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Antimicrobial activity of hard candy with basil (Ocimum sanctum L.) essential oil addition

10.11591/ijaas.v14.i4.pp1061-1071
Maria Belqis , Giyarto Giyarto , Moch Yusuf Irvanto , Fitri Setyoningrum , Siti Susanti
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.
Volume: 14
Issue: 4
Page: 1061-1071
Publish at: 2025-12-01

Unveiling anomalies in industrial control systems: a kernel SHAP-based approach with temporal convolution autoencoder

10.11591/ijaas.v14.i4.pp1420-1432
Sangeeta Oswal , Subhash Shinde , Vijayalaksmi Murli
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.
Volume: 14
Issue: 4
Page: 1420-1432
Publish at: 2025-12-01

New approach of the neighborhood structure of fuzzy points

10.11591/ijaas.v14.i4.pp1083-1088
Amer Himza Almyaly , Jwngsar Moshahary
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.
Volume: 14
Issue: 4
Page: 1083-1088
Publish at: 2025-12-01

Thermally stable sol-gel yttrium aluminum garnet cerium phosphors for white light-emitting diodes

10.11591/ijaas.v14.i4.pp1367-1374
Phan Xuan Le , Nguyen Thi Phuong Loan , Nguyen Doan Quoc Anh , Hsiao-Yi Lee
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.
Volume: 14
Issue: 4
Page: 1367-1374
Publish at: 2025-12-01

Bioecological characteristics of modern soil cover in subtropic regions of Azerbaijan

10.11591/ijaas.v14.i4.pp1200-1207
Farida Verdiyeva Bahram , Turkan Hasanova Allahverdi , Mahsati Ismayilova Eyvaz , Elnur Huseynov Yusif , Telli Jabiyeva Elshad , Gunel Asgarova Farhad
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.
Volume: 14
Issue: 4
Page: 1200-1207
Publish at: 2025-12-01

Computer simulation and software engineering in optical analysis of phosphor-converted white light-emitting diodes utilizing barium sulfate

10.11591/ijaas.v14.i4.pp1384-1392
Le Thi Trang , Nguyen Thi Phuong Loan , Pham Hong Cong , Nguyen Doan Quoc Anh , Hsiao-Yi Lee
Achieving uniform nanoparticle dispersion in electrospun polymer nanofibers remains a critical challenge, as conventional electrospinning often leads to particle agglomeration and nozzle clogging, reducing fiber uniformity and functional efficiency. This study explicitly addresses this problem by developing poly (vinyl alcohol) (PVA)/BaSO4 composite nanofibers through both conventional and ultrasonic-assisted electrospinning. Scanning electron microscopy (SEM) revealed that ultrasonication effectively disrupted nanoparticle agglomerates, yielding smoother and more uniform fiber morphologies. X-ray diffraction (XRD) analysis further confirmed that ultrasonic processing reduced the crystalline intensity of PVA and BaSO4, indicating enhanced polymer–filler interaction and finer BaSO4 distribution. Quantitatively, the agglomeration slope decreased from 0.039 (conventional) to 0.006, and the mean crystallite size was reduced from approximately 470 to 300 nm. These results are consistent with recent advances showing that ultrasonic electrospinning improves nanoparticle dispersion and stability in polymer matrices, thereby enhancing optical and mechanical properties. Ultimately, this work demonstrates that ultrasonic-assisted electrospinning provides a robust and scalable strategy to fabricate lightweight, flexible, and multifunctional PVA-based radiation shielding materials with superior nanoparticle dispersion and structural homogeneity.
Volume: 14
Issue: 4
Page: 1384-1392
Publish at: 2025-12-01

Optimizing smart grids with blockchain-driven automation and demand response

10.11591/ijaas.v14.i4.pp985-998
B. Jyothi , Bhavana Pabbuleti , Ravi Ponnala , Kambhampati Venkata Govardhan Rao , S. Sai Srilakshmi , Putta Dhanush Narasimha , Mareboyina Karthik Yadav , Malligunta Kiran Kumar , Ch. Rami Reddy
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.
Volume: 14
Issue: 4
Page: 985-998
Publish at: 2025-12-01

Development of a hydraulic jack system bending tool for improved manufacturing efficiency

10.11591/ijaas.v14.i4.pp1072-1082
Muhammad Arsyad Suyuti , Rusdi Nur , Ahmad Nurul Muttaqin , Arminas Arminas , Zainal Sudirman
This article presents the design, fabrication, and testing of a hydraulic sheet metal bending tool. The main objective was to create a tool capable of bending sheets of various thicknesses, ranging from 2 to 4 mm, with high precision and minimal operator effort. The design incorporates a hydraulic ram for easy operation, allowing multiple plates to be bent in a short period of time. Key calculations, including bending force, spring load, and hydraulic force, are performed to ensure the efficiency and safety of the tool. Experimental results show that the tool is able to achieve the desired bending angles, with minimal spring return, and can handle up to three 10 cm wide sheets in approximately 10 minutes. The performance of the tool has been proven by tests, and the results confirm that it can meet the requirements of industrial sheet metal bending. Based on these results, the tool demonstrates its effectiveness in small and medium-scale operations, providing a cost-effective solution for sheet metal production.
Volume: 14
Issue: 4
Page: 1072-1082
Publish at: 2025-12-01

Advancements in electric vehicle safety and charging infrastructure

10.11591/ijaas.v14.i4.pp1332-1339
Debani Prasad Mishra , Rudranarayan Senapati , Nisha Kedia , Sanchita Sahay , Raj Alpha Swain , Surender Reddy Salkuti
In electric vehicles (EVs), safety measures must be taken to prevent dangerous accidents. Safety regulations must be in place for two important things: electric or EV batteries and EV equipment. Operating an electric vehicle charging stations (EVCS) is a challenging task. This holistic approach is used to evaluate when renewable energy is produced. It's best to focus on the popularity of EVs as more and more people choose this mode of transportation. It is important to know that power plants can be risky. Therefore, safety issues related to EV charging must be addressed quickly and appropriately. Potential safety issues with EVs include overcurrent, ground faults, and overheating. If the charging system does not work, the electric car's battery may heat up and catch fire, and overcharging may cause other problems. To avoid security risks, you must comply with security regulations, use payment devices that meet security requirements, and follow the manufacturer's instructions.
Volume: 14
Issue: 4
Page: 1332-1339
Publish at: 2025-12-01

Li-Fi technology for automated transport

10.11591/ijaas.v14.i4.pp1129-1136
Popuri Rajani Kumari , Chalasani Suneetha , Maddali Anil Kumar , Tangirala Mrudula , Anbumani Venkatachalam , Bodapati Venkata Rajanna , Giriprasad Ambati
India is now one of the countries that is growing quickly worldwide. Today, practically for everything, a vehicle is necessary. Vehicle production is growing rapidly. One of the downsides of this enormous increase is the ineffective management of traffic. The well-planned expansion of transport organizations has resulted in a variety of challenges with travel. It is detrimental to both mankind and the economy when emergency vehicles like ambulances and fire engines are late in arriving. Smart transport is the most effective strategy to lower vehicle accidents and communicate with other cars to open a way for emergency vehicles. Here, the preliminary ideas and findings of a small-scale model of an automated transport system are presented using an innovative discovery known as Li-Fi, also known as light-fidelity. Full duplex communication is accomplished with Li-Fi, in which light is modified at speeds that are too rapid for the eye to follow. Li Fi may be used to create intelligent transportation systems since it offers various advantages over other communication protocols.
Volume: 14
Issue: 4
Page: 1129-1136
Publish at: 2025-12-01

AI-integrated pharmacy systems: bridging technology, ethics, and patient care

10.11591/ijaas.v14.i4.pp1305-1321
Adi El-Dalahmeh , Nevien Nedal , Khulood Abu Maria , Sara Abu Tarboosh
The operation of pharmacy systems undergoes transformation through artificial intelligence (AI), which advances from manual procedures to intelligent adaptive tools. These technologies enhance daily operations through prescription verification, drug interaction alerts, and inventory management while decreasing human mistakes. Through AI, patients gain access to customized medication recommendations, automatic appointment alerts, and virtual support services. The advancement of technology creates multiple new difficulties for healthcare systems. The increasing integration of AI in healthcare creates growing concerns about data privacy alongside algorithmic bias and the requirement for decision-making explanations. This paper evaluates AI systems against conventional pharmacy methods through an assessment of their precision and speed and their impact on patient safety and ethical preparedness. The adoption of AI systems requires strong ethical protections together with defined regulatory frameworks to maintain human clinical decision-making authority in patient care.
Volume: 14
Issue: 4
Page: 1305-1321
Publish at: 2025-12-01

Stacking architecture-endpoint detection: a hybrid multi layered architecture for endpoint threat detection

10.11591/ijaas.v14.i4.pp1263-1280
Abd Rahman Wahid , Desi Anggreani , Muhyiddin A. M. Hayat , Aedah Abd Rahman , Muhammad Faisal
Modern endpoint threat detection systems face persistent challenges in balancing detection accuracy, resilience against zero-day attacks, and the interpretability of artificial intelligence (AI) models. Although deep learning (DL) approaches often achieve high accuracy on benchmark datasets, they remain vulnerable to adversarial perturbations and operate as opaque “black boxes,” thereby reducing trust and limiting practical adoption in critical infrastructures. This research introduces stacking architecture-endpoint detection (STACK-ED), a hybrid multi-layered architecture for endpoint threat detection. STACK-ED integrates three complementary paradigms: supervised learning for known attack patterns, self-supervised Fgraph-based learning for structural relationships, and unsupervised anomaly detection for emerging or unknown threats. The outputs are consolidated by a meta learner, followed by a post-hoc correction (PHC) mechanism to minimize false negatives. The framework was evaluated on a combined benchmark dataset (CSE-CIC-IDS2018 and UNSW-NB15, hereafter referred to as HIDS-Set). Experimental results demonstrate state-of-the-art performance, achieving an F2-score of 98.89% after hybrid integration and active learning, with the primary optimization objective being the reduction of undetected attacks. Furthermore, the Shapley additive explanations (SHAP) method enhances interpretability by revealing feature contributions, while the PHC successfully recovered 62.64% of missed zero-day candidates. The findings position STACK-ED not only as a highly accurate detection model but also as an adaptive, resilient, and transparent framework, offering practical implications for enterprise-grade endpoint defense and future zero-trust cybersecurity systems.
Volume: 14
Issue: 4
Page: 1263-1280
Publish at: 2025-12-01

Artificial intelligence-based multi-key security for protected and transparent medical cloud storage

10.11591/ijaas.v14.i4.pp1241-1250
Ravi Kiran Bagadi , Neelima Santoshi Koraganji , Bandreddi Venkata Seshukumari , Kavya Ramya Sree Karuturi , Sireesha Abotula , Bodapati Venkata Rajanna , Mahalakshmi Annavarapu , Nitalaksheswara Rao Kolukula , Jayasree Pinajala , James Stephen Meka
Ensuring the security and privacy for the patient medical records and medical reports data is a crucial challenge as cloud-based healthcare technologies become more prevalent. For cloud-hosted medical data, internet of things (IoT) and artificial intelligence (AI) technologies shows best solutions for the challenges in the medical domain. This study suggests a Secure and Transparent Multi-Key Authentication Framework that makes use of AI. Using Z-score normalization, the framework first preprocesses the data before clustering to create a multi-level multi-key security structure. The physics-informed triangulation aggregation neural network (PITANN) model in the study reduces computation costs by minimizing overhead, ensuring secure handling of location-based and medical data for enhanced data classification and encryption effectiveness. A multi-key derivation of an elliptic curve, the ElGamal cryptography scheme is presented, which allows for safe multi-key encryption with little increase in the length of the ciphertext. This method guarantees safe, confidential access to cloud-hosted encrypted health information. An envisioned amalgamation improves flexibility by enhancing performance metrics such as speed of computation while safeguarding patient information through enhanced security measures and ensuring precise medical record integrity within virtual healthcare systems.
Volume: 14
Issue: 4
Page: 1241-1250
Publish at: 2025-12-01

Investigating relationships between reading comprehension and oral reading fluency through AI-driven tool reading progress

10.11591/ijaas.v14.i4.pp1192-1199
Pham Duc Thuan , Pham Thi Tam
This study investigates the relationship between reading comprehension and oral reading fluency components—accuracy and rate—among 113 Vietnamese EFL university students using the AI-powered tool Microsoft Reading Progress. Over 14 weeks, students engaged in weekly oral reading and comprehension tasks using integrated Microsoft Teams features. Fluency metrics (accuracy and rate) and comprehension scores were automatically collected and analyzed using Pearson correlation. The results revealed weak but statistically significant positive correlations between reading comprehension and accuracy (r = .257, p < .01), and between comprehension and rate (r = .289, p < .01), suggesting that improvements in fluency modestly support comprehension. A strong correlation between accuracy and rate (r = .765, p < .01) was also observed. The study highlights the effectiveness of Reading Progress in capturing fluency data and promoting self-paced improvement. However, limitations such as the short duration, localized sample, and constraints of accent recognition in AI-based speech analysis affect the generalizability and validity of results. The findings support the pedagogical integration of AI tools in EFL instruction while calling for future research with larger samples, extended timelines, and diversified digital tools to further validate and expand on these results.
Volume: 14
Issue: 4
Page: 1192-1199
Publish at: 2025-12-01

Clinical dental students' perceptions of difficulties in fixed prosthodontics bridgework denture preparation: a pilot study

10.11591/ijphs.v14i4.24623
Aditya Pratama Sarwono , Khairunnisa Febianti
Preparing abutment teeth for fixed bridgework presents varying challenges to dental students, impacting their training effectiveness and clinical outcomes. Understanding the most difficult stages can help improve educational strategies. This study aims to rank the difficulty of each stage in abutment tooth preparation using student evaluations, identifying the greatest challenges. A quantitative approach was used, analyzing perceptions of 155 clinical dental students from 2021-2023 cohorts at Faculty of Dentistry, Universitas Trisakti, through the non-parametric Friedman’s ANOVA Test. Student evaluations covered seven stages of abutment tooth preparation, identifying variability in perceived difficulty from most difficult to easiest. Results indicate the most difficult stage is proximal reduction (mean rank: 3.01), followed by cervical preparation (mean rank: 3.28), and lingual reduction (mean rank: 3.35). The stages with the lowest difficulty are finishing (mean rank: 5.35), followed by alignment of preparation between 2 abutment teeth (mean rank: 4.85), buccal reduction (mean rank: 4.13), and occlusal reduction (mean rank: 4.03). Proximal reduction is particularly difficult due to the need for high technical skills and precision, requiring accurate space estimation and careful reduction without damaging adjacent teeth. This difficulty is compounded by natural variations in tooth shapes and positions among patients. Findings highlight the importance of refining educational strategies to tackle these challenges, enhancing student learning and clinical skills. This research provides crucial data on which stages need greater emphasis in the curriculum, aiding the creation of more efficient and focused training methods.
Volume: 14
Issue: 4
Page: 1730-1737
Publish at: 2025-12-01
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