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An attribute reduct, an important concept of rough set theory, is a subset that is sufficient and individually necessary for preserving a particular property of the given information system. In this study, we present a proposed method to calculate the accuracy of data by using the concepts of pre-open and semi-open. We also compared the results of accuracies in the proposed method with the accuracies in Yao and Pawlak methods. Our study revealed that the new model calculating the degree of accuracy was better than the previous models. Additionally, we provided a new insight into the application of the attribute reduction and we used MATLAB programming to obtain the result. [ABSTRACT FROM AUTHOR]

Although individuals generally avoid negative information, recent research documents that they voluntarily explore negative information to resolve uncertainty. However, it remains unclear (a) whether uncertainty facilitates exploration similarly when exploration is expected to lead to negative, neutral, or positive information, and (b) whether older adults seek negative information to reduce uncertainty like younger adults do. This study addresses the two issues across four experimental studies (N = 407). The results indicate that individuals are more likely to expose themselves to negative information when uncertainty is high. In contrast, when information was expected to be neutral or positive, the uncertainty surrounding it did not significantly alter individuals' exploration behavior. Furthermore, we found that uncertainty increased the exploration of negative information in both older and younger adults. In addition, both younger and older adults chose to explore negative information to reduce uncertainty, even when there were positive or neutral alternatives. In contrast to the age-related similarities in these behavioral measures, older adults demonstrated reduced scores in questionnaires on sensation seeking and curiosity, relative to their counterparts who were younger. These results suggest that information uncertainty has a selective facilitation effect on exploration for negative information and that normal aging does not alter this tendency, despite age-related reductions in self-reported measures of personality traits relevant to information seeking. [ABSTRACT FROM AUTHOR]

This paper proposes a versatile intelligent fault diagnosis (IFD) scheme for a distribution grid integrated with intermittent renewable energy resources (RER). Renewable generation parameters (wind speed and solar irradiation) and load demand intermittency along with fault information (fault inception angle and resistance) uncertainty are modeled by employing different probability density functions. Then, advanced signal processing techniques are used to extract useful features from the recorded signals. The proposed approach sends the extracted features as inputs to feedforward neural networks (FF-NNs) to diagnose (detect, classify, and identify faulty sections) and locate the faults. The presented results confirm the efficacy of the developed IFD scheme and show that it is independent of renewable generation and load demand intermittency along with fault information uncertainty. Additionally, the proposed scheme is independent of the presence of measurement noises. Furthermore, this work investigates the effectiveness of the developed IFD scheme under various contingency cases (branch outages and RER generation outages). Finally, a laboratory prototype IFD scheme is built by integrating a physical phasor measurement unit (PMU) with a real-time digital simulator (RTDS) rack to diagnose faults in the distribution grid. The results confirm the effectiveness of the prototype IFD scheme, as they show good agreement with the simulation results. [ABSTRACT FROM AUTHOR]

Based on the knowledge generation model for visual analytics including uncertainty propagation and human trust building (Sacha et al. 2016), the cognitive theory of multimedia learning (Mayer, 2014), the multimedia principle (Butcher, 2014), and previous studies on the effects of different uncertainty visualization styles, an integrated theoretical approach is proposed to examine the influence of different degrees of information uncertainty and different uncertainty visualization styles on processing pictures of two archeological reconstructions with accompanying audio explanations presented in a multimedia learning environment. A 4 × 3 design with condition (without uncertainty visualization vs. stop light colors vs. geometric contrast vs. both uncertainty visualizations) as the between-subjects factor and uncertainty value (uncertain vs. medium vs. certain) as the within-subject factor was used. The results showed that appearance of certain content, its uncertainty values, and their verbal scientific justifications were remembered better than uncertain ones. Furthermore, stop light colors enhanced the memory of uncertainty values compared to no uncertainty visualization and were better understood, discriminated, and transferred than geometric contrast. Geometric contrast decreased the memory of the appearance of uncertain architectural elements compared to no uncertainty visualization and was better than stop light colors regarding the memory of the appearance of certain architectural elements. The study integrates and extends existing theories by showing that certain contents are processed with higher priority than uncertain contents and that the multimedia effect is also valid for metainformation such as the uncertainties of contents. Finally, recommendations for designing learning material including uncertainty visualizations are given. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to build an agent-based model which is adapted to study the information cascades in financial markets. Thus, we design and implement a model with asynchronous continuous-time management, populated by heterogeneous traders, connected by an interaction network with directed and weighted edges, which allows them to observe and learn about the actions of their peers. The proposed model relaxes unrealistic assumptions of previous analytical models, particularly, homogeneity of traders and access to all previous decisions (full network). Therefore, the proposed model allows to study the impact of different factors in the emergence and magnitude of information cascades: mainly, the impact of the heterogeneity of traders behaviours and characteristics of the interaction network. Moreover, unlike analytical models which focus only on how information cascades occur, the proposed model allows studying the impact of information cascades on the price dynamics. Then, we use the model to perform a series of experiments to investigate the impact of various factors in the formation and magnitude of information cascades. The obtained results show in particular that informational cascades only occur when the market is dominated by an overwhelming majority of traders who have significant uncertainty in their own signals. This shows the benefit of designing policies to reduce uncertainty among investors to avoid informational cascades, whether by financial regulatory authorities or by companies with high degrees of information uncertainty. [ABSTRACT FROM AUTHOR]

The construction and building industry (CBI) is considered one of the major carbon emission contributors to the environment and faces various social and technical challenges in implementing decarbonized and circular economy (DCE) practices. Resource optimization can be achieved using the CBI product circularity and carbon offset mechanisms for greater business sustainability. In past studies, DCE practices have been loosely considered for improving the sustainability performance of emerging economies’ CBI. To fill this gap, this study uniquely focuses on CBI practices on DCE in consideration of socio-technical system (STS) availability because STS plays a vital role in adopting DCE practices. The proposed research framework is based on STS theory to measure the inter-influence of socio-technical challenges in achieving decarbonized and circular CBI. The STS-based framework consists of six dimensions namely: goals of circular construction (GCC), people barriers (PB), cultural barriers (CB), infrastructural barriers (IB), technological barriers (TB), and construction process and procedural barriers (CPB). The main STS dimensions are further divided into 26 sub-dimensions to assess interinfluencing mapping. The proposed framework is analyzed using integrated grey information uncertainty theory with decision-making trial and evaluation laboratory (DEMATEL), and interpretive structural modelling (ISM), i.e., grey-DISM. The grey-DISM method measures the driving power and dependence of the interdependencies of the decarbonized circularity barriers of the Indian CBI. Fifteen industry experts participated in the data survey, and their participation consistency was more than 95%. Barriers IB and CPB were found to be the major and minor challenges in implementing DCE in CBI. The findings of this research reported that lack of decarbonized and CE-based infrastructure hinders the adoption of DCE practices. This paper’s results also highlight the construction design dependency on infrastructure and machinery and low DCE practice perceptions for improving circularity in CBI. The entire decision model is divided into three levels of hierarchical mapping, which helps construction practitioners and policymakers develop strategic planning for improving DCE practices in CBI. The paper also presented managerial and policy implications for CBI practitioners and policymakers. [ABSTRACT FROM AUTHOR]

The primary goal of carrier screening is to identify asymptomatic individuals who carry variants associated with genetic diseases, to inform about the risk of having a child with a genetic disease. Carrier screening can be accomplished through different approaches including ethnicity-based screening, pan-ethnic screening, and expanded carrier screening (ECS), and the decision to pursue carrier screening is voluntary. ECS takes a broad approach by screening for a large number of genetic diseases irrespective of ethnic background, and ideally is performed prior to conception. ECS has many benefits, including that it does not depend on accuracy of reported ancestry, as well as its greater yield of information that can be used for reproductive decision-making. However, there are also many important limitations of ECS to consider, ranging from the yield of unexpected information, uncertainty about the phenotype of a particular disease for which an individual is a carrier, and greater downstream costs associated with further testing and genetic counseling. Detailed genetic counseling both prior to and after ECS is essential in order for patients to understand the breadth of this approach, potential and actual results, and limitations. [ABSTRACT FROM AUTHOR]

This paper provides the inter-temporal capital asset pricing model with incomplete information and short sales constraints. We derive the general equilibrium market equation and the security market line of the "classical" capital asset pricing model in continuous time in the presence of incomplete information and short sales. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive neural network approach to classification which combines modified probabilistic neural network and D-S evidence theory (PNN-DS) is proposed. It attempts to deal with the drawbacks of information uncertainty and imprecision using single classification algorithm. This PNN-DS approach firstly adopts a modified probabilistic neural network (PNN) to obtain posteriori probabilities and make a primary classification decision in feature-level fusion. Then posteriori probabilities are transformed to masses noting the evidence of the D-S evidential theory. Finally advanced D-S evidential theory is utilized to gain more accurate classification results in the last decision-level fusion. In order to implement PNN-DS, covariance matrices are firstly employed in the modified PNN module to replace the singular smoothing factor in the PNN's kernel function, and linear function is utilized in the pattern of summation layer. Secondly, the whole scheme of the proposed approach is explained in depth. Thirdly, three classification experiments are carried out on the proposed approach and a large amount of comparable analyses are done to demonstrate the effectiveness and robustness of the proposed approach. Experiments reveal that the PNN-DS outperforms BPNN-DS, which provides encouraging results in terms of classification accuracy and the speed of learning convergence. [ABSTRACT FROM AUTHOR]

It is necessary to emphasize both the process and results of performance management to find the balance between quality and quantity needed to ensure the sustainable development of universities to make the best use of limited educational resources and meet the diverse needs of students. This study applies failure mode and effects analysis (FMEA) to analyze obstacles to university sustainability by constructing complete risk assessment modes and reference indicators. The neutrosophic set theory was incorporated into the FMEA to account for information uncertainty and asymmetry. A specialist team then evaluated the importance of the risk factors using neutrosophic indifference threshold-based attribute ratio analysis to determine objective weights for the risk factors. Furthermore, the neutrosophic technique for order preference by similarity to the ideal solution based on aspiration level (N-TOPSIS-AL) is employed to aggregate the total risk scores of the failure modes. Using neutrosophic sets to measure truth, falsity, and indeterminacy in the assessment significantly improve the adaptability of the fuzzy theory to real-world problems. The study results indicate that when assessing university affairs management and analyzing possible risks, priority must be given to the occurrence of risks and that the lack of educational facilities is the riskiest item in the specialist assessment. The proposed assessment model can be applied as a basis for university sustainability assessments to accelerate the development of other forward-looking approaches. [ABSTRACT FROM AUTHOR]

With the development of system complexity, a variety of nondeterministic information is frequently encountered in networks. To deal with the nondeterministic information, uncertainty theory is proposed as a powerful tool. Within the framework of uncertainty theory, in this paper, a concept of tree index of uncertain graph is proposed. It also gives a method to calculate tree index of uncertain graphs. Moreover, the tree index of uncertain cycle and the path index of uncertain graphs are proposed and analyzed in a similar way. [ABSTRACT FROM AUTHOR]

Probabilistic approaches are widely adopted for the modeling of rockfall trajectories, but are not widely discussed in the literature. This paper aims to help fill this gap by reviewing probabilistic models of rockfall trajectories, while providing some perspectives for future study. We first make it clear that, from a theoretical point of view, the probabilistic approach is necessitated by both the ontic (inherent) uncertainty associated with rockfalls and the epistemic (information) uncertainty associated with numerical modeling. The review suggests that there may be the potential to improve the probabilistic modeling of rockfall trajectories in various aspects, including the systematic probabilistic modeling criterion, the random sampling approaches employed for probabilistic variables, the probabilistic modeling of rock shape, and the probabilistic prediction of rockfall intensity. However, there are still some open questions regarding the promotion of probabilistic modeling in practice. It is not clear whether probabilistically treating all of the variables of rockfall trajectory model with reasoned distributions will lead to significantly improved results, or whether the improvements will be great enough (given the difficulties and costs involved) that it is worth quantifying all of the uncertainties involved in rockfall trajectory modeling. The answers to these questions can be found in the practice of probabilistic modeling itself. [ABSTRACT FROM AUTHOR]