Seminars and Trainings

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ISO 9001:2015 Retooling
Awarded by FEU Tech Quality Assurance Office on October 03, 2024
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Data Privacy Act Awareness Seminar
Awarded by FEU Tech Human Resources Office on August 07, 2024
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Tech-Enabled Pedagogies: Empowering Modern Teachers with Educational Technologies
Awarded by Educational Innovation and Technology Hub on August 09, 2023
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Conference Paper · 10.1063/5.0162444
Artificial Neural Network Modeling of Shear Strength of Concrete Beams with Fiber Reinforced Polymer BarsAIP Conference Proceedings, (2023), Vol. 2868, pp. 020005
Fiber-reinforced polymer (FRP) is an innovative material in the construction industry. It is beneficial because of its toughness, and unlike steel, it is not prone to corrosion. Some research studies focus its behavior as a reinforcement in concrete while deriving several equations pertaining to its shear strength capacity. This study used the artificial neural network modeling technique to derive a more accurate solution to predict concrete shear capacity with FRP as reinforcement. Experimental data from previous studies were collected and used to train the model. The parameters considered were compressive strength of concrete, FRP ratio, beam dimensions, and modulus of elasticity. As a result, the model consistently provides a better prediction of the shear capacity of concrete against existing models like ACI 440.1R-03, ACI 440.1R-06, and El-Sayed. Furthermore, the ANN model showed no sign of disarray in predicting every parameter compared to other existing models. According to ACI 440.1R-06, FRP bars largely affect the total shear capacity of concrete. In the model provided by ACI, FRP reinforcement’s axial stiffness accounts linearly to the shear strength capacity of concrete. Since then, the predicted capacity in accordance with the ACI was excessively conservative. With respect to the derived model, axial stiffness offered a variation in the shear capacity. The proposed ANN model can be utilized for the design since the minimum ratio between the actual test result yields to 0.77 which is greater than the strength reduction factor of 0.75. Parametric studies were also conducted to show the effect of the modulus of elasticity of FRP, FRP ratio, and beam dimensions on the shear capacity.

Conference Paper · 10.1109/HNICEM57413.2022.10109617
Modular Construction for Fast-Paced Residential Housing in the Philippines2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-7
As the Philippine Government continues to encourage the use of modular construction for its fast completion rate, still, the said innovative method is not well-known and practiced in the Philippines. The aim of this study is to analyze the modular construction system as a feasible solution for the Philippine's housing crisis and construction delays, as well as for its wide applicability in the Philippines for residential housing projects by the means of comparing its project duration to the conventional way. This seeks to identify if there are significant differences between the two construction methods. The Jamovi Software was used to execute the one-tailed independent samples t-testing. A survey was also done to compare and validate the results of the statistical analysis. Based on the findings, modular construction was found substantially faster, but in some instances, the difference between the overall project duration of conventional and modular construction does not vary significantly. Based on the survey result, 77.67% of the respondents agreed that modular construction is faster in terms of project duration. Although the numerical results revealed that the differences are not considered as statistically significant, still, modular construction takes the upper hand by looking at the average construction time, in which the survey respondents also believed. With that, the potential of modular construction can still be recognized as a feasible solution to the construction delays and the Philippines' housing crisis.