A detailed comparison of optimality and simplicity in perceptual decision-making
Shen, Shan; Ma, Wei Ji
2017-01-01
Two prominent ideas in the study of decision-making have been that organisms behave near-optimally, and that they use simple heuristic rules. These principles might be operating in different types of tasks, but this possibility cannot be fully investigated without a direct, rigorous comparison within a single task. Such a comparison was lacking in most previous studies, because a) the optimal decision rule was simple; b) no simple suboptimal rules were considered; c) it was unclear what was optimal, or d) a simple rule could closely approximate the optimal rule. Here, we used a perceptual decision-making task in which the optimal decision rule is well-defined and complex, and makes qualitatively distinct predictions from many simple suboptimal rules. We find that all simple rules tested fail to describe human behavior, that the optimal rule accounts well for the data, and that several complex suboptimal rules are indistinguishable from the optimal one. Moreover, we found evidence that the optimal model is close to the true model: first, the better the trial-to-trial predictions of a suboptimal model agree with those of the optimal model, the better that suboptimal model fits; second, our estimate of the Kullback-Leibler divergence between the optimal model and the true model is not significantly different from zero. When observers receive no feedback, the optimal model still describes behavior best, suggesting that sensory uncertainty is implicitly represented and taken into account. Beyond the task and models studied here, our results have implications for best practices of model comparison. PMID:27177259
A simple threshold rule is sufficient to explain sophisticated collective decision-making.
Robinson, Elva J H; Franks, Nigel R; Ellis, Samuel; Okuda, Saki; Marshall, James A R
2011-01-01
Decision-making animals can use slow-but-accurate strategies, such as making multiple comparisons, or opt for simpler, faster strategies to find a 'good enough' option. Social animals make collective decisions about many group behaviours including foraging and migration. The key to the collective choice lies with individual behaviour. We present a case study of a collective decision-making process (house-hunting ants, Temnothorax albipennis), in which a previously proposed decision strategy involved both quality-dependent hesitancy and direct comparisons of nests by scouts. An alternative possible decision strategy is that scouting ants use a very simple quality-dependent threshold rule to decide whether to recruit nest-mates to a new site or search for alternatives. We use analytical and simulation modelling to demonstrate that this simple rule is sufficient to explain empirical patterns from three studies of collective decision-making in ants, and can account parsimoniously for apparent comparison by individuals and apparent hesitancy (recruitment latency) effects, when available nests differ strongly in quality. This highlights the need to carefully design experiments to detect individual comparison. We present empirical data strongly suggesting that best-of-n comparison is not used by individual ants, although individual sequential comparisons are not ruled out. However, by using a simple threshold rule, decision-making groups are able to effectively compare options, without relying on any form of direct comparison of alternatives by individuals. This parsimonious mechanism could promote collective rationality in group decision-making.
Bayesian design of decision rules for failure detection
NASA Technical Reports Server (NTRS)
Chow, E. Y.; Willsky, A. S.
1984-01-01
The formulation of the decision making process of a failure detection algorithm as a Bayes sequential decision problem provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Bayesian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is potentially a useful one.
An automated approach to the design of decision tree classifiers
NASA Technical Reports Server (NTRS)
Argentiero, P.; Chin, R.; Beaudet, P.
1982-01-01
An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.
NASA Astrophysics Data System (ADS)
Gehrmann, Andreas; Nagai, Yoshimitsu; Yoshida, Osamu; Ishizu, Syohei
Since management decision-making becomes complex and preferences of the decision-maker frequently becomes inconsistent, multi-attribute decision-making problems were studied. To represent inconsistent preference relation, the concept of evaluation structure was introduced. We can generate simple rules to represent inconsistent preference relation by the evaluation structures. Further rough set theory for the preference relation was studied and the concept of approximation was introduced. One of our main aims of this paper is to introduce a concept of rough evaluation structure for representing inconsistent preference relation. We apply rough set theory to the evaluation structure, and develop a method for generating simple rules for inconsistent preference relations. In this paper, we introduce concepts of totally ordered information system, similarity class of preference relation, upper and lower approximation of preference relations. We also show the properties of rough evaluation structure and provide a simple example. As an application of rough evaluation structure, we analyze questionnaire survey of customer preferences about audio players.
A study of some nine-element decision rules. [for multispectral recognition of remote sensing
NASA Technical Reports Server (NTRS)
Richardson, W.
1974-01-01
A nine-element rule is one that makes a classification decision for each pixel based on data from that pixel and its eight immediate neighbors. Three such rules, all fast and simple to use, are defined and tested. All performed substantially better on field interiors than the best one-point rule. Qualitative results indicate that fine detail and contradictory testimony tend to be overlooked by the rules.
Perry, Jeffrey J; Stiell, Ian G
2006-12-01
Traumatic injuries to the ankle/foot, knee, cervical spine, and head are very commonly seen in emergency and accident departments around the world. There has been much interest in the development of clinical decision rules to help guide the investigations of these patients in a standardised and cost-effective manner. In this article we reviewed the impact of the Ottawa ankle rules, Ottawa knee rules, Canadian C-spine rule and the Canadian CT head rule. The studies conducted have confirmed that the use of well developed clinical decision rules results in less radiography, less time spent in the emergency department and does not decrease patient satisfaction or result in misdiagnosis. Emergency physicians around the world should adopt the use of clinical decision rules for ankle/foot, knee, cervical spine and minor head injuries. With relatively simple implementation strategies, care can be standardized and costs reduced while providing excellent clinical care.
Working dogs cooperate among one another by generalised reciprocity.
Gfrerer, Nastassja; Taborsky, Michael
2017-03-06
Cooperation by generalised reciprocity implies that individuals apply the decision rule "help anyone if helped by someone". This mechanism has been shown to generate evolutionarily stable levels of cooperation, but as yet it is unclear how widely this cooperation mechanism is applied among animals. Dogs (Canis familiaris) are highly social animals with considerable cognitive potential and the ability to differentiate between individual social partners. But although dogs can solve complex problems, they may use simple rules for behavioural decisions. Here we show that dogs trained in an instrumental cooperative task to provide food to a social partner help conspecifics more often after receiving help from a dog before. Remarkably, in so doing they show no distinction between partners that had helped them before and completely unfamiliar conspecifics. Apparently, dogs use the simple decision rule characterizing generalised reciprocity, although they are probably capable of using the more complex decision rule of direct reciprocity: "help someone who has helped you". However, generalized reciprocity involves lower information processing costs and is therefore a cheaper cooperation strategy. Our results imply that generalised reciprocity might be applied more commonly than direct reciprocity also in other mutually cooperating animals.
Working dogs cooperate among one another by generalised reciprocity
Gfrerer, Nastassja; Taborsky, Michael
2017-01-01
Cooperation by generalised reciprocity implies that individuals apply the decision rule “help anyone if helped by someone”. This mechanism has been shown to generate evolutionarily stable levels of cooperation, but as yet it is unclear how widely this cooperation mechanism is applied among animals. Dogs (Canis familiaris) are highly social animals with considerable cognitive potential and the ability to differentiate between individual social partners. But although dogs can solve complex problems, they may use simple rules for behavioural decisions. Here we show that dogs trained in an instrumental cooperative task to provide food to a social partner help conspecifics more often after receiving help from a dog before. Remarkably, in so doing they show no distinction between partners that had helped them before and completely unfamiliar conspecifics. Apparently, dogs use the simple decision rule characterizing generalised reciprocity, although they are probably capable of using the more complex decision rule of direct reciprocity: “help someone who has helped you”. However, generalized reciprocity involves lower information processing costs and is therefore a cheaper cooperation strategy. Our results imply that generalised reciprocity might be applied more commonly than direct reciprocity also in other mutually cooperating animals. PMID:28262722
Zhang, Wenyu; Zhang, Zhenjiang
2015-01-01
Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399
Making sense of information in noisy networks: human communication, gossip, and distortion.
Laidre, Mark E; Lamb, Alex; Shultz, Susanne; Olsen, Megan
2013-01-21
Information from others can be unreliable. Humans nevertheless act on such information, including gossip, to make various social calculations, thus raising the question of whether individuals can sort through social information to identify what is, in fact, true. Inspired by empirical literature on people's decision-making when considering gossip, we built an agent-based simulation model to examine how well simple decision rules could make sense of information as it propagated through a network. Our simulations revealed that a minimalistic decision-rule 'Bit-wise mode' - which compared information from multiple sources and then sought a consensus majority for each component bit within the message - was consistently the most successful at converging upon the truth. This decision rule attained high relative fitness even in maximally noisy networks, composed entirely of nodes that distorted the message. The rule was also superior to other decision rules regardless of its frequency in the population. Simulations carried out with variable agent memory constraints, different numbers of observers who initiated information propagation, and a variety of network types suggested that the single most important factor in making sense of information was the number of independent sources that agents could consult. Broadly, our model suggests that despite the distortion information is subject to in the real world, it is nevertheless possible to make sense of it based on simple Darwinian computations that integrate multiple sources. Copyright © 2012 Elsevier Ltd. All rights reserved.
Simple heuristics and rules of thumb: where psychologists and behavioural biologists might meet.
Hutchinson, John M C; Gigerenzer, Gerd
2005-05-31
The Centre for Adaptive Behaviour and Cognition (ABC) has hypothesised that much human decision-making can be described by simple algorithmic process models (heuristics). This paper explains this approach and relates it to research in biology on rules of thumb, which we also review. As an example of a simple heuristic, consider the lexicographic strategy of Take The Best for choosing between two alternatives: cues are searched in turn until one discriminates, then search stops and all other cues are ignored. Heuristics consist of building blocks, and building blocks exploit evolved or learned abilities such as recognition memory; it is the complexity of these abilities that allows the heuristics to be simple. Simple heuristics have an advantage in making decisions fast and with little information, and in avoiding overfitting. Furthermore, humans are observed to use simple heuristics. Simulations show that the statistical structures of different environments affect which heuristics perform better, a relationship referred to as ecological rationality. We contrast ecological rationality with the stronger claim of adaptation. Rules of thumb from biology provide clearer examples of adaptation because animals can be studied in the environments in which they evolved. The range of examples is also much more diverse. To investigate them, biologists have sometimes used similar simulation techniques to ABC, but many examples depend on empirically driven approaches. ABC's theoretical framework can be useful in connecting some of these examples, particularly the scattered literature on how information from different cues is integrated. Optimality modelling is usually used to explain less detailed aspects of behaviour but might more often be redirected to investigate rules of thumb.
Interpretable Decision Sets: A Joint Framework for Description and Prediction
Lakkaraju, Himabindu; Bach, Stephen H.; Jure, Leskovec
2016-01-01
One of the most important obstacles to deploying predictive models is the fact that humans do not understand and trust them. Knowing which variables are important in a model’s prediction and how they are combined can be very powerful in helping people understand and trust automatic decision making systems. Here we propose interpretable decision sets, a framework for building predictive models that are highly accurate, yet also highly interpretable. Decision sets are sets of independent if-then rules. Because each rule can be applied independently, decision sets are simple, concise, and easily interpretable. We formalize decision set learning through an objective function that simultaneously optimizes accuracy and interpretability of the rules. In particular, our approach learns short, accurate, and non-overlapping rules that cover the whole feature space and pay attention to small but important classes. Moreover, we prove that our objective is a non-monotone submodular function, which we efficiently optimize to find a near-optimal set of rules. Experiments show that interpretable decision sets are as accurate at classification as state-of-the-art machine learning techniques. They are also three times smaller on average than rule-based models learned by other methods. Finally, results of a user study show that people are able to answer multiple-choice questions about the decision boundaries of interpretable decision sets and write descriptions of classes based on them faster and more accurately than with other rule-based models that were designed for interpretability. Overall, our framework provides a new approach to interpretable machine learning that balances accuracy, interpretability, and computational efficiency. PMID:27853627
A programmable rules engine to provide clinical decision support using HTML forms.
Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R
1999-01-01
The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.
Heuristics: foundations for a novel approach to medical decision making.
Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V
2015-03-01
Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.
Edwards, W; Fasolo, B
2001-01-01
This review is about decision technology-the rules and tools that help us make wiser decisions. First, we review the three rules that are at the heart of most traditional decision technology-multi-attribute utility, Bayes' theorem, and subjective expected utility maximization. Since the inception of decision research, these rules have prescribed how we should infer values and probabilities and how we should combine them to make better decisions. We suggest how to make best use of all three rules in a comprehensive 19-step model. The remainder of the review explores recently developed tools of decision technology. It examines the characteristics and problems of decision-facilitating sites on the World Wide Web. Such sites now provide anyone who can use a personal computer with access to very sophisticated decision-aiding tools structured mainly to facilitate consumer decision making. It seems likely that the Web will be the mode by means of which decision tools will be distributed to lay users. But methods for doing such apparently simple things as winnowing 3000 options down to a more reasonable number, like 10, contain traps for unwary decision technologists. The review briefly examines Bayes nets and influence diagrams-judgment and decision-making tools that are available as computer programs. It very briefly summarizes the state of the art of eliciting probabilities from experts. It concludes that decision tools will be as important in the 21st century as spreadsheets were in the 20th.
Connecting clinical and actuarial prediction with rule-based methods.
Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H
2015-06-01
Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).
A programmable rules engine to provide clinical decision support using HTML forms.
Heusinkveld, J.; Geissbuhler, A.; Sheshelidze, D.; Miller, R.
1999-01-01
The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser. Images Figure 1 PMID:10566470
Mock jury trials in Taiwan--paving the ground for introducing lay participation.
Huang, Kuo-Chang; Lin, Chang-Ching
2014-08-01
The first mock jury study in Taiwan, in which 279 community members watched a videotaped trial, investigated how jurors' estimates of the relative undesirability of wrongful conviction versus wrongful acquittal predicted individual decisions and how decision rules affected outcomes. The percentage of jurors who viewed wrongful conviction as more undesirable increased from 50.9% to 60.9% after deliberation and jurors' postdeliberation acquittal rate (71.7%) was higher than predeliberation acquittal rate (58.8%). Jurors' estimates of the undesirability of wrongful conviction were not correlated with their predeliberation votes but became positively correlated with their postdeliberation decisions. The unanimous rule facilitated jurors' change of vote, predominantly from conviction to acquittal, than the simple majority rule. Jurors reaching a verdict under the unanimous rule viewed deliberation and the verdict more positively. This study indicates that deliberation can ameliorate the problem of most Taiwanese citizens not viewing wrongful conviction as more undesirable than wrongful acquittal. It also suggests that Taiwan should adopt a unanimous rule for its proposed lay participation system.
Rational Choice and the Framing of Decisions.
1986-05-29
decision under risk is the deriva- .- tion of the expected utility rule from simple principles of rational choice that make no . reference to long-run...corrective power of incentives depends on the nature of the particular error and cannot be taken for granted. The assumption of rationality of decision making ...easily eliminated by experience must be demonstrated. Finally, it is sometimes argued that failures of rationality in individual decision making are
Is expected utility theory normative for medical decision making?
Cohen, B J
1996-01-01
Expected utility theory is felt by its proponents to be a normative theory of decision making under uncertainty. The theory starts with some simple axioms that are held to be rules that any rational person would follow. It can be shown that if one adheres to these axioms, a numerical quantity, generally referred to as utility, can be assigned to each possible outcome, with the preferred course of action being that which has the highest expected utility. One of these axioms, the independence principle, is controversial, and is frequently violated in experimental situations. Proponents of the theory hold that these violations are irrational. The independence principle is simply an axiom dictating consistency among preferences, in that it dictates that a rational agent should hold a specified preference given another stated preference. When applied to preferences between lotteries, the independence principle can be demonstrated to be a rule that is followed only when preferences are formed in a particular way. The logic of expected utility theory is that this demonstration proves that preferences should be formed in this way. An alternative interpretation is that this demonstrates that the independence principle is not a valid general rule of consistency, but in particular, is a rule that must be followed if one is to consistently apply the decision rule "choose the lottery that has the highest expected utility." This decision rule must be justified on its own terms as a valid rule of rationality by demonstration that violation would lead to decisions that conflict with the decision maker's goals. This rule does not appear to be suitable for medical decisions because often these are one-time decisions in which expectation, a long-run property of a random variable, would not seem to be applicable. This is particularly true for those decisions involving a non-trivial risk of death.
Simple heuristics in over-the-counter drug choices: a new hint for medical education and practice.
Riva, Silvia; Monti, Marco; Antonietti, Alessandro
2011-01-01
Over-the-counter (OTC) drugs are widely available and often purchased by consumers without advice from a health care provider. Many people rely on self-management of medications to treat common medical conditions. Although OTC medications are regulated by the National and the International Health and Drug Administration, many people are unaware of proper dosing, side effects, adverse drug reactions, and possible medication interactions. This study examined how subjects make their decisions to select an OTC drug, evaluating the role of cognitive heuristics which are simple and adaptive rules that help the decision-making process of people in everyday contexts. By analyzing 70 subjects' information-search and decision-making behavior when selecting OTC drugs, we examined the heuristics they applied in order to assess whether simple decision-making processes were also accurate and relevant. Subjects were tested with a sequence of two experimental tests based on a computerized Java system devised to analyze participants' choices in a virtual environment. We found that subjects' information-search behavior reflected the use of fast and frugal heuristics. In addition, although the heuristics which correctly predicted subjects' decisions implied significantly fewer cues on average than the subjects did in the information-search task, they were accurate in describing order of information search. A simple combination of a fast and frugal tree and a tallying rule predicted more than 78% of subjects' decisions. The current emphasis in health care is to shift some responsibility onto the consumer through expansion of self medication. To know which cognitive mechanisms are behind the choice of OTC drugs is becoming a relevant purpose of current medical education. These findings have implications both for the validity of simple heuristics describing information searches in the field of OTC drug choices and for current medical education, which has to prepare competent health specialists to orientate and support the choices of their patients.
Simple heuristics in over-the-counter drug choices: a new hint for medical education and practice
Riva, Silvia; Monti, Marco; Antonietti, Alessandro
2011-01-01
Introduction Over-the-counter (OTC) drugs are widely available and often purchased by consumers without advice from a health care provider. Many people rely on self-management of medications to treat common medical conditions. Although OTC medications are regulated by the National and the International Health and Drug Administration, many people are unaware of proper dosing, side effects, adverse drug reactions, and possible medication interactions. Purpose This study examined how subjects make their decisions to select an OTC drug, evaluating the role of cognitive heuristics which are simple and adaptive rules that help the decision-making process of people in everyday contexts. Subjects and methods By analyzing 70 subjects’ information-search and decision-making behavior when selecting OTC drugs, we examined the heuristics they applied in order to assess whether simple decision-making processes were also accurate and relevant. Subjects were tested with a sequence of two experimental tests based on a computerized Java system devised to analyze participants’ choices in a virtual environment. Results We found that subjects’ information-search behavior reflected the use of fast and frugal heuristics. In addition, although the heuristics which correctly predicted subjects’ decisions implied significantly fewer cues on average than the subjects did in the information-search task, they were accurate in describing order of information search. A simple combination of a fast and frugal tree and a tallying rule predicted more than 78% of subjects’ decisions. Conclusion The current emphasis in health care is to shift some responsibility onto the consumer through expansion of self medication. To know which cognitive mechanisms are behind the choice of OTC drugs is becoming a relevant purpose of current medical education. These findings have implications both for the validity of simple heuristics describing information searches in the field of OTC drug choices and for current medical education, which has to prepare competent health specialists to orientate and support the choices of their patients. PMID:23745077
A Taxonomy of Network Centric Warfare Architectures
2008-01-01
mound structure emerges as a result of the termites following very simple rules, and exchanging very simple pheromone signals (Solé & Goodwin 2000...only fairly simple decisions.” For example, in far northern Australia, “magnetic termites ” build large termite mounds which are oriented north-south...and contain a complex ventilation system which controls temperature, humidity, and oxygen levels. But termite brains are too small to store a plan
Mapping Network Centric Operational Architectures to C2 and Software Architectures
2007-06-01
Instead, the termite mound structure emerges as a result of the termites following very simple rules, and exchanging very simple pheromone signals...Each worker need make only fairly simple decisions.” For example, in far northern Australia, “magnetic termites ” build large termite mounds which are...oriented north-south and contain a complex ventilation system which controls temperature, humidity, and oxygen levels. But termite brains are too
Comparative study of multimodal biometric recognition by fusion of iris and fingerprint.
Benaliouche, Houda; Touahria, Mohamed
2014-01-01
This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.
Comparative Study of Multimodal Biometric Recognition by Fusion of Iris and Fingerprint
Benaliouche, Houda; Touahria, Mohamed
2014-01-01
This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results. PMID:24605065
Less can be more: How to make operations more flexible and robust with fewer resources
NASA Astrophysics Data System (ADS)
Haksöz, ćaǧrı; Katsikopoulos, Konstantinos; Gigerenzer, Gerd
2018-06-01
We review empirical evidence from practice and general theoretical conditions, under which simple rules of thumb can help to make operations flexible and robust. An operation is flexible when it responds adaptively to adverse events such as natural disasters; an operation is robust when it is less affected by adverse events in the first place. We illustrate the relationship between flexibility and robustness in the context of supply chain risk. In addition to increasing flexibility and robustness, simple rules simultaneously reduce the need for resources such as time, money, information, and computation. We illustrate the simple-rules approach with an easy-to-use graphical aid for diagnosing and managing supply chain risk. More generally, we recommend a four-step process for determining the amount of resources that decision makers should invest in so as to increase flexibility and robustness.
Collaborative Brain-Computer Interface for Aiding Decision-Making
Poli, Riccardo; Valeriani, Davide; Cinel, Caterina
2014-01-01
We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making. PMID:25072739
Does the cost function matter in Bayes decision rule?
Schlü ter, Ralf; Nussbaum-Thom, Markus; Ney, Hermann
2012-02-01
In many tasks in pattern recognition, such as automatic speech recognition (ASR), optical character recognition (OCR), part-of-speech (POS) tagging, and other string recognition tasks, we are faced with a well-known inconsistency: The Bayes decision rule is usually used to minimize string (symbol sequence) error, whereas, in practice, we want to minimize symbol (word, character, tag, etc.) error. When comparing different recognition systems, we do indeed use symbol error rate as an evaluation measure. The topic of this work is to analyze the relation between string (i.e., 0-1) and symbol error (i.e., metric, integer valued) cost functions in the Bayes decision rule, for which fundamental analytic results are derived. Simple conditions are derived for which the Bayes decision rule with integer-valued metric cost function and with 0-1 cost gives the same decisions or leads to classes with limited cost. The corresponding conditions can be tested with complexity linear in the number of classes. The results obtained do not make any assumption w.r.t. the structure of the underlying distributions or the classification problem. Nevertheless, the general analytic results are analyzed via simulations of string recognition problems with Levenshtein (edit) distance cost function. The results support earlier findings that considerable improvements are to be expected when initial error rates are high.
Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence.
Naso, David; Turchiano, Biagio
2005-04-01
In many manufacturing environments, automated guided vehicles are used to move the processed materials between various pickup and delivery points. The assignment of vehicles to unit loads is a complex problem that is often solved in real-time with simple dispatching rules. This paper proposes an automated guided vehicles dispatching approach based on computational intelligence. We adopt a fuzzy multicriteria decision strategy to simultaneously take into account multiple aspects in every dispatching decision. Since the typical short-term view of dispatching rules is one of the main limitations of such real-time assignment heuristics, we also incorporate in the multicriteria algorithm a specific heuristic rule that takes into account the empty-vehicle travel on a longer time-horizon. Moreover, we also adopt a genetic algorithm to tune the weights associated to each decision criteria in the global decision algorithm. The proposed approach is validated by means of a comparison with other dispatching rules, and with other recently proposed multicriteria dispatching strategies also based on computational Intelligence. The analysis of the results obtained by the proposed dispatching approach in both nominal and perturbed operating conditions (congestions, faults) confirms its effectiveness.
Toward sensor-based context aware systems.
Sakurai, Yoshitaka; Takada, Kouhei; Anisetti, Marco; Bellandi, Valerio; Ceravolo, Paolo; Damiani, Ernesto; Tsuruta, Setsuo
2012-01-01
This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and level of uncertainty. Then, the appropriate context is selected. Reconciliation of different uncertainty types is achieved by a simple technique that moves uncertainty from events to business rules by generating combs of standard Boolean predicates. Finally, context rules are evaluated together with the events to take a decision. The feasibility of our idea is demonstrated via a case study where a context-reasoning engine has been connected to simulated heartbeat sensors using prerecorded experimental data. We use sensor outputs to identify the proper context of operation of a system and trigger decision-making based on context information.
Précis of Simple heuristics that make us smart.
Todd, P M; Gigerenzer, G
2000-10-01
How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we explore fast and frugal heuristics--simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data--that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program.
Simply criminal: predicting burglars' occupancy decisions with a simple heuristic.
Snook, Brent; Dhami, Mandeep K; Kavanagh, Jennifer M
2011-08-01
Rational choice theories of criminal decision making assume that offenders weight and integrate multiple cues when making decisions (i.e., are compensatory). We tested this assumption by comparing how well a compensatory strategy called Franklin's Rule captured burglars' decision policies regarding residence occupancy compared to a non-compensatory strategy (i.e., Matching Heuristic). Forty burglars each decided on the occupancy of 20 randomly selected photographs of residences (for which actual occupancy was known when the photo was taken). Participants also provided open-ended reports on the cues that influenced their decisions in each case, and then rated the importance of eight cues (e.g., deadbolt visible) over all decisions. Burglars predicted occupancy beyond chance levels. The Matching Heuristic was a significantly better predictor of burglars' decisions than Franklin's Rule, and cue use in the Matching Heuristic better corresponded to the cue ecological validities in the environment than cue use in Franklin's Rule. The most important cue in burglars' models was also the most ecologically valid or predictive of actual occupancy (i.e., vehicle present). The majority of burglars correctly identified the most important cue in their models, and the open-ended technique showed greater correspondence between self-reported and captured cue use than the rating over decision technique. Our findings support a limited rationality perspective to understanding criminal decision making, and have implications for crime prevention.
Goal-Directed Decision Making with Spiking Neurons.
Friedrich, Johannes; Lengyel, Máté
2016-02-03
Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. Copyright © 2016 the authors 0270-6474/16/361529-18$15.00/0.
Goal-Directed Decision Making with Spiking Neurons
Lengyel, Máté
2016-01-01
Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. SIGNIFICANCE STATEMENT Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. PMID:26843636
Cost-effectiveness on a local level: whether and when to adopt a new technology.
Woertman, Willem H; Van De Wetering, Gijs; Adang, Eddy M M
2014-04-01
Cost-effectiveness analysis has become a widely accepted tool for decision making in health care. The standard textbook cost-effectiveness analysis focuses on whether to make the switch from an old or common practice technology to an innovative technology, and in doing so, it takes a global perspective. In this article, we are interested in a local perspective, and we look at the questions of whether and when the switch from old to new should be made. A new approach to cost-effectiveness from a local (e.g., a hospital) perspective, by means of a mathematical model for cost-effectiveness that explicitly incorporates time, is proposed. A decision rule is derived for establishing whether a new technology should be adopted, as well as a general rule for establishing when it pays to postpone adoption by 1 more period, and a set of decision rules that can be used to determine the optimal timing of adoption. Finally, a simple example is presented to illustrate our model and how it leads to optimal decision making in a number of cases.
Clinical decision rules for termination of resuscitation in out-of-hospital cardiac arrest.
Sherbino, Jonathan; Keim, Samuel M; Davis, Daniel P
2010-01-01
Out-of-hospital cardiac arrest (OHCA) has a low probability of survival to hospital discharge. Four clinical decision rules (CDRs) have been validated to identify patients with no probability of survival. Three of these rules focus on exclusive prehospital basic life support care for OHCA, and two of these rules focus on prehospital advanced life support care for OHCA. Can a CDR for the termination of resuscitation identify a patient with no probability of survival in the setting of OHCA? Six validation studies were selected from a PubMed search. A structured review of each of the studies is presented. In OHCA receiving basic life support care, the BLS-TOR (basic life support termination of resuscitation) rule has a positive predictive value for death of 99.5% (95% confidence interval 98.9-99.8%), and decreases the transportation of all patients by 62.6%. This rule has been appropriately validated for widespread use. In OHCA receiving advanced life support care, no current rule has been appropriately validated for widespread use. The BLS-TOR rule is a simple rule that identifies patients who will not survive OHCA. Further research is required to identify similarly robust CDRs for patients receiving advanced life support care in the setting of OHCA. Copyright 2010 Elsevier Inc. All rights reserved.
Why Rules Matter in Complex Event Processing...and Vice Versa
NASA Astrophysics Data System (ADS)
Vincent, Paul
Many commercial and research CEP solutions are moving beyond simple stream query languages to more complete definitions of "process" and thence to "decisions" and "actions". And as capabilities increase in event processing capabilities, there is an increasing realization that the humble "rule" is as relevant to the event cloud as it is to specific services. Less obvious is how much event processing has to offer the process and rule execution and management technologies. Does event processing change the way we should manage businesses, processes and services, together with their embedded (and hopefully managed) rulesets?
Wallace, Lorraine Silver; Ballard, Joyce E.; Holiday, David; Turner, Lori W.; Keenum, Amy J.; Pearman, Cynthia M.
2004-01-01
OBJECTIVE: While African-American women tend to have greater bone mineral density (BMD) than caucasian women, they are still at risk of developing osteoporosis later in life. Clinical decision rules (i.e., algorithms) have been developed to assist clinicians identify women at greatest risk of low BMD. However, such tools have only been validated in caucasian and Asian populations. Accordingly, the objective of this study was to compare the performance of five clinical decision rules in identifying postmenopausal African-American women at greatest risk for low femoral BMD. METHODOLOGY: One hundred-seventy-four (n=174) postmenopausal African-American women completed a valid and reliable oral questionnaire to assess lifestyle characteristics, and completed height and weight measures. BMD at the femoral neck was measured via dual energy x-ray absorptiometry (DXA). We calculated sensitivity, specificity, positive predictive value, and negative predictive value for identifying African-American women with low BMD (T-Score < or = -2.0 SD) using five clinical decision rules: Age, Body Size, No Estrogen (ABONE), Osteoporosis Risk Assessment Instrument (ORAI), Osteoporosis Self-Assessment Tool (OST), Simple Calculated Osteoporosis Risk Estimation (SCORE), and body weight less than 70 kg. RESULTS: Approximately 30% of African-American women had low BMD, half of whom had osteoporosis (BMD T-Score < or = -2.5 SD). Sensitivity for identifying women with a low BMD (T-Score < or = -2.0 SD) ranged from 65.57-83.61%, while specificity ranged from 53.85-78.85%. Positive predictive values ranged from 80.95-87.91%, while negative predictive values ranged from 48.44-58.33%. CONCLUSION: Our data suggest that the clinical decision rules analyzed in this study have some usefulness for identifying postmenopausal African-American women with low BMD. However, there is a need to establish cut-points for these clinical decision rules in a larger, more diverse sample of African-American women. PMID:15040510
A novel methodology for building robust design rules by using design based metrology (DBM)
NASA Astrophysics Data System (ADS)
Lee, Myeongdong; Choi, Seiryung; Choi, Jinwoo; Kim, Jeahyun; Sung, Hyunju; Yeo, Hyunyoung; Shim, Myoungseob; Jin, Gyoyoung; Chung, Eunseung; Roh, Yonghan
2013-03-01
This paper addresses a methodology for building robust design rules by using design based metrology (DBM). Conventional method for building design rules has been using a simulation tool and a simple pattern spider mask. At the early stage of the device, the estimation of simulation tool is poor. And the evaluation of the simple pattern spider mask is rather subjective because it depends on the experiential judgment of an engineer. In this work, we designed a huge number of pattern situations including various 1D and 2D design structures. In order to overcome the difficulties of inspecting many types of patterns, we introduced Design Based Metrology (DBM) of Nano Geometry Research, Inc. And those mass patterns could be inspected at a fast speed with DBM. We also carried out quantitative analysis on PWQ silicon data to estimate process variability. Our methodology demonstrates high speed and accuracy for building design rules. All of test patterns were inspected within a few hours. Mass silicon data were handled with not personal decision but statistical processing. From the results, robust design rules are successfully verified and extracted. Finally we found out that our methodology is appropriate for building robust design rules.
Implementing a Commercial Rule Base as a Medication Order Safety Net
Reichley, Richard M.; Seaton, Terry L.; Resetar, Ervina; Micek, Scott T.; Scott, Karen L.; Fraser, Victoria J.; Dunagan, W. Claiborne; Bailey, Thomas C.
2005-01-01
A commercial rule base (Cerner Multum) was used to identify medication orders exceeding recommended dosage limits at five hospitals within BJC HealthCare, an integrated health care system. During initial testing, clinical pharmacists determined that there was an excessive number of nuisance and clinically insignificant alerts, with an overall alert rate of 9.2%. A method for customizing the commercial rule base was implemented to increase rule specificity for problematic rules. The system was subsequently deployed at two facilities and achieved alert rates of less than 1%. Pharmacists screened these alerts and contacted ordering physicians in 21% of cases. Physicians made therapeutic changes in response to 38% of alerts presented to them. By applying simple techniques to customize rules, commercial rule bases can be used to rapidly deploy a safety net to screen drug orders for excessive dosages, while preserving the rule architecture for later implementations of more finely tuned clinical decision support. PMID:15802481
A simple randomisation procedure for validating discriminant analysis: a methodological note.
Wastell, D G
1987-04-01
Because the goal of discriminant analysis (DA) is to optimise classification, it designedly exaggerates between-group differences. This bias complicates validation of DA. Jack-knifing has been used for validation but is inappropriate when stepwise selection (SWDA) is employed. A simple randomisation test is presented which is shown to give correct decisions for SWDA. The general superiority of randomisation tests over orthodox significance tests is discussed. Current work on non-parametric methods of estimating the error rates of prediction rules is briefly reviewed.
Influence in Action in "Catch Me if You Can"
ERIC Educational Resources Information Center
Meyer, Gary; Roberto, Anthony J.
2005-01-01
For decades, scholars have worked to understand the precise manner in which messages affect attitudes and ultimately behaviors. The dominant paradigm suggests that there are two methods or routes to attitude change, one based on careful consideration of the messages and the other based on simple decision rules, often referred to as heuristics…
Syed, Shahbaz; Gatien, Mathieu; Perry, Jeffrey J.; Chaudry, Hina; Kim, Soo-Min; Kwong, Kenneth; Mukarram, Muhammad; Thiruganasambandamoorthy, Venkatesh
2017-01-01
BACKGROUND: Most patients with chest pain in the emergency department are assigned to cardiac monitoring for several hours, blocking access for patients in greater need. We sought to validate a previously derived decision rule for safe removal of patients from cardiac monitoring after initial evaluation in the emergency department. METHODS: We prospectively enrolled adults (age ≥ 18 yr) who presented with chest pain and were assigned to cardiac monitoring at 2 academic emergency departments over 18 months. We collected standardized baseline characteristics, findings from clinical evaluations and predictors for the Ottawa Chest Pain Cardiac Monitoring Rule: whether the patient is currently free of chest pain, and whether the electrocardiogram is normal or shows only nonspecific changes. The outcome was an arrhythmia requiring intervention in the emergency department or within 8 hours of presentation to the emergency department. We calculated diagnostic characteristics for the clinical prediction rule. RESULTS: We included 796 patients (mean age 63.8 yr, 55.8% male, 8.9% admitted to hospital). Fifteen patients (1.9%) had an arrhythmia, and the rule performed with the following characteristics: sensitivity 100% (95% confidence interval [CI] 78.2%–100%) and specificity 36.4% (95% CI 33.0%–39.6%). Application of the Ottawa Chest Pain Cardiac Monitoring Rule would have allowed 284 out of 796 patients (35.7%) to be safely removed from cardiac monitoring. INTERPRETATION: We successfully validated the decision rule for safe removal of a large subset of patients with chest pain from cardiac monitoring after initial evaluation in the emergency department. Implementation of this simple yet highly sensitive rule will allow for improved use of health care resources. PMID:28246315
Pathologic C-spine fracture with low risk mechanism and normal physical exam.
Hunter, Andrew; McGreevy, Jolion; Linden, Judith
2017-09-01
Cervical spinal fracture is a rare, but potentially disabling complication of trauma to the neck. Clinicians often rely on clinical decision rules and guidelines to decide whether or not imaging is necessary when a patient presents with neck pain. Validated clinical guidelines include the Canadian C-Spine Rule and the Nexus criteria. Studies suggest that the risks of a pathologic fracture from a simple rear end collision are negligible. We present a case of an individual who presented to an emergency department (ED) after a low speed motor vehicle collision complaining of lateral neck pain and had multiple subsequent visits for the same complaint with negative exam findings. Ultimately, he was found to have a severely pathologic cervical spine fracture with notable cord compression. Our objective is to discuss the necessity to incorporate clinical decision rules with physician gestalt and the need to take into account co-morbidities of a patient presenting after a minor MVC. Copyright © 2017 Elsevier Inc. All rights reserved.
Parodi, Stefano; Manneschi, Chiara; Verda, Damiano; Ferrari, Enrico; Muselli, Marco
2018-03-01
This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set of clinical variables and more than 54,000 gene features. Machine learning classifiers included three black-box algorithms ( k-nearest neighbour, Artificial Neural Network, and Support Vector Machine) and two methods based on intelligible rules (Decision Tree and the innovative Logic Learning Machine method). Support Vector Machine clearly outperformed any of the other methods. Among the two rule-based algorithms, Logic Learning Machine performed better and identified a set of simple intelligible rules based on a combination of clinical variables and gene expressions. Decision Tree identified a non-coding gene ( XIST) involved in the early phases of X chromosome inactivation that was overexpressed in females and in non-relapsed patients. XIST expression might be responsible for the better prognosis of female Hodgkin's lymphoma patients.
2012-01-01
Objectives This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. Methods A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. Results The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. Conclusions An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community. PMID:23346475
Not just for consumers: context effects are fundamental to decision making.
Trueblood, Jennifer S; Brown, Scott D; Heathcote, Andrew; Busemeyer, Jerome R
2013-06-01
Context effects--preference changes that depend on the availability of other options--have attracted a great deal of attention among consumer researchers studying high-level decision tasks. In the experiments reported here, we showed that these effects also arise in simple perceptual-decision-making tasks. This finding casts doubt on explanations limited to consumer choice and high-level decisions, and it indicates that context effects may be amenable to a general explanation at the level of the basic decision process. We demonstrated for the first time that three important context effects from the preferential-choice literature--similarity, attraction, and compromise effects--all occurred within a single perceptual-decision task. Not only do our results challenge previous explanations for context effects proposed by consumer researchers, but they also challenge the choice rules assumed in theories of perceptual decision making.
Housing decision making methods for initiation development phase process
NASA Astrophysics Data System (ADS)
Zainal, Rozlin; Kasim, Narimah; Sarpin, Norliana; Wee, Seow Ta; Shamsudin, Zarina
2017-10-01
Late delivery and sick housing project problems were attributed to poor decision making. These problems are the string of housing developer that prefers to create their own approach based on their experiences and expertise with the simplest approach by just applying the obtainable standards and rules in decision making. This paper seeks to identify the decision making methods for housing development at the initiation phase in Malaysia. The research involved Delphi method by using questionnaire survey which involved 50 numbers of developers as samples for the primary stage of collect data. However, only 34 developers contributed to the second stage of the information gathering process. At the last stage, only 12 developers were left for the final data collection process. Finding affirms that Malaysian developers prefer to make their investment decisions based on simple interpolation of historical data and using simple statistical or mathematical techniques in producing the required reports. It was suggested that they seemed to skip several important decision-making functions at the primary development stage. These shortcomings were mainly due to time and financial constraints and the lack of statistical or mathematical expertise among the professional and management groups in the developer organisations.
1981-03-01
paid from the date the Contracting Officer accepts the claim until payment thereof. Simple interest will be paid as computed at the rate established by...were of quantum (e.g., involved monetary decisions). If money is part of the decision, the Board will often rule in favor of one party based on the... quantum is in issue the exact amount had to be stated. This sum would then have to be certified if it exceeded $50,000. Althoug ’ the legislative
2013-01-01
Introduction One of the most important decisions that an animal has to make in its life is choosing a mate. Although most studies in sexual selection assume that mate choice is rational, this assumption has not been tested seriously. A crucial component of rationality is that animals exhibit transitive choices: if an individual prefers option A over B, and B over C, then it also prefers A over C. Results We assessed transitivity in mate choice: 40 female convict cichlids had to make a series of binary choices between males of varying size. Ninety percent of females showed transitive choices. The mean preference index was significantly higher when a female chose between their most preferred and least preferred male (male 1 vs. male 3) compared to when they chose between males of adjacent ranks (1 vs. 2 or 2 vs. 3). The results are consistent with a simple underlying preference function leading to transitive choice: females preferred males about one third larger than themselves. This rule of thumb correctly predicted which male was preferred in 67% of the cases and the ordering in binary choices in 78% of cases. Conclusions This study provides the first evidence for strong stochastic transitivity in a context of mate choice. The females exhibited ordinal preferences and the direction and magnitude of these preferences could be predicted from a simple rule. The females do not necessarily compare two males to choose the best; it is sufficient to use a self-referent evaluation. Such a simple decision rule has important implications for the evolution of the mating strategies and it is consistent with patterns of assortative mating repeatedly observed at population level. PMID:24216003
The impact of sleep deprivation on decision making: a review.
Harrison, Y; Horne, J A
2000-09-01
Few sleep deprivation (SD) studies involve realism or high-level decision making, factors relevant to managers, military commanders, and so forth, who are undergoing prolonged work during crises. Instead, research has favored simple tasks sensitive to SD mostly because of their dull monotony. In contrast, complex rule-based, convergent, and logical tasks are unaffected by short-term SD, seemingly because of heightened participant interest and compensatory effort. However, recent findings show that despite this effort, SD still impairs decision making involving the unexpected, innovation, revising plans, competing distraction, and effective communication. Decision-making models developed outside SD provide useful perspectives on these latter effects, as does a neuropsychological explanation of sleep function. SD presents particular difficulties for sleep-deprived decision makers who require these latter skills during emergency situations.
Althoff, Seth; Overberger, Ryan; Sochor, Mark; Bose, Dipan; Werner, Joshua
2017-10-01
There are established and validated clinical decision tools for cervical spine clearance. Almost all the rules include spinal tenderness on exam as an indication for imaging. Our goal was to apply GLASS, a previously derived clinical decision tool for cervical spine clearance, to thoracolumbar injuries. GLass intact Assures Safe Spine (GLASS) is a simple, objective method to evaluate those patients involved in motor vehicle collisions and determine which are at low risk for thoracolumbar injuries. We performed a retrospective cohort study using the National Accident Sampling System-Crashworthiness Data System (NASS-CDS) over an 11-year period (1998-2008). Sampled occupant cases selected in this study included patients age 16-60 who were belt-restrained, front- seat occupants involved in a crash with no airbag deployment, and no glass damage prior to the crash. We evaluated 14,191 occupants involved in motor vehicle collisions in this analysis. GLASS had a sensitivity of 94.4% (95% CI [86.3-98.4%]), specificity of 54.1% (95% CI [53.2-54.9%]), and negative predictive value of 99.9% (95% CI [99.8-99.9%]) for thoracic injuries, and a sensitivity of 90.3% (95% CI [82.8-95.2%]), specificity of 54.2% (95% CI [53.3-54.9%]), and negative predictive value of 99.9% (95% CI [99.7-99.9%]) for lumbar injuries. The GLASS rule represents the possibility of a novel, more-objective thoracolumbar spine clearance tool. Prospective evaluation would be required to further evaluate the validity of this clinical decision rule.
Two vs. One Keep Away: A Simple Game of Beginning Tactics
ERIC Educational Resources Information Center
Belka, David E.
2005-01-01
In the last decade or so, there has been a shift toward small-sided games played in smaller spaces, with limited rules and an emphasis on tactics. The goal of the current instruction is to use less complex game settings to develop players who then learn to make more appropriate and quicker tactical decisions. In this article, the author presents…
Gradient Scouting in Reversed-Phase HPLC Revisited
ERIC Educational Resources Information Center
Alcazar, A.; Jurado, J. M.; Gonzalez, A. G.
2011-01-01
Gradient scouting is the best way to decide the most suitable elution mode in reversed-phase high-performance liquid chromatography (RP-HPLC). A simple rule for this decision involves the evaluation of the ratio [delta]t/t[subscript G] (where [delta]t is the difference in the retention time between the last and the first peak and t[subscript G] is…
A cognitive prosthesis for complex decision-making.
Tremblay, Sébastien; Gagnon, Jean-François; Lafond, Daniel; Hodgetts, Helen M; Doiron, Maxime; Jeuniaux, Patrick P J M H
2017-01-01
While simple heuristics can be ecologically rational and effective in naturalistic decision making contexts, complex situations require analytical decision making strategies, hypothesis-testing and learning. Sub-optimal decision strategies - using simplified as opposed to analytic decision rules - have been reported in domains such as healthcare, military operational planning, and government policy making. We investigate the potential of a computational toolkit called "IMAGE" to improve decision-making by developing structural knowledge and increasing understanding of complex situations. IMAGE is tested within the context of a complex military convoy management task through (a) interactive simulations, and (b) visualization and knowledge representation capabilities. We assess the usefulness of two versions of IMAGE (desktop and immersive) compared to a baseline. Results suggest that the prosthesis helped analysts in making better decisions, but failed to increase their structural knowledge about the situation once the cognitive prosthesis is removed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Ren, Yue; Li, Jinhai; Aswani Kumar, Cherukuri; Liu, Wenqi
2014-01-01
Rule acquisition is one of the main purposes in the analysis of formal decision contexts. Up to now, there have been several types of rules in formal decision contexts such as decision rules, decision implications, and granular rules, which can be viewed as ∧-rules since all of them have the following form: "if conditions 1,2,…, and m hold, then decisions hold." In order to enrich the existing rule acquisition theory in formal decision contexts, this study puts forward two new types of rules which are called ∨-rules and ∨-∧ mixed rules based on formal, object-oriented, and property-oriented concept lattices. Moreover, a comparison of ∨-rules, ∨-∧ mixed rules, and ∧-rules is made from the perspectives of inclusion and inference relationships. Finally, some real examples and numerical experiments are conducted to compare the proposed rule acquisition algorithms with the existing one in terms of the running efficiency.
Ren, Yue; Aswani Kumar, Cherukuri; Liu, Wenqi
2014-01-01
Rule acquisition is one of the main purposes in the analysis of formal decision contexts. Up to now, there have been several types of rules in formal decision contexts such as decision rules, decision implications, and granular rules, which can be viewed as ∧-rules since all of them have the following form: “if conditions 1,2,…, and m hold, then decisions hold.” In order to enrich the existing rule acquisition theory in formal decision contexts, this study puts forward two new types of rules which are called ∨-rules and ∨-∧ mixed rules based on formal, object-oriented, and property-oriented concept lattices. Moreover, a comparison of ∨-rules, ∨-∧ mixed rules, and ∧-rules is made from the perspectives of inclusion and inference relationships. Finally, some real examples and numerical experiments are conducted to compare the proposed rule acquisition algorithms with the existing one in terms of the running efficiency. PMID:25165744
Analytical model for minority games with evolutionary learning
NASA Astrophysics Data System (ADS)
Campos, Daniel; Méndez, Vicenç; Llebot, Josep E.; Hernández, Germán A.
2010-06-01
In a recent work [D. Campos, J.E. Llebot, V. Méndez, Theor. Popul. Biol. 74 (2009) 16] we have introduced a biological version of the Evolutionary Minority Game that tries to reproduce the intraspecific competition for limited resources in an ecosystem. In comparison with the complex decision-making mechanisms used in standard Minority Games, only two extremely simple strategies ( juveniles and adults) are accessible to the agents. Complexity is introduced instead through an evolutionary learning rule that allows younger agents to learn taking better decisions. We find that this game shows many of the typical properties found for Evolutionary Minority Games, like self-segregation behavior or the existence of an oscillation phase for a certain range of the parameter values. However, an analytical treatment becomes much easier in our case, taking advantage of the simple strategies considered. Using a model consisting of a simple dynamical system, the phase diagram of the game (which differentiates three phases: adults crowd, juveniles crowd and oscillations) is reproduced.
Scheduling Software for Complex Scenarios
NASA Technical Reports Server (NTRS)
2006-01-01
Preparing a vehicle and its payload for a single launch is a complex process that involves thousands of operations. Because the equipment and facilities required to carry out these operations are extremely expensive and limited in number, optimal assignment and efficient use are critically important. Overlapping missions that compete for the same resources, ground rules, safety requirements, and the unique needs of processing vehicles and payloads destined for space impose numerous constraints that, when combined, require advanced scheduling. Traditional scheduling systems use simple algorithms and criteria when selecting activities and assigning resources and times to each activity. Schedules generated by these simple decision rules are, however, frequently far from optimal. To resolve mission-critical scheduling issues and predict possible problem areas, NASA historically relied upon expert human schedulers who used their judgment and experience to determine where things should happen, whether they will happen on time, and whether the requested resources are truly necessary.
Assessing predation risk: optimal behaviour and rules of thumb.
Welton, Nicky J; McNamara, John M; Houston, Alasdair I
2003-12-01
We look at a simple model in which an animal makes behavioural decisions over time in an environment in which all parameters are known to the animal except predation risk. In the model there is a trade-off between gaining information about predation risk and anti-predator behaviour. All predator attacks lead to death for the prey, so that the prey learns about predation risk by virtue of the fact that it is still alive. We show that it is not usually optimal to behave as if the current unbiased estimate of the predation risk is its true value. We consider two different ways to model reproduction; in the first scenario the animal reproduces throughout its life until it dies, and in the second scenario expected reproductive success depends on the level of energy reserves the animal has gained by some point in time. For both of these scenarios we find results on the form of the optimal strategy and give numerical examples which compare optimal behaviour with behaviour under simple rules of thumb. The numerical examples suggest that the value of the optimal strategy over the rules of thumb is greatest when there is little current information about predation risk, learning is not too costly in terms of predation, and it is energetically advantageous to learn about predation. We find that for the model and parameters investigated, a very simple rule of thumb such as 'use the best constant control' performs well.
Althoff, Seth; Overberger, Ryan; Sochor, Mark; Bose, Dipan; Werner, Joshua
2017-01-01
Introduction There are established and validated clinical decision tools for cervical spine clearance. Almost all the rules include spinal tenderness on exam as an indication for imaging. Our goal was to apply GLASS, a previously derived clinical decision tool for cervical spine clearance, to thoracolumbar injuries. GLass intact Assures Safe Spine (GLASS) is a simple, objective method to evaluate those patients involved in motor vehicle collisions and determine which are at low risk for thoracolumbar injuries. Methods We performed a retrospective cohort study using the National Accident Sampling System-Crashworthiness Data System (NASS-CDS) over an 11-year period (1998–2008). Sampled occupant cases selected in this study included patients age 16–60 who were belt-restrained, front- seat occupants involved in a crash with no airbag deployment, and no glass damage prior to the crash. Results We evaluated 14,191 occupants involved in motor vehicle collisions in this analysis. GLASS had a sensitivity of 94.4% (95% CI [86.3–98.4%]), specificity of 54.1% (95% CI [53.2–54.9%]), and negative predictive value of 99.9% (95% CI [99.8–99.9%]) for thoracic injuries, and a sensitivity of 90.3% (95% CI [82.8–95.2%]), specificity of 54.2% (95% CI [53.3–54.9%]), and negative predictive value of 99.9% (95% CI [99.7–99.9%]) for lumbar injuries. Conclusion The GLASS rule represents the possibility of a novel, more-objective thoracolumbar spine clearance tool. Prospective evaluation would be required to further evaluate the validity of this clinical decision rule. PMID:29085544
Bhanji, Jamil P.; Beer, Jennifer S.; Bunge, Silvia A.
2014-01-01
A decision may be difficult because complex information processing is required to evaluate choices according to deterministic decision rules and/or because it is not certain which choice will lead to the best outcome in a probabilistic context. Factors that tax decision making such as decision rule complexity and low decision certainty should be disambiguated for a more complete understanding of the decision making process. Previous studies have examined the brain regions that are modulated by decision rule complexity or by decision certainty but have not examined these factors together in the context of a single task or study. In the present functional magnetic resonance imaging study, both decision rule complexity and decision certainty were varied in comparable decision tasks. Further, the level of certainty about which choice to make (choice certainty) was varied separately from certainty about the final outcome resulting from a choice (outcome certainty). Lateral prefrontal cortex, dorsal anterior cingulate cortex, and bilateral anterior insula were modulated by decision rule complexity. Anterior insula was engaged more strongly by low than high choice certainty decisions, whereas ventromedial prefrontal cortex showed the opposite pattern. These regions showed no effect of the independent manipulation of outcome certainty. The results disambiguate the influence of decision rule complexity, choice certainty, and outcome certainty on activity in diverse brain regions that have been implicated in decision making. Lateral prefrontal cortex plays a key role in implementing deterministic decision rules, ventromedial prefrontal cortex in probabilistic rules, and anterior insula in both. PMID:19781652
Deductibles in health insurance
NASA Astrophysics Data System (ADS)
Dimitriyadis, I.; Öney, Ü. N.
2009-11-01
This study is an extension to a simulation study that has been developed to determine ruin probabilities in health insurance. The study concentrates on inpatient and outpatient benefits for customers of varying age bands. Loss distributions are modelled through the Allianz tool pack for different classes of insureds. Premiums at different levels of deductibles are derived in the simulation and ruin probabilities are computed assuming a linear loading on the premium. The increase in the probability of ruin at high levels of the deductible clearly shows the insufficiency of proportional loading in deductible premiums. The PH-transform pricing rule developed by Wang is analyzed as an alternative pricing rule. A simple case, where an insured is assumed to be an exponential utility decision maker while the insurer's pricing rule is a PH-transform is also treated.
Assessing the chances of success: naïve statistics versus kind experience.
Hogarth, Robin M; Mukherjee, Kanchan; Soyer, Emre
2013-01-01
Additive integration of information is ubiquitous in judgment and has been shown to be effective even when multiplicative rules of probability theory are prescribed. We explore the generality of these findings in the context of estimating probabilities of success in contests. We first define a normative model of these probabilities that takes account of relative skill levels in contests where only a limited number of entrants can win. We then report 4 experiments using a scenario about a competition. Experiments 1 and 2 both elicited judgments of probabilities, and, although participants' responses demonstrated considerable variability, their mean judgments provide a good fit to a simple linear model. Experiment 3 explored choices. Most participants entered most contests and showed little awareness of appropriate probabilities. Experiment 4 investigated effects of providing aids to calculate probabilities, specifically, access to expert advice and 2 simulation tools. With these aids, estimates were accurate and decisions varied appropriately with economic consequences. We discuss implications by considering when additive decision rules are dysfunctional, the interpretation of overconfidence based on contest-entry behavior, and the use of aids to help people make better decisions.
Navigating a Mobile Robot Across Terrain Using Fuzzy Logic
NASA Technical Reports Server (NTRS)
Seraji, Homayoun; Howard, Ayanna; Bon, Bruce
2003-01-01
A strategy for autonomous navigation of a robotic vehicle across hazardous terrain involves the use of a measure of traversability of terrain within a fuzzy-logic conceptual framework. This navigation strategy requires no a priori information about the environment. Fuzzy logic was selected as a basic element of this strategy because it provides a formal methodology for representing and implementing a human driver s heuristic knowledge and operational experience. Within a fuzzy-logic framework, the attributes of human reasoning and decision- making can be formulated by simple IF (antecedent), THEN (consequent) rules coupled with easily understandable and natural linguistic representations. The linguistic values in the rule antecedents convey the imprecision associated with measurements taken by sensors onboard a mobile robot, while the linguistic values in the rule consequents represent the vagueness inherent in the reasoning processes to generate the control actions. The operational strategies of the human expert driver can be transferred, via fuzzy logic, to a robot-navigation strategy in the form of a set of simple conditional statements composed of linguistic variables. These linguistic variables are defined by fuzzy sets in accordance with user-defined membership functions. The main advantages of a fuzzy navigation strategy lie in the ability to extract heuristic rules from human experience and to obviate the need for an analytical model of the robot navigation process.
Yield of computed tomography of the cervical spine in cases of simple assault.
Uriell, Matthew L; Allen, Jason W; Lovasik, Brendan P; Benayoun, Marc D; Spandorfer, Robert M; Holder, Chad A
2017-01-01
Computed tomography (CT) of the cervical spine (C-spine) is routinely ordered for low-impact, non-penetrating or "simple" assault at our institution and others. Common clinical decision tools for C-spine imaging in the setting of trauma include the National Emergency X-Radiography Utilization Study (NEXUS) and the Canadian Cervical Spine Rule for Radiography (CCR). While NEXUS and CCR have served to decrease the amount of unnecessary imaging of the C-spine, overutilization of CT is still of concern. A retrospective, cross-sectional study was performed of the electronic medical record (EMR) database at an urban, Level I Trauma Center over a 6-month period for patients receiving a C-spine CT. The primary outcome of interest was prevalence of cervical spine fracture. Secondary outcomes of interest included appropriateness of C-spine imaging after retrospective application of NEXUS and CCR. The hypothesis was that fracture rates within this patient population would be extremely low. No C-spine fractures were identified in the 460 patients who met inclusion criteria. Approximately 29% of patients did not warrant imaging by CCR, and 25% by NEXUS. Of note, approximately 44% of patients were indeterminate for whether imaging was warranted by CCR, with the most common reason being lack of assessment for active neck rotation. Cervical spine CT is overutilized in the setting of simple assault, despite established clinical decision rules. With no fractures identified regardless of other factors, the likelihood that a CT of the cervical spine will identify clinically significant findings in the setting of "simple" assault is extremely low, approaching zero. At minimum, adherence to CCR and NEXUS within this patient population would serve to reduce both imaging costs and population radiation dose exposure. Copyright © 2016 Elsevier Ltd. All rights reserved.
Using Bayesian Networks and Decision Theory to Model Physical Security
2003-02-01
Home automation technologies allow a person to monitor and control various activities within a home or office setting. Cameras, sensors and other...components used along with the simple rules in the home automation software provide an environment where the lights, security and other appliances can be...monitored and controlled. These home automation technologies, however, lack the power to reason under uncertain conditions and thus the system can
Samwald, Matthias; Miñarro Giménez, Jose Antonio; Boyce, Richard D; Freimuth, Robert R; Adlassnig, Klaus-Peter; Dumontier, Michel
2015-02-22
Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles. Our methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners. The ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of pharmacogenomic knowledge, as well as to identify errors, inconsistencies and insufficient definitions in source data sets or individual patient data. Our study highlights both advantages and potential practical issues with such an ontology-based approach.
Meys, Evelyne; Rutten, Iris; Kruitwagen, Roy; Slangen, Brigitte; Lambrechts, Sandrina; Mertens, Helen; Nolting, Ernst; Boskamp, Dieuwke; Van Gorp, Toon
2017-12-01
To analyze how well untrained examiners - without experience in the use of International Ovarian Tumor Analysis (IOTA) terminology or simple ultrasound-based rules (simple rules) - are able to apply IOTA terminology and simple rules and to assess the level of agreement between non-experts and an expert. This prospective multicenter cohort study enrolled women with ovarian masses. Ultrasound was performed by non-expert examiners and an expert. Ultrasound features were recorded using IOTA nomenclature, and used for classifying the mass by simple rules. Interobserver agreement was evaluated with Fleiss' kappa and percentage agreement between observers. 50 consecutive women were included. We observed 46 discrepancies in the description of ovarian masses when non-experts utilized IOTA terminology. Tumor type was misclassified often (n = 22), resulting in poor interobserver agreement between the non-experts and the expert (kappa = 0.39, 95 %-CI 0.244 - 0.529, percentage of agreement = 52.0 %). Misinterpretation of simple rules by non-experts was observed 57 times, resulting in an erroneous diagnosis in 15 patients (30 %). The agreement for classifying the mass as benign, malignant or inconclusive by simple rules was only moderate between the non-experts and the expert (kappa = 0.50, 95 %-CI 0.300 - 0.704, percentage of agreement = 70.0 %). The level of agreement for all 10 simple rules features varied greatly (kappa index range: -0.08 - 0.74, percentage of agreement 66 - 94 %). Although simple rules are useful to distinguish benign from malignant adnexal masses, they are not that simple for untrained examiners. Training with both IOTA terminology and simple rules is necessary before simple rules can be introduced into guidelines and daily clinical practice. © Georg Thieme Verlag KG Stuttgart · New York.
Instance-based categorization: automatic versus intentional forms of retrieval.
Neal, A; Hesketh, B; Andrews, S
1995-03-01
Two experiments are reported which attempt to disentangle the relative contribution of intentional and automatic forms of retrieval to instance-based categorization. A financial decision-making task was used in which subjects had to decide whether a bank would approve loans for a series of applicants. Experiment 1 found that categorization was sensitive to instance-specific knowledge, even when subjects had practiced using a simple rule. L. L. Jacoby's (1991) process-dissociation procedure was adapted for use in Experiment 2 to infer the relative contribution of intentional and automatic retrieval processes to categorization decisions. The results provided (1) strong evidence that intentional retrieval processes influence categorization, and (2) some preliminary evidence suggesting that automatic retrieval processes may also contribute to categorization decisions.
Assessing an AI knowledge-base for asymptomatic liver diseases.
Babic, A; Mathiesen, U; Hedin, K; Bodemar, G; Wigertz, O
1998-01-01
Discovering not yet seen knowledge from clinical data is of importance in the field of asymptomatic liver diseases. Avoidance of liver biopsy which is used as the ultimate confirmation of diagnosis by making the decision based on relevant laboratory findings only, would be considered an essential support. The system based on Quinlan's ID3 algorithm was simple and efficient in extracting the sought knowledge. Basic principles of applying the AI systems are therefore described and complemented with medical evaluation. Some of the diagnostic rules were found to be useful as decision algorithms i.e. they could be directly applied in clinical work and made a part of the knowledge-base of the Liver Guide, an automated decision support system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berman, D.W.; Allen, B.C.; Van Landingham, C.B.
1998-12-31
The decision rules commonly employed to determine the need for cleanup are evaluated both to identify conditions under which they lead to erroneous conclusions and to quantify the rate that such errors occur. Their performance is also compared with that of other applicable decision rules. The authors based the evaluation of decision rules on simulations. Results are presented as power curves. These curves demonstrate that the degree of statistical control achieved is independent of the form of the null hypothesis. The loss of statistical control that occurs when a decision rule is applied to a data set that does notmore » satisfy the rule`s validity criteria is also clearly demonstrated. Some of the rules evaluated do not offer the formal statistical control that is an inherent design feature of other rules. Nevertheless, results indicate that such informal decision rules may provide superior overall control of error rates, when their application is restricted to data exhibiting particular characteristics. The results reported here are limited to decision rules applied to uncensored and lognormally distributed data. To optimize decision rules, it is necessary to evaluate their behavior when applied to data exhibiting a range of characteristics that bracket those common to field data. The performance of decision rules applied to data sets exhibiting a broader range of characteristics is reported in the second paper of this study.« less
IOTA simple rules in differentiating between benign and malignant ovarian tumors.
Tantipalakorn, Charuwan; Wanapirak, Chanane; Khunamornpong, Surapan; Sukpan, Kornkanok; Tongsong, Theera
2014-01-01
To evaluate the diagnostic performance of IOTA simple rules in differentiating between benign and malignant ovarian tumors. A study of diagnostic performance was conducted on women scheduled for elective surgery due to ovarian masses between March 2007 and March 2012. All patients underwent ultrasound examination for IOTA simple rules within 24 hours of surgery. All examinations were performed by the authors, who had no any clinical information of the patients, to differentiate between benign and malignant adnexal masses using IOTA simple rules. Gold standard diagnosis was based on pathological or operative findings. A total of 398 adnexal masses, in 376 women, were available for analysis. Of them, the IOTA simple rules could be applied in 319 (80.1%) including 212 (66.5%) benign tumors and 107 (33.6%) malignant tumors. The simple rules yielded inconclusive results in 79 (19.9%) masses. In the 319 masses for which the IOTA simple rules could be applied, sensitivity was 82.9% and specificity 95.3%. The IOTA simple rules have high diagnostic performance in differentiating between benign and malignant adnexal masses. Nevertheless, inconclusive results are relatively common.
Evaluation of a rule base for decision making in general practice.
Essex, B; Healy, M
1994-01-01
BACKGROUND. Decision making in general practice relies heavily on judgmental expertise. It should be possible to codify this expertise into rules and principles. AIM. A study was undertaken to evaluate the effectiveness, of rules from a rule base designed to improve students' and trainees' management decisions relating to patients seen in general practice. METHOD. The rule base was developed after studying decisions about and management of thousands of patients seen in one general practice over an eight year period. Vignettes were presented to 93 fourth year medical students and 179 general practitioner trainees. They recorded their perception and management of each case before and after being presented with a selection of relevant rules. Participants also commented on their level of agreement with each of the rules provided with the vignettes. A panel of five independent assessors then rated as good, acceptable or poor, the participants' perception and management of each case before and after seeing the rules. RESULTS. Exposure to a few selected rules of thumb improved the problem perception and management decisions of both undergraduates and trainees. The degree of improvement was not related to previous experience or to the stated level of agreement with the proposed rules. The assessors identified difficulties students and trainees experienced in changing their perceptions and management decisions when the rules suggested options they had not considered. CONCLUSION. The rules developed to improve decision making skills in general practice are effective when used with vignettes. The next phase is to transform the rule base into an expert system to train students and doctors to acquire decision making skills. It could also be used to provide decision support when confronted with difficult management decisions in general practice. PMID:8204334
A Plea for Process in Personality Prevarication
Kuncel, Nathan R.; Goldberg, Lewis R.; Kiger, Tom
2011-01-01
We make a series recommendations for focusing research on personality test faking. Overall we suggest that a focus on the response process test takers go through will accelerate our understanding of faking behavior. We argue that the decision making process for faking must be simple and dependent on a modest set of decision rules or heuristics. The set of heuristics used by any given test taker will, in turn, be the result of test taker goals and situational press. By focusing in on what the test taker is doing we will avoid adopting the wrong frame of reference and, hopefully, make ever more rapid progress. PMID:21966260
Kameda, Tatsuya; Tsukasaki, Takafumi; Hastie, Reid; Berg, Nathan
2011-01-01
We introduce a game theory model of individual decisions to cooperate by contributing personal resources to group decisions versus by free riding on the contributions of other members. In contrast to most public-goods games that assume group returns are linear in individual contributions, the present model assumes decreasing marginal group production as a function of aggregate individual contributions. This diminishing marginal returns assumption is more realistic and generates starkly different predictions compared to the linear model. One important implication is that, under most conditions, there exist equilibria where some, but not all, members of a group contribute, even with completely self-interested motives. An agent-based simulation confirmed the individual and group advantages of the equilibria in which behavioral asymmetry emerges from a game structure that is a priori perfectly symmetric for all agents (all agents have the same payoff function and action space but take different actions in equilibria). A behavioral experiment demonstrated that cooperators and free riders coexist in a stable manner in groups performing with the nonlinear production function. A collateral result demonstrated that, compared to a dictatorial decision scheme guided by the best member in a group, the majority/plurality decision rules can pool information effectively and produce greater individual net welfare at equilibrium, even if free riding is not sanctioned. This is an original proof that cooperation in ad hoc decision-making groups can be understood in terms of self-interested motivations and that, despite the free-rider problem, majority/plurality decision rules can function robustly as simple, efficient social decision heuristics.
INDEXABILITY AND OPTIMAL INDEX POLICIES FOR A CLASS OF REINITIALISING RESTLESS BANDITS.
Villar, Sofía S
2016-01-01
Motivated by a class of Partially Observable Markov Decision Processes with application in surveillance systems in which a set of imperfectly observed state processes is to be inferred from a subset of available observations through a Bayesian approach, we formulate and analyze a special family of multi-armed restless bandit problems. We consider the problem of finding an optimal policy for observing the processes that maximizes the total expected net rewards over an infinite time horizon subject to the resource availability. From the Lagrangian relaxation of the original problem, an index policy can be derived, as long as the existence of the Whittle index is ensured. We demonstrate that such a class of reinitializing bandits in which the projects' state deteriorates while active and resets to its initial state when passive until its completion possesses the structural property of indexability and we further show how to compute the index in closed form. In general, the Whittle index rule for restless bandit problems does not achieve optimality. However, we show that the proposed Whittle index rule is optimal for the problem under study in the case of stochastically heterogenous arms under the expected total criterion, and it is further recovered by a simple tractable rule referred to as the 1-limited Round Robin rule. Moreover, we illustrate the significant suboptimality of other widely used heuristic: the Myopic index rule, by computing in closed form its suboptimality gap. We present numerical studies which illustrate for the more general instances the performance advantages of the Whittle index rule over other simple heuristics.
INDEXABILITY AND OPTIMAL INDEX POLICIES FOR A CLASS OF REINITIALISING RESTLESS BANDITS
Villar, Sofía S.
2016-01-01
Motivated by a class of Partially Observable Markov Decision Processes with application in surveillance systems in which a set of imperfectly observed state processes is to be inferred from a subset of available observations through a Bayesian approach, we formulate and analyze a special family of multi-armed restless bandit problems. We consider the problem of finding an optimal policy for observing the processes that maximizes the total expected net rewards over an infinite time horizon subject to the resource availability. From the Lagrangian relaxation of the original problem, an index policy can be derived, as long as the existence of the Whittle index is ensured. We demonstrate that such a class of reinitializing bandits in which the projects’ state deteriorates while active and resets to its initial state when passive until its completion possesses the structural property of indexability and we further show how to compute the index in closed form. In general, the Whittle index rule for restless bandit problems does not achieve optimality. However, we show that the proposed Whittle index rule is optimal for the problem under study in the case of stochastically heterogenous arms under the expected total criterion, and it is further recovered by a simple tractable rule referred to as the 1-limited Round Robin rule. Moreover, we illustrate the significant suboptimality of other widely used heuristic: the Myopic index rule, by computing in closed form its suboptimality gap. We present numerical studies which illustrate for the more general instances the performance advantages of the Whittle index rule over other simple heuristics. PMID:27212781
Optimal joint detection and estimation that maximizes ROC-type curves
Wunderlich, Adam; Goossens, Bart; Abbey, Craig K.
2017-01-01
Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation. PMID:27093544
Optimal Joint Detection and Estimation That Maximizes ROC-Type Curves.
Wunderlich, Adam; Goossens, Bart; Abbey, Craig K
2016-09-01
Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation.
Multisensor fusion with non-optimal decision rules: the challenges of open world sensing
NASA Astrophysics Data System (ADS)
Minor, Christian; Johnson, Kevin
2014-05-01
In this work, simple, generic models of chemical sensing are used to simulate sensor array data and to illustrate the impact on overall system performance that specific design choices impart. The ability of multisensor systems to perform multianalyte detection (i.e., distinguish multiple targets) is explored by examining the distinction between fundamental design-related limitations stemming from mismatching of mixture composition to fused sensor measurement spaces, and limitations that arise from measurement uncertainty. Insight on the limits and potential of sensor fusion to robustly address detection tasks in realistic field conditions can be gained through an examination of a) the underlying geometry of both the composition space of sources one hopes to elucidate and the measurement space a fused sensor system is capable of generating, and b) the informational impact of uncertainty on both of these spaces. For instance, what is the potential impact on sensor fusion in an open world scenario where unknown interferants may contaminate target signals? Under complex and dynamic backgrounds, decision rules may implicitly become non-optimal and adding sensors may increase the amount of conflicting information observed. This suggests that the manner in which a decision rule handles sensor conflict can be critical in leveraging sensor fusion for effective open world sensing, and becomes exponentially more important as more sensors are added. Results and design considerations for handling conflicting evidence in Bayes and Dempster-Shafer fusion frameworks are presented. Bayesian decision theory is used to provide an upper limit on detector performance of simulated sensor systems.
Route choice in mountain navigation, Naismith's rule, and the equivalence of distance and climb.
Scarf, Philip
2007-04-01
In this paper, I consider decision making about routes in mountain navigation. In particular, I discuss Naismith's rule, a method of calculating journey times in mountainous terrain, and its use for route choice. The rule is essentially concerned with the equivalence, in terms of time duration, between climb or ascent and distance travelled. Naismith himself described a rule that is purported to be based on trigonometry and simple assumptions about rate of ascent; his rule with regard to hill-walking implies that 1 m of ascent is equivalent to 7.92 m of horizontal travel (1:7.92). The analysis of data on fell running records presented here supports Naismith's rule and it is recommended that male runners and walkers use a 1:8 equivalence ratio and females a 1:10 ratio. The present findings are contrasted with those based on the analysis of data relating to treadmill running experiments (1:3.3), and with those based on the analysis of times for a mountain road-relay (1:4.4). Analysis of cycling data suggests a similar rule (1:8.2) for cycling on mountainous roads and tracks.
Schouten, Henrike J; Koek, Huiberdina L; Oudega, Ruud; van Delden, Johannes J M; Moons, Karel G M; Geersing, Geert-Jan
2015-02-01
We aimed to validate the Oudega diagnostic decision rule-which was developed and validated among younger aged primary care patients-to rule-out deep vein thrombosis (DVT) in frail older outpatients. In older patients (>60 years, either community dwelling or residing in nursing homes) with clinically suspected DVT, physicians recorded the score on the Oudega rule and d-dimer test. DVT was confirmed with a composite reference standard including ultrasonography examination and 3-month follow-up. The proportion of patients with a very low probability of DVT according to the Oudega rule (efficiency), and the proportion of patients with symptomatic venous thromboembolism during 3 months follow-up within this 'very low risk' group (failure rate) was calculated. DVT occurred in 164 (47%) of the 348 study participants (mean age 81 years, 85% residing in nursing homes). The probability of DVT was very low in 69 patients (Oudega score ≤3 points plus a normal d-dimer test; efficiency 20%) of whom four had non-fatal DVT (failure rate 5.8%; 2.3-14%). With a simple revised version of the Oudega rule for older suspected patients, 43 patients had a low risk of DVT (12% of the total population) of whom only one had DVT (failure rate 2.3%; 0.4-12%). In older suspected patients, application of the original Oudega rule to exclude DVT resulted in a higher failure rate as compared to previous studies. A revised and simplified Oudega strategy specifically developed for elderly suspected patients resulted in a lower failure rate though at the expense of a lower efficiency. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Highly scalable and robust rule learner: performance evaluation and comparison.
Kurgan, Lukasz A; Cios, Krzysztof J; Dick, Scott
2006-02-01
Business intelligence and bioinformatics applications increasingly require the mining of datasets consisting of millions of data points, or crafting real-time enterprise-level decision support systems for large corporations and drug companies. In all cases, there needs to be an underlying data mining system, and this mining system must be highly scalable. To this end, we describe a new rule learner called DataSqueezer. The learner belongs to the family of inductive supervised rule extraction algorithms. DataSqueezer is a simple, greedy, rule builder that generates a set of production rules from labeled input data. In spite of its relative simplicity, DataSqueezer is a very effective learner. The rules generated by the algorithm are compact, comprehensible, and have accuracy comparable to rules generated by other state-of-the-art rule extraction algorithms. The main advantages of DataSqueezer are very high efficiency, and missing data resistance. DataSqueezer exhibits log-linear asymptotic complexity with the number of training examples, and it is faster than other state-of-the-art rule learners. The learner is also robust to large quantities of missing data, as verified by extensive experimental comparison with the other learners. DataSqueezer is thus well suited to modern data mining and business intelligence tasks, which commonly involve huge datasets with a large fraction of missing data.
Design and usability of heuristic-based deliberation tools for women facing amniocentesis.
Durand, Marie-Anne; Wegwarth, Odette; Boivin, Jacky; Elwyn, Glyn
2012-03-01
Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health-care decisions), fast and frugal decision-making strategies (heuristics) may perform better than complex rules of reasoning. To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). The 'Take The Best' heuristic (i.e. selection of a 'most important reason') and 'The Tallying' integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web-based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health-care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of 'your most important reason' (Take The Best) and 'weighing it up' (Tallying). Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health-care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that 'weighing it up' and 'your most important reason' were not appropriate when facing such a difficult and emotional decision. Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real-world decisions about amniocentesis. © 2011 Blackwell Publishing Ltd.
2012-01-01
Clinical decision rules are an increasingly common presence in the biomedical literature and represent one strategy of enhancing clinical-decision making with the goal of improving the efficiency and effectiveness of healthcare delivery. In the context of rehabilitation research, clinical decision rules have been predominantly aimed at classifying patients by predicting their treatment response to specific therapies. Traditionally, recommendations for developing clinical decision rules propose a multistep process (derivation, validation, impact analysis) using defined methodology. Research efforts aimed at developing a “diagnosis-based clinical decision rule” have departed from this convention. Recent publications in this line of research have used the modified terminology “diagnosis-based clinical decision guide.” Modifications to terminology and methodology surrounding clinical decision rules can make it more difficult for clinicians to recognize the level of evidence associated with a decision rule and understand how this evidence should be implemented to inform patient care. We provide a brief overview of clinical decision rule development in the context of the rehabilitation literature and two specific papers recently published in Chiropractic and Manual Therapies. PMID:22726639
Eisenhardt, K M; Sull, D N
2001-01-01
The success of Yahoo!, eBay, Enron, and other companies that have become adept at morphing to meet the demands of changing markets can't be explained using traditional thinking about competitive strategy. These companies have succeeded by pursuing constantly evolving strategies in market spaces that were considered unattractive according to traditional measures. In this article--the third in an HBR series by Kathleen Eisenhardt and Donald Sull on strategy in the new economy--the authors ask, what are the sources of competitive advantage in high-velocity markets? The secret, they say, is strategy as simple rules. The companies know that the greatest opportunities for competitive advantage lie in market confusion, but they recognize the need for a few crucial strategic processes and a few simple rules. In traditional strategy, advantage comes from exploiting resources or stable market positions. In strategy as simple rules, advantage comes from successfully seizing fleeting opportunities. Key strategic processes, such as product innovation, partnering, or spinout creation, place the company where the flow of opportunities is greatest. Simple rules then provide the guidelines within which managers can pursue such opportunities. Simple rules, which grow out of experience, fall into five broad categories: how- to rules, boundary conditions, priority rules, timing rules, and exit rules. Companies with simple-rules strategies must follow the rules religiously and avoid the temptation to change them too frequently. A consistent strategy helps managers sort through opportunities and gain short-term advantage by exploiting the attractive ones. In stable markets, managers rely on complicated strategies built on detailed predictions of the future. But when business is complicated, strategy should be simple.
Microarray-based cancer prediction using soft computing approach.
Wang, Xiaosheng; Gotoh, Osamu
2009-05-26
One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.
Dypas: A dynamic payload scheduler for shuttle missions
NASA Technical Reports Server (NTRS)
Davis, Stephen
1988-01-01
Decision and analysis systems have had broad and very practical application areas in the human decision making process. These software systems range from the help sections in simple accounting packages, to the more complex computer configuration programs. Dypas is a decision and analysis system that aids prelaunch shutlle scheduling, and has added functionality to aid the rescheduling done in flight. Dypas is written in Common Lisp on a Symbolics Lisp machine. Dypas differs from other scheduling programs in that it can draw its knowledge from different rule bases and apply them to different rule interpretation schemes. The system has been coded with Flavors, an object oriented extension to Common Lisp on the Symbolics hardware. This allows implementation of objects (experiments) to better match the problem definition, and allows a more coherent solution space to be developed. Dypas was originally developed to test a programmer's aptitude toward Common Lisp and the Symbolics software environment. Since then the system has grown into a large software effort with several programmers and researchers thrown into the effort. Dypas is currently using two expert systems and three inferencing procedures to generate a many object schedule. The paper will review the abilities of Dypas and comment on its functionality.
Decision making in a human population living sustainably.
Hicks, John S; Burgman, Mark A; Marewski, Julian N; Fidler, Fiona; Gigerenzer, Gerd
2012-10-01
The Tiwi people of northern Australia have managed natural resources continuously for 6000-8000 years. Tiwi management objectives and outcomes may reflect how they gather information about the environment. We qualitatively analyzed Tiwi documents and management techniques to examine the relation between the social and physical environment of decision makers and their decision-making strategies. We hypothesized that principles of bounded rationality, namely, the use of efficient rules to navigate complex decision problems, explain how Tiwi managers use simple decision strategies (i.e., heuristics) to make robust decisions. Tiwi natural resource managers reduced complexity in decision making through a process that gathers incomplete and uncertain information to quickly guide decisions toward effective outcomes. They used management feedback to validate decisions through an information loop that resulted in long-term sustainability of environmental use. We examined the Tiwi decision-making processes relative to management of barramundi (Lates calcarifer) fisheries and contrasted their management with the state government's management of barramundi. Decisions that enhanced the status of individual people and their attainment of aspiration levels resulted in reliable resource availability for Tiwi consumers. Different decision processes adopted by the state for management of barramundi may not secure similarly sustainable outcomes. ©2012 Society for Conservation Biology.
On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems
NASA Technical Reports Server (NTRS)
Tunstel, Edward; Jamshidi, Mo
1997-01-01
Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.
Tinnangwattana, Dangcheewan; Vichak-Ururote, Linlada; Tontivuthikul, Paponrad; Charoenratana, Cholaros; Lerthiranwong, Thitikarn; Tongsong, Theera
2015-01-01
To evaluate the diagnostic performance of IOTA simple rules in predicting malignant adnexal tumors by non-expert examiners. Five obstetric/gynecologic residents, who had never performed gynecologic ultrasound examination by themselves before, were trained for IOTA simple rules by an experienced examiner. One trained resident performed ultrasound examinations including IOTA simple rules on 100 women, who were scheduled for surgery due to ovarian masses, within 24 hours of surgery. The gold standard diagnosis was based on pathological or operative findings. The five-trained residents performed IOTA simple rules on 30 patients for evaluation of inter-observer variability. A total of 100 patients underwent ultrasound examination for the IOTA simple rules. Of them, IOTA simple rules could be applied in 94 (94%) masses including 71 (71.0%) benign masses and 29 (29.0%) malignant masses. The diagnostic performance of IOTA simple rules showed sensitivity of 89.3% (95%CI, 77.8%; 100.7%), specificity 83.3% (95%CI, 74.3%; 92.3%). Inter-observer variability was analyzed using Cohen's kappa coefficient. Kappa indices of the four pairs of raters are 0.713-0.884 (0.722, 0.827, 0.713, and 0.884). IOTA simple rules have high diagnostic performance in discriminating adnexal masses even when are applied by non-expert sonographers, though a training course may be required. Nevertheless, they should be further tested by a greater number of general practitioners before widely use.
Decision Rules and Group Rationality: Cognitive Gain or Standstill?
Curşeu, Petru Lucian; Jansen, Rob J. G.; Chappin, Maryse M. H.
2013-01-01
Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members’ cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups. PMID:23451050
Decision rules and group rationality: cognitive gain or standstill?
Curşeu, Petru Lucian; Jansen, Rob J G; Chappin, Maryse M H
2013-01-01
Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members' cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups.
46 CFR 201.3 - Authentication of rules, orders, determinations and decisions of the Administration.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 46 Shipping 8 2010-10-01 2010-10-01 false Authentication of rules, orders, determinations and decisions of the Administration. 201.3 Section 201.3 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF....3 Authentication of rules, orders, determinations and decisions of the Administration. All rules...
Cognitive Processes in Decisions Under Risk are not the Same as in Decisions Under Uncertainty
Volz, Kirsten G.; Gigerenzer, Gerd
2012-01-01
We deal with risk versus uncertainty, a distinction that is of fundamental importance for cognitive neuroscience yet largely neglected. In a world of risk (“small world”), all alternatives, consequences, and probabilities are known. In uncertain (“large”) worlds, some of this information is unknown or unknowable. Most of cognitive neuroscience studies exclusively study the neural correlates for decisions under risk (e.g., lotteries), with the tacit implication that understanding these would lead to an understanding of decision making in general. First, we show that normative strategies for decisions under risk do not generalize to uncertain worlds, where simple heuristics are often the more accurate strategies. Second, we argue that the cognitive processes for making decisions in a world of risk are not the same as those for dealing with uncertainty. Because situations with known risks are the exception rather than the rule in human evolution, it is unlikely that our brains are adapted to them. We therefore suggest a paradigm shift toward studying decision processes in uncertain worlds and provide first examples. PMID:22807893
48 CFR 6103.306 - Decisions [Rule 306].
Code of Federal Regulations, 2010 CFR
2010-10-01
... 48 Federal Acquisition Regulations System 7 2010-10-01 2010-10-01 false Decisions [Rule 306]. 6103.306 Section 6103.306 Federal Acquisition Regulations System CIVILIAN BOARD OF CONTRACT APPEALS, GENERAL SERVICES ADMINISTRATION TRANSPORTATION RATE CASES 6103.306 Decisions [Rule 306]. The judge will issue a written decision based upon the record,...
Wang, Xi; Sun, Lixing; Li, Jinhua; Xia, Dongpo; Sun, Binghua; Zhang, Dao
2015-01-01
Collective behavior has recently attracted a great deal of interest in both natural and social sciences. While the role of leadership has been closely scrutinized, the rules used by joiners in collective decision making have received far less attention. Two main hypotheses have been proposed concerning these rules: mimetism and quorum. Mimetism predicts that individuals are increasingly likely to join collective behavior as the number of participants increases. It can be further divided into selective mimetism, where relationships among the participants affect the process, and anonymous mimetism, where no such effect exists. Quorum predicts that a collective behavior occurs when the number of participants reaches a threshold. To probe into which rule is used in collective decision making, we conducted a study on the joining process in a group of free-ranging Tibetan macaques (Macaca thibetana) in Huangshan, China using a combination of all-occurrence and focal animal sampling methods. Our results show that the earlier individuals joined movements, the more central a role they occupied among the joining network. We also found that when less than three adults participated in the first five minutes of the joining process, no entire group movement occurred subsequently. When the number of these early joiners ranged from three to six, selective mimetism was used. This means higher rank or closer social affiliation of early joiners could be among the factors of deciding whether to participate in movements by group members. When the number of early joiners reached or exceeded seven, which was the simple majority of the group studied, entire group movement always occurred, meaning that the quorum rule was used. Putting together, Macaca thibetana used a combination of selective mimetism and quorum, and early joiners played a key role in deciding which rule should be used.
Measuring the effect of attention on simple visual search.
Palmer, J; Ames, C T; Lindsey, D T
1993-02-01
Set-size in visual search may be due to 1 or more of 3 factors: sensory processes such as lateral masking between stimuli, attentional processes limiting the perception of individual stimuli, or attentional processes affecting the decision rules for combining information from multiple stimuli. These possibilities were evaluated in tasks such as searching for a longer line among shorter lines. To evaluate sensory contributions, display set-size effects were compared with cuing conditions that held sensory phenomena constant. Similar effects for the display and cue manipulations suggested that sensory processes contributed little under the conditions of this experiment. To evaluate the contribution of decision processes, the set-size effects were modeled with signal detection theory. In these models, a decision effect alone was sufficient to predict the set-size effects without any attentional limitation due to perception.
Using light gradients to investigate symmetry breaking in fish schools
NASA Astrophysics Data System (ADS)
Puckett, James; Giannini, Julia
Theoretical models of social animals successfully reproduce many structures found in nature (e.g. swarms, flocks, mills) using simple interaction rules. However, the interactions between individuals is complex and undoubtedly depends on the environment. Using schools of fish, we use visual perturbations to investigate how individuals negotiate both social and environmental information to reach a consensus. Starting with an unpolarized school of fish, we examine how the symmetry is broken and find that not all fish contribute equally to this decision.
Potter, Adam W; Blanchard, Laurie A; Friedl, Karl E; Cadarette, Bruce S; Hoyt, Reed W
2017-02-01
Physiological models provide useful summaries of complex interrelated regulatory functions. These can often be reduced to simple input requirements and simple predictions for pragmatic applications. This paper demonstrates this modeling efficiency by tracing the development of one such simple model, the Heat Strain Decision Aid (HSDA), originally developed to address Army needs. The HSDA, which derives from the Givoni-Goldman equilibrium body core temperature prediction model, uses 16 inputs from four elements: individual characteristics, physical activity, clothing biophysics, and environmental conditions. These inputs are used to mathematically predict core temperature (T c ) rise over time and can estimate water turnover from sweat loss. Based on a history of military applications such as derivation of training and mission planning tools, we conclude that the HSDA model is a robust integration of physiological rules that can guide a variety of useful predictions. The HSDA model is limited to generalized predictions of thermal strain and does not provide individualized predictions that could be obtained from physiological sensor data-driven predictive models. This fully transparent physiological model should be improved and extended with new findings and new challenging scenarios. Published by Elsevier Ltd.
Biodiversity, conservation biology, and rational choice.
Frank, David
2014-03-01
This paper critically discusses two areas of Sahotra Sarkar's recent work in environmental philosophy: biodiversity and conservation biology and roles for decision theory in incorporating values explicitly in the environmental policy process. I argue that Sarkar's emphasis on the practices of conservation biologists, and especially the role of social and cultural values in the choice of biodiversity constituents, restricts his conception of biodiversity to particular practical conservation contexts. I argue that life scientists have many reasons to measure many types of diversity, and that biodiversity metrics could be value-free. I argue that Sarkar's emphasis on the limitations of normative decision theory is in tension with his statement that decision theory can "put science and ethics together." I also challenge his claim that multi-criteria decision tools lacking axiomatic foundations in preference and utility theory are "without a rational basis," by presenting a case of a simple "outranking" multi-criteria decision rule that can violate a basic normative requirement of preferences (transitivity) and ask whether there may nevertheless be contexts in which such a procedure might assist decision makers. Copyright © 2013 Elsevier Ltd. All rights reserved.
Regan, Tracey J; Taylor, Barbara L; Thompson, Grant G; Cochrane, Jean Fitts; Ralls, Katherine; Runge, Michael C; Merrick, Richard
2013-08-01
Lack of guidance for interpreting the definitions of endangered and threatened in the U.S. Endangered Species Act (ESA) has resulted in case-by-case decision making leaving the process vulnerable to being considered arbitrary or capricious. Adopting quantitative decision rules would remedy this but requires the agency to specify the relative urgency concerning extinction events over time, cutoff risk values corresponding to different levels of protection, and the importance given to different types of listing errors. We tested the performance of 3 sets of decision rules that use alternative functions for weighting the relative urgency of future extinction events: a threshold rule set, which uses a decision rule of x% probability of extinction over y years; a concave rule set, where the relative importance of future extinction events declines exponentially over time; and a shoulder rule set that uses a sigmoid shape function, where relative importance declines slowly at first and then more rapidly. We obtained decision cutoffs by interviewing several biologists and then emulated the listing process with simulations that covered a range of extinction risks typical of ESA listing decisions. We evaluated performance of the decision rules under different data quantities and qualities on the basis of the relative importance of misclassification errors. Although there was little difference between the performance of alternative decision rules for correct listings, the distribution of misclassifications differed depending on the function used. Misclassifications for the threshold and concave listing criteria resulted in more overprotection errors, particularly as uncertainty increased, whereas errors for the shoulder listing criteria were more symmetrical. We developed and tested the framework for quantitative decision rules for listing species under the U.S. ESA. If policy values can be agreed on, use of this framework would improve the implementation of the ESA by increasing transparency and consistency. Conservation Biology © 2013 Society for Conservation Biology No claim to original US government works.
Oosterman, Joukje M; Heringa, Sophie M; Kessels, Roy P C; Biessels, Geert Jan; Koek, Huiberdina L; Maes, Joseph H R; van den Berg, Esther
2017-04-01
Rule induction tests such as the Wisconsin Card Sorting Test require executive control processes, but also the learning and memorization of simple stimulus-response rules. In this study, we examined the contribution of diminished learning and memorization of simple rules to complex rule induction test performance in patients with amnestic mild cognitive impairment (aMCI) or Alzheimer's dementia (AD). Twenty-six aMCI patients, 39 AD patients, and 32 control participants were included. A task was used in which the memory load and the complexity of the rules were independently manipulated. This task consisted of three conditions: a simple two-rule learning condition (Condition 1), a simple four-rule learning condition (inducing an increase in memory load, Condition 2), and a complex biconditional four-rule learning condition-inducing an increase in complexity and, hence, executive control load (Condition 3). Performance of AD patients declined disproportionately when the number of simple rules that had to be memorized increased (from Condition 1 to 2). An additional increment in complexity (from Condition 2 to 3) did not, however, disproportionately affect performance of the patients. Performance of the aMCI patients did not differ from that of the control participants. In the patient group, correlation analysis showed that memory performance correlated with Condition 1 performance, whereas executive task performance correlated with Condition 2 performance. These results indicate that the reduced learning and memorization of underlying task rules explains a significant part of the diminished complex rule induction performance commonly reported in AD, although results from the correlation analysis suggest involvement of executive control functions as well. Taken together, these findings suggest that care is needed when interpreting rule induction task performance in terms of executive function deficits in these patients.
Do humans (Homo sapiens) and fish (Pterophyllum scalare) make similar numerosity judgments?
Miletto Petrazzini, Maria Elena; Agrillo, Christian; Izard, Véronique; Bisazza, Angelo
2016-11-01
Numerous studies have shown that many animal species can be trained to discriminate between stimuli differing in numerosity. However, in the absence of generalization tests with untrained numerosities, what decision criterion was used by subjects remains unclear: the subjects may succeed by selecting a specific number of items (a criterion over absolute numerosities), or by applying a more general relative numerosity rule, for example, selecting the larger/smaller quantity of items. The latter case may require more powerful representations, supporting judgments of order ("more/less") beyond simple "same/different" judgments, but a relative numerosity rule may also be more adaptive. In previous research, we showed that guppies (Poecilia reticulata) spontaneously prefer relative numerosity rules. To date it is unclear whether this preference is shared by other fish and, more broadly, other species. Here we compared the performance of angelfish (Pterophyllum scalare) with that of human adults (Homo sapiens) in a task in which subjects were initially trained to select arrays containing 10 dots (either in 5 vs. 10 or 10 vs. 20 comparisons). Subsequently they were tested with the previously trained numerosity and a novel numerosity (respectively, 20 or 5). In the absence of explicit instructions, both species spontaneously favored a relative rule, selecting the novel numerosity. These similarities demonstrate that, beyond shared representations for numerical quantities, vertebrate species may also share a system for taking decisions about quantities. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Design and usability of heuristic‐based deliberation tools for women facing amniocentesis
Durand, Marie‐Anne; Wegwarth, Odette; Boivin, Jacky; Elwyn, Glyn
2011-01-01
Abstract Background Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health‐care decisions), fast and frugal decision‐making strategies (heuristics) may perform better than complex rules of reasoning. Objective To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). Design The ‘Take The Best’ heuristic (i.e. selection of a ‘most important reason’) and ‘The Tallying’ integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web‐based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health‐care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of ‘your most important reason’ (Take The Best) and ‘weighing it up’ (Tallying). Results Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health‐care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that ‘weighing it up’ and ‘your most important reason’ were not appropriate when facing such a difficult and emotional decision. Conclusion Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real‐world decisions about amniocentesis. PMID:21241434
Economic modelling with low-cognition agents
NASA Astrophysics Data System (ADS)
Ormerod, Paul
2006-10-01
The standard socio-economic model (SSSM) postulates very considerable cognitive powers on the part of its agents. They are able to gather all relevant information in any given situation, and to take the optimal decision on the basis of it, given their tastes and preferences. This behavioural rule is postulated to be universal. The concept of bounded rationality relaxes this somewhat, by permitting agents to have access to only limited amounts of information. But agents still optimise subject to their information set and tastes. Empirical work in economics over the past 20 years or so has shown that in general these behavioural postulates lack empirical validity. Instead, agents appear to have limited ability to gather information, and use simple rules of thumb to process the information which they have in order to take decisions. Building theoretical models on these realistic foundations which give better accounts of empirical phenomena than does the SSSM is an important challenge to both economists and econophysicists. Considerable progress has already been made in a short space of time, and examples are given in this paper.
NASA Technical Reports Server (NTRS)
Kettig, R. L.
1975-01-01
A method of classification of digitized multispectral images is developed and experimentally evaluated on actual earth resources data collected by aircraft and satellite. The method is designed to exploit the characteristic dependence between adjacent states of nature that is neglected by the more conventional simple-symmetric decision rule. Thus contextual information is incorporated into the classification scheme. The principle reason for doing this is to improve the accuracy of the classification. For general types of dependence this would generally require more computation per resolution element than the simple-symmetric classifier. But when the dependence occurs in the form of redundance, the elements can be classified collectively, in groups, therby reducing the number of classifications required.
The optimum decision rules for the oddity task.
Versfeld, N J; Dai, H; Green, D M
1996-01-01
This paper presents the optimum decision rule for an m-interval oddity task in which m-1 intervals contain the same signal and one is different or odd. The optimum decision rule depends on the degree of correlation among observations. The present approach unifies the different strategies that occur with "roved" or "fixed" experiments (Macmillan & Creelman, 1991, p. 147). It is shown that the commonly used decision rule for an m-interval oddity task corresponds to the special case of highly correlated observations. However, as is also true for the same-different paradigm, there exists a different optimum decision rule when the observations are independent. The relation between the probability of a correct response and d' is derived for the three-interval oddity task. Tables are presented of this relation for the three-, four-, and five-interval oddity task. Finally, an experimental method is proposed that allows one to determine the decision rule used by the observer in an oddity experiment.
Rosi, Alessia; Bruine de Bruin, Wändi; Del Missier, Fabio; Cavallini, Elena; Russo, Riccardo
2017-12-28
Older adults perform worse than younger adults when applying decision rules to choose between options that vary along multiple attributes. Although previous studies have shown that general fluid cognitive abilities contribute to the accurate application of decision rules, relatively little is known about which specific cognitive abilities play the most important role. We examined the independent roles of working memory, verbal fluency, semantic knowledge, and components of executive functioning. We found that age-related decline in applying decision rules was statistically mediated by age-related decline in working memory and verbal fluency. Our results have implications for theories of aging and decision-making.
Ma, Wei Ji; Shen, Shan; Dziugaite, Gintare; van den Berg, Ronald
2015-01-01
In tasks such as visual search and change detection, a key question is how observers integrate noisy measurements from multiple locations to make a decision. Decision rules proposed to model this process haven fallen into two categories: Bayes-optimal (ideal observer) rules and ad-hoc rules. Among the latter, the maximum-of-outputs (max) rule has been most prominent. Reviewing recent work and performing new model comparisons across a range of paradigms, we find that in all cases except for one, the optimal rule describes human data as well as or better than every max rule either previously proposed or newly introduced here. This casts doubt on the utility of the max rule for understanding perceptual decision-making. PMID:25584425
A Decision Making Methodology in Support of the Business Rules Lifecycle
NASA Technical Reports Server (NTRS)
Wild, Christopher; Rosca, Daniela
1998-01-01
The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.
Schaafsma, Murk; van der Deijl, Wilfred; Smits, Jacqueline M; Rahmel, Axel O; de Vries Robbé, Pieter F; Hoitsma, Andries J
2011-05-01
Organ allocation systems have become complex and difficult to comprehend. We introduced decision tables to specify the rules of allocation systems for different organs. A rule engine with decision tables as input was tested for the Kidney Allocation System (ETKAS). We compared this rule engine with the currently used ETKAS by running 11,000 historical match runs and by running the rule engine in parallel with the ETKAS on our allocation system. Decision tables were easy to implement and successful in verifying correctness, completeness, and consistency. The outcomes of the 11,000 historical matches in the rule engine and the ETKAS were exactly the same. Running the rule engine simultaneously in parallel and in real time with the ETKAS also produced no differences. Specifying organ allocation rules in decision tables is already a great step forward in enhancing the clarity of the systems. Yet, using these tables as rule engine input for matches optimizes the flexibility, simplicity and clarity of the whole process, from specification to the performed matches, and in addition this new method allows well controlled simulations. © 2011 The Authors. Transplant International © 2011 European Society for Organ Transplantation.
GROUP DECISIONS. Shared decision-making drives collective movement in wild baboons.
Strandburg-Peshkin, Ariana; Farine, Damien R; Couzin, Iain D; Crofoot, Margaret C
2015-06-19
Conflicts of interest about where to go and what to do are a primary challenge of group living. However, it remains unclear how consensus is achieved in stable groups with stratified social relationships. Tracking wild baboons with a high-resolution global positioning system and analyzing their movements relative to one another reveals that a process of shared decision-making governs baboon movement. Rather than preferentially following dominant individuals, baboons are more likely to follow when multiple initiators agree. When conflicts arise over the direction of movement, baboons choose one direction over the other when the angle between them is large, but they compromise if it is not. These results are consistent with models of collective motion, suggesting that democratic collective action emerging from simple rules is widespread, even in complex, socially stratified societies. Copyright © 2015, American Association for the Advancement of Science.
Voting systems for environmental decisions.
Burgman, Mark A; Regan, Helen M; Maguire, Lynn A; Colyvan, Mark; Justus, James; Martin, Tara G; Rothley, Kris
2014-04-01
Voting systems aggregate preferences efficiently and are often used for deciding conservation priorities. Desirable characteristics of voting systems include transitivity, completeness, and Pareto optimality, among others. Voting systems that are common and potentially useful for environmental decision making include simple majority, approval, and preferential voting. Unfortunately, no voting system can guarantee an outcome, while also satisfying a range of very reasonable performance criteria. Furthermore, voting methods may be manipulated by decision makers and strategic voters if they have knowledge of the voting patterns and alliances of others in the voting populations. The difficult properties of voting systems arise in routine decision making when there are multiple criteria and management alternatives. Because each method has flaws, we do not endorse one method. Instead, we urge organizers to be transparent about the properties of proposed voting systems and to offer participants the opportunity to approve the voting system as part of the ground rules for operation of a group. © 2014 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of the Society for Conservation Biology.
38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 38 Pensions, Bonuses, and Veterans' Relief 2 2010-07-01 2010-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...
38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 38 Pensions, Bonuses, and Veterans' Relief 2 2011-07-01 2011-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...
38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 38 Pensions, Bonuses, and Veterans' Relief 2 2013-07-01 2013-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...
38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 38 Pensions, Bonuses, and Veterans' Relief 2 2014-07-01 2014-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...
38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 38 Pensions, Bonuses, and Veterans' Relief 2 2012-07-01 2012-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...
19 CFR 177.10 - Publication of decisions.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 19 Customs Duties 2 2014-04-01 2014-04-01 false Publication of decisions. 177.10 Section 177.10... TREASURY (CONTINUED) ADMINISTRATIVE RULINGS General Ruling Procedure § 177.10 Publication of decisions. (a....8(a)(3). (b) [Reserved] (c) Changes of practice. Before the publication of a ruling which has the...
A Swarm Optimization approach for clinical knowledge mining.
Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A
2015-10-01
Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Development of clinical decision rules to predict recurrent shock in dengue
2013-01-01
Introduction Mortality from dengue infection is mostly due to shock. Among dengue patients with shock, approximately 30% have recurrent shock that requires a treatment change. Here, we report development of a clinical rule for use during a patient’s first shock episode to predict a recurrent shock episode. Methods The study was conducted in Center for Preventive Medicine in Vinh Long province and the Children’s Hospital No. 2 in Ho Chi Minh City, Vietnam. We included 444 dengue patients with shock, 126 of whom had recurrent shock (28%). Univariate and multivariate analyses and a preprocessing method were used to evaluate and select 14 clinical and laboratory signs recorded at shock onset. Five variables (admission day, purpura/ecchymosis, ascites/pleural effusion, blood platelet count and pulse pressure) were finally trained and validated by a 10-fold validation strategy with 10 times of repetition, using a logistic regression model. Results The results showed that shorter admission day (fewer days prior to admission), purpura/ecchymosis, ascites/pleural effusion, low platelet count and narrow pulse pressure were independently associated with recurrent shock. Our logistic prediction model was capable of predicting recurrent shock when compared to the null method (P < 0.05) and was not outperformed by other prediction models. Our final scoring rule provided relatively good accuracy (AUC, 0.73; sensitivity and specificity, 68%). Score points derived from the logistic prediction model revealed identical accuracy with AUCs at 0.73. Using a cutoff value greater than −154.5, our simple scoring rule showed a sensitivity of 68.3% and a specificity of 68.2%. Conclusions Our simple clinical rule is not to replace clinical judgment, but to help clinicians predict recurrent shock during a patient’s first dengue shock episode. PMID:24295509
Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition
Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan
2017-01-01
Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. PMID:29172273
Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition
Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan
2017-11-26
Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License
Occupational exposure decisions: can limited data interpretation training help improve accuracy?
Logan, Perry; Ramachandran, Gurumurthy; Mulhausen, John; Hewett, Paul
2009-06-01
Accurate exposure assessments are critical for ensuring that potentially hazardous exposures are properly identified and controlled. The availability and accuracy of exposure assessments can determine whether resources are appropriately allocated to engineering and administrative controls, medical surveillance, personal protective equipment and other programs designed to protect workers. A desktop study was performed using videos, task information and sampling data to evaluate the accuracy and potential bias of participants' exposure judgments. Desktop exposure judgments were obtained from occupational hygienists for material handling jobs with small air sampling data sets (0-8 samples) and without the aid of computers. In addition, data interpretation tests (DITs) were administered to participants where they were asked to estimate the 95th percentile of an underlying log-normal exposure distribution from small data sets. Participants were presented with an exposure data interpretation or rule of thumb training which included a simple set of rules for estimating 95th percentiles for small data sets from a log-normal population. DIT was given to each participant before and after the rule of thumb training. Results of each DIT and qualitative and quantitative exposure judgments were compared with a reference judgment obtained through a Bayesian probabilistic analysis of the sampling data to investigate overall judgment accuracy and bias. There were a total of 4386 participant-task-chemical judgments for all data collections: 552 qualitative judgments made without sampling data and 3834 quantitative judgments with sampling data. The DITs and quantitative judgments were significantly better than random chance and much improved by the rule of thumb training. In addition, the rule of thumb training reduced the amount of bias in the DITs and quantitative judgments. The mean DIT % correct scores increased from 47 to 64% after the rule of thumb training (P < 0.001). The accuracy for quantitative desktop judgments increased from 43 to 63% correct after the rule of thumb training (P < 0.001). The rule of thumb training did not significantly impact accuracy for qualitative desktop judgments. The finding that even some simple statistical rules of thumb improve judgment accuracy significantly suggests that hygienists need to routinely use statistical tools while making exposure judgments using monitoring data.
Conformance Testing: Measurement Decision Rules
NASA Technical Reports Server (NTRS)
Mimbs, Scott M.
2010-01-01
The goal of a Quality Management System (QMS) as specified in ISO 9001 and AS9100 is to provide assurance to the customer that end products meet specifications. Measuring devices, often called measuring and test equipment (MTE), are used to provide the evidence of product conformity to specified requirements. Unfortunately, processes that employ MTE can become a weak link to the overall QMS if proper attention is not given to the measurement process design, capability, and implementation. Documented "decision rules" establish the requirements to ensure measurement processes provide the measurement data that supports the needs of the QMS. Measurement data are used to make the decisions that impact all areas of technology. Whether measurements support research, design, production, or maintenance, ensuring the data supports the decision is crucial. Measurement data quality can be critical to the resulting consequences of measurement-based decisions. Historically, most industries required simplistic, one-size-fits-all decision rules for measurements. One-size-fits-all rules in some cases are not rigorous enough to provide adequate measurement results, while in other cases are overly conservative and too costly to implement. Ideally, decision rules should be rigorous enough to match the criticality of the parameter being measured, while being flexible enough to be cost effective. The goal of a decision rule is to ensure that measurement processes provide data with a sufficient level of quality to support the decisions being made - no more, no less. This paper discusses the basic concepts of providing measurement-based evidence that end products meet specifications. Although relevant to all measurement-based conformance tests, the target audience is the MTE end-user, which is anyone using MTE other than calibration service providers. Topics include measurement fundamentals, the associated decision risks, verifying conformance to specifications, and basic measurement decisions rules.
Automated rule-base creation via CLIPS-Induce
NASA Technical Reports Server (NTRS)
Murphy, Patrick M.
1994-01-01
Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.
Ma, Wei Ji; Shen, Shan; Dziugaite, Gintare; van den Berg, Ronald
2015-11-01
In tasks such as visual search and change detection, a key question is how observers integrate noisy measurements from multiple locations to make a decision. Decision rules proposed to model this process have fallen into two categories: Bayes-optimal (ideal observer) rules and ad-hoc rules. Among the latter, the maximum-of-outputs (max) rule has been the most prominent. Reviewing recent work and performing new model comparisons across a range of paradigms, we find that in all cases except for one, the optimal rule describes human data as well as or better than every max rule either previously proposed or newly introduced here. This casts doubt on the utility of the max rule for understanding perceptual decision-making. Copyright © 2015 Elsevier Ltd. All rights reserved.
Adaptive decision rules for the acquisition of nature reserves.
Turner, Will R; Wilcove, David S
2006-04-01
Although reserve-design algorithms have shown promise for increasing the efficiency of conservation planning, recent work casts doubt on the usefulness of some of these approaches in practice. Using three data sets that vary widely in size and complexity, we compared various decision rules for acquiring reserve networks over multiyear periods. We explored three factors that are often important in real-world conservation efforts: uncertain availability of sites for acquisition, degradation of sites, and overall budget constraints. We evaluated the relative strengths and weaknesses of existing optimal and heuristic decision rules and developed a new set of adaptive decision rules that combine the strengths of existing optimal and heuristic approaches. All three of the new adaptive rules performed better than the existing rules we tested under virtually all scenarios of site availability, site degradation, and budget constraints. Moreover, the adaptive rules required no additional data beyond what was readily available and were relatively easy to compute.
Parnell, S; Gottwald, T R; Cunniffe, N J; Alonso Chavez, V; van den Bosch, F
2015-09-07
Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally. © 2015 The Author(s).
Parnell, S.; Gottwald, T. R.; Cunniffe, N. J.; Alonso Chavez, V.; van den Bosch, F.
2015-01-01
Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally. PMID:26336177
Correlated pay-offs are key to cooperation
Frommen, Joachim G.; Riehl, Christina
2016-01-01
The general belief that cooperation and altruism in social groups result primarily from kin selection has recently been challenged, not least because results from cooperatively breeding insects and vertebrates have shown that groups may be composed mainly of non-relatives. This allows testing predictions of reciprocity theory without the confounding effect of relatedness. Here, we review complementary and alternative evolutionary mechanisms to kin selection theory and provide empirical examples of cooperative behaviour among unrelated individuals in a wide range of taxa. In particular, we focus on the different forms of reciprocity and on their underlying decision rules, asking about evolutionary stability, the conditions selecting for reciprocity and the factors constraining reciprocal cooperation. We find that neither the cognitive requirements of reciprocal cooperation nor the often sequential nature of interactions are insuperable stumbling blocks for the evolution of reciprocity. We argue that simple decision rules such as ‘help anyone if helped by someone’ should get more attention in future research, because empirical studies show that animals apply such rules, and theoretical models find that they can create stable levels of cooperation under a wide range of conditions. Owing to its simplicity, behaviour based on such a heuristic may in fact be ubiquitous. Finally, we argue that the evolution of exchange and trading of service and commodities among social partners needs greater scientific focus. PMID:26729924
Decision Rules Used in Academic Program Closure: Where the Rubber Meets the Road.
ERIC Educational Resources Information Center
Eckel, Peter D.
This study examines, from an organizational perspective, decision rules guiding program discontinuance, testing the framework of decision rule rationality versus action rationality. A multi-site case study method was used; interviews were conducted with 11-16 individuals at each of four research I or II universities that had discontinued at least…
Fific, Mario; Little, Daniel R; Nosofsky, Robert M
2010-04-01
We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli along a set of component dimensions. Those independent decisions are then combined via logical rules to determine the overall categorization response. The time course of the independent decisions is modeled via random-walk processes operating along individual dimensions. Alternative mental architectures are used as mechanisms for combining the independent decisions to implement the logical rules. We derive fundamental qualitative contrasts for distinguishing among the predictions of the rule models and major alternative models of classification RT. We also use the models to predict detailed RT-distribution data associated with individual stimuli in tasks of speeded perceptual classification. PsycINFO Database Record (c) 2010 APA, all rights reserved.
14 CFR 16.227 - Standard of proof.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or rule in a party's favor only if the decision or ruling...
Presenting Germany's drug pricing rule as a cost-per-QALY rule.
Gandjour, Afschin
2012-06-01
In Germany, the Institute for Quality and Efficiency in Health Care (IQWiG) makes recommendations for ceiling prices of drugs based on an evaluation of the relationship between costs and effectiveness. To set ceiling prices, IQWiG uses the following decision rule: the incremental cost-effectiveness ratio of a new drug compared with the next effective intervention should not be higher than that of the next effective intervention compared to its comparator. The purpose of this paper is to show that IQWiG's decision rule can be presented as a cost-per-QALY rule by using equity-weighted QALYs. This transformation shows where both rules share commonalities. Furthermore, it makes the underlying ethical implications of IQWiG's decision rule transparent and open to debate.
Emergency physicians' attitudes toward and use of clinical decision rules for radiography.
Graham, I D; Stiell, I G; Laupacis, A; O'Connor, A M; Wells, G A
1998-02-01
1) To assess Canadian emergency physicians' (EPs') use of and attitudes toward 2 radiographic clinical decision rules that have recently been developed and to identify physician characteristics associated with decision rule use; 2) to determine the use of CT head and cervical spine radiography by EPs and their beliefs about the appropriateness of expert recommendations supporting the routine use of these radiographic procedures; and 3) to determine the potential acceptance of clinical decision rules for CT scan in patients with minor head injury and cervical spine radiography in trauma patients. A cross-sectional anonymous mail survey of a random sample of 300 members of the Canadian Association of Emergency Physicians using Dillman's Total Design Method for mail surveys. Of 288 eligible physicians, 232 (81%) responded. More than 95% of the respondents stated they currently used the Ottawa Ankle Rules and were willing to consider using the newly developed Ottawa Knee Rule. Physician characteristics related to frequent use of the Ottawa Ankle Rules were younger age, fewer years since graduating from medical school, part time or resident employment status, working in a hospital without a CT scanner, and believing that decision rules are not oversimplified cookbook medicine or too rigid to apply. Eighty-five percent did not agree that all patients with minor head injuries should receive a CT head scan and only 3.5% stated they always refer such patients for CT scan. Similarly, 78.5% of the respondents did not agree that all trauma patients should receive cervical spine radiography and only 13.2% said they always refer such patients for cervical spine radiography. Ninety-seven and 98% stated they would be willing to consider using well-validated decision rules for CT scan of the head and cervical spine radiography, respectively. Fifty-two percent and 67% of the respondents required the proposed CT and C-spine to be 100% sensitive for identifying serious injuries, respectively. Canadian EPs are generally supportive of clinical decision rules and, in particular, have very positive attitudes toward the Ottawa Ankle and Knee Rules. Furthermore, EPs disagree with recommendations for routine use of CT head and cervical spine radiography and strongly support the development of well-validated decision rules for the use of CT head and cervical spine radiography. Most EPs expected the latter rules to be 100% sensitive for acute clinically significant lesions.
Sendi, Pedram; Al, Maiwenn J; Gafni, Amiram; Birch, Stephen
2004-05-01
Bridges and Terris (Soc. Sci. Med. (2004)) critique our paper on the alternative decision rule of economic evaluation in the presence of uncertainty and constrained resources within the context of a portfolio of health care programs (Sendi et al. Soc. Sci. Med. 57 (2003) 2207). They argue that by not adopting a formal portfolio theory approach we overlook the optimal solution. We show that these arguments stem from a fundamental misunderstanding of the alternative decision rule of economic evaluation. In particular, the portfolio theory approach advocated by Bridges and Terris is based on the same theoretical assumptions that the alternative decision rule set out to relax. Moreover, Bridges and Terris acknowledge that the proposed portfolio theory approach may not identify the optimal solution to resource allocation problems. Hence, it provides neither theoretical nor practical improvements to the proposed alternative decision rule.
Building gene expression profile classifiers with a simple and efficient rejection option in R.
Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Hafeezurrehman, Hafeez
2011-01-01
The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers. This paper presents a set of empirical decision rules that can be used to implement a rejection option in a set of multi-class classifiers widely used for the analysis of gene expression profiles. In particular, we focus on the classifiers implemented in the R Language and Environment for Statistical Computing (R for short in the remaining of this paper). The main contribution of the proposed rules is their simplicity, which enables an easy integration with available data analysis environments. Since in the definition of a rejection model tuning of the involved parameters is often a complex and delicate task, in this paper we exploit an evolutionary strategy to automate this process. This allows the final user to maximize the rejection accuracy with minimum manual intervention. This paper shows how the use of simple decision rules can be used to help the use of complex machine learning algorithms in real experimental setups. The proposed approach is almost completely automated and therefore a good candidate for being integrated in data analysis flows in labs where the machine learning expertise required to tune traditional classifiers might not be available.
Graham, I D; Stiell, I G; Laupacis, A; McAuley, L; Howell, M; Clancy, M; Durieux, P; Simon, N; Emparanza, J I; Aginaga, J R; O'connor, A; Wells, G
2001-03-01
We evaluate the international diffusion of the Ottawa Ankle and Knee Rules and determine emergency physicians' attitudes toward clinical decision rules in general. We conducted a cross-sectional, self-administered mail survey of random samples of 500 members each of the American College of Emergency Physicians, Canadian Association of Emergency Physicians, British Association for Accident and Emergency Medicine, Spanish Society for Emergency Medicine, and all members (n=1,350) of the French Speaking Society of Emergency Physicians, France. Main outcome measures were awareness of the Ottawa Ankle and Knee Rules, reported use of these rules, and attitudes toward clinical decision rules in general. A total of 1,769 (57%) emergency physicians responded, with country-specific response rates between 49% (United States and France) and 79% (Canada). More than 69% of physicians in all countries, except Spain, were aware of the Ottawa Ankle Rules. Use of the Ottawa Ankle Rules differed by country with more than 70% of all responding Canadian and United Kingdom physicians reporting frequent use of the rules compared with fewer than one third of US, French, and Spanish physicians. The Ottawa Knee Rule was less well known and less used by physicians in all countries. Most physicians in all countries viewed decision rules as intended to improve the quality of health care (>78%), a convenient source of advice (>67%), and good educational tools (>61%). Of all physicians, those from the United States held the least positive attitudes toward decision rules. This constitutes the largest international survey of emergency physicians' attitudes toward and use of clinical decision rules. Striking differences were apparent among countries with regard to knowledge and use of decision rules. Despite similar awareness in the United States, Canada, and the United Kingdom, US physicians appeared much less likely to use the Ottawa Ankle Rules. Future research should investigate factors leading to differences in rates of diffusion among countries and address strategies to enhance dissemination and implementation of such rules in the emergency department.
An Analysis of Categorical and Quantitative Methods for Planning Under Uncertainty
Langlotz, Curtis P.; Shortliffe, Edward H.
1988-01-01
Decision theory and logical reasoning are both methods for representing and solving medical decision problems. We analyze the usefulness of these two approaches to medical therapy planning by establishing a simple correspondence between decision theory and non-monotonic logic, a formalization of categorical logical reasoning. The analysis indicates that categorical approaches to planning can be viewed as comprising two decision-theoretic concepts: probabilities (degrees of belief in planning hypotheses) and utilities (degrees of desirability of planning outcomes). We present and discuss examples of the following lessons from this decision-theoretic view of categorical (nonmonotonic) reasoning: (1) Decision theory and artificial intelligence techniques are intended to solve different components of the planning problem. (2) When considered in the context of planning under uncertainty, nonmonotonic logics do not retain the domain-independent characteristics of classical logical reasoning for planning under certainty. (3) Because certain nonmonotonic programming paradigms (e.g., frame-based inheritance, rule-based planning, protocol-based reminders) are inherently problem-specific, they may be inappropriate to employ in the solution of certain types of planning problems. We discuss how these conclusions affect several current medical informatics research issues, including the construction of “very large” medical knowledge bases.
Estimating Classification Accuracy for Complex Decision Rules Based on Multiple Scores
ERIC Educational Resources Information Center
Douglas, Karen M.; Mislevy, Robert J.
2010-01-01
Important decisions about students are made by combining multiple measures using complex decision rules. Although methods for characterizing the accuracy of decisions based on a single measure have been suggested by numerous researchers, such methods are not useful for estimating the accuracy of decisions based on multiple measures. This study…
Weiss, Volker C
2010-07-22
One of Guggenheim's many corresponding-states rules for simple fluids implies that the molar enthalpy of vaporization (determined at the temperature at which the pressure reaches 1/50th of its critical value, which approximately coincides with the normal boiling point) divided by the critical temperature has a value of roughly 5.2R, where R is the universal gas constant. For more complex fluids, such as strongly polar and ionic fluids, one must expect deviations from Guggenheim's rule. Such a deviation has far-reaching consequences for other empirical rules related to the vaporization of fluids, namely Guldberg's rule and Trouton's rule. We evaluate these characteristic quantities for simple fluids, polar fluids, hydrogen-bonding fluids, simple inorganic molten salts, and room temperature ionic liquids (RTILs). For the ionic fluids, the critical parameters are not accessible to direct experimental observation; therefore, suitable extrapolation schemes have to be applied. For the RTILs [1-n-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imides, where the alkyl chain is ethyl, butyl, hexyl, or octyl], the critical temperature is estimated by extrapolating the surface tension to zero using Guggenheim's and Eotvos' rules; the critical density is obtained using the linear-diameter rule. It is shown that the RTILs adhere to Guggenheim's master curve for the reduced surface tension of simple and moderately polar fluids, but that they deviate significantly from his rule for the reduced enthalpy of vaporization of simple fluids. Consequences for evaluating the Trouton constant of RTILs, the value of which has been discussed controversially in the literature, are indicated.
Hybrid modeling of nitrate fate in large catchments using fuzzy-rules
NASA Astrophysics Data System (ADS)
van der Heijden, Sven; Haberlandt, Uwe
2010-05-01
Especially for nutrient balance simulations, physically based ecohydrological modeling needs an abundance of measured data and model parameters, which for large catchments all too often are not available in sufficient spatial or temporal resolution or are simply unknown. For efficient large-scale studies it is thus beneficial to have methods at one's disposal which are parsimonious concerning the number of model parameters and the necessary input data. One such method is fuzzy-rule based modeling, which compared to other machine-learning techniques has the advantages to produce models (the fuzzy-rules) which are physically interpretable to a certain extent, and to allow the explicit introduction of expert knowledge through pre-defined rules. The study focuses on the application of fuzzy-rule based modeling for nitrate simulation in large catchments, in particular concerning decision support. Fuzzy-rule based modeling enables the generation of simple, efficient, easily understandable models with nevertheless satisfactory accuracy for problems of decision support. The chosen approach encompasses a hybrid metamodeling, which includes the generation of fuzzy-rules with data originating from physically based models as well as a coupling with a physically based water balance model. For the generation of the needed training data and also as coupled water balance model the ecohydrological model SWAT is employed. The conceptual model divides the nitrate pathway into three parts. The first fuzzy-module calculates nitrate leaching with the percolating water from soil surface to groundwater, the second module simulates groundwater passage, and the final module replaces the in-stream processes. The aim of this modularization is to create flexibility for using each of the modules on its own, for changing or completely replacing it. For fuzzy-rule based modeling this can explicitly mean that the re-training of one of the modules with newly available data will be possible without problem, while the module assembly does not have to be modified. Apart from the concept of hybrid metamodeling first results are presented for the fuzzy-module for nitrate passage through the unsaturated zone.
Li, Jinhua; Xia, Dongpo; Sun, Binghua; Zhang, Dao
2015-01-01
Collective behavior has recently attracted a great deal of interest in both natural and social sciences. While the role of leadership has been closely scrutinized, the rules used by joiners in collective decision making have received far less attention. Two main hypotheses have been proposed concerning these rules: mimetism and quorum. Mimetism predicts that individuals are increasingly likely to join collective behavior as the number of participants increases. It can be further divided into selective mimetism, where relationships among the participants affect the process, and anonymous mimetism, where no such effect exists. Quorum predicts that a collective behavior occurs when the number of participants reaches a threshold. To probe into which rule is used in collective decision making, we conducted a study on the joining process in a group of free-ranging Tibetan macaques (Macaca thibetana) in Huangshan, China using a combination of all-occurrence and focal animal sampling methods. Our results show that the earlier individuals joined movements, the more central a role they occupied among the joining network. We also found that when less than three adults participated in the first five minutes of the joining process, no entire group movement occurred subsequently. When the number of these early joiners ranged from three to six, selective mimetism was used. This means higher rank or closer social affiliation of early joiners could be among the factors of deciding whether to participate in movements by group members. When the number of early joiners reached or exceeded seven, which was the simple majority of the group studied, entire group movement always occurred, meaning that the quorum rule was used. Putting together, Macaca thibetana used a combination of selective mimetism and quorum, and early joiners played a key role in deciding which rule should be used. PMID:25992882
Narrative dynamics in social groups: A discrete choice model
NASA Astrophysics Data System (ADS)
Antoci, A.; Bellanca, N.; Galdi, G.; Sodini, M.
2018-05-01
Individuals follow different rules for action: they react swiftly, grasping the short-term advantages in sight, or they waste cognitive resources to complete otherwise easy tasks, but they are able to plan ahead future complex decisions. Scholars from different disciplines studied the conditions under which either decision rule may enhance the fitness of its adopters, with a focus on the environmental features. However, we here propose that a crucial feature of the evolution of populations and their decision rules is rather inter-group interactions. Indeed, we study what happens when two groups support different decision rules, encapsulated in narratives, and their populations interact with each other. In particular, we assume that the payoff of each rule depends on the share of both social groups which adopt such rules. We then describe the most salient dynamics scenarios and identify the conditions which lead to chaotic dynamics and multistability regimes.
The US Court of Appeals for the D.C. Circuit Ruling to Stay the CSAPR
The United States Court of Appeals for the D.C. Circuit issued its ruling to stay the CSAPR pending judicial review. The court's decision is not a decision on the merits of the rule. EPA is ensuring the transition back to the Clean Air Interstate Rule.
Yang, Zheng Rong; Thomson, Rebecca; Hodgman, T Charles; Dry, Jonathan; Doyle, Austin K; Narayanan, Ajit; Wu, XiKun
2003-11-01
This paper presents an algorithm which is able to extract discriminant rules from oligopeptides for protease proteolytic cleavage activity prediction. The algorithm is developed using genetic programming. Three important components in the algorithm are a min-max scoring function, the reverse Polish notation (RPN) and the use of minimum description length. The min-max scoring function is developed using amino acid similarity matrices for measuring the similarity between an oligopeptide and a rule, which is a complex algebraic equation of amino acids rather than a simple pattern sequence. The Fisher ratio is then calculated on the scoring values using the class label associated with the oligopeptides. The discriminant ability of each rule can therefore be evaluated. The use of RPN makes the evolutionary operations simpler and therefore reduces the computational cost. To prevent overfitting, the concept of minimum description length is used to penalize over-complicated rules. A fitness function is therefore composed of the Fisher ratio and the use of minimum description length for an efficient evolutionary process. In the application to four protease datasets (Trypsin, Factor Xa, Hepatitis C Virus and HIV protease cleavage site prediction), our algorithm is superior to C5, a conventional method for deriving decision trees.
A Simple Computer-Aided Three-Dimensional Molecular Modeling for the Octant Rule
ERIC Educational Resources Information Center
Kang, Yinan; Kang, Fu-An
2011-01-01
The Moffitt-Woodward-Moscowitz-Klyne-Djerassi octant rule is one of the most successful empirical rules in organic chemistry. However, the lack of a simple effective modeling method for the octant rule in the past 50 years has posed constant difficulties for researchers, teachers, and students, particularly the young generations, to learn and…
Raposo, Letícia M; Nobre, Flavio F
2017-08-30
Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.
NASA Astrophysics Data System (ADS)
Malekmohammadi, Bahram; Ramezani Mehrian, Majid; Jafari, Hamid Reza
2012-11-01
One of the most important water-resources management strategies for arid lands is managed aquifer recharge (MAR). In establishing a MAR scheme, site selection is the prime prerequisite that can be assisted by geographic information system (GIS) tools. One of the most important uncertainties in the site-selection process using GIS is finite ranges or intervals resulting from data classification. In order to reduce these uncertainties, a novel method has been developed involving the integration of multi-criteria decision making (MCDM), GIS, and a fuzzy inference system (FIS). The Shemil-Ashkara plain in the Hormozgan Province of Iran was selected as the case study; slope, geology, groundwater depth, potential for runoff, land use, and groundwater electrical conductivity have been considered as site-selection factors. By defining fuzzy membership functions for the input layers and the output layer, and by constructing fuzzy rules, a FIS has been developed. Comparison of the results produced by the proposed method and the traditional simple additive weighted (SAW) method shows that the proposed method yields more precise results. In conclusion, fuzzy-set theory can be an effective method to overcome associated uncertainties in classification of geographic information data.
Neural net diagnostics for VLSI test
NASA Technical Reports Server (NTRS)
Lin, T.; Tseng, H.; Wu, A.; Dogan, N.; Meador, J.
1990-01-01
This paper discusses the application of neural network pattern analysis algorithms to the IC fault diagnosis problem. A fault diagnostic is a decision rule combining what is known about an ideal circuit test response with information about how it is distorted by fabrication variations and measurement noise. The rule is used to detect fault existence in fabricated circuits using real test equipment. Traditional statistical techniques may be used to achieve this goal, but they can employ unrealistic a priori assumptions about measurement data. Our approach to this problem employs an adaptive pattern analysis technique based on feedforward neural networks. During training, a feedforward network automatically captures unknown sample distributions. This is important because distributions arising from the nonlinear effects of process variation can be more complex than is typically assumed. A feedforward network is also able to extract measurement features which contribute significantly to making a correct decision. Traditional feature extraction techniques employ matrix manipulations which can be particularly costly for large measurement vectors. In this paper we discuss a software system which we are developing that uses this approach. We also provide a simple example illustrating the use of the technique for fault detection in an operational amplifier.
46 CFR 201.159 - Decisions; contents and service.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 46 Shipping 8 2012-10-01 2012-10-01 false Decisions; contents and service. 201.159 Section 201.159 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION POLICY, PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Briefs, Requests for Findings, Decisions, Exceptions (Rule 16) § 201.159 Decisions; contents and service. All initial,...
Mellers, B A; Schwartz, A; Cooke, A D
1998-01-01
For many decades, research in judgment and decision making has examined behavioral violations of rational choice theory. In that framework, rationality is expressed as a single correct decision shared by experimenters and subjects that satisfies internal coherence within a set of preferences and beliefs. Outside of psychology, social scientists are now debating the need to modify rational choice theory with behavioral assumptions. Within psychology, researchers are debating assumptions about errors for many different definitions of rationality. Alternative frameworks are being proposed. These frameworks view decisions as more reasonable and adaptive that previously thought. For example, "rule following." Rule following, which occurs when a rule or norm is applied to a situation, often minimizes effort and provides satisfying solutions that are "good enough," though not necessarily the best. When rules are ambiguous, people look for reasons to guide their decisions. They may also let their emotions take charge. This chapter presents recent research on judgment and decision making from traditional and alternative frameworks.
Extraneous factors in judicial decisions
Danziger, Shai; Levav, Jonathan; Avnaim-Pesso, Liora
2011-01-01
Are judicial rulings based solely on laws and facts? Legal formalism holds that judges apply legal reasons to the facts of a case in a rational, mechanical, and deliberative manner. In contrast, legal realists argue that the rational application of legal reasons does not sufficiently explain the decisions of judges and that psychological, political, and social factors influence judicial rulings. We test the common caricature of realism that justice is “what the judge ate for breakfast” in sequential parole decisions made by experienced judges. We record the judges’ two daily food breaks, which result in segmenting the deliberations of the day into three distinct “decision sessions.” We find that the percentage of favorable rulings drops gradually from ≈65% to nearly zero within each decision session and returns abruptly to ≈65% after a break. Our findings suggest that judicial rulings can be swayed by extraneous variables that should have no bearing on legal decisions. PMID:21482790
Acute knee injuries: use of decision rules for selective radiograph ordering.
Tandeter, H B; Shvartzman, P; Stevens, Max A
1999-12-01
Family physicians often encounter patients with acute knee trauma. Radiographs of injured knees are commonly ordered, even though fractures are found in only 6 percent of such patients and emergency department physicians can usually discriminate clinically between fracture and nonfracture. Decision rules have been developed to reduce the unnecessary use of radiologic studies in patients with acute knee injury. The Ottawa knee rules and the Pittsburgh decision rules are the latest guidelines for the selective use of radiographs in knee trauma. Application of these rules may lead to a more efficient evaluation of knee injuries and a reduction in health costs without an increase in adverse outcomes.
SIRE: A Simple Interactive Rule Editor for NICBES
NASA Technical Reports Server (NTRS)
Bykat, Alex
1988-01-01
To support evolution of domain expertise, and its representation in an expert system knowledge base, a user-friendly rule base editor is mandatory. The Nickel Cadmium Battery Expert System (NICBES), a prototype of an expert system for the Hubble Space Telescope power storage management system, does not provide such an editor. In the following, a description of a Simple Interactive Rule Base Editor (SIRE) for NICBES is described. The SIRE provides a consistent internal representation of the NICBES knowledge base. It supports knowledge presentation and provides a user-friendly and code language independent medium for rule addition and modification. The SIRE is integrated with NICBES via an interface module. This module provides translation of the internal representation to Prolog-type rules (Horn clauses), latter rule assertion, and a simple mechanism for rule selection for its Prolog inference engine.
Collective decision making and social interaction rules in mixed-species flocks of songbirds
Farine, Damien R.; Aplin, Lucy M.; Garroway, Colin J.; Mann, Richard P.; Sheldon, Ben C.
2014-01-01
Associations in mixed-species foraging groups are common in animals, yet have rarely been explored in the context of collective behaviour. Despite many investigations into the social and ecological conditions under which individuals should form groups, we still know little about the specific behavioural rules that individuals adopt in these contexts, or whether these can be generalized to heterospecifics. Here, we studied collective behaviour in flocks in a community of five species of woodland passerine birds. We adopted an automated data collection protocol, involving visits by RFID-tagged birds to feeding stations equipped with antennae, over two winters, recording 91 576 feeding events by 1904 individuals. We demonstrated highly synchronized feeding behaviour within patches, with birds moving towards areas of the patch with the largest proportion of the flock. Using a model of collective decision making, we then explored the underlying decision rule birds may be using when foraging in mixed-species flocks. The model tested whether birds used a different decision rule for conspecifics and heterospecifics, and whether the rules used by individuals of different species varied. We found that species differed in their response to the distribution of conspecifics and heterospecifics across foraging patches. However, simulating decisions using the different rules, which reproduced our data well, suggested that the outcome of using different decision rules by each species resulted in qualitatively similar overall patterns of movement. It is possible that the decision rules each species uses may be adjusted to variation in mean species abundance in order for individuals to maintain the same overall flock-level response. This is likely to be important for maintaining coordinated behaviour across species, and to result in quick and adaptive flock responses to food resources that are patchily distributed in space and time. PMID:25214653
Utility of Decision Rules for Transcutaneous Bilirubin Measurements
Burgos, Anthony E.; Flaherman, Valerie; Chung, Esther K.; Simpson, Elizabeth A.; Goyal, Neera K.; Von Kohorn, Isabelle; Dhepyasuwan, Niramol
2016-01-01
BACKGROUND: Transcutaneous bilirubin (TcB) meters are widely used for screening newborns for jaundice, with a total serum bilirubin (TSB) measurement indicated when the TcB value is classified as “positive” by using a decision rule. The goal of our study was to assess the clinical utility of 3 recommended TcB screening decision rules. METHODS: Paired TcB/TSB measurements were collected at 34 newborn nursery sites. At 27 sites (sample 1), newborns were routinely screened with a TcB measurement. For sample 2, sites that typically screen with TSB levels also obtained a TcB measurement for the study. Three decision rules to define a positive TcB measurement were evaluated: ≥75th percentile on the Bhutani nomogram, 70% of the phototherapy level, and within 3 mg/dL of the phototherapy threshold. The primary outcome was a TSB level at/above the phototherapy threshold. The rate of false-negative TcB screens and percentage of blood draws avoided were calculated for each decision rule. RESULTS: For sample 1, data were analyzed on 911 paired TcB-TSB measurements from a total of 8316 TcB measurements. False-negative rates were <10% with all decision rules; none identified all 31 newborns with a TSB level at/above the phototherapy threshold. The percentage of blood draws avoided ranged from 79.4% to 90.7%. In sample 2, each rule correctly identified all 8 newborns with TSB levels at/above the phototherapy threshold. CONCLUSIONS: Although all of the decision rules can be used effectively to screen newborns for jaundice, each will “miss” some infants with a TSB level at/above the phototherapy threshold. PMID:27244792
Hoover, Kevin M.; Bubak, Andrew N.; Law, Isaac J.; Yaeger, Jazmine D. W.; Renner, Kenneth J.; Swallow, John G.; Greene, Michael J.
2016-01-01
Abstract Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant’s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions. PMID:29491915
Hoover, Kevin M; Bubak, Andrew N; Law, Isaac J; Yaeger, Jazmine D W; Renner, Kenneth J; Swallow, John G; Greene, Michael J
2016-06-01
Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant's brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions.
16 CFR 3.51 - Initial decision.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Initial decision. 3.51 Section 3.51 Commercial Practices FEDERAL TRADE COMMISSION ORGANIZATION, PROCEDURES AND RULES OF PRACTICE RULES OF PRACTICE FOR ADJUDICATIVE PROCEEDINGS Decision § 3.51 Initial decision. (a) When filed and when effective. The Administrative Law Judge shall file an...
16 CFR 3.52 - Appeal from initial decision.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Appeal from initial decision. 3.52 Section 3.52 Commercial Practices FEDERAL TRADE COMMISSION ORGANIZATION, PROCEDURES AND RULES OF PRACTICE RULES OF PRACTICE FOR ADJUDICATIVE PROCEEDINGS Decision § 3.52 Appeal from initial decision. (a) Automatic review of cases in which the Commission sough...
49 CFR 1503.631 - Interlocutory appeals.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Rules of Practice in TSA Civil Penalty Actions § 1503.631 Interlocutory appeals. (a) General. Unless otherwise provided in this subpart, a party may not appeal a ruling or decision of the ALJ to the TSA decision maker until the initial decision has been entered on the record. A decision or order of the TSA...
Is there a need for a clinical decision rule in blunt wrist trauma?
van den Brand, Crispijn L; van Leerdam, Roderick H; van Ufford, Jet H M E Quarles; Rhemrev, Steven J
2013-11-01
Blunt wrist trauma is a very common injury in emergency medicine. However, in contrast to other extremity trauma, there is no clinical decision rule for radiography in patients with blunt wrist trauma. The purpose of this study is to describe current practice and to assess the need and feasibility for a clinical decision rule for radiography in patients with blunt wrist trauma. All patients with blunt wrist trauma who presented to our Emergency Department (ED) during a 6-month period were included in this study. Basic demographics were analysed and the radiography ratio was determined. The radiography results were compared for different demographic groups. Current practice and the need and feasibility for a decision rule were evaluated using Stiell's checklist for clinical decision rules. A total of 1019 patients with 1032 blunt wrist injuries presented at our ED in a period of 6 months. In 91.4% of patients, radiographs were taken. In 41.6% of those radiographed, a fracture was visible on plain radiography. Fractures were most common in the paediatric and senior age groups. However, even in the lower-risk groups we observed a fracture incidence of about 20%. There is no need for a clinical decision rule for radiography in patients with blunt wrist trauma because the fracture ratio is high. Neither does it seem feasible to develop a highly sensitive and efficient decision rule. Therefore, the authors recommend radiography in all patients with blunt wrist trauma presenting to the ED. Copyright © 2013 Elsevier Ltd. All rights reserved.
Medical ethics: four principles plus attention to scope.
Gillon, R
1994-07-16
The "four principles plus scope" approach provides a simple, accessible, and culturally neutral approach to thinking about ethical issues in health care. The approach, developed in the United States, is based on four common, basic prima facie moral commitments--respect for autonomy, beneficence, nonmaleficence, and justice--plus concern for their scope of application. It offers a common, basic moral analytical framework and a common, basic moral language. Although they do not provide ordered rules, these principles can help doctors and other health care workers to make decisions when reflecting on moral issues that arise at work.
Decision theory applied to image quality control in radiology.
Lessa, Patrícia S; Caous, Cristofer A; Arantes, Paula R; Amaro, Edson; de Souza, Fernando M Campello
2008-11-13
The present work aims at the application of the decision theory to radiological image quality control (QC) in diagnostic routine. The main problem addressed in the framework of decision theory is to accept or reject a film lot of a radiology service. The probability of each decision of a determined set of variables was obtained from the selected films. Based on a radiology service routine a decision probability function was determined for each considered group of combination characteristics. These characteristics were related to the film quality control. These parameters were also framed in a set of 8 possibilities, resulting in 256 possible decision rules. In order to determine a general utility application function to access the decision risk, we have used a simple unique parameter called r. The payoffs chosen were: diagnostic's result (correct/incorrect), cost (high/low), and patient satisfaction (yes/no) resulting in eight possible combinations. Depending on the value of r, more or less risk will occur related to the decision-making. The utility function was evaluated in order to determine the probability of a decision. The decision was made with patients or administrators' opinions from a radiology service center. The model is a formal quantitative approach to make a decision related to the medical imaging quality, providing an instrument to discriminate what is really necessary to accept or reject a film or a film lot. The method presented herein can help to access the risk level of an incorrect radiological diagnosis decision.
A neural network model of foraging decisions made under predation risk.
Coleman, Scott L; Brown, Vincent R; Levine, Daniel S; Mellgren, Roger L
2005-12-01
This article develops the cognitive-emotional forager (CEF) model, a novel application of a neural network to dynamical processes in foraging behavior. The CEF is based on a neural network known as the gated dipole, introduced by Grossberg, which is capable of representing short-term affective reactions in a manner similar to Solomon and Corbit's (1974) opponent process theory. The model incorporates a trade-off between approach toward food and avoidance of predation under varying levels of motivation induced by hunger. The results of simulations in a simple patch selection paradigm, using a lifetime fitness criterion for comparison, indicate that the CEF model is capable of nearly optimal foraging and outperforms a run-of-luck rule-of-thumb model. Models such as the one presented here can illuminate the underlying cognitive and motivational components of animal decision making.
Expert systems for automated maintenance of a Mars oxygen production system
NASA Astrophysics Data System (ADS)
Huang, Jen-Kuang; Ho, Ming-Tsang; Ash, Robert L.
1992-08-01
Application of expert system concepts to a breadboard Mars oxygen processor unit have been studied and tested. The research was directed toward developing the methodology required to enable autonomous operation and control of these simple chemical processors at Mars. Failure detection and isolation was the key area of concern, and schemes using forward chaining, backward chaining, knowledge-based expert systems, and rule-based expert systems were examined. Tests and simulations were conducted that investigated self-health checkout, emergency shutdown, and fault detection, in addition to normal control activities. A dynamic system model was developed using the Bond-Graph technique. The dynamic model agreed well with tests involving sudden reductions in throughput. However, nonlinear effects were observed during tests that incorporated step function increases in flow variables. Computer simulations and experiments have demonstrated the feasibility of expert systems utilizing rule-based diagnosis and decision-making algorithms.
Holt, Johnson; Leach, Adrian W; Schrader, Gritta; Petter, Françoise; MacLeod, Alan; van der Gaag, Dirk Jan; Baker, Richard H A; Mumford, John D
2014-01-01
Utility functions in the form of tables or matrices have often been used to combine discretely rated decision-making criteria. Matrix elements are usually specified individually, so no one rule or principle can be easily stated for the utility function as a whole. A series of five matrices are presented that aggregate criteria two at a time using simple rules that express a varying degree of constraint of the lower rating over the higher. A further nine possible matrices were obtained by using a different rule either side of the main axis of the matrix to describe situations where the criteria have a differential influence on the outcome. Uncertainties in the criteria are represented by three alternative frequency distributions from which the assessors select the most appropriate. The output of the utility function is a distribution of rating frequencies that is dependent on the distributions of the input criteria. In pest risk analysis (PRA), seven of these utility functions were required to mimic the logic by which assessors for the European and Mediterranean Plant Protection Organization arrive at an overall rating of pest risk. The framework enables the development of PRAs that are consistent and easy to understand, criticize, compare, and change. When tested in workshops, PRA practitioners thought that the approach accorded with both the logic and the level of resolution that they used in the risk assessments. © 2013 Society for Risk Analysis.
Concurrent approach for evolving compact decision rule sets
NASA Astrophysics Data System (ADS)
Marmelstein, Robert E.; Hammack, Lonnie P.; Lamont, Gary B.
1999-02-01
The induction of decision rules from data is important to many disciplines, including artificial intelligence and pattern recognition. To improve the state of the art in this area, we introduced the genetic rule and classifier construction environment (GRaCCE). It was previously shown that GRaCCE consistently evolved decision rule sets from data, which were significantly more compact than those produced by other methods (such as decision tree algorithms). The primary disadvantage of GRaCCe, however, is its relatively poor run-time execution performance. In this paper, a concurrent version of the GRaCCE architecture is introduced, which improves the efficiency of the original algorithm. A prototype of the algorithm is tested on an in- house parallel processor configuration and the results are discussed.
Tongsong, Theera; Tinnangwattana, Dangcheewan; Vichak-Ururote, Linlada; Tontivuthikul, Paponrad; Charoenratana, Cholaros; Lerthiranwong, Thitikarn
2016-01-01
To compare diagnostic performance in differentiating benign from malignant ovarian masses between IOTA (the International Ovarian Tumor Analysis) simple rules and subjective sonographic assessment. Women scheduled for elective surgery because of ovarian masses were recruited into the study and underwent ultrasound examination within 24 hours of surgery to apply the IOTA simple rules by general gynecologists and to record video clips for subjective assessment by an experienced sonographer. The diagnostic performance of the IOTA rules and subjective assessment for differentiation between benign and malignant masses was compared. The gold standard diagnosis was pathological or operative findings. A total of 150 ovarian masses were covered, comprising 105 (70%) benign and 45 (30%) malignant. Of them, the IOTA simple rules could be applied in 119 (79.3%) and were inconclusive in 31 (20.7%) whereas subjective assessment could be applied in all cases (100%). The sensitivity and the specificity of the IOTA simple rules and subjective assessment were not significantly different, 82.9% vs 86.7% and 94.0% vs 94.3% respectively. The agreement of the two methods in prediction was high with a Kappa index of 0.835. Both techniques had a high diagnostic performance in differentiation between benign and malignant ovarian masses but the IOTA rules had a relatively high rate of inconclusive results. The IOTA rules can be used as an effective screening technique by general gynecologists but when the results are inconclusive they should consult experienced sonographers.
Collective decision making in cohesive flocks
NASA Astrophysics Data System (ADS)
Bhattacharya, K.; Vicsek, Tamás
2010-09-01
Most of us must have been fascinated by the eye-catching displays of collectively moving animals. Schools of fish can move in a rather orderly fashion and then change direction amazingly abruptly. There are a large number of further examples both from the living and the non-living world for phenomena during which the many interacting, permanently moving units seem to arrive at a common behavioural pattern taking place in a short time. As a paradigm of this type of phenomena we consider the problem of how birds arrive at a decision resulting in their synchronized landing. We introduce a simple model to interpret this process. Collective motion prior to landing is modelled using a simple self-propelled particle (SPP) system with a new kind of boundary condition, while the tendency and the sudden propagation of the intention of landing are introduced through rules analogous to the random field Ising model in an external field. We show that our approach is capable of capturing the most relevant features of collective decision making in a system of units with variance of individual intentions and being under an increasing level of pressure to switch states. We find that as a function of the few parameters of our model the collective switching from the flying to the landing state is indeed much sharper than the distribution of individual landing intentions. The transition is accompanied by a number of interesting features discussed in this paper.
Automatic rule generation for high-level vision
NASA Technical Reports Server (NTRS)
Rhee, Frank Chung-Hoon; Krishnapuram, Raghu
1992-01-01
A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...
Code of Federal Regulations, 2014 CFR
2014-01-01
... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...
Code of Federal Regulations, 2010 CFR
2010-01-01
... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...
Code of Federal Regulations, 2013 CFR
2013-01-01
... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...
Code of Federal Regulations, 2012 CFR
2012-01-01
... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...
14 CFR 16.227 - Standard of proof.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or shall rule in a party's favor only if the decision or...
14 CFR 16.227 - Standard of proof.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or shall rule in a party's favor only if the decision or...
14 CFR 16.227 - Standard of proof.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or shall rule in a party's favor only if the decision or...
14 CFR 16.227 - Standard of proof.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or shall rule in a party's favor only if the decision or...
Linan, Margaret K; Sottara, Davide; Freimuth, Robert R
2015-01-01
Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines.
Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Yu, Kai; Shortreed, Susan M.; Pronk, Anjoeka; Stewart, Patricia A.; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Silverman, Debra T.; Friesen, Melissa C.
2014-01-01
Objectives Evaluating occupational exposures in population-based case-control studies often requires exposure assessors to review each study participants' reported occupational information job-by-job to derive exposure estimates. Although such assessments likely have underlying decision rules, they usually lack transparency, are time-consuming and have uncertain reliability and validity. We aimed to identify the underlying rules to enable documentation, review, and future use of these expert-based exposure decisions. Methods Classification and regression trees (CART, predictions from a single tree) and random forests (predictions from many trees) were used to identify the underlying rules from the questionnaire responses and an expert's exposure assignments for occupational diesel exhaust exposure for several metrics: binary exposure probability and ordinal exposure probability, intensity, and frequency. Data were split into training (n=10,488 jobs), testing (n=2,247), and validation (n=2,248) data sets. Results The CART and random forest models' predictions agreed with 92–94% of the expert's binary probability assignments. For ordinal probability, intensity, and frequency metrics, the two models extracted decision rules more successfully for unexposed and highly exposed jobs (86–90% and 57–85%, respectively) than for low or medium exposed jobs (7–71%). Conclusions CART and random forest models extracted decision rules and accurately predicted an expert's exposure decisions for the majority of jobs and identified questionnaire response patterns that would require further expert review if the rules were applied to other jobs in the same or different study. This approach makes the exposure assessment process in case-control studies more transparent and creates a mechanism to efficiently replicate exposure decisions in future studies. PMID:23155187
Determining rules for closing customer service centers: A public utility company's fuzzy decision
NASA Technical Reports Server (NTRS)
Dekorvin, Andre; Shipley, Margaret F.
1992-01-01
In the present work, we consider the general problem of knowledge acquisition under uncertainty. A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision was made. Unique to this work is the fuzzy set representation of the conditions or attributes upon which the decision make may base his fuzzy set decision. From our examples, we infer certain and possible rules containing fuzzy terms. It should be stressed that the procedure determines how closely the expert follows the conditions under consideration in making his decision. We offer two examples pertaining to the possible decision to close a customer service center of a public utility company. In the first example, the decision maker does not follow too closely the conditions. In the second example, the conditions are much more relevant to the decision of the expert.
14 CFR 302.607 - Decision by administrative law judge.
Code of Federal Regulations, 2014 CFR
2014-01-01
... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...
14 CFR 302.607 - Decision by administrative law judge.
Code of Federal Regulations, 2013 CFR
2013-01-01
... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...
14 CFR 302.607 - Decision by administrative law judge.
Code of Federal Regulations, 2010 CFR
2010-01-01
... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...
14 CFR 302.607 - Decision by administrative law judge.
Code of Federal Regulations, 2011 CFR
2011-01-01
... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...
14 CFR 302.607 - Decision by administrative law judge.
Code of Federal Regulations, 2012 CFR
2012-01-01
... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...
Jacob, Louis; Uvarova, Maria; Boulet, Sandrine; Begaj, Inva; Chevret, Sylvie
2016-06-02
Multi-Arm Multi-Stage designs aim at comparing several new treatments to a common reference, in order to select or drop any treatment arm to move forward when such evidence already exists based on interim analyses. We redesigned a Bayesian adaptive design initially proposed for dose-finding, focusing our interest in the comparison of multiple experimental drugs to a control on a binary criterion measure. We redesigned a phase II clinical trial that randomly allocates patients across three (one control and two experimental) treatment arms to assess dropping decision rules. We were interested in dropping any arm due to futility, either based on historical control rate (first rule) or comparison across arms (second rule), and in stopping experimental arm due to its ability to reach a sufficient response rate (third rule), using the difference of response probabilities in Bayes binomial trials between the treated and control as a measure of treatment benefit. Simulations were then conducted to investigate the decision operating characteristics under a variety of plausible scenarios, as a function of the decision thresholds. Our findings suggest that one experimental treatment was less efficient than the control and could have been dropped from the trial based on a sample of approximately 20 instead of 40 patients. In the simulation study, stopping decisions were reached sooner for the first rule than for the second rule, with close mean estimates of response rates and small bias. According to the decision threshold, the mean sample size to detect the required 0.15 absolute benefit ranged from 63 to 70 (rule 3) with false negative rates of less than 2 % (rule 1) up to 6 % (rule 2). In contrast, detecting a 0.15 inferiority in response rates required a sample size ranging on average from 23 to 35 (rules 1 and 2, respectively) with a false positive rate ranging from 3.6 to 0.6 % (rule 3). Adaptive trial design is a good way to improve clinical trials. It allows removing ineffective drugs and reducing the trial sample size, while maintaining unbiased estimates. Decision thresholds can be set according to predefined fixed error decision rates. ClinicalTrials.gov Identifier: NCT01342692 .
NASA Astrophysics Data System (ADS)
Liu, Xiaojia; An, Haizhong; Wang, Lijun; Guan, Qing
2017-09-01
The moving average strategy is a technical indicator that can generate trading signals to assist investment. While the trading signals tell the traders timing to buy or sell, the moving average cannot tell the trading volume, which is a crucial factor for investment. This paper proposes a fuzzy moving average strategy, in which the fuzzy logic rule is used to determine the strength of trading signals, i.e., the trading volume. To compose one fuzzy logic rule, we use four types of moving averages, the length of the moving average period, the fuzzy extent, and the recommend value. Ten fuzzy logic rules form a fuzzy set, which generates a rating level that decides the trading volume. In this process, we apply genetic algorithms to identify an optimal fuzzy logic rule set and utilize crude oil futures prices from the New York Mercantile Exchange (NYMEX) as the experiment data. Each experiment is repeated for 20 times. The results show that firstly the fuzzy moving average strategy can obtain a more stable rate of return than the moving average strategies. Secondly, holding amounts series is highly sensitive to price series. Thirdly, simple moving average methods are more efficient. Lastly, the fuzzy extents of extremely low, high, and very high are more popular. These results are helpful in investment decisions.
FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects.
Lagorce, David; Sperandio, Olivier; Galons, Hervé; Miteva, Maria A; Villoutreix, Bruno O
2008-09-24
Drug discovery and chemical biology are exceedingly complex and demanding enterprises. In recent years there are been increasing awareness about the importance of predicting/optimizing the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of small chemical compounds along the search process rather than at the final stages. Fast methods for evaluating ADMET properties of small molecules often involve applying a set of simple empirical rules (educated guesses) and as such, compound collections' property profiling can be performed in silico. Clearly, these rules cannot assess the full complexity of the human body but can provide valuable information and assist decision-making. This paper presents FAF-Drugs2, a free adaptable tool for ADMET filtering of electronic compound collections. FAF-Drugs2 is a command line utility program (e.g., written in Python) based on the open source chemistry toolkit OpenBabel, which performs various physicochemical calculations, identifies key functional groups, some toxic and unstable molecules/functional groups. In addition to filtered collections, FAF-Drugs2 can provide, via Gnuplot, several distribution diagrams of major physicochemical properties of the screened compound libraries. We have developed FAF-Drugs2 to facilitate compound collection preparation, prior to (or after) experimental screening or virtual screening computations. Users can select to apply various filtering thresholds and add rules as needed for a given project. As it stands, FAF-Drugs2 implements numerous filtering rules (23 physicochemical rules and 204 substructure searching rules) that can be easily tuned.
ERIC Educational Resources Information Center
Shockley-Zalabak, Pamela
A study of decision making processes and communication rules, in a corporate setting undergoing change as a result of organizational ineffectiveness, examined whether (1) decisions about formal communication reporting systems were linked to management assumptions about technical creativity/effectiveness, (2) assumptions about…
38 CFR 20.1401 - Rule 1401. Definitions.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 38 Pensions, Bonuses, and Veterans' Relief 2 2012-07-01 2012-07-01 false Rule 1401. Definitions... Unmistakable Error § 20.1401 Rule 1401. Definitions. (a) Issue. Unless otherwise specified, the term “issue” in this subpart means a matter upon which the Board made a final decision (other than a decision under...
38 CFR 20.1401 - Rule 1401. Definitions.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 38 Pensions, Bonuses, and Veterans' Relief 2 2011-07-01 2011-07-01 false Rule 1401. Definitions... Unmistakable Error § 20.1401 Rule 1401. Definitions. (a) Issue. Unless otherwise specified, the term “issue” in this subpart means a matter upon which the Board made a final decision (other than a decision under...
38 CFR 20.1401 - Rule 1401. Definitions.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 38 Pensions, Bonuses, and Veterans' Relief 2 2014-07-01 2014-07-01 false Rule 1401. Definitions... Unmistakable Error § 20.1401 Rule 1401. Definitions. (a) Issue. Unless otherwise specified, the term “issue” in this subpart means a matter upon which the Board made a final decision (other than a decision under...
Complexity, Training Paradigm Design, and the Contribution of Memory Subsystems to Grammar Learning
Ettlinger, Marc; Wong, Patrick C. M.
2016-01-01
Although there is variability in nonnative grammar learning outcomes, the contributions of training paradigm design and memory subsystems are not well understood. To examine this, we presented learners with an artificial grammar that formed words via simple and complex morphophonological rules. Across three experiments, we manipulated training paradigm design and measured subjects' declarative, procedural, and working memory subsystems. Experiment 1 demonstrated that passive, exposure-based training boosted learning of both simple and complex grammatical rules, relative to no training. Additionally, procedural memory correlated with simple rule learning, whereas declarative memory correlated with complex rule learning. Experiment 2 showed that presenting corrective feedback during the test phase did not improve learning. Experiment 3 revealed that structuring the order of training so that subjects are first exposed to the simple rule and then the complex improved learning. The cumulative findings shed light on the contributions of grammatical complexity, training paradigm design, and domain-general memory subsystems in determining grammar learning success. PMID:27391085
Ameye, Lieveke; Fischerova, Daniela; Epstein, Elisabeth; Melis, Gian Benedetto; Guerriero, Stefano; Van Holsbeke, Caroline; Savelli, Luca; Fruscio, Robert; Lissoni, Andrea Alberto; Testa, Antonia Carla; Veldman, Joan; Vergote, Ignace; Van Huffel, Sabine; Bourne, Tom; Valentin, Lil
2010-01-01
Objectives To prospectively assess the diagnostic performance of simple ultrasound rules to predict benignity/malignancy in an adnexal mass and to test the performance of the risk of malignancy index, two logistic regression models, and subjective assessment of ultrasonic findings by an experienced ultrasound examiner in adnexal masses for which the simple rules yield an inconclusive result. Design Prospective temporal and external validation of simple ultrasound rules to distinguish benign from malignant adnexal masses. The rules comprised five ultrasonic features (including shape, size, solidity, and results of colour Doppler examination) to predict a malignant tumour (M features) and five to predict a benign tumour (B features). If one or more M features were present in the absence of a B feature, the mass was classified as malignant. If one or more B features were present in the absence of an M feature, it was classified as benign. If both M features and B features were present, or if none of the features was present, the simple rules were inconclusive. Setting 19 ultrasound centres in eight countries. Participants 1938 women with an adnexal mass examined with ultrasound by the principal investigator at each centre with a standardised research protocol. Reference standard Histological classification of the excised adnexal mass as benign or malignant. Main outcome measures Diagnostic sensitivity and specificity. Results Of the 1938 patients with an adnexal mass, 1396 (72%) had benign tumours, 373 (19.2%) had primary invasive tumours, 111 (5.7%) had borderline malignant tumours, and 58 (3%) had metastatic tumours in the ovary. The simple rules yielded a conclusive result in 1501 (77%) masses, for which they resulted in a sensitivity of 92% (95% confidence interval 89% to 94%) and a specificity of 96% (94% to 97%). The corresponding sensitivity and specificity of subjective assessment were 91% (88% to 94%) and 96% (94% to 97%). In the 357 masses for which the simple rules yielded an inconclusive result and with available results of CA-125 measurements, the sensitivities were 89% (83% to 93%) for subjective assessment, 50% (42% to 58%) for the risk of malignancy index, 89% (83% to 93%) for logistic regression model 1, and 82% (75% to 87%) for logistic regression model 2; the corresponding specificities were 78% (72% to 83%), 84% (78% to 88%), 44% (38% to 51%), and 48% (42% to 55%). Use of the simple rules as a triage test and subjective assessment for those masses for which the simple rules yielded an inconclusive result gave a sensitivity of 91% (88% to 93%) and a specificity of 93% (91% to 94%), compared with a sensitivity of 90% (88% to 93%) and a specificity of 93% (91% to 94%) when subjective assessment was used in all masses. Conclusions The use of the simple rules has the potential to improve the management of women with adnexal masses. In adnexal masses for which the rules yielded an inconclusive result, subjective assessment of ultrasonic findings by an experienced ultrasound examiner was the most accurate diagnostic test; the risk of malignancy index and the two regression models were not useful. PMID:21156740
Implementation of clinical decision rules in the emergency department.
Stiell, Ian G; Bennett, Carol
2007-11-01
Clinical decision rules (CDRs) are tools designed to help clinicians make bedside diagnostic and therapeutic decisions. The development of a CDR involves three stages: derivation, validation, and implementation. Several criteria need to be considered when designing and evaluating the results of an implementation trial. In this article, the authors review the results of implementation studies evaluating the effect of four CDRs: the Ottawa Ankle Rules, the Ottawa Knee Rule, the Canadian C-Spine Rule, and the Canadian CT Head Rule. Four implementation studies demonstrated that the implementation of CDRs in the emergency department (ED) safely reduced the use of radiography for ankle, knee, and cervical spine injuries. However, a recent trial failed to demonstrate an impact on computed tomography imaging rates. Well-developed and validated CDRs can be successfully implemented into practice, efficiently standardizing ED care. However, further research is needed to identify barriers to implementation in order to achieve improved uptake in the ED.
Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya
2006-01-01
We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.
Evaluation of IOTA Simple Ultrasound Rules to Distinguish Benign and Malignant Ovarian Tumours.
Garg, Sugandha; Kaur, Amarjit; Mohi, Jaswinder Kaur; Sibia, Preet Kanwal; Kaur, Navkiran
2017-08-01
IOTA stands for International Ovarian Tumour Analysis group. Ovarian cancer is one of the common cancers in women and is diagnosed at later stage in majority. The limiting factor for early diagnosis is lack of standardized terms and procedures in gynaecological sonography. Introduction of IOTA rules has provided some consistency in defining morphological features of ovarian masses through a standardized examination technique. To evaluate the efficacy of IOTA simple ultrasound rules in distinguishing benign and malignant ovarian tumours and establishing their use as a tool in early diagnosis of ovarian malignancy. A hospital based case control prospective study was conducted. Patients with suspected ovarian pathology were evaluated using IOTA ultrasound rules and designated as benign or malignant. Findings were correlated with histopathological findings. Collected data was statistically analysed using chi-square test and kappa statistical method. Out of initial 55 patients, 50 patients were included in the final analysis who underwent surgery. IOTA simple rules were applicable in 45 out of these 50 patients (90%). The sensitivity for the detection of malignancy in cases where IOTA simple rules were applicable was 91.66% and the specificity was 84.84%. Accuracy was 86.66%. Classifying inconclusive cases as malignant, the sensitivity and specificity was 93% and 80% respectively. High level of agreement was found between USG and histopathological diagnosis with Kappa value as 0.323. IOTA simple ultrasound rules were highly sensitive and specific in predicting ovarian malignancy preoperatively yet being reproducible, easy to train and use.
Clean Air Interstate Rule: Changes and Modeling in AEO2010 (released in AEO2010)
2010-01-01
On December 23, 2008, the D.C. Circuit Court remanded but did not vacate the Clean Air Interstate Rule (CAIR), overriding its previous decision on February 8, 2008, to remand and vacate CAIR. The December decision, which is reflected in Annual Energy Outlook 2010 (AEO) , allows CAIR to remain in effect, providing time for the Environmental Protection Agency to modify the rule in order to address objections raised by the Court in its earlier decision. A similar rule, referred to as the Clean Air Mercury Rule (CAMR), which was to set up a cap-and-trade system for reducing mercury emissions by approximately 70%, is not represented in the AEO2010 projections, because it was vacated by the D.C. Circuit Court in February 2008.
Curral, Luis; Marques-Quinteiro, Pedro; Gomes, Catarina; Lind, Pedro G
2016-01-01
Recent theoretical contributions have suggested a theory of leadership that is grounded in complexity theory, hence regarding leadership as a complex process (i.e., nonlinear; emergent). This article tests if complexity leadership theory promotes efficiency in work groups. 40 groups of five participants each had to complete four decision making tasks using the city simulation game SimCity4. Before engaging in the four decision making tasks, participants received information regarding what sort of leadership behaviors were more adequate to help them perform better. Results suggest that if complexity leadership theory is applied, groups can achieve higher efficiency over time, when compared with other groups where complexity leadership is not applied. This study goes beyond traditional views of leadership as a centralized form of control, and presents new evidence suggesting that leadership is a collective and emergent phenomenon, anchored in simple rules of behavior.
Marques-Quinteiro, Pedro; Gomes, Catarina; Lind, Pedro G.
2016-01-01
Recent theoretical contributions have suggested a theory of leadership that is grounded in complexity theory, hence regarding leadership as a complex process (i.e., nonlinear; emergent). This article tests if complexity leadership theory promotes efficiency in work groups. 40 groups of five participants each had to complete four decision making tasks using the city simulation game SimCity4. Before engaging in the four decision making tasks, participants received information regarding what sort of leadership behaviors were more adequate to help them perform better. Results suggest that if complexity leadership theory is applied, groups can achieve higher efficiency over time, when compared with other groups where complexity leadership is not applied. This study goes beyond traditional views of leadership as a centralized form of control, and presents new evidence suggesting that leadership is a collective and emergent phenomenon, anchored in simple rules of behavior. PMID:27973596
Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks
Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu
2015-01-01
Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908
A clinical decision rule to prioritize polysomnography in patients with suspected sleep apnea.
Rodsutti, Julvit; Hensley, Michael; Thakkinstian, Ammarin; D'Este, Catherine; Attia, John
2004-06-15
To derive and validate a clinical decision rule that can help to prioritize patients who are on waiting lists for polysomnography, Prospective data collection on consecutive patients referred to a sleep center. The Newcastle Sleep Disorders Centre, University of Newcastle, NSW, Australia. Consecutive adult patients who had been scheduled for initial diagnostic polysomnography. Eight hundred and thirty-seven patients were used for derivation of the decision rule. An apnea-hypopnoea index of at least 5 was used as the cutoff point to diagnose sleep apnea. Fifteen clinical features were included in the analyses using logistic regression to construct a model from the derivation data set. Only 5 variables--age, sex, body mass index, snoring, and stopping breathing during sleep--were significantly associated with sleep apnea. A scoring scheme based on regression coefficients was developed, and the total score was trichotomized into low-, moderate-, and high-risk groups with prevalence of sleep apnea of 8%, 51%, and 82%, respectively. Color-coded tables were developed for ease of use. The clinical decision rule was validated on a separate set of 243 patients. Receiver operating characteristic analysis confirmed that the decision rule performed well, with the area under the curve being similar for both the derivation and validation sets: 0.81 and 0.79, P =.612. We conclude that this decision rule was able to accurately classify the risk of sleep apnea and will be useful for prioritizing patients with suspected sleep apnea who are on waiting lists for polysomnography.
18 CFR 385.2201 - Rules governing off-the-record communications (Rule 2201).
Code of Federal Regulations, 2010 CFR
2010-04-01
...) Relevant to the merits means capable of affecting the outcome of a proceeding, or of influencing a decision, or providing an opportunity to influence a decision, on any issue in the proceeding, but does not... Commission in a manner that permits fully informed decision making by the Commission while ensuring the...
18 CFR 385.704 - Rights of participants before initial decision (Rule 704).
Code of Federal Regulations, 2010 CFR
2010-04-01
... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Rights of participants... PROCEDURE Decisions § 385.704 Rights of participants before initial decision (Rule 704). After testimony is... good cause, deny opportunity for reply or limit the issues which may be addressed in any reply. ...
17 CFR 201.410 - Appeal of initial decisions by hearing officers.
Code of Federal Regulations, 2010 CFR
2010-04-01
... COMMISSION RULES OF PRACTICE Rules of Practice Appeal to the Commission and Commission Review § 201.410 Appeal of initial decisions by hearing officers. (a) Petition for review; when available. In any... would have been entitled to judicial review of the decision entered therein if the Commission itself had...
Wolf, Max; Krause, Jens; Carney, Patricia A; Bogart, Andy; Kurvers, Ralf H J M
2015-01-01
While collective intelligence (CI) is a powerful approach to increase decision accuracy, few attempts have been made to unlock its potential in medical decision-making. Here we investigated the performance of three well-known collective intelligence rules ("majority", "quorum", and "weighted quorum") when applied to mammography screening. For any particular mammogram, these rules aggregate the independent assessments of multiple radiologists into a single decision (recall the patient for additional workup or not). We found that, compared to single radiologists, any of these CI-rules both increases true positives (i.e., recalls of patients with cancer) and decreases false positives (i.e., recalls of patients without cancer), thereby overcoming one of the fundamental limitations to decision accuracy that individual radiologists face. Importantly, we find that all CI-rules systematically outperform even the best-performing individual radiologist in the respective group. Our findings demonstrate that CI can be employed to improve mammography screening; similarly, CI may have the potential to improve medical decision-making in a much wider range of contexts, including many areas of diagnostic imaging and, more generally, diagnostic decisions that are based on the subjective interpretation of evidence.
Medical ethics: four principles plus attention to scope.
Gillon, R.
1994-01-01
The "four principles plus scope" approach provides a simple, accessible, and culturally neutral approach to thinking about ethical issues in health care. The approach, developed in the United States, is based on four common, basic prima facie moral commitments--respect for autonomy, beneficence, nonmaleficence, and justice--plus concern for their scope of application. It offers a common, basic moral analytical framework and a common, basic moral language. Although they do not provide ordered rules, these principles can help doctors and other health care workers to make decisions when reflecting on moral issues that arise at work. Images p184-a p187-a PMID:8044100
Evolving optimised decision rules for intrusion detection using particle swarm paradigm
NASA Astrophysics Data System (ADS)
Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.
2012-12-01
The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.
Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis
NASA Astrophysics Data System (ADS)
Wang, M.; Hu, N. Q.; Qin, G. J.
2011-07-01
In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.
Code of Federal Regulations, 2010 CFR
2010-07-01
... of 38 U.S.C. 6104 and 6105, issues involved in a survivor's claim for death benefits will be decided... death benefits by survivor-prior unfavorable decisions during veteran's lifetime. 20.1106 Section 20... VETERANS' APPEALS: RULES OF PRACTICE Finality § 20.1106 Rule 1106. Claim for death benefits by survivor...
48 CFR 6101.26 - Reconsideration; amendment of decisions; new hearings [Rule 26].
Code of Federal Regulations, 2012 CFR
2012-10-01
... in 6101.27(a) (Rule 27(a)) and the reasons established by the rules of common law or equity... for granting a new hearing. Upon granting a motion for a new hearing, the Board will take additional testimony and, if a decision has been issued, either amend its findings of fact and conclusions or law or...
Federal Register 2010, 2011, 2012, 2013, 2014
2012-10-25
... provide input to decision-making for updating the Waste Confidence Decision and Rule and would not involve... Commission's tentative planning and decision-making schedule; g. Identify any cooperating agencies and, as... #0;notices is to give interested persons an opportunity to participate in #0;the rule making prior to...
Order of Verdict Consideration and Decision Rule Effects on Mock Jury Decision Making.
ERIC Educational Resources Information Center
Olaye, Imafidon M.
A study investigated the effects of order verdict consideration and decision rule on jury verdicts. After reading the summary of an actual trial, 240 mock jurors drawn from undergraduate communications classes were randomly assigned to six-member juries. Jury assignments were made under two verdict orders (ascending and descending order of…
ERIC Educational Resources Information Center
Fific, Mario; Little, Daniel R.; Nosofsky, Robert M.
2010-01-01
We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli…
Federal Register 2010, 2011, 2012, 2013, 2014
2013-04-01
... Reconsideration (MO&O) denies or dismisses petitions seeking reconsideration of certain decisions made by the Commission in the 700 MHz Second Report and Order, relating to the 698-806 MHz Band, including decisions..., public safety narrowband relocation procedures, and the decisions not to impose wholesale requirements...
2014-01-01
Background Previous efforts such as Assessing Care of Vulnerable Elders (ACOVE) provide quality indicators for assessing the care of elderly patients, but thus far little has been done to leverage this knowledge to improve care for these patients. We describe a clinical decision support system to improve general practitioner (GP) adherence to ACOVE quality indicators and a protocol for investigating impact on GPs’ adherence to the rules. Design We propose two randomized controlled trials among a group of Dutch GP teams on adherence to ACOVE quality indicators. In both trials a clinical decision support system provides un-intrusive feedback appearing as a color-coded, dynamically updated, list of items needing attention. The first trial pertains to real-time automatically verifiable rules. The second trial concerns non-automatically verifiable rules (adherence cannot be established by the clinical decision support system itself, but the GPs report whether they will adhere to the rules). In both trials we will randomize teams of GPs caring for the same patients into two groups, A and B. For the automatically verifiable rules, group A GPs receive support only for a specific inter-related subset of rules, and group B GPs receive support only for the remainder of the rules. For non-automatically verifiable rules, group A GPs receive feedback framed as actions with positive consequences, and group B GPs receive feedback framed as inaction with negative consequences. GPs indicate whether they adhere to non-automatically verifiable rules. In both trials, the main outcome measure is mean adherence, automatically derived or self-reported, to the rules. Discussion We relied on active end-user involvement in selecting the rules to support, and on a model for providing feedback displayed as color-coded real-time messages concerning the patient visiting the GP at that time, without interrupting the GP’s workflow with pop-ups. While these aspects are believed to increase clinical decision support system acceptance and its impact on adherence to the selected clinical rules, systems with these properties have not yet been evaluated. Trial registration Controlled Trials NTR3566 PMID:24642339
Evaluation of IOTA Simple Ultrasound Rules to Distinguish Benign and Malignant Ovarian Tumours
Kaur, Amarjit; Mohi, Jaswinder Kaur; Sibia, Preet Kanwal; Kaur, Navkiran
2017-01-01
Introduction IOTA stands for International Ovarian Tumour Analysis group. Ovarian cancer is one of the common cancers in women and is diagnosed at later stage in majority. The limiting factor for early diagnosis is lack of standardized terms and procedures in gynaecological sonography. Introduction of IOTA rules has provided some consistency in defining morphological features of ovarian masses through a standardized examination technique. Aim To evaluate the efficacy of IOTA simple ultrasound rules in distinguishing benign and malignant ovarian tumours and establishing their use as a tool in early diagnosis of ovarian malignancy. Materials and Methods A hospital based case control prospective study was conducted. Patients with suspected ovarian pathology were evaluated using IOTA ultrasound rules and designated as benign or malignant. Findings were correlated with histopathological findings. Collected data was statistically analysed using chi-square test and kappa statistical method. Results Out of initial 55 patients, 50 patients were included in the final analysis who underwent surgery. IOTA simple rules were applicable in 45 out of these 50 patients (90%). The sensitivity for the detection of malignancy in cases where IOTA simple rules were applicable was 91.66% and the specificity was 84.84%. Accuracy was 86.66%. Classifying inconclusive cases as malignant, the sensitivity and specificity was 93% and 80% respectively. High level of agreement was found between USG and histopathological diagnosis with Kappa value as 0.323. Conclusion IOTA simple ultrasound rules were highly sensitive and specific in predicting ovarian malignancy preoperatively yet being reproducible, easy to train and use. PMID:28969237
ERIC Educational Resources Information Center
Nahavandi, Naemeh; Mukundan, Jayakaran
2013-01-01
The present study investigated the impact of textual input enhancement and explicit rule presentation on 93 Iranian EFL learners' intake of simple past tense. Three intact general English classes in Tabriz Azad University were randomly assigned to: 1) a control group; 2) a TIE group; and 3) a TIE plus explicit rule presentation group. All…
Robson, Barry; Mushlin, Richard
2004-01-01
The physician and researcher must ultimately be able to combine qualitative and quantitative features from a variety of combinations of observations on data of many component items (i.e., many dimensions), and hence reach simple conclusions about interpretation, rational courses of action, and design. In the first paper of this series, it was noted that such needs are challenging the classical means of using statistics. Hence, the paper proposed the use of a Generalized Theory of Expected Information or "Zeta Theory". The conjoint event [a,b,c,..] is seen as a rule of association for a,b,c,.. associated with a rule strength I(a;b;c;...) = xi(s,o[a,b,c,..]) - xi (s,e[a,b,c,...]), where xi is the incomplete Zeta Function. Here, o[a,b,c,...] is the observed, and e[a,b,c,..] the expected, frequency of occurrence of conjoint event [a,b,c,...]. The present paper explores how output from this approach might be assembled in a form better suited for decision support. Related to this is the difficulty that the treatment of covariance and multivariance was previously rendered as a "fuzzy association" so that the output would fall into a similar form as the true associations, but this was a somewhat ad hoc approach in which only the final I( ) had any meaning. Users at clinical research sites had subsequently requested an alternative approach in which "effective frequencies" o[ ] and e[ ] calculated from the above variances and used to evaluate I( ) give some intuitive feeling analogous to the association treatment, and this is explored here. Though the present paper is theoretical, real examples are used to illustrate application. One clinical-genomic example illustrates experimental design by identifying data which is, or is not, statistically germane to the study. We also report on some impressions based on applying these techniques in studies of real, extensive patient record data which are now emerging, as well as on molecular design data originally studied in part to test the ability to deduce the effects of simple natural patient sequence variations ("SNPs") on patient protein activity. On the basis of these study experiences, methods of rationalizing and condensing the rules implied by associations and variances between data, as well as discussion of the difficulty of what is meant by "condensed", are presented in the Appendix.
Sanfilippo, Paul G; Hewitt, Alex W; Mackey, David A
2017-04-01
To outline and detail the importance of conditional probability in clinical decision making and discuss the various diagnostic measures eye care practitioners should be aware of in order to improve the scope of their clinical practice. We conducted a review of the importance of conditional probability in diagnostic testing for the eye care practitioner. Eye care practitioners use diagnostic tests on a daily basis to assist in clinical decision making and optimizing patient care and management. These tests provide probabilistic information that can enable the clinician to increase (or decrease) their level of certainty about the presence of a particular condition. While an understanding of the characteristics of diagnostic tests are essential to facilitate proper interpretation of test results and disease risk, many practitioners either confuse or misinterpret these measures. In the interests of their patients, practitioners should be aware of the basic concepts associated with diagnostic testing and the simple mathematical rule that underpins them. Importantly, the practitioner needs to recognize that the prevalence of a disease in the population greatly determines the clinical value of a diagnostic test.
Gimbel, Ronald W; Pirrallo, Ronald G; Lowe, Steven C; Wright, David W; Zhang, Lu; Woo, Min-Jae; Fontelo, Paul; Liu, Fang; Connor, Zachary
2018-03-12
The frequency of head computed tomography (CT) imaging for mild head trauma patients has raised safety and cost concerns. Validated clinical decision rules exist in the published literature and on-line sources to guide medical image ordering but are often not used by emergency department (ED) clinicians. Using simulation, we explored whether the presentation of a clinical decision rule (i.e. Canadian CT Head Rule - CCHR), findings from malpractice cases related to clinicians not ordering CT imaging in mild head trauma cases, and estimated patient out-of-pocket cost might influence clinician brain CT ordering. Understanding what type and how information may influence clinical decision making in the ordering advanced medical imaging is important in shaping the optimal design and implementation of related clinical decision support systems. Multi-center, double-blinded simulation-based randomized controlled trial. Following standardized clinical vignette presentation, clinicians made an initial imaging decision for the patient. This was followed by additional information on decision support rules, malpractice outcome review, and patient cost; each with opportunity to modify their initial order. The malpractice and cost information differed by assigned group to test the any temporal relationship. The simulation closed with a second vignette and an imaging decision. One hundred sixteen of the 167 participants (66.9%) initially ordered a brain CT scan. After CCHR presentation, the number of clinicians ordering a CT dropped to 76 (45.8%), representing a 21.1% reduction in CT ordering (P = 0.002). This reduction in CT ordering was maintained, in comparison to initial imaging orders, when presented with malpractice review information (p = 0.002) and patient cost information (p = 0.002). About 57% of clinicians changed their order during study, while 43% never modified their imaging order. This study suggests that ED clinician brain CT imaging decisions may be influenced by clinical decision support rules, patient out-of-pocket cost information and findings from malpractice case review. NCT03449862 , February 27, 2018, Retrospectively registered.
Rejecting the Baby Doe rules and defending a "negative" analysis of the Best Interests Standard.
Kopelman, Loretta M
2005-08-01
Two incompatible policies exist for guiding medical decisions for extremely premature, sick, or terminally ill infants, the Best Interests Standard and the newer, 20-year old "Baby Doe" Rules. The background, including why there were two sets of Baby Doe Rules, and their differences with the Best Interests Standard, are illustrated. Two defenses of the Baby Doe Rules are considered and rejected. The first, held by Reagan, Koop, and others, is a "right-to-life" defense. The second, held by some leaders of the American Academy of Pediatrics, is that the Baby Doe Rules are benign and misunderstood. The Baby Doe Rules should be rejected since they can thwart compassionate and individualized decision-making, undercut duties to minimize unnecessary suffering, and single out one group for treatment adults would not want for themselves. In these ways, they are inferior to the older Best Interests Standard. A "negative" analysis of the Best Interests Standard is articulated and defended for decision-making for all incompetent individuals.
Schiebener, Johannes; Brand, Matthias
2017-06-01
Previous literature has explained older individuals' disadvantageous decision-making under ambiguity in the Iowa Gambling Task (IGT) by reduced emotional warning signals preceding decisions. We argue that age-related reductions in IGT performance may also be explained by reductions in certain cognitive abilities (reasoning, executive functions). In 210 participants (18-86 years), we found that the age-related variance on IGT performance occurred only in the last 60 trials. The effect was mediated by cognitive abilities and their relation with decision-making performance under risk with explicit rules (Game of Dice Task). Thus, reductions in cognitive functions in older age may be associated with both a reduced ability to gain explicit insight into the rules of the ambiguous decision situation and with failure to choose the less risky options consequently after the rules have been understood explicitly. Previous literature may have underestimated the relevance of cognitive functions for age-related decline in decision-making performance under ambiguity.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Where are the rules concerning the effect of the Department not issuing a decision in my appeal within the statutory time frame? 290.107 Section... PROCEDURES Minerals Revenue Management Appeal Procedures § 290.107 Where are the rules concerning the effect...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-04-15
... package to OMB for its review and approval because the changes in this rule making do not affect the...: Final rule. SUMMARY: The United States Court of Appeals for the Federal Circuit issued a decision in Agilent Technologies, Inc. v. Affymetrix, Inc., 567 F.3d 1366 (Fed. Cir. 2009). That decision impacted the...
An overview of bipolar qualitative decision rules
NASA Astrophysics Data System (ADS)
Bonnefon, Jean-Francois; Dubois, Didier; Fargier, Hélène
Making a good decision is often a matter of listing and comparing positive and negative arguments, as studies in cognitive psychology have shown. In such cases, the evaluation scale should be considered bipolar, that is, negative and positive values are explicitly distinguished. Generally, positive and negative features are evaluated separately, as done in Cumulative Prospect Theory. However, contrary to the latter framework that presupposes genuine numerical assessments, decisions are often made on the basis of an ordinal ranking of the pros and the cons, and focusing on the most salient features, i.e., the decision process is qualitative. In this paper, we report on a project aiming at characterizing several decision rules, based on possibilistic order of magnitude reasoning, and tailored for the joint handling of positive and negative affects, and at testing their empirical validity. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case and, like them, suffer from a lack of discrimination power. More decisive rules that refine them are also proposed. They account for both the principle of Pareto-efficiency and the notion of order of magnitude reasoning. The most decisive one uses a lexicographic ranking of the pros and cons. It comes down to a special case of Cumulative Prospect Theory, and subsumes the “Take the best” heuristic.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-01-24
... which is delegated the authority to review disciplinary decisions on behalf of the Exchange Board of... organization. Under the rule, the decision of a majority of the Hearing Panel is the decision of the Hearing..., may request a determination of guilt by default, and may recommend a penalty to be imposed. If the...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-07-12
... that a refusal by a member to take action necessary to effectuate a final decision of a FINRA officer... necessary to effectuate a final decision of a FINRA officer or the UPC Committee under the UPC Code (FINRA Rule 11000 Series) or other FINRA rules that permit review of FINRA decisions by the UPC Committee...
48 CFR 6101.26 - Reconsideration; amendment of decisions; new hearings [Rule 26].
Code of Federal Regulations, 2010 CFR
2010-10-01
... amend a decision or order for any reason that would justify such action on motion of a party. (d) Effect... for granting a new hearing. Upon granting a motion for a new hearing, the Board will take additional... issue a new decision. (b) Procedure. Any motion under 6101.26 (Rule 26) shall comply with the provisions...
48 CFR 6101.26 - Reconsideration; amendment of decisions; new hearings [Rule 26].
Code of Federal Regulations, 2011 CFR
2011-10-01
... amend a decision or order for any reason that would justify such action on motion of a party. (d) Effect... for granting a new hearing. Upon granting a motion for a new hearing, the Board will take additional... issue a new decision. (b) Procedure. Any motion under 6101.26 (Rule 26) shall comply with the provisions...
An Autonomous Flight Safety System
2008-11-01
are taken. AFSS can take vehicle navigation data from redundant onboard sensors and make flight termination decisions using software-based rules...implemented on redundant flight processors. By basing these decisions on actual Instantaneous Impact Predictions and by providing for an arbitrary...number of mission rules, it is the contention of the AFSS development team that the decision making process used by Missile Flight Control Officers
Minimizing Significant Figure Fuzziness.
ERIC Educational Resources Information Center
Fields, Lawrence D.; Hawkes, Stephen J.
1986-01-01
Addresses the principles and problems associated with the use of significant figures. Explains uncertainty, the meaning of significant figures, the Simple Rule, the Three Rule, and the 1-5 Rule. Also provides examples of the Rules. (ML)
Determining rules for closing customer service centers: A public utility company's fuzzy decision
NASA Technical Reports Server (NTRS)
Dekorvin, Andre; Shipley, Margaret F.; Lea, Robert N.
1992-01-01
In the present work, we consider the general problem of knowledge acquisition under uncertainty. Simply stated, the problem reduces to the following: how can we capture the knowledge of an expert when the expert is unable to clearly formulate how he or she arrives at a decision? A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision may have been made. Unique to our work is the fuzzy set representation of the conditions or attributes upon which the expert may possibly base his fuzzy decision. From our examples, we infer certain and possible fuzzy rules for closing a customer service center and illustrate the importance of having the decision closely relate to the conditions under consideration.
78 FR 36434 - Revisions to Rules of Practice
Federal Register 2010, 2011, 2012, 2013, 2014
2013-06-18
... federal holidays, make grammatical corrections, and remove the reference to part-day holidays. Rule 3001... section, the following categories of persons are designated ``decision-making personnel'': (i) The.... The following categories of person are designated ``non-decision-making personnel'': (i) All...
Extracting decision rules from police accident reports through decision trees.
de Oña, Juan; López, Griselda; Abellán, Joaquín
2013-01-01
Given the current number of road accidents, the aim of many road safety analysts is to identify the main factors that contribute to crash severity. To pinpoint those factors, this paper shows an application that applies some of the methods most commonly used to build decision trees (DTs), which have not been applied to the road safety field before. An analysis of accidents on rural highways in the province of Granada (Spain) between 2003 and 2009 (both inclusive) showed that the methods used to build DTs serve our purpose and may even be complementary. Applying these methods has enabled potentially useful decision rules to be extracted that could be used by road safety analysts. For instance, some of the rules may indicate that women, contrary to men, increase their risk of severity under bad lighting conditions. The rules could be used in road safety campaigns to mitigate specific problems. This would enable managers to implement priority actions based on a classification of accidents by types (depending on their severity). However, the primary importance of this proposal is that other databases not used here (i.e. other infrastructure, roads and countries) could be used to identify unconventional problems in a manner easy for road safety managers to understand, as decision rules. Copyright © 2012 Elsevier Ltd. All rights reserved.
Simple modification of Oja rule limits L1-norm of weight vector and leads to sparse connectivity.
Aparin, Vladimir
2012-03-01
This letter describes a simple modification of the Oja learning rule, which asymptotically constrains the L1-norm of an input weight vector instead of the L2-norm as in the original rule. This constraining is local as opposed to commonly used instant normalizations, which require the knowledge of all input weights of a neuron to update each one of them individually. The proposed rule converges to a weight vector that is sparser (has more zero weights) than the vector learned by the original Oja rule with or without the zero bound, which could explain the developmental synaptic pruning.
Form and Objective of the Decision Rule in Absolute Identification
NASA Technical Reports Server (NTRS)
Balakrishnan, J. D.
1997-01-01
In several conditions of a line length identification experiment, the subjects' decision making strategies were systematically biased against the responses on the edges of the stimulus range. When the range and number of the stimuli were small, the bias caused the percentage of correct responses to be highest in the center and lowest on the extremes of the range. Two general classes of decision rules that would explain these results are considered. The first class assumes that subjects intend to adopt an optimal decision rule, but systematically misrepresent one or more parameters of the decision making context. The second class assumes that subjects use a different measure of performance than the one assumed by the experimenter: instead of maximizing the chances of a correct response, the subject attempts to minimize the expected size of the response error (a "fidelity criterion"). In a second experiment, extended experience and feedback did not diminish the bias effect, but explicitly penalizing all response errors equally, regardless of their size, did reduce or eliminate it in some subjects. Both results favor the fidelity criterion over the optimal rule.
A Bayesian model averaging method for the derivation of reservoir operating rules
NASA Astrophysics Data System (ADS)
Zhang, Jingwen; Liu, Pan; Wang, Hao; Lei, Xiaohui; Zhou, Yanlai
2015-09-01
Because the intrinsic dynamics among optimal decision making, inflow processes and reservoir characteristics are complex, functional forms of reservoir operating rules are always determined subjectively. As a result, the uncertainty of selecting form and/or model involved in reservoir operating rules must be analyzed and evaluated. In this study, we analyze the uncertainty of reservoir operating rules using the Bayesian model averaging (BMA) model. Three popular operating rules, namely piecewise linear regression, surface fitting and a least-squares support vector machine, are established based on the optimal deterministic reservoir operation. These individual models provide three-member decisions for the BMA combination, enabling the 90% release interval to be estimated by the Markov Chain Monte Carlo simulation. A case study of China's the Baise reservoir shows that: (1) the optimal deterministic reservoir operation, superior to any reservoir operating rules, is used as the samples to derive the rules; (2) the least-squares support vector machine model is more effective than both piecewise linear regression and surface fitting; (3) BMA outperforms any individual model of operating rules based on the optimal trajectories. It is revealed that the proposed model can reduce the uncertainty of operating rules, which is of great potential benefit in evaluating the confidence interval of decisions.
2012-01-01
Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting. PMID:23145874
Van Norman, Ethan R; Christ, Theodore J
2016-10-01
Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Application of decision rules for empowering of Indonesian telematics services SMEs
NASA Astrophysics Data System (ADS)
Tosida, E. T.; Hairlangga, O.; Amirudin, F.; Ridwanah, M.
2018-03-01
The independence of the field of telematics became one of Indonesia's vision in 2024. One effort to achieve it can be done by empowering SMEs in the field of telematics. Empowerment carried out need a practical mechanism by utilizing data centered, including through the National Economic Census database (Susenas). Based on the Susenas can be formulated the decision rules of determining the provision of assistance for SMEs in the field of telematics. The way it did by generating the rule base through the classification technique. The CART algorithm-based decision rule model performs better than C45 and ID3 models. The high level of performance model is also in line with the regulations applied by the government. This becomes one of the strengths of research, because the resulting model is consistent with the existing conditions in Indonesia. The rules base generated from the three classification techniques show different rules. The CART technique has pattern matching with the realization of activities in The Ministry of Cooperatives and SMEs. So far, the government has difficulty in referring data related to the empowerment of SMEs telematics services. Therefore, the findings resulting from this research can be used as an alternative decision support system related to the program of empowerment of SMEs in telematics.
2015-12-30
This final rule establishes a prior authorization program for certain durable medical equipment, prosthetics, orthotics, and supplies (DMEPOS) items that are frequently subject to unnecessary utilization. This rule defines unnecessary utilization and creates a new requirement that claims for certain DMEPOS items must have an associated provisional affirmed prior authorization decision as a condition of payment. This rule also adds the review contractor's decision regarding prior authorization of coverage of DMEPOS items to the list of actions that are not initial determinations and therefore not appealable.
Risk perception and communication in vaccination decisions: a fuzzy-trace theory approach.
Reyna, Valerie F
2012-05-28
The tenets of fuzzy-trace theory, along with prior research on risk perception and risk communication, are used to develop a process model of vaccination decisions in the era of Web 2.0. The theory characterizes these decisions in terms of background knowledge, dual mental representations (verbatim and gist), retrieval of values, and application of values to representations in context. Lack of knowledge interferes with the ability to extract the essential meaning, or gist, of vaccination messages. Prevention decisions have, by definition, a status quo option of "feeling okay." Psychological evidence from other prevention decisions, such as cancer screening, indicates that many people initially mentally represent their decision options in terms of simple, categorical gist: a choice between (a) a feeling-okay option (e.g., the unvaccinated status quo) versus (b) taking up preventive behavior that can have two potential categorical outcomes: feeling okay or not feeling okay. Hence, applying the same theoretical rules as used to explain framing effects and the Allais paradox, the decision to get a flu shot, for example, boils down to feeling okay (not sick) versus feeling okay (not sick) or not feeling okay (sick, side effects, or death). Because feeling okay is superior to not feeling okay (a retrieved value), this impoverished gist supports choosing not to have the flu vaccine. Anti-vaccination sources provide more coherent accounts of the gist of vaccination than official sources, filling a need to understand rare adverse outcomes. Copyright © 2011 Elsevier Ltd. All rights reserved.
Risk Perception and Communication in Vaccination Decisions: A Fuzzy-Trace Theory Approach
Reyna, Valerie F.
2012-01-01
The tenets of fuzzy-trace theory, along with prior research on risk perception and risk communication, are used to develop a process model of vaccination decisions in the era of Web 2.0. The theory characterizes these decisions in terms of background knowledge, dual mental representations (verbatim and gist), retrieval of values, and application of values to representations in context. Lack of knowledge interferes with the ability to extract the essential meaning, or gist, of vaccination messages. Prevention decisions have, by definition, a status quo option of “feeling okay.” Psychological evidence from other prevention decisions, such as cancer screening, indicates that many people initially mentally represent their decision options in terms of simple, categorical gist: a choice between (a) a feeling-okay option (e.g., the unvaccinated status quo) versus (b) taking up preventive behavior that can have two potential categorical outcomes: feeling okay or not feeling okay. Hence, applying the same theoretical rules as used to explain framing effects and the Allais paradox, the decision to get a flu shot, for example, boils down to feeling okay (not sick) versus feeling okay (not sick) or not feeling okay (sick, side effects, or death). Because feeling okay is superior to not feeling okay (a retrieved value), this impoverished gist supports choosing not to have the flu vaccine. Anti-vaccination sources provide more coherent accounts of the gist of vaccination than official sources, filling a need to understand rare adverse outcomes. PMID:22133507
Proposed Clinical Decision Rules to Diagnose Acute Rhinosinusitis Among Adults in Primary Care.
Ebell, Mark H; Hansen, Jens Georg
2017-07-01
To reduce inappropriate antibiotic prescribing, we sought to develop a clinical decision rule for the diagnosis of acute rhinosinusitis and acute bacterial rhinosinusitis. Multivariate analysis and classification and regression tree (CART) analysis were used to develop clinical decision rules for the diagnosis of acute rhinosinusitis, defined using 3 different reference standards (purulent antral puncture fluid or abnormal finding on a computed tomographic (CT) scan; for acute bacterial rhinosinusitis, we used a positive bacterial culture of antral fluid). Signs, symptoms, C-reactive protein (CRP), and reference standard tests were prospectively recorded in 175 Danish patients aged 18 to 65 years seeking care for suspected acute rhinosinusitis. For each reference standard, we developed 2 clinical decision rules: a point score based on a logistic regression model and an algorithm based on a CART model. We identified low-, moderate-, and high-risk groups for acute rhinosinusitis or acute bacterial rhinosinusitis for each clinical decision rule. The point scores each had between 5 and 6 predictors, and an area under the receiver operating characteristic curve (AUROCC) between 0.721 and 0.767. For positive bacterial culture as the reference standard, low-, moderate-, and high-risk groups had a 16%, 49%, and 73% likelihood of acute bacterial rhinosinusitis, respectively. CART models had an AUROCC ranging from 0.783 to 0.827. For positive bacterial culture as the reference standard, low-, moderate-, and high-risk groups had a likelihood of acute bacterial rhinosinusitis of 6%, 31%, and 59% respectively. We have developed a series of clinical decision rules integrating signs, symptoms, and CRP to diagnose acute rhinosinusitis and acute bacterial rhinosinusitis with good accuracy. They now require prospective validation and an assessment of their effect on clinical and process outcomes. © 2017 Annals of Family Medicine, Inc.
Ten simple rules for Lightning and PechaKucha presentations.
NASA Astrophysics Data System (ADS)
Lortie, C. J.
2016-12-01
An interesting opportunity has emerged that bridges the gap between lengthy, detailed presentations of scientific findings and `sound bites' appropriate for media reporting - very short presentations often presented in sets. Lightning or Ignite (20 slides @15 seconds each) and PechaKucha (20 slides @20 seconds each) presentations are common formats for short, rapid communications at scientific conferences and public events. The simple rules for making good presentations also apply, but these presentation formats provide both unique communication opportunities and novel challenges. In the spirit of light, quick, and exact (but without the fox), here are ten simple rules for presentation formats that do not wait for the speaker.
Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman
2018-06-01
Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.
Failure detection system design methodology. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Chow, E. Y.
1980-01-01
The design of a failure detection and identification system consists of designing a robust residual generation process and a high performance decision making process. The design of these two processes are examined separately. Residual generation is based on analytical redundancy. Redundancy relations that are insensitive to modelling errors and noise effects are important for designing robust residual generation processes. The characterization of the concept of analytical redundancy in terms of a generalized parity space provides a framework in which a systematic approach to the determination of robust redundancy relations are developed. The Bayesian approach is adopted for the design of high performance decision processes. The FDI decision problem is formulated as a Bayes sequential decision problem. Since the optimal decision rule is incomputable, a methodology for designing suboptimal rules is proposed. A numerical algorithm is developed to facilitate the design and performance evaluation of suboptimal rules.
Textural features for image classification
NASA Technical Reports Server (NTRS)
Haralick, R. M.; Dinstein, I.; Shanmugam, K.
1973-01-01
Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.
19 CFR 177.13 - Inconsistent customs decisions.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 19 Customs Duties 2 2010-04-01 2010-04-01 false Inconsistent customs decisions. 177.13 Section 177.13 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) ADMINISTRATIVE RULINGS General Ruling Procedure § 177.13 Inconsistent customs...
19 CFR 177.13 - Inconsistent customs decisions.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 19 Customs Duties 2 2012-04-01 2012-04-01 false Inconsistent customs decisions. 177.13 Section 177.13 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) ADMINISTRATIVE RULINGS General Ruling Procedure § 177.13 Inconsistent customs...
19 CFR 177.13 - Inconsistent customs decisions.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 19 Customs Duties 2 2011-04-01 2011-04-01 false Inconsistent customs decisions. 177.13 Section 177.13 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) ADMINISTRATIVE RULINGS General Ruling Procedure § 177.13 Inconsistent customs...
Dissociation of emotional decision-making from cognitive decision-making in chronic schizophrenia.
Lee, Yanghyun; Kim, Yang-Tae; Seo, Eugene; Park, Oaktae; Jeong, Sung-Hun; Kim, Sang Heon; Lee, Seung-Jae
2007-08-30
Recent studies have examined the decision-making ability of schizophrenic patients using the Iowa Gambling Task (IGT). These studies, however, were restricted to the assessment of emotional decision-making. Decision-making depends on cognitive functions as well as on emotion. The purpose of this study was to examine the performance of schizophrenic patients on the IGT and the Game of Dice Task (GDT), a decision-making task with explicit rules for gains and losses. In addition, it was intended to test whether poor performance on IGT is attributable to impairments in reversal learning within the schizophrenia group using the Simple Reversal Learning Task (SRLT), which is sensitive to measure the deficit of reversal learning following ventromedial prefrontal cortex damage. A group of 23 stable schizophrenic patients and 28 control subjects performed computerized versions of the IGT, GDT, SRLT and Wisconsin Card Sorting Test (WCST). While schizophrenic patients performed poorly on the IGT relative to normal controls, there was no significant difference between the two groups on GDT performance. The performance of the schizophrenia group on the SRLT was poorer than that of controls, but was not related to IGT performance. These data suggest that schizophrenic patients have impaired emotional decision-making but intact cognitive decision-making, suggesting that these two processes of decision-making are different. Furthermore, the impairments in reversal learning did not contribute to poor performance on the IGT in schizophrenia. Therefore, schizophrenic patients have difficulty in making decisions under ambiguous and uncertain situations whereas they make choices easily in clear and unequivocal ones. The emotional decision-making deficits in schizophrenia might be attributable more to another mechanism such as a somatic marker hypothesis than to an impairment in reversal learning.
Learning stage-dependent effect of M1 disruption on value-based motor decisions.
Derosiere, Gerard; Vassiliadis, Pierre; Demaret, Sophie; Zénon, Alexandre; Duque, Julie
2017-11-15
The present study aimed at characterizing the impact of M1 disruption on the implementation of implicit value information in motor decisions, at both early stages (during reinforcement learning) and late stages (after consolidation) of action value encoding. Fifty subjects performed, over three consecutive days, a task that required them to select between two finger responses according to the color (instruction) and to the shape (implicit, undisclosed rule) of an imperative signal: considering the implicit rule in addition to the instruction allowed subjects to earn more money. We investigated the functional contribution of M1 to the implementation of the implicit rule in subjects' motor decisions. Continuous theta burst stimulation (cTBS) was applied over M1 either on Day 1 or on Day 3, producing a temporary lesion either during reinforcement learning (cTBS Learning group) or after consolidation of the implicit rule, during decision-making (cTBS Decision group), respectively. Interestingly, disrupting M1 activity on Day 1 improved the reliance on the implicit rule, plausibly because M1 cTBS increased dopamine release in the putamen in an indirect way. This finding corroborates the view that cTBS may affect activity in unstimulated areas, such as the basal ganglia. Notably, this effect was short-lasting; it did not persist overnight, suggesting that the functional integrity of M1 during learning is a prerequisite for the consolidation of implicit value information to occur. Besides, cTBS over M1 did not impact the use of the implicit rule when applied on Day 3, although it did so when applied on Day 2 in a recent study where the reliance on the implicit rule declined following cTBS (Derosiere et al., 2017). Overall, these findings indicate that the human M1 is functionally involved in the consolidation and implementation of implicit value information underlying motor decisions. However, M1 contribution seems to vanish as subjects become more experienced in using the implicit value information to make their motor decisions. Copyright © 2017 Elsevier Inc. All rights reserved.
The Cape Town Clinical Decision Rule for Streptococcal Pharyngitis in Children
Engel, Mark Emmanuel; Cohen, Karen; Gounden, Ronald; Kengne, Andre P.; Barth, Dylan Dominic; Whitelaw, Andrew C; Francis, Veronica; Badri, Motasim; Stewart, Annemie; Dale, James B.; Mayosi, Bongani M.; Maartens, Gary
2016-01-01
Background Existing clinical decision rules (CDR) to diagnose group A streptococcal (GAS) pharyngitis have not been validated in sub-Saharan Africa. We developed a locally applicable CDR while evaluating existing CDRs for diagnosing GAS pharyngitis in South African children. Methods We conducted a prospective cohort study and enrolled 997 children aged 3-15 years presenting to primary care clinics with a complaint of sore throat, and whose parents provided consent. Main outcome measures were signs and symptoms of pharyngitis, and a positive GAS culture from a throat swab. Bivariate and multivariate analyses were used to develop the clinical decision rule. In addition, the diagnostic effectiveness of six existing rules for predicting a positive culture in our cohort was assessed. Results 206 of 982 children (21%) had a positive GAS culture. Tonsillar swelling, tonsillar exudates, tender or enlarged anterior cervical lymph nodes, absence of cough and absence of rhinorrhea were associated with positive cultures in bivariate and multivariate analyses. Four variables (tonsillar swelling and one of tonsillar exudate, no rhinorrhea, no cough), when used in a cumulative score, showed 83.7% sensitivity and 32.2% specificity for GAS pharyngitis. Of existing rules tested, the McIsaac rule had the highest positive predictive value (28%), but missed 49% of the culture-positive children who should have been treated. Conclusion The new four-variable clinical decision rule for GAS pharyngitis (i.e., tonsillar swelling and one of tonsillar exudate, no rhinorrhea, no cough) outperformed existing rules for GAS pharyngitis diagnosis in children with symptomatic sore throat in Cape Town. PMID:27870815
MacGillivray, Brian H
2017-08-01
In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases; and basing decision rules on clearly articulated values and evidence, rather than convention. Copyright © 2017. Published by Elsevier Ltd.
Rule groupings in expert systems using nearest neighbour decision rules, and convex hulls
NASA Technical Reports Server (NTRS)
Anastasiadis, Stergios
1991-01-01
Expert System shells are lacking in many areas of software engineering. Large rule based systems are not semantically comprehensible, difficult to debug, and impossible to modify or validate. Partitioning a set of rules found in CLIPS (C Language Integrated Production System) into groups of rules which reflect the underlying semantic subdomains of the problem, will address adequately the concerns stated above. Techniques are introduced to structure a CLIPS rule base into groups of rules that inherently have common semantic information. The concepts involved are imported from the field of A.I., Pattern Recognition, and Statistical Inference. Techniques focus on the areas of feature selection, classification, and a criteria of how 'good' the classification technique is, based on Bayesian Decision Theory. A variety of distance metrics are discussed for measuring the 'closeness' of CLIPS rules and various Nearest Neighbor classification algorithms are described based on the above metric.
A Left-Hand Rule for Faraday's Law
ERIC Educational Resources Information Center
Salu, Yehuda
2014-01-01
A left-hand rule for Faraday's law is presented here. This rule provides a simple and quick way of finding directional relationships between variables of Faraday's law without using Lenz's rule.
Web-based Weather Expert System (WES) for Space Shuttle Launch
NASA Technical Reports Server (NTRS)
Bardina, Jorge E.; Rajkumar, T.
2003-01-01
The Web-based Weather Expert System (WES) is a critical module of the Virtual Test Bed development to support 'go/no go' decisions for Space Shuttle operations in the Intelligent Launch and Range Operations program of NASA. The weather rules characterize certain aspects of the environment related to the launching or landing site, the time of the day or night, the pad or runway conditions, the mission durations, the runway equipment and landing type. Expert system rules are derived from weather contingency rules, which were developed over years by NASA. Backward chaining, a goal-directed inference method is adopted, because a particular consequence or goal clause is evaluated first, and then chained backward through the rules. Once a rule is satisfied or true, then that particular rule is fired and the decision is expressed. The expert system is continuously verifying the rules against the past one-hour weather conditions and the decisions are made. The normal procedure of operations requires a formal pre-launch weather briefing held on Launch minus 1 day, which is a specific weather briefing for all areas of Space Shuttle launch operations. In this paper, the Web-based Weather Expert System of the Intelligent Launch and range Operations program is presented.
Simple and accurate sum rules for highly relativistic systems
NASA Astrophysics Data System (ADS)
Cohen, Scott M.
2005-03-01
In this paper, I consider the Bethe and Thomas-Reiche-Kuhn sum rules, which together form the foundation of Bethe's theory of energy loss from fast charged particles to matter. For nonrelativistic target systems, the use of closure leads directly to simple expressions for these quantities. In the case of relativistic systems, on the other hand, the calculation of sum rules is fraught with difficulties. Various perturbative approaches have been used over the years to obtain relativistic corrections, but these methods fail badly when the system in question is very strongly bound. Here, I present an approach that leads to relatively simple expressions yielding accurate sums, even for highly relativistic many-electron systems. I also offer an explanation for the difference between relativistic and nonrelativistic sum rules in terms of the Zitterbewegung of the electrons.
Validation of the Ottawa Knee Rules.
Emparanza, J I; Aginaga, J R
2001-10-01
We sought to validate the Ottawa Knee Rules for determining the need for radiography in patients with acute knee injury. A prospective cohort study was performed in emergency departments of 11 hospitals of the Osakidetza-Basque Country Health Service. The patient population was composed of a convenience sample of 1,522 eligible adults of 2,315 patients with acute knee injuries. The attending emergency physicians assessed each patient for standardized clinical variables and determined the need for radiography according to the decision rule. Radiography was performed in each patient, irrespective of the determination of the rule, after clinical evaluation findings were recorded. The rule was assessed for the ability to correctly identify fracture of the knee. The decision rule had a sensitivity of 1.0 (95% confidence interval [CI] 0.96 to 1.0), identifying 89 patients with clinically important fractures. The potential reduction in use of radiography was estimated to be 49%. The probability of fracture, if the decision rules were negative, is estimated to be 0% (95% CI 0% to 0.5%). Prospective validation has shown the Ottawa Knee Rules to be 100% sensitive for identifying fractures of the knee and to have the potential to allow physicians to reduce the use of radiography in patients with acute knee injuries.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-06-01
... Association decisions in disciplinary, membership denial, registration, and member responsibility actions... and disciplinary actions. The Commission estimates the burden of this collection of information as... Renew Collection: Rules Relating To Review of National Futures Association Decisions in Disciplinary...
19 CFR 177.1 - General ruling practice and definitions.
Code of Federal Regulations, 2010 CFR
2010-04-01
... in applicable Treasury Decisions, rulings, opinions, or court decisions published in the Customs... in response to a written request therefor and set forth in a letter addressed to the person making... more than call attention to a well-established interpretation or principle of Customs law, without...
A lack of appetite for information and computation. Simple heuristics in food choice.
Schulte-Mecklenbeck, Michael; Sohn, Matthias; de Bellis, Emanuel; Martin, Nathalie; Hertwig, Ralph
2013-12-01
The predominant, but largely untested, assumption in research on food choice is that people obey the classic commandments of rational behavior: they carefully look up every piece of relevant information, weight each piece according to subjective importance, and then combine them into a judgment or choice. In real world situations, however, the available time, motivation, and computational resources may simply not suffice to keep these commandments. Indeed, there is a large body of research suggesting that human choice is often better accommodated by heuristics-simple rules that enable decision making on the basis of a few, but important, pieces of information. We investigated the prevalence of such heuristics in a computerized experiment that engaged participants in a series of choices between two lunch dishes. Employing MouselabWeb, a process-tracing technique, we found that simple heuristics described an overwhelmingly large proportion of choices, whereas strategies traditionally deemed rational were barely apparent in our data. Replicating previous findings, we also observed that visual stimulus segments received a much larger proportion of attention than any nutritional values did. Our results suggest that, consistent with human behavior in other domains, people make their food choices on the basis of simple and informationally frugal heuristics. Copyright © 2013 Elsevier Ltd. All rights reserved.
McGinn, Thomas G; McCullagh, Lauren; Kannry, Joseph; Knaus, Megan; Sofianou, Anastasia; Wisnivesky, Juan P; Mann, Devin M
2013-09-23
There is consensus that incorporating clinical decision support into electronic health records will improve quality of care, contain costs, and reduce overtreatment, but this potential has yet to be demonstrated in clinical trials. To assess the influence of a customized evidence-based clinical decision support tool on the management of respiratory tract infections and on the effectiveness of integrating evidence at the point of care. In a randomized clinical trial, we implemented 2 well-validated integrated clinical prediction rules, namely, the Walsh rule for streptococcal pharyngitis and the Heckerling rule for pneumonia. INTERVENTIONS AND MAIN OUTCOMES AND MEASURES: The intervention group had access to the integrated clinical prediction rule tool and chose whether to complete risk score calculators, order medications, and generate progress notes to assist with complex decision making at the point of care. The intervention group completed the integrated clinical prediction rule tool in 57.5% of visits. Providers in the intervention group were significantly less likely to order antibiotics than the control group (age-adjusted relative risk, 0.74; 95% CI, 0.60-0.92). The absolute risk of the intervention was 9.2%, and the number needed to treat was 10.8. The intervention group was significantly less likely to order rapid streptococcal tests compared with the control group (relative risk, 0.75; 95% CI, 0.58-0.97; P= .03). The integrated clinical prediction rule process for integrating complex evidence-based clinical decision report tools is of relevant importance for national initiatives, such as Meaningful Use. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01386047.
Wolf, Max; Kurvers, Ralf H J M; Ward, Ashley J W; Krause, Stefan; Krause, Jens
2013-04-07
In a wide range of contexts, including predator avoidance, medical decision-making and security screening, decision accuracy is fundamentally constrained by the trade-off between true and false positives. Increased true positives are possible only at the cost of increased false positives; conversely, decreased false positives are associated with decreased true positives. We use an integrated theoretical and experimental approach to show that a group of decision-makers can overcome this basic limitation. Using a mathematical model, we show that a simple quorum decision rule enables individuals in groups to simultaneously increase true positives and decrease false positives. The results from a predator-detection experiment that we performed with humans are in line with these predictions: (i) after observing the choices of the other group members, individuals both increase true positives and decrease false positives, (ii) this effect gets stronger as group size increases, (iii) individuals use a quorum threshold set between the average true- and false-positive rates of the other group members, and (iv) individuals adjust their quorum adaptively to the performance of the group. Our results have broad implications for our understanding of the ecology and evolution of group-living animals and lend themselves for applications in the human domain such as the design of improved screening methods in medical, forensic, security and business applications.
Wolf, Max; Kurvers, Ralf H. J. M.; Ward, Ashley J. W.; Krause, Stefan; Krause, Jens
2013-01-01
In a wide range of contexts, including predator avoidance, medical decision-making and security screening, decision accuracy is fundamentally constrained by the trade-off between true and false positives. Increased true positives are possible only at the cost of increased false positives; conversely, decreased false positives are associated with decreased true positives. We use an integrated theoretical and experimental approach to show that a group of decision-makers can overcome this basic limitation. Using a mathematical model, we show that a simple quorum decision rule enables individuals in groups to simultaneously increase true positives and decrease false positives. The results from a predator-detection experiment that we performed with humans are in line with these predictions: (i) after observing the choices of the other group members, individuals both increase true positives and decrease false positives, (ii) this effect gets stronger as group size increases, (iii) individuals use a quorum threshold set between the average true- and false-positive rates of the other group members, and (iv) individuals adjust their quorum adaptively to the performance of the group. Our results have broad implications for our understanding of the ecology and evolution of group-living animals and lend themselves for applications in the human domain such as the design of improved screening methods in medical, forensic, security and business applications. PMID:23407830
Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling.
Tsipouras, Markos G; Exarchos, Themis P; Fotiadis, Dimitrios I; Kotsia, Anna P; Vakalis, Konstantinos V; Naka, Katerina K; Michalis, Lampros K
2008-07-01
A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated dataset, using a four stage methodology: 1) induction of a decision tree from the data; 2) extraction of a set of rules from the decision tree, in disjunctive normal form and formulation of a crisp model; 3) transformation of the crisp set of rules into a fuzzy model; and 4) optimization of the parameters of the fuzzy model. The dataset used for the DSS generation and evaluation consists of 199 subjects, each one characterized by 19 features, including demographic and history data, as well as laboratory examinations. Tenfold cross validation is employed, and the average sensitivity and specificity obtained is 62% and 54%, respectively, using the set of rules extracted from the decision tree (first and second stages), while the average sensitivity and specificity increase to 80% and 65%, respectively, when the fuzzification and optimization stages are used. The system offers several advantages since it is automatically generated, it provides CAD diagnosis based on easily and noninvasively acquired features, and is able to provide interpretation for the decisions made.
The impact of the Rasouli decision: a Survey of Canadian intensivists.
Cape, David; Fox-Robichaud, Alison; Turgeon, Alexis F; Seely, Andrew; Hall, Richard; Burns, Karen; Singal, Rohit K; Dodek, Peter; Bagshaw, Sean; Sibbald, Robert; Downar, James
2016-03-01
In a landmark 2013 decision, the Supreme Court of Canada (SCC) ruled that the withdrawal of life support in certain circumstances is a treatment requiring patient or substitute decision maker (SDM) consent. How intensive care unit (ICU) physicians perceive this ruling is unknown. To determine physician knowledge of and attitudes towards the SCC decision, as well as the self-reported changes in practice attributed to the decision. We surveyed intensivists at university hospitals across Canada. We used a knowledge test and Likert-scale questions to measure respondent knowledge of and attitudes towards the ruling. We used vignettes to assess decision making in cases of intractable physician-SDM conflict over the management of patients with very poor prognoses. We compared management choices pre-SCC decision versus post-SCC decision versus the subjective, respondent-defined most appropriate choice. Responses were compared across predefined subgroups. We performed qualitative analysis on free-text responses. We received 82 responses (response rate=42%). Respondents reported providing high levels of self-defined inappropriate treatment. Although most respondents reported no change in practice, there was a significant overall shift towards higher intensity and less subjectively appropriate management after the SCC decision. Attitudes to the SCC decision and approaches to disputes over end-of-life (EoL) care in the ICU were highly variable. There were no significant differences among predefined subgroups. Many Canadian ICU physicians report providing a higher intensity of treatment, and less subjectively appropriate treatment, in situations of dispute over EoL care after the Supreme Court of Canada's ruling in Cuthbertson versus Rasouli. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Califf, Robert M; Rasiel, Emma B; Schulman, Kevin A
2008-11-01
The pharmaceutical and medical device industries function in a business environment in which shareholders expect companies to optimize profit within legal and ethical standards. A fundamental tool used to optimize decision making is the net present value calculation, which estimates the current value of cash flows relating to an investment. We examined 3 prototypical research investment decisions that have been the source of public scrutiny to illustrate how policy decisions can be better understood when their impact on societally desirable investments by industry are viewed from the standpoint of their impact on net present value. In the case of direct, comparative clinical trials, a simple net present value calculation provides insight into why companies eschew such investments. In the case of pediatric clinical trials, the Pediatric Extension Rule changed the net present value calculation from unattractive to potentially very attractive by allowing patent extensions; thus, the dramatic increase in pediatric clinical trials can be explained by the financial return on investment. In the case of products for small markets, the fixed costs of development make this option financially unattractive. Policy decisions can be better understood when their impact on societally desirable investments by the pharmaceutical and medical device industries are viewed from the standpoint of their impact on net present value.
12 CFR 263.38 - Recommended decision and filing of record.
Code of Federal Regulations, 2010 CFR
2010-01-01
... FEDERAL RESERVE SYSTEM RULES OF PRACTICE FOR HEARINGS Uniform Rules of Practice and Procedure § 263.38... expiration of the time allowed for filing reply briefs under § 263.37(b), the administrative law judge shall... the administrative law judge's recommended decision, recommended findings of fact, recommended...
49 CFR 1115.1 - Scope of rule.
Code of Federal Regulations, 2010 CFR
2010-10-01
... other than initial decisions. For each category, this rule describes the types of appeal permitted, the requirements to be observed in filing an appeal, provisions for stay of the action, and the status of the action in the absence of a stay. (c) Appeals from the decisions of employees acting under authority...
12 CFR 622.12 - Proposed findings and conclusions; recommended decision.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Proposed findings and conclusions; recommended decision. 622.12 Section 622.12 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM RULES OF PRACTICE AND PROCEDURE Rules Applicable to Formal Hearings § 622.12 Proposed findings and conclusions...
Code of Federal Regulations, 2010 CFR
2010-01-01
... provisions of the Atomic Energy Act and to all applicable rules, regulations, decisions and orders of the... conditions when required by amendments of the Atomic Energy Act or other applicable law, or by other rules, regulations, decisions or orders issued in accordance with the terms of the Atomic Energy Act or other...
19 CFR 177.2 - Submission of ruling requests.
Code of Federal Regulations, 2010 CFR
2010-04-01
... Headquarters Office will prepare final decisions under § 177.11 (Requests for Advice by Field Officers), or § 174.23 (Further Review of Protests), § 177.10 (Change of Practice), decisions under part 175 of this... Carrier rulings should be addressed to the Commissioner of Customs and Border Protection, Attention...
17 CFR 201.411 - Commission consideration of initial decisions by hearing officers.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 17 Commodity and Securities Exchanges 2 2010-04-01 2010-04-01 false Commission consideration of initial decisions by hearing officers. 201.411 Section 201.411 Commodity and Securities Exchanges SECURITIES AND EXCHANGE COMMISSION RULES OF PRACTICE Rules of Practice Appeal to the Commission and...
76 FR 37274 - Outer Continental Shelf Air Regulations Consistency Update for Alaska
Federal Register 2010, 2011, 2012, 2013, 2014
2011-06-27
... and prevents EPA from making substantive changes to the requirements it incorporates. As a result, EPA... narrative discussing how EPA made the decision to include or exclude rules. The Alaska Eskimo Whaling Commission expressed specific concern with EPA's decision to exclude administrative and procedural rules and...
Abortion foes get turn to ask Supreme Court for constitutional protection.
Denniston, L
1994-04-28
The US Supreme Court began hearing arguments on the constitutionality of a Florida judge's order which placed limits on anti-abortion protesting. This case will be the last abortion--related decision for Justice Harry A. Blackmun, who was the author of the original decision granting the right to abortion in Roe vs. Wade, before retiring from the Court in September 1994. Anti-abortion activists claim 1st Amendment protection, much the same as Dr. Martin Luther King's marches in advancing Blacks' civil rights. The case involved a Melbourne abortion clinic. The murder of Dr. Gunn outside an abortion clinic in Pensacola, Florida, will be used to support the need for protection from extremist violence. The conflict appears to be over the right to save women's right to abortion and over simple, peaceful protests and prayers against abortion. One anti-abortion foe, affiliated with Operational Rescue and initiating the appeal to the Supreme Court, is scheduled to testify before the Court: Judy Madsen, a protester who has counseled outside clinics. Ms. Madsen says she is exercising her freedom to protect human life. Other testimony will come from Reverend Ed Martin of Ocala, Rescue America's founder, and Shirley Hobbs, a homemaker from Orlando. Representation will be made by lawyer Matthew Staver, who will argue that the ruling was directed to a political position. Other support will come from religious and anti-abortion groups and the AFL-CIO. Testifying for the clinic, the Aware Women's Center for Choice, will be the owner and operator Patricia Baird Windle. Over the past 5 years, the Melbourne Clinic had been a target for the nationwide anti-abortion campaign by Operation Rescue. Because of the conflicting rulings between the Florida Supreme Court, which ruled to keep protesters away from clinic grounds and staff homes, and 11th US Circuit Court of Appeals ruling of unconstitutionality, no protection is afforded the clinic. Previous protection had occurred due to a 1992 judge's order. Clinic lawyer, Talbot D'Alemberte, president of Florida State University and former president of the American Bar Association, will argue that the issue is about intimidation. The Clinton administration's Solicitor General Drew S. Days III will support Seminole County Circuit Court Judge Robert S. McGregor's decision limiting protester activity.
Clairvoyant fusion: a new methodology for designing robust detection algorithms
NASA Astrophysics Data System (ADS)
Schaum, Alan
2016-10-01
Many realistic detection problems cannot be solved with simple statistical tests for known alternative probability models. Uncontrollable environmental conditions, imperfect sensors, and other uncertainties transform simple detection problems with likelihood ratio solutions into composite hypothesis (CH) testing problems. Recently many multi- and hyperspectral sensing CH problems have been addressed with a new approach. Clairvoyant fusion (CF) integrates the optimal detectors ("clairvoyants") associated with every unspecified value of the parameters appearing in a detection model. For problems with discrete parameter values, logical rules emerge for combining the decisions of the associated clairvoyants. For many problems with continuous parameters, analytic methods of CF have been found that produce closed-form solutions-or approximations for intractable problems. Here the principals of CF are reviewed and mathematical insights are described that have proven useful in the derivation of solutions. It is also shown how a second-stage fusion procedure can be used to create theoretically superior detection algorithms for ALL discrete parameter problems.
Derosiere, Gerard; Zénon, Alexandre; Alamia, Andrea; Duque, Julie
2017-02-01
In the present study, we investigated the functional contribution of the human primary motor cortex (M1) to motor decisions. Continuous theta burst stimulation (cTBS) was used to alter M1 activity while participants performed a decision-making task in which the reward associated with the subjects' responses (right hand finger movements) depended on explicit and implicit value-based rules. Subjects performed the task over two consecutive days and cTBS occurred in the middle of Day 2, once the subjects were just about to implement implicit rules, in addition to the explicit instructions, to choose their responses, as evident in the control group (cTBS over the right somatosensory cortex). Interestingly, cTBS over the left M1 prevented subjects from implementing the implicit value-based rule while its implementation was enhanced in the group receiving cTBS over the right M1. Hence, cTBS had opposite effects depending on whether it was applied on the contralateral or ipsilateral M1. The use of the explicit value-based rule was unaffected by cTBS in the three groups of subject. Overall, the present study provides evidence for a functional contribution of M1 to the implementation of freshly acquired implicit rules, possibly through its involvement in a cortico-subcortical network controlling value-based motor decisions. Copyright © 2016 Elsevier Inc. All rights reserved.
Toulet, Sylvain; Gautrais, Jacques; Bon, Richard; Peruani, Fernando
2015-01-01
For group-living animals, reaching consensus to stay cohesive is crucial for their fitness, particularly when collective motion starts and stops. Understanding the decision-making at individual and collective levels upon sudden disturbances is central in the study of collective animal behavior, and concerns the broader question of how information is distributed and evaluated in groups. Despite the relevance of the problem, well-controlled experimental studies that quantify the collective response of groups facing disruptive events are lacking. Here we study the behavior of small-sized groups of uninformed individuals subject to the departure and stop of a trained conspecific. We find that the groups reach an effective consensus: either all uninformed individuals follow the trained one (and collective motion occurs) or none does. Combining experiments and a simple mathematical model we show that the observed phenomena results from the interplay between simple mimetic rules and the characteristic duration of the stimulus, here, the time during which the trained individual is moving away. The proposed mechanism strongly depends on group size, as observed in the experiments, and even if group splitting can occur, the most likely outcome is always a coherent collective group response (consensus). The prevalence of a consensus is expected even if the groups of naives face conflicting information, e.g. if groups contain two subgroups of trained individuals, one trained to stay and one trained to leave. Our results indicate that collective decision-making and consensus in (small) animal groups are likely to be self-organized phenomena that do not involve concertation or even communication among the group members.
18 CFR 385.702 - Definitions (Rule 702).
Code of Federal Regulations, 2010 CFR
2010-04-01
... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Definitions (Rule 702). 385.702 Section 385.702 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY PROCEDURAL RULES RULES OF PRACTICE AND PROCEDURE Decisions § 385.702 Definitions (Rule...
New tools for evaluating LQAS survey designs
2014-01-01
Lot Quality Assurance Sampling (LQAS) surveys have become increasingly popular in global health care applications. Incorporating Bayesian ideas into LQAS survey design, such as using reasonable prior beliefs about the distribution of an indicator, can improve the selection of design parameters and decision rules. In this paper, a joint frequentist and Bayesian framework is proposed for evaluating LQAS classification accuracy and informing survey design parameters. Simple software tools are provided for calculating the positive and negative predictive value of a design with respect to an underlying coverage distribution and the selected design parameters. These tools are illustrated using a data example from two consecutive LQAS surveys measuring Oral Rehydration Solution (ORS) preparation. Using the survey tools, the dependence of classification accuracy on benchmark selection and the width of the ‘grey region’ are clarified in the context of ORS preparation across seven supervision areas. Following the completion of an LQAS survey, estimation of the distribution of coverage across areas facilitates quantifying classification accuracy and can help guide intervention decisions. PMID:24528928
New tools for evaluating LQAS survey designs.
Hund, Lauren
2014-02-15
Lot Quality Assurance Sampling (LQAS) surveys have become increasingly popular in global health care applications. Incorporating Bayesian ideas into LQAS survey design, such as using reasonable prior beliefs about the distribution of an indicator, can improve the selection of design parameters and decision rules. In this paper, a joint frequentist and Bayesian framework is proposed for evaluating LQAS classification accuracy and informing survey design parameters. Simple software tools are provided for calculating the positive and negative predictive value of a design with respect to an underlying coverage distribution and the selected design parameters. These tools are illustrated using a data example from two consecutive LQAS surveys measuring Oral Rehydration Solution (ORS) preparation. Using the survey tools, the dependence of classification accuracy on benchmark selection and the width of the 'grey region' are clarified in the context of ORS preparation across seven supervision areas. Following the completion of an LQAS survey, estimation of the distribution of coverage across areas facilitates quantifying classification accuracy and can help guide intervention decisions.
An Integrated Product Environment
NASA Technical Reports Server (NTRS)
Higgins, Chuck
1997-01-01
Mechanical Advantage is a mechanical design decision support system. Unlike our CAD/CAM cousins, Mechanical Advantage addresses true engineering processes, not just the form and fit of geometry. If we look at a traditional engineering environment, we see that an engineer starts with two things - performance goals and design rules. The intent is to have a product perform specific functions and accomplish that within a designated environment. Geometry should be a simple byproduct of that engineering process - not the controller of it. Mechanical Advantage is a performance modeler allowing engineers to consider all these criteria in making their decisions by providing such capabilities as critical parameter analysis, tolerance and sensitivity analysis, math driven Geometry, and automated design optimizations. If you should desire an industry standard solid model, we would produce an ACIS-based solid model. If you should desire an ANSI/ISO standard drawing, we would produce this as well with a virtual push of the button. For more information on this and other Advantage Series products, please contact the author.
VEG: An intelligent workbench for analysing spectral reflectance data
NASA Technical Reports Server (NTRS)
Harrison, P. Ann; Harrison, Patrick R.; Kimes, Daniel S.
1994-01-01
An Intelligent Workbench (VEG) was developed for the systematic study of remotely sensed optical data from vegetation. A goal of the remote sensing community is to infer the physical and biological properties of vegetation cover (e.g. cover type, hemispherical reflectance, ground cover, leaf area index, biomass, and photosynthetic capacity) using directional spectral data. VEG collects together, in a common format, techniques previously available from many different sources in a variety of formats. The decision as to when a particular technique should be applied is nonalgorithmic and requires expert knowledge. VEG has codified this expert knowledge into a rule-based decision component for determining which technique to use. VEG provides a comprehensive interface that makes applying the techniques simple and aids a researcher in developing and testing new techniques. VEG also provides a classification algorithm that can learn new classes of surface features. The learning system uses the database of historical cover types to learn class descriptions of one or more classes of cover types.
Chen, Zhenyu; Li, Jianping; Wei, Liwei
2007-10-01
Recently, gene expression profiling using microarray techniques has been shown as a promising tool to improve the diagnosis and treatment of cancer. Gene expression data contain high level of noise and the overwhelming number of genes relative to the number of available samples. It brings out a great challenge for machine learning and statistic techniques. Support vector machine (SVM) has been successfully used to classify gene expression data of cancer tissue. In the medical field, it is crucial to deliver the user a transparent decision process. How to explain the computed solutions and present the extracted knowledge becomes a main obstacle for SVM. A multiple kernel support vector machine (MK-SVM) scheme, consisting of feature selection, rule extraction and prediction modeling is proposed to improve the explanation capacity of SVM. In this scheme, we show that the feature selection problem can be translated into an ordinary multiple parameters learning problem. And a shrinkage approach: 1-norm based linear programming is proposed to obtain the sparse parameters and the corresponding selected features. We propose a novel rule extraction approach using the information provided by the separating hyperplane and support vectors to improve the generalization capacity and comprehensibility of rules and reduce the computational complexity. Two public gene expression datasets: leukemia dataset and colon tumor dataset are used to demonstrate the performance of this approach. Using the small number of selected genes, MK-SVM achieves encouraging classification accuracy: more than 90% for both two datasets. Moreover, very simple rules with linguist labels are extracted. The rule sets have high diagnostic power because of their good classification performance.
Cooperation and Defection in Ghetto
NASA Astrophysics Data System (ADS)
Kułakowski, Krzysztof
We consider ghetto as a community of people ruled against their will by an external power. Members of the community feel that their laws are broken. However, attempts to leave ghetto makes their situation worse. We discuss the relation of the ghetto inhabitants to the ruling power in context of their needs, organized according to the Maslow hierarchy. Decisions how to satisfy successive needs are undertaken in cooperation with or defection the ruling power. This issue allows to construct the tree of decisions and to adopt the pruning technique from the game theory. Dynamics of decisions can be described within the formalism of fundamental equations. The result is that the strategy of defection is stabilized by the estimated payoff.
A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning
Balcarras, Matthew; Womelsdorf, Thilo
2016-01-01
Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context-specific selections to drive responses. PMID:27064794
Rule Systems for Runtime Verification: A Short Tutorial
NASA Astrophysics Data System (ADS)
Barringer, Howard; Havelund, Klaus; Rydeheard, David; Groce, Alex
In this tutorial, we introduce two rule-based systems for on and off-line trace analysis, RuleR and LogScope. RuleR is a conditional rule-based system, which has a simple and easily implemented algorithm for effective runtime verification, and into which one can compile a wide range of temporal logics and other specification formalisms used for runtime verification. Specifications can be parameterized with data, or even with specifications, allowing for temporal logic combinators to be defined. We outline a number of simple syntactic extensions of core RuleR that can lead to further conciseness of specification but still enabling easy and efficient implementation. RuleR is implemented in Java and we will demonstrate its ease of use in monitoring Java programs. LogScope is a derivation of RuleR adding a simple very user-friendly temporal logic. It was developed in Python, specifically for supporting testing of spacecraft flight software for NASA’s next 2011 Mars mission MSL (Mars Science Laboratory). The system has been applied by test engineers to analysis of log files generated by running the flight software. Detailed logging is already part of the system design approach, and hence there is no added instrumentation overhead caused by this approach. While post-mortem log analysis prevents the autonomous reaction to problems possible with traditional runtime verification, it provides a powerful tool for test automation. A new system is being developed that integrates features from both RuleR and LogScope.
Sideline coverage: when to get radiographs? A review of clinical decision tools.
Gould, Sara J; Cardone, Dennis A; Munyak, John; Underwood, Philipp J; Gould, Stephen A
2014-05-01
Sidelines coverage presents unique challenges in the evaluation of injured athletes. Health care providers may be confronted with the question of when to obtain radiographs following an injury. Given that most sidelines coverage occurs outside the elite level, radiographs are not readily available at the time of injury, and the decision of when to send a player for radiographs must be made based on physical examination. Clinical tools have been developed to aid in identifying injuries that are likely to result in radiographically important fractures or dislocations. A search for the keywords x-ray and decision rule along with the anatomic locations shoulder, elbow, wrist, knee, and ankle was performed using the PubMed database. No limits were set regarding year of publication. We selected meta-analyses, randomized controlled trials, and survey results. Our selection focused on the largest, most well-studied published reports. We also attempted to include studies that reported the application of the rules to the field of sports medicine. Retrospective literature review. Level 4. The Ottawa Foot and Ankle Rules have been validated and implemented and are appropriate for use in both pediatric and adult populations. The Ottawa Knee Rules have been widely studied, validated, and accepted for evaluation of knee injuries. There are promising studies of decision rules for clinically important fractures of the wrist, but these studies have not been validated. The elbow has been evaluated with good outcomes via the elbow extension test, which has been validated in both single and multicenter studies. Currently, there are no reliable clinical decision tools for traumatic sports injuries to the shoulder to aid in the decision of when to obtain radiographs. Clinical decision tools have been developed to aid in the diagnosis and management of injuries commonly sustained during sporting events. Tools that have been appropriately validated in populations outside the initial study population can assist sports medicine physicians in the decision of when to get radiographs from the sidelines.
Orellana, Liliana; Rotnitzky, Andrea; Robins, James M
2010-01-01
Dynamic treatment regimes are set rules for sequential decision making based on patient covariate history. Observational studies are well suited for the investigation of the effects of dynamic treatment regimes because of the variability in treatment decisions found in them. This variability exists because different physicians make different decisions in the face of similar patient histories. In this article we describe an approach to estimate the optimal dynamic treatment regime among a set of enforceable regimes. This set is comprised by regimes defined by simple rules based on a subset of past information. The regimes in the set are indexed by a Euclidean vector. The optimal regime is the one that maximizes the expected counterfactual utility over all regimes in the set. We discuss assumptions under which it is possible to identify the optimal regime from observational longitudinal data. Murphy et al. (2001) developed efficient augmented inverse probability weighted estimators of the expected utility of one fixed regime. Our methods are based on an extension of the marginal structural mean model of Robins (1998, 1999) which incorporate the estimation ideas of Murphy et al. (2001). Our models, which we call dynamic regime marginal structural mean models, are specially suitable for estimating the optimal treatment regime in a moderately small class of enforceable regimes of interest. We consider both parametric and semiparametric dynamic regime marginal structural models. We discuss locally efficient, double-robust estimation of the model parameters and of the index of the optimal treatment regime in the set. In a companion paper in this issue of the journal we provide proofs of the main results.
Yap, Christina; Billingham, Lucinda J; Cheung, Ying Kuen; Craddock, Charlie; O'Quigley, John
2017-12-15
The ever-increasing pace of development of novel therapies mandates efficient methodologies for assessment of their tolerability and activity. Evidence increasingly support the merits of model-based dose-finding designs in identifying the recommended phase II dose compared with conventional rule-based designs such as the 3 + 3 but despite this, their use remains limited. Here, we propose a useful tool, dose transition pathways (DTP), which helps overcome several commonly faced practical and methodologic challenges in the implementation of model-based designs. DTP projects in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, de-escalate, or stop early), using all the accumulated information. After specifying a model with favorable statistical properties, we utilize the DTP to fine-tune the model to tailor it to the trial's specific requirements that reflect important clinical judgments. In particular, it can help to determine how stringent the stopping rules should be if the investigated therapy is too toxic. Its use to design and implement a modified continual reassessment method is illustrated in an acute myeloid leukemia trial. DTP removes the fears of model-based designs as unknown, complex systems and can serve as a handbook, guiding decision-making for each dose update. In the illustrated trial, the seamless, clear transition for each dose recommendation aided the investigators' understanding of the design and facilitated decision-making to enable finer calibration of a tailored model. We advocate the use of the DTP as an integral procedure in the co-development and successful implementation of practical model-based designs by statisticians and investigators. Clin Cancer Res; 23(24); 7440-7. ©2017 AACR . ©2017 American Association for Cancer Research.
4 CFR 22.4 - Appeal File [Rule 4].
Code of Federal Regulations, 2010 CFR
2010-01-01
... contracting officer relied in making the decision, and any correspondence relating thereto; (v) Transcripts of... 4 Accounts 1 2010-01-01 2010-01-01 false Appeal File [Rule 4]. 22.4 Section 22.4 Accounts... consisting of all documents pertinent to the appeal, including: (i) The decision from which the appeal is...
29 CFR 18.103 - Rulings on evidence.
Code of Federal Regulations, 2010 CFR
2010-07-01
... is more probably true than not true that the error did not materially contribute to the decision or... if explicitly not relied upon by the judge in support of the decision or order. (b) Record of offer... making of an offer in question and answer form. (c) Plain error. Nothing in this rule precludes taking...
34 CFR 31.8 - Rules of decision.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 34 Education 1 2010-07-01 2010-07-01 false Rules of decision. 31.8 Section 31.8 Education Office of the Secretary, Department of Education SALARY OFFSET FOR FEDERAL EMPLOYEES WHO ARE INDEBTED TO THE.... (3) The act or omission of an institution of higher education at which the employee was enrolled does...
Student Expression: The Uncertain Future
ERIC Educational Resources Information Center
Bathon, Justin M.; McCarthy, Martha M.
2008-01-01
On June 25, 2007, the United States Supreme Court rendered its decision in "Morse v. Frederick", a long-awaited ruling regarding student speech in public schools. For nearly twenty years, the Supreme Court had been silent on the issue while lower courts attempted to apply the rules announced in previous Supreme Court decisions. It is…
Gubhaju, Bina; De Jong, Gordon F
2009-03-01
This research tests the thesis that the neoclassical micro-economic and the new household economic theoretical assumptions on migration decision-making rules are segmented by gender, marital status, and time frame of intention to migrate. Comparative tests of both theories within the same study design are relatively rare. Utilizing data from the Causes of Migration in South Africa national migration survey, we analyze how individually held "own-future" versus alternative "household well-being" migration decision rules effect the intentions to migrate of male and female adults in South Africa. Results from the gender and marital status specific logistic regressions models show consistent support for the different gender-marital status decision rule thesis. Specifically, the "maximizing one's own future" neoclassical microeconomic theory proposition is more applicable for never married men and women, the "maximizing household income" proposition for married men with short-term migration intentions, and the "reduce household risk" proposition for longer time horizon migration intentions of married men and women. Results provide new evidence on the way household strategies and individual goals jointly affect intentions to move or stay.
The WHI offers an opportunity to evaluate ovarian cancer markers and screening decision rules developed and validated in EDRN CVC Studies 2 and 3 in women who were not being screened. It is particularly well suited to validation of risk markers, since many serum samples were drawn well before clinical diagnosis of cancer in the WHI cohorts. A strategy is needed to identify from among the general population of women over the age of 50 those at high-risk for a diagnosis of ovarian/fallopian tube cancer so that they can be referred for appropriate surveillance, imaging or surgical consult. Tools to identify high-risk women will be investigated including serum markers CA125, HE4, MSLN, and MMP7 and epidemiologic risk factors. We will optimize decision rules using stored serum samples from the WHI OS and conduct a simulated prospective validation using stored serum samples from the WHI CT. Decision rules to select women for ovarian cancer screening will be investigated as well as decision rules for use in ovarian cancer screening.
Ventral striatum and the evaluation of memory retrieval strategies.
Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M; Scimeca, Jason M
2014-09-01
Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant's subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies.
Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi
2012-10-01
We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.
Combined rule extraction and feature elimination in supervised classification.
Liu, Sheng; Patel, Ronak Y; Daga, Pankaj R; Liu, Haining; Fu, Gang; Doerksen, Robert J; Chen, Yixin; Wilkins, Dawn E
2012-09-01
There are a vast number of biology related research problems involving a combination of multiple sources of data to achieve a better understanding of the underlying problems. It is important to select and interpret the most important information from these sources. Thus it will be beneficial to have a good algorithm to simultaneously extract rules and select features for better interpretation of the predictive model. We propose an efficient algorithm, Combined Rule Extraction and Feature Elimination (CRF), based on 1-norm regularized random forests. CRF simultaneously extracts a small number of rules generated by random forests and selects important features. We applied CRF to several drug activity prediction and microarray data sets. CRF is capable of producing performance comparable with state-of-the-art prediction algorithms using a small number of decision rules. Some of the decision rules are biologically significant.
The Analysis of Forward and Backward Dynamic Programming for Multistage Graph
NASA Astrophysics Data System (ADS)
Sitinjak, Anna Angela; Pasaribu, Elvina; Simarmata, Justin E.; Putra, Tedy; Mawengkang, Herman
2018-01-01
Dynamic programming is an optimization approach that divides the complex problems into the simple sequences of problems in which they are interrelated leading to decisions. In the dynamic programming, there is no standard formula that can be used to make a certain formulation. In this paper we use forward and backward method to find path which have the minimum cost and to know whether they make the same final decision. Convert the problem into several successive sequential stages starting on from stages 1,2,3 and 4 for forward dynamic programming and the step back from stage 4.3,2,1 for backward dynamic programming and interconnected with a decision rule in each stage. Find the optimal solution with cost principle at next stage. Based on the characteristics of the dynamic programming, the case is divided into several stages and the decision is has to be made (xk) at each stage. The results obtained at a stage are used for the states in the next stage so that at the forward stage 1, f1 (s) is obtained and used as a consideration of the decision in the next stage. In the backward, used firstly stage 4, f4 (s) is obtained and used as a consideration of the decision in the next stage. Cost forward and backward always increase steadily, because the cost in the next stage depends on the cost in the previous stage and formed the decision of each stage by taking the smallest fk value. Therefore the forward and backward approaches have the same result.
Leroy, S; Marc, E; Adamsbaum, C; Gendrel, D; Bréart, G; Chalumeau, M
2006-03-01
To test the reproducibility of a highly sensitive clinical decision rule proposed to predict vesicoureteral reflux (VUR) after a first febrile urinary tract infection in children. This rule combines clinical (family history of uropathology, male gender, young age), biological (raised C reactive protein), and radiological (urinary tract dilation on renal ultrasound) predictors in a score, and provides 100% sensitivity. A retrospective hospital based cohort study included all children, 1 month to 4 years old, with a first febrile urinary tract infection. The sensitivities and specificities of the rule at the two previously proposed score thresholds (< or =0 and < or =5) to predict respectively, all-grade or grade > or =3 VUR, were calculated. A total of 149 children were included. VUR prevalence was 25%. The rule yielded 100% sensitivity and 3% specificity for all-grade VUR, and 93% sensitivity and 13% specificity for grade > or =3 VUR. Some methodological weaknesses explain this lack of reproducibility. The reproducibility of the previously proposed decision rule was poor and its potential contribution to clinical management of children with febrile urinary tract infection seems to be modest.
Leroy, S; Marc, E; Adamsbaum, C; Gendrel, D; Bréart, G; Chalumeau, M
2006-01-01
Aims To test the reproducibility of a highly sensitive clinical decision rule proposed to predict vesicoureteral reflux (VUR) after a first febrile urinary tract infection in children. This rule combines clinical (family history of uropathology, male gender, young age), biological (raised C reactive protein), and radiological (urinary tract dilation on renal ultrasound) predictors in a score, and provides 100% sensitivity. Methods A retrospective hospital based cohort study included all children, 1 month to 4 years old, with a first febrile urinary tract infection. The sensitivities and specificities of the rule at the two previously proposed score thresholds (⩽0 and ⩽5) to predict respectively, all‐grade or grade ⩾3 VUR, were calculated. Results A total of 149 children were included. VUR prevalence was 25%. The rule yielded 100% sensitivity and 3% specificity for all‐grade VUR, and 93% sensitivity and 13% specificity for grade ⩾3 VUR. Some methodological weaknesses explain this lack of reproducibility. Conclusions The reproducibility of the previously proposed decision rule was poor and its potential contribution to clinical management of children with febrile urinary tract infection seems to be modest. PMID:15890693
Klaczynski, Paul A
2011-05-01
To examine age trends in precedent-setting decisions and the effects of these decisions on perceptions of authorities, preadolescents and adolescents were presented with deontic rule infractions that occurred in the absence or presence of mitigating circumstances. In Study 1, in the absence of mitigating circumstances, adolescents recommended punishing rule violations more than preadolescents; when mitigating circumstances were present, adolescents recommended punishing infractions less than preadolescents. In Study 2, before and after receiving information that authorities had punished or permitted rule violations, participants indicated their beliefs in authority legitimacy, rule strength, and rule deterrence value. In the absence of mitigating circumstances, beliefs strengthened when infractions were punished and beliefs weakened when infractions were permitted. When mitigating circumstances were present and authorities punished violations, preadolescents' legitimacy and deterrence beliefs strengthened. Adolescents' deterrence beliefs strengthened, but their beliefs in authority legitimacy weakened. When justifiable infractions were permitted, preadolescents' legitimacy and deterrence beliefs weakened, whereas adolescents' beliefs strengthened. Discussion focuses on age differences in legitimacy beliefs and understanding the consequences of setting precedents and on the relevance of the findings to theories of deontic reasoning, moral judgments, and epistemological development. Copyright © 2010 Elsevier Inc. All rights reserved.
Babl, Franz E; Lyttle, Mark D; Bressan, Silvia; Borland, Meredith; Phillips, Natalie; Kochar, Amit; Dalziel, Stuart R; Dalton, Sarah; Cheek, John A; Furyk, Jeremy; Gilhotra, Yuri; Neutze, Jocelyn; Ward, Brenton; Donath, Susan; Jachno, Kim; Crowe, Louise; Williams, Amanda; Oakley, Ed
2014-06-13
Head injuries in children are responsible for a large number of emergency department visits. Failure to identify a clinically significant intracranial injury in a timely fashion may result in long term neurodisability and death. Whilst cranial computed tomography (CT) provides rapid and definitive identification of intracranial injuries, it is resource intensive and associated with radiation induced cancer. Evidence based head injury clinical decision rules have been derived to aid physicians in identifying patients at risk of having a clinically significant intracranial injury. Three rules have been identified as being of high quality and accuracy: the Canadian Assessment of Tomography for Childhood Head Injury (CATCH) from Canada, the Children's Head Injury Algorithm for the Prediction of Important Clinical Events (CHALICE) from the UK, and the prediction rule for the identification of children at very low risk of clinically important traumatic brain injury developed by the Pediatric Emergency Care Applied Research Network (PECARN) from the USA. This study aims to prospectively validate and compare the performance accuracy of these three clinical decision rules when applied outside the derivation setting. This study is a prospective observational study of children aged 0 to less than 18 years presenting to 10 emergency departments within the Paediatric Research in Emergency Departments International Collaborative (PREDICT) research network in Australia and New Zealand after head injuries of any severity. Predictor variables identified in CATCH, CHALICE and PECARN clinical decision rules will be collected. Patients will be managed as per the treating clinicians at the participating hospitals. All patients not undergoing cranial CT will receive a follow up call 14 to 90 days after the injury. Outcome data collected will include results of cranial CTs (if performed) and details of admission, intubation, neurosurgery and death. The performance accuracy of each of the rules will be assessed using rule specific outcomes and inclusion and exclusion criteria. This study will allow the simultaneous comparative application and validation of three major paediatric head injury clinical decision rules outside their derivation setting. The study is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR)- ACTRN12614000463673 (registered 2 May 2014).
A Simple Demonstration of a General Rule for the Variation of Magnetic Field with Distance
ERIC Educational Resources Information Center
Kodama, K.
2009-01-01
We describe a simple experiment demonstrating the variation in magnitude of a magnetic field with distance. The method described requires only an ordinary magnetic compass and a permanent magnet. The proposed graphical analysis illustrates a unique method for deducing a general rule of magnetostatics. (Contains 1 table and 6 figures.)
Hess, Erik P; Wells, George A; Jaffe, Allan; Stiell, Ian G
2008-01-01
Background Chest pain is the second most common chief complaint in North American emergency departments. Data from the U.S. suggest that 2.1% of patients with acute myocardial infarction and 2.3% of patients with unstable angina are misdiagnosed, with slightly higher rates reported in a recent Canadian study (4.6% and 6.4%, respectively). Information obtained from the history, 12-lead ECG, and a single set of cardiac enzymes is unable to identify patients who are safe for early discharge with sufficient sensitivity. The 2007 ACC/AHA guidelines for UA/NSTEMI do not identify patients at low risk for adverse cardiac events who can be safely discharged without provocative testing. As a result large numbers of low risk patients are triaged to chest pain observation units and undergo provocative testing, at significant cost to the healthcare system. Clinical decision rules use clinical findings (history, physical exam, test results) to suggest a diagnostic or therapeutic course of action. Currently no methodologically robust clinical decision rule identifies patients safe for early discharge. Methods/design The goal of this study is to derive a clinical decision rule which will allow emergency physicians to accurately identify patients with chest pain who are safe for early discharge. The study will utilize a prospective cohort design. Standardized clinical variables will be collected on all patients at least 25 years of age complaining of chest pain prior to provocative testing. Variables strongly associated with the composite outcome acute myocardial infarction, revascularization, or death will be further analyzed with multivariable analysis to derive the clinical rule. Specific aims are to: i) apply standardized clinical assessments to patients with chest pain, incorporating results of early cardiac testing; ii) determine the inter-observer reliability of the clinical information; iii) determine the statistical association between the clinical findings and the composite outcome; and iv) use multivariable analysis to derive a highly sensitive clinical decision rule to guide triage decisions. Discussion The study will derive a highly sensitive clinical decision rule to identify low risk patients safe for early discharge. This will improve patient care, lower healthcare costs, and enhance flow in our busy and overcrowded emergency departments. PMID:18254973
Crises and Collective Socio-Economic Phenomena: Simple Models and Challenges
NASA Astrophysics Data System (ADS)
Bouchaud, Jean-Philippe
2013-05-01
Financial and economic history is strewn with bubbles and crashes, booms and busts, crises and upheavals of all sorts. Understanding the origin of these events is arguably one of the most important problems in economic theory. In this paper, we review recent efforts to include heterogeneities and interactions in models of decision. We argue that the so-called Random Field Ising model ( rfim) provides a unifying framework to account for many collective socio-economic phenomena that lead to sudden ruptures and crises. We discuss different models that can capture potentially destabilizing self-referential feedback loops, induced either by herding, i.e. reference to peers, or trending, i.e. reference to the past, and that account for some of the phenomenology missing in the standard models. We discuss some empirically testable predictions of these models, for example robust signatures of rfim-like herding effects, or the logarithmic decay of spatial correlations of voting patterns. One of the most striking result, inspired by statistical physics methods, is that Adam Smith's invisible hand can fail badly at solving simple coordination problems. We also insist on the issue of time-scales, that can be extremely long in some cases, and prevent socially optimal equilibria from being reached. As a theoretical challenge, the study of so-called "detailed-balance" violating decision rules is needed to decide whether conclusions based on current models (that all assume detailed-balance) are indeed robust and generic.
Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care.
Sesen, M Berkan; Peake, Michael D; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael
2014-09-06
Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments.
Flu Diagnosis System Using Jaccard Index and Rough Set Approaches
NASA Astrophysics Data System (ADS)
Efendi, Riswan; Azah Samsudin, Noor; Mat Deris, Mustafa; Guan Ting, Yip
2018-04-01
Jaccard index and rough set approaches have been frequently implemented in decision support systems with various domain applications. Both approaches are appropriate to be considered for categorical data analysis. This paper presents the applications of sets operations for flu diagnosis systems based on two different approaches, such as, Jaccard index and rough set. These two different approaches are established using set operations concept, namely intersection and subset. The step-by-step procedure is demonstrated from each approach in diagnosing flu system. The similarity and dissimilarity indexes between conditional symptoms and decision are measured using Jaccard approach. Additionally, the rough set is used to build decision support rules. Moreover, the decision support rules are established using redundant data analysis and elimination of unclassified elements. A number data sets is considered to attempt the step-by-step procedure from each approach. The result has shown that rough set can be used to support Jaccard approaches in establishing decision support rules. Additionally, Jaccard index is better approach for investigating the worst condition of patients. While, the definitely and possibly patients with or without flu can be determined using rough set approach. The rules may improve the performance of medical diagnosis systems. Therefore, inexperienced doctors and patients are easier in preliminary flu diagnosis.
Scheeline, Alexander
2017-10-01
Designing a spectrometer requires knowledge of the problem to be solved, the molecules whose properties will contribute to a solution of that problem and skill in many subfields of science and engineering. A seemingly simple problem, design of an ultraviolet, visible, and near-infrared spectrometer, is used to show the reasoning behind the trade-offs in instrument design. Rather than reporting a fully optimized instrument, the Yin and Yang of design choices, leading to decisions about financial cost, materials choice, resolution, throughput, aperture, and layout are described. To limit scope, aspects such as grating blaze, electronics design, and light sources are not presented. The review illustrates the mixture of mathematical rigor, rule of thumb, esthetics, and availability of components that contribute to the art of spectrometer design.
Orthogonal search-based rule extraction for modelling the decision to transfuse.
Etchells, T A; Harrison, M J
2006-04-01
Data from an audit relating to transfusion decisions during intermediate or major surgery were analysed to determine the strengths of certain factors in the decision making process. The analysis, using orthogonal search-based rule extraction (OSRE) from a trained neural network, demonstrated that the risk of tissue hypoxia (ROTH) assessed using a 100-mm visual analogue scale, the haemoglobin value (Hb) and the presence or absence of on-going haemorrhage (OGH) were able to reproduce the transfusion decisions with a joint specificity of 0.96 and sensitivity of 0.93 and a positive predictive value of 0.9. The rules indicating transfusion were: 1. ROTH > 32 mm and Hb < 94 g x l(-1); 2. ROTH > 13 mm and Hb < 87 g x l(-1); 3. ROTH > 38 mm, Hb < 102 g x l(-1) and OGH; 4. Hb < 78 g x l(-1).
Magid, Steven K; Pancoast, Paul E; Fields, Theodore; Bradley, Diane G; Williams, Robert B
2007-01-01
Clinical decision support can be employed to increase patient safety and improve workflow efficiencies for physicians and other healthcare providers. Physician input into the design and deployment of clinical decision support systems can increase the utility of the alerts and reduce the likelihood of "alert fatigue." The Hospital for Special Surgery is a 146-bed orthopedic facility that performs approximately 18,000 surgeries a year Efficient work processes are a necessity. The facility began implementing a new electronic health record system in June 2005 and plan to go live in summer 2007. This article reports on some of the clinical decision support rules and alerts being incorporated into the facility's system in the following categories--high-risk, high-frequency scenarios, rules that provide efficiencies and value from the presciber perspective, and rules that relate to patient safety.
How power influences moral thinking.
Lammers, Joris; Stapel, Diederik A
2009-08-01
The authors conducted 5 studies to test the idea that both thinking about and having power affects the way in which people resolve moral dilemmas. It is shown that high power increases the use of rule-based (deontological) moral thinking styles, whereas low power increases reliance on outcome-based (consequentialist) moral thinking. Stated differently, in determining whether an act is right or wrong, the powerful focus on whether rules and principles are violated, whereas the powerless focus on the consequences. For this reason, the powerful are also more inclined to stick to the rules, irrespective of whether this has positive or negative effects, whereas the powerless are more inclined to make exceptions. The first 3 experiments show that thinking about power increases rule-based thinking and decreases outcome-based thinking in participants' moral decision making. A 4th experiment shows the mediating role of moral orientation in the effect of power on moral decisions. The 5th experiment demonstrates the role of self-interest by showing that the power-moral link is reversed when rule-based decisions threaten participants' own self-interests.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-09-20
... regarding EPA's Zinc Fertilizer Rule in a separate final rule (following the proposed rule) as it... the Zinc Fertilizer Rule. Today's action responds to that comment but does not agree with it and, thus, finalizes the Agency's decision to authorize Rhode Island for EPA's Zinc Fertilizer Rule. In addition, the...
ERIC Educational Resources Information Center
Torres, Mario S., Jr.
2012-01-01
This study examined federal and state court decisions related to student Fourth Amendment rights following the "New Jersey v. T.L.O." ruling in 1985. There has been minimal research in judicial treatment of students' Fourth Amendment rights across regions of the country and less to what extent regional rulings implicitly or explicitly…
An Intelligent Decision Support System for Workforce Forecast
2011-01-01
ARIMA ) model to forecast the demand for construction skills in Hong Kong. This model was based...Decision Trees ARIMA Rule Based Forecasting Segmentation Forecasting Regression Analysis Simulation Modeling Input-Output Models LP and NLP Markovian...data • When results are needed as a set of easily interpretable rules 4.1.4 ARIMA Auto-regressive, integrated, moving-average ( ARIMA ) models
Brain Regions Involved in the Learning and Application of Reward Rules in a Two-Deck Gambling Task
ERIC Educational Resources Information Center
Hartstra, E.; Oldenburg, J. F. E.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.
2010-01-01
Decision-making involves the ability to choose between competing actions that are associated with uncertain benefits and penalties. The Iowa Gambling Task (IGT), which mimics real-life decision-making, involves learning a reward-punishment rule over multiple trials. Patients with damage to ventromedial prefrontal cortex (VMPFC) show deficits…
We will collaborate with investigators from University College London to test a screening decision rule in preclinical serial samples from the U.K. Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) to learn if the panel can do better than CA125 alone. The UKCTOCS is an ideal setting for retrospective validation of an early detection marker panel and decision rule because it offers serial samples collected annually and use of imaging in women with rising CA125. Multi-modal strategies using serum markers HE4, MSLN, MMP7, and CA125 will be compared to strategies relying exclusively on CA125 and transvaginal sonography (TVS).
Decision rules for unbiased inventory estimates
NASA Technical Reports Server (NTRS)
Argentiero, P. D.; Koch, D.
1979-01-01
An efficient and accurate procedure for estimating inventories from remote sensing scenes is presented. In place of the conventional and expensive full dimensional Bayes decision rule, a one-dimensional feature extraction and classification technique was employed. It is shown that this efficient decision rule can be used to develop unbiased inventory estimates and that for large sample sizes typical of satellite derived remote sensing scenes, resulting accuracies are comparable or superior to more expensive alternative procedures. Mathematical details of the procedure are provided in the body of the report and in the appendix. Results of a numerical simulation of the technique using statistics obtained from an observed LANDSAT scene are included. The simulation demonstrates the effectiveness of the technique in computing accurate inventory estimates.
Reasoning and Knowledge Acquisition Framework for 5G Network Analytics
2017-01-01
Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration. PMID:29065473
Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.
Sotelo Monge, Marco Antonio; Maestre Vidal, Jorge; García Villalba, Luis Javier
2017-10-21
Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration.
Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis.
Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta
2017-01-01
In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants' choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection.
Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis
Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta
2017-01-01
In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants’ choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection. PMID:28867996
Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.
Barros, Rodrigo C; Winck, Ana T; Machado, Karina S; Basgalupp, Márcio P; de Carvalho, André C P L F; Ruiz, Duncan D; de Souza, Osmar Norberto
2012-11-21
This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.
Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data
2012-01-01
Background This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor. PMID:23171000
The expert explorer: a tool for hospital data visualization and adverse drug event rules validation.
Băceanu, Adrian; Atasiei, Ionuţ; Chazard, Emmanuel; Leroy, Nicolas
2009-01-01
An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).
Aktipis, C. Athena
2011-01-01
The evolution of cooperation through partner choice mechanisms is often thought to involve relatively complex cognitive abilities. Using agent-based simulations I model a simple partner choice rule, the ‘Walk Away’ rule, where individuals stay in groups that provide higher returns (by virtue of having more cooperators), and ‘Walk Away’ from groups providing low returns. Implementing this conditional movement rule in a public goods game leads to a number of interesting findings: 1) cooperators have a selective advantage when thresholds are high, corresponding to low tolerance for defectors, 2) high thresholds lead to high initial rates of movement and low final rates of movement (after selection), and 3) as cooperation is selected, the population undergoes a spatial transition from high migration (and a many small and ephemeral groups) to low migration (and large and stable groups). These results suggest that the very simple ‘Walk Away’ rule of leaving uncooperative groups can favor the evolution of cooperation, and that cooperation can evolve in populations in which individuals are able to move in response to local social conditions. A diverse array of organisms are able to leave degraded physical or social environments. The ubiquitous nature of conditional movement suggests that ‘Walk Away’ dynamics may play an important role in the evolution of social behavior in both cognitively complex and cognitively simple organisms. PMID:21666771
Rule-governed behavior: teaching a preliminary repertoire of rule-following to children with autism.
Tarbox, Jonathan; Zuckerman, Carrie K; Bishop, Michele R; Olive, Melissa L; O'Hora, Denis P
2011-01-01
Rule-governed behavior is generally considered an integral component of complex verbal repertoires but has rarely been the subject of empirical research. In particular, little or no previous research has attempted to establish rule-governed behavior in individuals who do not already display the repertoire. This study consists of two experiments that evaluated multiple exemplar training procedures for teaching a simple component skill, which may be necessary for developing a repertoire of rule-governed behavior. In both experiments, children with autism were taught to respond to simple rules that specified antecedents and the behaviors that should occur in their presence. In the first study, participants were taught to respond to rules containing "if/then" statements, where the antecedent was specified before the behavior. The second experiment was a replication and extension of the first. It involved a variation on the manner in which rules were presented. Both experiments eventually demonstrated generalization to novel rules for all participants; however variations to the standard procedure were required for several participants. Results suggest that rule-following can be analyzed and taught as generalized operant behavior and implications for future research are discussed.
Ten simple rules for making research software more robust
2017-01-01
Software produced for research, published and otherwise, suffers from a number of common problems that make it difficult or impossible to run outside the original institution or even off the primary developer’s computer. We present ten simple rules to make such software robust enough to be run by anyone, anywhere, and thereby delight your users and collaborators. PMID:28407023
Gould, Sara J.; Cardone, Dennis A.; Munyak, John; Underwood, Philipp J.; Gould, Stephen A.
2014-01-01
Context: Sidelines coverage presents unique challenges in the evaluation of injured athletes. Health care providers may be confronted with the question of when to obtain radiographs following an injury. Given that most sidelines coverage occurs outside the elite level, radiographs are not readily available at the time of injury, and the decision of when to send a player for radiographs must be made based on physical examination. Clinical tools have been developed to aid in identifying injuries that are likely to result in radiographically important fractures or dislocations. Evidence Acquisition: A search for the keywords x-ray and decision rule along with the anatomic locations shoulder, elbow, wrist, knee, and ankle was performed using the PubMed database. No limits were set regarding year of publication. We selected meta-analyses, randomized controlled trials, and survey results. Our selection focused on the largest, most well-studied published reports. We also attempted to include studies that reported the application of the rules to the field of sports medicine. Study Design: Retrospective literature review. Level of Evidence: Level 4. Results: The Ottawa Foot and Ankle Rules have been validated and implemented and are appropriate for use in both pediatric and adult populations. The Ottawa Knee Rules have been widely studied, validated, and accepted for evaluation of knee injuries. There are promising studies of decision rules for clinically important fractures of the wrist, but these studies have not been validated. The elbow has been evaluated with good outcomes via the elbow extension test, which has been validated in both single and multicenter studies. Currently, there are no reliable clinical decision tools for traumatic sports injuries to the shoulder to aid in the decision of when to obtain radiographs. Conclusion: Clinical decision tools have been developed to aid in the diagnosis and management of injuries commonly sustained during sporting events. Tools that have been appropriately validated in populations outside the initial study population can assist sports medicine physicians in the decision of when to get radiographs from the sidelines. PMID:24790698
Nassar, Matthew R; Wilson, Robert C; Heasly, Benjamin; Gold, Joshua I
2010-09-15
Maintaining appropriate beliefs about variables needed for effective decision making can be difficult in a dynamic environment. One key issue is the amount of influence that unexpected outcomes should have on existing beliefs. In general, outcomes that are unexpected because of a fundamental change in the environment should carry more influence than outcomes that are unexpected because of persistent environmental stochasticity. Here we use a novel task to characterize how well human subjects follow these principles under a range of conditions. We show that the influence of an outcome depends on both the error made in predicting that outcome and the number of similar outcomes experienced previously. We also show that the exact nature of these tendencies varies considerably across subjects. Finally, we show that these patterns of behavior are consistent with a computationally simple reduction of an ideal-observer model. The model adjusts the influence of newly experienced outcomes according to ongoing estimates of uncertainty and the probability of a fundamental change in the process by which outcomes are generated. A prior that quantifies the expected frequency of such environmental changes accounts for individual variability, including a positive relationship between subjective certainty and the degree to which new information influences existing beliefs. The results suggest that the brain adaptively regulates the influence of decision outcomes on existing beliefs using straightforward updating rules that take into account both recent outcomes and prior expectations about higher-order environmental structure.
Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen
2017-11-10
Cardiovascular disease(CVD) is the leading cause of mortality among patients with type 2 diabetes mellitus(T2DM), and a risk classification model for CVD among primary care diabetic patients is pivotal for risk-based interventions and patient information. This study developed a simple tool for a 5-year CVD risk prediction for primary care Chinese patients with T2DM. A retrospective cohort study was conducted on 137,935 primary care Chinese T2DM patients aged 18-79 years without history of CVD between 1 January 2010 and 31 December 2010. New events of CVD of the cohort over a median follow up of 5 years were extracted from the medical records. A classification rule of 5-year CVD risk was obtained from the derivation cohort and validated in the validation cohort. Significant risk factors included in decision tree were age, gender, smoking status, diagnosis duration, obesity, unsatisfactory control on haemoglobin A1c and cholesterol, albuminuria and stage of chronic kidney disease, which categorized patients into five 5-year CVD risk groups(<5%; 5-9%; 10-14%; 15-19% and ≥20%). Taking the group with the lowest CVD risk, the hazard ratios varied from 1.92(1.77,2.08) to 8.46(7.75,9.24). The present prediction model performed comparable discrimination and better calibration from the plot compared to other current existing models.
Empirical study on voting power in participatory forest planning.
Vainikainen, N; Kangas, A; Kangas, J
2008-07-01
Multicriteria decision support systems are applied in natural resource management in order to clarify the planning process for the stakeholders, to make all available information usable and all objectives manageable. Especially when the public is involved in planning, the decision support system should be easy to comprehend, transparent and fair. Social choice theory has recently been applied to group decision-making in natural resources management to accomplish these objectives. Although voting forms the basis of democracy, and is usually taken as a fair method, the influence of voters over the outcome may vary. It is also possible to vote strategically to improve the results from each stakeholder's point of view. This study examines the use of social choice theory in revealing stakeholders' preferences in participatory forest planning, and the influence of different voters on the outcome. The positional voting rules examined were approval voting and Borda count, but both rules were slightly modified for the purposes of this study. The third rule examined, cumulative rule, resembles utilitarian voting rules. The voting rules were tested in a real participatory forest planning situation in eastern Lapland, Finland. All voting rules resulted in a different joint order of importance of the criteria. Yet, the preference orders produced had also a lot in common and the criteria could be divided into three quite distinct groups according to their importance. The influence of individual voters varied between the voting rules, and in each case different voter was the most influential.
A probabilistic method to diagnose faults of air handling units
NASA Astrophysics Data System (ADS)
Dey, Debashis
Air handling unit (AHU) is one of the most extensively used equipment in large commercial buildings. This device is typically customized and lacks quality system integration which can result in hardwire failures and controller errors. Air handling unit Performance Assessment Rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon sensor data and control signals that are commonly available in these systems. Although APAR has many advantages over other methods, for example no training data required and easy to implement commercially, most of the time it is unable to provide the diagnosis of the faults. For instance, a fault on temperature sensor could be fixed bias, drifting bias, inappropriate location, complete failure. Also a fault in mixing box can be return and outdoor damper leak or stuck. In addition, when multiple rules are satisfied the list of faults increases. There is no proper way to have the correct diagnosis for rule based fault detection system. To overcome this limitation we proposed Bayesian Belief Network (BBN) as a diagnostic tool. BBN can be used to simulate diagnostic thinking of FDD experts through a probabilistic way. In this study we developed a new way to detect and diagnose faults in AHU through combining APAR rules and Bayesian Belief network. Bayesian Belief Network is used as a decision support tool for rule based expert system. BBN is highly capable to prioritize faults when multiple rules are satisfied simultaneously. Also it can get information from previous AHU operating conditions and maintenance records to provide proper diagnosis. The proposed model is validated with real time measured data of a campus building at University of Texas at San Antonio (UTSA).The results show that BBN is correctly able to prioritize faults which can be verified by manual investigation.
Wright, Adam; Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W
2011-01-01
Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100,000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100,000 records to assess its accuracy. Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100,000 randomly selected patients showed high sensitivity (range: 62.8-100.0%) and positive predictive value (range: 79.8-99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.
NASA Astrophysics Data System (ADS)
Herd, A.; Wolff, M.
2012-01-01
Extended mission operations, such as human spaceflight to Mars provide an opportunity for take current human exploration beyond Low Earth Orbit, such as the operations undertaken on the International Space Station (ISS). This opportunity also presents a challenge in terms of extending what we currently understand as "remote operations" performed on ISS, offering learning beyond that gained from the successful moon- lander expeditions. As such there is a need to assess how the existing operations concept of ground support teams directing (and supporting) on-orbit ISS operations can be applied in the extended mission concept. The current mission support concept involves three interacting operations products - a short term plan, crew procedures and flight rules. Flight rules (for ISS operations) currently provide overall planning, engineering and operations constraints (including those derived from a safety perspective) in the form of a rule book. This paper will focus specifically on flight rules, and describe the current use of them, and assess the future role of flight rules to support exploration, including the deployment of decision support tools (DSTs) to ensure flight rule compliancy for missions with minimal ground support. Taking consideration of the historical development of pre-planned decisions, and their manifestation within the operations environment, combined with the extended remoteness of human exploration missions, we will propose a future development of this product and a platform on which it could be presented.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-01-05
... decisions. The MSRB is firmly of the belief that the proposed rule change is within its statutory authority... Proposed Rule Change Relating to Rule G-32, on Disclosures in Connection With Primary Offerings, Form G-32... proposed rule change relating to Rule G-32, on disclosures in connection with primary offerings, Form G-32...
McCoyd, Judith L M
2009-10-01
The sociology of emotion is rapidly evolving and has implications for medical settings. Advancing medical technologies create new contexts for decision-making and emotional reaction that are framed by "feeling rules." Feeling rules guide not only behavior, but also how one believes one should feel, thereby causing one to attempt to bring one's authentic feelings into line with perceived feeling rules. Using qualitative data, the theoretical existence of feeling rules in pregnancy and prenatal testing is confirmed. Further examination extends this analysis: at times of technological development feeling rules are often discrepant, leaving patients with unscripted emotion work. Data from a study of women who interrupted anomalous pregnancies indicate that feeling rules are unclear when competing feeling rules are operating during times of societal and technological change. Because much of this occurs below the level of consciousness, medical and psychological services providers need to be aware of potential discrepancies in feeling rules and assist patients in identifying the salient feeling rules. Patients' struggles ease when they can recognize the discrepancies and assess their implications for decision-making and emotional response. (c) 2009 APA, all rights reserved.
Boosting medical diagnostics by pooling independent judgments
Kurvers, Ralf H. J. M.; Herzog, Stefan M.; Hertwig, Ralph; Krause, Jens; Carney, Patricia A.; Bogart, Andy; Argenziano, Giuseppe; Zalaudek, Iris; Wolf, Max
2016-01-01
Collective intelligence refers to the ability of groups to outperform individual decision makers when solving complex cognitive problems. Despite its potential to revolutionize decision making in a wide range of domains, including medical, economic, and political decision making, at present, little is known about the conditions underlying collective intelligence in real-world contexts. We here focus on two key areas of medical diagnostics, breast and skin cancer detection. Using a simulation study that draws on large real-world datasets, involving more than 140 doctors making more than 20,000 diagnoses, we investigate when combining the independent judgments of multiple doctors outperforms the best doctor in a group. We find that similarity in diagnostic accuracy is a key condition for collective intelligence: Aggregating the independent judgments of doctors outperforms the best doctor in a group whenever the diagnostic accuracy of doctors is relatively similar, but not when doctors’ diagnostic accuracy differs too much. This intriguingly simple result is highly robust and holds across different group sizes, performance levels of the best doctor, and collective intelligence rules. The enabling role of similarity, in turn, is explained by its systematic effects on the number of correct and incorrect decisions of the best doctor that are overruled by the collective. By identifying a key factor underlying collective intelligence in two important real-world contexts, our findings pave the way for innovative and more effective approaches to complex real-world decision making, and to the scientific analyses of those approaches. PMID:27432950
Federal Register 2010, 2011, 2012, 2013, 2014
2010-09-14
... specified in the proposed rule: i. Clarify the time frames within which members must take action to effect... a final decision of a FINRA officer or the UPC Committee under NASD Rule 11890 (Clearly Erroneous... refusal by a member to take action necessary to effectuate a final decision of a FINRA officer or the UPC...
The Supreme Court Spanking Ruling: An Issue in Debate.
ERIC Educational Resources Information Center
Welsh, Ralph S.; And Others
Few issues have polarized the educational community so completely as the 1975 and 1977 decisions by the U.S. Supreme Court to allow corporal punishment in the schools. The symposium reported here was organized and conducted following the 1975 decision but prior to the 1977 one. Three papers in support and three papers against the ruling were read,…
Code of Federal Regulations, 2010 CFR
2010-01-01
... a conference will advance its evaluation of the request. (b) Criteria. Except where modification or... rule or order. (a) OFE will consider the entire administrative record in its evaluation of the decision... request under this subpart and all interested persons will be afforded an opportunity to respond to these...
Gubhaju, Bina; De Jong, Gordon F.
2009-01-01
This research tests the thesis that the neoclassical micro-economic and the new household economic theoretical assumptions on migration decision-making rules are segmented by gender, marital status, and time frame of intention to migrate. Comparative tests of both theories within the same study design are relatively rare. Utilizing data from the Causes of Migration in South Africa national migration survey, we analyze how individually held “own-future” versus alternative “household well-being” migration decision rules effect the intentions to migrate of male and female adults in South Africa. Results from the gender and marital status specific logistic regressions models show consistent support for the different gender-marital status decision rule thesis. Specifically, the “maximizing one’s own future” neoclassical microeconomic theory proposition is more applicable for never married men and women, the “maximizing household income” proposition for married men with short-term migration intentions, and the “reduce household risk” proposition for longer time horizon migration intentions of married men and women. Results provide new evidence on the way household strategies and individual goals jointly affect intentions to move or stay. PMID:20161187
Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.
Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab
2017-09-01
Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.
Portable design rules for bulk CMOS
NASA Technical Reports Server (NTRS)
Griswold, T. W.
1982-01-01
It is pointed out that for the past several years, one school of IC designers has used a simplified set of nMOS geometric design rules (GDR) which is 'portable', in that it can be used by many different nMOS manufacturers. The present investigation is concerned with a preliminary set of design rules for bulk CMOS which has been verified for simple test structures. The GDR are defined in terms of Caltech Intermediate Form (CIF), which is a geometry-description language that defines simple geometrical objects in layers. The layers are abstractions of physical mask layers. The design rules do not presume the existence of any particular design methodology. Attention is given to p-well and n-well CMOS processes, bulk CMOS and CMOS-SOS, CMOS geometric rules, and a description of the advantages of CMOS technology.
Crawford, E D; Batuello, J T; Snow, P; Gamito, E J; McLeod, D G; Partin, A W; Stone, N; Montie, J; Stock, R; Lynch, J; Brandt, J
2000-05-01
The current study assesses artificial intelligence methods to identify prostate carcinoma patients at low risk for lymph node spread. If patients can be assigned accurately to a low risk group, unnecessary lymph node dissections can be avoided, thereby reducing morbidity and costs. A rule-derivation technology for simple decision-tree analysis was trained and validated using patient data from a large database (4,133 patients) to derive low risk cutoff values for Gleason sum and prostate specific antigen (PSA) level. An empiric analysis was used to derive a low risk cutoff value for clinical TNM stage. These cutoff values then were applied to 2 additional, smaller databases (227 and 330 patients, respectively) from separate institutions. The decision-tree protocol derived cutoff values of < or = 6 for Gleason sum and < or = 10.6 ng/mL for PSA. The empiric analysis yielded a clinical TNM stage low risk cutoff value of < or = T2a. When these cutoff values were applied to the larger database, 44% of patients were classified as being at low risk for lymph node metastases (0.8% false-negative rate). When the same cutoff values were applied to the smaller databases, between 11 and 43% of patients were classified as low risk with a false-negative rate of between 0.0 and 0.7%. The results of the current study indicate that a population of prostate carcinoma patients at low risk for lymph node metastases can be identified accurately using a simple decision algorithm that considers preoperative PSA, Gleason sum, and clinical TNM stage. The risk of lymph node metastases in these patients is < or = 1%; therefore, pelvic lymph node dissection may be avoided safely. The implications of these findings in surgical and nonsurgical treatment are significant.
Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul
2013-01-01
Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters. PMID:24204873
Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul
2013-01-01
Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters.
76 FR 18383 - Extension of Sunset Date for Attorney Advisor Program
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-04
... rule. SUMMARY: We are extending for 2 years our rule authorizing attorney advisors to conduct certain prehearing procedures and to issue fully favorable decisions. The current rule will expire on August 10, 2011... would end on August 10, 2009, unless we decided either to terminate the rule earlier or to extend it...
Ventral Striatum and the Evaluation of Memory Retrieval Strategies
Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M.; Scimeca, Jason M.
2015-01-01
Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant’s subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies. PMID:24564466
Baker, Stuart G
2018-02-01
When using risk prediction models, an important consideration is weighing performance against the cost (monetary and harms) of ascertaining predictors. The minimum test tradeoff (MTT) for ruling out a model is the minimum number of all-predictor ascertainments per correct prediction to yield a positive overall expected utility. The MTT for ruling out an added predictor is the minimum number of added-predictor ascertainments per correct prediction to yield a positive overall expected utility. An approximation to the MTT for ruling out a model is 1/[P (H(AUC model )], where H(AUC) = AUC - {½ (1-AUC)} ½ , AUC is the area under the receiver operating characteristic (ROC) curve, and P is the probability of the predicted event in the target population. An approximation to the MTT for ruling out an added predictor is 1 /[P {(H(AUC Model:2 ) - H(AUC Model:1 )], where Model 2 includes an added predictor relative to Model 1. The latter approximation requires the Tangent Condition that the true positive rate at the point on the ROC curve with a slope of 1 is larger for Model 2 than Model 1. These approximations are suitable for back-of-the-envelope calculations. For example, in a study predicting the risk of invasive breast cancer, Model 2 adds to the predictors in Model 1 a set of 7 single nucleotide polymorphisms (SNPs). Based on the AUCs and the Tangent Condition, an MTT of 7200 was computed, which indicates that 7200 sets of SNPs are needed for every correct prediction of breast cancer to yield a positive overall expected utility. If ascertaining the SNPs costs $500, this MTT suggests that SNP ascertainment is not likely worthwhile for this risk prediction.
ERIC Educational Resources Information Center
Minkiewicz, Piotr; Darewicz, Malgorzata; Iwaniak, Anna
2018-01-01
A simple equation to calculate the oxidation states (oxidation numbers) of individual atoms in molecules and ions may be introduced instead of rules associated with words alone. The equation includes two of three categories of bonds, classified as proposed by Goodstein: number of bonds with more electronegative atoms and number of bonds with less…
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-18
... solicit comments on the proposed rule change from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR..., all tied hedge transactions (regardless of whether the option order is a simple or complex order) are... simple order the execution of the option leg of a tied hedge transaction does not qualify it for any NBBO...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-03-27
... solicit comments on the proposed rule change from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR.... Purpose The purpose of the proposed rule change is to increase certain Simple Order Fees for Removing... market. Section I Amendments The Exchange proposes to amend the Simple Order fees in Section I, Part A of...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-04-16
... comments on the proposed rule change from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4... applicable to simple orders in the options class under Exchange Rule 6.42--Minimum Increments of Bids and..., with the increment of trading being the standard trading increment applicable to simple orders in the...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-03-01
... to solicit comments on the proposed rule change from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2... recently filed a rule change to amend its transaction fees and rebates for simple,\\6\\ non-complex orders.... \\6\\ C2 defines simple orders to exclude ETFs and indexes. \\7\\ See Securities Exchange Act Release No...
Profitability of simple technical trading rules of Chinese stock exchange indexes
NASA Astrophysics Data System (ADS)
Zhu, Hong; Jiang, Zhi-Qiang; Li, Sai-Ping; Zhou, Wei-Xing
2015-12-01
Although technical trading rules have been widely used by practitioners in financial markets, their profitability still remains controversial. We here investigate the profitability of moving average (MA) and trading range break (TRB) rules by using the Shanghai Stock Exchange Composite Index (SHCI) from May 21, 1992 through December 31, 2013 and Shenzhen Stock Exchange Component Index (SZCI) from April 3, 1991 through December 31, 2013. The t-test is adopted to check whether the mean returns which are conditioned on the trading signals are significantly different from unconditioned returns and whether the mean returns conditioned on the buy signals are significantly different from the mean returns conditioned on the sell signals. We find that TRB rules outperform MA rules and short-term variable moving average (VMA) rules outperform long-term VMA rules. By applying White's Reality Check test and accounting for the data snooping effects, we find that the best trading rule outperforms the buy-and-hold strategy when transaction costs are not taken into consideration. Once transaction costs are included, trading profits will be eliminated completely. Our analysis suggests that simple trading rules like MA and TRB cannot beat the standard buy-and-hold strategy for the Chinese stock exchange indexes.
Kriegeskorte, Nikolaus; Carlin, Johan D.; Rowe, James B.
2013-01-01
Behavior is governed by rules that associate stimuli with responses and outcomes. Human and monkey studies have shown that rule-specific information is widely represented in the frontoparietal cortex. However, it is not known how establishing a rule under different contexts affects its neural representation. Here, we use event-related functional MRI (fMRI) and multivoxel pattern classification methods to investigate the human brain's mechanisms of establishing and maintaining rules for multiple perceptual decision tasks. Rules were either chosen by participants or specifically instructed to them, and the fMRI activation patterns representing rule-specific information were compared between these contexts. We show that frontoparietal regions differ in the properties of their rule representations during active maintenance before execution. First, rule-specific information maintained in the dorsolateral and medial frontal cortex depends on the context in which it was established (chosen vs specified). Second, rule representations maintained in the ventrolateral frontal and parietal cortex are independent of the context in which they were established. Furthermore, we found that the rule-specific coding maintained in anticipation of stimuli may change with execution of the rule: representations in context-independent regions remain invariant from maintenance to execution stages, whereas rule representations in context-dependent regions do not generalize to execution stage. The identification of distinct frontoparietal systems with context-independent and context-dependent task rule representations, and the distinction between anticipatory and executive rule representations, provide new insights into the functional architecture of goal-directed behavior. PMID:23864675
Simultaneous Optimization of Decisions Using a Linear Utility Function.
ERIC Educational Resources Information Center
Vos, Hans J.
1990-01-01
An approach is presented to simultaneously optimize decision rules for combinations of elementary decisions through a framework derived from Bayesian decision theory. The developed linear utility model for selection-mastery decisions was applied to a sample of 43 first year medical students to illustrate the procedure. (SLD)
49 CFR 1503.655 - Initial decision.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Rules of Practice in TSA Civil Penalty Actions § 1503.655 Initial decision. (a) Contents. The ALJ may... copies of that initial decision available to all parties and the TSA decision maker. (b) Written decision... ALJ is persuasive authority in any other civil penalty action, unless appealed and reversed by the TSA...
20 CFR 501.6 - Decisions and orders.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Decisions and orders. 501.6 Section 501.6 Employees' Benefits EMPLOYEES' COMPENSATION APPEALS BOARD, DEPARTMENT OF LABOR RULES OF PROCEDURE § 501.6 Decisions and orders. (a) Decisions. A decision of the Board will contain a written opinion setting forth...
Decentralisation of Health Services in Fiji: A Decision Space Analysis.
Mohammed, Jalal; North, Nicola; Ashton, Toni
2015-11-15
Decentralisation aims to bring services closer to the community and has been advocated in the health sector to improve quality, access and equity, and to empower local agencies, increase innovation and efficiency and bring healthcare and decision-making as close as possible to where people live and work. Fiji has attempted two approaches to decentralisation. The current approach reflects a model of deconcentration of outpatient services from the tertiary level hospital to the peripheral health centres in the Suva subdivision. Using a modified decision space approach developed by Bossert, this study measures decision space created in five broad categories (finance, service organisation, human resources, access rules, and governance rules) within the decentralised services. Fiji's centrally managed historical-based allocation of financial resources and management of human resources resulted in no decision space for decentralised agents. Narrow decision space was created in the service organisation category where, with limited decision space created over access rules, Fiji has seen greater usage of its decentralised health centres. There remains limited decision space in governance. The current wave of decentralisation reveals that, whilst the workload has shifted from the tertiary hospital to the peripheral health centres, it has been accompanied by limited transfer of administrative authority, suggesting that Fiji's deconcentration reflects the transfer of workload only with decision-making in the five functional areas remaining largely centralised. As such, the benefits of decentralisation for users and providers are likely to be limited. © 2016 by Kerman University of Medical Sciences.
VanGeest, Jonathan; Weiner, Saul; Johnson, Timothy; Cummins, Deborah
2007-07-01
To develop and test an explanatory model of the impact of managed care on physicians' decisions to manipulate reimbursement rules for patients. A self-administered mailed questionnaire of a national random sample of 1124 practicing physicians in the USA. Structural equation modelling was used. The main outcome measure assessed whether or not physicians had manipulated reimbursement rules (such as exaggerated the severity of patients conditions, changed billing diagnoses, or reported signs or symptoms that the patients did not have) to help patients secure coverage for needed treatment or services. The response rate was 64% (n = 720). Physicians' decisions to manipulate reimbursement rules for patients are directly driven not only by ethical beliefs about gaming the system but also by requests from patients, the perception of insufficient time to deliver care, and the proportion of Medicaid patients. Covert advocacy is also the indirect result of utilization review hassles, primary care specialty, and practice environment. Managed care is not just a set of rules that physicians choose to follow or disobey, but an environment of competing pressures from patients, purchasers, and high workload. Reimbursement manipulation is a response to that environment, rather than simply a reflection of individual physicians' values.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-08-06
...'s Republic of China: Notice of Court Decision Not in Harmony With Final Scope Ruling and Notice of... Corporation's toolkits from the People's Republic of China (``PRC''), pursuant to the CIT's remand order in... judgment in this case is not in harmony with the Department's final scope ruling and is amending its final...
ERIC Educational Resources Information Center
Van Norman, Ethan R.; Parker, David C.
2018-01-01
Recent simulations suggest that trend line decision rules applied to curriculum-based measurement of reading progress monitoring data may lead to inaccurate interpretations unless data are collected for upward of 3 months. The authors of those studies did not manipulate goal line slope or account for a student's level of initial performance when…
Micheyl, Christophe; Dai, Huanping
2010-01-01
The equal-variance Gaussian signal-detection-theory (SDT) decision model for the dual-pair change-detection (or “4IAX”) paradigm has been described in earlier publications. In this note, we consider the equal-variance Gaussian SDT model for the related dual-pair AB vs BA identification paradigm. The likelihood ratios, optimal decision rules, receiver operating characteristics (ROCs), and relationships between d' and proportion-correct (PC) are analyzed for two special cases: that of statistically independent observations, which is likely to apply in constant-stimuli experiments, and that of highly correlated observations, which is likely to apply in experiments where stimuli are roved widely across trials or pairs. A surprising outcome of this analysis is that although these two situations lead to different optimal decision rules, the predicted ROCs and proportions of correct responses (PCs) for these two cases are not substantially different, and are either identical or similar to those observed in the basic Yes-No paradigm. PMID:19633356
Economic interpretation of environmental flow regime downstream diverted river reaches.
NASA Astrophysics Data System (ADS)
Gorla, Lorenzo; Perona, Paolo
2013-04-01
Water demand for hydropower production is increasing together with the consciousness of the importance of riparian ecosystems and biodiversity. Some Cantons in Switzerland and other alpine regions in Austria and in Sud Tirol (Italy) started replacing the inadequate concept of Minimum Flow Requirement (MFR) with a dynamic one, by releasing a fix percentage of the total inflow (e.g. 25 %) to the environment. In the same direction Perona et al. (in revision) mathematically formulated a method particularly suitable for small hydropower plants, handling the environment as a non-traditional water use, which competes with exploitators. This model uses the Principle of Equal Marginal Utility (PEMU) as optimal water allocation rule for generating like-natural flow releases while maximizing the aggregate economic benefit of all uses (Gorla and Perona, in revision). In this paper we show how redistribution policies can be interpreted in terms of PEMU, particularly we focus at traditional water repartition rules, such as the MFR, but also to dynamic ones like proportional redistribution. For the first case we show both ecological and economical arguments suggesting its inappropriateness; in the second case we highlight explicit points of strength and weakness, and suggest ways of improvement. For example the flow release allocation rule can be changed from inflow-independent ones (e.g., proportional redistribution), to inflow-dependent ones (e.g., non-proportional). The latters, having fewer constraints, can generally lead to better both ecological and economical performances. A class of simple functions, based on the PEMU, is then proposed as a suitable solution in run-of-river or small hydropower plants. Each water repartition policy underlies an ecosystem monetization. We explicit the value of the ecosystem health underlying each policy by means of the PEMU under a few assumptions, and discuss how the theoretic efficient redistribution law obtained by our approach is feasible and doesn't imply high costs or advanced management tools. Our approach is a simple but effective step towards eco-sustainability in the growing market of mini hydropower plants, where operation rules like MFR are still widespread. As such, this method is a powerful instrument for political managers to explicit contradictions thus enlightening best compromise measures/decisions. References Perona, P., Characklis, G., Duerrenmatt, D.J., in revision. Inverse parameters estimation of simple riparian benefit economical models. Journal of Environmental Management . Gorla, L. and Perona, P., in revision. On quantifying ecologically sustainable flow releases in a diverted river reach. Journal of Hydrology.
Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W
2011-01-01
Background Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. Objective To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. Study design and methods We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100 000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100 000 records to assess its accuracy. Results Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100 000 randomly selected patients showed high sensitivity (range: 62.8–100.0%) and positive predictive value (range: 79.8–99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. Conclusion We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts. PMID:21613643
Salzmann-Erikson, Martin
2017-11-01
Ward rules in psychiatric care aim to promote safety for both patients and staff. Simultaneously, ward rules are associated with increased patient violence, leading to neither a safe work environment nor a safe caring environment. Although ward rules are routinely used, few studies have explicitly accounted for their impact. To describe the process of a team development project considering ward rule issues, and to develop a working model to empower staff in their daily in-patient psychiatric nursing practices. The design of this study is explorative and descriptive. Participatory action research methodology was applied to understand ward rules. Data consists of audio-recorded group discussions, observations and field notes, together creating a data set of 556 text pages. More than 100 specific ward rules were identified. In this process, the word rules was relinquished in favor of adopting the term principles, since rules are inconsistent with a caring ideology. A linguistic transition led to the development of a framework embracing the (1) Principle of Safety, (2) Principle of Structure and (3) Principle of Interplay. The principles were linked to normative guidelines and applied ethical theories: deontology, consequentialism and ethics of care. The work model reminded staff about the principles, empowered their professional decision-making, decreased collegial conflicts because of increased acceptance for individual decisions, and, in general, improved well-being at work. Furthermore, the work model also empowered staff to find support for their decisions based on principles that are grounded in the ethics of totality.
Ontogeny of collective behavior reveals a simple attraction rule.
Hinz, Robert C; de Polavieja, Gonzalo G
2017-02-28
The striking patterns of collective animal behavior, including ant trails, bird flocks, and fish schools, can result from local interactions among animals without centralized control. Several of these rules of interaction have been proposed, but it has proven difficult to discriminate which ones are implemented in nature. As a method to better discriminate among interaction rules, we propose to follow the slow birth of a rule of interaction during animal development. Specifically, we followed the development of zebrafish, Danio rerio , and found that larvae turn toward each other from 7 days postfertilization and increase the intensity of interactions until 3 weeks. This developmental dataset allows testing the parameter-free predictions of a simple rule in which animals attract each other part of the time, with attraction defined as turning toward another animal chosen at random. This rule makes each individual likely move to a high density of conspecifics, and moving groups naturally emerge. Development of attraction strength corresponds to an increase in the time spent in attraction behavior. Adults were found to follow the same attraction rule, suggesting a potential significance for adults of other species.
NASA Astrophysics Data System (ADS)
Zhou, Lingfei; Chapuis, Yves-Andre; Blonde, Jean-Philippe; Bervillier, Herve; Fukuta, Yamato; Fujita, Hiroyuki
2004-07-01
In this paper, the authors proposed to study a model and a control strategy of a two-dimensional conveyance system based on the principles of the Autonomous Decentralized Microsystems (ADM). The microconveyance system is based on distributed cooperative MEMS actuators which can produce a force field onto the surface of the device to grip and move a micro-object. The modeling approach proposed here is based on a simple model of a microconveyance system which is represented by a 5 x 5 matrix of cells. Each cell is consisted of a microactuator, a microsensor, and a microprocessor to provide actuation, autonomy and decentralized intelligence to the cell. Thus, each cell is able to identify a micro-object crossing on it and to decide by oneself the appropriate control strategy to convey the micro-object to its destination target. The control strategy could be established through five simple decision rules that the cell itself has to respect at each calculate cycle time. Simulation and FPGA implementation results are given in the end of the paper in order to validate model and control approach of the microconveyance system.
Multiple neural network approaches to clinical expert systems
NASA Astrophysics Data System (ADS)
Stubbs, Derek F.
1990-08-01
We briefly review the concept of computer aided medical diagnosis and more extensively review the the existing literature on neural network applications in the field. Neural networks can function as simple expert systems for diagnosis or prognosis. Using a public database we develop a neural network for the diagnosis of a major presenting symptom while discussing the development process and possible approaches. MEDICAL EXPERTS SYSTEMS COMPUTER AIDED DIAGNOSIS Biomedicine is an incredibly diverse and multidisciplinary field and it is not surprising that neural networks with their many applications are finding more and more applications in the highly non-linear field of biomedicine. I want to concentrate on neural networks as medical expert systems for clinical diagnosis or prognosis. Expert Systems started out as a set of computerized " ifthen" rules. Everything was reduced to boolean logic and the promised land of computer experts was said to be in sight. It never came. Why? First the computer code explodes as the number of " ifs" increases. All the " ifs" have to interact. Second experts are not very good at reducing expertise to language. It turns out that experts recognize patterns and have non-verbal left-brain intuition decision processes. Third learning by example rather than learning by rule is the way natural brains works and making computers work by rule-learning is hideously labor intensive. Neural networks can learn from example. They learn the results
Advancing reservoir operation description in physically based hydrological models
NASA Astrophysics Data System (ADS)
Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo
2016-04-01
Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir operating strategies.
Paradis, Michelle; Stiell, Ian; Atkinson, Katherine M; Guerinet, Julien; Sequeira, Yulric; Salter, Laura; Forster, Alan J; Murphy, Malia Sq; Wilson, Kumanan
2018-06-11
The Ottawa Ankle Rules, Ottawa Knee Rule, and Canadian C-Spine Rule-together known as The Ottawa Rules-are a set of internationally validated clinical decision rules developed to decrease unnecessary diagnostic imaging in the emergency department. In this study, we sought to develop and evaluate the use of a mobile app version of The Ottawa Rules. The primary objective of this study was to determine acceptability of The Ottawa Rules app among emergency department clinicians. The secondary objective was to evaluate the effect of publicity efforts on uptake of The Ottawa Rules app. The Ottawa Rules app was developed and publicly released for free on iOS and Android operating systems in April 2016. Local and national news and academic media coverage coincided with app release. This study was conducted at a large tertiary trauma care center in Ottawa, Canada. The study was advertised through posters and electronically by email. Emergency department clinicians were approached in person to enroll via in-app consent for a 1-month study during which time they were encouraged to use the app when evaluating patients with suspected knee, foot, or neck injuries. A 23-question survey was administered at the end of the study period via email to determine self-reported frequency, perceived ease of use of the app, and participant Technology Readiness Index scores. A total of 108 emergency department clinicians completed the study including 42 nurses, 33 residents, 20 attending physicians, and 13 medical students completing emergency department rotations. The median Technology Readiness Index for this group was 3.56, indicating a moderate degree of openness for technological adoption. The majority of survey respondents indicated favorable receptivity to the app including finding it helpful to applying the rules (73/108, 67.6%), that they would recommend the app to colleagues (81/108, 75.0%), and that they would continue using the app (73/108, 67.6%). Feedback from study participants highlighted a desire for access to more clinical decision rules and a higher degree of interactivity of the app. Between April 21, 2016, and June 1, 2017, The Ottawa Rules app was downloaded approximately 4000 times across 89 countries. We have found The Ottawa Rules app to be an effective means to disseminate the Ottawa Ankle Rules, Ottawa Knee Rule, and Canadian C-Spine Rule among all levels of emergency department clinicians. We have been successful in monitoring uptake and access of the rules in the app as a result of our publicity efforts. Mobile technology can be leveraged to improve the accessibility of clinical decision tools to health professionals. ©Michelle Paradis, Ian Stiell, Katherine M Atkinson, Julien Guerinet, Yulric Sequeira, Laura Salter, Alan J Forster, Malia SQ Murphy, Kumanan Wilson. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 11.06.2018.
Code of Federal Regulations, 2010 CFR
2010-04-01
...) Application of 10-percent shareholder test to interest paid to a simple trust or grantor trust. Whether interest paid to a simple trust or grantor trust and distributed to or included in the gross income of a... 26 Internal Revenue 9 2010-04-01 2010-04-01 false Rules relating to repeal of tax on interest of...
Calendar methods of fertility regulation: a rule of thumb.
Colombo, B; Scarpa, B
1996-01-01
"[Many] illiterate women, particularly in the third world, find [it] difficult to apply usual calendar methods for the regulation of fertility. Some of them are even unable to make simple subtractions. In this paper we are therefore trying to evaluate the applicability and the efficiency of an extremely simple rule which entails only [the ability to count] a number of days, and always the same way." (SUMMARY IN ITA) excerpt
Silvestre, Liliane; Martins, Wellington P; Candido-Dos-Reis, Francisco J
2015-07-29
This study describes the accuracy of three-dimensional power Doppler (3D-PD) angiography as secondary method for differential diagnosis of ovarian tumors. Seventy-five women scheduled for surgical removal of adnexal masses were assessed by transvaginal ultrasound. Ovarian tumors were classified by IOTA simple rules and two three-dimensional blocks were recorded. In a second step analyses, a 4 cm(3) spherical sample was obtained from the highest vascularized solid area of each stored block. Vascularization index (VI), flow index (FI) and vascularization-flow index (VFI) were calculated. The repeatability was assessed by concordance correlation coefficient (CCC) and limits of agreement (LoA), and diagnostic accuracy by area under ROC curve. IOTA simple rules classified 26 cases as benign, nine as inconclusive and 40 as malignant. There were eight false positive and no false negative. Among the masses classified as inconclusive or malignant by IOTA simple rules, the CCCs were 0.91 for VI, 0.70 for FI, and 0.86 for VFI. The areas under ROC curve were 0.82 for VI, 0.67 for FI and 0.81 for VFI. 3D-PD angiography presented considerable intraobserver variability and low accuracy for identifying false positive results of IOTA simple rules.
Estimation of State Transition Probabilities: A Neural Network Model
NASA Astrophysics Data System (ADS)
Saito, Hiroshi; Takiyama, Ken; Okada, Masato
2015-12-01
Humans and animals can predict future states on the basis of acquired knowledge. This prediction of the state transition is important for choosing the best action, and the prediction is only possible if the state transition probability has already been learned. However, how our brains learn the state transition probability is unknown. Here, we propose a simple algorithm for estimating the state transition probability by utilizing the state prediction error. We analytically and numerically confirmed that our algorithm is able to learn the probability completely with an appropriate learning rate. Furthermore, our learning rule reproduced experimentally reported psychometric functions and neural activities in the lateral intraparietal area in a decision-making task. Thus, our algorithm might describe the manner in which our brains learn state transition probabilities and predict future states.
AdaBoost-based algorithm for network intrusion detection.
Hu, Weiming; Hu, Wei; Maybank, Steve
2008-04-01
Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.
Medical Data Analytics Is Not a Simple Task.
Babič, František; Vadovský, Michal; Paralič, Ján
2018-01-01
Data analytics represents a new chance for medical diagnosis and treatment to make it more effective and successful. This expectation is not so easy to achieve as it may look like at a first glance. The medical experts, doctors or general practitioners have their own vocabulary, they use specific terms and type of speaking. On the other side, data analysts have to understand the task and to select the right algorithms. The applicability of the results depends on the effectiveness of the interactions between those two worlds. This paper presents our experiences with various medical data samples in form of SWOT analysis. We identified the most important input attributes for the target diagnosis or extracted decision rules and analysed their interestingness with cooperating doctors, for most promising new cut-off values or an investigation of possible important relations hidden in data sample. In general, this type of knowledge can be used for clinical decision support, but it has to be evaluated on different samples, conditions and ideally in long-term studies. Sometimes, the interaction needed much more time than we expected at the beginning but our experiences are mostly positive.
Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges.
Klabunde, Anna; Willekens, Frans
We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.
Code of Federal Regulations, 2010 CFR
2010-04-01
... limited to any advantage, preference, privilege, license, permit, favorable decision, ruling, status, or... United States Government. Individual means a natural person. Initial decision means the written decision of the ALJ required by § 224.10 or § 224.37, and includes a revised initial decision issued following...
Code of Federal Regulations, 2010 CFR
2010-07-01
... advantage, preference, privilege, license, permit, favorable decision, ruling, status, or loan guarantee.... Initial Decision means the written decision of the ALJ required by § 42.10 or § 42.37 of this part, and includes a revised initial decision issued following a remand or a motion for reconsideration...
76 FR 28209 - Committee on Regulation
Federal Register 2010, 2011, 2012, 2013, 2014
2011-05-16
... #0; #0;Notices #0; Federal Register #0; #0; #0;This section of the FEDERAL REGISTER contains documents other than rules #0;or proposed rules that are applicable to the public. Notices of hearings #0;and investigations, committee meetings, agency decisions and rulings, #0;delegations of authority...
78 FR 22842 - Nicolet Resource Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2013-04-17
... #0; #0;Notices #0; Federal Register #0; #0; #0;This section of the FEDERAL REGISTER contains documents other than rules #0;or proposed rules that are applicable to the public. Notices of hearings #0;and investigations, committee meetings, agency decisions and rulings, #0;delegations of authority...
Bereby-Meyer, Yoella; Meyer, Joachim; Budescu, David V
2003-02-01
This paper assesses framing effects on decision making with internal uncertainty, i.e., partial knowledge, by focusing on examinees' behavior in multiple-choice (MC) tests with different scoring rules. In two experiments participants answered a general-knowledge MC test that consisted of 34 solvable and 6 unsolvable items. Experiment 1 studied two scoring rules involving Positive (only gains) and Negative (only losses) scores. Although answering all items was the dominating strategy for both rules, the results revealed a greater tendency to answer under the Negative scoring rule. These results are in line with the predictions derived from Prospect Theory (PT) [Econometrica 47 (1979) 263]. The second experiment studied two scoring rules, which allowed respondents to exhibit partial knowledge. Under the Inclusion-scoring rule the respondents mark all answers that could be correct, and under the Exclusion-scoring rule they exclude all answers that might be incorrect. As predicted by PT, respondents took more risks under the Inclusion rule than under the Exclusion rule. The results illustrate that the basic process that underlies choice behavior under internal uncertainty and especially the effect of framing is similar to the process of choice under external uncertainty and can be described quite accurately by PT. Copyright 2002 Elsevier Science B.V.
Vexler, Albert; Yu, Jihnhee
2018-04-13
A common statistical doctrine supported by many introductory courses and textbooks is that t-test type procedures based on normally distributed data points are anticipated to provide a standard in decision-making. In order to motivate scholars to examine this convention, we introduce a simple approach based on graphical tools of receiver operating characteristic (ROC) curve analysis, a well-established biostatistical methodology. In this context, we propose employing a p-values-based method, taking into account the stochastic nature of p-values. We focus on the modern statistical literature to address the expected p-value (EPV) as a measure of the performance of decision-making rules. During the course of our study, we extend the EPV concept to be considered in terms of the ROC curve technique. This provides expressive evaluations and visualizations of a wide spectrum of testing mechanisms' properties. We show that the conventional power characterization of tests is a partial aspect of the presented EPV/ROC technique. We desire that this explanation of the EPV/ROC approach convinces researchers of the usefulness of the EPV/ROC approach for depicting different characteristics of decision-making procedures, in light of the growing interest regarding correct p-values-based applications.
Newgard, C D; Hedges, J R; Stone, J V; Lenfesty, B; Diggs, B; Arthur, M; Mullins, R J
2005-12-01
To derive a clinical decision rule for people with traumatic brain injury (TBI) that enables early identification of patients requiring specialised trauma care. We collected data from 1999 through 2003 on a retrospective cohort of consecutive people aged 18-65 years with a serious head injury (AIS > or =3), transported directly from the scene of injury, and evaluated in the ED. Information on 22 demographical, physiological, radiographic, and lab variables was collected. Resource based "high therapeutic intensity" measures occurring within 72 hours of ED arrival (the outcome measure) were identified a priori and included: neurosurgical intervention, exploratory laparotomy, intensive care interventions, or death. We used classification and regression tree analysis to derive and cross validate the decision rule. 504 consecutive trauma patients were identified as having a serious head injury: 246 (49%) required at least one of the HTI measures. Five ED variables (GCS, respiratory rate, age, temperature, and pulse rate) identified subjects requiring at least one of the HTI measures with 94% sensitivity (95% CI 91 to 97%) and 63% specificity (95% CI 57 to 69%) in the derivation sample, and 90% sensitivity and 55% specificity using cross validation. This decision rule identified among a cohort of head injured patients evaluated in the ED the majority of those who urgently required specialised trauma care. The rule will require prospective validation in injured people presenting to non-tertiary care hospitals before implementation can be recommended.
Irrational decision-making in an amoeboid organism: transitivity and context-dependent preferences.
Latty, Tanya; Beekman, Madeleine
2011-01-22
Most models of animal foraging and consumer choice assume that individuals make choices based on the absolute value of items and are therefore 'economically rational'. However, frequent violations of rationality by animals, including humans, suggest that animals use comparative valuation rules. Are comparative valuation strategies a consequence of the way brains process information, or are they an intrinsic feature of biological decision-making? Here, we examine the principles of rationality in an organism with radically different information-processing mechanisms: the brainless, unicellular, slime mould Physarum polycephalum. We offered P. polycephalum amoebas a choice between food options that varied in food quality and light exposure (P. polycephalum is photophobic). The use of an absolute valuation rule will lead to two properties: transitivity and independence of irrelevant alternatives (IIA). Transitivity is satisfied if preferences have a consistent, linear ordering, while IIA states that a decision maker's preference for an item should not change if the choice set is expanded. A violation of either of these principles suggests the use of comparative rather than absolute valuation rules. Physarum polycephalum satisfied transitivity by having linear preference rankings. However, P. polycephalum's preference for a focal alternative increased when a third, inferior quality option was added to the choice set, thus violating IIA and suggesting the use of a comparative valuation process. The discovery of comparative valuation rules in a unicellular organism suggests that comparative valuation rules are ubiquitous, if not universal, among biological decision makers.
Seismic Safety Of Simple Masonry Buildings
DOE Office of Scientific and Technical Information (OSTI.GOV)
Guadagnuolo, Mariateresa; Faella, Giuseppe
2008-07-08
Several masonry buildings comply with the rules for simple buildings provided by seismic codes. For these buildings explicit safety verifications are not compulsory if specific code rules are fulfilled. In fact it is assumed that their fulfilment ensures a suitable seismic behaviour of buildings and thus adequate safety under earthquakes. Italian and European seismic codes differ in the requirements for simple masonry buildings, mostly concerning the building typology, the building geometry and the acceleration at site. Obviously, a wide percentage of buildings assumed simple by codes should satisfy the numerical safety verification, so that no confusion and uncertainty have tomore » be given rise to designers who must use the codes. This paper aims at evaluating the seismic response of some simple unreinforced masonry buildings that comply with the provisions of the new Italian seismic code. Two-story buildings, having different geometry, are analysed and results from nonlinear static analyses performed by varying the acceleration at site are presented and discussed. Indications on the congruence between code rules and results of numerical analyses performed according to the code itself are supplied and, in this context, the obtained result can provide a contribution for improving the seismic code requirements.« less
Geriatric Fever Score: a new decision rule for geriatric care.
Chung, Min-Hsien; Huang, Chien-Cheng; Vong, Si-Chon; Yang, Tzu-Meng; Chen, Kuo-Tai; Lin, Hung-Jung; Chen, Jiann-Hwa; Su, Shih-Bin; Guo, How-Ran; Hsu, Chien-Chin
2014-01-01
Evaluating geriatric patients with fever is time-consuming and challenging. We investigated independent mortality predictors of geriatric patients with fever and developed a prediction rule for emergency care, critical care, and geriatric care physicians to classify patients into mortality risk and disposition groups. Consecutive geriatric patients (≥65 years old) visiting the emergency department (ED) of a university-affiliated medical center between June 1 and July 21, 2010, were enrolled when they met the criteria of fever: a tympanic temperature ≥37.2°C or a baseline temperature elevated ≥1.3°C. Thirty-day mortality was the primary endpoint. Internal validation with bootstrap re-sampling was done. Three hundred thirty geriatric patients were enrolled. We found three independent mortality predictors: Leukocytosis (WBC >12,000 cells/mm3), Severe coma (GCS ≤ 8), and Thrombocytopenia (platelets <150 10(3)/mm3) (LST). After assigning weights to each predictor, we developed a Geriatric Fever Score that stratifies patients into two mortality-risk and disposition groups: low (4.0%) (95% CI: 2.3-6.9%): a general ward or treatment in the ED then discharge and high (30.3%) (95% CI: 17.4-47.3%): consider the intensive care unit. The area under the curve for the rule was 0.73. We found that the Geriatric Fever Score is a simple and rapid rule for predicting 30-day mortality and classifying mortality risk and disposition in geriatric patients with fever, although external validation should be performed to confirm its usefulness in other clinical settings. It might help preserve medical resources for patients in greater need.
Rules, Schema, and Decision Making.
1987-09-01
discussion ............................................................ 47 6. GENERAL DISCUSSION...65 6.3. Generality of results................................................................ 68 6.4. Implications for...3 2-1 General model of decision making
ERIC Educational Resources Information Center
Kupperman, Joel J.
1978-01-01
Explores the use of the concept of inhibition in moral philosophy. Argues that there are strong practical reasons for basing moral teaching on simple moral rules and for inculcating inhibitions about breaking these rules. (Author)
New QCD sum rules based on canonical commutation relations
NASA Astrophysics Data System (ADS)
Hayata, Tomoya
2012-04-01
New derivation of QCD sum rules by canonical commutators is developed. It is the simple and straightforward generalization of Thomas-Reiche-Kuhn sum rule on the basis of Kugo-Ojima operator formalism of a non-abelian gauge theory and a suitable subtraction of UV divergences. By applying the method to the vector and axial vector current in QCD, the exact Weinberg’s sum rules are examined. Vector current sum rules and new fractional power sum rules are also discussed.
Diagnostic accuracy and reproducibility of the Ottawa Knee Rule vs the Pittsburgh Decision Rule.
Cheung, Tung C; Tank, Yeliz; Breederveld, Roelf S; Tuinebreijer, Wim E; de Lange-de Klerk, Elly S M; Derksen, Robert J
2013-04-01
The aim of this present study was to compare the diagnostic accuracy and reproducibility of 2 clinical decision rules (the Ottawa Knee Rules [OKR] and Pittsburgh Decision Rules [PDR]) developed for selective use of x-rays in the evaluation of isolated knee trauma. Application of a decision rule leads to a more efficient evaluation of knee injuries and a reduction in health care costs. The diagnostic accuracy and reproducibility are compared in this study. A cross-sectional interobserver study was conducted in the emergency department of an urban teaching hospital from October 2008 to July 2009. Two observer groups collected data on standardized case-report forms: emergency medicine residents and surgical residents. Standard knee radiographs were performed in each patient. Participants were patients 18 years and older with isolated knee injuries. Pooled sensitivity and specificity were compared using χ(2) statistics, and interobserver agreement was calculated by using κ statistics. Ninety injuries were assessed. Seven injuries concerned fractures (7.8%). For the OKR, the pooled sensitivity and specificity were 0.86 (95% confidence interval [CI], 0.57-0.96) and 0.27 (95% CI, 0.21-0.35), respectively. The PDR had a pooled sensitivity and specificity of 0.86 (95% CI, 0.57-0.96) and 0.51 (95% CI, 0.44-0.59). The PDR was significantly (P = .002) more specific. The κ values for the OKR and PDR were 0.51 (95% CI, 0.32-0.71) and 0.71 (95% CI, 0.57-0.86), respectively. The PDR was found to be more specific than the OKR, with equal sensitivity. Interobserver agreement was moderate for the OKR and substantial for the PDR. Copyright © 2013 Elsevier Inc. All rights reserved.
Dixon, Matthew L.; Christoff, Kalina
2012-01-01
Cognitive control is a fundamental skill reflecting the active use of task-rules to guide behavior and suppress inappropriate automatic responses. Prior work has traditionally used paradigms in which subjects are told when to engage cognitive control. Thus, surprisingly little is known about the factors that influence individuals' initial decision of whether or not to act in a reflective, rule-based manner. To examine this, we took three classic cognitive control tasks (Stroop, Wisconsin Card Sorting Task, Go/No-Go task) and created novel ‘free-choice’ versions in which human subjects were free to select an automatic, pre-potent action, or an action requiring rule-based cognitive control, and earned varying amounts of money based on their choices. Our findings demonstrated that subjects' decision to engage cognitive control was driven by an explicit representation of monetary rewards expected to be obtained from rule-use. Subjects rarely engaged cognitive control when the expected outcome was of equal or lesser value as compared to the value of the automatic response, but frequently engaged cognitive control when it was expected to yield a larger monetary outcome. Additionally, we exploited fMRI-adaptation to show that the lateral prefrontal cortex (LPFC) represents associations between rules and expected reward outcomes. Together, these findings suggest that individuals are more likely to act in a reflective, rule-based manner when they expect that it will result in a desired outcome. Thus, choosing to exert cognitive control is not simply a matter of reason and willpower, but rather, conforms to standard mechanisms of value-based decision making. Finally, in contrast to current models of LPFC function, our results suggest that the LPFC plays a direct role in representing motivational incentives. PMID:23284730
The future of decision-making in critical care after Cuthbertson v. Rasouli.
Hawryluck, Laura; Baker, Andrew J; Faith, Andrew; Singh, Jeffrey M
2014-10-01
The Supreme Court of Canada (SCC) ruling on Cuthbertson v. Rasouli has implications for all acute healthcare providers. This well-publicized case involved a disagreement between healthcare providers and a patient's family regarding the principles surrounding withdrawal of life support, which the physicians involved considered no longer of medical benefit and outside the standard of care, and whether consent was required for such withdrawals. Our objective in writing this article is to clarify the implications of this ruling on the care of critically ill patients. SCC ruling Cuthbertson v. Rasouli. The SCC ruled that consent must be obtained for all treatments that serve a "health-related purpose", including withdrawal of such treatments. The SCC did not fully consider what the standard of care should be. Health-related purpose is not sufficient in and of itself to mandate treatment, and clinicians must still ensure that their patients or decision-makers are aware of the possible medical benefits, risks, and expected outcomes of treatments. The provision of treatments that have no potential to provide medical benefit and carry only risks would still fall outside the standard of care. Nevertheless, due to their health-related purpose, physicians must seek consent for the discontinuation of these treatments. The SCC ruled that due to the legal definition of "health-related purpose", which is distinct from medical benefit, consent is required to withdraw life-support and outlined the steps to be taken should conflict arise. The SCC decision did not directly address the role of medical standard of care in these situations. In order to ensure optimal decision-making and communication with patients and their families, it is critical for healthcare providers to have a clear understanding of the implications of this legal ruling on medical practice.
NASA Astrophysics Data System (ADS)
Ma, Junhai; Xie, Lei
2018-02-01
This paper, based on the China's communications and the current situation of the mobile phone industry, focuses on the stability of a supply chain system that consists of one supplier and one bounded rational retailer. We explore the influence of the decision makers' loss sensitivity and decision adjustment speed on the stability of the supply chain. It is found that when the retailer is not sensitive to the loss or adjusts decisions cautiously, the system can be stable. The single-retailer model is extended to a multi-retailer one to study the influence of competition on the system stability. The results show that the market share of each retailer does not affect the system stability when it is fixed. The decision of each retailer does not affect that of any other retailer and the system stability. We present two decision adjustment rules (;bounded rationality expectation (BRE); and "adaptive exponential smoothing (AES)") and compare their performances on the system stability, and find that the AES rule does not affect the system stability, while the BRE rule will make the system stability be sensitive to the retailers' loss sensitivity and the decision adjustment speed. We also reveal the unstable system's negative impact on the retailers' decisions and profits, to emphasize the importance to maintain the system stability.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false What are the rules for reopening a decision by an administrative law judge of the Office of Medicare Hearings and Appeals (OMHA) or by the Medicare Appeals Council (MAC)? 418.1355 Section 418.1355 Employees' Benefits SOCIAL SECURITY ADMINISTRATION MEDICARE SUBSIDIES Medicare Part B...
Price, Morgan; Davies, Iryna; Rusk, Raymond; Lesperance, Mary; Weber, Jens
2017-06-15
Potentially Inappropriate Prescriptions (PIPs) are a common cause of morbidity, particularly in the elderly. We sought to understand how the Screening Tool of Older People's Prescriptions (STOPP) prescribing criteria, implemented in a routinely used primary care Electronic Medical Record (EMR), could impact PIP rates in community (non-academic) primary care practices. We conducted a mixed-method, pragmatic, cluster, randomized control trial in research naïve primary care practices. Phase 1: In the randomized controlled trial, 40 fully automated STOPP rules were implemented as EMR alerts during a 16-week intervention period. The control group did not receive the 40 STOPP rules (but received other alerts). Participants were recruited through the OSCAR EMR user group mailing list and in person at user group meetings. Results were assessed by querying EMR data PIPs. EMR data quality probes were included. Phase 2: physicians were invited to participate in 1-hour semi-structured interviews to discuss the results. In the EMR, 40 STOPP rules were successfully implemented. Phase 1: A total of 28 physicians from 8 practices were recruited (16 in intervention and 12 in control groups). The calculated PIP rate was 2.6% (138/5308) (control) and 4.11% (768/18,668) (intervention) at baseline. No change in PIPs was observed through the intervention (P=.80). Data quality probes generally showed low use of problem list and medication list. Phase 2: A total of 5 physicians participated. All the participants felt that they were aware of the alerts but commented on workflow and presentation challenges. The calculated PIP rate was markedly less than the expected rate found in literature (2.6% and 4.0% vs 20% in literature). Data quality probes highlighted issues related to completeness of data in areas of the EMR used for PIP reporting and by the decision support such as problem and medication lists. Users also highlighted areas for better integration of STOPP guidelines with prescribing workflows. Many of the STOPP criteria can be implemented in EMRs using simple logic. However, data quality in EMRs continues to be a challenge and was a limiting step in the effectiveness of the decision support in this study. This is important as decision makers continue to fund implementation and adoption of EMRs with the expectation of the use of advanced tools (such as decision support) without ongoing review of data quality and improvement. Clinicaltrials.gov NCT02130895; https://clinicaltrials.gov/ct2/show/NCT02130895 (Archived by WebCite at http://www.webcitation.org/6qyFigSYT). ©Morgan Price, Iryna Davies, Raymond Rusk, Mary Lesperance, Jens Weber. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 15.06.2017.
Hubert, Ph; Nguyen-Huu, J-J; Boulanger, B; Chapuzet, E; Chiap, P; Cohen, N; Compagnon, P-A; Dewé, W; Feinberg, M; Lallier, M; Laurentie, M; Mercier, N; Muzard, G; Nivet, C; Valat, L
2004-11-15
This paper is the first part of a summary report of a new commission of the Société Française des Sciences et Techniques Pharmaceutiques (SFSTP). The main objective of this commission was the harmonization of approaches for the validation of quantitative analytical procedures. Indeed, the principle of the validation of theses procedures is today widely spread in all the domains of activities where measurements are made. Nevertheless, this simple question of acceptability or not of an analytical procedure for a given application, remains incompletely determined in several cases despite the various regulations relating to the good practices (GLP, GMP, ...) and other documents of normative character (ISO, ICH, FDA, ...). There are many official documents describing the criteria of validation to be tested, but they do not propose any experimental protocol and limit themselves most often to the general concepts. For those reasons, two previous SFSTP commissions elaborated validation guides to concretely help the industrial scientists in charge of drug development to apply those regulatory recommendations. If these two first guides widely contributed to the use and progress of analytical validations, they present, nevertheless, weaknesses regarding the conclusions of the performed statistical tests and the decisions to be made with respect to the acceptance limits defined by the use of an analytical procedure. The present paper proposes to review even the bases of the analytical validation for developing harmonized approach, by distinguishing notably the diagnosis rules and the decision rules. This latter rule is based on the use of the accuracy profile, uses the notion of total error and allows to simplify the approach of the validation of an analytical procedure while checking the associated risk to its usage. Thanks to this novel validation approach, it is possible to unambiguously demonstrate the fitness for purpose of a new method as stated in all regulatory documents.
40 CFR 164.90 - Initial decision.
Code of Federal Regulations, 2010 CFR
2010-07-01
....90 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS RULES OF... REFUSALS TO REGISTER, CANCELLATIONS OF REGISTRATIONS, CHANGES OF CLASSIFICATIONS, SUSPENSIONS OF... Environmental Appeals Board. The initial decision shall become the decision of the Environmental Appeals Board...
40 CFR 164.90 - Initial decision.
Code of Federal Regulations, 2011 CFR
2011-07-01
....90 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS RULES OF... REFUSALS TO REGISTER, CANCELLATIONS OF REGISTRATIONS, CHANGES OF CLASSIFICATIONS, SUSPENSIONS OF... Environmental Appeals Board. The initial decision shall become the decision of the Environmental Appeals Board...
DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia
2016-01-01
Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.
Separating Decision and Encoding Noise in Signal Detection Tasks
Cabrera, Carlos Alexander; Lu, Zhong-Lin; Dosher, Barbara Anne
2015-01-01
In this paper we develop an extension to the Signal Detection Theory (SDT) framework to separately estimate internal noise arising from representational and decision processes. Our approach constrains SDT models with decision noise by combining a multi-pass external noise paradigm with confidence rating responses. In a simulation study we present evidence that representation and decision noise can be separately estimated over a range of representative underlying representational and decision noise level configurations. These results also hold across a number of decision rules and show resilience to rule miss-specification. The new theoretical framework is applied to a visual detection confidence-rating task with three and five response categories. This study compliments and extends the recent efforts of researchers (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008; Rosner & Kochanski, 2009, Kellen, Klauer, & Singmann, 2012) to separate and quantify underlying sources of response variability in signal detection tasks. PMID:26120907
Johnson, M M
1990-03-01
This study explored the use of process tracing techniques in examining the decision-making processes of older and younger adults. Thirty-six college-age and thirty-six retirement-age participants decided which one of six cars they would purchase on the basis of computer-accessed data. They provided information search protocols. Results indicate that total time to reach a decision did not differ according to age. However, retirement-age participants used less information, spent more time viewing, and re-viewed fewer bits of information than college-age participants. Information search patterns differed markedly between age groups. Patterns of retirement-age adults indicated their use of noncompensatory decision rules which, according to decision-making literature (Payne, 1976), reduce cognitive processing demands. The patterns of the college-age adults indicated their use of compensatory decision rules, which have higher processing demands.
16 CFR 5.65 - Review of initial decision.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Review of initial decision. 5.65 Section 5.65 Commercial Practices FEDERAL TRADE COMMISSION ORGANIZATION, PROCEDURES AND RULES OF PRACTICE... initial decision. Appeals from the initial decision of the Administrative Law Judge or review by the...
Code of Federal Regulations, 2010 CFR
2010-04-01
..., permit, favorable decision, ruling, status, or loan gurarantee. (e) Claim means any request, demand, or.... (k) Initial decision means the written decision of the ALJ required by § 35.10 or § 35.37, and includes a revised initial decision issued following a remand or a motion for reconsideration. (l...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-10-12
... information collection requirements contained in its Used Motor Vehicle Trade Regulation Rule (``Used Car Rule...-5634. SUPPLEMENTARY INFORMATION: The Used Car Rule facilitates informed purchasing decisions by requiring used car dealers to disclose information about warranty coverage, if any, and the mechanical...
77 FR 52676 - Submission for OMB Review; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2012-08-30
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78 FR 62296 - Combined Notice of Filings #1
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76 FR 6596 - Submission for OMB Review; Comment Request
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2011-02-07
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78 FR 76100 - Black Hills National Forest Advisory Board
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2013-12-16
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77 FR 53168 - Submission for OMB Review; Comment Request
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78 FR 17920 - Submission for OMB Review; Comment Request
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2013-03-25
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76 FR 62336 - Submission for OMB Review; Comment Request
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2011-10-07
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77 FR 56606 - Glenn/Colusa County Resource Advisory Committee
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2012-09-13
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75 FR 71411 - Radio Broadcasting Services; Silverpeak, NV
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2010-11-23
... rule; dismissal. SUMMARY: The Audio Division dismisses the petition for rule making filed by Shamrock... Division dismissed the petition for rule making and terminated the proceeding without adoption of a final..., and released November 5, 2010. The full text of this Commission decision is available for inspection...
34 CFR 668.98 - Interlocutory appeals to the Secretary from rulings of a hearing official.
Code of Federal Regulations, 2010 CFR
2010-07-01
... a hearing official. 668.98 Section 668.98 Education Regulations of the Offices of the Department of... Secretary from rulings of a hearing official. (a) A ruling by a hearing official may not be appealed to the... issuance of the initial decision, grant a review of a ruling upon either a certification by a hearing...
Models of Quantitative Estimations: Rule-Based and Exemplar-Based Processes Compared
ERIC Educational Resources Information Center
von Helversen, Bettina; Rieskamp, Jorg
2009-01-01
The cognitive processes underlying quantitative estimations vary. Past research has identified task-contingent changes between rule-based and exemplar-based processes (P. Juslin, L. Karlsson, & H. Olsson, 2008). B. von Helversen and J. Rieskamp (2008), however, proposed a simple rule-based model--the mapping model--that outperformed the…
Scalable software architectures for decision support.
Musen, M A
1999-12-01
Interest in decision-support programs for clinical medicine soared in the 1970s. Since that time, workers in medical informatics have been particularly attracted to rule-based systems as a means of providing clinical decision support. Although developers have built many successful applications using production rules, they also have discovered that creation and maintenance of large rule bases is quite problematic. In the 1980s, several groups of investigators began to explore alternative programming abstractions that can be used to build decision-support systems. As a result, the notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) problem-solving methods--domain-independent algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper highlights how developers can construct large, maintainable decision-support systems using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.
Koontz, Lynne; Hoag, Dana L.
2005-01-01
Many programs and tools have been developed by different disciplines to facilitate group negotiation and decision making. Three examples are relevant here. First, decision analysis models such as the Analytical Hierarchy Process (AHP) are commonly used to prioritize the goals and objectives of stakeholders’ preferences for resource planning by formally structuring conflicts and assisting decision makers in developing a compromised solution (Forman, 1998). Second, institutional models such as the Legal Institutional Analysis Model (LIAM) have been used to describe the organizational rules of behavior and the institutional boundaries constraining management decisions (Lamb and others, 1998). Finally, public choice models have been used to predict the potential success of rent-seeking activity (spending additional time and money to exert political pressure) to change the political rules (Becker, 1983). While these tools have been successful at addressing various pieces of the natural resource decision making process, their use in isolation is not enough to fully depict the complexities of the physical and biological systems with the rules and constraints of the underlying economic and political systems. An approach is needed that combines natural sciences, economics, and politics.
Park, Myonghwa; Choi, Sora; Shin, A Mi; Koo, Chul Hoi
2013-02-01
The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.
Exceptional Events Submissions Table (2016 Rule)
This table contains examples of air agency submitted exceptional events demonstrations and responsive EPA decision documents that have been prepared and/or acted upon under the 2016 Exceptional Events Rule
NASA Astrophysics Data System (ADS)
Kotelnikov, E. V.; Milov, V. R.
2018-05-01
Rule-based learning algorithms have higher transparency and easiness to interpret in comparison with neural networks and deep learning algorithms. These properties make it possible to effectively use such algorithms to solve descriptive tasks of data mining. The choice of an algorithm depends also on its ability to solve predictive tasks. The article compares the quality of the solution of the problems with binary and multiclass classification based on the experiments with six datasets from the UCI Machine Learning Repository. The authors investigate three algorithms: Ripper (rule induction), C4.5 (decision trees), In-Close (formal concept analysis). The results of the experiments show that In-Close demonstrates the best quality of classification in comparison with Ripper and C4.5, however the latter two generate more compact rule sets.
A rule-based approach for the correlation of alarms to support Disaster and Emergency Management
NASA Astrophysics Data System (ADS)
Gloria, M.; Minei, G.; Lersi, V.; Pasquariello, D.; Monti, C.; Saitto, A.
2009-04-01
Key words: Simple Event Correlator, Agent Platform, Ontology, Semantic Web, Distributed Systems, Emergency Management The importance of recognition of emergency's typology to control the critical situation for security of citizens has been always recognized. It follows this aspect is very important for proper management of a hazardous event. In this work we present a solution for the recognition of emergency's typology adopted by an Italian research project, called CI6 (Centro Integrato per Servizi di Emergenza Innovativi). In our approach, CI6 receives alarms by citizen or people involved in the work (for example: police, operator of 112, and so on). CI6 represents any alarm by a set of information, including a text that describes it and obtained when the user points out the danger, and a pair of coordinates for its location. The system realizes an analysis of text and automatically infers information on the type of emergencies by means a set of parsing rules and rules of inference applied by a independent module: a correlator of events based on their log and called Simple Event Correlator (SEC). SEC, integrated in CI6's platform, is an open source and platform independent event correlation tool. SEC accepts input both files and text derived from standard input, making it flexible because it can be matched to any application that is able to write its output to a file stream. The SEC configuration is stored in text files as rules, each rule specifying an event matching condition, an action list, and optionally a Boolean expression whose truth value decides whether the rule can be applied at a given moment. SEC can produce output events by executing user-specified shell scripts or programs, by writing messages to files, and by various other means. SEC has been successfully applied in various domains like network management, system monitoring, data security, intrusion detection, log file monitoring and analysis, etc; it has been used or integrated with many application as CiscoWorks, HP OpenView NNM and Operation, BMC Patrol, etc. Analysis of text of an alarm can detect some keywords that allow to classify the particular event. The inference rules were developed by means an analysis about news regard real emergency found by web reaserches. We have seen that often a kind of emergency is characterized by more keyword. Keywords are not uniquely associated with a specific emergency, but they can be shared by different types of emergencies (such as. keyword "landslide" can be associated both emergency "landslide" and emergency "Flood"). However, the identification of two or more keywords associated with a particular type of emergency identified in most cases the correct type of emergency. So, for example, if text contains words as "water", "flood", "overflowing", "landslide" o other words belonging to the set of defined keywords or words that have some root of keywords, the system "decides" that this alarm belongs to specific typology, in this case "flood typology". The system has the memory of this information, so if a new alarm is reported and belongs to one of the typology already identified, it proceeds with the comparison of coordinates. The comparison between the centers of the alarms allows to see if they describe an area inscribed in an ideal circle that has centered on the first alarm and radius defined by the typology above mentioned. If this happens the system CI6 creates an emergency that has centered on the centre of that area and typology equal to that of the alarms. It follows that an emergency is represented by at least two alarms. Thus, the system suggests to manager (CI6's user) the possibility that most alarms can concern same events and makes a classification of this event. It is important to stress that CI6 is a system of decision support, hence also this service is limited to providing advice to the user to facilitate his task, leaving him the decision to accept it or not. REFERENCES SEC (Simple Event Correlator), http://kodu.neti.ee/~risto/sec/ M. Gloria,V. Lersi, G. Minei, D. Pasquariello, C. Monti, A. Saitto, "A Semantic WEB Services Platform to support Disaster and Emergency Management", 4th biennial Meeting of International Environmental Modelling and Software Society (iEMSs), 2008
Flexible functional regression methods for estimating individualized treatment regimes.
Ciarleglio, Adam; Petkova, Eva; Tarpey, Thaddeus; Ogden, R Todd
2016-01-01
A major focus of personalized medicine is on the development of individualized treatment rules. Good decision rules have the potential to significantly advance patient care and reduce the burden of a host of diseases. Statistical methods for developing such rules are progressing rapidly, but few methods have considered the use of pre-treatment functional data to guide in decision-making. Furthermore, those methods that do allow for the incorporation of functional pre-treatment covariates typically make strong assumptions about the relationships between the functional covariates and the response of interest. We propose two approaches for using functional data to select an optimal treatment that address some of the shortcomings of previously developed methods. Specifically, we combine the flexibility of functional additive regression models with Q -learning or A -learning in order to obtain treatment decision rules. Properties of the corresponding estimators are discussed. Our approaches are evaluated in several realistic settings using synthetic data and are applied to real data arising from a clinical trial comparing two treatments for major depressive disorder in which baseline imaging data are available for subjects who are subsequently treated.
Pavlovic, Dragan; Lehmann, Christian; Wendt, Michael
2009-01-01
It is generally claimed that there exist exceptional circumstances when taking human life may be approved and when such actions may be justified on moral grounds. Precise guidelines in the medical field for making such decisions concerning patients who are terminally ill or have irreparable injuries incompatible with a bearable life, are difficult to establish. Recommendations that take the particular logical form of a rule, such as "in dubio pro vita", "when in doubt favour life") have been suggested and in some countries incorporated into legal texts (Germany). We claim here that such a rule is of no value since it is open-ended and always allows for doubt, and a decision to employ measures that would support human life could always be argued to be a valid choice. Preservation of this rule could be encouraged, but giving it the force of law may put physicians at risk, as they may be challenged for choosing to terminate life in otherwise ethically and medically uncontroversial circumstances. PMID:19442284
Control, Contingency and Delegation in Decision-Making.
ERIC Educational Resources Information Center
Michael, Stephen R.
1979-01-01
Proposes a model which emphasizes the delegation of decision-making authority and managerial control of operations. Suggests that risks can be reduced by using (1) a contingency approach to delegation, (2) decision rules for consistency, (3) decision models for specific situations, (4) vital indicator reports, (5) management by objectives, and (6)…
10 CFR 824.13 - Initial decision.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 10 Energy 4 2011-01-01 2011-01-01 false Initial decision. 824.13 Section 824.13 Energy DEPARTMENT OF ENERGY PROCEDURAL RULES FOR THE ASSESSMENT OF CIVIL PENALTIES FOR CLASSIFIED INFORMATION SECURITY VIOLATIONS § 824.13 Initial decision. (a) The Hearing Officer shall issue an initial decision as soon as...
13 CFR 134.409 - Decision on appeal.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Decision on appeal. 134.409 Section 134.409 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION RULES OF PROCEDURE GOVERNING... § 134.409 Decision on appeal. (a) A decision of the Administrative Law Judge under this subpart is the...
30 CFR 44.41 - Summary decision.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Summary decision. 44.41 Section 44.41 Mineral... REQUIREMENTS RULES OF PRACTICE FOR PETITIONS FOR MODIFICATION OF MANDATORY SAFETY STANDARDS Summary Decisions § 44.41 Summary decision. (a) No genuine issue of material fact. (1) Where no genuine issue of a...
29 CFR 1905.41 - Summary decision.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 29 Labor 5 2010-07-01 2010-07-01 false Summary decision. 1905.41 Section 1905.41 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR RULES OF... OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 Summary Decisions § 1905.41 Summary decision. (a) No genuine issue...
Against the empirical viability of the Deutsch-Wallace-Everett approach to quantum mechanics
NASA Astrophysics Data System (ADS)
Dawid, Richard; Thébault, Karim P. Y.
2014-08-01
The subjective Everettian approach to quantum mechanics presented by Deutsch and Wallace fails to constitute an empirically viable theory of quantum phenomena. The decision theoretic implementation of the Born rule realized in this approach provides no basis for rejecting Everettian quantum mechanics in the face of empirical data that contradicts the Born rule. The approach of Greaves and Myrvold, which provides a subjective implementation of the Born rule as well but derives it from empirical data rather than decision theoretic arguments, avoids the problem faced by Deutsch and Wallace and is empirically viable. However, there is good reason to cast doubts on its scientific value.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-09-25
... information collection requirements in its regulation ``Used Motor Vehicle Trade Regulation Rule'' (``Used Car... INFORMATION section below. Write ``Used Car Rule, PRA Comment, P137606'' on your comment and file your comment.... SUPPLEMENTARY INFORMATION: The Used Car Rule promotes informed purchasing decisions by requiring used car...
77 FR 19610 - Proposed Information Collection; Comment Request; Advance Monthly Retail Trade Survey
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2012-04-02
... #0; #0;Notices #0; Federal Register #0; #0; #0;This section of the FEDERAL REGISTER contains documents other than rules #0;or proposed rules that are applicable to the public. Notices of hearings #0;and investigations, committee meetings, agency decisions and rulings, #0;delegations of authority...
78 FR 54444 - Advisory Committee on Voluntary Foreign Aid Meeting
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2013-09-04
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75 FR 65606 - NCFRR Meeting Change From November 10 to November 30
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2010-10-26
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76 FR 9740 - National Urban and Community Forestry Advisory Council
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2011-02-22
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77 FR 66432 - Privacy Act of 1974, System of Records
Federal Register 2010, 2011, 2012, 2013, 2014
2012-11-05
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2011-04-01
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78 FR 27178 - Notice of May 17 President's Global Development Council Meeting
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2013-05-09
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29 CFR 102.25 - Ruling on motions.
Code of Federal Regulations, 2012 CFR
2012-07-01
... motions. An administrative law judge designated by the chief administrative law judge, by the associate... his decision. Whenever the administrative law judge has reserved his ruling on any motion, and the... 29 Labor 2 2012-07-01 2012-07-01 false Ruling on motions. 102.25 Section 102.25 Labor Regulations...
29 CFR 102.25 - Ruling on motions.
Code of Federal Regulations, 2014 CFR
2014-07-01
... motions. An administrative law judge designated by the chief administrative law judge, by the associate... his decision. Whenever the administrative law judge has reserved his ruling on any motion, and the... 29 Labor 2 2014-07-01 2014-07-01 false Ruling on motions. 102.25 Section 102.25 Labor Regulations...
29 CFR 102.25 - Ruling on motions.
Code of Federal Regulations, 2010 CFR
2010-07-01
... motions. An administrative law judge designated by the chief administrative law judge, by the associate... his decision. Whenever the administrative law judge has reserved his ruling on any motion, and the... 29 Labor 2 2010-07-01 2010-07-01 false Ruling on motions. 102.25 Section 102.25 Labor Regulations...
29 CFR 102.25 - Ruling on motions.
Code of Federal Regulations, 2013 CFR
2013-07-01
... motions. An administrative law judge designated by the chief administrative law judge, by the associate... his decision. Whenever the administrative law judge has reserved his ruling on any motion, and the... 29 Labor 2 2013-07-01 2013-07-01 false Ruling on motions. 102.25 Section 102.25 Labor Regulations...
Adding Only One Priority Rule Allows Extending CIP Rules to Supramolecular Systems.
Alkorta, Ibon; Elguero, José; Cintas, Pedro
2015-05-01
There are frequent situations both in supramolecular chemistry and in crystallography that result in stereogenic centers, whose absolute configuration needs to be specified. With this aim we propose the inclusion of one simple additional rule to the Cahn-Ingold-Prelog (CIP) system of priority rules stating that noncovalent interactions have a fictitious number between 0 and 1. © 2015 Wiley Periodicals, Inc.
43 CFR 4.801 - Suspension of rules.
Code of Federal Regulations, 2011 CFR
2011-10-01
... Special Procedural Rules Applicable to Practice and Procedure for Hearings, Decisions, and Administrative... determination that no party will be unduly prejudiced and the ends of justice will thereby be served. ...
43 CFR 4.801 - Suspension of rules.
Code of Federal Regulations, 2014 CFR
2014-10-01
... Special Procedural Rules Applicable to Practice and Procedure for Hearings, Decisions, and Administrative... determination that no party will be unduly prejudiced and the ends of justice will thereby be served. ...
43 CFR 4.801 - Suspension of rules.
Code of Federal Regulations, 2013 CFR
2013-10-01
... Special Procedural Rules Applicable to Practice and Procedure for Hearings, Decisions, and Administrative... determination that no party will be unduly prejudiced and the ends of justice will thereby be served. ...
43 CFR 4.801 - Suspension of rules.
Code of Federal Regulations, 2012 CFR
2012-10-01
... Special Procedural Rules Applicable to Practice and Procedure for Hearings, Decisions, and Administrative... determination that no party will be unduly prejudiced and the ends of justice will thereby be served. ...
37 CFR 354.2 - Novel questions.
Code of Federal Regulations, 2010 CFR
2010-07-01
..., or rulings under the Copyright Act of the Copyright Royalty Judges, the Librarian of Congress, the... the current decisions, determinations, or rulings of the Register of Copyrights or the Librarian of...
Mathew, R; Davies, N; Manthorpe, J; Iliffe, S
2016-07-19
Decision-making, when providing care and treatment for a person with dementia at the end of life, can be complex and challenging. There is a lack of guidance available to support practitioners and family carers, and even those experienced in end of life dementia care report a lack of confidence in decision-making. It is thought that the use of heuristics (rules of thumb) may aid decision-making. The aim of this study is to identify whether heuristics are used in end of life dementia care, and if so, to identify the context in which they are being used. A narrative literature review was conducted taking a systematic approach to the search strategy, using the Centre for Reviews and Dissemination guidelines. Rapid appraisal methodology was used in order to source specific and relevant literature regarding the use of heuristics in end of life dementia care. A search using terms related to dementia, palliative care and decision-making was conducted across 4 English language electronic databases (MEDLINE, EMBASE, PsycINFO and CINAHL) in 2015. The search identified 12 papers that contained an algorithm, guideline, decision tool or set of principles that we considered compatible with heuristic decision-making. The papers addressed swallowing and feeding difficulties, the treatment of pneumonia, management of pain and agitation, rationalising medication, ending life-sustaining treatment, and ensuring a good death. The use of heuristics in palliative or end of life dementia care is not described in the research literature. However, this review identified important decision-making principles, which are largely a reflection of expert opinion. These principles may have the potential to be developed into simple heuristics that could be used in practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Mathew, R; Davies, N; Manthorpe, J; Iliffe, S
2016-01-01
Objective Decision-making, when providing care and treatment for a person with dementia at the end of life, can be complex and challenging. There is a lack of guidance available to support practitioners and family carers, and even those experienced in end of life dementia care report a lack of confidence in decision-making. It is thought that the use of heuristics (rules of thumb) may aid decision-making. The aim of this study is to identify whether heuristics are used in end of life dementia care, and if so, to identify the context in which they are being used. Design A narrative literature review was conducted taking a systematic approach to the search strategy, using the Centre for Reviews and Dissemination guidelines. Rapid appraisal methodology was used in order to source specific and relevant literature regarding the use of heuristics in end of life dementia care. Data sources A search using terms related to dementia, palliative care and decision-making was conducted across 4 English language electronic databases (MEDLINE, EMBASE, PsycINFO and CINAHL) in 2015. Results The search identified 12 papers that contained an algorithm, guideline, decision tool or set of principles that we considered compatible with heuristic decision-making. The papers addressed swallowing and feeding difficulties, the treatment of pneumonia, management of pain and agitation, rationalising medication, ending life-sustaining treatment, and ensuring a good death. Conclusions The use of heuristics in palliative or end of life dementia care is not described in the research literature. However, this review identified important decision-making principles, which are largely a reflection of expert opinion. These principles may have the potential to be developed into simple heuristics that could be used in practice. PMID:27436665
Developing Novel Reservoir Rule Curves Using Seasonal Inflow Projections
NASA Astrophysics Data System (ADS)
Tseng, Hsin-yi; Tung, Ching-pin
2015-04-01
Due to significant seasonal rainfall variations, reservoirs and their flexible operational rules are indispensable to Taiwan. Furthermore, with the intensifying impacts of climate change on extreme climate, the frequency of droughts in Taiwan has been increasing in recent years. Drought is a creeping phenomenon, the slow onset character of drought makes it difficult to detect at an early stage, and causes delays on making the best decision of allocating water. For these reasons, novel reservoir rule curves using projected seasonal streamflow are proposed in this study, which can potentially reduce the adverse effects of drought. This study dedicated establishing new rule curves which consider both current available storage and anticipated monthly inflows with leading time of two months to reduce the risk of water shortage. The monthly inflows are projected based on the seasonal climate forecasts from Central Weather Bureau (CWB), which a weather generation model is used to produce daily weather data for the hydrological component of the GWLF. To incorporate future monthly inflow projections into rule curves, this study designs a decision flow index which is a linear combination of current available storage and inflow projections with leading time of 2 months. By optimizing linear relationship coefficients of decision flow index, the shape of rule curves and the percent of water supply in each zone, the best rule curves to decrease water shortage risk and impacts can be developed. The Shimen Reservoir in the northern Taiwan is used as a case study to demonstrate the proposed method. Existing rule curves (M5 curves) of Shimen Reservoir are compared with two cases of new rule curves, including hindcast simulations and historic seasonal forecasts. The results show new rule curves can decrease the total water shortage ratio, and in addition, it can also allocate shortage amount to preceding months to avoid extreme shortage events. Even though some uncertainties in historic forecasts would result unnecessary discounts of water supply, it still performs better than M5 curves during droughts.
Verhaert, Dominique V M; Bonnes, Judith L; Nas, Joris; Keuper, Wessel; van Grunsven, Pierre M; Smeets, Joep L R M; de Boer, Menko Jan; Brouwer, Marc A
2016-03-01
Of the proposed algorithms that provide guidance for in-field termination of resuscitation (TOR) decisions, the guidelines for cardiopulmonary resuscitation (CPR) refer to the basic and advanced life support (ALS)-TOR rules. To assess the potential consequences of implementation of the ALS-TOR rule, we performed a case-by-case evaluation of our in-field termination decisions and assessed the corresponding recommendations of the ALS-TOR rule. Cohort of non-traumatic out-of-hospital cardiac arrest (OHCA)-patients who were resuscitated by the ALS-practising emergency medical service (EMS) in the Nijmegen area (2008-2011). The ALS-TOR rule recommends termination in case all following criteria are met: unwitnessed arrest, no bystander CPR, no shock delivery, no return of spontaneous circulation (ROSC). Of the 598 cases reviewed, resuscitative efforts were terminated in the field in 46% and 15% survived to discharge. The ALS-TOR rule would have recommended in-field termination in only 6% of patients, due to high percentages of witnessed arrests (73%) and bystander CPR (54%). In current practice, absence of ROSC was the most important determinant of termination [aOR 35.6 (95% CI 18.3-69.3)]. Weaker associations were found for: unwitnessed and non-public arrests, non-shockable initial rhythms and longer EMS-response times. While designed to optimise hospital transportations, application of the ALS-TOR rule would almost double our hospital transportation rate to over 90% of OHCA-cases due to the favourable arrest circumstances in our region. Prior to implementation of the ALS-TOR rule, local evaluation of the potential consequences for the efficiency of triage is to be recommended and initiatives to improve field-triage for ALS-based EMS-systems are eagerly awaited. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks.
Fogelmark, Karl; Peterson, Carsten; Troein, Carl
2016-01-01
Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks.
Decision blocks: A tool for automating decision making in CLIPS
NASA Technical Reports Server (NTRS)
Eick, Christoph F.; Mehta, Nikhil N.
1991-01-01
The human capability of making complex decision is one of the most fascinating facets of human intelligence, especially if vague, judgemental, default or uncertain knowledge is involved. Unfortunately, most existing rule based forward chaining languages are not very suitable to simulate this aspect of human intelligence, because of their lack of support for approximate reasoning techniques needed for this task, and due to the lack of specific constructs to facilitate the coding of frequently reoccurring decision block to provide better support for the design and implementation of rule based decision support systems. A language called BIRBAL, which is defined on the top of CLIPS, for the specification of decision blocks, is introduced. Empirical experiments involving the comparison of the length of CLIPS program with the corresponding BIRBAL program for three different applications are surveyed. The results of these experiments suggest that for decision making intensive applications, a CLIPS program tends to be about three times longer than the corresponding BIRBAL program.
Langhout, Regina Day; Kohfeldt, Danielle M; Ellison, Erin Rose
2011-12-01
The current study examines 16 Latina/o fifth grade children's desires for a decision-making structure within a youth participatory action research (yPAR) program. When given the choices of consensus, majority rule, authoritarian rule, delegation, and random choice models, children chose random choice. Procedural, distributive and emotional justice were heavily weighted in their reasoning around fairness and decision making. Many thought random choice offered the best alternative because it flattened power hierarchies so that each child would, at some point, have the power to make a decision. Additionally, children argued that the neutrality of random choice allowed them to sidestep interpersonal tensions. Implications include how social identities inform definitions of fairness and how yPAR programs should work with youth around how they will make decisions.
Bressan, Silvia; Romanato, Sabrina; Mion, Teresa; Zanconato, Stefania; Da Dalt, Liviana
2012-07-01
Of the currently published clinical decision rules for the management of minor head injury (MHI) in children, the Pediatric Emergency Care Applied Research Network (PECARN) rule, derived and validated in a large multicenter prospective study cohort, with high methodologic standards, appears to be the best clinical decision rule to accurately identify children at very low risk of clinically important traumatic brain injuries (ciTBI) in the pediatric emergency department (PED). This study describes the implementation of an adapted version of the PECARN rule in a tertiary care academic PED in Italy and evaluates implementation success, in terms of medical staff adherence and satisfaction, as well as its effects on clinical practice. The adapted PECARN decision rule algorithms for children (one for those younger than 2 years and one for those older than 2 years) were actively implemented in the PED of Padova, Italy, for a 6-month testing period. Adherence and satisfaction of medical staff to the new rule were calculated. Data from 356 visits for MHI during PECARN rule implementation and those of 288 patients attending the PED for MHI in the previous 6 months were compared for changes in computed tomography (CT) scan rate, ciTBI rate (defined as death, neurosurgery, intubation for longer than 24 hours, or hospital admission at least for two nights associated with TBI) and return visits for symptoms or signs potentially related to MHI. The safety and efficacy of the adapted PECARN rule in clinical practice were also calculated. Adherence to the adapted PECARN rule was 93.5%. The percentage of medical staff satisfied with the new rule, in terms of usefulness and ease of use for rapid decision-making, was significantly higher (96% vs. 51%, p<0.0001) compared to the previous, more complex, internal guideline. CT scan was performed in 30 patients (8.4%, 95% confidence interval [CI]=6% to 11.8%) in the implementation period versus 21 patients (7.3%, 95% CI=4.8% to 10.9%) before implementation. A ciTBI occurred in three children (0.8%, 95% CI=0.3 to 2.5) during the implementation period and in two children (0.7%, 95% CI=0.2 to 2.5) in the prior 6 months. There were five return visits (1.4%) postimplementation and seven (2.4%) before implementation (p=0.506). The safety of use of the adapted PECARN rule in clinical practice was 100% (95% CI=36.8 to 100; three of three patients with ciTBI who received CT scan at first evaluation), while efficacy was 92.3% (95% CI=89 to 95; 326 of 353 patients without ciTBI who did not receive a CT scan). The adapted PECARN rule was successfully implemented in an Italian tertiary care academic PED, achieving high adherence and satisfaction of medical staff. Its use determined a low CT scan rate that was unchanged compared to previous clinical practice and showed an optimal safety and high efficacy profile. Strict monitoring is mandatory to evaluate the long-lasting benefit in patient care and/or resource utilization. © 2012 by the Society for Academic Emergency Medicine.
Deontic reasoning with emotional content: evolutionary psychology or decision theory?
Perham, Nick; Oaksford, Mike
2005-09-10
Three experiments investigated the contrasting predictions of the evolutionary and decision-theoretic approaches to deontic reasoning. Two experiments embedded a hazard management (HM) rule in a social contract scenario that should lead to competition between innate modules. A 3rd experiment used a pure HM task. Threatening material was also introduced into the antecedent, p, of a deontic rule, if p then must q. According to the evolutionary approach, more HM responses (Cosmides & Tooby, 2000) are predicted when p is threatening, whereas decision theory predicts fewer. All 3 experiments were consistent with decision theory. Other theories are discussed, and it is concluded that they cannot account for the behavior observed in these experiments. 2005 Lawrence Erlbaum Associates, Inc.
Automatic Recognition of Phonemes Using a Syntactic Processor for Error Correction.
1980-12-01
OF PHONEMES USING A SYNTACTIC PROCESSOR FOR ERROR CORRECTION THESIS AFIT/GE/EE/8D-45 Robert B. ’Taylor 2Lt USAF Approved for public release...distribution unlimilted. AbP AFIT/GE/EE/ 80D-45 AUTOMATIC RECOGNITION OF PHONEMES USING A SYNTACTIC PROCESSOR FOR ERROR CORRECTION THESIS Presented to the...Testing ..................... 37 Bayes Decision Rule for Minimum Error ........... 37 Bayes Decision Rule for Minimum Risk ............ 39 Mini Max Test
Systematic Analysis of the Decision Rules of Traditional Chinese Medicine
Bin-Rong, Ma; Xi-Yuan, Jiang; Su-Ming, Liso; Huai-ning, Zhu; Xiu-ru, Lin
1981-01-01
Chinese traditional medicine has evolved over many centuries, and has accumulated a body of observed relationships between symptoms, signs and prognoses, and the efficacy of alternative treatments and prescriptions. With the assistance of a computer-based clinical data base for recording the diagnostic and therapeutic practice of skilled practitioners of Chinese traditional medicine, a systematic program is being conducted to identify and define the clinical decision-making rules that underlie current practice.
Knowledge-based reasoning in the Paladin tactical decision generation system
NASA Technical Reports Server (NTRS)
Chappell, Alan R.
1993-01-01
A real-time tactical decision generation system for air combat engagements, Paladin, has been developed. A pilot's job in air combat includes tasks that are largely symbolic. These symbolic tasks are generally performed through the application of experience and training (i.e. knowledge) gathered over years of flying a fighter aircraft. Two such tasks, situation assessment and throttle control, are identified and broken out in Paladin to be handled by specialized knowledge based systems. Knowledge pertaining to these tasks is encoded into rule-bases to provide the foundation for decisions. Paladin uses a custom built inference engine and a partitioned rule-base structure to give these symbolic results in real-time. This paper provides an overview of knowledge-based reasoning systems as a subset of rule-based systems. The knowledge used by Paladin in generating results as well as the system design for real-time execution is discussed.
Learning a New Selection Rule in Visual and Frontal Cortex.
van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R
2016-08-01
How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.
Trading Speed and Accuracy by Coding Time: A Coupled-circuit Cortical Model
Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.
2013-01-01
Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT) provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by ‘climbing’ activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification. PMID:23592967
Verbakel, Jan Y; Lemiengre, Marieke B; De Burghgraeve, Tine; De Sutter, An; Aertgeerts, Bert; Bullens, Dominique M A; Shinkins, Bethany; Van den Bruel, Ann; Buntinx, Frank
2015-08-07
Acute infection is the most common presentation of children in primary care with only few having a serious infection (eg, sepsis, meningitis, pneumonia). To avoid complications or death, early recognition and adequate referral are essential. Clinical prediction rules have the potential to improve diagnostic decision-making for rare but serious conditions. In this study, we aimed to validate a recently developed decision tree in a new but similar population. Diagnostic accuracy study validating a clinical prediction rule. Acutely ill children presenting to ambulatory care in Flanders, Belgium, consisting of general practice and paediatric assessment in outpatient clinics or the emergency department. Physicians were asked to score the decision tree in every child. The outcome of interest was hospital admission for at least 24 h with a serious infection within 5 days after initial presentation. We report the diagnostic accuracy of the decision tree in sensitivity, specificity, likelihood ratios and predictive values. In total, 8962 acute illness episodes were included, of which 283 lead to admission to hospital with a serious infection. Sensitivity of the decision tree was 100% (95% CI 71.5% to 100%) at a specificity of 83.6% (95% CI 82.3% to 84.9%) in the general practitioner setting with 17% of children testing positive. In the paediatric outpatient and emergency department setting, sensitivities were below 92%, with specificities below 44.8%. In an independent validation cohort, this clinical prediction rule has shown to be extremely sensitive to identify children at risk of hospital admission for a serious infection in general practice, making it suitable for ruling out. NCT02024282. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Robot decisions: on the importance of virtuous judgment in clinical decision making.
Gelhaus, Petra
2011-10-01
The aim of this article is to argue for the necessity of emotional professional virtues in the understanding of good clinical practice. This understanding is required for a proper balance of capacities in medical education and further education of physicians. For this reason an ideal physician, incarnating the required virtues, skills and knowledge is compared with a non-emotional robot that is bound to moral rules. This fictive confrontation is meant to clarify why certain demands on the personality of the physician are justified, in addition to a rule- and principle-based moral orientation and biomedical knowledge and skills. Philosophical analysis of thought experiments inspired by science fiction literature by Isaac Asimov. Although prima facie a rule-oriented robot seems more reliable and trustworthy, the complexity of clinical judgment is not met by an encompassing and never contradictory set of rules from which one could logically derive decisions. There are different ways how the robot could still work, but at the cost of the predictability of its behaviour and its moral orientation. In comparison, a virtuous human doctor who is also bound to these rules, although less strictly, will more reliably keep at moral objectives, be understandable, be more flexible in case the rules come to their limits, and will be more predictable in these critical situations. Apart from these advantages of the virtuous human doctor referring to her own person, the most problematic deficit of the robot is its lacking deeper understanding of the inner mental events of patients which makes good contact, good communication and good influence impossible. Although an infallibly rule-oriented robot seems more reliable at first view, in situations that require complex decisions like clinical practice the agency of a moral human person is more trustworthy. Furthermore, the understanding of the patient's emotions must remain insufficient for a non-emotional, non-human being. Because these are crucial preconditions for good clinical practice, enough attention should be given to develop these virtues and emotional skills, in addition to the usual attention on knowledge, technical skills and the obedience to moral rules and principles. © 2011 Blackwell Publishing Ltd.
NASA Technical Reports Server (NTRS)
Howard, Ayanna; Bayard, David
2006-01-01
Fuzzy Feature Observation Planner for Small Body Proximity Observations (FuzzObserver) is a developmental computer program, to be used along with other software, for autonomous planning of maneuvers of a spacecraft near an asteroid, comet, or other small astronomical body. Selection of terrain features and estimation of the position of the spacecraft relative to these features is an essential part of such planning. FuzzObserver contributes to the selection and estimation by generating recommendations for spacecraft trajectory adjustments to maintain the spacecraft's ability to observe sufficient terrain features for estimating position. The input to FuzzObserver consists of data from terrain images, including sets of data on features acquired during descent toward, or traversal of, a body of interest. The name of this program reflects its use of fuzzy logic to reason about the terrain features represented by the data and extract corresponding trajectory-adjustment rules. Linguistic fuzzy sets and conditional statements enable fuzzy systems to make decisions based on heuristic rule-based knowledge derived by engineering experts. A major advantage of using fuzzy logic is that it involves simple arithmetic calculations that can be performed rapidly enough to be useful for planning within the short times typically available for spacecraft maneuvers.
76 FR 77230 - Agency Information Collection Activities; Proposed Collection; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2011-12-12
... consumers in making informed purchasing decisions, and recordkeeping requirements that assist the Commission... Rules establish disclosure requirements that assist consumers in making informed purchasing decisions... consumers in making informed purchasing decisions, and recordkeeping requirements that assist the Commission...
76 FR 20233 - Appliance Labeling Rule
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-12
... possible to help consumers make informed purchasing decisions.\\5\\ Also, Earthjustice noted that NEMA's... help consumers understand the new label and use it in purchasing decisions. In addition, extending the... the effective date was originally established. In reaching this decision, the Commission considered...
van Es, Nick; Bleker, Suzanne M; Di Nisio, Marcello; Kleinjan, Ankie; Beyer-Westendorf, Jan; Camporese, Giuseppe; Kamphuisen, Pieter W; Büller, Harry R; Bossuyt, Patrick M
2016-12-01
In a management study, a diagnostic algorithm consisting of a clinical decision rule, D-dimer, and ultrasonography was shown to safely exclude upper extremity deep vein thrombosis (UEDVT). Efficiency may be lower in high-risk subgroups: those with a central venous catheter or pacemaker, inpatients, cancer, and elderly patients. Data of 406 patients with suspected UEDVT enrolled in a prospective management study were used for the present analysis. The aim was to evaluate the efficiency of the algorithm in subgroups, defined as the proportion of patients in whom imaging could be safely withheld based on the combination of a decision rule result indicating "UEDVT unlikely" and a normal D-dimer result. The strategy excluded UEDVT in 87 of 406 patients (21%); ultrasonography was withheld in these patients and none developed UEDVT during 3months of follow-up. In contrast, ultrasonography could be withheld in only 4 of 92 patients with a catheter or pacemaker (4.3%; 95% CI: 1.7% to 11%) and in 4 of 83 inpatients (4.8%; 95% CI: 1.9% to 12%). The efficiency was 11% in patients with cancer and 13% in those older than 75years. Although the combination of a decision rule and D-dimer testing is safe in excluding UEDVT in the overall population of patients with suspected UEDVT, its efficiency appears limited in some subgroups, in particular those with a central venous catheter or pacemaker, and inpatients. Copyright © 2016 Elsevier Ltd. All rights reserved.
Jabez Christopher, J; Khanna Nehemiah, H; Kannan, A
2015-10-01
Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis. Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert. The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model. The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests. Copyright © 2015 Elsevier Ltd. All rights reserved.
A diagnostic process extended in time as a fuzzy model
NASA Astrophysics Data System (ADS)
Rakus-Andersson, Elisabeth; Gerstenkorn, Tadeusz
1999-03-01
The paper refers to earlier results obtained by the authors and constitutes their essential complement and extension by introducing to a diagnostic model the assumption that the decision concerning the diagnosis is based on observations of symptoms carried out repeatedly, by stages, which may have effect in a change of these symptoms in increasing time. The model concerns the observations of symptoms at an individual patient at a time interval. The changes of the symptoms give some additional information, sometimes very important in the diagnostic process when the clinical picture of a patient in a certain interval of time differs from that one which has been received from the beginning of the disease. It may occur that the change in the intensity of a symptom decides an acceptance of another diagnosis after some time when the patient does not feel better. The aim is to fix an optimal diagnosis on the basis of clinical symptoms typical of several morbid units with respect to the changes of these symptoms in time. In order to solve such a posed problem the authors apply the method of fuzzy relation equations which are modelled by means of logical rules of inference. Moreover, in the final decision concerning the choice of a proper diagnosis, a normed Euclidean distance is introduced as a measure between a real decision and an "ideal" decision. A simple example presents the practical action of the method to show its relevance to a possible user.
Congestion relaxation due to density-dependent junction rules in TASEP network
NASA Astrophysics Data System (ADS)
Tannai, Takahiro; Nishinari, Katsuhiro
2017-09-01
We now consider a small network module of Totally Asymmetric Simple Exclusion Process with branching and aggregation points, and rules of junctions dependent on the densities of segments of the network module. We also focus on the interaction among junctions which are branching and aggregation. The interaction among junctions with density-dependent rules possesses more complexity than those with density-independent rules studied in the previous papers. In conclusion, we confirm the result that density-dependent rules enable vehicles to move more effectively than the density-independent rules.
2014-01-01
Background Limited information is available about predictors of short-term outcomes in patients with exacerbation of chronic obstructive pulmonary disease (eCOPD) attending an emergency department (ED). Such information could help stratify these patients and guide medical decision-making. The aim of this study was to develop a clinical prediction rule for short-term mortality during hospital admission or within a week after the index ED visit. Methods This was a prospective cohort study of patients with eCOPD attending the EDs of 16 participating hospitals. Recruitment started in June 2008 and ended in September 2010. Information on possible predictor variables was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up. Main short-term outcomes were death during hospital admission or within 1 week of discharge to home from the ED, as well as at death within 1 month of the index ED visit. Multivariate logistic regression models were developed in a derivation sample and validated in a validation sample. The score was compared with other published prediction rules for patients with stable COPD. Results In total, 2,487 patients were included in the study. Predictors of death during hospital admission, or within 1 week of discharge to home from the ED were patient age, baseline dyspnea, previous need for long-term home oxygen therapy or non-invasive mechanical ventilation, altered mental status, and use of inspiratory accessory muscles or paradoxical breathing upon ED arrival (area under the curve (AUC) = 0.85). Addition of arterial blood gas parameters (oxygen and carbon dioxide partial pressures (PO2 and PCO2)) and pH) did not improve the model. The same variables were predictors of death at 1 month (AUC = 0.85). Compared with other commonly used tools for predicting the severity of COPD in stable patients, our rule was significantly better. Conclusions Five clinical predictors easily available in the ED, and also in the primary care setting, can be used to create a simple and easily obtained score that allows clinicians to stratify patients with eCOPD upon ED arrival and guide the medical decision-making process. PMID:24758312
Park, Junchol; Wood, Jesse; Bondi, Corina; Del Arco, Alberto; Moghaddam, Bita
2016-03-16
Anxiety is a debilitating symptom of most psychiatric disorders, including major depression, post-traumatic stress disorder, schizophrenia, and addiction. A detrimental aspect of anxiety is disruption of prefrontal cortex (PFC)-mediated executive functions, such as flexible decision making. Here we sought to understand how anxiety modulates PFC neuronal encoding of flexible shifting between behavioral strategies. We used a clinically substantiated anxiogenic treatment to induce sustained anxiety in rats and recorded from dorsomedial PFC (dmPFC) and orbitofrontal cortex (OFC) neurons while they were freely moving in a home cage and while they performed a PFC-dependent task that required flexible switches between rules in two distinct perceptual dimensions. Anxiety elicited a sustained background "hypofrontality" in dmPFC and OFC by reducing the firing rate of spontaneously active neuronal subpopulations. During task performance, the impact of anxiety was subtle, but, consistent with human data, behavior was selectively impaired when previously correct conditions were presented as conflicting choices. This impairment was associated with reduced recruitment of dmPFC neurons that selectively represented task rules at the time of action. OFC rule representation was not affected by anxiety. These data indicate that a neural substrate of the decision-making deficits in anxiety is diminished dmPFC neuronal encoding of task rules during conflict-related actions. Given the translational relevance of the model used here, the data provide a neuronal encoding mechanism for how anxiety biases decision making when the choice involves overcoming a conflict. They also demonstrate that PFC encoding of actions, as opposed to cues or outcome, is especially vulnerable to anxiety. A debilitating aspect of anxiety is its impact on decision making and flexible control of behavior. These cognitive constructs depend on proper functioning of the prefrontal cortex (PFC). Understanding how anxiety affects PFC encoding of cognitive events is of great clinical and evolutionary significance. Using a clinically valid experimental model, we find that, under anxiety, decision making may be skewed by salient and conflicting environmental stimuli at the expense of flexible top-down guided choices. We also find that anxiety suppresses spontaneous activity of PFC neurons, and weakens encoding of task rules by dorsomedial PFC neurons. These data provide a neuronal encoding scheme for how anxiety disengages PFC during decision making. Copyright © 2016 the authors 0270-6474/16/363322-14$15.00/0.
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On the Lawfulness of the Decision to Terminate Memory Search
ERIC Educational Resources Information Center
Harbison, J. Isaiah; Dougherty, Michael R.; Davelaar, Eddy J.; Fayyad, Basma
2009-01-01
Nearly every memory retrieval episode ends with a decision to terminate memory search. Yet, no research has investigated whether these search termination decisions are systematic, let alone whether they are made consistent with a particular rule. In the present paper, we used a modified free-recall paradigm to examine the decision to terminate…
13 CFR 134.715 - Can a Judge reconsider his decision?
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13 CFR 134.212 - Summary decision.
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