T-optimum designs for model discrimination are notoriously difficult to find because of the computational difficulty involved in solving an optimization problem that involves two layers of optimization. Only a handful of analytical T-optimal designs are available for the simplest problems; the rest in the literature are found using specialized numerical procedures for a specific problem. We pro...

Satellites’ rendezvous and docking is a challenging problem for space exploitation. Saving time, fuel, or any other resource, expressed for example as a combination of the two previous ones, is not a straightforward task if onboard calculation is required to make the control autonomous. A direct method for a rapid generation of near-optimal trajectories of proximity maneuvers onboard a flying v...

This paper studies various strategies in constrained simulated annealing (CSA), a global optimization algorithm that achieves asymptotic convergence to constrained global minima (CGM) with probability one for solving discrete constrained nonlinear programming problems (NLPs). The algorithm is based on the necessary and suucient condition for discrete constrained local minima (CLM) in the theory...

Batched sparse (BATS) code is a promising technology for reliable data transmission in multi-hop wireless networks. As a BATS code consists of an outer code and an inner code that typically is a random linear network code, one main research topic for BATS codes is to design an inner code with good performance in transmission efficiency and complexity. In this paper, this issue is addressed with...

Adaptive Random Searches (ARS) are simple and effective optimization methods used for handling complicated nonconvex / multimodal nonlinear programming (NLP) and mixed-integer nonlinear programming (MINLP) problems. ARS iteratively adapt search characteristics according to the past successful / failure steps. Periodic search domain expansions and contractions improve significantly the reliabili...

Neuro-Linguistic Programming (NLP) is a widely used approach, introduced by Bandler and Grinder (1970). In this study, the researcher explores different techniques involved in NLP, which can be utilized teachers teaching genres of literature such as drama, prose, etc. quasi-experimental research, selected two groups: one experimental group consisting 108 students, other control 141 enrolled Mas...

The paper describes a Flexible Language Acquisition Tool (FLAT) kit, a suite of multipurpose interactive tools for developing NLP systems and/or training computational linguists. The kit facilitates the use of linguistic expertise in developing NLP applications and allows for maintaining and improving a system output without extra programming effort. It can be used for any language based on ANS...

Joint inference approaches such as Integer Linear Programming (ILP) and Markov Logic Networks (MLNs) have recently been successfully applied to many natural language processing (NLP) tasks, often outperforming their pipeline counterparts. However, MLNs are arguably much less popular among NLP researchers than ILP. While NLP researchers who desire to employ these joint inference frameworks do no...

Neuro-Linguistic Programming (NLP), an emergent, contested approach to communication and personal development created in the 1970’s, has become increasingly familiar in education and teaching. There is little academic work on NLP to date. This article offers an informed introduction to, and appraisal of, the field for educators. We review the origins of NLP, and summarise its nature as a method...