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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 758 Documents
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A novel multi-terminal fuzzy-logic controlled IUPQC device for power quality enhancement in multi-feeder distribution systems Venna Jaya Lakshmi; Katragadda Swarnasri
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp760-774

Abstract

Non-linear sensitive loads are increasingly being used in a wide range of industrial and home applications. Particularly, some nonlinear sensitive loads degrade the power quality (PQ) of a multi-feeder distribution system by causing current as well as voltage quality to deviate from normal standards. To address these PQ issues, a unique multi-terminal interline unified power quality conditioner (MT-IUPQC) device has been implemented in a multi-feeder distribution system. This MT-IUPQC is made up of multi-voltage source inverters (VSI) coupled by a common direct current (DC)-linked capacitor, and which is controlled by using proportional integral (PI) control method. However, due to an inappropriate gain setting choice, this PI is not suitable for regulating the DC voltage at the specified voltage level. In this paper, an intelligent fuzzy-logic controlled MT-IUPQC provides an intelligent knowledge set with subjective assessments for improved mitigation of PQ difficulties. The recovered total harmonic distortion (THD) of source current is 2.45%, 2.71%, which are well within IEEE-519/2014 norms and significantly lower than the THD of non-linear sensitive load current of 30.19%, 30.05% in both feeder-1 and 2. In a similar way, the THD of non-linear sensitive load voltage is obtained at 0.43%, which fits well under IEEE-519/2014 norms and is significantly lower than the THD of the voltage source measured at 20.62% in feeder-1.
A new generation of artificial intelligence contributing to improving the image quality Salwa A. Alagha; Hadeel N. Abdullah; Suad Khairi Mohammed
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp664-676

Abstract

High-resolution (HR) images provide inclusive and critical information, which is substantial for many implementations. Production operation for high-quality images from low-quality images can be costly and time consuming. The main advancement in this domain is produced by enhanced super-resolution generative adversarial network (ESRGAN); the ESRGAN and different deep learning (DL) models exhibit prominent advances in image super-quality. This research proposes introducing the discrete wavelet transform (DWT) as a multi-scale analysis stage that feeds into the network, whereby the frequencies are analyzed before being fed into the generative adversarial networks (GAN). The goal is to enhance the ability to recover edges and fine details, especially in low-resolution images. The performance of this proposed model is implemented, evaluated, and comparatively assessed. Key performance parameters, such as peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM), are calculated, which compare the proposed model with other image-improving models (Bicubic, SRResNet, and ESRGAN). The experimental results indicate that the proposed method ESRGAN new yields a good result in image improvement, with a PSNR of (26.22, 26.00, 25.51, and 23.89) and an SSIM of (0.6638, 0.6255, 0.5882, and 0.6286) for four datasets, respectively.
Vertical-horizontal flow roughing filter for improving water quality in sustainable water supply infrastructure Anggara Wiyono Wit Saputra; Prasetyo Rubiantoro; Very Dermawan
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp518-531

Abstract

Water is fundamental to cooking, bathing and hygiene, and essentially for life itself. Across many areas, communities rely on bore well water as a source of raw water for domestic needs. Yet this resulting water is mostly not of an appropriate quality, as it has a high iron content and hardness. This study evaluates the performance of a combined vertical-flow and horizontal flow roughing filter (VRF and HRF) system for bore well water treatment. The system was tested using various alternative filter media, including coconut fiber, silica sand, activated carbon, zeolite, pumice stone, and volcanic black sand, arranged in different configurations. The vertical-flow unit used a media depth of 6 cm, while the horizontal-flow unit used a depth of 15 cm. The results showed that all configurations effectively improved water quality and met standard requirements. The highest performing model, consisting of volcanic black sand, activated carbon, zeolite, and silica sand, achieved a 97.5% reduction in iron and a 13.2% reduction in hardness. These findings indicate that optimized roughing filter systems offer a low cost and efficient solution for decentralized water treatment.
Validation of a child emotional learning activity kit using the fuzzy Delphi technique Uzzairah Nabila Ahmad Tazli; Zaharah Osman; Nadia Shahira Amiruddin; Mazlina Che’ Mustafa
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp854-860

Abstract

Early childhood is a critical period for socio-emotional development, yet parents often lack structured tools to reinforce these skills at home. The study aims to obtain the experts’ unanimous agreement on the contents and components of an emotional learning activity kit for children. This study used the fuzzy Delphi method (FDM) to gather feedback from 13 experts in early childhood education. The survey contained 27 items, which used the seven-point Likert scale. FDM data was analyzed using triangular fuzzy numbers (TFN). The results of the study demonstrated consensus of the construct is at a high level. The overall expert consensus agreement exceeds 75%, the overall value of the threshold (d) is 0.2, and the α-cut exceeds 0.5. The value of the learning contents showed that the expert agreement of this kit is highly acceptable. Findings also showed learning material in this kit has a high agreement value, and it can be used to empower teachers and parents to cultivate their children’s emotional learning, bridging the gap between curriculum and home-based learning. Future research should consider expanding the application of this emotional learning activity to children in preschool.
Assessment of deep learning based Hindi Odia bidirectional machine translation system Subhashree Satpathy; Smitaprava Mishra; Ajit Kumar Nayak
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp687-695

Abstract

India is a vast nation with a diverse range of cultures and languages. Most Indians choose to use their native languages when communicating with machines. To integrate smart technologies into every facet of Indian society, efficient systems that can positively identify Indian languages must be established. Machine translation (MT) studies comprise most of the natural language processing (NLP) in the era of multilingual computer-human interaction. Till now, less emphasis has been placed to develop MT systems among Indian languages. Yet again, building a qualitative and quantitative corpus in these languages is challenging. This work focuses on two Indic languages for the development of a Hindi to Odia bidirectional machine translation system (HOBMT). Bilingual evaluation understudy (BLEU), word error rate (WER), character error rate (CER), and metric for evaluation of translation with explicit ordering (METEOR) evaluation metrics are used to assess the accuracy of the translation. The most advanced sequential deep learning (DL) models, such as recurrent neural network (RNN), long short term memory (LSTM), and gated recurrent unit (GRU), are used in this study. In this research, RNN is observed with improved translation results due to its sequential data handling with context preservation.
Comparison of thermal and non-thermal images for tomato fruit detection Sulfayanti Faharuddin Situju; Wawan Firgiawan; Hironori Takimoto
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp451-461

Abstract

Farmers use manual observation to sort, grade, and estimate tomato production results to meet market demands. However, this method requires a lot of energy and time, making it unsuitable for large-scale tomato cultivation utilizing the detection process. This study aims to develop the automatic tomato detection technology in an industrial environment based on a conveyor belt by using thermal or non-thermal imaging and you only look once version 8 (YOLOv8). The dataset consists of 570 images obtained from each thermal and non-thermal camera and has undergone augmentation techniques to enrich the data variety. The model was trained and validated using 640×640-pixel images for 40 epochs. In this paper, we conduct a comparative analysis of the tomato detection result using YOLOv8 on thermal and non-thermal imaging. The results indicate that the model trained with thermal data significantly outperformed the non-thermal model, achieving 99% precision, 98% recall, 98% F1-score, and 99% mean average precision (mAP)50 during validation. The thermal model received a 99% accuracy rate during validation, while the non-thermal model attained 94% accuracy, exhibiting a slightly poorer performance and committing several mistakes in detection. The use of thermal cameras on moving automation systems has demonstrated its capability and effectiveness, making it more optimal for application in the agricultural industry.
Impact of heavy metal and pesticide contamination in water and soil on hemoglobin synthesis and lymphocyte counts Artati Artati; Nuradi Nuradi; Herman Herman; Asyhari Asyikin; Nurisyah Nurisyah; Ratnasari Dewi; Rafidah Rafidah; Aan Yulianingsih; Asriyani Ridwan
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp718-731

Abstract

Heavy metal and pesticide pollution represent a significant public health concern, particularly due to their detrimental effects on hematological health. This study investigates the levels of heavy metals, specifically lead (Pb), cadmium (Cd), and arsenic, and organophosphate pesticides in water and soil within five sub-districts of Jeneponto City, utilizing a quantitative descriptive analysis methodology with the simple random sampling over a six-month period. Analytical techniques employed include atomic absorption spectrophotometry (AAS) for heavy metals and UV-Vis spectrophotometry for pesticides, complemented by blood analyses for hemoglobin and lymphocyte counts. Results reveal that soil samples exhibited heavy metal concentrations exceeding regulatory thresholds, with copper (Cu) and Cd identified as particularly concerning. While most organophosphate pesticide levels were below established limits, concerns regarding potential residue accumulation persist. Exposure to these pollutants has been linked to disrupted hematopoiesis and immune system impairments, potentially resulting in anemia and heightened vulnerability to infections. This study underscores the critical need for continuous monitoring of heavy metal and pesticide levels in environmental matrices to mitigate adverse health outcomes and protect ecosystems. Regular assessments are vital for public health policy and environmental management strategies.
PhyFizball: a game-based tool to enhance student’s understanding of force and motion Muhammad Alfi Yusra Jalani; Adibah Abu Bakar; Syazwan Saidin
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp573-582

Abstract

Difficulties in understanding the concepts of force and motion continue to challenge secondary school students due to the abstract nature of physics and the limited use of interactive teaching methods. This study introduces PhyFizball, a pinball-inspired, low-cost game-based learning (GBL) tool designed to make physics learning more engaging and concrete. The tool aims to help students visualize fundamental concepts such as Newton’s laws, friction, and the relationship between force and motion through hands-on and collaborative gameplay. A quasi-experimental pretest–posttest control group design was employed with 30 form two students from a Malaysian secondary school, divided equally into experimental (n =15) and control (n =15) groups. Over four weeks, the experimental group learned using PhyFizball, while the control group received conventional lecture-based instruction. A validated conceptual understanding test was administered before and after the intervention. Results from paired and independent t-tests revealed that the experimental group achieved significantly higher post-test scores than the control group (t(28) =3.282, p =0.003). The findings confirm that PhyFizball effectively enhances students’ conceptual understanding and engagement in learning physics. Its accessible design demonstrates potential as a cost-effective and scalable teaching tool for improving science learning outcomes in secondary education.
SWOT-TOWS analysis of an electronic health referral system: basis for development strategy Emmanuel Carlos Navarro; Cristina Enriquez Dumdumaya
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp804-819

Abstract

Along with the implementing rules and regulations of Republic Act No. 11223 (Universal Health Care Act) and the national mandate for the digital transformation of basic services, the Philippine health sector faces the imperative to implement an interoperable electronic referral (eReferral) system. This study applies strengths, weaknesses, opportunities, threats (SWOT) and threats, opportunities, weaknesses, strengths (TOWS) to conduct a SWOT–TOWS strategic analysis of internal and external factors affecting the existing healthcare referral system and to generate evidence-based strategies for national eReferral system adoption. The analysis identifies strong policy support and institutional frameworks as key enablers, while fragmented information and communication technology (ICT) infrastructure, absence of Health Level Seven International (HL7)/Fast Healthcare Interoperability Resources (FHIR) interoperability standards, limited bandwidth in rural facilities, and insufficient technical personnel constitute primary barriers. Comparative benchmarking against the UK NHS eReferral service and US EHR-based referral systems highlights critical design gaps in the Philippine context. The proposed strategies, encompassing a centralized system architecture, ICT readiness investments, and compliance with ISO/IEC 27799 health informatics security standards, provide an actionable framework for policymakers, ICT planners, and healthcare administrators. This study contributes to health informatics literature by applying strategic analysis to health IT system design as a novel methodological intersection.
Characteristics of biochar from agricultural residues produced by traditional combustion and its potential as a soil amendment Ali Rahmat; Sukamto Sukamto; Santi Ari Respat; Fera Arum; Wiwiek Dwi Susanti; Yudia Azmi; Zurrahmi Wirda
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp611-621

Abstract

Biochar is a carbon-rich material produced through pyrolysis. However, pyrolysis methods that generate high-quality biochar typically require expensive equipment and technical expertise. This study examines the characteristics of biochar produced from rice husk, cassava wood, and corn cobs using a traditional burning method as an alternative to pyrolysis. The research results showed that the carbon content of biochar produced using traditional methods was comparable to, or even higher than, biochar produced using more advanced pyrolysis methods. Corncob biochar had the highest carbon content among all samples. X-ray fluorescence (XRF) analysis revealed that rice husk biochar had the highest silica content, while cassava wood biochar showed higher percentages of calcium (Ca) and magnesium (Mg) than the other biochars. X-ray diffraction (XRD) characterization results indicated a higher degree of graphitic crystallinity in the corncob biochar, while Fourier transform infrared spectroscopy (FTIR) spectra confirmed the presence of hydroxyl groups, aromatic C=C, and cellulose residues in all samples. thermogravimetric–differential thermal analysis (TG-DTA) and differential scanning calorimetry (DSC) analyses provided insights into thermal behavior and carbonization levels, with corncob biochar having the highest carbon content and thermal resistance. The application of biochar to acidic soils has been shown to significantly increase soil pH and organic carbon content. The simple combustion method used in this study is capable of producing biochar with diverse physicochemical properties, thus offering a sustainable approach to soil improvement, increased nutrient retention, and carbon sequestration, while providing added value to agricultural waste and waste valorization strategy.

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