https://research.lorma.edu/xmlui/handle/123456789/371 Fri, 24 Jul 2026 22:35:27 GMT 2026-07-24T22:35:27Z https://research.lorma.edu/xmlui/handle/123456789/373 Catsonic: Cat Sound Classification Using Machine Learning Algorithms Sarah D. Oghenekaro Catsonic is a unique project aimed at helping cat owners and veterinarians understand the sounds that cats make. Cats communicate through various sounds, and deciphering these can be challenging. In collaboration with cat owners and veterinarians, the researchers gathered a diverse set of cat sounds both online and from local communities in City of San Fernando, La Union. Cat sounds dataset forms the basis for training our machine learning model. The researchers approach involves using advanced technology called Convolutional Neural Networks (CNN) to classify and recognize different cat sounds. The researchers rigorously tested and evaluated the model to ensure accuracy and effectiveness in identifying various sounds, considering factors like sensitivity and specificity. The result of the researchers’ efforts is a user friendly mobile application. Catsonic provides a tool for cat owners and veterinarians to interpret and understand cat sounds better. The researchers also assessed the application's ease of use through the System Usability Scale (SUS), the developed application was evaluated in terms of its usability and found to be acceptable with a percentage of 80.13%. Catsonic is not just an innovative solution; Catsonic serves as a bridge for improved communication between humans and their feline friends. This project showcases the power of technology, specifically machine learning, in addressing real challenges faced by pet owners and veterinarians. This capstone project highlights the transformative power of technology, specifically machine learning, in addressing tangible challenges faced by pet owners and veterinarians. Catsonic stands as a testament to the potential of leveraging advanced technologies for the betterment of the human-animal bond, showcasing how innovation can enhance understanding and connection with beloved pets. Mon, 08 Jul 2024 00:00:00 GMT https://research.lorma.edu/xmlui/handle/123456789/373 2024-07-08T00:00:00Z https://research.lorma.edu/xmlui/handle/123456789/372 A Smooth Fluidity of Life: The Hypertension Intervention in the Rural Health Unit in Tubao, La Union as the Foundation for the Stability of the Community Geo Louise C. Madriaga; Ailah Rajabelle G. Alviar; Vince Gabriel C. Fernandez; Paris Izabel H. Gaerlan; Jonnabie B. Julaton; Lionel Alfred Karl I. Montilla Hypertension is a pervasive and life-threatening global health crisis that demands urgent attention. This study explores the challenges faced by medical professionals in monitoring hypertension, their coping strategies, interventions used, and level of involvement in patient care. Utilizing a descriptive mixed-method design, the study selected ten participants through purposive sampling, gathering data through semi-structured interviews and survey questionnaires. Thematization was employed to analyze the data, yielding three major themes and three to four sub-themes each, providing deep insights into the experiences of medical professionals at Tubao Rural Health Unit. Additionally, descriptive analysis using means determined the level of involvement among medical professionals in monitoring hypertension. Challenges identified included miscommunications due to lack of health education on hypertension, patient disinterest in blood pressure monitoring, limited access to remote areas, and cultural and belief differences. Despite these obstacles, medical professionals adapted and developed effective coping strategies such as collaboration with peers, taking the initiative to monitor patients who do not visit the RHU, and embracing induced relaxation. They implemented interventions like frequent blood pressure monitoring, strategic approaches to hypertensive patients, and health education campaigns to raise awareness. The study observed a significant degree of participation among medical professionals in hypertension monitoring, with an overall mean of 4.42, highlighting their level of involvement as “Very Involved.” The research emphasizes the critical need for substantial support from government and local government units to empower medical professionals to manage hypertension effectively within rural communities and ensure better health outcomes for the population. Mon, 08 Jul 2024 00:00:00 GMT https://research.lorma.edu/xmlui/handle/123456789/372 2024-07-08T00:00:00Z