Successful execution of missions is contingent upon learning a range of skills for a variety of tasks. The U.S. Army identifies common core tasks as well as tasks specific to each Military Occupational Specialty (MOS), and organizes them by skill level to support the learning progression throughout a Soldier’s career. While operational units are ultimately responsible for ensuring Soldiers are ...

In this article, we describe the effort being carried out in the analysis, design and implementation of the Vehicle and Mission Management Systems of a mobile platform for autonomous transportation, surveillance and inspection in structured and semi-structured industrial environments. The Vehicle and Mission Management System is based in a hierarchical structure organized linguistically permitt...

INFERRING structured predictions based on correlated covariates remains a central problem in many fields, including NLP, computer vision, and computational biology. Typically, both the input covariates and output predictions can be high-dimensional, multi-modal, noisy, partially observable, and bearing latent structures, each of these characteristics adds a degree of complexity to the task of l...

Wiki use may help EFL instructors to create an effective learning environment for inquiry-based language teaching and learning. The purpose of this study was to investigate the effects of wikis on the EFL learners’ IBL process. Forty-nine EFL students participated in the study while they conducted research projects in English. The Non-wiki group (n = 25) received traditional inquiry instr...

A key challenge in the realization of autonomous vehicles is the machine’s ability to perceive its surrounding environment. This task is tackled through a model that partitions vehicle camera input into distinct semantic classes, by taking into account visual contextual cues. The use of structured machine learning models is investigated, which not only allow for complex input, but also arbitrar...

This paper presents a large-scale evaluation study of dependency-based distributional semantic models. We evaluate dependencyfiltered and dependency-structured DSMs in a number of standard semantic similarity tasks, systematically exploring their parameter space in order to give them a “fair shot” against window-based models. Our results show that properly tuned window-based DSMs still outperfo...

With the rapid development of measurement technology, LiDAR and depth cameras are widely used in perception 3D environment. Recent learning based methods for robot most focus on image or video, but deep dynamic point cloud sequences underexplored. Therefore, developing efficient accurate method compatible with these advanced instruments is pivotal to autonomous driving service robots. An Anchor...

Many structured prediction tasks in machine vision have a collection of acceptable answers, instead of one definitive ground truth answer. Segmentation of images, for example, is subject to human labeling bias. Similarly, there are multiple possible pixel values that could plausibly complete occluded image regions. State-of-the art supervised learning methods are typically optimized to make a s...