Applied Mechanics and Materials Vols. 644-650

Abstract: . For the purpose of showing the importance of certain items in the negative sequences and make negative sequences have more practicality, this paper presents a method for mining weighted negative sequence pattern. Set the weight value to calculate the weighted support and prune the weighted negative sequences which don’t meet conditions. We use IRIS data set which belongs to UCI data sets to verify the new algorithm. Comparing with Neg-GSP algorithm, showing the benefit of the weighted concept.

Abstract: With the deepening of the negative association rules mining technology research, many key problems have been solved, but the solution of these problems are all on a single predicate in the transaction database. However, the data in the database often involves multiple predicates. This paper focuses on solving multi-dimensional support and confidence, negative association rules mining algorithm design problems. The experiment proves that the algorithm is correct and efficiency.

Abstract: For the aim of establishing visual growth model of gramineous adventitious root system, using computer to simulate the growth process of gramineous adventitious root system, we analyze the experiment data, refer to the growth law of adventitious root system, and then establish the growth model of gramineous adventitious root system based on three-dimension DLA, and test the model on computer, the result confirmed that the model is right and suitable.

Abstract: To establish digital growth model of Kentucky bluegrass repent stem, and study growth process of Kentucky bluegrass repent stem in coordinate system. After observing and studying growth data we found that there is a quick-slow-quick growth rhythm in the growing process, and the growth model of length is established according to the growth rhythm. Then using RMSE statistical methods to verify the model, the results indicates that the growth model is in line with grasses repent stem natural growth rhythm and has a certain degree of reliability and accuracy, it can describe the growth of repent stem exactly.

Abstract: The nonlinear motion state of object seriously affects the object tracking characteristics in complex motion scene. In this paper, we propose an interacting multiple model LK (IMM-LK) tracking algorithm to enhance the performance of tracking nonlinear moving object. LK tracking approach is based on the localized gradient obtaining stable optical-flow feature, based on LK, we build several motion models of the tracked object that interact with each other in the tracking process. The method extracts different model's object features, estimates the object state and calculates the matching rate of each model with the current motion model using theory of minimum variance. Combining with the optimal transfer matrix then we can track the nonlinear moving object. The proposed IMM-LK algorithm performs favorably against conventional LK tracking on the performance of tracking nonlinear moving object.

Abstract: Clustering, rough sets and decision tree theory were applied to the evaluation of soil fertility levels ,and provided new ideas and methods among the spatial data mining and knowledge discovery. In the experiment, the rough sets - decision tree evaluation model establish by 1400 study samples, the accuracy rate is 92% of the test. The results show :model has good generalization ability; the use of rough sets attribute reduction, can remove redundant attributes, can reduce the size of decision tree decision-making model, reduce the decision-making rules and improving the decision-making accuracy, using the combination of rough set and decision tree decision-making method to infer the level of a large number of unknown samples.

Abstract: For the problems of the human geometric modeling by using software, such as more complex, poor fidelity and controllability, the optimized mathematical model for human simulation movement is designed at first. A three-dimensional human motion system coordinate is established to construct the simplified virtual human geometric model. Using the knowledge of computer graphics, and Denavic-Hartenberg method, construct a space joint coordinate system of virtual hierarchal human movement chain. 3DS MAX is used in realistic geometric modeling to achieve the three-dimensional motion simulation analysis in basketball motion. The results show that the model is realistic, the optimized geometric model in software is easy to control, and the overall effect is good. It greatly enhances the realism and action effects of the three-dimensional motion simulation, and achieves a good virtual basketball motion.

Abstract: Three-dimensional modeling is a key technology in many fields of research and application. In recent years, the application of three-dimensional architectural design visualization is widely used worldwide, which makes significant progress in terms of data models, visualization, 3D topological relations research. Due to the complexity of the own spatial structure of architectural design, by using virtual reality technology and combination of the surface characteristics of the entity modeling and structural modeling, the idea and implementation process of architectural design three-dimensional virtual model algorithm are described in detail. This article discusses the whole process of integrated CAD system's basic design, architecture and implementation techniques. This system has features of high integration, strong applicability, high reliability, able to complete the whole process of architectural design work, with a wide range of application prospects.

Abstract: In large construction projects, a single construction features data cannot be found to use as constraint. Traditional data classification methods use multi-feature constraints. Using multiple features for construction data uniqueness expressed has excessive features to express so that affect the efficiency of the classification. This paper proposes a construction project based on discrete transform big data classification. By enhancing the features of the construction project data, use the enhanced identification as the basis data classification, so that the scope of construction data classification can be obtained. Experimental results show that use the improved algorithm to perform big data classification on massive construction projects, it can effectively improve the accuracy of classification.

Abstract: Resulting in an optimal grasping pose of satisfying task requirements is a critical problem for hands manipulation. Based on the problem, taxonomy of grasping poses was created. This paper presents key-based search method that can obtain all hand manipulation poses matching the grasped object. However, these grasping pose must be ranked by combining with task requirements and object geometry. In this way, optimal grasping pose can be achieved. The effectiveness of the method was demonstrated by using grasping pose taxonomy comparisons from motion capture example database.