PERFORMANCE-DRIVEN BUSINESS PROCESS MANAGEMENT METHODOLOGY FOR SMALL AND MEDIUM SIZED-ENTERPRISES

Based on the analysis of the common limitations of business processmanagement (BPM) methodologies and the requirements of small and medium sized-enterprises (SMEs),the importance of a 'performance construct' of BPM methodologies is identified, a six-phaseperformance-driven BPM methodology for the production and operation processes of Chinese SMEs isdeveloped. A case study on the process management of a medium-sized enterprise shows a successfulexample of running the methodology.

Performance-driven Routing Tree Construction with Buffer Insertion and Wire Sizing

A new approach was proposed to construct a performance-driven rectilinear Steiner tree with simultaneous buffer insertion and wiresizing optimization (PDRST/BW) under a higher order resistance-inductance-capacitance (RLC) delay model. This approach is based on the concept of sharing-buffer insertion and dynamic programming approach combined with a bottom-up rectilinear Steiner tree construction. The performances include the timing delay and the quality of signal waveform. The experimental results show that our proposed approach is scalable and obtains better performance than SP-tree and graph-RTBW approaches for the test signal nets.

Generation of Performance-Driven Facial Expressions

Coordinates of the key facial feature points can be captured by motion capture system OPTOTRAK with real-time character and high accuracy. The facial model is considered as an undirected weighted graph. By iteratively subdividing the related triangle edges, the geodesic distance between points on the model surface is finally obtained. The RBF （Radial Basis Functions） interpolation technique based on geodesic distance is applied to generate deformation of the facial mesh model. Experimental results demonstrate that the geodesic distance can explore the complex topology of human face models perfectly and the method can generate realistic facial expressions.

Performance-Driven Multi-Objective Optimization Method for DLR Transonic Tandem Cascade Shape Design

Transonic tandem cascades can effectively increase the working load,and this feature conforms with the requirement of the large loads and pressure ratios of modern axial compressors.This paper presents an optimization strategy for a German Aerospace Center(DLR)transonic tandem cascade,with one front blade and two rear blades,at the inlet Mach number of 1.051.The tandem cascade profile was parameterized using 19 control parameters.Non-dominated sorting Genetic algorithm(NSGA-II)was used to drive the optimization evolution,with the computational fluid dynamics(CFD)-based cascade performances correction added for each generation.Inside the automatic optimization system,a pressure boundary condition iterative algorithm was developed for simulating the cascade performance with a constant supersonic inlet Mach number.The optimization results of the cascade showed that the deflection of the subsonic blade changed evidently.The shock wave intensity of the first blade row was weakened because of the reduced curvatures of the optimized pressure and suction sides of the front blade part and the downstream moved maximum thickness position.The total pressure losses decreased by 15.6%,20.9%and 19.9%with a corresponding increase in cascade static pressure ratio by 1.3%,1.8%and 1.7%,for the three cascade shapes in the Pareto solution sets under the near choke,the design and near stall conditions,respectively.

Performance-driven design methodology for habitation shell design in extreme conditions on Mars

The research project illustrates how performance-driven design tools can be conducted as an architectural design methodology that suggests an innovative approach to design a habitation shell in extreme environmental conditions without human assistance.This research study attempts to use environmental data revealed by NASA and its habitat design requirements to develop a conceptual design for an innovative habitation form and then simulate it with Mars conditions to analyze the habitation shell’s structural behavior according to finite element analysis.In this regard,research phases,including layout configuration,form-finding,and structural analysis,have been conducted to explore a habitation concept implemented with generative design tools as a decision-maker in extreme conditions.In conclusion,two generated typologies of proposed habitation forms will be compared in terms of their structural performance under extreme loads of the martian environment.Within this research project,due to the numerous extreme challenges of design and construction of habitation in extreme conditions using conventional approaches,a performance-driven design methodology will provide a rational and sustainable design methodology to tackle extreme barriers to Mars’s environment.

Performance driven expression mapping based on segmented examples

We present a method that combines performance-driven method with segmented 3D blendshape models to animate a face. First we prepare key sample examples and corresponding key target examples. Next we segment the whole face into two regions, for each region we reduce dimensionality of source examples using PAC into abstract space which is defined by truncated PCA eigen- vectors. Then for each example we fix the cardinal base function, which can determine the weight of the target example. Finally, in the animation stage we compute the weight of each example for each frame and add the weighted displacement vectors of each re- gion on the general face model.

System partitioning on MCM using a new neural network model

A new self-organizing neural network model is presented, which can get rid of some fatal defects facing the Kohonen self-organizing neural network, known as the slow training speed, difficulty in designing neighboring zone, and disability to deal with area constraints directly. Based on the new neural network, a new approach for performance-driven system partitioning on MCM is presented. In the algorithm, the total routing cost between the chips and the circle time are both minimized, while satisfying area and timing constraints. The neural network has a reasonable structure and its training speed is high. The algorithm is able to deal with the large scale circuit partitioning, and has total optimization effect. The algorithm is programmed with Visual C + + language, and experimental result shows that it is an effective method.