The computer in literary analysis: UsingTACT with students

TACT, a freeware program from the University of Toronto's Centre for Computing in the Humanities, is a highly sophisticated tool for text retrieval; although written for experienced critics and researchers, it can teach undergraduate students to read literature in new, fresh ways. Without requiring that the user become either a programmer, linguist, mathematician, or statistician,TACT introduces the literature student to the computer as a research tool. Studies of imagery and symbolism, of structural patterns, and of prosody can result from the student's careful tagging of a literary text and can yield significant insights into the work of literature. Students who use the computer as such a tool learn to read literary texts more closely and to think more clearly about literary problems.     

Distributed Control for 3D Metamorphosis

In this paper, we define Proteo as a class of three-dimensional (3D) metamorphic robotic system capable of approximating arbitrary 3D shapes by utilizing repeated modules. Each Proteo module contains embedded sensors, actuators and a controller, and each resides in a 3D grid space. A module can move itself to one of its open neighbor sites under certain motion constraints. Distributed control for the self-reconfiguration of such robots is an interesting and challenging problem. We present a class of distributed control algorithms for the reconfiguration of Proteo robots based on the goal-ordering mechanism. Performance results are shown for experiments of these algorithms in a simulation environment, and the properties of these algorithms are analyzed.     

Adoption of Asynchronous Learning Tools by Traditional Full-Time Students: A Pilot Study

Comparing the performance of distance learning and on-campus students is a well-studied problem. Results have shown that distance learners can perform as well or better than on-campus students. Few studies, however, have explored how or why traditional on-campus students utilize the technology intended for distance learners. Many universities and corporations provide educational and training content simultaneously to both face-to-face and distance students. Thus, exploring how instructional technology typically designed for distance learning students could benefit traditional students is important to our understanding of present and future learning environments. To this end, a pilot study was undertaken that explored how graduate students – primarily business majors – adopted and used video-streaming technology for a one semester course on Knowledge Management Tools and Techniques. Results indicated that age, previous use of the technology, need for interaction and Internet connectivity all influenced the decisions of the subjects to adopt the technology. Two-thirds of the subjects used the technology, with a self-reported estimate of procuring 16% of the course content asynchronously. Most used video streaming for convenience reasons and to review class material.     

Influence of material handling devices on the physical load during the end assembly of cars

The effect of using a mechanical device on physical load was analysed during the end assembly of cars. Five tasks, further sub-divided into lifting and positioning, were performed by someone experienced in working with and without the mechanical tool. A practical methodology was used: the subjective walk and talk through method, the NIOSH equation (1991), a three-dimensional goniometer (Back Tracker) and surface electromyography (EMG) of the relevant muscle groups. According to the NIOSH equation, 8 out of 10 of the tasks should only be performed by trained workers and preferably with tools. The Back Tracker revealed that the mechanical tools reduced posture angles significantly (p0.05) for installing the windows, but not for left lateroflexion during pre-assembly of windows. It was clear from the EMG analysis that using tools did not always decrease muscular activity significantly. In general, the appropriateness of each tool needs to be evaluated separately taking the subjective criteria into account.

Relevance to industry

In this study, the relevance of using a mechanical device to reduce the physical load during car assembly, is evaluated. As the tools are expensive, it is important to the industry whether they are being used and how efficient they are.     

A graphical user interface for Boolean query specification

Online information repositories commonly provide keyword search facilities through textual query languages based on Boolean logic. However, there is evidence to suggest that the syntactic demands of such languages can lead to user errors and adversely affect the time that it takes users to form queries. Users also face difficulties because of the conflict in semantics between AND and OR when used in Boolean logic and English language. Analysis of usage logs for the New Zealand Digital Library (NZDL) show that few Boolean queries contain more than three terms, use of the intersection operator dominates and that query refinement is common. We suggest that graphical query languages, in particular Venn-like diagrams, can alleviate the problems that users experience when forming Boolean expressions with textual languages. A study of the utility of Venn diagrams for query specification indicates that with little or no training users can interpret and form Venn-like diagrams in a consistent manner which accurately correspond to Boolean expressions. We describe VQuery, a Venn-diagram based user interface to the New Zealand Digital Library (NZDL). In a study which compared VQuery with a standard textual Boolean interface, users took significantly longer to form queries and produced more erroneous queries when using VQuery. We discuss the implications of these results and suggest directions for future work. Received: 15 December 1997 / Revised: June 1999     

An Introduction to Using XML for the Management of Laboratory Data

Extensible Markup Language (XML) and the XML Path Language (XPath) are introduced with software examples demonstrating how one can use them to write laboratory data management programs. Topics explored include XML document creation, manipulation, and searching. Programming examples make use of the Microsoft® XML Parser library and the Visual Basic programming language. The problem of managing microplate screening data is used as an illustration. Source code for all examples can be downloaded from http://www.labprogrammer.net.     

Kernel PCA for Feature Extraction and De-Noising in Nonlinear Regression

In this paper, we propose the application of the Kernel Principal Component Analysis (PCA) technique for feature selection in a high-dimensional feature space, where input variables are mapped by a Gaussian kernel. The extracted features are employed in the regression problems of chaotic Mackey–Glass time-series prediction in a noisy environment and estimating human signal detection performance from brain event-related potentials elicited by task relevant signals. We compared results obtained using either Kernel PCA or linear PCA as data preprocessing steps. On the human signal detection task, we report the superiority of Kernel PCA feature extraction over linear PCA. Similar to linear PCA, we demonstrate de-noising of the original data by the appropriate selection of various nonlinear principal components. The theoretical relation and experimental comparison of Kernel Principal Components Regression, Kernel Ridge Regression and ε-insensitive Support Vector Regression is also provided.     

Designing Agent-Based Electronic Employment Markets

Two modes of matching people with jobs prevail at present: 1) hierarchical planning and 2) distributed markets. Each has strengths and limitations, but few systems have been designed to take advantage of strengths corresponding to both. With evolving information technology, however, the job-matching process could be accomplished far more equitably and efficiently using web-based markets within the firm, and intelligent agents offer excellent potential to help both potential employees and employers find one another in a distributed, electronic marketplace. But realizing this potential goes well beyond simply changing the rules of internal job matching or making agent technology available to job searchers. Rather, the corresponding markets and technologies must be designed, together, to mutually accomplish the desired results (e.g., efficient and effective matching) and conform to necessary properties (e.g., market clearing). Through the research described in this paper, we draw from Game Theory results to assess the feasibility of using two-sided matching algorithms to address this market-design problem. We also draw from current agent research to address the information technology dimension of the problem by implementing a proof-of-concept multi-agent system to enact, automate and support the corresponding market solution. This paper integrates the key economic and technological elements required to design robust electronic employment markets. And the corresponding research provides new knowledge and insight into co-development of the requisite economic markets and agent technologies.     

Iterated Phantom Induction: A Knowledge-Based Approach to Learning Control

We advance a knowledge-based learning method that allows prior domain knowledge to be effectively utilized by machine learning systems. The domain knowledge is incorporated not into the learning algorithm itself but instead affects only the training data. The domain knowledge is used to explain and then transform the actual training examples into a more informative set of imaginary, or phantom examples. These phantom examples are added to the training set; the experienced examples are discarded. A new control policy is induced from the phantom training set. This policy is then exercised, yielding additional training points, and the process repeats.We investigate the performance of this method in a stylized air-hockey domain which demands a difficult nonlinear control policy. Our experiments show that, surprisingly, an accurate policy can be learned even if the domain theory is only imprecise and approximate. We advance an interpretation which indicates that the information available from a plausible qualitative domain theory is sufficient for robust successful learning. This interpretation is used to make a number of predictions which are tested in subsequent experiments. The outcomes confirm the interpretation and the robustness of the approach.     

Alleviating convergence problems in Group Support Systems

Not all Group Support Systems are identical, as is demonstrated by their software implementations. We discuss two existing implementations of group support tools and the process models underlying them. We demonstrate that fundamental to both processes is the merging or integration of individual data. Based on this and other empirical research, the Shared Context Model (SCM) of cooperative work is adopted and we show that it supports existing processes and others. We expect that groups will find merging their work easier with the SCM. This model is presented and embedded in the architecture and implementation of four group tools. Because these tools are destined to be used by dispersed groups, synchronously or asynchronously, an object-based communication and control mechanism is incorporated. Finally, as graphics and multi-tasking have been shown to be increasingly important, the tools are implemented in Microsoft Windows for personal computers attached to local area networks.