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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 680 Documents
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Prediction index drought use neural network based rainfall Nafiiyah, Nur; Mokhtar, Ali
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.pp1146-1154

Abstract

Prolonged dry seasons compared to rainy seasons often lead to drought, making drought index observations essential. In Indonesia, drought monitoring commonly uses the standardized precipitation index (SPI), yet there is no common standard for drought index measurement. Therefore, this research applies the Z-score index (ZSI) and China-Z index (CZI), which, like SPI, are rainfall-based drought indices but have rarely been explored in previous research. To predict ZSI and CZI, this research compares the weighted moving average (WMA) and multilayer perceptron (MLP) methods. Two input scenarios are tested: the previous two periods (t-2, t-1) and the previous three periods (t-3, t-2, t-1). The results show that MLP outperforms WMA, with the best performance achieved by the MLP model at a mean absolute percentage error (MAPE) of 4.177% using the three variable input scenario and MLP architecture 3-6-10-1.
Optimizing smart grids with blockchain-driven automation and demand response Jyothi, B.; Pabbuleti, Bhavana; Ponnala, Ravi; Rao, Kambhampati Venkata Govardhan; Srilakshmi, S. Sai; Narasimha, Putta Dhanush; Yadav, Mareboyina Karthik; Kumar, Malligunta Kiran; Reddy, Ch. Rami
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.pp985-998

Abstract

To increase resilience, efficiency, and engagement in the network, it shall develop and test its smart grid system integrating blockchain-based authentication and automated demand response management. Simulations are made on the dynamic behavior of the grid in energy generation, consumption, and management through demand responses through MATLAB/Simulink assessment of performance and stability. Ethereum is used in implementing and managing smart contracts that automate and secure events of demand response and consumer interactions for transparency in transactions. It uses Python with Pandas to process, analyze, and visualize simulation data that gives insight into the effectiveness of demand response strategies; PostgreSQL supports the structured storage and querying of data with comprehensive data management. Proper integration of such tools can result in the proper robust simulation of the smart grid system that is highly reliable, efficient usage of energy, and can empower consumers through secure, efficient demand response mechanisms. These immediate issues about managing the grid can thus solve the way toward the future development of such smart grid technologies and their possible integration with the blockchain.
Thermally stable sol-gel yttrium aluminum garnet cerium phosphors for white light-emitting diodes Le, Phan Xuan; Loan, Nguyen Thi Phuong; Anh, Nguyen Doan Quoc; Lee, Hsiao-Yi
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.pp1367-1374

Abstract

This study aims to develop structurally controlled TiO2-based materials that serve a dual purpose as high-performance photocatalysts and optical scattering agents for white light-emitting diodes (LEDs). Hollow spherical TiO2, TiO2/Ag, and TiO2/Au particles were synthesized via a one-step spray thermolysis process using aqueous titanium citrate and titanium oxalate precursors. The method enables precise control of morphology and crystalline phase composition, producing hollow microspheres with tunable anatase–rutile ratios (10–100%) and crystallite sizes ranging from 12 to 120 nm. Photocatalytic performance, evaluated through the ultraviolet (UV) driven oxidation of methylene blue, showed that as-prepared TiO2 exhibited comparable activity to Degussa P25, while metal doping accelerated the anatase-to-rutile transition with minimal plasmonic enhancement under UV light. For LED applications, incorporating hollow TiO2 particles into YAG:Ce phosphor films improved luminous intensity, reaching a peak of ∼71 lm at 1 wt.% TiO2, and enhanced color uniformity, achieving a D-CCT as low as ∼60 K at 5 wt.%. These results confirm that spray thermolysis provides a scalable route to tailor morphology and phase composition, enabling multifunctional TiO2 materials optimized for both environmental photocatalysis and high-quality LED lighting.
New approach of the neighborhood structure of fuzzy points Almyaly, Amer Himza; Moshahary, Jwngsar
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.pp1083-1088

Abstract

This paper provides a comparative analysis of the fuzzy Q-neighborhood and the fuzzy neighborhood system of a fuzzy point. Specifically, we investigate the relationship between the elements of these systems when both are defined at the same fuzzy point. We address questions such as: how are these elements interconnected, and which system contains the other? Furthermore, we give the dual of the fuzzy Q-neighborhood system, which is named the fuzzy DQ-neighborhood system, and prove that these two systems are not equivalent. Finally, we examine the properties of these systems to determine whether they satisfy the conditions of fuzzy topology, Supra topology, or filter theory.
Unveiling anomalies in industrial control systems: a kernel SHAP-based approach with temporal convolution autoencoder Oswal, Sangeeta; Shinde, Subhash; Murli, Vijayalaksmi
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.pp1420-1432

Abstract

Industrial control systems (ICS) are often the target of cyber-attacks, leading to undesirable consequences. ICSs operate without human supervision, making them vulnerable to adversaries. In recent years, numerous deep learning-based solutions have demonstrated their efficiency in detecting anomalies in ICSs. However, there is a lack of ability to pinpoint the sensors and actuators that contributed to the anomaly. In this research work, we use kernel Shapley additive explanations (SHAP) to explain anomalies detected by a temporal convolution autoencoder (TCAE). The proposed TCAE model handles the long-term dependency effectively and is computationally effective on a large dataset. A comprehensive explanation is provided, focusing on the feature that contributed to the anomaly for each identified attack. The SHAP values are extracted for each identified attack and visually depict the feature that contributed to the anomaly for each attack, helping the expert to handle the attack and build user trust.
Bioecological characteristics of modern soil cover in subtropic regions of Azerbaijan Verdiyeva Bahram, Farida; Allahverdi, Turkan Hasanova; Eyvaz, Mahsati Ismayilova; Yusif, Elnur Huseynov; Jabiyeva Elshad, Telli; Asgarova Farhad, Gunel
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.pp1200-1207

Abstract

The purpose of this study is to introduce innovation in the field of agriculture in Azerbaijan by determining the abundance of various ecotrophic groups of microorganisms (involved in the formation and mineralization of humic substances) in natural and cultivated gray-brown soils. Studying the microbiological indicators of humic substance transformation in virgin soils and determining the direction of these processes under the influence of anthropogenic factors in agrocenoses soils is considered relevant for the development of the agricultural sector in the Lankaran region. It was found that perennial woody vegetation increased the abundance of pedotrophic microorganisms by 17-21% and humate decomposers by 12-14% compared to completely natural soil. The correlation coefficient between the abundance of humate decomposers and the pedotrophic index was r=-0.685±0.09. Plowing natural gray-brown soils reduces the total humus content and the abundance of micromycetes, which form the peripheral portion of humic substances.
Multi-dimensional brand experiences in co-branded products across generations Erlyana, Yana; Yi, Lim Jing
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.pp1018-1027

Abstract

As consumer expectations evolve, brands are tasked with creating multifaceted experiences that resonate with different generations. This study examines the influence of sensory, affective, behavioral, and cognitive brand experiences on consumer perceptions of co-branded products, with a focus on two key cohorts: Generation Y (Gen Y) and Generation Z (Gen Z). A mixed-methods approach, integrating quantitative surveys and qualitative focus groups, was employed to gain deeper insights into generational differences in brand engagement. The findings reveal that Gen Y consumers prioritize emotional and behavioral experiences, seeking meaningful interactions and emotional connections that align with their values and life stages. In contrast, Gen Z consumers are more interested in sensory novelty and cognitive engagement, favoring brands that emphasize originality, digital interactions, and distinctive experiences. Both generations showed strong reactions to behavioral factors, particularly direct product interactions. These insights highlight the importance of tailoring brand experience strategies to the unique preferences of each generation. By embedding sensory, emotional, and cognitive elements into brand experiences, companies can create deeper emotional connections with consumers, enhance brand value, and build long-term loyalty. The results offer actionable strategies for brand managers seeking differentiation and sustainable success in today’s competitive market environment.
Antimicrobial activity of hard candy with basil (Ocimum sanctum L.) essential oil addition Belqis, Maria; Giyarto, Giyarto; Irvanto, Moch Yusuf; Setyoningrum, Fitri; Susanti, Siti
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.pp1061-1071

Abstract

The basil plant belongs to the Lamiaceae family and contains various active compounds, including phenols, saponins, alkaloids, flavonoids, tannins, and essential oils. These compounds have antimicrobial activity against Streptococcus mutans and Candida albicans, two types of bacteria that can cause bad breath. The addition of basil essential oil to hard candy has the potential to reduce bad breath. This study aimed to determine the concentration effect of basil essential oil on hard candy in inhibiting the growth of Streptococcus mutans and Candida albicans and its acceptance by the panelists. This research was conducted with five treatments with variations in the concentration of basil essential oil, which were 0, 0.25, 0.5, 0.75, and 1%. The results showed that the higher basil essential oil concentration in hard candy inhibited the growth of Streptococcus mutans and Candida albicans. The best treatment was at 0.75% basil essential oil, with sensory panelist acceptance for color 69%, aroma 57%, taste 43%, and overall 58%. Several compounds in basil essential oil, including linalool, eugenol, caryophyllene, and trans-α-bergamotene, are thought to contribute to the ability of this candy to inhibit microbial growth.
Generative adversarial network for intelligent haze removal from high quality images Qazzaz, Ali Abdulazeez Mohammed Baqer; T. Hussein, Hayfaa; Al-janabi, Shroouq J.; Mudhafar, Yousif
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.pp1340-1349

Abstract

Suspended atmospheric particulates like haze, mist, and fog greatly degrade captured images, creating considerable challenges for computer vision applications operating in safety-sensitive areas such as autonomous driving, surveillance, and remote sensing. In this paper, we treat the important challenge of single-image haze removal by proposing a novel and robust conditional generative adversarial network (cGAN)-based framework. The proposal utilizes a U-Net-based generator with self-attention and skip connections to preserve spatial fidelity, and a PatchGAN discriminator to enforce local realism. At the heart of our contribution is a carefully weighted multi-component loss function that applies reconstruction, perceptual, edge, structural similarity (SSIM), and adversarial losses to optimize pixel-level accuracy and perceptual quality. We trained and evaluated our proposal on the large-scale real-world LMHaze dataset. Experimental results demonstrate state-of-the-art performance with a peak signal-to-noise ratio (PSNR) of 33.42 dB and SSIM of 0.9590. Our qualitative and comparative analyses further support our claims by assessing our proposed model's capacity to recover clear and artifact-free images from hazy images - outperforming the existing methods on this challenging real-world benchmark.
Cloud-based secure data storage in healthcare using elliptic curve cryptography Nalina, Gayathri Govindappa; Raju, Channakrishna
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.pp1281-1294

Abstract

The growth of cloud computing in the healthcare field has led to significant developments, but ensuring the confidentiality and protection of medical records such as electronic health records (EHRs) remains a major concern for healthcare service applications. In cloud computing, the basic authentication provided by most service providers is insufficient to ensure secure access to critical or sensitive resources. Moreover, most of the existing healthcare management systems are ineffective in handling a number of patient data, which leads to single points of failure. To address these issues, elliptic curve cryptography (ECC) with Curve25519 is utilized to enhance security in cloud storage, particularly within healthcare management systems. The ECC with Curve25519 is optimized for efficient and fast scalar multiplication, which reduces computational overhead and enhances performance. The curve parameters are selected to prevent vulnerabilities and ensure security against known attacks. Moreover, it is efficient in maintaining the integrity of patient records, which reduces storage and bandwidth requirements. The ECC with Curve25519 achieves lower Key-Gen, prove, verify, proving key size, and verification key size of 13.7 s, 48 s, 0.608 s, 13.27 Mb, and 123.70 Kb, respectively, in comparison with proxy re-encryption algorithm with zero-knowledge proof (ZKP).

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