“确定”信息下的AIDUCHI的功能分析

以日语的母语话者的AIDUCHI为基准,将中国的高水平学习者的AIDUCHI进行了功能方面的分类,考察学习者使用的AIDUCHI在各个分类里将如何体现。在考察中,将说话人提供的信息分为"确定"的信息与"不确定"的信息。以"确定"信息为背景,把学习者的AIDUCHI分为"已理解"、"已理解+确认"、"已理解+态度"三种功能,分析了学习者如何通过"重复"、"换言"及"肯定"、"否定"、惊讶等的"情感表露"及"评论"等AIDUCHI的形式体现这些功能的例子。考察结果显示作为考察对象的学习者虽然日语能力已经达到比较高的水平,但在AIDUCHI的使用上呈现出不稳定性、不均衡性和使用不当等问题。

Congestion aware routing algorithm for delay-disruption tolerance networks

There were many contradictory evaluation criteria to select next-hop in the delay-disruption tolerance networks(DTN).To solve this problem,an attribute hierarchical model was proposed,in which the predefined criteria were summarized as static identity attributes,forwarding desire attributes and delivery capability attributes(IDC).Based on this model,a novel multi-attributes congestion aware routing(MACAR) scheme with uncertain information for next-hop selection was presented,by adopting an decision theory to aggregate attributes with belief structure and computing partial ordering relations.The simulation results show that MACAR presents higher successful delivery rate,lower average delay and effectively alleviate congestion.

Integrating unascertained measurement and information entropy theory to assess blastability of rock mass

Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual characteristics of the project. Considering a comprehensive range of intact rock properties and discontinuous structures of rock mass, twelve main factors influencing the evaluation blastability of rock mass were taken into account in the UM model, and the blastability evaluation index system of rock mass was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. Then, the UM function of each evaluation index was obtained based on the initial data for the analysis of the blastability of six rock mass at a highway improvement cutting site in North Wales. The index weights of the factors were calculated by entropy theory, and credible degree identification （CDI） criteria were established according to the UM theory. The results of rock mass blastability evaluation were obtained by the CDI criteria. The results show that the UM model assessment results agree well with the actual records, and are consistent with those of the fuzzy sets evaluation method. Meanwhile, the unascertained superiority degree of rock mass blastability of samples S1-$6 which can be calculated by scoring criteria are 3.428 5, 3.453 3, 4.058 7, 3.675 9, 3.516 7 and 3.289 7, respectively. Furthermore, the proposed method can take into account large amount of uncertain information in blastability evaluation, which can provide an effective, credible and feasible way for estimating the blastability of rock mass. Engineering practices show that it can complete the blastability assessment systematically and scientifically without any assumption by the proposed model, which can be applied to practical engineering.

IMPROVED ACCURACY AND ROUGHNESS MEASURES FOR ROUGH SETS

Accuracy and roughness, proposed by Pawlak(1982), might draw a conclusion inconsistent with our intuition in some cases. This letter analyzes the limitations in these measures and proposes improved accuracy and roughness measures based on information theory.

RANDOM SETS: A UNIFIED FRAMEWORK FOR MULTISOURCE INFORMATION FUSION

The more diverse the ways and means of information acquisition are,the more complex and various the types of information are. The qualities of available information are usually uncertain,vague,imprecise,incomplete,and so on. However,the information is modeled and fused traditionally in particular,name some of the known theories: evidential,fuzzy sets,possibilistic,rough sets or conditional events,etc. For several years,researchers have explored the unification of theories enabling the fusion of multisource information and have finally considered random set theory as a powerful mathematical tool. This paper attempts to overall review the close relationships between random set theory and other theories,and introduce recent research results which present how different types of information can be dealt with in this unified framework. Finally,some possible future directions are discussed.

A novel fuzzy sensor fusion algorithm

A novel fusion algorithm was given based on fuzzy similarity and fuzzy integral theory. First, it calculated the fuzzy similarity among a certain sensor＇s measurement values and the multiple sensors＇ objective prediction values to determine the importance weight of each sensor and realize multi-sensor data fusion. Then according to the determined importance weight, an intelligent fusion system based on fuzzy integral theory was given, which can solve FEI-DEO and DEI-DEO fusion problems and realize the decision fusion. Simulation results were proved that fuzzy integral algorithm has enhanced the capability of handling the uncertain information and improved the intelligence degrees

Identification of contamination source in water distribution network based on consumer complaints

A new methodology was proposed for contamination source identification using information provided by consumer complaints from a probabilistic view.Due to the high uncertainties of information derived from users,the objective of the proposed methodology doesn't aim to capture a unique solution,but to minimize the number of possible contamination sources.In the proposed methodology,all the possible pollution nodes are identified through the CSA methodology firstly.And then based on the principle of total probability formula,the probability of each possible contamination node is obtained through a series of calculation.According to magnitude of the probability,the number of possible pollution nodes is minimized.The effectiveness and feasibility of the methodology is demonstrated through an application to a real case of ZJ City.Four scenarios were designed to investigate the influence of different uncertainties on the results in this case.The results show that pollutant concentration,injection duration,the number of consumer complaints nodes used for calculation and the prior probability with which consumers would complaint have no particular effect on the identification of contamination source.Three nodes were selected as the most possible pollution sources in water pipe network of ZJ City which includes more than 3 000 nodes.The results show the potential of the proposed method to identify contamination source through consumer complaints.

Generalized Uncertainty Principle and Thermodynamic Quantities of SAdS_5 Black Hole

Recently, there has been much attention devoted to resolving the quantum corrections to the Bekenstein- Hawking black hole entropy. The different correction leading terms are obtained by the different methods. In this paper, we calculate the correction to SAdS5 black hole thermodynamic quantity due to the generalized uncertainty principle. Furthermore we derive that the black hole entropy obeys Bekenstein Hawking area theorem. The entropy has infinite correction terms. And every term is finite and calculable. The corrected Cardy-Vedinde formula is derived. In our calculation, Bekenstein Hawking area theorem still holds after considering the generalized uncertainty principle. We have not introduced any hypothesis. The calculation is simple. Physics meaning is clear. We note that our results are quite general. It is not only valid for four-dimensional spacetime but also for higher-dimensional SAdS spacetime.

On Normalization of Comprehensive Evaluation System with Complex Uncertain Information

This paper systematically proposes basic requirements on normalization of comprehensive evaluation system with complex uncertain information due to human participation. Four basic academic ideas are as follows: 1) It is necessary to normalize conditions of information acquisition. 2) The effectiveness of comprehensive evaluation depends on the correctness of information acquisition. 3) Any evaluation results can be transformed into linguistic satisfactory degrees. 4) Linguistic values can include a great deal of information. This paper mainly deals with how to select objects to be evaluated, evaluators (panelists) and the methods of information processing, how to construct criteria of evaluation, how to normalize terms of evaluation, the results of evaluation, and the procedure of evaluation.

Quantitative comparison of similarity measure and entropy for fuzzy sets

Comparison and data analysis with the similarity measures and entropy for fuzzy sets were carried out. The distance proportional value between the fuzzy set and the corresponding crisp set was considered by the fuzzy entropy. The relation between the similarity measure and the entropy for fuzzy set was also analyzed. The fuzzy entropy was reformulated as the dissimilarity measure. Furthermore, crisp set having the minimum uncertainty with respect to the corresponding fuzzy set was also proposed. Finally, derivation of a similarity measure from entropy with the help of total information property was derived. A simple example shows the relation between similarity measure and fuzzy entropy, in which the summation of similarity measure and fuzzy entropy represents a constant value.

Sign Flip in Giorgi-Pasquale-Paganelli Model

Taking advantage of our improved gates as well as the Giorgi-Pasquale-Paganelli （GPP） nondestructive gate [Phys. Rev. A 70 （2004） 022319], the sign of any term of the initial state in the GPP model can be flipped. The success possibility of the sign flip of odd number of terms is probabilistic （11/4）, while the success possibility of the sign flip of even number of terms is deterministic （1）.

A Variation Account of Divergent Thinking

A variation account was applied to divergent thinking accommodated as a kind of creative thinking. To provide control （contrast） condition the variation account was applied to psychometric intelligence. Guilford＇s （1956, 1967, 1988） theory of divergent-----convergent thinking served the background of our study. The main premise was that creative variation represents ＂thought trials＂ with diverse ways to find a solution to the problem. Task demands and the respective creative problem solving reveal advantageous sources that suggest the variation. Probably, uncertainty, information search, and finding alternatives extracted from memory precede, entail and provide variety of seeking, as well. A principal hypothesis to be tested was that divergent thinking enables its variation rather than intelligence does that to its variation. As predicted, the divergent thinking and its variation were related. Compared to uncreative, creative persons were characterized by larger variation. Apart from the mathematical intelligence, other kinds of intelligence and their variation did not correlate. Mainly, the data obtained, thus, lend support to the claimed hypothesis.

Security analysis of access control model in hybrid cloud based on security entropy

To resolve the problem of quantitative analysis in hybrid cloud,a quantitative analysis method,which is based on the security entropy,is proposed.Firstly,according to the information theory,the security entropy is put forward to calculate the uncertainty of the system' s determinations on the irregular access behaviors.Secondly,based on the security entropy,security theorems of hybrid cloud are defined.Finally,typical access control models are analyzed by the method,the method's practicability is validated,and security and applicability of these models are compared.Simulation results prove that the proposed method is suitable for the security quantitative analysis of the access control model and evaluation to access control capability in hybrid cloud.

Dynamic estimation and reliability control of quality assurance for bored piles

A systematic method was proposed to estimate the occurrence probability of defective piles(OPDP) from a site according to quality assurance inspection. The OPDP was firstly suggested as the criterion to weight the performance of a pile foundation. Its prior distribution and updating distribution were deduced to follow Beta distributions. To calibrate the OPDP, a dynamic estimation model was established according to the relationships between prior mean and variance and updating mean and variance. Finally, a reliability-control method dealing with uncertainties arising from quality assurance inspection was formalized to judge whether all the bored piles from a site can be accepted. It is exemplified that the OPDP can be substantially improved when more definite prior information and sampling formation become available. For the example studied herein, the Bayesian estimator of updating variance for OPDP is reduced from 0.0037 to 0.0014 for the first inspection, from 0.0014 to 0.0009 for the second inspection, and with less uncertainty by incorporating experience information.

Uncertainty Assessment of Soil Erosion Model Using Particle Filtering

Recent advances in computer with geographic information system(GIS) technologies have allowed modelers to develop physics-based models for modeling soil erosion processes in time and space.However, it has been widely recognized that the effect of uncertainties on model predictions may be more significant when modelers apply such models for their own modeling purposes.Sources of uncertainty involved in modeling include data, model structural, and parameter uncertainty.To deal with the uncertain parameters of a catchment-scale soil erosion model(CSEM) and assess simulation uncertainties in soil erosion, particle filtering modeling(PF) is introduced in the CSEM.The proposed method, CSEM-PF, estimates parameters of non-linear and non-Gaussian systems, such as a physics-based soil erosion model by assimilating observation data such as discharge and sediment discharge sequences at outlets.PF provides timevarying feasible parameter sets as well as uncertainty bounds of outputs while traditional automatic calibration techniques result in a time-invariant global optimal parameter set.CSEM-PF was applied to a small mountainous catchment of the Yongdamdam in Korea for soil erosion modeling and uncertainty assessment for three historical typhoon events.Finally, the most optimal parameter sets and uncertainty bounds of simulation of both discharge and sediment discharge at each time step of the study events are provided.

Modification of evidence theory based on feature extraction

Although evidence theory has been widely used in information fusion due to its effectiveness of uncertainty reasoning, the classical DS evidence theory involves counter-intuitive behaviors when high conflict information exists. Many modification methods have been developed which can be classified into the following two kinds of ideas, either modifying the combination rules or modifying the evidence sources. In order to make the modification more reasonable and more effective, this paper gives a thorough analysis of some typical existing modification methods firstly, and then extracts the intrinsic feature of the evidence sources by using evidence distance theory. Based on the extracted features, two modified plans of evidence theory according to the corresponding modification ideas have been proposed. The results of numerical examples prove the good performance of the plans when combining evidence sources with high conflict information.

Day-to-day traffic user equilibrium model considering influence of intelligent highways and advanced traveler information systems

To explore the influence of intelligent highways and advanced traveler information systems(ATIS)on path choice behavior,a day-to-day(DTD)traffic flow evolution model with information from intelligent highways and ATIS is proposed,whereby the network reliability and experiential learning theory are introduced into the decision process for the travelers’route choice.The intelligent highway serves all the travelers who drive on it,whereas ATIS serves vehicles equipped with information systems.Travelers who drive on intelligent highways or vehicles equipped with ATIS determine their trip routes based on real-time traffic information,whereas other travelers use both the road network conditions from the previous day and historical travel experience to choose a route.Both roadway capacity degradation and travel demand fluctuations are considered to demonstrate the uncertainties in the network.The theory of traffic network flow is developed to build a DTD model considering information from intelligent highway and ATIS.The fixed point theorem is adopted to investigate the equivalence,existence and stability of the proposed DTD model.Numerical examples illustrate that using a high confidence level and weight parameter for the traffic flow reduces the stability of the proposed model.The traffic flow reaches a steady state as travelers’routes shift with repetitive learning of road conditions.The proposed model can be used to formulate scientific traffic organization and diversion schemes during road expansion or reconstruction.

A K-means clustering based blind multiband spectrum sensing algorithm for cognitive radio

In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method.

Women in Leadership and Decision-Making： Understanding Different Styles of Leading

Women in leadership and decision-making roles influence the policies and directions of organizations （Ahuja, 2002）. Women in leadership value supports from their organizations. Pro-social outcomes of relationship competence are mediated by the development of empathy, collaborative approaches to conflict, self-disclosure, and social interest （Jogulu ＆ Wood, 2006）. Decision-making perspectives have uncertainty as the sole reason for organizational leaders to search for additional relevant information to solidify or clarify the information at the leader＇s disposal. A phenomenological qualitative research study which explored the preferred style of leadership based on three leadership and decision-making styles is presented in this paper1. The researcher gathered insights into the lived experiences of like-minded sample of respondents from the research population as they described their leadership and decisionmaking experiences within their organizations.

Inter-signal interaction and uncertain information in anuran multimodal signals

Disentangling the influence of multiple signal components on receivers and elucidating general processes influencing complex signal evolution are difficult tasks. In this study we test mate preferences of female squirrel treefrogs Hyla squirella and female tungara frogs Physalaemus pustulosus for similar combinations of acoustic and visual components of their multimodal courtship signals. In a two-choice playback experiment with squirrel treefrogs, the visual stimulus of a male model significantly increased the attractivness of a relatively unattractive slow call rate. A previous study demonstrated that faster call rates are more attractive to female squirrel treefrogs, and all else being equal, models of male frogs with large body stripes are more attractive. In a similar experiment with female tungara frogs, the visual stimulus of a robotic frog failed to increase the attractiveness of a relatively unattractive call. Females also showed no preference for the distinct stripe on the robot that males commonly bear on their throat. Thus, features of conspicuous signal components such as body stripes are not universally important and signal function is likely to differ even among species with similar ecologies and communication systems. Finally, we discuss the putative information content of anuran signals and suggest that the categorization of redundant versus multiple messages may not be sufficient as a general explanation for the evolution of multimodal signaling. Instead of relying on untested assumptions concerning the information content of signals, we discuss the value of initially collecting comparative empirical data sets related to receiver responses.