A Method for Knowledge Engineering in Clinical Decision Making

The purpose of this study was to validate the problem behavior evaluation section of an expert system computer program, Class.BO. Class.BO was developed to assist special education personnel in determining whether students qualify for special education services as behaviorally disordered/severely emotionally disturbed students. The subjects were six Utah who regularly individuals from the state of 1) work with behaviorally disordered/severely emotionally disturbed students and 2) participate in multidisciplinary assessment teams. Three of the subjects were special educators, and three were school psychologists. Specifically, this study investigated the impact of five behavioral factors on the subjects\u27 ratings of the seriousness of problem behaviors. The five behavioral factors were 1) the severity or nature of the problem behavior, 2) the frequency with which the problem behavior occurs, 3) the duration over which the problem behavior has been occurring, 4) the generality of the problem behavior or the number of school environments the behavior occurs in , and 5) the percentage of the student\u27s peers who engage in the same behavior. For each behavioral factor, three levels of that factor were determined: high, moderate, and low. Problem behavior descriptions were developed by the researcher, each of which presented the five behavioral factors at a predetermined combination of levels. Of 65 problem behavior descriptions, 3 3 described externalized problem behaviors and 32 described internalized problem behaviors. Subjects were asked to rate the seriousness of each problem behavior description on an 11 point scale, where l=mild and ll=severe. The results showed high levels of agreement among subjects on ratings of seriousness of problem behaviors. There was also high agreement between the subjects\u27 ratings and ratings generated by the Class.BO expert system. Thus, Class. BD was validated. Further, the subjects gave highly similar ratings to descriptions of externalized and internalized problem behaviors. The results also indicated that the severity of the problem behaviors had the most impact on subjects\u27 ratings. Subjects discriminated three levels of severity but only two levels of frequency, duration, generality, and percentage of peers. Finally, the results provided support for the use of analysis of variance as a viable method of knowledge engineering, i.e., extracting information about how experts make decisions. Its superiority over traditional interview methods is discussed

Baroclinic instability with variable gravity: A perturbation analysis

Solutions for a quasigeostrophic baroclinic stability problem in which gravity is a function of height were obtained. Curvature and horizontal shear of the basic state flow were omitted and the vertical and horizontal temperature gradients of the basic state were taken as constant. The effect of a variable dielectric body force, analogous to gravity, on baroclinic instability for the design of a spherical, baroclinic model for Spacelab was determined. Such modeling could not be performed in a laboratory on the Earth's surface because the body force could not be made strong enough to dominate terrestrial gravity. A consequence of the body force variation and the preceding assumptions was that the potential vorticity gradient of the basic state vanished. The problem was solved using a perturbation method. The solution gives results which are qualitatively similar to Eady's results for constant gravity; a short wavelength cutoff and a wavelength of maximum growth rate were observed. The averaged values of the basic state indicate that both the wavelength range of the instability and the growth rate at maximum instability are increased. Results indicate that the presence of the variable body force will not significantly alter the dynamics of the Spacelab experiment. The solutions are also relevant to other geophysical fluid flows where gravity is constant but the static stability or Brunt-Vaisala frequency is a function of height

Paper Session III-A - Artificial Expertise in Systems Engineering

As technology development and engineering problems have grown in complexity, technical systems have evolved to meet these challenges. This evolution has occurred within a foundation of traditional engineering analysis and work processes originating prior to current computer technology. These processes were designed to improvise and compensate for ambiguous design or analysis information. Systems engineering optimization of computer technology applications can eliminate or redesign engineering processes such that the unified system function focuses on innovation, flexibility, speed, and quality. Artificial Expertise for systems engineering refers to the application of artificial intelligence expert systems and shared data bases to promote the integration of cross-functional engineering groups through technical interchange and control mechanisms. This paper presents some conceptual applications and examples for implementing artificial expertise in system development

Experimental quantification of the Fe-valence state at amosite-asbestos boundaries using acSTEM dual-electron energy-loss spectroscopy

Determination of the oxidation state and coordination geometry of iron in Fe-bearing minerals expands our knowledge obtained by standard mineralogical characterization. It provides information that is crucial in assessing the potential of minerals to interact with their surrounding environment and to generate reactive oxygen species, which can disrupt the normal function of living organisms. Aberration-corrected scanning transmission electron microscopy dual-electron energy-loss spectroscopy (acSTEM Dual-EELS) has only rarely been applied in environmental and medical mineralogy, but it can yield data that are essential for the description of near-surface and surface mechanisms involved in many environmental and health-related processes. In this study, we have applied the energy loss near-edge structure (ELNES) and L2,3 white-line intensity-ratio methods using both the universal curve and progressively larger integrating windows to verify their effectiveness in satisfactorily describing the valence state of iron at amosite grain boundaries, and, at the same time, to estimate thickness in the same region of interest. The average valence state obtained from acSTEM Dual-EELS and from a simplified geometrical model were in good agreement, and within the range defined by the bulk and the measured surface-valence states. In the specific case presented here, the use of the universal curve was most suitable in defining the valence state of iron at amosite grain boundaries. The study of ELNES revealed an excellent correspondence with the valence state determined by the L2,3 white-line intensity-ratio method through the use of the universal curve, and it seems that the spectra carry some information regarding the coordination geometry of Fe. The combination of visual examination, reconstruction of the grain boundaries through a simple geometrical model, and Dual-EELS investigation is a powerful tool for characterizing the grain boundaries of hazardous minerals and foreseeing their potential activity in an organism, with the possibility to describe toxic mechanisms in a stepwise fashion

Control of Diffuse Vacuum Arc Using Axial Magnetic Fields in Commercial High Voltage Switchgear

During the development of a commercial vacuum interrupter for application in HV (high voltage) switchgear at a rated voltage of 145kV, we investigated the behavior of vacuum arcs controlled by axial magnetic fields (AMF). AMF arc control is already extensively used in medium voltage (1-52kV) applications, the key difference is the 2-3 times larger contact gap and the corresponding reduction of the AMF strength for HV applications. We conducted several stress tests with short circuit currents up to 40kA, thus not only testing the interrupting capability, but also the electrical endurance of such a contact system. We also investigated the dielectric behavior of the vacuum interrupter by testing the capacitive switching duty. Overall, the contacts were used in about 40 operations at high currents. Despite this large number of operations, they showed a minimal amount of contact erosion and damage and demonstrated behavior very similar to the extensive experience with MV vacuum interrupters. In line with simulation results, we conclude that even at high contact gaps and currents, a diffuse vacuum arc was maintained which distributed the arc energy evenly over the contacts

How Probabilistic Causation Can Account for the Use of Mechanistic Evidence

In a recent paper in this journal, Federica Russo and Jon Williamson argue that an analysis of causality in terms of probabilistic relationships does not do justice to the use of mechanistic evidence to support causal claims. I will present Ronald Giere=s theory of probabilistic causation, and show that it can account for the use of mechanistic evidence (both in the health sciences B on which Russo and Williamson focus B and elsewhere). I also review some other probabilistic theories of causation (of Suppes, Eells and Humphreys) and show that they cannot account for the use of mechanistic evidence. I argue that these theories are also inferior to Giere's theory in other respects

How organizational cognitive neuroscience can deepen understanding of managerial decision-making:a review of the recent literature and future directions

There is growing interest in exploring the potential links between human biology and management and organization studies, which is bringing greater attention to bear on the place of mental processes in explaining human behaviour and effectiveness. The authors define this new field as organizational cognitive neuroscience (OCN), which is in the exploratory phase of its emergence and diffusion. It is clear that there are methodological debates and issues associated with OCN research, and the aim of this paper is to illuminate these concerns, and provide a roadmap for rigorous and relevant future work in the area. To this end, the current reach of OCN is investigated by the systematic review methodology, revealing three clusters of activity, covering the fields of economics, marketing and organizational behaviour. Among these clusters, organizational behaviour seems to be an outlier, owing to its far greater variety of empirical work, which the authors argue is largely a result of the plurality of research methods that have taken root within this field. Nevertheless, all three clusters contribute to a greater understanding of the biological mechanisms that mediate choice and decision-making. The paper concludes that OCN research has already provided important insights regarding the boundaries surrounding human freedom to act in various domains and, in turn, self-determination to influence the workplace. However, there is much to be done, and emerging research of significant interest is highlighted

Epistemic Dependence and Collective Scientific Knowledge

I argue that scientific knowledge is collective knowledge, in a sense to be specified and defended. I first consider some existing proposals for construing collective knowledge and argue that they are unsatisfactory, at least for scientific knowledge as we encounter it in actual scientific practice. Then I introduce an alternative conception of collective knowledge, on which knowledge is collective if there is a strong form of mutual epistemic dependence among scientists, which makes it so that satisfaction of the justification condition on knowledge ineliminably requires a collective. Next, I show how features of contemporary science support the conclusion that scientific knowledge is collective knowledge in this sense. Finally, I consider implications of my proposal and defend it against objections. © 2013 Springer Science+Business Media Dordrecht

The turn of the valve: representing with material models

Many scientific models are representations. Building on Goodman and Elgin’s notion of representation-as we analyse what this claim involves by providing a general definition of what makes something a scientific model, and formulating a novel account of how they represent. We call the result the DEKI account of representation, which offers a complex kind of representation involving an interplay of, denotation, exemplification, keying up of properties, and imputation. Throughout we focus on material models, and we illustrate our claims with the Phillips-Newlyn machine. In the conclusion we suggest that, mutatis mutandis, the DEKI account can be carried over to other kinds of models, notably fictional and mathematical models