Dataparallel C has been designed for various kinds of architectures and was developed jointly at University of New Hampshire and Oregon State University.
This project dealt with porting the libraries to the nCUBE 2 system and helping a user compile his programs on nCUBE 2 directly from a Sun workstation...
CREEDA-BG (Crop Rotation Economic and Environmental Decision-Aid Budget Generator) is a web-based enterprise budgeting tool that allows a user to manage information on her fields, rotations, crops, and operations, and to view estimates of income and expenses. The user can then use this information to evaluate alternative plans and make...
In this paper we describe a fuzzy logic based control system implemented on a PC architecture. The rule based inference engine of this expert system is easily configured through an ascii text file and is demonstrated to be capable of controlling various simulations, including an inverted pendulum. The controller is...
Component based software technologies are viewed as essential for creating the software systems of the future. However the use of externally provided components has serious drawbacks for a wide range of software engineering activities often because of a lack of information about the components. One such drawback involves validation of...
We present a model for a distributed virtual market place that can be constructed on the Internet to support selling and buying requests, such as those found as classified advertisements. One requirement for a transaction to take place in the virtual market place is that a sell request and a...
We have developed SearchPak, a machine independent parallel searching tool on shared and distributed memory machines. It can be used for combinatorial optimization problems and OR-parallel computations as well. Both depth-first and best-first search of the state space can be performed using the SearchPak. With SearchPak, a user just provides...
Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
Papers proposing novel machine learning algorithms tend to present the algorithm or technique in question in the best possible light. The standard practice is generally for authors to emphasize their proposed algorithms' performance in the precise setting where it is maximally impressive, often by only fully evaluating their best known...
We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...