This paper presents a deep neural network-based online trajectory generation method for the aerodynamic characteristic description and terminal-area energy management of wave-rider aircrafts. First, flight dynamics equations in domain are linearized discretized to generate numerous aircraft samples with sequential convex optimization (SCO) methods. Then, an objective function is designed promot...

In this paper, we present Kathaa1, an open source web based Visual Programming Framework for NLP applications. It supports design, execution and analysis of complex NLP systems by choosing and visually connecting NLP modules from an already available and easily extensible Module library. It models NLP systems as a Directed Acyclic Graph of optionally parallalized information flow, and lets the ...

In this paper we outline the nature of Neuro-linguistic Programming and explore its potential for learning and teaching. The paper draws on current research by Mathison (2003) to illustrate the role of language and internal imagery in teacherlearner interactions, and the way language influences beliefs about learning. Neuro-linguistic Programming (NLP) developed in the USA in the 1970's. It has...

We describe our first attempts to re-engineer the curriculum of our introductory NLP course by using two important building blocks: (1) Access to an easy-to-learn programming language and framework to build hands-on programming assignments with real-world data and corpora and, (2) Incorporation of interesting ideas from recent NLP research publications into assignment and examination problems. ...

We present a novel way for designing complex joint inference and learning models using Saul (Kordjamshidi et al., 2015), a recently-introduced declarative learning-based programming language (DeLBP). We enrich Saul with components that are necessary for a broad range of learning based Natural Language Processing tasks at various levels of granularity. We illustrate these advances using three di...

In this work, disjunctive-genetic programming (D-GP), based on the integration of genetic algorithm (GA) with the disjunctive formulations of generalized disjunctive programming (GDP) for the optimization of process networks, has been proposed. Discrete optimization problems, which give rise to the conditional modeling of equations through representations as logic based disjunctions, are very i...

Stackelberg games form the core of a number of tools deployed for computing optimal patrolling strategies in adversarial domains, such as the US Federal Air Marshall Service and the US Coast Guard. In traditional Stackelberg security game models the attacker knows only the probability that each target is covered by the defender, but is oblivious to the detailed timing of the coverage schedule. ...