Building language resources for a Multi-Engine English-Filipino machine translation system

In this paper, we present the building of various language resources for a multi-engine bi-directional English-Filipino Machine Translation (MT) system. Since linguistics information on Philippine languages are available, but as of yet, the focus has been on theoretical linguistics and little is done on the computational aspects of these languages, attempts are reported here on the manual construction of these language resources such as the grammar, lexicon, morphological information, and the corpora which were literally built from almost non-existent digital forms. Due to the inherent difficulties of manual construction, we also discuss our experiments on various technologies for automatic extraction of these resources to handle the intricacies of the Filipino language, designed with the intention of using them for the MT system. To implement the different MT engines and to ensure the improvement of translation quality, other language tools (such as the morphological analyzer and generator, and the part of speech tagger) were developed.     

Using informal notes for sharing corporate technology know-how

Corporate and academic communities have focused a great deal of attention on formalized approaches for creating, capturing, and propagating knowledge. Far less attention has been paid to the informal mechanisms that individuals share and employ to help them navigate complex processes in order to ‘get things done.’ In this paper, we examine the creation, use, and content of informal documents for supporting users of an enterprise resource planning system in a Fortune 500 company. We contend that such notes, which are commonly used for supporting information systems-related work, are an overlooked source of knowledgeability about organizational practices. This study is a first but necessary step in analyzing the types of information that can be derived from informal notes so that organizations can more fully utilize this largely untapped resource.     

Configuration Maintenance for Distributed Applications Management

The MANDAS project has defined a layered architecture for the management of distributed applications. In this paper we examine a vertical slice of this architecture, namely the management applications and services related to configuration management. We introduce an information model which captures the configuration information for distributed applications and discuss a repository service based on the model. We define a set of services and management applications to support maintenance of configuration information, and describe how the different types of configuration information are collected. Finally, we present two management applications that use configuration information.     

80 million tiny images: a large data set for nonparametric object and scene recognition

With the advent of the Internet, billions of images are now freely available online and constitute a dense sampling of the visual world. Using a variety of non-parametric methods, we explore this world with the aid of a large dataset of 79,302,017 images collected from the Internet. Motivated by psychophysical results showing the remarkable tolerance of the human visual system to degradations in image resolution, the images in the dataset are stored as 32 x 32 color images. Each image is loosely labeled with one of the 75,062 non-abstract nouns in English, as listed in the Wordnet lexical database. Hence the image database gives a comprehensive coverage of all object categories and scenes. The semantic information from Wordnet can be used in conjunction with nearest-neighbor methods to perform object classification over a range of semantic levels minimizing the effects of labeling noise. For certain classes that are particularly prevalent in the dataset, such as people, we are able to demonstrate a recognition performance comparable to class-specific Viola-Jones style detectors.     

A Framework for Average Case Analysis of Conjunctive Learning Algorithms

We present an approach to modeling the average case behavior of learning algorithms. Our motivation is to predict the expected accuracy of learning algorithms as a function of the number of training examples. We apply this framework to a purely empirical learning algorithm, (the one-sided algorithm for pure conjunctive concepts), and to an algorithm that combines empirical and explanation-based learning. The model is used to gain insight into the behavior of these algorithms on a series of problems. Finally, we evaluate how well the average case model performs when the training examples violate the assumptions of the model.     

Optimizing XML queries: Bitmapped materialized views vs. indexes

Optimizing queries using materialized views has not been addressed adequately in the context of XML due to the many limitations associated with the definition and usability of materialized views in traditional XML query evaluation models.     

Equations to predict female manual arm strength based on hand location relative to the shoulder

The purpose of this study was to develop regression equations to predict manual arm strength for a wide variety of hand locations within the reach envelope. Maximum voluntary manual arm strength was determined from 71 female participants in six exertion directions (superior, inferior, anterior, posterior, medial and lateral), in a total of 28 hand locations. Forces ranged from 51.3 to 164.4 N, and had a pooled coefficient of variation of 29.9%. Across all 168 combinations of hand locations and exertion directions, the multivariate regression equations explained 92.5% of the variance and had a root mean square error (RMSE) of only 6.4 N, using only the anterior, lateral and vertical location of the hand relative to the active shoulder joint as inputs. These equations provide a proof-of-principle for our novel regression approach, and represent a first step towards a more comprehensive equation to estimate maximum acceptable forces for occupational tasks.     

The development of a sound viewer for an open hypermedia system

Abstract

While rich support for a wide variety of media such as text, video and image is common among contemporary hypermedia systems, so too is the inadequate support for audio. The primary reason that audio has not attracted as much attention as other media can be attributed to its obvious lack of visual identity. The main focus of this work was to identify a generic and meaningful visual representation of audio within a hypermedia context, and significantly promote hypermedia support for audio through the provision of a sound viewer.

This paper describes the inherent difficulties in providing a consistent interface to audio, and discusses in some depth the issues raised during the development process. The sound viewer is then introduced and the associated concepts described. The creation and traversal of links to and from audio are facilitated by the sound viewer across formats including WAV (proprietary digital sound file format from Microsoft), CD (Compact Disc) Audio and MIDI (Musical Instrument Digital Interface). The resultant viewer provides a unified and extensible framework for interacting with audio from within an open hypermedia environment. The open hypermedia system Microcosm was used as the development platform for this work. Microcosm can be augmented to supply a hypermedia link service to additional media with minimal overhead.     

Reading in the dark: effects of age and contrast on reading speed and comprehension

OBJECTIVE: To explore the effects of contrast reduction on younger and older adults' reading behavior and to examine whether readers rely on word predictability to compensate for poor contrast. BACKGROUND: Poor contrast can degrade text and may influence reading behavior. Readers may compensate for visual degradation of text by taking advantage of word predictability. METHOD: In Experiment 1, 5 younger and 5 older adults read sentences presented with 10 levels of contrast. In Experiment 2, 40 younger and 40 older adults read high-, medium-, and low-contrast sentences that varied in target word predictability (high vs. low). RESULTS: Relative to those of younger adults, older adults' reading rates were more slowed by low contrast; comprehension was less influenced by contrast (i.e., not significantly). Older adults read high-predictability words faster and comprehended them better than low-predictability words, significantly so for high- and medium-contrast sentences. Younger adults comprehended high-predictability words significantly better than low-predictability words for high- and low-contrast sentences. CONCLUSION: Low contrast was more detrimental for older adults. High-predictability words benefited older adults by significantly reducing their reading times and benefited all readers by significantly increasing their comprehension. APPLICATION: The current findings demonstrate the benefit of adequate contrast and word predictability for optimal text design to facilitate both reading times and reading comprehension.     

Understanding challenges in the front lines of home health care: A human-systems approach

A human-systems perspective is a fruitful approach to understanding home health care because it emphasizes major individual components of the system – persons, equipment/technology, tasks, and environments – as well as the interaction between these components. The goal of this research was to apply a human-system perspective to consider the capabilities and limitations of the persons, in relation to the demands of the tasks and equipment/technology in home health care. Identification of challenges and mismatches between the person(s) capabilities and the demands of providing care provide guidance for human factors interventions. A qualitative study was conducted with 8 home health Certified Nursing Assistants and 8 home health Registered Nurses interviewed about challenges they encounter in their jobs. A systematic categorization of the challenges the care providers reported was conducted and human factors recommendations were proposed in response, to improve home health. The challenges inform a human-systems model of home health care.