Biliran Province State University

Image processing is a technique to translate an image into digital form and execute some operations on it to obtain an improved image or extract some useful information from it. FloraFolium aimed to address the challenges in plant identification, especially in the Philippines, where many plant species are not well-studied or properly recorded. Many people struggle to tell which plants are edible, medicinal, or toxic because of limited access to official guides and reliable information. To solve this problem, the FloraFolium project created a mobile application that uses Convolutional Neural Networks (CNNs) to identify plant leaves and classify them into three categories: edible, medicinal, or toxic. The system was tested and evaluated based on ISO 25010 software quality standards. The results showed high ratings for functionality, usability, and efficiency, making the app reliable for everyday use. While the app performed well, some areas, like security and reliability in unusual conditions, need improvement. The study also found that the image quality greatly affects the system's accuracy. A balanced dataset of 15,000 images was divided into 80% for training and 20% for testing/validation. The model achieved a test accuracy of 99% and an overall validation accuracy of 98.8%, with the best weights saved at epoch 20 during the 30-epoch training period. The FloraFolium app is a helpful tool for outdoor enthusiasts, gardeners, farmers, and anyone interested in learning more about plants. It can also help preserve traditional knowledge about medicinal plants

This study proposes a multidimensional metric for evaluating deep learning models in face image classification, addressing long-standing limitations of accuracy-centered evaluation. While modern architectures such as convolutional neural networks and Vision Transformers demonstrate strong predictive performance, conventional metrics fail to capture deeper structural behaviors, including fairness, representational quality, interpretability, and computational viability. To address this gap, the proposed framework integrates six components: validation F 1 score, linear-probe embedding separability, fairness via skin-tone gap reduction, compute efficiency, anatomical interpretability, and embedding stability, yielding a holistic assessment of model performance. Applied across six benchmark architectures and four Baumann Skin Type tasks, the metric reveals consistent superiority of transformer-based models, which exhibit stronger fairness, stability, and interpretability compared to CNNs. Findings demonstrate that responsible facial model evaluation requires multidimensional criteria that move beyond accuracy to ensure equitable, transparent, and deployment-ready systems. This work contributes toward trustworthy and fairness-aware facial AI.

This cross‑sectional study assessed the prevalence, predictors, and substance use risk profile among 333 incarcerated males at the Freetown Male Correctional Centre. The WHO-ASSIST tool was used for data collection. The risk of substance-related issues was categorised as low, moderate, or high. Logistic regression was done to identify predictors of lifetime substance use (Model I) and recent use within the past three months within or outside prisons (Model II). The prevalence of lifetime substance use was 88.6% (95% CI: 0.85-0.92), recent use 73.9% (95% CI: 0.69-0.79), and polysubstance use 77.2% (95% CI: 0.73-0.82). Tobacco (80.5%), cannabis (70.0%), alcohol (68.2%), and opioids (64.0%) were the most used substances. In adjusted models, older age, unmarried status, and rural residence were significant predictors of both lifetime and recent use, while education status was specifically associated with recent use. Risk profiles revealed a high level of dependence among tobacco users and moderate risk among most cannabis and opioid users. Substance use was notably high, with tobacco, cannabis, and opioids emerging as the primary substances of concern. These findings underscore the burden of substance use and highlight the need for targeted interventions and the integration of cessation programs within the correctional centre.

This study explored the everyday realities of female barangay captains in Leyte, Philippines. It focused on their personal identities and strategies they used to navigate the social and political spheres within their local communities. This study employed a qualitative-phenomenological method. 13 female chiefs served as informants and were purposively selected by the researchers. An interview guide was used as the primary data collection instrument. The analysis follows Braun and Clarke approach to generate themes to describe the informant’s experiences. The results were categorized into experiences, coping with challenges, and aspirations. Seven themes were identified for the experiences: Impactful Service, Personal Fulfillment, Collaborative Environment, Leadership Identity, Personal Hardship, External Adversity, and Leadership Demands. Conversely, three themes were identified as the coping strategies of the female village chiefs, namely Community-Centric Action, Personal Leadership Stance, and Strategic Governance. Moreover, three themes were generated to represent the aspirations: Holistic Community Progress, Enhanced Community Harmony, and Effective Governance. This deep dive into the lifeworld of female village chiefs in the communities in the 3rd congressional district of Leyte has unveiled a myriad of noteworthy leadership stories, struggles, and triumphs, which are evidence of strategic actions and support programs from both the local government and from the community members they led.

Layunin ng pag-aaral na ito na idokumento, ilarawan, at isalin ang mga leksikon sa pangingisdang kubkuban, partikular ang mga katawagan sa mga proseso, kagamitan, at uri ng mga isdang nahuhuli sa bayan ng Kawayan, Biliran. Ginamit ang kuwalitatibong metodong mini-etnography upang makipamuhay sa mga mangingisda at holistikong mailarawan ang mga leksikon ng kubkuban. Pinili ang 17 kalahok na kubkubero mula sa dalawang barangay gamit ang purposive sampling. Ang mga pamamaraan ng pagkolekta ng datos ay kinabibilangan ng pakikipagkuwentuhan, impormal na panayam, gabay na tanong, paggamit ng rekorder, at pagtatala ng mga field notes. Isinagawa ang transkripsiyon, pagkilala, paghahanay, pagkategorya ng mga leksikon, at pagsusuri sa kayarian at bahagi ng pananalita. Nagsagawa rin ng member checking at balidasyon ng mga eksperto sa paglalarawan at pagsasalin ng leksikon. Natuklasan sa pag-aaral ang kabuuang 100 leksikon: 37 tumutukoy sa mga proseso, 38 sa mga kagamitan, at 25 sa mga uri ng nahuhuling isda. Karamihan sa mga leksikong ito ay mga pandiwa, pangngalang pambalana, at pang-uri. Mayroon ding mga hiram mula sa ibang wika, mga terminong walang katumbas na salin sa Ingles at Filipino, at mga salitang may partikular na kahulugan na mas nauunawaan sa kultural na konteksto ng paggamit. Ang mga leksikong ito sa pangingisdang kubkuban ay nagbubukas ng pananaw sa natatanging kultura ng mga lokal na industriya ng pangingisda sa bansa. Mahalaga ang pag-aaral sa pagpapayaman ng mga leksikal na entri sa wikang Filipino mula sa mga wika ng rehiyon, tungo sa pagpapahusay ng lokalisado at kontekstuwalisadong kasangkapan sa pagtuturo. Makabuluhan din ang nakalap na datos sa pagsusulong at pagpapanatili ng mga yamang panglingguwistika ng bansa para sa pangangalaga ng kultura at pagpapanatili ng pamanang pangisdaan.