All of the articles in this proceedings volume have been presented at the Workshop on Computation: Theory and Practice (WCTP2024) during November 4th -6th in Henry Sy Hall, the University of the Philippines Manila, Philippines. These articles have been peer reviewed by the members of the Program Committee...

Computational systems that deal with discrete time, such as stream computations and synchronous data flow languages, can be modeled using lists. However, most list operations are on finite lists, and it is not easy to define them for infinite lists to express persistent behavior. In particular, when...

A function closure is a construct that encapsulates the body of a function, along with the bindings of free variables to their corresponding values in the scope of the function. Environment extraction refers to the process of retrieving these bindings from a function closure. A lambda calculus with environment...

The Game of Life gained widespread interest due to its properties and its implications on fields such as biology, mathematics, and computer science. Hyperbolic geometry, on the other hand, is a type of geometry in which tilings are less restrictive than its Euclidean counterpart. Using the hyperbolic...

This study delves into the impact of serious games on individuals’ awareness on data privacy seriousness. The game incorporates thriller themes, a pixel art-style, and a point-and-click approach that enhances its immersive experience. With the game at hand, the research examines the relationship between...

Deceptive designs, also known as dark patterns, are user interface tricks websites and applications use to manipulate user behaviour and collect data without informed consent. These patterns include misleading language, asymmetrical options, and hidden information. Websites commonly manifest these deceptive...

Folk Dance showcases both the performative and cultural dimensions of dance. Although its instruction has been integrated into the Philippine education system, the declining interest and exposure, compounded by the challenges of instruction and lack of surrounding research, prompts the need for alternate...

Forecasts of electricity are crucial for providers and beneficial for consumers, aiding in the planning and management of electric use and grid operations. Time series forecasting has been a vital tool in this field, with various methods and architectures emerging over the decades. With the availability...

This study evaluates the application of Gradient Boosted Decision Tree (GBDT) models—LightGBM and CatBoost—in behavior-based malware detection, addressing challenges such as limited publicly available datasets and inconsistent evaluation metrics. The research involved comprehensive dataset analysis,...

We numerically compute tables of zeroes and weights of Legendre polynomials Pn(x) correct to thirty-two decimal places for n = 2, 3, 4, …, 10, 12, 16, 20, 24, 32, 40, 48, 64, 80, and 96. These zeroes and weights are useful in Gaussian quadrature of arbitrary continuous functions over finite intervals....

As the transistor count in modern central processing units (CPUs) reaches the physical limits of Moore’s Law, the parallelization of software-based compute has become the next step in maximizing the instruction-level and thread-level parallelism of modern multi-core architectures (e.g., advanced superscalar...

Machine learning (ML) techniques are increasingly being used in viral strain classification. Along with this increase use, it becomes more practical to outsource these machine learning computations to the cloud. However, there are privacy issues that surround the outsourcing of viral genomic data. Hence,...

The underlying biology of mental health disorders, such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ), remains an enigma for healthcare professionals and biomedical researchers. This study investigates the genes associated with these disorders, focusing on the dorsolateral...

This study explored hierarchical community detection in gene co-expression networks to enhance the functional classification of cellcycle regulated genes in Saccharomyces cerevisiae. We evaluated three hierarchical community detection algorithms—Girvan-Newman (GN), Paris, and Local Optimization Function...

Network science offers a powerful way of exploring and discovering on knowledge and insights. Making use of graphs as mathematical structures, it is able to model pair-wise relations between objects, thus, providing in-depth understanding of relationships of entities within and among networks and structures...

Even before the COVID-19 pandemic, many Emergency Departments (ED) were already dealing with overcrowding issues. This study investigates how machine learning (ML) can help ED triage patients and predict the length of their stay (LOS). Using the MIMIC-IVED dataset, this study’s findings include that...

Kidney Renal Clear Cell Carcinoma (KIRC) is one of the most common cancers in the world. With limited ideal testing and screening methods, this disease has been prone to misclassification and poor prognosis leading to late-stage detection and metastasis. One of the few methods that have been developed...

Predicting the survival outcomes of pediatric hematologic transplant patients remains to be a formidable task for clinicians. This study aims to assess the capability to predict survival post bone marrow transplantation of machine learning classifiers namely: random forest, decision trees, logistic regression,...

Social support refers to resources that are made available through social ties. Persons with diabetes often seek social support on social media. The Endocrine Witch Facebook page posts about diabetes mellitus and is moderated by an endocrinologist. This study introduces novel machine learning models...

Classification of white blood cells (WBCs) is a crucial process in medical diagnosis and research. Automated image classification of white blood cells using machine learning techniques provides faster and more accurate results compared to manual procedures. Convolutional Neural Networks (CNNs) are deep...

The incidence cases of gastrointestinal diseases continue to rise in developing countries such as the Philippines. Some of these diseases such as colorectal cancer, ulcerative colitis, and colon polyps are a common sight during colonoscopy, a procedure used to detect abnormalities in the colon. Clinicians...