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31,456 Article Results

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

Mapping research trends in innovative pedagogies: a bibliometric analysis

10.11591/ijere.v14i6.34519
Nurul Eeffah Awang , Hafizhah Zulkifli , Mohd Isa Hamzah
This study examines global research trends in innovative pedagogy through a bibliometric analysis of 901 Scopus-indexed publications from 2022 to 2024. Despite the growing importance of innovative pedagogy in modern education, a systematic evaluation of its research landscape is still limited. This study bridges this gap by analyzing key trends, including influential works, authors, citation networks, and emerging themes. Using VOSviewer for data visualization, the findings reveal a growing research focus on AI-driven learning, immersive technologies, and problem-based methodologies. The analysis highlights the social sciences as the dominant field (45.3%), with increasing contributions from computer science and engineering. The United States, Australia, China, and India emerge as leading contributors, while developing regions show an increasing presence in pedagogical innovation. Research indicates a shift towards digital and experiential learning environments, yet challenges such as digital accessibility, equity, and ethical concerns persist. The study underscores the importance of interdisciplinary collaboration and policy interventions to tackle these challenges. By providing a comprehensive overview of the research landscape, this study serves as a roadmap for educators, policymakers, and researchers to promote sustainable and inclusive advancements in innovative pedagogy.
Volume: 14
Issue: 6
Page: 4567-4579
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

Generative adversarial network for intelligent haze removal from high quality images

10.11591/ijaas.v14.i4.pp1340-1349
Ali Abdulazeez Mohammed Baqer Qazzaz , Hayfaa T. Hussein , Shroouq J. Al-janabi , Yousif Mudhafar
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.
Volume: 14
Issue: 4
Page: 1340-1349
Publish at: 2025-12-01

STEM teaching competency framework for pre-service teacher: a study in Vietnam

10.11591/ijere.v14i6.35387
Phan Nguyen Truc Phuong , Bui Van Hong , Dinh Van De
Science, technology, engineering, and mathematics (STEM) education has been emphasized in Vietnam’s new general education curriculum; however, the teaching competencies of pre-service teachers in this area remain underexplored. This study addresses that gap by proposing and validating a STEM teaching competency framework tailored for pre-service teachers. A mixed-methods approach was employed, including literature review, expert interviews, and surveys. The sample consisted of 400 participants— pre-service teachers, in-service teachers, and lecturers—selected through stratified random sampling. Data were collected using questionnaires and analyzed with SPSS 24. Reliability was confirmed using Cronbach’s alpha (0.724) and construct validity was assessed through exploratory factor analysis (EFA). Results indicate that pre-service teachers face challenges in interdisciplinary integration, classroom organization, and technology application. The proposed framework includes five key domains: understanding STEM education, designing integrated lessons, organizing learning environments, implementing instruction, and evaluating and improving teaching practices. This study offers a reliable and practical tool to assess and enhance STEM teaching competencies. Its novelty lies in contextualizing competencies for pre-service teachers in Vietnam. The framework has practical implications for teacher training programs and policy development, and further application across teacher education institutions is recommended.
Volume: 14
Issue: 6
Page: 4734-4743
Publish at: 2025-12-01

Prediction index drought use neural network based rainfall

10.11591/ijaas.v14.i4.pp1146-1154
Nur Nafiiyah , Ali Mokhtar
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.
Volume: 14
Issue: 4
Page: 1146-1154
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

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

Assessment apps to evaluate students’ reading progress in English classroom

10.11591/ijere.v14i6.32907
Gina Karina Camacho-Minuche , Eva Ulehlova , Verónica Espinoza-Celi
The traditional way to assess students’ reading progress hinders their motivation and engagement, which negatively affects their academic performance. Therefore, this study seeks to address the issue by analyzing the effectiveness of three interactive technological assessment tools: Kahoot, Quizizz, and Socrative, as alternatives for assessing English as foreign language (EFL) students’ reading comprehension, as well as exploring the students’ perceptions about the use of these technological tools. This quasi-experimental study involved mixed method approach and consider 60 senior high school students of Loja, South of Ecuador as a purposive sample. There were outlined advantages and drawbacks linked to three assessment technological tools applied; however, Socrative revealed to be the most effective. Effectiveness seemed contingent upon several variables, such as the educational goals, functionalities of the tools, and the students’ settings. Additionally, the use of technological tools provided a range of resources to enhance dynamism and engagement of learning by facilitating interaction among students. In essence, this resulted in the consolidation of new knowledge, enabling students to retain information over an extended duration.
Volume: 14
Issue: 6
Page: 5151-5160
Publish at: 2025-12-01

Adopting the principal instructional management rating scale for enhancing instructional delivery in Nigerian schools

10.11591/ijere.v14i6.34958
Hafsat Aliyu Bada , Habibat Abubakar Yusuf , Jumoke Iyabode Oladele , Peter Babajide Oloba
This study explores the validation and application of the principal instructional management rating scale (PIMRS) for enhancing instructional leadership in Nigerian secondary schools. This was achieved by checking its content, face, construct, and reliability, with a focus on how clear the language was and how it related to culture. A sample of 100 secondary school teachers from four schools in North-Central Nigeria participated in this research. Expert reviews ensured content validity, while the instrument demonstrated high reliability, with an overall Cronbach’s alpha coefficient of 0.95. The subscales for the three dimensions achieved acceptable reliability: 0.83 for defining the school mission (DSM), 0.87 for managing the instructional program (MIP), and 0.91 for shaping the school learning climate (SLC). The results also showed strong positive relationships between the PIMRS dimensions, which supports the tool’s usefulness for evaluating how Nigerian schools handle instructional leadership. This study provides a robust foundation for further research on instructional leadership in Nigeria and offers a validated tool to improve school leadership practices, enhance instructional delivery, and ultimately foster student achievement. The adoption of the PIMRS in Nigerian secondary schools has the potential to drive systemic improvements in school effectiveness and instructional leadership. The findings suggest refining the sub-scales of monitoring halls, venues, and instructional feedback to teachers (IFT) for enhanced reliability. Additionally, capacity-building workshops for principals and integration of PIMRS into leadership training programs, as well as policy adoption for standardized evaluation, are essential for successful implementation and improved instructional leadership.
Volume: 14
Issue: 6
Page: 5067-5079
Publish at: 2025-12-01

Navigating ethics: social media challenges in Indonesian dental practice

10.11591/ijphs.v14i4.24582
Aditya Pratama Sarwono , Marie Louisa
Social media has evolved into an important tool for dental practitioners to promote their services and attract patients, necessitating a careful balance between effective promotion and upholding ethical standards to maintain patient trust. This research delves into the challenges and implications associated with using social media in dentistry, emphasizing the ethical considerations, legal frameworks, and the potential impact on public understanding of oral and dental health. By providing a comprehensive discussion on the importance of ethical promotion in the dental profession, the study not only highlights the need for dental practitioners to prioritize ethical standards in their social media activities but also offers effective strategies for attracting patients. These strategies include delivering relevant and informative content, engaging with followers, demonstrating professionalism and expertise, obtaining informed consent, and respecting patient privacy. The research underscores that navigating these complexities is essential for dental practitioners to promote their services ethically, contributing to the success and growth of their practice while safeguarding the integrity of health information and fostering positive relationships with the public.
Volume: 14
Issue: 4
Page: 1897-1908
Publish at: 2025-12-01

A qualitative study on factors of management institute: alumni association contributing to the institute’s growth

10.11591/ijere.v14i6.32690
Raghav Sandhane , Kanchan Patil
Institutes imparting management education in India are rising in numbers. They are struggling to keep in pace with the competition and are facing several challenges. After studying these challenges, researchers have proposed several approaches including better advertisement, having experienced faculty and attracting companies for recruitment as possible areas for improvements. One of the proposed areas that seems to address a variety of the challenges, is having a better institute-alumni association. The research conducted on the alumni-institute association thus far have highlighted only a limited number of areas. Hence, this grounded study was conducted to bring forth all the possible factors and the sub factors of association between the alumni and the institute. This is a qualitative study that uses dialogic theory as an underpinning theory to aid data collection and analysis. The 13 decision makers with minimum of 15 years of teaching/administration experience in post graduate institutes were interviewed. The empirical data was analyzed using code analysis technique. The analysis presented a model of factors and sub factors to enable better institute-alumni association. The model clearly identifies the areas to focus on for developing a strong alumni association. One of the foremost findings of the research is the identification of the need for institute’s contribution in alumni growth and the ways to make this happen. Institute risk identification is another important area for alumni contribution. The developed model serves as a ready reckoner for the management institutes in its pursuit of growth.
Volume: 14
Issue: 6
Page: 4340-4352
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

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

Chatbot for virtual medical assistance

10.11591/ijict.v14i3.pp914-922
Aravalli Sainath Chaithanya , Sampangi Lahari Vishista , Adepu MadhuSri
A healthy population is vital for societal prosperity and happiness. Amidst busy lifestyles and the challenges posed by the COVID-19 pandemic, individuals often neglect their health needs. To address this, we introduce a novel approach utilizing a chatbot for virtual medical assistance. Tailored for individuals confined indoors or hesitant to visit hospitals for minor ailments, our chatbot offers personalized medical support by diagnosing ailments based on user-reported symptoms and engaging in interactive conversations. Leveraging a robust dataset containing 132 symptoms, 41 diseases, and corresponding medications, our chatbot employs a systematic approach for symptom refinement, enhancing diagnostic precision. Upon identifying a disease, the chatbot promptly suggests basic medications tailored to the specific ailment. Furthermore, our system integrates user demographics to evaluate medication history and current state, allowing for personalized medication recommendations based on individual needs. Through extensive testing and validation, we demonstrate the effectiveness of our chatbot in accurately predicting ailments and providing timely treatment advice. Our study introduces a novel paradigm for medicine recommendation and disease prediction, with the potential to enhance healthcare accessibility and effectiveness.
Volume: 14
Issue: 3
Page: 914-922
Publish at: 2025-12-01
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