Using knowledge structures to redesign an instructor-operator station

Frequently, user interface (UI) designers must choose between modifying an established, but suboptimal and familiar, UI or to avoid such changes. Changing the UI’s, organization may frustrate users who have become familiar with the original design, whereas failing to make changes may force users to perform at an unsatisfactory level. This paper presents two studies that investigate whether users familiar with a poorly designed UI would find items faster, and prefer a reorganized UI that conformed to domain expert knowledge, or would their familiarity with the original UI yield faster performance and higher satisfaction.This paper describes activities to redesign a menu structure in a simulator instructor–operator station (IOS) using hierarchical card sorting and cluster analysis (Romesburg, 2004). This analysis was used to reorganize the menu structure to reflect the knowledge representations of domain experts in accordance with the principle of proximity compatibility (Wickens and Carswell, 1995, Rothrock et al., 2006). The new design was validated with a separate set of users by a reaction time experiment and preference selection.     

A flexible extreme value mixture model

Extreme value theory is used to derive asymptotically motivated models for unusual or rare events, e.g. the upper or lower tails of a distribution. A new flexible extreme value mixture model is proposed combining a non-parametric kernel density estimator for the bulk of the distribution with an appropriate tail model. The complex uncertainties associated with threshold choice are accounted for and new insights into the impact of threshold choice on density and quantile estimates are obtained. Bayesian inference is used to account for all uncertainties and enables inclusion of expert prior information, potentially overcoming the inherent sparsity of extremal data. A simulation study and empirical application for determining normal ranges for physiological measurements for pre-term infants is used to demonstrate the performance of the proposed mixture model. The potential of the proposed model for overcoming the lack of consistency of likelihood based kernel bandwidth estimators when faced with heavy tailed distributions is also demonstrated.     

A Stronger Model of Dynamic Programming Algorithms

We define a formal model of dynamic programming algorithms which we call Prioritized Branching Programs (pBP). Our model is a generalization of the BT model of Alekhnovich et al. (IEEE Conference on Computational Complexity, pp. 308–322, 2005), which is in turn a generalization of the priority algorithms model of Borodin, Nielson and Rackoff. One of the distinguishing features of these models is that they not only capture large classes of algorithms generally considered to be greedy, backtracking or dynamic programming algorithms, but they also allow characterizations of their limitations. Hence they give meaning to the statement that a given problem can or cannot be solved by dynamic programming. After defining the model, we prove three main results: (i) that certain types of natural restrictions of our seemingly more powerful model can be simulated by the BT model; (ii) that in general our model is stronger than the BT model—a fact which is witnessed by the classical shortest paths problem; (iii) that our model has very real limitations, namely that bipartite matching cannot be efficiently computed in it, hence suggesting that there are problems that can be solved efficiently by network flow algorithms and by simple linear programming that cannot be solved by natural dynamic programming approaches.     

Performance enhancement in an uninhabited air vehicle task using psychophysiologically determined adaptive aiding

OBJECTIVE: We show that psychophysiologically driven real-time adaptive aiding significantly enhances performance in a complex aviation task. A further goal was to assess the importance of individual operator capabilities when providing adaptive aiding. BACKGROUND: Psychophysiological measures are useful for monitoring cognitive workload in laboratory and real-world settings. They can be recorded without intruding into task performance and can be analyzed in real time, making them candidates for providing operator functional state estimates. These estimates could be used to determine if and when system intervention should be provided to assist the operator to improve system performance. METHODS: Adaptive automation was implemented while operators performed an uninhabited aerial vehicle task. Psychophysiological data were collected and an artificial neural network was used to detect periods of high and low mental workload in real time. The high-difficulty task levels used to initiate the adaptive automation were determined separately for each operator, and a group-derived mean difficulty level was also used. RESULTS: Psychophysiologically determined aiding significantly improved performance when compared with the no-aiding conditions. Improvement was greater when adaptive aiding was provided based on individualized criteria rather than on group-derived criteria. The improvements were significantly greater than when the aiding was randomly provided. CONCLUSION: These results show that psychophysiologically determined operator functional state assessment in real time led to performance improvement when included in closed loop adaptive automation with a complex task. APPLICATION: Potential future applications of this research include enhanced workstations using adaptive aiding that would be driven by operator functional state.     

Toxicoproteomics and its application to human health risk assessment

Toxicoproteomics is the use of proteomic technologies to better understand environmental and genetic factors, toxic mechanisms, and modes of action in response to acute exposure to toxicants and in the long-term development of diseases caused or influenced by these exposures. Use of toxicoproteomic technologies to identify key biochemical pathways, mechanisms, and biomarkers of exposure and toxicity will decrease the uncertainties that are associated with human health risk assessments. This review provides an overview of toxicoproteomics from human health risk assessment perspectives. Key toxicoproteomic technologies such as 2-D gel-based proteomic methods and toxicoproteomic approaches are described, and examples of applications of these technologies and methodologies in the risk assessment context are presented. The discussion includes a focus on challenges and future directions.     

Learning and retention of associations between auditory icons and denotative referents: implications for the design of auditory warnings

OBJECTIVE: This study examined the way in which the type and preexisting strength of association between an auditory icon and a warning event affects the ease with which the icon/event pairing can be learned and retained. BACKGROUND: To be effective, an auditory warning must be audible, identifiable, interpretable, and heeded. Warnings consisting of familiar environmental sounds, or auditory icons, have potential to facilitate identification and interpretation. The ease with which pairings between auditory icons and warning events can be learned and retained is likely to depend on the type and strength of the preexisting icon/event association. METHOD: Sixty-three participants each learned eight auditory-icon/denotative-referent pairings and attempted to recall them 4 weeks later. Three icon/denotative-referent association types (direct, related, and unrelated) were employed. Participants rated the strength of the association for each pairing on a 7-point scale. RESULTS: The number of errors made while learning pairings was greater for unrelated than for either related or direct associations, whereas the number of errors made while attempting to recall pairings 4 weeks later was greater for unrelated than for related associations and for related than for direct associations. Irrespective of association type, both learning and retention performance remained at very high levels, provided the strength of the association was rated greater than 5. CONCLUSION: This suggests that strong preexisting associations are used to facilitate learning and retention of icon/denotative-referent pairings. APPLICATION: The practical implication of this study is that auditory icons having either direct or strong, indirect associations with warning events should be preferred.     

Predicting function from structure: examples of the serine protease inhibitor canonical loop conformation found in extracellular proteins.

The prediction of protein function from structure is becoming of growing importance in the age of structural genomics. We have focused on the problem of identifying sites of potential serine protease inhibitor interactions on the surface of proteins of known structure. Given that there is no sequence conservation within canonical loops from different inhibitor families we first compare representative loops to all fragments of equal length among proteins of known structure by calculating main-chain RMS deviation. Fragments with RMS deviation below a certain threshold (hits) are removed if residues have solvent accessibilities appreciably lower than those observed in the search structure. These remaining hits are further filtered to remove those occurring largely within secondary structure elements. Likely functional significance is restricted further by considering only extracellular protein domains. Also a test is performed to see if the loop can dock into the binding site of the serine protease trypsin without unacceptable steric clashes. By comparing different canonical loop structures to the protein structure database we show that the method was able to detect previously known inhibitors. In addition, we discuss potentially new canonical loop structures found in secreted hydrolases, toxins, viral proteins, cytokines and other proteins. We discuss the possible functional significance of several of the examples found.     

Managing acute care

In the last few years, much medical-facility construction has been driven by what insurers want. Hospitals have built facilities for well-reimbursed procedures and closed money-losing ones. Health-maintenance organizations increasingly expect to hold down costs by making prepayment arrangements with doctors and their hospitals. President Clinton has pledged early action on health-care reform, which will likely change planners' priorities. Whether the nation goes to Clintonian "managed competition" or a Canadian-style nationwide single-payer system (the two most likely options), the projects on these pages reflect two large-scale trends that are likely to continue: the movement of more procedures from inpatient to outpatient facilities and the separation of treatment functions from ordinary office and administrative tasks so that the latter are not performed in the same high-cost buildings as technology-intensive procedures. Various schemes that make care more "patient-centered" have been tried and been shown to speed healing, even for outpatients, but such hard-to-quantify issues get short shrift in an era of knee-jerk cost containment. The challenge in tomorrow's healthcare universe--whatever it becomes--will be to keep these issues on the table.     

Early assessment of diaphragmatic dysfunction in children in the ITU: chest radiology and phrenic nerve stimulation

Diaphragmatic dysfunction is a common postoperative complication of cardiac surgery in children, with important effects on respiratory morbidity. Its early diagnosis, followed by prompt surgical intervention, has been shown to reduce morbidity. However, the commonest method of diagnosis, based on hemi-diaphragmatic elevation on the chest radiograph, may be less accurate than direct techniques for assessing phrenic nerve function. We have compared electrophysiological and radiological diagnoses of diaphragmatic abnormality in 100 children (aged 3 days to 17.5 yrs) undergoing cardiac surgery, looking at respiratory morbidity as assessed by the duration of ventilation, the time spent on the cardiac intensive care unit (CICU), and the requirement for reintubation. Despite showing good reproducibility, radiological diagnosis was neither sensitive nor specific in identifying patients with electrophysiological phrenic nerve damage. Analysis of the measures of outcome supported the electrophysiological technique. Patients with electrophysiological evidence of damage had a longer duration of ventilation, spent longer on the CICU, and had a greater incidence of reintubation than either radiologically abnormal or "normal" patients. Chest X-rays are not a good method for diagnosing phrenic nerve damage in the early postoperative period in children. If early diagnosis is needed, then direct assessment of phrenic nerve function, such as the measurement of phrenic latency, may be a better technique.     

Avoidance of bird repellents by mice (Mus musculus)

It is believed that mammalian chemosensory irritants are not aversive to birds and vice versa. Nevertheless, few avian repellents have been tested against mammals. For that reason, we evaluated the efficacy of 1.0% w/v methyl anthranilate, orthoaminoacetophenone, 2-amino-4,5-methoxyacetophenone, 2-methoxyacetophenone, and veratryl amine as mouse repellents in 3-hr no-choice drinking tests. Relative to ingestion of plain water, all test substances significantly reduced (P < 0.05) intake. Orthoaminoaceto-phenone was the most effective repellent, with intake reduced to levels statistically indistinguishable from zero.