Journal of Asian Scientific Research

Wildlife protection through UAV surveillance with thermal infrared imaging and deep learning

Raja Vavekanand, Abdullah Ayub Khan — Fri, 06 Feb 2026 00:00:00 -0600

The purpose of this study is to develop a real-time UAV-based wildlife surveillance system capable of detecting camouflaged and nocturnal animals using thermal infrared imaging. The study addresses the limitations of RGB and night-vision cameras, which perform poorly in low-light and vegetation-dense environments, by introducing a unified deep learning approach tailored for TIR data. The methodology uses the BIRDSAI aerial thermal dataset and adapts the YOLOR architecture through multi-channel TIR augmentation and adaptive thresholding. The model was evaluated against YOLOv5 and CenterNet2 under identical configurations, with performance assessed through mAP, inference speed, and precision-recall analysis. Experiments were performed on both synthetic and real TIR sequences with extensive augmentation to enhance robustness. The findings show that the proposed YOLOR-based framework achieves a mAP of 38.2% and real-time processing at 73.6 FPS, outperforming YOLOv5 and CenterNet2 in detecting small, low-contrast, and camouflaged animals. Adaptive thresholding improved precision by 4%, particularly for species with overlapping heat signatures. Class-merging and multi-channel enhancement further improved detection stability under limited data conditions. The practical implications indicate that UAV-mounted TIR imaging combined with unified deep learning models offers an efficient solution for nocturnal wildlife protection, anti-poaching operations, and remote habitat monitoring. The system’s real-time capability supports large-scale conservation applications in environments where traditional visual-spectrum methods fail.

Emotional burnout in psychology students and its correction using cognitive-behavioral therapy

Tue, 10 Feb 2026 00:00:00 -0600

Emotional burnout among psychology students has specific characteristics. 1) Background: This condition results from the nature of the profession, which involves constant interaction with people, requiring sociability, empathy, and a strong professional identity. There are also particular features of emotional burnout in junior and senior psychology students. The differences in burnout between students at various academic levels have not been sufficiently studied. Additionally, methods for preventing mental health issues in students using cognitive-behavioral therapy have not been extensively researched. This study aims to examine the specific aspects of emotional burnout in junior and senior students and to correct their mental state through cognitive-behavioral therapy. 2) Methods: The research employed a pedagogical experiment, Spearman correlation analysis, Holland’s Vocational Interest Test, cognitive-behavioral therapy, Rational Emotive Behavioral Therapy (REBT), Cognitive Behavioral Art Therapy (CBAT), and cognitive therapy, which focuses on the connection between thoughts, feelings, and behaviors. 3) Results: The study found that emotional burnout in junior students is primarily associated with academic reasons, whereas in senior students, it relates to professional identity and competence in psychological practice. 4) Conclusion: The novelty of this research lies in the comparative analysis of the phases of emotional burnout among psychology students, identifying the causes of their mental states, and applying the latest cognitive-behavioral therapy methods.

Policies and strategies for the prevention and control of anemia and malnutrition in children and pregnant women: A systematic review

Tue, 10 Feb 2026 00:00:00 -0600

Malnutrition and anemia among children and pregnant women remain significant global public health challenges, particularly in low- and middle-income countries. These conditions hinder physical growth and cognitive development in children and compromise maternal health, thereby reinforcing cycles of poverty, disease, and premature mortality. Addressing these issues requires effective, sustainable, and context-sensitive responses. This study aims to systematically organize and examine policies and intervention strategies designed to prevent and control anemia and malnutrition in children under five and pregnant women. A systematic review was conducted using databases such as Scopus, EBSCO, Web of Science, and Taylor & Francis, covering publications from 2000 to 2023. The review adhered to PRISMA guidelines and applied the Joanna Briggs Institute quality appraisal standards. From an initial pool of 554 records, 28 studies met the inclusion criteria and were analyzed. Most of the included studies employed quantitative research designs, while fewer utilized qualitative or mixed-method approaches. Common interventions identified include iron and folic acid supplementation, deworming, food fortification, nutrition education, dietary diversification, and behavior change communication. Iron and folic acid supplementation consistently demonstrated effectiveness, especially when combined with educational components. However, several challenges persist, including low adherence to supplementation, socioeconomic and cultural barriers, limited resources, weaknesses in implementation, and regional differences in intervention effectiveness.

Development of ZE41 Mg–Nano-CDHA composites for biodegradable implant applications

Tue, 10 Feb 2026 00:00:00 -0600

In this current work, nanocrystalline calcium-deficient hydroxyapatite (CDHA) was synthetically produced using calcium hydroxide and diammonium phosphate through a wet chemical synthesis route. X-ray diffraction (XRD) analysis and electron microscopy demonstrated the nano-level (~47 nm) of the produced CDHA. Then, the nano-CDHA was reinforced into ZE41 Mg alloy by friction stir processing (FSP) aimed at manufacturing degradable bone implants. Microstructures clearly demonstrated the development of a fine-grained structure (7.4 ± 6.9 µm) in addition to incorporating nano-CDHA into ZE41 Mg alloy. FSP resulted in decreased intermetallic phases, which suggests increased solubility of zinc into magnesium due to FSP. XRD analysis of the composite confirms the development of a basal-dominated texture in the composite. From the potentiodynamic polarization studies, corrosion performance was assessed using simulated body fluid (SBF). The composite exhibited noble behavior by demonstrating a lower corrosion current density (-1.23 ± 0.8 × 10^-4 A/cm²) compared with ZE41 alloy (-4.75 ± 1.1 × 10^-4 A/cm²). Lower weight loss was observed for the composite after 72 hours of immersion in SBF, indicating improved degradation resistance due to the incorporated nano-CDAH and grain refinement. The lower corrosion rate measured for the composite (11.4 ± 2.1 mm/year) is 40% lower compared with ZE41 alloy (19.3 ± 1.8 mm/year) based on weight loss data. The results demonstrate the feasibility of FSP to develop ZE41-nano-CDHA composite with better corrosion control.

A semi-supervised deep learning framework for efficient PCB defect detection confidence-thresholded self-training with YOLOv5

Zhenxia Wang, Nurulazlina Ramli, Tzer Hwai Gilbert Thio — Wed, 25 Feb 2026 00:00:00 -0600

Printed Circuit Board (PCB) defect inspection is critical in electronics manufacturing, yet annotating large training sets is labor-intensive and costly. This paper proposes a semi-supervised PCB defect detection framework based on YOLOv5, which leverages a small labeled dataset and a larger pool of unlabeled images through an iterative self-training pipeline. A YOLOv5 detector is first trained on the limited labeled data, then used to generate pseudo-labels on unlabeled images; high-confidence detections are retained as defect annotations, and the model is retrained on the combination of labeled and pseudo-labeled data. This pseudo-labeling and retraining cycle is repeated for multiple iterations to progressively refine the detector. The approach is evaluated on a PCB defect dataset with 100 labeled and 1,000 unlabeled images, and shows significant gains over a fully supervised baseline. The proposed semi-supervised YOLOv5 achieves 91.6% mAP@0.5 with only 100 labeled images, outperforming both the baseline (87.0% mAP) and prior semi-supervised methods, while substantially improving recall and precision. The results demonstrate that the method effectively reduces annotation effort while maintaining high detection accuracy, providing a simple, confidence-thresholded self-training strategy for deploying PCB defect detectors under limited labeling resources. This work directly supports SDG 9 by enabling cost-efficient, high-accuracy AI-based PCB inspection that strengthens intelligent and sustainable manufacturing systems.

Modeling environmental behavior of elderly tourists in Northern Thailand: An extended theory of planned behavior approach

Warach Madhyamapurush — Tue, 10 Mar 2026 00:00:00 -0500

The rapid growth of aging tourism, combined with the urgent need for sustainable travel practices, underscores the importance of understanding the environmental behavior of elderly tourists. This study models the environmental behavior of elderly Thai tourists visiting Northern Thailand by extending the Theory of Planned Behavior (TPB) to include Environmental Knowledge and Connectedness to Nature. Data were collected from 400 elderly Thai tourists using a structured questionnaire and analyzed with Structural Equation Modeling (SEM). The measurement model demonstrated strong reliability, convergent validity, and discriminant validity, with both cognitive (Environmental Knowledge) and affective (Connectedness to Nature) constructs significantly enhancing predictive power. Multi-group analysis identified gender-based differences in model pathways, suggesting the need for targeted interventions. The study reveals that destination image significantly influences travel intentions, with a path coefficient of 0.67 (p < 0.01), while country image contributes with a path coefficient of 0.52 (p < 0.05). These findings highlight the importance of strategic marketing in shaping positive tourist perceptions. The findings contribute to theory by addressing critiques of TPB’s rationalistic bias, demonstrating the value of integrating emotional dimensions into behavioral models. This study also contributes to the literature by providing insights into the relationships between destination image and travel intentions. The main contribution of the study is the discovery that destination images, as well as country images, have a significant impact on the decision-making process of tourists. Limitations, including the use of non-probability sampling and cross-sectional data, are acknowledged, with directions for longitudinal, experimental, and goal-oriented future research proposed.

Efficient image cryptosystem using low-dimensional chaos, SHA-256, and random permutation

Joshua C Dagadu — Tue, 10 Mar 2026 00:00:00 -0500

Securing digital images has become increasingly challenging due to the vast volume of images produced and transmitted across various platforms, coupled with the rising incidence of cybersecurity threats. Although attention has shifted toward utilizing hyperchaotic systems for image encryption, many cryptosystems that incorporate high-dimensional chaos along with other computationally intensive techniques face drawbacks, including speed limitations. Therefore, there is a pressing need for encryption schemes that are simple, fast, and sufficiently robust to meet the requirements of lightweight systems. This paper proposes a simple and efficient image encryption algorithm based on chaotic diffusion and random permutation. In this scheme, two low-dimensional chaotic systems are used to generate encryption keys, with one system being influenced by a SHA-256 hash value. The encryption process involves two rounds of chaotic diffusion interleaved with a random permutation to secure the images. The two distinct chaotic keystreams are applied at different stages of the encryption process to enhance randomness. Hashing is incorporated into keystream generation to ensure that the encryption key has a partial dependence on the image being encrypted. Pixel scrambling is performed mid-way by the permutation function to enhance randomness in the process. Experimental analyses, including key, differential, and statistical analyses, demonstrate that the proposed algorithm is fast, robust, and resistant to various types of security attacks on digital images.

Assessment of the carbon footprint of football field rental operations in Thailand

Jakkarat Tabwav, Patikorn Sriphirom, Aungsiri Tipayarom — Wed, 11 Mar 2026 00:00:00 -0500

This study is the first to evaluate the greenhouse gas (GHG) emissions associated with football field rental operations in Thailand. The Carbon Footprint for Organization framework, following ISO 14064-1:2018 and the GHG Protocol, was applied to quantify the carbon footprint for both current-year operations (2024) and a 10-year renovation cycle. Two facilities were studied: Field A in Ratchaburi Province (8,000 m²; natural grass and artificial turf fields) and Field B in Nonthaburi Province (4,800 m²; two artificial turf fields). GHG emissions were categorized into direct (Scope 1), electricity-related indirect (Scope 2), and other indirect (Scope 3) emissions. In 2024, Scopes 1, 2, and 3 comprised 18.4%, 41.3%, and 40.3% of the total carbon footprint of Field A, and 37.0%, 22.8%, and 40.2% of the total carbon footprint of Field B, respectively. Over the 10-year cycle, renovation activities largely contributed to Scope 3 emissions, increasing total annual carbon footprints by 27.4% for Field A and 19.9% for Field B compared to current operations. Refrigerant leakage, electricity consumption, and employee and customer commuting were the main contributors to Scopes 1, 2, and 3 emissions, respectively. The annual carbon intensity per area ranged from 17.2 to 19.1 kg CO₂eq/m² for Field A and 15.2 to 16.4 kg CO₂eq/m² for Field B. Field surface type was the major contributor to emission patterns: natural grass fields generated higher operational emissions, whereas artificial turf fields produced greater renovation-related emissions. Using low-carbon electricity, low-carbon or natural refrigerants, and low-embodied-carbon materials may reduce emissions and promote sustainable football field management.

Digital charisma, cultural frames, and purchase intentions: Mediating role of attractiveness and moderation by self-concept

Wenhui Shi, Ribka Alan, Rohaizahtulamni Binti Radzlan — Wed, 11 Mar 2026 00:00:00 -0500

The study examines how digital charisma and cultural frames shape female consumers’ purchase intentions in the Chinese digital marketplace, focusing on the mediating role of perceived attractiveness and the moderating role of consumer self-concept. It aims to provide an advanced understanding of how psychological and cultural mechanisms interact in digital persuasion. A quantitative, cross-sectional design was adopted, and data were collected from 312 female consumers in China through a structured questionnaire. The scales for all constructs were adapted from prior research. Structural equation modeling (SmartPLS) was employed to examine the measurement and structural models, including direct, mediating, and moderating effects. The model demonstrated strong explanatory power, with R² = 0.684 for perceived attractiveness and R² = 0.739 for purchase intention, supported by satisfactory predictive relevance (Q² values of 0.733 and 0.680, respectively). Findings reveal that digital charisma and cultural frames significantly influence perceived attractiveness, which in turn mediates their impact on purchase intentions. Furthermore, consumer self-concept strengthens the attractiveness–purchase intention relationship when influencer image aligns closely with consumer identity. This study integrates digital charisma, cultural frames, and psychological constructs into a unified framework, emphasizing the strategic importance of cultural resonance and self-concept alignment in digital marketing.

Rice wine fermentation from Thai low-price rice using saccharomyces cerevisiae mutant with enhanced fatty acid ethyl ester production

Wed, 11 Mar 2026 00:00:00 -0500

Thai traditional rice wine, known as Sato, is produced from glutinous rice using a mixed-culture starter called Lookpang. This traditional method often suffers from variability and inconsistent flavor profiles. To address these issues, the study aimed to improve the quality of Thai traditional rice wine by utilizing a defined starter culture composed of high-fatty acid ethyl esters (FAEEs)-producing Saccharomyces cerevisiae and Aspergillus oryzae. The fermentation process followed a methodology similar to that used in Japanese sake production, aiming to achieve more consistent quality and flavor profiles in the final product. Furthermore, this study involved fermenting rice wine using low-cost Thai rice to enhance its value. The parental Saccharomyces cerevisiae strain, 312WT, was isolated from Thai Sugar Industry Co., Ltd., and demonstrated fermentation performance comparable to the commercial wine yeast strain EC-1118. Subsequently, conventional mutagenesis was applied to 312WT, resulting in a mutant strain, 312/6, which overproduces fatty acid ethyl esters (FAEE). Rice wine fermented with the 312/6 strain exhibited the highest concentrations of ethyl hexanoate (28.55 ± 7.91 µg/kg, OAV = 29) and ethyl octanoate (207.22 ± 51.65 µg/kg, OAV = 41). These compounds contribute sweet and sour apple flavors to beverages, respectively. Genomic DNA analysis, compared to the parental strain 312WT, demonstrated that 312/6 harbored several mutations in the fatty acid ethyl ester (FAEE) biosynthesis pathway genes (FAS1, FAS2, ACC1, EHT1, and EEB1). These genetic changes could account for the overproduction of FAEEs.

Multisensory engagement and inclusive learning: Exploring the museum experiences of Chinese visually impaired children

Yang Han, Norfarizah Mohd Bakhir — Wed, 11 Mar 2026 00:00:00 -0500

The researcher utilized the Multisensory Learning Theory and the Three-Dimensional Engagement Theory to support the methodology of this study, which employed both quantitative and qualitative methods of data collection through a combination of surveys and interviews. The research participant selection process was a purposive sample taken from two specific special educational schools in Fujian Province of China. There were thirty children who were visually impaired who participated in both multisensory exhibitions and conventional exhibitions. Based on the quantitative data collected, there was found to be a very large effect size on all dimensions of comfort, engagement, reinforcement, meaningfulness, and service for the children who attended the multisensory exhibition versus those who attended the traditional exhibition of museum exhibits. The qualitative data revealed that through the use of tactile, auditory, and visual stimuli, the children who attended the multisensory exhibition were afforded much greater emotional security, were more curious, and had a much stronger base for a cognitive understanding of the exhibits. Additionally, through a supportive staff member interaction environment, the children-built confidence and a sense of belonging. It offers practitioners an evidence-based reference for creating inclusive, child-focused educational environments that promote autonomy, confidence, and substantive participation for visually impaired learners.