Bringing the Field into the Classroom by Using Dynamic Digital Maps to Engage Undergraduate Students in Petrology Research

This article describes the use of Dynamic Digital Maps (DDMs) in undergraduate petrology courses. A DDM is a stand-alone computer program that presents interactive geologic maps, digital images, movies, animations, text and data. DDMs were developed for use in two undergraduate research projects, and impacts on student learning were evaluated by administering assessments on students before and after participation in one of the projects. Researchers found significant gains in both students' confidence in their ability to do research and to understand petrology, and noted that DDMs are versatile and can potentially be adapted effectively from 100-level introductory geology labs to research-oriented gradute level courses and in a variety of geologic subdisciplines. Educational levels: Graduate or professional, Graduate or professional

The business machine in biology: the commercialization of AI in the life science

This paper traces one important trajectory in the history of expert systems. Through a collaboration between Edward Feigenbaum and the geneticist Joshua Lederberg, Nobel Laureate in Medicine, AI became deeply connected to the life sciences. Biology was a crucial test-bed for some of Feigenbaums systems and, in the long term, these systems had a transformative effect on biology. In particular, the work of Feigenbaum and his collaborators and students, brought biology and computing together in especially powerful ways. We now take for granted that biology can be computerized we have whole sub-disciplines such as bioinformatics, biocomputing, and computational biology devoted to the task of studying life as information. The computer systems and software that Feigenbaums lab helped to develop played an important role in establishing the possibility of these kinds of work

Expert system technology

The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends

Third Conference on Artificial Intelligence for Space Applications, part 2

Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed

The People Inside

Our collection begins with an example of computer vision that cuts through time and bureaucratic opacity to help us meet real people from the past. Buried in thousands of files in the National Archives of Australia is evidence of the exclusionary “White Australia” policies of the nineteenth and twentieth centuries, which were intended to limit and discourage immigration by non-Europeans. Tim Sherratt and Kate Bagnall decided to see what would happen if they used a form of face-detection software made ubiquitous by modern surveillance systems and applied it to a security system of a century ago. What we get is a new way to see the government documents, not as a source of statistics but, Sherratt and Bagnall argue, as powerful evidence of the people affected by racism

Meta-programming composers in 2nd generation component systems

Future component systems will require that components can be composed flexibly. In contrast to current systems which only support a fixed set of composition mechanisms, the component system should provide a composition language in which users can define their own specific composers. It is argued for an object-oriented setting that this will be possible by meta-programming the class-graph. Composers will be based on two important elements. First, they will express coupling by graph-based operators which transform parts of the class-graph (coupling design patterns). Second, during these transformations, elementary meta-operators will be used to transform data and code, rearranging slots and methods of parameter-components. Thus during their reuse, components are queried by introspection and transformed by meta-programming. Composers that use meta-programming generalize connectors in architectural languages. Hence they encapsulate context-dependent aspects of a system, and make components independent of their embedding context. Since meta-programming composers may change behavior of components transparently, meta-programming composers will lead to a nice form of grey-box reuse, which supports embedding of components (and classes) into application contexts in a new and flexible way

Making power visible for museum educators : a theoretical framework for multicultural museum education

The central guiding question of this study is how can museum educators (and volunteers) effectively engage multicultural audiences, who may face langauge and socioeconomic barriers, with objects of art in museum galleries?

Making diagnosis explicit

What is good diagnostic practice? The answer is elusive for many medical students and equally puzzling for those trying to build effective medical decision support systems. Much of the problem lies in the difficult of 'getting at' diagnosis. Expert diagnosticians find it difficult to introspect on their own strategies, thus making it difficult to pass on their expertise.Traditional knowledge acquisition methods are designed for gathering static domain knowledge and are inappropriate for the acquisition of knowledge about the diagnos¬ tic 'task'. More advanced knowledge acquisition methodologies, particularly those which focus on the modelling of problem-solving knowledge seem to hold more promise, but are not sufficiently practicable to allow anyone other than a knowledge engineer to operate directly. Given the difficulty experts have in accessing their own diagnostic strategies what is needed is a tool which would enable diagnosticians themselves to directly formu¬ late and experiment with their own methods of diagnosis.This research describes the development of a knowledge acquisition methodology geared specifically towards the exposition of medical diagnosis. The methodology is implemented as a toolkit enabling exploration and construction of medical diagnostic models and production of model-based medical diagnostic support systems. The toolkit allows someone skilled in diagnosis to articulate their diagnostic strategy so that it can be used by those with less experience

A reusable knowledge acquisition shell: KASH

KASH (Knowledge Acquisition SHell) is proposed to assist a knowledge engineer by providing a set of utilities for constructing knowledge acquisition sessions based on interviewing techniques. The information elicited from domain experts during the sessions is guided by a question dependency graph (QDG). The QDG defined by the knowledge engineer, consists of a series of control questions about the domain that are used to organize the knowledge of an expert. The content information supplies by the expert, in response to the questions, is represented in the form of a concept map. These maps can be constructed in a top-down or bottom-up manner by the QDG and used by KASH to generate the rules for a large class of expert system domains. Additionally, the concept maps can support the representation of temporal knowledge. The high degree of reusability encountered in the QDG and concept maps can vastly reduce the development times and costs associated with producing intelligent decision aids, training programs, and process control functions

Grand tour of concepts for object-orientation from a database point of view

Over the last few years, object-orientation has gained more and more importance within several disciplines of computer science (e.g. programming languages, knowledge engineering, and database systems). Numerous papers have defined one or another of its underlying concepts (sometimes in quite different ways), and some systems have been developed following those heterogeneous definitions. Nevertheless, papers investigating the dependencies and degrees of freedom of these concepts are rarely found. For this reason, the goal of this paper is not to add yet another definition of object-oriented concepts, but to identify existing relationships among these basic concepts that allow one to cover and classify various conceivable combinations of these conceptual building blocks. Dependencies, orthogonalities, and relations among concepts like object identity, encapsulation, classification, generalization, inheritance, etc. are revealed, showing numerous ways to compose different shades of object-orientation. This leads to alternatives encountered when constructing object-oriented systems, which are illustrated by classifying some well-known systems and prototypes from different areas. However, it is not our purpose to analyze the relative importance of these concepts. Instead, we investigate the concepts from a neutral point of view, presenting (but not evaluating) several degrees of object-orientation