Building by design /

Cover title.

Building by design /

A grants program supported by Build Illinois, and the National Endowment for the Arts.

Design guidelines for creating defensible space /

Includes bibliographical references.

Selecting optimal instantiations of data models - Theory and validation of an ex ante approach

The schema of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. Obtaining quickly the appropriate data increases the likelihood that an organization will make good decisions and respond adeptly to challenges. This research presents and validates a methodology for evaluating, ex ante, the relative desirability of alternative instantiations of a model of data. In contrast to prior research, each instantiation is based on a different formal theory. This research theorizes that the instantiation that yields the lowest weighted average query complexity for a representative sample of information requests is the most desirable instantiation for end-user queries. The theory was validated by an experiment that compared end-user performance using an instantiation of a data structure based on the relational model of data with performance using the corresponding instantiation of the data structure based on the object-relational model of data. Complexity was measured using three different Halstead metrics: program length, difficulty, and effort. For a representative sample of queries, the average complexity using each instantiation was calculated. As theorized, end users querying the instantiation with the lower average complexity made fewer semantic errors, i.e., were more effective at composing queries. (c) 2005 Elsevier B.V. All rights reserved.

Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project

Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

A reference architecture for instructional educational software

Our extensive research has indicated that high-school teachers are reluctant to make use of existing instructional educational software (Pollard, 2005). Even software developed in a partnership between a teacher and a software engineer is unlikely to be adopted by teachers outside the partnership (Pollard, 2005). In this paper we address these issues directly by adopting a reusable architectural design for instructional educational software which allows easy customisation of software to meet the specific needs of individual teachers. By doing this we will facilitate more teachers regularly using instructional technology within their classrooms. Our domain-specific software architecture, Interface-Activities-Model, was designed specifically to facilitate individual customisation by redefining and restructuring what constitutes an object so that they can be readily reused or extended as required. The key to this architecture is the way in which the software is broken into small generic encapsulated components with minimal domain specific behaviour. The domain specific behaviour is decoupled from the interface and encapsulated in objects which relate to the instructional material through tasks and activities. The domain model is also broken into two distinct models - Application State Model and Domainspecific Data Model. This decoupling and distribution of control gives the software designer enormous flexibility in modifying components without affecting other sections of the design. This paper sets the context of this architecture, describes it in detail, and applies it to an actual application developed to teach high-school mathematical concepts.

Data quality initiatives - striving for continuous improvements

Although managers consider accurate, timely, and relevant information as critical to the quality of their decisions, evidence of large variations in data quality abounds. Over a period of twelve months, the action research project reported herein attempted to investigate and track data quality initiatives undertaken by the participating organisation. The investigation focused on two types of errors: transaction input errors and processing errors. Whenever the action research initiative identified non-trivial errors, the participating organisation introduced actions to correct the errors and prevent similar errors in the future. Data quality metrics were taken quarterly to measure improvements resulting from the activities undertaken during the action research project. The action research project results indicated that for a mission-critical database to ensure and maintain data quality, commitment to continuous data quality improvement is necessary. Also, communication among all stakeholders is required to ensure common understanding of data quality improvement goals. The action research project found that to further substantially improve data quality, structural changes within the organisation and to the information systems are sometimes necessary. The major goal of the action research study is to increase the level of data quality awareness within all organisations and to motivate them to examine the importance of achieving and maintaining high-quality data.

Dissecting query performance in logical data models: Parsimony vs. greater ontological clarity

Even when data repositories exhibit near perfect data quality, users may formulate queries that do not correspond to the information requested. Users’ poor information retrieval performance may arise from either problems understanding of the data models that represent the real world systems, or their query skills. This research focuses on users’ understanding of the data structures, i.e., their ability to map the information request and the data model. The Bunge-Wand-Weber ontology was used to formulate three sets of hypotheses. Two laboratory experiments (one using a small data model and one using a larger data model) tested the effect of ontological clarity on users’ performance when undertaking component, record, and aggregate level tasks. The results indicate for the hypotheses associated with different representations but equivalent semantics that parsimonious data model participants performed better for component level tasks but that ontologically clearer data model participants performed better for record and aggregate level tasks.

Neural networks for time-varying data

This paper reviews some basic issues and methods involved in using neural networks to respond in a desired fashion to a temporally-varying environment. Some popular network models and training methods are introduced. A speech recognition example is then used to illustrate the central difficulty of temporal data processing: learning to notice and remember relevant contextual information. Feedforward network methods are applicable to cases where this problem is not severe. The application of these methods are explained and applications are discussed in the areas of pure mathematics, chemical and physical systems, and economic systems. A more powerful but less practical algorithm for temporal problems, the moving targets algorithm, is sketched and discussed. For completeness, a few remarks are made on reinforcement learning.

Is China's manufacturing sector becoming more high-tech? Evidence on shifts in comparative advantage, 1987-2005

Purpose – The paper assesses the extent to which China’s comparative advantage in manufacturing has shifted towards higher-tech sectors between 1987 and 2005 and proposes possible explanations for the shift. Design/methodology/approach – Revealed comparative advantage (RCA) indices for 27 product groups, representing high-, medium and low-tech sectors have been calculated. Examination of international market attractiveness complements the RCA analysis. Findings for selected sectors are evaluated in the context of other evidence. Findings – While China maintains its competitiveness in low-tech labour intensive products, it has gained RCA in selected medium-tech sectors (e.g. office machines and electric machinery) and the high-tech telecommunications and automatic data processing equipment sectors. Evidence from firm and sector specific studies suggests that improved comparative advantage in medium and high-tech sectors is based on capabilities developing through combining international technology transfer and learning. Research limitations/implications – The quantitative analysis does not explain the shifts in comparative advantage, though the paper suggests possible explanations. Further research at firm and sector levels is required to understand the underlying capability development of Chinese enterprises and the relative competitiveness of Chinese and foreign invested enterprises. Practical implications – Western companies should take account of capability development in China in forming their international manufacturing strategies. The rapid shifts in China’s comparative advantage have lessons for other industrialising countries. Originality/value – While RCA is a well-known methodology, its application at the disaggregated product group level combined with market attractiveness assessment is distinctive. The paper provides a broad assessment of changes in Chinese manufacturing as a basis for further research on capability development at firm and sector levels.

Exploratory database visualisation: the application and assessment of data and dimensionality reduction

This thesis describes the development of a complete data visualisation system for large tabular databases, such as those commonly found in a business environment. A state-of-the-art 'cyberspace cell' data visualisation technique was investigated and a powerful visualisation system using it was implemented. Although allowing databases to be explored and conclusions drawn, it had several drawbacks, the majority of which were due to the three-dimensional nature of the visualisation. A novel two-dimensional generic visualisation system, known as MADEN, was then developed and implemented, based upon a 2-D matrix of 'density plots'. MADEN allows an entire high-dimensional database to be visualised in one window, while permitting close analysis in 'enlargement' windows. Selections of records can be made and examined, and dependencies between fields can be investigated in detail. MADEN was used as a tool for investigating and assessing many data processing algorithms, firstly data-reducing (clustering) methods, then dimensionality-reducing techniques. These included a new 'directed' form of principal components analysis, several novel applications of artificial neural networks, and discriminant analysis techniques which illustrated how groups within a database can be separated. To illustrate the power of the system, MADEN was used to explore customer databases from two financial institutions, resulting in a number of discoveries which would be of interest to a marketing manager. Finally, the database of results from the 1992 UK Research Assessment Exercise was analysed. Using MADEN allowed both universities and disciplines to be graphically compared, and supplied some startling revelations, including empirical evidence of the 'Oxbridge factor'.

Novel approaches in nonlinear optical fibre-based signal processing

All-optical data processing is expected to play a major role in future optical communications. Nonlinear effects in optical fibres have many attractive features and a great, not yet fully explored potential in optical signal processing. Here, we overview our recent advances in developing novel techniques and approaches to all-optical processing based on optical fibre nonlinearities.