Design of Authoring Tool for Static and Dynamic Projection Mapping

This study introduces the design details of a tool to create interactive projection-mapping content in a convenient manner.For the proposed tool design,a homography-based camera–projector calibration method was applied with the use of red–green–blue-depth images from a Kinect V2 sensor that did not require accurate camera calibration prerequisites.In addition,the proposed tool simultaneously achieved static projection mapping that projected the image content onto a fixed object,and dynamic projection mapping that projected the image content onto a user’s body,by tracing the moving user.To verify the effectiveness of the proposed content-creation tool,users with no programming capabilities were employed to create contents that were projected onto various objects in fixed positions and a user’s body in various poses,thereby analyzing the tool’s completeness.Moreover,the projection accuracy was analyzed at different depth positions,and the projection-mapping accuracy was verified with the use of the proposed method.

Analysis on Rules of Investment Decision Based on Payback Period of Dynamic Investment

The index of payback period of dynamic investment is an improvement on index of payback period of static investment, which is the problem that the rules to evaluate the project are feasible or not. This paper proves that rules shall be apt when using payback period of dynamic investment to evaluate the project feasibility under the condition of keeping the dynamic evaluation index to evaluate the same scheme and the consistent feasibility.

Forward indifference valuation for dynamically incoming projects

Classical indifference valuation,a widely studied approach in incomplete markets,uses critically the a priori knowledge of the characteristics(arrival,maturity,payoff structure)of the projects in consideration.This assumption,however,may not accommodate realistic scenarios in which projects,not initially anticipated,arrive at later times.To accommodate this,we employ forward indifference valuation criteria,which by construction are flexible enough to adapt to such"non-anticipated"cases while yielding time-consistent indifference prices.We consider and analyze in detail two representative cases:valuation adjustments due to incoming non-anticipated project and the relative forward indifference valuation of new projects in relation to existing ones.

A Projection Pursuit Dynamic Cluster Model Based on a Memetic Algorithm

A Projection Pursuit Dynamic Cluster(PPDC) model optimized by Memetic Algorithm(MA) was proposed to solve the practical problems of nonlinearity and high dimensions of sample data, which appear in the context of evaluation or prediction in complex systems. Projection pursuit theory was used to determine the optimal projection direction; then dynamic clusters and minimal total distance within clusters(min TDc) were used to build a PPDC model. 17 agronomic traits of 19 tomato varieties were evaluated by a PPDC model. The projection direction was optimized by Simulated Annealing(SA) algorithm, Particle Swarm Optimization(PSO), and MA. A PPDC model,based on an MA, avoids the problem of parameter calibration in Projection Pursuit Cluster(PPC) models. Its final results can be output directly, making the cluster results objective and definite. The calculation results show that a PPDC model based on an MA can solve the practical difficulties of nonlinearity and high dimensionality of sample data.

Collaborative work model based on peer-to-peer network

In this paper, we incorporated peer-to-peer (P2P) concept with agent technology and put forward a collaborative work model based on peer-to-peer network (P2PCWM) after investigating into business demands of modern enterprises and problems prevailing in mainstream collaborative work systems based on central server. Theoretically, the P2PCWM can effectively overcome the problems in a conventional system with a central server and meet the practical demands of modern businesses. It is distinguished from other systems by its features of equality, openness, promptness, fairness, expandability and convenience.

A distributed coding-decoding-based Nash equilibrium seeking algorithm over directed communication network

This paper is concerned with the distributed Nash equilibrium(NE) computation problem for non-cooperative games subject to partial-decision information.For the purpose of congestion mitigation,coding-decoding-based schemes are constructed on the basis of logarithmic and uniform quantizers,respectively.To be specific,the data(decision variable) are first mapped to codewords by an encoder scheme,and then sent to the neighboring agents through a directed communication network(with non-doubly stochastic weighted matrix).By using a decoder scheme,a new distributed algorithm is established for seeking the NE.In order to eliminate the convergence error caused by quantization,a dynamic variable is introduced and a modified codingdecoding-based algorithm is constructed under the uniform quantization scheme,which ensures the asymptotic convergence to the NE.The proposed algorithm only requires that the weighted adjacency matrix is row stochastic instead of double stochastic.Finally,one numerical example is provided to validate the effectiveness of our algorithms.