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Elyssia Barrie H. Ong

Publications and source records attributed to Elyssia Barrie H. Ong.

2 recordsLinked to original sources

AniFrame: A Programming Language for 2D Drawing and Frame-Based Animation

Creative coding is an experimentation-heavy activity that requires translating high-level visual ideas into code. However, most languages and libraries for creative coding may not be adequately intuitive for beginners. In this paper, we present AniFrame, a domain-specific language for drawing and animation. Designed for novice programmers, it (i) features animation-specific data types, operations, and built-in functions to simplify the creation and animation of composite objects, (ii) allows for fine-grained control over animation sequences through explicit specification of the target object and the start and end frames, (iii) reduces the learning curve through a Python-like syntax, type inferencing, and a minimal set of control structures and keywords that map closely to their semantic intent, and (iv) promotes computational expressivity through support for common mathematical operations, built-in trigonometric functions, and user-defined recursion. Our usability test demonstrates AniFrame's potential to enhance readability and writability for multiple creative coding use cases. AniFrame is open-source, and its implementation and reference are available at https://github.com/memgonzales/aniframe-language.

cs.PL↗

From Unstructured to Structured: Transforming Chatbot Dialogues into Data Mart Schema for Visualization

Schools are among the primary avenues for public healthcare interventions. With resource limitations posing challenges to the routine conduct of health and wellness checks in Philippine public schools, the deployment of a chatbot-assisted health monitoring system may provide an alternative method. However, deriving insights from raw conversations is not straightforward due to the expressiveness of natural language that causes variances in the input. In this paper, we present a process for transforming unstructured dialogues into a structured schema. The process comprises four stages: (i) processing the dialogues through entity extraction and data aggregation, (ii) storing them as NoSQL documents on the cloud, (iii) transforming them into a star schema for online analytical processing and building an extract-transform-load workflow, and (iv) creating a web-based dashboard for visualizing summarized data and reports. Performance evaluation of this dashboard showed that increasing the number of stored dialogues by a factor of 100,000 increased the loading time for the display of roll-up, drill-down, and filter results by around only one second.

cs.DB↗