Scopus ID: 105030537698
2025 23rd International Conference on ICT and Knowledge Engineering (ICT&KE), (2025), pp. 1-6
Conference Paper | Published: December 9, 2025
Abstract
Despite the potential for e-commerce to boost productivity and market access for farmers, adoption remains low, particularly in rural areas of developing countries. This study addresses the research gap by predicting farmers' adoption of digital platforms in the National Capital Region, Philippines, using the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM). Based on a survey of 615 farmers and analysis with various machine learning models, with XGBoost as the top performer, the study found that perceived usefulness, trust, and price value are the most significant factors influencing adoption. Social influence and ease of use also play important roles. The findings provide guidance for policymakers and platform developers, highlighting the need to improve digital literacy, build trust, and ensure affordability to accelerate the digital transformation of the agricultural sector.
Scopus ID: 105031358679
2025 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), (2025), pp. 227-232
Conference Paper | Published: December 5, 2025
Abstract
The integration of artificial intelligence (AI) into computational materials science (CMS) has introduced powerful approaches for accelerating the discovery and optimization of advanced energy materials. As energy demands shift toward renewable systems, the development of efficient materials for batteries, fuel cells, and electrocatalysts becomes increasingly critical. This paper systematically reviews recent AI methodologies applied within CMS, particularly those leveraging density functional theory (DFT), molecular dynamics (MD), and kinetic Monte Carlo (KMC) simulations. Emphasis is placed on the use of machine learning (ML) models, including supervised learning, deep learning, and hybrid strategies for property prediction, structure optimization, and inverse design. The review categorizes current applications across key energy technologies and discusses how AI is reshaping material screening and development pipelines. It concludes with an outlook on future directions, highlighting the need for standardized datasets, interpretable models, and physics-informed frameworks to improve predictive accuracy and facilitate AI adoption in practical materials research.
Scopus ID: 105031391365
2025 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), (2025), pp. 221-226
Conference Paper | Published: December 5, 2025
Abstract
Artificial Intelligence (AI) is transforming the prediction and optimization of advanced energy materials by enabling accurate, scalable modeling beyond traditional methods. This review evaluates recent AI applications—including Graph Neural Networks (GNNs), Convolutional and Recurrent Neural Networks (CNNs, RNNs), tree-based ensembles, and Gaussian Process Regression (GPR)—for forecasting performance metrics such as overpotential, conductivity, capacity, and degradation. GNNs achieved R2 > 0.90 in structure-sensitive tasks; LSTM models predicted battery degradation with <10% error; and tree-based models balanced accuracy (MAE < 0.15 V) with interpretability. GPR excelled in low-data regimes via uncertainty quantification. Hybrid and physics-informed models improved generalizability and data efficiency. While challenges remain in data quality and integration with experiments, emerging strategies like autonomous labs and generative design offer promising advances. This review provides comparative benchmarks and highlights pathways for robust AI-driven materials discovery.
Scopus ID: 105031368506
2025 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), (2025), pp. 368-373
Conference Paper | Published: December 5, 2025
Abstract
High voltage engineering has evolved rapidly, driven by the growing need for efficient energy transmission and the integration of renewable energy into modern power grids, including urban areas. Innovations such as HVDC systems are central to this transformation, ensuring that grids can handle the increasing complexity and demand for sustainable energy. However, challenges remain, especially when it comes to coordinating insulation in hybrid AC/DC systems and maintaining the resilience of the overall infrastructure. This review looks at how Artificial Intelligence (AI) can help tackle these challenges, focusing on its role in fault detection, predictive maintenance, and improving system reliability. By comparing traditional methods with AI-driven solutions, we highlight how AI can enhance the scalability, efficiency, and adaptability of power systems. With AI, utilities can predict and prevent faults, optimize grid performance, and seamlessly integrate renewable energy sources into both rural and urban environments. Our goal is to provide insights for researchers, industry professionals, and policymakers on how AI can be harnessed to build more sustainable, resilient, and reliable energy systems. The insights shared here aim to help shape the future of power grids, positioning AI as a key player in the transition to cleaner, more efficient energy solutions.
Scopus ID: 105030135995
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2025), pp. 1-4
Florante D. Poso &
Jaychris Georgette Y. Onia
Jaychris Georgette Y. Onia
Conference Paper | Published: December 3, 2025
Abstract
In the Philippines, a country characterized by mountainous landscapes and frequent intense weather events such as typhoons and monsoons, the issue of slope failures has become increasingly pressing. This study investigated the impact of soil cohesion on slope stability using numerical modeling. The SLOPE/W software and Morgenstern-Price method were employed to simulate various slope scenarios with varying cohesion values. Results indicated a strong positive correlation between cohesion and factor of safety (FOS), highlighting the critical role of cohesion in slope stability. Analysis of Variance confirmed the statistical significance of cohesion variations on Factor of Safety. The findings underscore the importance of incorporating cohesion in geotechnical design and slope management, especially in regions like the Philippines with diverse topography. Future research should explore the combined effects of other soil properties and validate numerical results through field testing. By considering cohesion, engineers can optimize slope safety and minimize the risks of slope failures.
Scopus ID: 105030160994
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2025), pp. 1-5
Conference Paper | Published: December 3, 2025
Abstract
Research on affinity spaces in the Philippines is lacking, namely the subjects-the online communities of vtubers, furries, and fanfiction. As such, the research objective includes to gain a better understanding of these affinity spaces, and implement them to the research's audience through informative explainer videos coupled with a narrative. There is also a digital campaign, and an animated music-video to act as a climax to the aforementioned narrative. The research is conducted in the perceived context of having these affinity spaces largely related to the nature of the multimedia space and contemporary world in general, as well as being related to the study of online community behaviors. Once project context and related literature are gathered, the output commences in production, then a formative evaluation is conducted, followed by a summative evaluation after sampling project demonstrations. The methodology used for the data gathering employs a mixed method approach, with a qualitative approach used mainly for interviews with experts on the fields, and quantitative on surveying the respondents about the project. Purposive nonprobability sampling will be used when dealing with quantitative data, purposive sampling for gathering substantial amounts of information from point persons, and Slovin's formula for unbiased samples respectively. The population sample will be gathered from third year students currently enrolled in the Multimedia Arts from FEU Institute of Technology, while clustering ages 16-25 in gen z. A majority of the data gathered from the evaluations yields satisfactory categories in surveys from summative testing, compared to a lower score on formative, which entails a success when deducing how audiences would learn more about these affinity spaces. Thus far, the research adds available academic information regarding these topics in the Philippine context, to which any interested party may source from.
Scopus ID: 105030147183
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2025), pp. 1-5
Conference Paper | Published: December 3, 2025
Abstract
The widespread use of Liquefied Petroleum Gas (LPG) in households and industries presents a significant risk due to its highly flammable nature, making early detection of leaks for preventing accidents. Traditional LPG detection methods often rely on manual monitoring, which may not provide timely alerts or automatic responses to prevent accidents. The Internet of Things (IoT) refers to a network of physical objects, or “things,” embedded with sensors, software, and other technologies that enable them to connect and exchange data with other devices and systems over the internet. The advantage of the Internet of Things (IoT) offers new opportunities to safety systems through real-time monitoring and remote alerts. By integrating IoT technology with LPG leak detection, it is possible to create a responsive and reliable safety system. This device focuses on the development of an IoT-based LPG tank leakage detection system with alarm and auto-off system, designed to detect leaks, sound an alarm, and automatically shut off the gas supply or even remotely turn off the valve through an android-based application to prevent accidents. The system uses IoT for real-time data transmission and remote monitoring, allowing users to receive instant notifications and take immediate action, even when away from the premises. The system uses gas sensors to continuously monitor LPG levels, triggering an immediate response in the event of a leak. Integrated with IoT technology, the system provides real-time alerts to users via android-based application, ensuring prompt action.
Scopus ID: 105030148685
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2025), pp. 1-6
Conference Paper | Published: December 3, 2025
Abstract
Bulacan has a rich history with significant events in the Philippines, but there's more to it than just that. Bulacan has its own unique culture, arts, and plenty of interesting tourist spots. This study explores how digital campaigns and institutional branding can be utilized to promote and help connect the youth with the history, arts, culture, and tourism of Bulacan and familiarize them with the Provincial History, Arts, Culture, and Tourism Office (PHACTO) with its programs and initiatives. It emphasizes how understanding cultural heritage is important for young people to express themselves and connect more with their roots, helping to increase the cultural heritage tourism in Bulacan. The digital campaign consists of an online series, titled, “Ika nga sa Bulacan!”, a 10-episode that will run 3-5 minutes each and also publication materials that incorporate holidays or events, trivia, tourist destination and message posting. The proponents will perform via a mock-up Facebook page by posting the online series and publication materials such as graphics and short-form videos. Along with this output is the institutional branding that consists of a campaign logo and audio-visual presentation (AVP). These multimedia outputs are supplementary materials that highlight Bulacan's cultural heritage tourism. To evaluate the effectiveness of the materials, the researchers will gather data from ages 15-30 from the target audience, subject matter expert and technical expert people, regardless of their gender, marital status, and race. The audience will evaluate the study through various processes such as Formative Evaluation and Summative Evaluation.
Scopus ID: 105030149865
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2025), pp. 1-5
Conference Paper | Published: December 3, 2025
Abstract
Social class inequality is the stratification of classes based on wealth, income, influence, and access to resources. Individuals who are categorized as low class face unequal access to basic needs, inaccessible health services, deterioration of mental health, entry into the poverty cycle, and crime. As suggested by the relative references, the factors of social class in the Philippines are underemployment, unemployment, and income inequality. In alignment with the Sustainable Development Goal (SDG) 10 entitled Reduced Inequalities, the proponents' objective is to raise awareness towards social class inequalities in the Philippines by creating a 3D first-person action investigation game entitled Overdrive to showcase a premise based on the experiences of the lower class and its possible solutions. The development used the SCRUM development cycle methodology. The game is accompanied by a Content Management System-based website to promote the game materials. To gather the data, the proponents conducted beta testing among IT students of the FEU Institute of Technology, and a few external technical and non-technical individuals. The testing was followed by a Likert scale questionnaire which gathered the satisfaction level of the game and assets, integration of the study within the story, and the website. A weighted average mean was utilized to evaluate the data. The overall data resulted in a mean of 4.35 which interprets a ‘Satisfied’ rating towards the created game and conducted project.
Scopus ID: 105030178217
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2025), pp. 1-6
Conference Paper | Published: December 3, 2025
Abstract
The use of Cocos nucifera (coconut shell) ash as a supplementary cementitious material has shown potential in enhancing the compressive strength of concrete. However, the optimal calcination temperature and duration for producing effective ash remain uncertain. This study employs a Central Composite Design (CCD) to investigate the effect of calcination on concrete strength. Nine combinations of temperatures 550°. to 800°C) and durations (1 to 3 hours) were tested, producing 13 samples, which were cured for 28 days before compressive strength testing. X-ray Fluorescence (XRF) analysis identified 15 elements, with iron significantly influencing strength. The highest compressive strength (24.9 MPa) was achieved at 675°C for 2 hours, where iron content reached 16.63 %. A full quadratic regression model was developed, with an R2 of 79.47 %, and backward elimination refined the model to a predicted R2 of 67.32 %. Sensitivity analysis revealed temperature as the most significant factor, with a sensitivity value of 14.53 compared to 1.48 for duration. Optimization indicated the ideal calcination temperature to be 672.81° C. This study supports sustainable development goals by advancing innovative materials for infrastructure and by promoting the use of agricultural waste, reducing the environmental footprint of concrete production.