• The project involved creating a conceptual Entity-Relationship (ER) diagram for a new dental practice, using Crow's Foot Notation to indicate cardinality.
• The ER diagram was created using a diagramming tool
• The ER diagram was created to capture the business operation from a database perspective, including entities such as staff, patients, insurance providers, and procedures.

draw.io, Lucidchart

• The project involved adding data to tables based on a previous database design, and writing SQL queries to run on those tables using Oracle Live SQL.
• The project includes four queries:
• Query 1: Given a time range, calculate the average cost and time of a procedure.
• Query 2: Given a date, calculate the income from all procedures performed on that day.
• Query 3: Create a new table to store employee skills and write a query to select employees who can perform all tasks in a given list.
• Query 4: Create a new query that the owners might find useful, using all the data in the database, and explain how it works.
• The project did not require installing any software or submitting code directly. Instead, links to the work on Oracle Live SQL are submitted.

Oracle Live SQL

• In this project, I worked with spatial data by collecting and creating their my data, visualizing it, and performing queries on it.

• Created longitude and latitude pairs for 12 locations on the UCLA campus, as well as home coordinates, and categorized them into 4 categories: department buildings, waterworks, coffee places, and blue light emergency phones.

• Cretaed a KML file using a text editor and use Google Earth to visualize the data.

• Installed Postgres+PostGIS and executed two spatial queries: computing the convex hull for the 13 points and finding the four nearest neighbors of the home/apt/dorm room location.

• Used OpenLayers and HTML5 localStorage to store and visualize the location data in a web browser.

• Used one of UCLA's locations as the center, to compute a set of lat-long coordinates that lie along a Spirograph curve, create a new KML file, converting it to an ESRI shapefile, and visualized the data using ArcGIS Online.

Text editor (for creating KML file) Google Earth (for visualizing KML data) Postgres+PostGIS (for executing spatial queries) OpenLayers and HTML5 localStorage (for storing and visualizing location data in a web browser) ArcGIS Online (for visualizing ESRI shapefile data)

• In this project, I worked with NoSQL and JSON data using MongoDB Atlas, a cloud-based installation of MongoDB.
• Created a database, added collections of documents to it, and performed queries.
• Sign up for MongoDB Atlas and set up a cluster
• Created a database called HW4DB
• Created a collection called HW3Data and insert your locations data from HW3 into it
• Wrote a query to output locations with a popularity of >=50
• Modified Spirograph code from Project 3 to output data in a specific format and create a collection called Spiro
• Created a collection called NPS and add data from the National Park Service to it
• Visualized the data using charts and performed spatial querying

MongoDB Atlas JSON data GeoJSON queries

The project compared the search results from Google and Bing for 100 pre-determined queries, determined the overlap with the search results, and calculated correlation using Spearman's rank coefficient (Spearman's rho).

• Java
• Jsoup
• Gson
• Apache Commons CSV
• Apache Commons Math

The project leveraged crawler4j library to crawl a news site and gather/measure various aspects of the crawl, study crawl characteristics and gather webpage metadata.

• Java
• Crawl4j
• Jsoup
• Open CV
• Sleepycat Berkeley DB

Created a program that index words from multiple text files in k-v format. Processed the files to remove the tab characters. Used MapReduce to count words in the files. The output is the inverted index with unigrams and bigrams.

• Java
• Hadoop MapReduce
• HashMap data structure
• Apache Hadoop for handling distributed storage and processing
• Classes provided by Hadoop for specifying the input and output formats for MapReduce jobs
• Hadoop-specific data types for representing textual and integer data in MapReduce jobs

• Used Weaviate (via Docker) and vectorizer transformer
• Loaded data in json format that would be searched

• Builder.io GPT-crawler
• npm

• small (3.56G) model
• Llama
• external knowledge source (.txt file) vectorized using Chroma
• .gguf format
• Streamlit

The project consists of two parts, each focusing on different aspects of sampling and aliasing. The overall project covers resampling, filtering, spatial and temporal aliasing, and the impact of various parameters on the output.

• Develop a program that processes images.
• The program displays two images side by side: original image displayed on the left: A 512x512 image with a radial pattern of black lines on a white background. Processed output image displayed on the right: The output of the algorithm applied to the original image, creating a resampled image based on the indicated parameters.

• Develop a program that processes videos.
• Display two videos side by side: original video displayed on the left: A 512x512 video with a radial pattern of black lines, rotating clockwise at a specified speed. Processed output video displayed on the right: A temporally sampled version of the original video, updated at specific times.
• The project includes analysis questions related to experiments with different values of s and fps and a formula for relating them.

The project implement image compression using Vector Quantization (VQ). It uses 2-pixel vectors and a specified number of vectors. The steps involve initializing codewords, clustering vectors around codewords, refining and updating codewords iteratively, and quantizing input vectors to produce an output image. The project also covers the following areas:

Color theory using a Rubik's cube under different colored lights.

Mapping of a printer's gamut to that of a color CRT monitor. Effectiveness of the algorithm, its performance on different types of images, and suggest improvements.

Entropy functions and probabilities for symbols.

Huffman codes for text and telegram versions of a letter, compare code lengths, and find which version contains more information.

The project's purpose is to provide an in-depth understanding of multimedia technology. The project involves extracting structure from media elements (video/audio) and building an interactive media player for exploring the media content. The project represents a solution that automatically creates a logical index or table of contents from a video with audio input.

• The project creates a solution that automatically builds a logical index or table of contents from a video with audio input.
• The index is hierarchical .
• The project relies on both visual and auditory information in the input video file.

• Once the index is extracted, the project builds an interactive media player that allows users to explore the media content.
• The media player enables users to jump to any index and browse the video/audio interactively.
• The audio and video components are synchronized.
• Basic player controls (play, pause, stop) are provided.

• The project includes a simple, functional interface that displays the extracted table of contents alongside the video.
• The table of contents is hierarchical and allows selection of different segments (scenes, shots).
• The interface supports play, pause, and stop buttons.