This paper used the methods interpolation, extrapolation and regression for prediction of road traffic volume. The application aims to identify the status of traffic flow of vehicles and predict accurate road traffic volume using the 2012-2020 traffic data (AADT) by MMDA. The application gained an accuracy of 84.96% on the average in 2019 and 2020 traffic volume prediction using 2012-2018 traffic data.
Math-alino is a mobile-based math practice application targeted toward lower elementary students (specifically for grades 1 to 3). With the use of gamified lessons and assessments, it enables users to improve their mathematical abilities. The evaluation score for this app has an increase of 0.11 points from before the use of the application to during its use.
The PRacticum Activity eXpedition and Integration Software (PRAXIS) is a unified dashboard web-application that functions as a platform for conducting different tasks related to the CMSC 198 internship program. It includes support for task management, timekeeping, and messaging functionalities accessible to student interns, company representatives, and practicum advisers. Developed using the MERN stack (MongoDB, Express, React, and Node), the system received a mean S.U.S. score of 86 from twelve evaluators–evenly represented by University faculty members and students. Emphasis on UI/UX improvements is highly recommended for further system development.
The convenience and accessibility of digital storefronts has increased the usage of digital music. However, the quality of digital music can not always be verified by checking encoding and bit rate in the metadata. Bad quality transcodes harm artists who produce high quality music and consumers who download an imperfect product. This study examines the use of spectrogram analysis to classify audio files using a convolutional neural network (CNN). Audio samples were randomly selected from online sources and converted into spectrogram images. These were used to train and evaluate the accuracy of the CNN. Evaluation revealed that the model scored 98.39% in overall accuracy. The model scored the lowest in precision for FLAC and V0 files which means that their spectrograms can be tricky to distinguish. Additionally, a desktop application was developed as an interface for inference. Results suggest that classifying audio files is effective through the use of spectrograms and a CNN.
The Villa Remedios East Homeowners Association (VREHOA) is a private organization with the aim of improving the residents’ quality of life through proper management anduse of organization funds. Not having a single platform for their management needs, record-keeping is done manually through the use of tools such as a spreadsheet. Task assignments are also done via messages through social media, SMS, or verbally. This study aims to provide a Management Reporting System to the VREHOA which will serve as a platform to record their income, expenses, resident complaints, and officer task assignments. Having a single platform for their management needs, the Management Reporting System aims to aid the VREHOA by providing relevant information to be used for decision making.
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