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International Journal of Advances in Applied Sciences
Published by Institute of Advanced Engineering and Science
ISSN : 22528814     EISSN : 27222594     DOI : http://doi.org/10.11591/ijaas
Core Subject : Science, Education, Social,
Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics
International Journal of Advances in Applied Sciences (IJAAS) is a peer-reviewed and open access journal dedicated to publish significant research findings in the field of applied and theoretical sciences. The journal is designed to serve researchers, developers, professionals, graduate students and others interested in state-of-the art research activities in applied science areas, which cover topics including: chemistry, physics, materials, nanoscience and nanotechnology, mathematics, statistics, geology and earth sciences.
Arjuna Subject : -
Articles 797 Documents
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Enhanced switching converter for photovoltaic systems: performance analysis and simulation Nikunj N. Patel; Rakeshkumar A. Patel
International Journal of Advances in Applied Sciences Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i3.pp1262-1269

Abstract

This paper focuses on reducing switching losses and stresses in photovoltaic (PV) inverters by introducing a new five-level hybrid T-type multilevel inverter (T-MLI). The proposed topology was designed and simulated using physical security information management (PSIM) software and validated using one year of solar radiation and temperature data to account for seasonal variations. The proposed inverter was also experimentally implemented through hardware development, and its performance was evaluated under different load conditions. Under nonlinear load conditions, the results demonstrate that the proposed T-MLI reduces total harmonic distortion (THD) to 3.8%, reduces voltage stress on the switches, improves direct current (DC)-link utilization, and enhances the overall efficiency of the inverter system compared with the traditional topology.
Amaranthus dubius seeds oil extraction using green solvent approach with terpenes Rachma Tia Evitasari; Gita Indah Budiarti; Endah Sulistiawati; Adi Permadi; Ika Dyah Kumalasari; Nazira Mahmud; Nor Adila Mhd Omar
International Journal of Advances in Applied Sciences Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i3.pp964-974

Abstract

This research will explore the potential for utilizing wild amaranth (Amaranthus dubius) seeds, which are abundant and have not been utilized in Indonesia. This research will focus on optimizing the amaranth seed oil extraction process using the response surface method and the characteristics of the oil produced from amaranth seeds. The solvent used in this research is a biobased green solvent, terpenes. This research aims to explore the potential of utilizing wild amaranth seeds by optimizing the oil extraction process using a biobased green solvent, terpenes, through the response surface methodology (RSM). Fourier transform infrared spectroscopy (FTIR) results indicate that the terpenes solvent contains various terpenoids such as α-pinene, β-pinene, and camphene. By applying ultrasound-assisted extraction (UAE) and optimizing the critical process parameters (liquid-to-solid ratio, extraction temperature, and extraction time) through a Box-Behnken RSM design, the maximum oil yield was achieved under environmentally friendly conditions. The optimum condition was reached at a solvent-to-solid ratio of 5.13 ml/0.1 g, a temperature of 49.39 °C, and an extraction time of 47 minutes. With these optimal parameters, the predicted oil yield was 2.04%. The optimized extraction not only delivered a high-quality oil-rich extract but also minimized solvent residue, energy consumption, and hazardous emissions.
Lesion-semantic token guided transformer fusion for stage-adaptive diabetic retinopathy grading and screening Murali Gujjula; Kumar Narayanan
International Journal of Advances in Applied Sciences Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i3.pp1112-1122

Abstract

Diabetic retinopathy (DR) screening from retinal fundus images is still difficult because of the heterogeneity of lesions, significant class imbalance, and low reliability of existing deep learning algorithms owing to their generic feature pooling and passive fusion mechanisms. To overcome such limitations, this study presents a hybrid model called HandEffiTrans-DR, which combines deep retinal representations with handcrafted lesion descriptors via the directed transformer-based attention mechanism. First, a lesion-prior-guided token squeezer (LPG-TS) module is proposed in the work, which is capable of creating lesion-specific visual tokens via integrating prior knowledge about pathology into the tokenization procedure. Moreover, a directed transformer-based fusion (T→V) strategy allows for actively fusing the handcrafted lesion features with visual representations. The introduced framework is assessed with a stratified five-fold cross-validation protocol. Its average classification accuracy surpasses 97%, while the macro-F1 score is higher than 0.97 and Cohen's kappa is greater than 0.95, indicating good agreement despite the presence of class imbalance. The probability reliability is measured in terms of expected calibration error (ECE) and Brier scores and shows well-calibrated confidence. Further validation is performed on two external datasets, where consistent performance with minor decline is shown.
Effect of post-weld heat treatment and cooling techniques on mechanical performance of AH36 steel for marine structures Ahmad Firdhaus; Blinka Hernawan Prasetya; Muhammad Adnan Rivaldi; Parlindungan Manik; Tuswan Tuswan
International Journal of Advances in Applied Sciences Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i3.pp944-953

Abstract

The mechanical properties of structural steels used in marine environments are significantly affected by welding procedures. This research examines the impact of various cooling techniques, coupled with post-weld heat treatment (PWHT), on the strength and ductility of AH36 steel welded via shielded metal arc welding (SMAW). Heat treatments were conducted at temperatures of 450 °C, 600 °C, and 750 °C. Oil quenching and normalizing were employed as the two cooling processes. Tensile strength, elastic modulus, elongation, and impact toughness were measured through mechanical testing. The findings demonstrate that oil quenching after treatment at 450 °C yields the most favorable tensile strength and elongation properties, surpassing established safety standards. Conversely, increasing the treatment temperature to 600 °C and 750 °C reduces strength and ductility, presumably due to grain coarsening and microstructural weakening. Impact toughness is substantially improved by normalizing, especially at 600 °C, which offers the best balance of strength and toughness. These findings show that PWHT at 600 °C followed by normalizing markedly improves the mechanical properties of AH36 steel, ensuring dependable performance in harsh marine environments. This research helps improve weld quality and the safety of marine structures by carefully selecting heat treatment and cooling procedures.
Low-switch count based excitation of induction generator in wind power generation Nijam Uddin Molla; Shilpi Bhattacharya; Debashis Chatterjee; Arabinda Das
International Journal of Advances in Applied Sciences Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i3.pp1050-1058

Abstract

The power sector is undergoing sea changes from conventional forms of power generation towards renewable energy due to diminishing resources of conventional sources of energy and also to deal with environmental issues. Three-phase self-excited induction generators (IGs) are popular in power generation from renewable sources in grid-connected as well as standalone systems. The single-phase induction generators (SPIG) with self-excitation capacitors are used in domestic applications. This paper proposes a novel reduced switch-based converter excitation system for an asymmetrical split-phase induction generators (ASPIG) application in a standalone wind energy-based power generation system. Instead of the normal six-switch inverter, the excitation scheme proposed here comprises of four numbers of power switches and four capacitors. Proper control shows that variable excitation can be effectively provided to the ASPIG using only four switches with reasonably good performance on sufficient loading and wide speed range. The proposed system is implemented and tested on load and at varied speeds in MATLAB/Simulink. This paper presents a novel excitation scheme, modeling, control, simulation, and analysis. The results obtained are reported to be effective and satisfactory in wide speed range in the standalone system.
Enhancing fraction multiplication and division performance through intelligent tutoring system with visual models Ida Bagus Indrabudhi Kusuma; Selly Meliana; Dade Nurjanah
International Journal of Advances in Applied Sciences Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i3.pp1214-1226

Abstract

Mathematical proficiency, especially fractions, help humans to succeed in their future. However, students tend to struggle in understanding fractions, one of them is natural number bias (NNB). This study aims to address this challenge by developing a web-based math intelligent tutoring system (ITS) using the cognitive tutor authoring tools (CTATs) to create a cognitive tutor with adaptive feedback and visual models to support students in learning fraction multiplication and division. This study compares the students’ learning performance from two schools which the first school has aligned visual method with the system proposed. The results show that the experimental groups in the first school outperformed the control group with an average learning gain of 33.78%, while in the second school the control group outperformed the experimental group with average learning gain of 65.79%. Each school suggests statistically significant differences in students’ results. This highlights the effectiveness of ITS depends not only on system features but also the importance of alignment between students’ prior visual models and the visualization method in the system. Students with aligned visual method suggest positive feedback from the survey conducted, indicating its potential for improving fraction learning when it is integrated consistently with existing visual instruction.
Comparative review on control strategies for doubly fed induction generator-based wind energy harnessing system Preethicaa Ramesh; Sowmmiya Uthayakumar; Tole Sutikno; Vigna Kumaran Ramachandaramurthy; Mochammad Facta; Auzani Jidin
International Journal of Advances in Applied Sciences Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i3.pp1166-1192

Abstract

Doubly fed induction generator (DFIG)-based variable-speed wind energy harvesting systems (WEHS) are widely employed owing to high efficiency and reliable grid integration under variable wind conditions. This paper presents a comprehensive review of conventional, intelligent, and hybrid control strategies for DFIG-based WEHS. Unlike previous studies that primarily focus on specific control techniques, this study systematically compares different approaches based on key performance indicators-dynamic response, total harmonic distortion (THD), robustness, and fault ride-through (FRT) capability. Conventional controllers such as proportional–integral (PI) control, field-oriented control (FOC), and direct torque control (DTC) are evaluated alongside intelligent techniques, including fuzzy logic control (FLC), artificial neural networks (ANNs), adaptive control, and optimization techniques. The comparison shows that intelligent and hybrid control strategies achieve superior dynamic response, lower THD, enhanced robustness, and improved FRT capability, although they require higher computational resources. Furthermore, this review highlights critical research challenges, including the lack of experimental validation, the absence of standardized benchmarking frameworks, and the complexity of real-time implementation in high-power WEHS. Finally, future research should focus on developing hybrid intelligent controllers, establishing evaluation methodologies, and integrating advanced control strategies with smart grid technologies to improve power quality, voltage regulation, and reliability of modern wind energy systems.

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