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.

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.

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.

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.

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.

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.

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.

综合处理专家意见的MABM方法

本文以不确定性信息处理的数学理论为基础 ,给出了多智能体系统 (MAS)不确定性结论合成的一般方法 ,即 MABM方法 。

Uncertainty and Sensitivity Analyses for Modeling Long-Term Soil Organic Carbon Dynamics of Paddy Soils Under Different Climate-Soil-Management Combinations

Reporting modeling results with uncertainty information can benefit decision making by decreasing the extent that variability exerts a disproportionate influence on the options selected. For making decisions with more confidence, the uncertainty interval should be as narrow as possible. Here, the soil organic carbon （SOC） dynamics of the major paddy soil subgroup from 4 different paddy field regions of China （located in 4 counties under different climate-soil-management combinations） were modeled using the DeNitrification- DeComposition （DNDC） model for the period from 1980 to 2008. Uncertainty intervals associated with the SOC dynamics for these 4 subgroups were estimated by a long-term global sensitivity and uncertainty analysis （i. e., the Sobolt method）, and their sensitivities to 7 influential factors were quantified using the total effect sensitivity index. The results, modeled with high confidence, indicated that in the past 29 years, the studied paddy soils in Xinxing, Yixing, and Zhongjiang counties were carbon （C） sinks, while the paddy soil in Helong County was a C source. The 3 C sinks sequestered 12.2 （5.4, 19.6）, 17.1 （8.9, 25.0）, and 16.9 （-1.2, 33.6） t C ha-1 （values in the parentheses are the 5th and 95th percentiles, respectively）. Conversely, the C source had a loss of -5.4 （-14.2, 0.06） t C ha-1 in the past 29 years. The 7 factors, which changed with the climate-soil-management context, exhibited variable influences on modeled SOC. Measures with potential to conserve or sequestrate more C into paddy soils, such as incorporating more crop residues into soils and reducing chemical fertilizer application rates, were recommended for specific soils based on the sensitivity analysis results.

A New Hybrid Reliability Index Definition and Its Application to the Structure Buckling Reliability Analysis of Supercavitating Projectiles

As structure buckling problems easily arise when supercavitating projectiles operate with high underwater velocity, it is necessary to perform structure buckling reliability analysis. Now it is widely known that probabilistic and non-probabilistic uncertain information exists in engineering analysis. Based on reliability comprehensive index of multi-ellipsoid convex set, probabilistic uncertain information is added and transferred into non-probabilistic interval variable. The hybrid reliability is calculated by a combined method of modified limit step length iteration algorithm(MLSLIA) and Monte-Carlo method. The results of engineering examples show that the convergence of MLSLIA is better than that of limit step length iteration algorithm(LSLIA). Structure buckling hybrid reliability increases with the increase of ratio of base diameter to cavitator diameter, and decreases with the increase of initial launch velocity. Also the changes of uncertain degree of projectile velocity and cavitator drag coefficient affect structure buckling hybrid reliability index obviously. Therefore, uncertain degree of projectile velocity and cavitator drag coefficient should be controlled in project for high structure buckling reliability.

Information Revelation in Sequential Auctions with Uncertainties About Future Objects

In many auctions,buyers know beforehand little about objects to be sold in the future.Whether and how to reveal information about future objects is an important decision problem for sellers.In this paper,two objects are sold sequentially and each buyer's valuation for the second object is k times that for the first one,and the true value of k is sellers' private information.The authors identify three factors which affect sellers' revelation strategies: The market's competition intensity which is characterized by the number of buyers,buyers' prior information about the second object,and the difference degree between two objects which is characterized by k.The authors give not only conditions under which revealing information about the second object in advance benefits the seller,but also the optimal releasing amount of information in the market with two sellers and one seller,respectively.