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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.
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Articles 45 Documents
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Search results for , issue "Vol 14, No 4: December 2025" : 45 Documents clear
Forecasting internet traffic patterns for the campus Metro-E network using a hybrid machine learning model Arbain, Norakmar; Kassim, Murizah; Ali, Darmawaty Mohd; Saaidin, Shuria
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1433-1443

Abstract

Complex traffic patterns lead to crucial campus Metro-E network management and resource allocation. This paper presents an internet traffic forecasting by pre-processing data to offer better bandwidth quality of service (QoS). Eight (8) campuses' traffic data were analysed for modelling predictions using statistical analysis. A Metro-E campus network presents four (4) locations: A, E, F, and H have is a strong correlation between inbound and outbound traffic, with correlation values between 0.4547 and 0.5204. As the inbound traffic increases, outbound traffic tends to rise as well. Conversely, locations B, C, and G have weak correlations, indicating more independent traffic patterns. Data outliers were found for locations C and F, where unusual traffic spikes require further network exploration and show key trends in traffic data. Descriptive statistics reveal notable differences, with H has the highest average traffic at about 75 Mbps, while C has the lowest at around 30 Mbps. Location F shows the greatest traffic fluctuation with a standard deviation of 0.4076, whereas Location G has very little fluctuation with a standard deviation of 0.0240. Overall, this pre process data is use to combine machine learning (ML) to improve prediction abilities for better bandwidth management and real-time handling in digital campus environments.
AI-driven emotion recognition systems for sustainable mental health care: an engineering perspective Ahmad, Akram; Singh, Vaishali; Upreti, Kamal
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1111-1117

Abstract

Emotion recognition systems are transforming human-computer interaction (HCI) applications by enabling AI-driven, adaptive, and responsive mental health interventions. This study explores AI-based emotion recognition technologies using facial expressions, voice analysis, text-based sentiment processing, and physiological signals to develop scalable, real-time mental health support systems. Utilizing datasets such as FER2013, JAFFE, and CK+, our research examines deep learning models, including EfficientNet XGBoost, which achieved over 90% accuracy across key evaluation metrics. Unlike traditional mental health interventions, AI-driven systems provide cost-effective, accessible, and sustainable solutions through telemedicine, wearable biosensors, and virtual counselors. The study also highlights critical challenges such as algorithmic bias, ethical AI compliance, and the energy consumption of deep learning models. By integrating machine learning, cloud-based deployment, and edge computing, this research contributes to the development of sustainable, ethical, and user-centric AI solutions for mental health care. Future directions include AI model optimization for energy-efficient deployments and the creation of diverse, inclusive datasets to improve performance across global populations.
Methods used to enhance the physicochemical properties of natural ester insulating oils for transformers: a review Johal, Muhammad Syahrani; Ghani, Sharin Ab; Ahmad Khiar, Mohd Shahril; Sutan Chairul, Imran; Abu Bakar, Norazhar
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1393-1401

Abstract

Natural ester insulating oils, derived from vegetable-based feedstocks, are increasingly regarded as sustainable alternatives to conventional mineral oils due to their high fire point, biodegradability, and lower environmental impact. However, their widespread adoption in high-voltage equipment is constrained by their inherent limitations, such as lower oxidation stability, higher viscosity, and poor low-temperature performance. In this review, the three principal enhancement strategies developed to address these shortcomings are examined. The use of antioxidants is analysed for its role in improving oxidative resistance and flow characteristics. Transesterification is evaluated as a chemical modification method to alter the molecular structure, thereby enhancing viscosity and thermal stability. Refining and adsorbent treatments are discussed with respect to oil purification and regeneration, emphasising their adsorption efficiency and influence on dielectric performance. A comparative evaluation of these methods highlights their relative effectiveness, scalability, and practical challenges in implementation. This review underscores that no single approach is sufficient, and a combination of different methods is desirable to achieve optimal performance. These insights provide researchers with clear directions for further investigation while offering practitioners a knowledge base to guide the selection and application of enhanced natural ester insulating oils for reliable, long-term transformer operation.
Optimized transfer learning for detection susceptibility vessel sign in stroke using gorilla troops optimizer Albashah, Nur Lyana Shahfiqa Lyana; Faye, Ibrahima; Roslan, Nur Syahirah; Bakar, Rohani; Muslim, Norliana
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1040-1049

Abstract

The blockage of blood vessels causes ischemic stroke due to clots. The susceptibility vessel sign (SVS), observed through susceptibility-weighted imaging (SWI) via magnetic resonance imaging (MRI), is a key indicator that reveals clots within brain vessels. Early detection of these clots is crucial for timely and effective treatment. Image-based detection methods, particularly non-invasive techniques like MRI, offer a superior approach compared to other modalities. This study proposes an optimized method using transfer learning to classify SVS. The deep convolutional neural network (DCNN) residual network 50 version 2 (ResNet50V2) was applied for classification, with hyperparameters fine-tuned using the gorilla troops optimizer (GTO). The optimized proposed model achieved an accuracy of 94%, sensitivity of 100%, specificity of 88%, and an F1-score of 93%. This significantly outperforms the standard ResNet50V2 model using the default parameter, which achieved an accuracy of 91%, sensitivity of 82%, specificity of 100%, and an F1-score of 77%. These results demonstrate that the proposed method significantly enhances the detection of SVS, offering a promising tool for early ischemic stroke diagnosis.
Ambulance tracking system using GPS module and IoT based telegram messenger to find fastest route Akram, Rizalul; Novianda, Novianda; Atmaja, Teuku Hadi Wibowo; Anam, M. Khairul; Cut, Banta
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1322-1331

Abstract

Traffic congestion in urban areas affects ambulance trips to hospitals. This research aims to find the fastest route for ambulances to travel. The fastest route has criteria such as road shape, road width, shortest distance traveled, and fewer road users. This detection system applies internet of things (IoT) technology to each ambulance equipped with global positioning system (GPS), NodeMCU, and Wi-Fi modem that can send GPS coordinates to the cloud server, which will then mark the shortest distance from its current location to the hospital through the place where the emergency call is raised. The components used in this research are Neo6M GPS, NodeMCU ESP8266, cloud computing, and smartphone. This system can provide realtime information on all ambulance positions via android applications and Telegram messenger. The results obtained can determine the fastest path, distance, and travel time. In addition, the operation of this system takes 2-3 minutes to find the GPS signal at the beginning, then there is a 1-2 second delay from the GPS Tracking movement. Testing the route accuracy of this system and google maps by driving by motorcycle shows the results of this GPS system are more accurate in terms of distance and travel time.
Cybersecurity skills in new graduates: a Philippine perspective Miranda, John Paul P.; Tayag, Marlon I.; Canlas, Joel D.
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1217-1228

Abstract

This study investigates the key skills and competencies needed by new cybersecurity graduates in the Philippines for entry-level positions. Using a descriptive cross-sectional research design, it combines analysis of job listings from Philippine online platforms with surveys of students, teachers, and professionals. The aim is to identify required skills and areas needing improvement, highlighting the balance between technical skills and other competencies like ethical conduct, suggesting a shift away from traditional cybersecurity skills towards a more diverse skillset. Furthermore, the results revealed common agreement on the importance of communication, critical thinking, problem-solving, and adaptability skills, albeit with slight variations in their prioritization. It recommends that aspiring cybersecurity professionals develop an inclusive skill set encompassing technical knowledge, soft skills, and personal competencies, with a focus on adaptability, continuous learning, and ethics. Skills such as business acumen are considered less vital for entry-level roles, proposing a preparation strategy that aligns with the changing demands of the cybersecurity industry.
Mandailing smoked fish cuisine: cultural, nutritional, and local wisdom insights Emilia, Esi; Haryana, Nila Reswari; Rosmiati, Risti; Mutiara, Erli; Fitria, Laili; Mulyana, Rachmat; Prayogo, Wisnu
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1166-1180

Abstract

This study explores the uniqueness of Mandailing traditional cuisine, focusing on the cultural and nutritional significance of its iconic smoked fish dishes, such as smoked fish rendang, smoked fish curry, smoked fish with chili sauce, and smoked fish with vegetables. These dishes showcase the traditional fish smoking practices developed as a preservation method, allowing the Mandailing community to adapt to the abundance of rivers and natural resources in their highland environment. Smoking fish not only extended its shelf life but also became a cornerstone of Mandailing culinary identity, reflecting the community’s ingenuity and resourcefulness. Mandailing cuisine is deeply influenced by neighboring culinary traditions from West Sumatra and North Tapanuli, resulting in a rich fusion of bold flavors, often characterized using coconut milk and fresh spices. The preparation of smoked fish combines traditional high-heat cooking techniques with unique flavor profiles that distinguish Mandailing dishes from other Indonesian cuisines. This research highlights the importance of Mandailing smoked fish practices in sustaining local food systems and preserving cultural heritage. By emphasizing both cultural and nutritional aspects, it underlines the relevance of these traditional practices in promoting food diversity, environmental sustainability, and the recognition of Indonesia’s rich culinary landscape.
A review of direct-to-device satellite technology in bridging connectivity gaps in Malaysia Mohd Hassan, Siti Maisurah; Roslee, Mardeni; Mohd Marzuki, Azah Syafiah
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1251-1262

Abstract

The connectivity gap in rural and remote regions of Malaysia remains a significant challenge due to the high costs and technical challenges of deploying fixed-line infrastructure like fiber optics and copper cables. Similarly, expanding cellular networks such as 4G and 5G to these areas is often economically unfeasible for mobile network operators (MNOs) due to low returns on investment. Direct-to-device (D2D) satellite technology has recently emerged as a promising solution, gaining interest from both industry and academia. D2D enables direct communication with standard mobile phones and internet of things (IoT) devices, extending coverage to underserved regions without requiring extensive ground infrastructure. This paper provides a comprehensive overview of D2D technology, its technical aspects, and its suitability as a complementary solution to terrestrial networks. This paper also discusses how D2D technology can bridge the connectivity gap in Malaysia, offering a possible solution to enhance digital inclusion in rural and remote communities.
Optimizing inventory management in the textile industry: a comprehensive evaluation of UHF-RFID technology integration Darmawi, Ahmad; Istikowati, Rita; Astrini, Galuh Yuli
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1411-1419

Abstract

The integration of ultra-high frequency radio frequency identification (UHF RFID) technology presents a transformative solution to inventory management challenges in the textile industry. This study examines the implementation of a web-based inventory management system incorporating UHF-RFID technology at AK-Tekstil Solo, focusing on its impact on inventory accuracy, operational efficiency, and product traceability. The developed system facilitates real-time tracking of yarn products, streamlines inventory audits, and minimizes manual errors, resulting in substantial improvements in inventory control and warehouse management processes. By enabling automated data capture and tracking, UHF-RFID technology supports the transition to smart warehousing by providing real-time insights into inventory movements. The findings demonstrate that UHF-RFID technology offers significant advantages, including enhanced inventory visibility, cost savings, and improved customer satisfaction through better product availability. Despite potential implementation challenges, the study shows that the long-term benefits of UHF-RFID integration outweigh the initial costs, proving it to be an effective solution for optimizing inventory management in the textile industry. Future research may explore the integration of complementary technologies such as the internet of things (IoT) and artificial intelligence (AI) to further enhance UHF-RFID enabled inventory management systems.
E-bikes unplugged: exploring the evolution and environmental benefits of electric cycling Manoj, Vasupalli; Sreedhar, Malleti; Sasidhar, Rebba; Kundala, Praveen Kumar Yadav; Chandra Mouli, Dasyam; Pilla, Ramana
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1295-1304

Abstract

Electric bicycles (e-bikes) have rapidly emerged as a sustainable alternative to conventional modes of transportation. This study reviews the evolution, technological advancements, and environmental benefits of e-bikes through comparative data analysis, survey results, and case studies. The findings demonstrate that the developments in lithium-ion batteries, lightweight materials, and smart motor systems have significantly improved e-bike performance, efficiency, and affordability. From an environmental perspective, e-bikes can cut greenhouse gas emissions by more than 90% compared to cars, while simultaneously improving urban air quality and reducing overall pollution levels. Survey responses indicate that e-bike users often substitute short car trips, promoting sustainable commuting behaviors and supporting public health. Despite these benefits, challenges persist regarding insufficient infrastructure, inconsistent policy support, and limited battery recycling programs. In summary, e-bikes constitute a transformative element in sustainable urban mobility and climate change mitigation. Beyond policy reforms, future work should prioritize renewable-powered charging systems and circular battery utilization models to ensure e-bikes contribute to a more resilient and environmentally friendly transportation ecosystem.

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