Geodesic Distance Function Learning via Heat Flow on Vector Fields

Learning a distance function or metric on a given data manifold is of great importance in machine learning and pattern recognition. Many of the previous works first embed the manifold to Euclidean space and then learn the distance function. However, such a scheme might not faithfully preserve the distance function if the original manifold is not Euclidean. Note that the distance function on a manifold can always be well-defined. In this paper, we propose to learn the distance function directly on the manifold without embedding. We first provide a theoretical characterization of the distance function by its gradient field. Based on our theoretical analysis, we propose to first learn the gradient field of the distance function and then learn the distance function itself. Specifically, we set the gradient field of a local distance function as an initial vector field. Then we transport it to the whole manifold via heat flow on vector fields. Finally, the geodesic distance function can be obtained by requiring its gradient field to be close to the normalized vector field. Experimental results on both synthetic and real data demonstrate the effectiveness of our proposed algorithm

Latest lessons from the bankruptcy of state-owned enterprises (SOEs) in China : an interpretative structural model (ISM) approach

State-owned enterprises (SOEs) play an important role in China. During the transformation from a planned to a market economy, plenty of Chinese SOEs fell into trouble. Dalian machine tool group (DMTG) who was once a leading enterprise in the Chinese machine tool industry bankrupted in 2017. To explore the causes of its collapse, we employ the interpretative structural model (ISM) to investigate the reasons for its failures from multi-aspect and at different levels. The results indicate that the root cause of this bankruptcy is the top manager’s mismanagement; the lack of a reasonable strategic positioning and long-term product planning are also important factors of DMTG’s failure, and the problems of human resource management accelerated the bankruptcy. Findings provide lessons to be learned from the bankruptcy for SOEs and offer managerial insight into SOEs.Peer ReviewedPostprint (published version

The Economic Role of Rating Behavior in Third-Party Application Market

This paper explores the fundamental influence of consumer rating behavior on an emerging third-party software application market, mobile app market. In app market, consumers’ ex ante belief on app utility essentially is determined by the app rating while at the same time the app rating itself is derived from the ex post utility obtained by purchased customers. We develop an analytical model which explicitly characterizes this bidirectional rating-utility conversion based on a newly introduced concept “reservation rating”. After building this conversion process into the utility function, we examine the market equilibrium and show how change in consumer rating attitude, such as being severer in offering ratings or being less critical in accepting ratings, would affect the developers’ optimal choices of app price and app quality level as well as the platform owner’s optimal revenue sharing policy

An approach to multiple attribute decision making based on the induced Choquet integral with fuzzy number intuitionistic fuzzy information

In this paper, we investigate the multiple attribute decision making problems with fuzzy number intuitionistic fuzzy information. Firstly, some operational laws of fuzzy number intuitionistic fuzzy values, score function and accuracy function of fuzzy number intuitionistic fuzzy values are introduced. Then, we have developed two fuzzy number intuitionistic fuzzy Choquet integral aggregation operators: induced fuzzy number intuitionistic fuzzy choquet ordered averaging (IFNIFCOA) operator and induced fuzzy number intuitionistic fuzzy choquet ordered geometric (IFNIFCOG) operator. The prominent characteristic of the operators is that they can not only consider the importance of the elements or their ordered positions, but also reflect the correlation among the elements or their ordered positions. We have studied some desirable properties of the IFNIFCOA and IFNIFCOG operators, such as commutativity, idempotency and monotonicity, and applied the IFNIFCOA and IFNIFCOGM operators to multiple attribute decision making with fuzzy number intuitionistic fuzzy information. Finally an illustrative example has been given to show the developed method

A scalable bloom filter based prefilter and hardware-oriented predispatcher

Presented in this paper a scalable bloom filter based prefilter and a hardware-oriented predispatcher pattern matching mechanism for content filtering applications, which are scalable in terms of speed, the number of patterns and the pattern length. Prefilter algorithm is based on a memory efficient multi-hashing data structure called bloom filter. According to the statistics of simulations, the filter ratio can reach up to 60% if the whole engine has been trained well. It has been showed that this engine could enhance the capabilities of general-purpose IDS solutions