Evaluating the effectiveness of augmented reality displays for a manual assembly task

The focus of this research was to examine how effectively augmented reality displays, generated with a wearable computer, could be used for aiding an operator performing a manual assembly task. Fifteen subjects were asked to assemble a computer motherboard using four types of instructional media: paper manual, computer-aided, opaque augmented reality display, and see-through augmented reality display. The time of assembly and assembly errors were measured for each type of instructional media, and a questionnaire focusing on usability was administered to each subject at the end of each condition. The results of the experiment indicated that the augmented reality conditions were more effective instructional aids for the assembly task than either the paper instruction manual or the computer-aided instruction. The see-through augmented reality display resulted in the fastest assembly times, followed by the opaque augmented reality display, the computer-aided instruction, and the paper instructions respectively. In addition, subjects made fewer errors using the augmented reality conditions compared to the computer-aided and paper instructional media. However, while the two augmented reality conditions were a more effective instructional media when time for assembly was the response measure, there were still some important usability issues associated with the augmented reality technology that were not present in the non-augmented reality conditions.     

Reading handwritten digits: a ZIP code recognition system

A neural network algorithm-based system that reads handwritten ZIP codes appearing on real US mail is described. The system uses a recognition-based segmenter, that is a hybrid of connected-components analysis (CCA), vertical cuts, and a neural network recognizer. Connected components that are single digits are handled by CCA. CCs that are combined or dissected digits are handled by the vertical-cut segmenter. The four main stages of processing are preprocessing, in which noise is removed and the digits are deslanted, CCA segmentation and recognition, vertical-cut-point estimation and segmentation, and directly lookup. The system was trained and tested on approximately 10000 images, five- and nine-digit ZIP code fields taken from real mail     

Large-scale simulation studies in image pattern recognition

Many obstacles to progress in image pattern recognition result from the fact that per-class distributions are often too irregular to be well-approximated by simple analytical functions. Simulation studies offer one way to circumvent these obstacles. We present three closely related studies of machine-printed character recognition that rely on synthetic data generated pseudo-randomly in accordance with an explicit stochastic model of document image degradations. The unusually large scale of experiments - involving several million samples that makes this methodology possible have allowed us to compute sharp estimates of the intrinsic difficulty (Bayes risk) of concrete image recognition problems, as well as the asymptotic accuracy and domain of competency of classifiers     

An intelligent control and decision approach for adaptive systems

An intelligent control and decision-making (ICD) approach that integrates expert systems technology with adaptive algorithms is presented. The controller parameters of adaptive systems can be determined using human expertise and knowledge, and they can also be adjusted based on active monitoring and identification. Decision-making, fine tuning and inexact reasoning provide the end-user and the control engineers with a natural and integrated methodology for use with intelligent control systems. Computer simulation results demonstrate the utility of the proposed technique that is an effective intelligent control and decision approach. The ICD system is implemented using a Lisp based expert system shell on an IBM PC.     

Issues in the design and use of wearable computers

Wearable computers are fully functional, self-powered, self-contained computers that allow the user to access information anywhere and at any time. In this paper, design issues for wearable computers are discussed, including power considerations, use of input devices, image registration, and the use of wearable computers for the design of smart spaces. Application areas for wearable computers are presented, including medicine, manufacturing, maintenance, and as personal assistants. Finally, future research directions for wearable computers are indicated.     

On the recognition of printed characters of any font and size

We describe the current state of a system that recognizes printed text of various fonts and sizes for the Roman alphabet. The system combines several techniques in order to improve the overall recognition rate. Thinning and shape extraction are performed directly on a graph of the run-length encoding of a binary image. The resulting strokes and other shapes are mapped, using a shape-clustering approach, into binary features which are then fed into a statistical Bayesian classifier. Large-scale trials have shown better than 97 percent top choice correct performance on mixtures of six dissimilar fonts, and over 99 percent on most single fonts, over a range of point sizes. Certain remaining confusion classes are disambiguated through contour analysis, and characters suspected of being merged are broken and reclassified. Finally, layout and linguistic context are applied. The results are illustrated by sample pages.     

Energy — audit and management

The authors, Nigel Isaacs, Michael Donn and Dr George Baird of the School of Architecture, Victoria University of Wellington, present a succinct account of the practical difficulties they encountered when implementing recommendations from energy audits in a defined number of New Zealand schools. It is concluded that these difficulties relate more to funding and personnel than the engineering of the energy savings in themselves.     

Loss of the thalamic nuclei for "head direction" impairs performance on spatial memory tasks in rats.

This study sought to characterize the effects of removing the nuclei of primary importance in relaying the thalamic head direction signal to the hippocampal formation (the anterior dorsal [AD] and lateral dorsal [LD] nuclei) on the performance of a variety of spatial and nonspatial tasks. The results indicate that combined excitotoxic lesions of the AD and LD nuclei produce marked deficits on a variety of spatial tasks. These tasks included T-maze alternation and the ability to locate a hidden platform set at a fixed distance and fixed direction from a beacon in a Morris water maze. Although object recognition appeared unaffected, marked impairments were found in the ability to detect when an object was placed in a novel position (object-in-place memory). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A statistical, nonparametric methodology for document degradation model validation

Printing, photocopying, and scanning processes degrade the image quality of a document. Statistical models of these degradation processes are crucial for document image understanding research. In this paper, we present a statistical methodology that can be used to validate local degradation models. This method is based on a nonparametric, two-sample permutation test. Another standard statistical device, the power function, is then used to choose between algorithm variables such as distance functions. Since the validation and the power function procedures are independent of the model, they can be used to validate any other degradation model. A method for comparing any two models is also described. It uses p-values associated with the estimated models to select the model that is closer to the real world.