Customized product development is facing the challenges of maintaining mass producibility and exploring customer perception on target products. The objective of this study was the application of ergonomic evaluation method for customized furniture design in virtual environment. At the first, the system architecture was built, and gordian techniques of the system were analyzed. Then a representative case was studied. In this case study, 3D scanning system and Motion Capture were used to get information of given user/users, REBA and Lifting Index (LI) of revised NIOSH lifting equation were selected as ergonomics evaluation methods. The prototype’s usability was verified by the result. This method can also be used to solve other relative problems.
The ability to understand human emotions is desirable for the computer in many applications recently. Recording and recognizing physiological signals of emotion has become an increasingly important field of research in affective computing and human computer interaction. For the problem of feature redundancy of physiological signals-based emotion recognition and low efficiency of traditional feature reduction algorithms on great sample data, this paper proposed an improved adaptive genetic algorithm (IAGA) to solve the problem of emotion feature selection, and then presented a weighted kNN classifier (wkNN) to classify features by making full use of emotion sample information. We demonstrated a case study of emotion recognition application and verified the algorithm's validity by the analysis of experimental simulation data and the comparison of several recognition methods.
In this paper, for the problems of low convergence rate and getting trapped in local optima easily, the average path similarity (APS) was proposed to present the optimization maturity by analyzing the relationship between parameters of local pheromone updating and global pheromone updating, as well as the optimizing capacity and convergence rate. Furthermore, the coefficients of pheromone updating adaptively were adjusted to improve the convergence rate and prevent the algorithm from getting stuck in local optima. The adaptive ACS has been applied to optimize several benchmark TSP instances. The solution quality and convergence rate of the algorithm were compared comprehensively with conventional ACS to verify the validity and the effectiveness.
For the problem of feature redundancy of emotion recognition based on multi-channel physiological signals and low efficiency of traditional feature reduction algorithms on great sample data, a new chaotic particle swarm optimization algorithm (TM-CPSO) was proposed to solve the problem of emotion feature selection by combining tent map based chaos search mechanism and improved particle swarm optimization algorithm. The problem of falling into local minimum can be avoided by mapping the search process to the recursive procedure of the chaotic orbit. The recognition rate and efficiency was increased and the algorithm's validity was verified through the analysis of experimental simulation data and the comparison of several recognition methods.
The paper introduced a computer-aided industrial design system: Forklift Truck’s Multi Plan Optimizaion System, and demonstrated the modules’ function and techniques with examples. Considering the requirements for efficiency and precision in the forklift styling, the author developed the forklift optimizing software for its styling, which includes parameter optimization, color optimization and part combination three modules. The parameter optimization module can vary the user defined parameters of the forklift models and generate new models. Color optimization module can group the model surfaces and render the groups with different color. New color plans are generated through random changing of the colors in each group. The parts combination module divides forklift into several parts and build lib for each part. The module can pick parts from the lib and assemble them into a whole forklift and demonstrate them. The thesis developed a proto system on the Solidworks platform with VBA programming tools. Interactive genetic algorithms are applied to realize the three module’s function.
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