns. The more gradual part in BaF2-Ce(0.2%) ceramic is linked to the dipole-dipole power transmission from the host structure to the Ce3+ luminous core and is quicker comparing to self-trapped excitons (STE) emitting in BaF2 host. BaF2-Ce offer various qualities, including significant illumination output, rapid degradation duration, and rapid scintillating reaction, which are desirable for many global fields such as medicine, radiation detection, industrial systems and nuclear safety.
Volume: 14
Issue: 3
Page: 717-724
Publish at: 2025-11-01

SPARTAN–field programmable gate array implementation for analog waveforms generation by direct digital synthesis

10.11591/ijres.v14.i3.pp597-604
Moulai Khatir Ahmed Nassim , Ziani Zakarya
In the last thirty years, low power field programmable gate arrays (FPGAs) becoming more commonly used to implement a countless of applications in different electronics industry domains. Due to their flexible design, strong compatibility, parallel computing, and compared to the CPU architecture, FPGA accentuate computing efficiency and con sidered as one of the devices with the lowest application risk and the shortest development cycle among the variety of available programmable circuits families. This article details the design and implementation of a direct digital synthesis (DDS) signal generator using the Spartan-6 FPGA, focusing on high-quality sine wave generation. The system utilizes look-up tables (LUTs) and Block RAM (BRAM) for efficient storage and retrieval of sine wave data, while an 8-bit DAC0808 digital-to-analog converter (DAC) ensures precise waveform output. The FPGA's reconfigurable architecture allows real-time adjustments of frequency and phase, making the design suitable for various signal processing applications and modulation techniques like binary phase shift keying (BPSK).
Volume: 14
Issue: 3
Page: 597-604
Publish at: 2025-11-01

The novel single-module communication subsystem architecture for industrial digital inkjet

10.11591/ijres.v14.i3.pp696-704
Maksim Popov , Aleksandr Romanov
The typical challenge in embedded hardware development is the data transfer subsystem. As long as the required speeds are low and high latency is acceptable, there is quite a simple solution with serial bus like controller area network (CAN). In case of high speed (hundreds of megabits per second) with the high temporal determinism, the solution becomes significantly more complicated, requiring expensive components and growing complexity of the embedded software/firmware. We consider industrial inkjet as an example. The device typically includes moving carriage (with printheads) to jet along the media. Existing solutions use optical fiber cable or shielded twisted pair (STP) cable to connect modules. So, additional physical and logical devices are required (for example, for buffering or serial-to-parallel data conversion). For a long time, this approach has no valuable alternative. The novel single-module solution involves abandoning the intermediate high-speed channel. Instead of multiple modules and high-speed communication links between them, the single module is installed near the data destination and connected to the master PC via Ethernet. The functionality of high-speed data transfer subsystem is delegated to the shared dynamic random-access memory (DRAM) and controller, implemented with field-programmable gate array (FPGA) resources. So, the connection cable is not needed anymore and the transfer speed is virtually limited only by DRAM performance.
Volume: 14
Issue: 3
Page: 696-704
Publish at: 2025-11-01

Hardware design for fast gate bootstrapping in fully homomorphic encryption over the Torus

10.11591/ijres.v14.i3.pp659-675
Saru Vig , Ahmad Al Badawi , Mohd Faizal Yusof
Fully homomorphic encryption (FHE) is a promising solution for privacy preserving computations, as it enables operations on encrypted data. Despite its potential, FHE is associated with high computational costs. As the theoretical foundations of FHE mature, mounting interest is focused towards hardware acceleration of established FHE schemes. In this work, we present a hardware implementation of the fast Fourier transform (FFT) tailored for polynomial multiplication and aimed at accelerating gate bootstrapping in Torus fully homomorphic encryption (TFHE) schemes. Our study includes an extensive design-space exploration at various implementation levels, leveraging parallel streaming data to reduce computational latency. We introduce a new algorithm to expedite modular polynomial multiplication using negative wrapped convolution. Our implementation, conducted on reconfigurable hardware, adheres to the default TFHE parameters with 1024-degree polynomials. The results demonstrate a significant performance enhancement, with improvements of up to 30-fold, depending on the FFT design parameters. Our work contributes to the ongoing efforts to optimize FHE, paving the way for more efficient and secure computations.
Volume: 14
Issue: 3
Page: 659-675
Publish at: 2025-11-01

Design of a real-time prayer clock using geographic coordinates

10.11591/ijres.v14.i3.pp834-842
Massoum Noreddine‬‏ , Moulai Khatir Ahmed Nassim
Prayer times and calendar clock are a valuable system that relies on programs that we developed in Mikroc that allow to mathematically calculate these prayer times, which differ from one place (city) to another and from one day to another using geographical coordinates. The more precise these coordinates (latitude and longitude), the more precise the prayer times are. The research that we conducted was carried out using a 16F876A microcontroller that uses the 74HC595 circuit, an 8-bit serial input and parallel output shift register for storage. Outputs can be added to the microcontroller thanks to this. It is possible to manage this integrated circuit from three pins of our microcontroller.
Volume: 14
Issue: 3
Page: 834-842
Publish at: 2025-11-01
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