Seeking the Important Nodes of Complex Networks in Product R&D Team Based on Fuzzy AHP and TOPSIS

How to seek the important nodes of complex networks in product research and development (R&D) team is particularly important for companies engaged in creativity and innovation. The previous literature mainly uses several single indicators to assess the node importance; this paper proposes a multiple attribute decision making model to tentatively solve these problems. Firstly, choose eight indicators as the evaluation criteria, four from centralization of complex networks: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality and four from structural holes of complex networks: effective size, efficiency, constraint, and hierarchy. Then, use fuzzy analytic hierarchy process (AHP) to obtain the weights of these indicators and use technique for order preference by similarity to an ideal solution (TOPSIS) to assess the importance degree of each node of complex networks. Finally, taking a product R&D team of a game software company as a research example, test the effectiveness, operability, and efficiency of the method we established

Seeking the Important Nodes of Complex Networks in Product R&D Team Based on Fuzzy AHP and TOPSIS

How to seek the important nodes of complex networks in product research and development (R&D) team is particularly important for companies engaged in creativity and innovation. The previous literature mainly uses several single indicators to assess the node importance; this paper proposes a multiple attribute decision making model to tentatively solve these problems. Firstly, choose eight indicators as the evaluation criteria, four from centralization of complex networks: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality and four from structural holes of complex networks: effective size, efficiency, constraint, and hierarchy. Then, use fuzzy analytic hierarchy process (AHP) to obtain the weights of these indicators and use technique for order preference by similarity to an ideal solution (TOPSIS) to assess the importance degree of each node of complex networks. Finally, taking a product R&D team of a game software company as a research example, test the effectiveness, operability, and efficiency of the method we established

Spatial Aided Decision-making System for E-Government

Non

Graphene ballistic nano-rectifier with very high responsivity

Although graphene has the longest mean free path of carriers of any known electronic material, very few novel devices have been reported to harness this extraordinary property. Here we demonstrate a ballistic nano-rectifier fabricated by creating an asymmetric cross-junction in single-layer graphene sandwiched between boron nitride flakes. A mobility ∼200,000 cm(2) V(−1) s(−1) is achieved at room temperature, well beyond that required for ballistic transport. This enables a voltage responsivity as high as 23,000 mV mW(−1) with a low-frequency input signal. Taking advantage of the output channels being orthogonal to the input terminals, the noise is found to be not strongly influenced by the input. Hence, the corresponding noise-equivalent power is as low as 0.64 pW Hz(−1/2). Such performance is even comparable to superconducting bolometers, which however need to operate at cryogenic temperatures. Furthermore, output oscillations are observed at low temperatures, the period of which agrees with the lateral size quantization

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

BACKGROUND: It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. RESULTS: In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network) to address the underlying regulations of genes that can span any unit(s) of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. CONCLUSION: We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex gene regulations related to the development, aging and progressive pathogenesis of a complex disease where potential dependences between different experiment units might occurs

Interorganizational Knowledge Division Decision Model Based on Cooperative Innovation of Supply Chain System

Within interorganizational cooperative innovation of construction supply chain system, the achievement of project value-adding could be reflected by several factors, such as project-based organizational effect level, and the relationship between project cooperative innovation objectives. In this paper, based on the assumption of equal cooperation between project-based organizations, we selected the knowledge cooperation between the owner and contractor in construction supply chain system as research object. From the perspective of maximizing project value-adding and the relationship of effort cost between knowledge input and innovation stage in consideration, we established the knowledge collaborative incentive model for interorganizational cooperative innovation of construction supply chain system and proposed the first-order and second-order approaches. Then we conducted the digital simulation and example analysis, its results showed that if the owner has the capability to achieve project value-adding in knowledge cooperation, he would adopt a part commissioned way. Otherwise, a fully commissioned way would be better

How to Develop the Interdisciplinary Innovation Teams Sustainably?—A Simulation Model from a Perspective of Knowledge Fission and Fusion

Knowledge interaction is vital in order that interdisciplinary innovation teams (IITs) develop sustainably. This paper aims to reveal the laws of knowledge interaction in IITs from a perspective of knowledge fission and fusion. Herein, the conceptions of knowledge fission to depict the team member’s divergent thinking and knowledge fusion to depict the team member’s convergent thinking based on the concept of social physics are proposed. Furthermore, the Markov process describing knowledge interaction is built. The paper uses a case study and a simulation analysis to explain the process of knowledge interaction. The results show that knowledge fission and knowledge fusion have different influences on the various stages of knowledge interaction. To conclude, the model built describes the complex phenomenon of the knowledge interaction process. It reveals the transformation rules from knowledge fission to knowledge fusion in the process of knowledge interaction in IITs. This study also provides new insight for IITs to maintain team sustainability

Exploring the Multi-Phase Driven Process for Disruptive Business Model Innovation of E-Business Microcredit: a Multiple Case Study from China

This paper uses a multiple case study to reveal and analyze how the disruptive business model innovation of e-business microcredit firms is driven by the three phases of discovering, screening, and combining and matching drivers with an internal business model. The results suggest that it is the integrated forces of the market, technology, policy, competition, and entrepreneurs’ groups to drive the process, and whose specific sub-drivers are further analyzed and have a significant impact on the second phase. The types of disruptive business model innovation of e-business microcredit firms are determined by matching the criteria and methods of entrepreneurs groups in terms of risk consideration. As little research has been done on the systematic analysis of the driven process of disruptive business model innovation from a holistic perspective of drivers, this study makes a contribution to complete the understanding of this process, especially in the e-business microcredit arena. This study also gives renewed knowledge to disruptive innovation theory. This study assesses managerial implications to the development and prediction of internet financial service firms