Lyceum of the Philippines University

This research presents an Android Emergency and Hotline Assistance using a Geolocation Triaging Algorithm with a Multi-Criteria Weighted Priority Scoring Model for intelligent response application in the Province of Cavite. Developed using Visual Studio, Dart, Flutter Software Development Kit (SDK), and Firebase, the app provides a comprehensive solution designed to enhance public safety, promote well-being, and foster community resilience. Key features include accurate real-time geolocation triaging, centralized dashboard monitoring, and a Content Management System (CMS) for resource management and emergency preparedness. Test results confirmed 100 % operational reliability and 96.45% compatibility across Android versions and screen resolutions. The application also maintained functionality under limited or no internet connectivity, with optimal performance observed on 4 G and 5 G networks. To assess the reliability of the 4-point Likert scale test instrument, Cronbach's alpha was utilized, yielding a reliability coefficient of $\alpha=0.87$, indicating strong reliability. Additionally, the Mobile Application Rating Scale indicated that KONTAK achieved a high level of acceptability, with a mean (M) score of 3.71 and a standard deviation (SD) of 0.46. The Wilcoxon Signed-Rank Test indicated statistically significant improvements across all effectiveness indicators, with KONTAK outperforming traditional systems in response time, accessibility, and user satisfaction ($\mathbf{p}<.001$). These findings demonstrate its potential as a transformative solution for real-time emergency response and information dissemination.

This study presents a detailed examination of the current status of secondary vocational education in Hainan, China, particularly concerning how well it meets the demands of industry and prepares students for the modern workforce. Some of the areas of vocational education that the study discusses are its structure, curriculum, resource allocation, policy infrastructures, and effectiveness of industry-academy linkages. Data were collected from 203 secondary vocational teachers in Hainan (Hainan Provincial Tourism School and Haikou Vocational Tourism School) using a descriptive research design based on a survey. In an attempt to offer a more in-depth understanding of the existing landscape of vocational education in conjunction with industry requirements, the survey was grounded on theoretical frameworks such as Human Capital Theory as proposed by Becker, Triple Helix Model (Etzkowitz), Skills Gap Theory (Sawchuk) and Situated Learning Theory (Lave and Wenger). The findings provide a diverse demographic profile of educators, highly favorable perceptions of the state of the current vocational education system, and perceptions that graduates are well-trained for the labor market, with the technical and soft skills, readiness for, and adaptability needed by the industry. But the study also notes small gaps between the skills being taught and the skills today’s employers want. While there is great potential for improving collaboration between industry and academia, there are crippling barriers that prevent effective collaboration. Several measures are recommended such as curriculum development, improving internship opportunities, and joint projects among industry and academia. The results underscore the need for continued efforts to address skills gaps and build closer connections between Hainan's vocational schools and the industries they serve.

This paper presents a comparative analysis of three SQL querying techniques—Recursive Common Table Expressions (CTE), Path Enumeration, and Self-Joins—for traversing and managing genealogical data within a relational database environment. The study was implemented using PostgreSQL as the database management system, while D3.js was utilized for data visualization to better illustrate hierarchical family relationships and query results. These approaches were evaluated based on key performance indicators such as execution time, query planning time, accuracy of retrieved relationships, and scalability across varying query depths.The experiment made use of a proprietary dummy dataset specifically designed to simulate complex genealogical structures, including multiple generations, extended family connections, and branching lineage relationships. This dataset enabled the researchers to observe how each querying technique performs under increasing levels of data complexity and traversal requirements. The testing process also examined how efficiently each method could maintain performance as the depth of relationship queries increased.Results indicate that all three methods demonstrated high accuracy and comparable execution times when applied to shallow hierarchical queries. However, as the depth and complexity of the data traversal increased, Recursive CTEs showed better scalability and more consistent performance compared to Path Enumeration and Self-Joins. This suggests that Recursive CTE is more suitable for applications involving dynamic, large-scale, or frequently updated genealogical databases.This performance evaluation aims to guide database developers, system architects, and government agencies in selecting efficient data retrieval strategies for managing familyoriented information systems, particularly those requiring reliable hierarchical data processing and long-term scalability.This study is framed as a preliminary, proof-of-concept benchmark operating on micro-scale synthetic data. The findings establish a reproducible baseline of raw execution times in milliseconds and algorithmic growth patterns across query depths, and are not intended as production-scale claims. Extension of the methodology to larger datasets, together with the measurement of memory consumption and I/O overhead, is identified as future work.

With the rapid development of the digital economy, cross-border enterprises are presented with new development opportunities. However, they also face numerous challenges in credit evaluation. Traditional credit evaluation models, which often faced limitations in information collection, analytical vigor, adaptability, and predictive accuracy, fail to meet the requirements of cross - border transactions. The study critically examined the challenges posed by cross - border enterprises in credit evaluation in the context of the digital economy. By addressing such challenges, the research proposed a five-dimensional model encompassing financial strength, enterprise quality, management factors, operational capabilities, and the external environment. Each dimension is analyzed to capture the unique attributes and risks associated with cross-border operations, giving a more multidimensional framework for credit evaluation. Also, the study explored practical, acceptable, and innovative pathways for model implementation such as strategies for integrating digital technologies focusing on transparency and predictive accuracy in credit assessments, thereby contributing to the resilience and competitiveness of global enterprises in an increasingly interconnected world.