The Neighborhood Median Pixel Method (NMPM) classifies land cover by summing per-band scores across 10 input features from Landsat-8 Operational Land Imager (OLI) data – bands 1 through 7 alongside three widely used index images: NDVI, NDWI, and NDBI. These features are typically treated equally within the classification framework, assuming uniform informational value across all bands and indices. However, indices such as NDVI, NDWI, and NDBI are specifically designed to highlight spatial properties of their respective land cover classes—particularly in urban settings—and are therefore expected to carry more relevant information for specific classification tasks. In this study, we experimented with different weighting schemes and found that giving greater emphasis to the indices led to a modest increase in overall classification accuracy, achieving an average overall accuracy of 0.9475 compared to 0.94 of the original implementations for the equal-weight baseline and other weighting strategies with a 9x9 neighborhood size. The results demonstrate how a targeted methodological innovation in image processing—assigning greater weight to highly relevant features—can enhance the reliable and efficient classification performance of the NMPM. This contributes to more accurate land cover mapping, particularly in complex urban environments, and supports data-driven development planning and resource management.

Fiber-reinforced rigid pavement offers a viable option for sustainable concrete development due to its superior mechanical properties, notably enhanced durability and crack resistance. Nonetheless, cracks remain inevitable. Recent studies have concentrated on harnessing biological mechanisms to introduce self-healing properties to concrete. A particularly promising method employs microorganisms like Bacillus subtilis, which can induce the precipitation of calcium carbonate (CaCO3) when exposed to moisture and air. This microbial-induced calcite precipitation (MICP) efficiently seals cracks, thereby reducing need for manual repairs and extensive maintenance. This study examined the application of 2.36 × 109 CFU of Bacillus Subtilis ATCC 6633 as a bio-admixture in fiber-reinforced concrete pavement. The study assessed the effectiveness of various concentrations. The research concluded that Bacillus subtilis effectively stimulated self-healing of cracks in concrete width of 1–2 mm and material recovery over the seven (7) day period, as verified by Absorption Test (Sorptivity), Ultrasonic Pulse Velocity (UPV), and X-ray Diffraction Analysis (XRD). However, the efficacy of the self-healing process varied based on the concentration of Bacillus subtilis. Higher concentrations (10%) of Bacillus subtilis improve fracture healing but diminished overall material performance. Furthermore, the direct application of 5% Bacillus subtilis proved to be a highly effective variant among the tested formulations, exhibiting an enhancement of flexural strength by 13.13% at 14 days, surpassing the design specifications.

The Neighborhood Median Pixel Method has previously been introduced as an image processing technique in remote sensing, developed to classify Landsat-8 OLI satellite image pixels into categories of vegetation, water, and built-up areas. This method relies on a lookup table based on the median pixel values within a pixel’s neighborhood and a scoring system that assigns point values for classification. While a 9x9 neighborhood size was originally proposed, a succeeding study suggested a 13x13 neighborhood for better classification accuracy. This study focuses on refining the scoring system used in the Neighborhood Median Pixel Method, particularly the original set of arbitrary point values 14, 4, and 1. Particle Swarm Optimization was employed to systematically explore and optimize these point values, iteratively seeking an ideal configuration for the scoring system. After optimization, the Neighborhood Median Pixel Method exhibited a slight increase in overall accuracy. Using the 9x9 neighborhood size, the accuracy rose from 94% to 94.75%, while with the 13x13 neighborhood size, the accuracy improved from 95.75% to 96%. Furthermore, results indicate that varying point value configurations yield similar classification outcomes, suggesting that the method’s scoring system is robust across multiple configurations and that the originally proposed point value set remains adequate for effective classification.

Artificial intelligence (AI) is revolutionizing digital marketing by enhancing targeting, personalization, and automation, leading to data-driven advertising strategies. AI-powered analytics optimize customer engagement, enabling businesses to deliver highly tailored ads that improve conversion rates and return on investment. Automated tools streamline content creation and campaign management, while chatbots enhance customer interactions on a scale. In the Philippines, AI adoption in marketing is expanding, with local retailers and online platforms leveraging AI for personalized recommendations and programmatic advertising. However, challenges remain, including data privacy concerns, algorithmic bias, and a widening skills gap, as AI proficiency becomes increasingly essential for marketers. While AI offers efficiency, a word cloud analysis highlights concerns about its impact on creativity and the human touch in branding. According to the Technology Acceptance Model, Filipino marketers and multimedia arts students must develop AI literacy and strategic thinking to remain competitive. Ethical considerations also require greater oversight in AI-powered advertising to ensure responsible consumer engagement. The future of digital marketing in the Philippines depends on balancing AI-driven efficiency with human creativity, storytelling, and cultural relevance. Businesses must invest in upskilling initiatives and ethical frameworks to maximize AI’s potential while mitigating risks. Further research should examine AI’s long-term impact on job roles, industry dynamics, and consumer trust. As AI becomes more integrated into marketing strategies, success will hinge on how well professionals merge automation with authentic, human-centric advertising practices.

The Philippines, known for its extraordinary biodiversity, holds a unique and ecologically vital position in the world of conservation. Despite the exceptional richness of its biodiversity, the gravity of the threats it faces has been notable for the lack of attention given to endangered animals in the Philippines. With that, this study aims to create an innovative learning material to inform children through a 360 interactive video about the lives of critically endangered species in the Philippines. To validate the study, mixed method technique was used to collect data and information. The researchers interviewed subject matter experts, technical experts, and 8 to 10- year-old target audiences. It revealed that innovative learning material like a 360 interactive video is an effective way to engage and help inform children in the Philippines about critically endangered species. This research offers valuable insights into the effectiveness of 360 interactive video promoting the advocacy supporting the SDG’s Quality Education, Life on Land, and Life on Water for the children of Manila City, contributing to broader societal goals of understanding.

In today’s society, technology has become an integral part of daily life. At home, families now have access to the Internet and electronic devices. Although digitalization offers numerous advantages, it also poses problems for young children who can be constantly exposed to online content, which can negatively affect their holistic development. Parents and guardians who are accustomed to traditional parenting can also experience challenges in handling technology at home. The study aims to educate and guide parents and guardians on how to manage their children’s digital activities effectively. Through a hybrid web series and a social media campaign, they can be encouraged to foster a conducive digital environment to better support their children’s early development. Children can also help them build a positive relationship with their children at home. Formative and summative evaluation were conducted to gather information on academic professionals and industry experts. Also included is a test screening to understand the impact of the project on the target audience. With a grand mean of 4.47, the study was able to increase the learning outcomes of the parents and guardians. This can contribute to the existing body of knowledge on digital parenting, child development, and digital media.

Generative AI tools are increasingly transforming multimedia arts courses by streamlining creative processes and expanding the possibilities for artistic expression. The integration of these tools into creative platforms has enabled students to enhance their productivity and experiment with innovative techniques, fostering an environment where digital artistry can thrive. Despite these benefits, the use of AI raises significant concerns regarding originality, artistic authenticity, and the potential erosion of traditional skills. Analysis using the technology acceptance model (TAM) reveals that students broadly accept these tools due to their perceived utility and ease of use, yet they remain cautious about their long-term impact on creative development. A word cloud analysis of student feedback illustrates a diverse array of sentiments, combining enthusiasm for the technological advancements with caution and ethical deliberation about the role of AI in art. Sentiment analysis further indicates an overall optimistic view toward the integration of generative AI, while also uncovering persistent concerns about ethical issues, such as copyright and the fair attribution of creative work. These findings highlight the critical need for educational strategies that balance the benefits of AI-driven efficiency and innovation with the preservation of traditional artistic practices. Future research should explore methods to integrate AI into multimedia arts curricula in a way that augments human creativity and safeguards the unique qualities of handcrafted art, ensuring that technological progress enhances rather than compromises artistic integrity.

Artificial intelligence is rapidly reshaping multimedia arts courses by enhancing creative workflows and expanding artistic possibilities. Its integration into creative platforms has allowed students to improve efficiency and explore new techniques, fostering a dynamic digital art environment. However, concerns persist regarding originality, artistic authenticity, and the potential decline of traditional skills. Using the Expectation Confirmation Model, this study examines students’ perceptions of AI in multimedia arts. While students acknowledge its convenience and practical benefits, they remain cautious about its long-term impact on artistic development. An N-gram analysis of student feedback reveals a spectrum of opinions ranging from enthusiasm for technological advancements to ethical concerns about copyright, fair attribution, and the future of handcrafted art. Notably, despite recognizing AI’s advantages, students express reservations about its role in shaping creative expression. These findings highlight the need for educational frameworks that balance AI-driven innovation with the preservation of traditional artistic techniques. Future research should explore on how Philippine institutions can integrate AI with traditional arts while educating students on ethics and industry practices to ensure responsible and competitive creative careers.

This research addresses the challenges faced by community welfare services in the Philippines, particularly within the context of healthcare delivery. With the rapid advancement of information technologies, there is a critical need to enhance the efficiency and efficacy of medical information management. The study highlights the issues of delayed access to accurate health information due to disparate systems and poor data quality, which hinder timely medical assistance. It proposes developing a comprehensive e-health solution designed to automate and digitize healthcare records management within barangays—the grassroots level of governance in Philippine society. In terms of the medical resources, allocation, the researcher used Exponential smoothing for forecasting resources ahead of time, reducing the risk of shortages or overstocking. The researcher used Technology Acceptance Model Software Quality Model to assess the system overall capability as perceived by experts and end users. In terms of ISO instrument, all criteria are rated very acceptable in which it emphasizes the system’s overall effectiveness and user-centered design, contributing to a favorable perception of its performance. In terms of the Technology Acceptance Model evaluation, the total mean of 4.03 demonstrates a strong consensus among respondents, highlighting their positive outlook on the system’s usefulness, ease of use, and overall attitude toward its implementation in academic environments.

Artificial Intelligence (AI) is reshaping higher education by streamlining tasks, supporting personalized learning, and enhancing student engagement. Yet, these benefits coexist with risks of dependence, reduced critical thinking, and inequities-a duality termed the relief paradox. This study examined the perceptions of 138 IT students at FEU Institute of Technology to explore how they experience both the relief and paradoxical burdens of AI in education, with attention to Sustainable Development Goal 4 (SDG 4) on inclusive and equitable quality education. Using a descriptiveanalytic design, validated survey instruments, and both descriptive and inferential statistics, results showed that students generally recognized AI's potential to reduce workload and improve inclusivity, while also expressing concern over ethical issues and overdependence. The study underscores the need for balanced integration of AI in education, offering recommendations for curriculum, policy, and capacity-building to ensure responsible adoption.