Delayed-decision making in noisy bistable switches

Bistable switches are frequently encountered in biological systems. Typically, a bistable switch models a binary decision where each decision corresponds to one of the two stable equilibria. Recently, we showed that the global decision-making process in bistable switches strongly depends on a particular equilibrium point of these systems, their saddle point. In particular, we showed that a saddle point with a time-scale separation between its attractive and repulsive directions can delay the decision-making process. In this paper, we study the effects of white Gaussian noise on this mechanism of delayed decision-making induced by the saddle point. Results show that the mean decision-time strongly depends on the balance between the initial distance to the separatrix and the noise strength. © IFAC.

Compact Reconfigurable Binary-Decision-Diagram Logic Circuit on a GaAs Nanowire Network

We describe a reconfigurable binary-decision-diagram logic circuit based on Shannon's expansion of Boolean logic function and its graphical representation on a semiconductor nanowire network. The circuit is reconfigured by using programmable switches that electrically connect and disconnect a small number of branches. This circuit has a compact structure with a small number of devices compared with the conventional look-up table architecture. A variable Boolean logic circuit was fabricated on an etched GaAs nanowire network having hexagonal topology with Schottky wrap gates and SiN-based programmable switches, and its correct logic operation together with dynamic reconfiguration was demonstrated.

An automata theoretic decision procedure for the propositional mu-calculus

The propositional mu-calculus is a propositional logic of programs which incorporates a least fixpoint operator and subsumes the propositional dynamic logic of Fischer and Ladner, the infinite looping construct of Streett, and the game logic of Parikh. We give an elementary time decision procedure, using a reduction to the emptiness problem for automata on infinite trees. A small model theorem is obtained as a corollary.

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection

Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.

品牌属性权重判断的反应时研究

In current days, many companies have carried out their branding strategies, because strong brand usually provides confidence and reduce risks to its consumers. No matter what a brand is based on tangible products or services, it will possess the common attributes of this category, and it also has its unique attributes. Brand attribute is defined as descriptive features, which are intrinsic characteristics, values or benefits endowed by users of the product or service (Keller, 1993; Romaniuk, 2003). The researches on models of brand multi-attributes are one of the most studied areas of consumer psychology (Werbel, 1978), and attribute weight is one of its key pursuits. Marketing practitioners also paid much attention to evaluations of attributes. Because those evaluations are relevant to the competitiveness and the strategies of promotion and new product development of the company (Green & Krieger, 1995). Then, how brand attributes correlate with weight judgments? And what features the attribute judgment reaction? Especially, what will feature the attribute weight judgment process of consumer who is facing the homogeneity of brands? Enlightened by the lexical hypothesis of researches on personality traits of psychology, this study choose search engine brands as the subject and adopt reaction time, which has been introduced into multi-attributes decision making by many researchers. Researches on independence of affect and cognition and on primacy of affect have cued us that we can categorize brand attributes into informative and affective ones. Meanwhile, Park has gone further to differentiate representative and experiential with functional attributes. This classification reflects the trend of emotion-branding and brand-consumer relationship. Three parts compose the research: the survey to collect attribute words, experiment one on affective primacy and experiment two on correlation between weight judgment and reaction. The results are as follow: In experiment one, we found: (1) affect words are not rated significantly from cognitive attributes, but affect words are responded faster than cognitive ones; (2) subjects comprehend and respond in different ways to functional attribute words and to representative and experiential words. In experiment two, we fund: (1) a significant negative correlation between attributes weight judgment and reaction time; (2) affective attributes will cause faster reaction than cognitive ones; (3) the reaction time difference between functional and representative or experiential attribute is significant, but there is no different between representative and experiential. In sum, we conclude that: (1): In word comprehension and weight judgment, we observed the affective primacy, even when the affect stimulus is presented as meaningful words. (2): The negative correlation between weight judgment and reaction time suggest us that the more important of attribute, the quicker of the reaction. (3): The difference on reaction time of functional, representative and experiential reflects the trend of emotional branding.

Naive Physics, Event Perception, Lexical Semantics, and Language Acquisition

This thesis proposes a computational model of how children may come to learn the meanings of words in their native language. The proposed model is divided into two separate components. One component produces semantic descriptions of visually observed events while the other correlates those descriptions with co-occurring descriptions of those events in natural language. The first part of this thesis describes three implementations of the correlation process whereby representations of the meanings of whole utterances can be decomposed into fragments assigned as representations of the meanings of individual words. The second part of this thesis describes an implemented computer program that recognizes the occurrence of simple spatial motion events in simulated video input.

A novel Information sharing model using binary decision diagrams for redundancy, shadowing, generalisation and correlation.

This paper outlines a novel information sharing method using Binary Decision Diagrams (BBDs). It is inspired by the work of Al-Shaer and Hamed, who applied BDDs into the modelling of network firewalls. This is applied into an information sharing policy system which optimizes the search of redundancy, shadowing, generalisation and correlation within information sharing rules.

Evaluation of binary decision diagrams for redundancy, shadowing, generalisation and correlation in an Information sharing model.

This paper defines a structured methodology which is based on the foundational work of Al-Shaer et al. in [1] and that of Hamed and Al-Shaer in [2]. It defines a methodology for the declaration of policy field elements, through to the syntax, ontology and functional verification stages. In their works of [1] and [2] the authors concentrated on developing formal definitions of possible anomalies between rules in a network firewall rule set. Their work is considered as the foundation for further works on anomaly detection, including those of Fitzgerald et al. [3], Chen et al. [4], Hu et al. [5], among others. This paper extends this work by applying the methods to information sharing policies, and outlines the evaluation related to these.

Understanding nurses’ decision-making when managing weaning from mechanical ventilation: a study of novice and experienced critical care nurses in Scotland and Greece.

Aim and objectives To examine how nurses collect and use cues from respiratory assessment to inform their decisions as they wean patients from ventilatory support. Background Prompt and accurate identification of the patient's ability to sustain reduction of ventilatory support has the potential to increase the likelihood of successful weaning. Nurses' information processing during the weaning from mechanical ventilation has not been well-described. Design A descriptive ethnographic study exploring critical care nurses' decision-making processes when weaning mechanically ventilated patients from ventilatory support in the real setting. Methods Novice and expert Scottish and Greek nurses from two tertiary intensive care units were observed in real practice of weaning mechanical ventilation and were invited to participate in reflective interviews near the end of their shift. Data were analysed thematically using concept maps based on information processing theory. Ethics approval and informed consent were obtained. Results Scottish and Greek critical care nurses acquired patient-centred objective physiological and subjective information from respiratory assessment and previous knowledge of the patient, which they clustered around seven concepts descriptive of the patient's ability to wean. Less experienced nurses required more encounters of cues to attain the concepts with certainty. Subjective criteria were intuitively derived from previous knowledge of patients' responses to changes of ventilatory support. All nurses used focusing decision-making strategies to select and group cues in order to categorise information with certainty and reduce the mental strain of the decision task. Conclusions Nurses used patient-centred information to make a judgment about the patients' ability to wean. Decision-making strategies that involve categorisation of patient-centred information can be taught in bespoke educational programmes for mechanical ventilation and weaning. Relevance to clinical practice Advanced clinical reasoning skills and accurate detection of cues in respiratory assessment by critical care nurses will ensure optimum patient management in weaning mechanical ventilation

Exploring the relationship between impulsivity and decision-making on mobile devices.

Mobile devices offer a common platform for both leisure and work-related tasks but this has resulted in a blurred boundary between home and work. In this paper we explore the security implications of this blurred boundary, both for the worker and the employer. Mobile workers may not always make optimum security-related choices when ‘on the go’ and more impulsive individuals may be particularly affected as they are considered more vulnerable to distraction. In this study we used a task scenario, in which 104 users were asked to choose a wireless network when responding to work demands while out of the office. Eye-tracking data was obtained from a subsample of 40 of these participants in order to explore the effects of impulsivity on attention. Our results suggest that impulsive people are more frequent users of public devices and networks in their day-to-day interactions and are more likely to access their social networks on a regular basis. However they are also likely to make risky decisions when working on-the-go, processing fewer features before making those decisions. These results suggest that those with high impulsivity may make more use of the mobile Internet options for both work and private purposes but they also show attentional behavior patterns that suggest they make less considered security-sensitive decisions. The findings are discussed in terms of designs that might support enhanced deliberation, both in the moment and also in relation to longer term behaviors that would contribute to a better work-life balance.