FEU Institute of Technology

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Year 2022 96 Publications

Discover all research papers published in 2022
Disaster and Crime Reporting and Monitoring System for Hagonoy Bulacan with Decision Support Mechanism

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-6

Conference Paper | Published: January 1, 2022

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Abstract
Disaster strikes in unexpected times. The first few hours after are critical to the survival of the victims directly hit by the event. This paper explores the utilization of the Monitoring and Reporting System with Decision Support Mechanism using web and mobile applications. The citizen of Hagonoy can use the mobile application to report a crime or a disaster, they can also access the official website to view important announcements regarding safety protocols or events. The Department of Police, Fire and MDRRMO of Hagonoy will take full responsibility for managing the emergency reports and updating the website’s content. From the experiment, the mobile application was able to show that the system can provide a feasible emergency and incident report that will help both the citizen and LGU of Hagonoy. The researcher used the prototyping model as a software development model. Overall, the system was evaluated 4.86 with an interpretation result of Very Acceptable. This means that the system is ready for deployment.
Kaiser and Cumulative Proportion Principal Component Analysis for Temperature Compensation of Vibration in Reinforced Concrete Bridge

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-6

Ronnie Concepcion, Febus Reidj G. Cruz, ... Pocholo James  M. Loresco Pocholo James M. Loresco

Conference Paper | Published: January 1, 2022

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Abstract
Structural health monitoring (SHM) was developed to provide diagnosis of the state of civil structures, such as bridge and building, throughout their lifespan. The superstructure degrades over time mainly because of the continuous effect of environmental factors including temperature, wind, humidity, and traffic loading. Consequently, this study is concerned in reducing the masking effect of environmental factors, specifically on temperature. Principal component analysis (PCA), a supervised machine learning algorithm, was employed as the embedded statistical treatment for multidimensional reduction of feature matrix data to eliminate the temperature effect. Kaiser’s criterion eliminated data variance of almost 20% that may result to poor data reconstruction. Cumulative proportion (CP) criterion eliminated data variance around 4%, which is a better choice for deciding the number of principal components to eliminate. Thus, the proposed experimental study addressed successful temperature compensation from reinforced concrete bridge vibration data by using PCA and CP criterion.
Sustainable Drainage System: Low Impact Development Practices to Minimize the Storm Water Runoff

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5

Jenny B. Calot, James Bryan R. Galang, ... Lady Lyn E. Escarieses

Conference Paper | Published: January 1, 2022

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Abstract
Low Impact Development (LID) is a green infrastructure approach to ease the surface runoff that arises due to climate change and from an increasing impervious surface area caused by urbanization. This study aims to determine which LID control is best suited for Barangay San Rafael, San Jose Del Monte, Bulacan. Using Storm Water Management Model (SWMM), a hydraulic model of the area was created to apply the LIDs and simulate a runoff. The data used in SWMM for the runoff simulation is the monthly rainfall values for year 2020. Based on the simulation using SWMM, the existing drainage system has a high total flood volume with total flood volume of 243.511 liters. Based on the data collected from SWMM, the most effective combination with total flood volume of 50.884 liters was the combination of all the LID practices. The study has used three (3) different LID practices and the combinations of the LID practices to obtain the ideal LID combination namely, Bioretention Cell, Bioswale, Bioswale and Permeable Pavement. In the final analysis, the combination of Permeable Pavement, Bioretention Cell, and Bioswale is the best combination out of the three LID controls mentioned. Bioretention Cells are primarily used in parking lot islands, traffic islands, and driveway runoff. The same is true for Permeable Pavement, which is used mainly on roadways and parking lot islands. Considering the total flood volume that the SWMM calculated, the combination of the three LID parameters alone has the lowest total flood volume.
Fabrication of a Hydroelectric Generator with a Dual-Axis Fluid Flow Turbine Blade Design

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5

John P. Henry Ricamara, Carl Wilfred D. Cabalce, ... Ritchard Q. Dizon

Conference Paper | Published: January 1, 2022

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Abstract
In the Philippines, it rains half if not most of the year. In an era where electricity is vital in all aspects of everyday life, there is a need to conserve and find alternative sources of energy. A better way to do it is by harnessing an abundant resource like rain. This project aimed to design and fabricate a hydroelectric generator that can be utilized even in situations where there is very little rainfall. The hydroelectric generator created was an innovative design that uses a dual-axis or bidirectional turbine design. Reservoirs, spillways, and gear ratios were used to optimize the input of rainwater into the generator. The designers showcased the functionality of their hydroelectric generator with hopes of raising awareness regarding energy-saving or energy-producing ideas and alternatives.
Mini Hydropower Potential for Low Energy Areas in Quezon Province

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5

Ivan Karl B. Camacho Ivan Karl B. Camacho , Johanna Tonia S. Javier, ... Melvin B. Solomon

Conference Paper | Published: January 1, 2022

Apollo: Dissecting the Human Body Through the Use of Interactive Animation

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-7

Conference Paper | Published: January 1, 2022

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Abstract
Apollo is an interactive animation that aims to provide both Junior High School teachers and students, additional materials for teaching and learning. It consists of three modules that present anatomical topics covered in the current K to 12 Curriculum Guide for Science (2016); Digestive, Respiratory, and Endocrine Systems of the Human Body. The modules contain interactive 3D animation videos that feature narrated lessons to guide student's learning and pop questions to further student's understanding. Several software programs used to produce Apollo includes Autodesk Maya, Adobe After Effects, Adobe Premiere, and Adobe Photoshop. In addition, the website which Apollo can be accessed through was developed using HTML and Adobe Dreamweaver.
BOOKEXPRESS: A Web and Mobile Based UV Express Reservation and Booking System with Data Analytics

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5

Francel Duke P. Anglo, Marc Kevin F. Santos, ... Jay-ar P. Lalata Jay-ar P. Lalata

Conference Paper | Published: January 1, 2022

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Abstract
UV Express is one of the most used modes of public transportation in the Philippines. However, the inconvenience in commuting, such as long queues of passengers at UV Express terminals and extended waiting time for UV Express drivers and passengers, is still present. The Book-Express aims to help UV Express, which operates on a terminal-to-terminal basis, by providing a reservation and booking system through a website and mobile application. The system’s primary functionalities were validated through user acceptance testing using the metrics of functionality, usability, reliability, performance, and supportability. Consequently, the system garnered an overall score for the mobile application of 4.60, which is "Excellent", and an overall score for the website of 4.53, which is "Excellent," as well.
Backpropagation Artificial Neural Network Model for Predicting the Mechanical Properties of Bagasse Ash Blended Concrete

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5

Conference Paper | Published: January 1, 2022

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Abstract
Technology in construction has been attempting to discover eco-friendly materials, to identify waste products that can be processed as an alternative supplement to cement. The study utilizes sugar cane bagasse ash (SCBA) to produce a bagasse ash blended concrete. There were 15 previous experimental studies that were gathered and analyzed which have the same variables in terms of determining the mechanical proeprties of the blended concrete with SCBA. The variables that were considered are: compressive strength, cement content (CC), fine aggregate (FA) and coarse aggregate (CA) content, water-cement ratio (W/C), water content (WC), and sugarcane bagasse ash content. 74 different data sets in all were obtained. The study's goal is to develop a prediction model for estimating the mechanical properties of concrete made with SCBA. The work employed MATLAB R2021a neural network (NN) toolbox for model development and simulation of the dataset with the use of the backpropagation ANN. The best model was observed to have a structure of 7-7-1 (input-hidden-output) having the highest R all value and lowest AIC value, with a mean absolute percentage error (MAPE) is 3.718% considered to be a highly accurate model. The relative importance (RI) showed that the FA, CA, and CC were the most significant factors to the CS while water and SCBA were the least influential parameters. The overall findings reveal that the MAPE of the compression strength prediction model decreased from 3.718% to 3.519% exhibiting a 5.35% improvement in the model’s performance.
CHARLIE: A Digital Awareness Campaign with Reporting System on Online Sexual Harassment for UNFPA Philippines

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5

Matthew Carl M. Bolatete, Kyel Pacifico T. Rojo, ... Ace C. Lagman Ace C. Lagman

Conference Paper | Published: January 1, 2022

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Abstract
Online sexual harassment has been an ongoing problem in this technological era. Gender-based violence has transformed online, making it more difficult for users to act on, as resources and knowledge about the issue are limited. Therefore, the study aims to contribute to introducing a safe space for the victims and an informational aid for potential perpetrators using animation series. They are composed of hybrid animations, a digital campaign through social media sites, and a website–that will serve as a medium for victims/potential victims to agencies that will help them assess their situations and publish multimedia materials. In order to assess the effectiveness of the materials produced for the target audience, which was the youth population, a pretest and posttest evaluation was conducted. The results showed that prior of the evaluation the youth were aware of online sexual harassment, but after assessing our digital campaign and its components they were now fully aware of the issue. This concludes that educating people using modern solutions of disseminating information through our digital campaign was effective. The key solution corresponds to the research main goals which are: A hybrid animation series, digital campaign, and the website, which to educate and raise awareness to online sexual harassment.
Corrosion Prediction Model of Steel in Filler Typed Self-Compacting Concrete Subjected to Carbonation Using Artificial Neural Network

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-6

Kevin J. Tanguin, Joanna Marie P. Maming, ... Villamor  D. Abad, Jr. Villamor D. Abad, Jr.

Conference Paper | Published: January 1, 2022

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Abstract
Carbonation is a dangerous threat to concrete since it reduces the alkalinity of normal or self-compacting concrete (SCC), allowing iron to corrode and spall the cover. The goal of this research is to use an artificial neural network to create a corrosion prediction model for steel in self-compacting concrete that has been subjected to carbonation. In this study, MATLABR2019a was used to create a feedforward back propagation neural network. As a training function, the researchers utilized the Levenberg-Marquardt back propagation (TRAINLM) which adjusts weights and bias values using Levenberg-Marquardt optimization. The researchers used gradient descent with momentum weight/bias learning (LEARNGDM) for the adaptation learning function, which is a technique that aids the gradient in determining which way to go. The network’s performance was measured using the mean square error (MSE). The Hyperbolic tangent sigmoid transfer function (TANSIG) was also employed as the transfer function since the values obtained by this function range from +1 to -1, considering both the positive and negative aspects of the parameter. To minimize overfitting, the number of hidden nodes should be fewer than the number of input parameters. The researchers tested 4-12 hidden nodes. Modeling was done using data from 102 experimental studies of self-compacting concrete exposed to corrosion. Using feed-forward back propagation ANN with 1 hidden layer and 8 hidden nodes, a Pearson R-value of 0.98748 and a mean square error of 0.5725 were obtained. The factor that most affect the carbonation depth were water-cement ratio and fly ash content. The suggested model was able to analytically describe the connection and behaviors of the various mixtures to the carbonation depth in the parametric investigation. The parameters characteristics were likewise described by the model.

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