[NB: This list is only partial, and is currently being updated.]
- Traffic Simulation in Traffic Intersection Using Improved Krauss and Improved Mobil Algorithm Implemented in Python (Maria April Rose Andaca, Jerwin Lloyd Cruda and Adrian Roy Valdez, Ph.D., 2016)
A traffic computer simulator is created to minimize on-road testing and speed up gathering of information for various traffic proposals. Current traffic models for car following and lane changing were improved to take into account Filipino traffic behaviors. A new model, which uses time as basis of comparison, were also created to handle motions on traffic intersections. These were all implemented in Python 2.7. A crude test was done which showed that the models follow a no-collision assertion.
- An Agent-Based Model of Post-Disaster Regrowth of Mangrove Forests (Franklin David Ang, J Stephen Mariano and Vena Pearl Bongolan, Ph.D., 2016)
This study aims to accurately model the recovery of mangrove populations after being damaged by storms. It adapts Salmo and Juanico's agent-based model for mangrove forest growth to a virtual reconstruction of the Bangrin Marine Protected Area in Pangasinan, Philippines. The virtual environment incorporates two models of Heibeler: Fragmented Habitat to simulate variable inhabitability per unit area, and Block Disturbance to simulate the occurence of storms. The model features planted (Rhizophora mucronata) and native (Avicennia and Sonneratia spp.) mangrove species, which have di.erent levels of sensitivity and adaptation to environmental factors.
- Optimal Water Allocation Policy for the Greater Manila Area Under Different Water Supply Regimes (Nicle Vynique Bedia, Mara Shen and Adrian Roy Valdez, Ph.D., 2016)
This study aims to know when will the demand overtake the supply using Euler approximation method. The resulting projection can identify how much water will be needed in the future and when should a new source for water supply be developed. Furthermore, a water allocation policy under El Niño phenomenon was developed which will satisfy the demand and maintain an above critical water level of the Angat dam. With the help of this study, water security and security from droughts can be provided for the people of the Greater Manila Area.
- Off-lattice Protein Structure Prediction on 3D Hydrophobic-Polar Side-Chain Model using Parallel Simulated Annealing (Gerald Roy Campañano, Francis Jonathan Lopez, Rowel Ventura and Adrian Roy Valdez, Ph.D., 2016)
This study presents an off-lattice implementation of the HPSC model in 3D space is presented and a metaheuristic method called simulated annealing is used to find a good conformation of a given protein. The total energy values and the number of hydrogen bonds formed will be compared to previous researches. Lastly, parallel computing will be applied to the method for improved identification of final conformations.
- Storm Surge Simulation in the Philippine Archipelago Using 3D ADCIRC + SWAN (Gwenevere Kay Gutierrez, Ace Irish Talibong and Vena Pearl Bongolan, Ph.D., 2016)
This study aims to develop an efficient model that produces real-time storm surge simulations with coastal inundation along the Philippine archipelago using the Advanced Circulation (ADCIRC) model coupled with Simulating WAves Nearshore (SWAN) model.
- 3D Printing Optimization Through Projection-Assisted Parameter Search (PAPS) (Niña Kamille Quiazon, Sarah Samonte and Vena Pearl Bongolan, Ph.D., 2016)
This study aims to find the best orientation (x-y-z axis parameters) of an STL model that gives the least 3D printing time and least use of filament materials through the rotation of the model in 3D space in order to minimize cost.
- Modeling the Protein Folding Process through Protein Backbone Folding (Karen Katrina Manalastas-Cantos, B.Sc. and Vena Pearl Bongolan, Ph.D., 2015)
This work tries to predict the final three-dimensional structure of a peptide backbone using a heuristic approach. Note that the backbone conformation almost determines the 3D structure of a protein fold.
- A Hybrid Method for Detecting Protein Complexes in Weighted Protein-Protein Interaction Networks (Jerome Cary Beltran, Catalina Montes, John Justine Villar, M.Sc., Jaymar Soriano, M.Sc. and Adrian Roy Valdez, Ph.D., 2015)
Second Prize, 2015 UP College of Engineering Undergraduate Project Competition
This research aims to incorporate biological information to purely graph-based clustering methods to more precisely predict relevant protein complexes from protein-protein interaction networks (PPIN). The resulting algorithm will be compared to existing PPIN frameworks, in terms of the number of complexes correctly predicted from gold standard datasets, and other performance metrics.
- Storm Surge Modeling in the Philippine Setting using ADCIRC+SWAN through Parallel Computing (Tricia Mae Esguerra, Ryan Anthony Jacinto, Joshua Frankie Rayo, Dustin Edric Ricio, Pablo Manalastas and Vena Pearl Bongolan, Ph.D., 2015)
Semifinalist, 2015 College of Engineering Undergraduate Project Competition
This study aims to understand the dynamics of storm surges using two computational models, ADCIRC and SWAN, and tailor it in the Philippine setting, as well as to design it to compute fast enough to be able to give real-time storm surge predictions around the country.
- On Protein Structure Prediction using the Hydrophobic-Polar Model on a Tetrahedral Lattice (Ryan Paul Gozum, Kristoffer Marion Mendoza, John Justine Villar, M.Sc., Jaymar Soriano, M.Sc. and Adrian Roy Valdez, Ph.D., 2015)
This work tries to understand the process of protein folding by using points on a regular 3D lattice through an energy minimization algorithm, as well as to predict the final structure of the protein given an amino acid sequence and through the proposed lattice model. One aspect is to characterize the properties of the proposed lattices and provide the bounds for the minimal energy of the resulting protein conformations.
- Scenario and Sensitivity Analysis for Flooding Vulnerability using Genetic Algorithms (Edward Nataniel Apostol, Joshua Kevin Cruz and Vena Pearl Bongolan, Ph.D., 2015)
This study models the flooding vulnerability of the Urdaneta City, Pangasinan through a risk assessment framework, and simulations are done using a genetic algorithm.
- Analysis of Signalized Traffic Intersections with Varied Traffic Conditions (Mark Paolo Navata, Joshua Martin Villano, Jaymar Soriano, M.Sc. and Adrian Roy Valdez, Ph.D., 2015)
This study tries to find an optimal way of improving traffic light or intersection systems through modeling actual and possible scenarios with main focus on signalized intersections with changes to variables such as traffic light durations, volume flow, exit rate, and road lengths.
- Optimizing Urban Growth for Flood Disaster Prevention using Genetic Algorithms in a Risk Assessment Framework (Charlie Aquino, Joyce Banting, Aina Olaes and Vena Pearl Bongolan)
This study tries to design a flood-resistant city by minimizing the vulnerability function arising from a flood risk assessment framework. They are investigating genetic algorithms and simulated annealing as optimization tools. They hope to aid in the planning of areas ear-marked for development.
- Simulating the Spatio-Temporal Spread of Diseases (Tel Sabate and Vena Pearl Bongolan)
This study continues our work on epidemiology, by solving epidemic models on a random graph structure, overlaid on a GIS representation of a specific area in Metro-Manila. She wants to provide a modeling tool to aid our disease prevention efforts.
- Rain-Induced Landslide Simulations (Jam Sapuay, Patrick Galanida and Vena Pearl Bongolan)
This work aims to model and simulate different types of rain-induced sliding events. It is their hope that, eventually, we can accurately predict rain-induced sliding, and be able to warn and evacuate affected areas in time.
This research tries to understand the red tide phenomenon by modeling the population dynamics of a phytoplankton named Pyrodinium Bahamense which takes into account the different life cycles of the said organism. Modeling is done in two ways: one via the construction of a system of ODEs to capture the population dynamics, and; two, thru agent-based modeling.
- Controllability of de St. Venant Equations
The de St. Venant equations are used to model behavior of shallow waters. Work is currently being undertaken to prove the existence of controllable boundaries that steer one unsteady flow to another. Existence is also verified using numerical simulations.
- Pricing a Bermudan Swaption
This work implements a hybrid pricing algorithm for Bermudan Swaptions combining different paradigms from a "Hull"-based algorithm and a "Brigo"-based one in a setting where time-domain decomposition is non-uniform.
- Optimal portfolio and utility-indifference pricing and hedging in a regime-switching model
This research extends the work of Becherer where indifference pricing and hedging was done not only to exponential utilities, but also to logarithmic and hyperbolic absolute risk aversion (HARA) types. Moreover, optimal portfolios were constructed using these three different utility function types.