Multivalued Decision Diagrams-Based Trust Level Analysis for Social Networks

Zhang, Li; Xing, Liudong; Liu, Anqing; Mao, Keming

doi:10.1109/access.2019.2956113

Cited by 5 publications

(4 citation statements)

References 36 publications

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“…A total of 400 questionnaires are sent out, and 340 are recovered with a recovery rate of 85%. Through the verification of incomplete questionnaires and sampling standards, 296 valid questionnaires are recovered with an effective recovery rate of about 87%, meeting relevant requirements ( Zhang et al, 2019 ).…”

Section: Methodsmentioning

confidence: 99%

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The Multinational New Ventures on Corporate Performance Under the Work Environment and Innovation Behavior

2022

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To cope with economic globalization and improve the competitiveness of transnational start-ups, the impact of the work environment and innovation behavior on corporate performance of multinational new ventures is analyzed. First, a model of the interaction among environment, innovation behavior, and enterprise performance is proposed. Then, 296 transnational start-ups in coastal areas are surveyed, and the model results are analyzed. Finally, a series of results are obtained. The results show that from the perspective of psychology, work dynamic organizational learning environment has a positive impact on enterprise performance (standardized path coefficient 0.436, p < 0.01), and resource environment has a significant positive impact on enterprise performance (standardized path coefficient 0.425, p < 0.01). Strategic environment also positively affects enterprise performance (standardized path coefficient 0.474, p < 0.01). Therefore, the working environment of multinational new ventures has a positive impact on firm performance, and the mediating function between the working environment and firm performance is firm innovation behavior. With the research to achieve enterprise innovation of multinational new ventures by improving their response to the dynamic environment, the corporate performance has been greatly promoted, and finally, the new ventures would participate in the international market competition.

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Section: Methodsmentioning

confidence: 99%

“…First, the enterprise must be established for more than 3 years of normal operation and less than 10 years. Second, it must be an (Zhang et al, 2019).…”

Section: Data Collectionmentioning

confidence: 99%

The Multinational New Ventures on Corporate Performance Under the Work Environment and Innovation Behavior

2022

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“…In the last years, MDDs have been applied in many disparate research domains proving the potential of this structure. MDDs are used, for instance, to improve random forest algorithms replacing the classic binary decision trees [12], to represent and analyze automotive product data of valid/invalid product configurations [6], and to perform trust analysis in social networks [16]. There are also applications related to mathematical models like Multi-State Systems (MSS) [15].…”

Section: Introductionmentioning

confidence: 99%

MDDs Boost Equation Solving on Discrete Dynamical Systems

Formenti

Régin

Riva

2021

Integration of Constraint Programming, Artificial Intelligence, and Operations Research

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Discrete dynamical systems (DDS) are a model to represent complex phenomena appearing in many different domains. In the finite case, they can be identified with a particular class of graphs called dynamics graphs. In [9] polynomial equations over dynamics graphs have been introduced. A polynomial equation represents a hypothesis on the fine structure of the system. Finding the solutions of such equations validate or invalidate the hypothesis. This paper proposes new algorithms that enumerate all the solutions of polynomial equations with constant right-hand term outperforming the current state-of-art methods [10]. The boost in performance of our algorithms comes essentially from a clever usage of Multi-valued decision diagrams. These results are an important step forward in the analysis of complex dynamics graphs as those appearing, for instance, in biological regulatory networks or in systems biology.

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“…The computational complexity of the calculation of IMs based on the system structure function depends on the system dimension (number of system components). Authors of papers [5,7] propose to use the Binary Decision Diagram (BDD) for the structure function representation to decrease the computational complexity of algorithms for reliability analysis. The application of BDD in importance analysis of system and IMs calculation have been considered in [5,8].…”

Section: Introductionmentioning

confidence: 99%

New Matrix Based Algorithm for Calculation of Importance Measures

Sedlaček¹,

Forgac²,

Zaitseva³

2019

CNCS

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The system reliability/availability is complex term that is evaluated based on numerous indices and measures. There are different methods for the calculation of these indices and measures. Some of the most used are importance measures. These measures allow to evaluate the influence of fixed system components or set of components to the system reliability/availability. Importance measures are used to allow for various aspects of the impact of system elements on its failure or operability. Analysis of element importance is used in the system design, diagnosis, and optimization. In this paper new algorithm for the calculation some of importance measures is developed based on the matrix procedures. This paper goal is development of new algorithm to calculate importance measures of the system based on the matrix procedures that can be transformed in the parallel procedures/algorithm. This algorithm is developed based on the application of Logical Differential Calculus of Boolean logic for importance analysis of system. The application of parallel algorithm in importance analysis allows the evaluation of system of large dimension. Importance specific of the proposed matrix procedures for calculation of importance measures is the application of structure function for the mathematical representation of investigated system. This function defined the correlation of the system components states and system reliability/ availability. The structure function in this case is defined as truth vector to be used in the matrix transformation. The truth vector of Boolean function is column of the truth table of function if the values of the variables are lexicographically ordered

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Multivalued Decision Diagrams-Based Trust Level Analysis for Social Networks

Cited by 5 publications

References 36 publications

The Multinational New Ventures on Corporate Performance Under the Work Environment and Innovation Behavior

The Multinational New Ventures on Corporate Performance Under the Work Environment and Innovation Behavior

MDDs Boost Equation Solving on Discrete Dynamical Systems

New Matrix Based Algorithm for Calculation of Importance Measures

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