SUSCEPTIBLE-INFECTED-REMOVED MODEL OF AIDS INCIDENCE IN THE PHILIPPINES

Acquired Immunodeficiency Syndrome (AIDS) being one of the top 10 most communicable diseases, according to the Alameda County Public Health Department. It is caused by the Human Immunodeficiency Virus (HIV). This virus is also known to have no ways to be removed inside the infected human body yet. The spread of this disease in the Philippines was studied using the Susceptible-Infected-Removed Model which is a modification of the usual Susceptible-Infected-Recovered Model for no data show a person recover from AIDS. In this model, the populations of the Philippines from 1984 to 2010 were gathered. Two methods were used to derive the model, first by curve fitting and the other by computing the infection rate and the removal rate. The number of infected by AIDS and death toll for 2011 to 2016 were predicted using the obtained functions and rates

PORK QUALITY ASSESSMENT THROUGH IMAGE SEGMENTATION AND SUPPORT VECTOR MACHINE IMPLEMENTATION

Pork is the most consumed meat in the Philippines, and efficient quality control is essential for ensuring the safety of its consumers. Current manual procedures of meat inspection are time-consuming and laboratory-intensive considering the large amount of supply to be examined. This research aims to construct a rapid objective system of pork quality assessment with respect to meat freshness through Support Vector Machine (SVM) implementation, and to ultimately have an accuracy rate of ≥ 90%. 35 meat samples were collected, and their images were acquired. 30 of these were randomly designated as part of the training dataset while the rest were designated as part of the testing dataset. Of the 30 training samples, 6 were randomly chosen for the creation of a microbial profile. In all of the acquired image samples, image segmentation was performed and the RGB, HSV, Lab, and statistical texture features were extracted. These were inputted in 15 different SVM configurations. SVM classification yielded an accuracy rate of 93.33 %. Results from the microbial profile revealed considerable microbial activity at the 5th and 6th intervals (10th and 12th hour) with 2 and 3 colonies formed, respectively. With the ability of the SVM to distinguish between samples with respect to the hour interval and with the supplementation of the microbial profile, an objective artificial intelligence mechanism for freshness detection was successfully created.Keywords: Meat quality, Image segmentation, Support vector machine, Artificial intelligenc

MODELLING THE SPREAD OF PNEUMONIA IN THE PHILIPPINES USING SUSCEPTIBLE-INFECTED-RECOVERED (SIR) MODEL WITH DEMOGRAPHIC CHANGES

Epidemic modeling is an important tool used by mathematicians in analyzing the rate of spread of an epidemic by taking in account of the parameters and vectors that facilitate the transmission rate of the disease. The measurement of the average transmission rate through mathematical analysis helps in finding the proper approach of disease control methods in mitigating the spread of diseases. The study aims to analyze and predict the rate of transmission of the global epidemic pneumonia in the Philippines population through epidemic modeling. The study methodology used the standard epidemic model known as the SIR model to quantify real-world data on pneumonia cases into a set of differential equations while taking in consideration of changes in the population experienced due to demographic change. The study yielded results that suggested positive correlation in real-world data and the modeled data points mostly for SIR models that assumed linear change in the infection rate and recovery rate. In addition, the implementation of population models showed increases in the infection rate and the recovery rate due to increasing trend observed in the given population. The study evaluated linear rate SIR assuming exponential population growth as the most applicable epidemic model from the selection in modeling real-world epidemic data. In addition, the study compared the effectiveness of using quarantine method and vaccination method in mitigating the spread of pneumonia

MODELLING THE SPREAD OF DENGUE IN A HUMAN POPULATION IN NATIONAL CAPITAL REGION (NCR), PHILIPPINES USING THE SIR (SUSCEPTIBLE-INFECTED-RECOVERED), SEIR (SUSCEPTIBLE-EXPOSED-INFECTED-RECOVERED), AND SIR WITH VERTICAL TRANSMISSION MODELS

The unimpeded growth of urban population has unfortunately paved way to spreading multiple infectious diseases that greatly puts a population the risk of incurring an outbreak had the spread of disease not been managed well. Dengue is a major contagious disease that has been plaguing the world ever since, and epidemic outbreaks trying to be mitigated and minimized by researchers. One way to predict the pattern of the disease on a macro scale is to use mathematical models to understand the dynamics of the epidemics caused by the disease. This study uses the SIR, SEIR, and SIR with Vertical Transmission to model the spread of dengue in NCR, Philippines within the year 2010. Afterwards, each model was then used to simulate two disease control methods: Constant Vaccination Strategy (CVS) and Quarantine, which controls the infection and recovery rate parameters with SIR with linear parameters having the highest accuracy among all the models the R2 value being 0.99683. The created models are accurate hence can be used to simulate dengue dynamics in NCR. CVS and Quarantine substantially decreased the peak of the epidemic for all models, confirming those methods as effective deterrents dengue incidenc