ENCE 688R Projects, Spring Semester, 2018

[ Project 1 ]: Charts Display of EPANET Computation Results
[ Project 2 ]: User Interface for Data Input in Dynamic Taxi Sharing
[ Project 3 ]: Obstacle Avoidance Simulation
[ Project 4 ]: Visualization of flight trajectory data in NASA World Wind
[ Project 5 ]: Simplfied Modeling of a Cancer Ontology and Rules
[ Project 6 ]: Determining Best Hiking Route based on Rigor of Trails
[ Project 7 ]: Map-based Visualization of To-Do Lists.


PROJECT 1

Title: Charts Display of EPANET Computation Results
Authors: Peng, Zebo

Abstract: EPANET is a software that models drinking water distribution piping systems. It performs extended period simulation of the water movement and quality behavior within pressurized pipe networks. Pipe networks consist of pipes, nodes (junctions), pumps, valves, and storage tanks or reservoirs. EPANET tracks the flow of water in each pipe, the pressure at each node, the height of the water in each tank, the type of chemical concentration throughout the network during a simulation period, the age of the water, and source tracing.

Figure 1. Graphical display of a water distribution piping system.

In this project, we will design a graphical user interface to display several charts of the real EPANET computation results. Users can choose different items by clicking button in the interface. Compared with the data value, it can be more intuitive and clear to watch the changes of data versus time. In short, this project can be as a compensation for the EPANET to help it to display data.


References


PROJECT 2

Title: User Interface for Data Input in Dynamic Taxi Sharing
Author: Yeming Hao

Abstract: Dynamic taxi-sharing (DTS) allows two groups of taxi users to ride on the same taxi together. We have a mathematical model that takes as its input sets of taxi rider origins and destinations, and matches taxi drivers and user pairs in certain sequences with a goal of maximizing taxi providers net revenue. The user interface provides an interface for taxi riders to input their origin, destination, and desired time window for the taxi trips. The interface will store all the input data in the desired format in a table to be further used as the input for the mathematical matching model.

Figure 2. Ride matching and fare calculation system structure.

We already have the taxi matching and fare calculation methods ready. That part takes origin and destinations (in latitude and longitude) and time preference as input. The part in the blue circle in Figure 2 shows what we want the interface to do in this project. e.g. users can enter street number as the origin/destination addresses and the interface will show it on the map and transform it into latitude and longitude and store in a table for further calculations.

Google maps or OpenStreet map will be used for the map part.

Javafx will be used for the desktop application.


References


PROJECT 3

Title: Obstacle Avoidance Simulation
Authors: Hao Wang

Abstract: Obstacles avoidance problems are the common and typical ones for creating self-driving cars in the future. Many problems like control, planning, and learning will be used to realize autonomous navigation.

In this project, we will use deep reinforcement learning (Q-learning) techniques to achieve our goal of avoiding obstacles while driving in a given environment. The simulation will be visualized on the Pygame Python packages for video games. The simulation and test process is illustrated in Figure 3.

Figure 3. Simulation and test for obstacle avoidance.

Simulation will be created to build a model that can be applied into the agent of interest. The agent is supposed to drive and automatically avoid the static and moving obstacles in the end.


References


PROJECT 4

Title: Visualization of flight trajectory data in NASA World Wind
Author: Santiago Sanz

Abstract: This project will consist of using Nasa World Wind in addition to public FAA data to create a simulation of flights across the US National Airspace. See Figure 4.

Figure 4. Sample visualization of FAA data in NASA World Wind.

To accomplish this task, the first step will be to plot the ARTCC boundaries on the map, and then add layers for real-time weather conditions. We will attempt to visualize data associated with special use airspaces (SUAs). Lastly, either actual historic flight data, or flight trajectories will be added. When combined with actual historic flight data and SUA's, this should show how flights attempt to avoid SUA's and areas of bad weather.


References


PROJECT 5

Title: Simplfied Modeling of a Cancer Ontology and Rules
Author: Joel Abraham

Abstract: Being able to create faithful models that successfully translate clinical trials to patient diagnosis, especially for cancer therapies, has proven to be challenging. With abundant patient and clinical data available, a systems-based platform can be developed to accumulate knowledge, construct and select models that recapitulate a patient's disease. In this project, a very simple model of a patient clinical trial sample and cancer sub-type (namely glioma) will be created.

Figure 5. Semantic graph of cancer (glioma) ontology and patient sample.

The ontologies will be created using the Apache Jena framework and simple reasoning will be done using Jena Rules. A secondary goal of the project is to create XML data files and become familiar with JAXB to marshall and unmarshall java objects to xml files and vice versa.


References


PROJECT 6

Title: Determining Best Hiking Route based on Rigor of Trails
Author: Priyanka Jayanti

Abstract: Hiking has always been a favorite pass-time of outdoorsy and non-outdoorsy people alike. Being able to take in those breathtaking scenes when you get to the end of the hike or even along the path cannot be traded for anything. Most national parks in the United States provide very detailed maps of the paths available to hikers online or in the pamphlets you find at their visitors centers so that hikers are informed of the trails available to them. Although the maps are useful, they are generally missing one key piece of information: how steep can these trails get and how would someone pick the best path for themselves based on the ups and downs of the various paths? This missing piece of information is important to many people because people with disabilities, elderly people, and people hiking with small children, among others, need to know whether they will be capable of hiking the path they have chosen.

Figure 6. Example of Highlighted Best Path Suggestion.
(Source: https://www.nps.gov/hafe/planyourvisit/maps.htm)

The goal of this project is to utilize Java to create a tool that generates a suggested best path for a given user based on the varying rigor due to rise and fall of the hiking trails in Harpers Ferry State Park. The tool would take in a hiker's preferred level of trail intensity and then generate an image in which the ideal trail is highlighted.


References


PROJECT 7

Title: Map-based Visualization of To-Do Lists.
Author: Shao-Hung Lee

Abstract: Nowadays, people always have lots of things to do, and there are also lots of kinds of to-do list application. I want to integrate the map interface with the user's specific event into a application. This application can store the data recording the events. In addition it can show the marker on the map indicating where the events are going to be held. By designing the user-friendly interface, users can easily sort up their to-do lists with the map. I will build the GUI system and create/parse the XML files to store datas instead of using database to simplify the data management.

Figure 7. Map-based visualization of to-do lists.

Main Objectives:


References


Developed in April 2018 by Mark Austin
Copyright © 2018, Department of Civil and Environmental Engineering, University of Maryland