Mindanao Journal of Science and Technology

About this Special Issue

2025-01-12T08:26:48+00:00

This special issue of the Mindanao Journal of Science and Technology (MJST) is the result of a collaborative effort involving the authors, the University of Science and Technology of Southern Philippines (USTP), Bukidnon State University, Universitas Negeri Padang, and Universitas Negeri Yogyakarta. It features carefully selected papers in the fields of science, technology, and engineering, presented at the International Conference on Research, Innovation, and Investment (ICRII) held on September 16-17, 2024.

Quality Evaluation of Powdered Fern (Diplazium esculentum): Physicochemical, Phytochemical, Antioxidant, and Anti-inflammatory Properties in Aqueous Extracts

2025-01-12T08:26:48+00:00

This study examined the physicochemical, microbiological, nutritional, and mineral properties of Diplazium esculentum powder and the phytochemical, antioxidant, and anti-inflammatory properties of its aqueous products. Fresh D. esculentum leaves were oven dried at 50 °C for 5 h. The powder derived from the dried leaves exhibited a 20% yield and significant nutritional profile, rich in zinc mineral and protein, with low fat content. Additionally, the powder exhibited favorable flow properties (CI: 24.85, HR: 1.33), making it suitable for incorporating into various food products. Aqueous extracts of D. esculentum were prepared using a 2 x 3 factorial design with different extraction conditions, revealing a significant influence of extraction time and temperature on phytochemical content and bioactivity. Treatment 3 (40 °C for 6 h) demonstrated the highest phenolic content of 360.65 mg GAE/g, while the control (ethanolic extraction) yielded the lowest with 115.53 mg GAE/g. Treatment 6 (60 °C for 6 h) showed the highest flavonoid content of 17.92 mg QE/g. Moreover, extracts from longer extraction times showed higher levels of phenols, flavonoids, and antioxidant activity, with an IC50 value of 135.55μg/mL. Furthermore, the extracts revealed potent anti-inflammatory properties, particularly inhibiting the COX-2 enzyme. These findings emphasized the potential of D. esculentum as a valuable source of nutrients and bioactive compounds. The powder’s nutritional content indicated its potential applications in functional foods such as prebiotic-enriched foods, beverages, food additives, and baked goods. Furthermore, the extracts’ antioxidant and anti-inflammatory properties are a potential ingredient in nutraceuticals such as antioxidants and probiotics.

Comparative Study of Flexural Capacity of Precast Light Concrete Plate Building with Experimental and FEM Analysis

2025-01-12T08:26:51+00:00

The use of precast structural elements in the construction industry has grown rapidly. This study aimed to determine the first crack value and maximum load of lightweight concrete slabs; the crack patterns of lightweight concrete slabs; and the comparison of the first crack value and floor slab displacement in experimental testing and finite element modeling. This study used the four-point loading which was validated by finite element method (FEM). The experimental test specimens consisted of two variants, namely PN-1 and PN-2 for flexural testing, and PN-A for FEM with 120 mm x 600 mm x 2970 mm in dimensions. The results showed that the displacement values at the first crack for PN-1 and PN-2 were 2.05 and 2.03 mm, respectively. The load capacities for PN1, PN2, and PNA were 24.40, 24.50, and 24.30 kN, respectively, with the first crack occurring at 8.33, 8.34, and 8.33 kN. The initial crack originated at the loading point and subsequently propagated along the tensile plane of the plate. It is recommended to conduct research on the impact of shear connectors in the 3D modeling of flexural plates.

TrafficEZ: Optimizing Traffic Monitoring through a Novel Two-Tier Edge Computing Model Integrating Advanced Computer Vision Algorithms

2025-01-12T08:26:52+00:00

This research introduces a novel two-tier edge computing model to optimize video processing for traffic monitoring systems, focusing on balancing computational tasks between edge nodes near traffic cameras and a centralized Traffic Management Center (TMC). The system integrates advanced computer vision models, including Perspective Transformation, MOG2 Background Subtraction, Convex Hull Detection, and Morphological Noise Reduction, to significantly improve vehicle detection and traffic density estimation. The model was rigorously tested through a real-world deployment in El Salvador City, Misamis Oriental, Philippines, where it demonstrated superior performance over traditional cloud-only and edge-only solutions. Key results include the accurate approximation of traffic density and dynamic traffic signal management, visualized through various figures, such as the system’s real-time processing capabilities and the successful integration of convex hull tracking. These outcomes highlight the system's effectiveness in managing complex traffic scenarios, underscoring its potential as a robust solution for intelligent transportation systems. The research presents significant advancements in edge computing applications for smart city infrastructure, particularly in real-time traffic monitoring and management.

Describing Leaf Shape Variations of Caladium varieties using Landmark-Based Geometric Morphometrics

2025-01-12T08:26:55+00:00

The interpretation of biological diversity has been greatly enriched by applying geometric morphometrics, an analytical approach that complements traditional morphological studies by providing a quantitative framework for shape analysis. Caladium, renowned for its foliage and patterns, provides a good subject for investigation. An investigation utilizing geometric morphometrics to examine intraspecific variation within Caladium, a species that has been the subject of various experiments. The importance of the intraspecific variation within Caladium opens potential implications for its ecological interactions. The main aim of this study was to describe and quantify the variation in shape within varieties of Caladium. This can help identify and analyze patterns of shape variation. An integrative approach to identify variations of the leaves of Caladium was done using landmark geometric morphometric analysis. The study utilized 540 scanned leaf images, establishing 13 putative homologous landmark points, which were analyzed in the principal component analysis (PCA), canonical variate analysis (CVA), and discriminant analysis (DA). The methods were used to test subtle differences in the leaf shapes of Caladium varieties. Findings showed that geometric morphometrics also differentiated the species significantly based on CVA with significant p values. However, the results of DA exhibited low percentage values. This notes that despite observable differences, there are still common morphological features shared among the varieties indicating the similarities of the leaf shapes of the six identified Caladium varieties. The current findings highlight the applicability of landmark analysis as a possible complement to traditional methods of species identification.

Decryption of Attendance Monitoring of Senior High School Students at ACTEC Using Zebra Crossing Algorithm

2025-01-12T08:26:57+00:00

This study focused on developing an attendance monitoring system for senior high school students at Asian Caregiving and Technology Education Centers, Inc. (ACTEC) using the Zebra Crossing (ZXing) algorithm to enhance efficiency and data security. The application functioned as an online platform where teachers could monitor attendance through QR codes, addressing the manual method’s inefficiencies, which are time-consuming and prone to record-keeping errors. By implementing a two-layered security feature, including a verification code and location-based access, the system enhanced data protection, reducing the risk of attendance manipulation by unauthorized individuals or students attempting to falsely log attendance remotely. The results indicated that the new system improved attendance reliability and integrity by allowing only authorized, on-site students to log attendance, with immediate implications for improved record accuracy, administrative efficiency, and secure data handling. Moreover, these measures safeguarded against potential security breaches and unauthorized access, which are critical as educational institutions increasingly adopt digital systems. Thus, this study suggests that integrating multi-layered security with QR code technology could serve as a model for similar attendance monitoring systems, ultimately contributing to a more trustworthy, cost-effective, and streamlined educational management process.

Assessing Nitrate and Phosphate Contaminants in Agricultural Soils and Groundwater: Implications for MLGU Restoration and Eutrophication Management

2025-01-12T08:26:59+00:00

Effective crop production depends on a sufficient supply of nutrients through fertilizer application to achieve optimal yield. However, farmers must properly manage soil nutrients to meet the fertility needs of crops without negatively impacting the quality of precious water resources. This study evaluated nitrate and phosphate levels in water and soil in Barangays Mangayang and Gabut, Dupax del Sur, Nueva Vizcaya, to understand the impact of fertilizer and agrochemical use in agriculture. The study revealed that nitrate concentrations in irrigation water were low, with mean values of 0.20275 mg/L in Mangayang and 0.41250 mg/L in Gabut, both within the acceptable limit of 7 mg/L, and showed no significant differences (p > 0.05). Soil nitrate levels were also low, with mean values of 0.57640 mg/kg in Mangayang and 0.31300 mg/kg in Gabut, falling below the recommended range of 10-50 mg/kg. Phosphate concentrations in water exceeded acceptable limits, with mean values of 1.5830 mg/L in Mangayang and 1.5415 mg/L in Gabut. In contrast, soil phosphate levels were low, with mean values of 6.1660 mg/kg in Mangayang and 1.6000 mg/kg in Gabut, with no significant differences (p > 0.05). In conclusion, nitrate levels were within safe limits, but elevated phosphate concentrations risk water quality and ecosystems. The findings suggest that improved fertilizer management practices, including precision agriculture and reduced nutrient runoff, are essential to mitigate environmental impact and ensure sustainable agricultural practices. Regular monitoring and farmer education are crucial to balancing crop production and environmental protection.

Baseline Information of the Manobo Tribe’s Amphibious Community Infrastructures Constructed Using the Indigenous Knowledge and Practices in Agusan Marsh, Philippines

2025-01-12T08:27:01+00:00

The Agusan Marsh in the Philippines has long been home to the indigenous Manobo people, who have developed unique amphibious houses designed to adapt to the region's fluctuating water levels. Despite their cultural importance, scientific studies on these structures still need to be expanded. This paper aims to provide baseline information on the construction of these amphibious houses, emphasizing the materials, structural components, and construction practices that enable them to thrive in the marsh's challenging environment. A rapid visual survey (RVS) and key informant interviews were conducted on 35 houses, most of which were built after 2012, with some dating back to the late 1990s. The RVS identified key materials such as bundled bamboo floaters, Mambog timber for framing, and nipa leaves or galvanized iron sheets for roofing. Essential structural components were also documented, including the Batangan (girders), Sakbat (floor beams), and Gal-gal (floor joists), which are critical for the stability of these houses. The study further highlighted the strategic placement of houses near trees to enhance stability and reduce environmental risks. The findings emphasize the value of indigenous knowledge in addressing environmental challenges, mainly through material selection and design flexibility, and offer insights into constructing resilient infrastructure.

Multi-Objective Optimization of CCTV Placement: A Case Study at Bukidnon State University

2025-01-12T08:27:01+00:00

Optimizing closed-circuit television (CCTV) camera placement in open-field environments is essential to enhance surveillance coverage while minimizing costs. This study addressed this challenge using a multi-objective optimization approach, employing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to balance coverage efficiency and cost-effectiveness. The method integrated grid-based layouts with varying densities and allowable camera orientations to identify optimal camera configurations. Bullet and omnidirectional cameras, characterized by differing angles of view (AOV) and depth of field (DOF), were strategically deployed to achieve comprehensive surveillance coverage. To validate this approach, the study focused on Bukidnon State University (BukSU), where wide-open campus areas presented unique monitoring challenges. Using Google Satellite imagery, optimal camera placements were determined, and the impact of grid density and camera orientation flexibility on cost and coverage was evaluated. Results showed that dense grid patterns with finer camera orientations (e.g., 45° intervals) maintained stable costs while improving positioning flexibility and reducing the need for additional cameras. In contrast, less dense grids with limited camera orientations (e.g., 90° intervals) increased costs due to the higher number of cameras required to achieve adequate coverage. Based on simulations, this study provided valuable insights for institutions aiming to enhance security in large, open spaces. By emphasizing the importance of grid density and flexible camera orientations, it contributed to the broader field of cost-efficient, large-scale surveillance optimization and offers a practical framework for addressing similar challenges in other settings.

Biochemical Oxygen Demand (BOD5) Reduction Using Chitin Containing Microbes for River to Reef Protection

2025-01-12T08:27:06+00:00

Chitin, a widely abundant biopolymer from insects and crustaceans, along with effective microorganisms (EM), was evaluated for its potential to reduce wastewater pollutants, particularly biochemical oxygen demand (BOD5). This study attempted to address the gap in cost-effective and environmentally friendly wastewater treatment methods. The objective of this study was to assess the combined effect of chitin and EM on BOD5 reduction and other contaminants. Wastewater samples were treated with chitin and EM mixtures, and BOD5 was measured after a five-day incubation at 20 °C. Results showed a significant reduction in BOD5 from 319 to 11 mg/L, after immediate application of the chitin-containing EM in combination with aeration-supplied microdiffusers and moving bed biofilm reactor (MBBR), with an additional decrease in pollutant levels, indicating improved water quality. This approach demonstrated the potential of using chitin and EM with micro diffusers and MBBR for enhanced wastewater treatment and ecosystem protection, especially in river systems where severe pollution is indicated by BOD5 values exceeding 8 mg/L. The findings provide a foundation for sustainable bioremediation practices. Such technology could be considered sustainable and productive for the agricultural sector and the environment, in general since both chitin and EM are renewable and biologically safe and secured.

Harnessing DevOps and Microservices for Scalable Teleconsultation — A Case Study on Healthcare Information Management System (HIMS) at USTP

2025-01-12T08:27:06+00:00

The Healthcare Information Management System (HIMS) was developed and implemented at the University of Science and Technology of Southern Philippines (USTP) to enhance healthcare accessibility, operational efficiency, and scalability. Leveraging the Technology Acceptance Model (TAM), DevOps practices, and Microservices architecture, the system features real-time teleconsultation, electronic documentation, and a Personal Health Record (PHR) module. HIMS facilitated 12,164 teleconsultations during deployment, comprising 8,294 physical and 3,870 virtual appointments. It achieved widespread adoption, with 12,164 registered users (8,854 students and 3,310 employees) and significant operational improvements, including a 70% reduction in record retrieval times. Performance metrics such as 99.9% uptime and <1-second response times validated its reliability. User feedback indicated high satisfaction, with 92% finding the system user-friendly. These results demonstrate HIMS' potential as a scalable, user-centered healthcare solution for academic and public institutions. Future directions include the integration of artificial intelligence for predictive analytics and exploring nationwide implementation to support broader healthcare delivery objectives.

eMonitorMo: An Early Detection of Out-of-School Youths at Risk of Non-completion in a Non-formal Education Using Gradient Boosting Method

2025-01-12T08:27:10+00:00

Out-of-School Youth (OSY) remains one of the major issues in many countries around the world. In the Philippines, approximately 3.8 million Filipino youths lacked access to formal education. Hence, the government has been implementing non-formal education programs to provide educational and career opportunities. However, low learner success rates have been prevalent, which may put the government’s investment at risk of being wasted. Thus, the early detection of a learner's success is needed. There have been a number of studies conducted to predict students at risk of dropping, but none of them tackle out-of-school youth in non-formal education. In this study, the researchers introduced an innovative approach to mapping OSY through the development of a web and mobile-based system that includes early detection of OSYs at-risk of non-completion in ALS program using different classifiers. There were 17 potential independent variables identified in building the model, with “distance between the learning center and the learner’s home” and “corresponding travel time” emerging as the top key predictors. The researchers considered decision tree, logistic regression, kNN, SVM, random forest, and gradient boosting as the most appropriate methods to build a model given a dataset size of 3,158. Experiments reveal that among the six methods employed, gradient boosting proved to be superior having an accuracy of 94.17%, with an area under curve (AUC) of 99.40%, thereby achieving better performance of at most 4.2% higher than the other 5 methods. This study aids administrators in identifying at-risk learners and delivering targeted interventions to boost completion rates.

Project TANAW: 3D-Printed Urban Model with Geohazard Simulations Using Virtual Environment and AR Projection Mapping

2025-01-12T08:27:11+00:00

Urbanization in the Philippines poses significant challenges to disaster risk management and sustainable city planning, driven by the absence of advanced, interactive tools for geospatial analysis and infrastructure assessment. Addressing this research gap, Project TANAW employed an innovative methodology combining 3D printing, augmented reality (AR), and geospatial technologies to enhance urban planning processes. Utilizing tools like SketchUp Pro, GIS software, and AR systems, the project developed highly accurate (± 5%) 3D urban models tailored to Catbalogan City, Samar, Philippines. These models identified 15 critical infrastructure vulnerabilities and delineated 10 high-risk zones. Quantitative analysis of stakeholder engagement workshops involving over 200 participants revealed a 93% satisfaction rate with the technology’s usability and effectiveness. Results underscored the potential of TANAW to improve visualization, risk assessment, and decision-making, aligning with Sustainable Development Goal 11 by fostering sustainable and resilient urban environments. Future directions include expanding datasets, refining tools, and applying methodologies to broader urban contexts, ensuring adaptability and scalability.

Nonsequential and Sequential Dual Detection Probe Lateral Flow Immunoassay Device for Staphylococcal Enterotoxin B Detection

2025-01-12T08:27:16+00:00

Staphylococcal enterotoxins (SEs) are among the leading causes of foodborne illnesses in the Philippines. Rapid and sensitive detection of these toxins in food, particularly staphylococcal enterotoxin B (SEB) – the most potent type of SE – is imperative. Rapid toxin detection can be achieved using a lateral flow immunoassay (LFIA) device. However, low sensitivity has been a persistent issue with LFIA devices. To develop an LFIA device with improved sensitivity, this study investigated the exclusive use of antibodies as biorecognition molecules in a dual-detection probe LFIA device format and the configuration of the LFIA device to release the probes nonsequentially and sequentially. The LFIA device was fitted with two layers of glass fiber sample pads, loaded separately with the two detection probes, and partially separated by a Scotch tape film. For the nonsequential LFIA device, the two sample pads were pretreated with blocking buffers containing the same sugar concentration, whereas for the sequential LFIA device, the two sample pads were pretreated with blocking buffers containing different sugar concentrations. When tested against a filtered, homogenized durian candy sample, the nonsequential LFIA device generated higher signal intensity than the sequential LFIA device. This result suggests that aggregation of the detection probes was superior to sequential binding in enhancing the signal of the LFIA device for SEB detection. The sensitivity of the nonsequential LFIA device at 5 ng/mL was two-fold higher compared to previous POCT LFIA devices for SEB detection in food samples.

Enhancing e-Governance through Microservices – The Development and Impact of the NTC-EDGE System

2025-01-12T08:27:17+00:00

The National Telecommunications Commission (NTC) Electronic Data Governance and Evaluation System (EDGE) was developed to modernize regulatory processes by leveraging microservices architecture. Traditional manual workflows caused inefficiencies, delays, and increased transaction costs, hindering effective service delivery. NTC-EDGE integrates modular services, AES256 encryption, and biometric authentication, aligning with international best practices and Philippine e-governance policies. The project achieved a scalable and secure system designed to handle high transaction volumes and regional disparities by implementing Agile methodologies and DevOps principles. The results demonstrate significant improvements, including a 40% reduction in processing times, a 25% increase in client satisfaction, and zero data breaches post-implementation. Key features include modular components for licensing, certifications, and complaints, complemented by client-facing dashboards and mobile applications for accessibility. Comparative analysis highlights enhanced security, transparency, and efficiency across operations. Despite these advancements, challenges remain in integrating microservices into legacy systems and addressing scalability for underserved regions. Future research should focus on artificial intelligence integration, performance evaluations, and extending DevOps frameworks for public sector adoption. The NTC-EDGE system exemplifies how innovative ICT solutions can transform governance, offering a replicable model for regulatory bodies worldwide.

Bayesian Modeling of Extreme Precipitation in Mindanao, Philippines

2025-01-12T08:27:20+00:00

The Philippines is one of the countries that is prone to typhoons and heavy rainfall. Various atmospheric measures are monitored to inform its citizens regarding climate and weather events. One of these is the r-year return level. In this study, the researchers developed precipitation return level maps with uncertainty measures for selected provinces in Mindanao, Philippines. Using advanced statistical and computational techniques, results demonstrated that a Generalized Pareto Distribution-based Bayesian hierarchical model can effectively estimate r-year precipitation return levels and their associated uncertainty. The hierarchical models efficiently handled the uncertainties in the estimation and easily integrated key covariates in the modeling. It is recommended that more parameters and other covariates be considered to extend the complexity of the model.