Three dimensional virtual crack closure-integral method (VCCM) with skewed and non-symmetric mesh arrangement at the crack front

In this paper, an extension of virtual crack closure-integral method (VCCM) for three dimensional linear fracture mechanics analysis using hexahedron finite elements is presented. In conventional three dimensional VCCM, there are some inherent requirements on the finite element model. They are (i) the faces of finite elements across the crack front have the same areas and (ii) they must be arranged symmetrically across the crack front. In present study, we developed a three dimensional VCCM without such requirements by considering work required to open one element face area whose shape is arbitrary. Though we assume the use of an ordinary 20 node serendipity element, present approach can be applied to other types of hexahedron elements.     

Complete Mining of Frequent Patterns from Graphs: Mining Graph Data

Basket Analysis, which is a standard method for data mining, derives frequent itemsets from database. However, its mining ability is limited to transaction data consisting of items. In reality, there are many applications where data are described in a more structural way, e.g. chemical compounds and Web browsing history. There are a few approaches that can discover characteristic patterns from graph-structured data in the field of machine learning. However, almost all of them are not suitable for such applications that require a complete search for all frequent subgraph patterns in the data. In this paper, we propose a novel principle and its algorithm that derive the characteristic patterns which frequently appear in graph-structured data. Our algorithm can derive all frequent induced subgraphs from both directed and undirected graph structured data having loops (including self-loops) with labeled or unlabeled nodes and links. Its performance is evaluated through the applications to Web browsing pattern analysis and chemical carcinogenesis analysis.     

A Knowledge Discovery System with Support for Model Selection and Visualization

The process of knowledge discovery in databases consists of several steps that are iterative and interactive. In each application, to go through this process the user has to exploit different algorithms and their settings that usually yield multiple models. Model selection, that is, the selection of appropriate models or algorithms to achieve such models, requires meta-knowledge of algorithm/model and model performance metrics. Therefore, model selection is usually a difficult task for the user. We believe that simplifying the process of model selection for the user is crucial to the success of real-life knowledge discovery activities. As opposed to most related work that aims to automate model selection, in our view model selection is a semiautomatic process, requiring an effective collaboration between the user and the discovery system. For such a collaboration, our solution is to give the user the ability to try various alternatives and to compare competing models quantitatively by performance metrics, and qualitatively by effective visualization. This paper presents our research on model selection and visualization in the development of a knowledge discovery system called D2MS. The paper addresses the motivation of model selection in knowledge discovery and related work, gives an overview of D2MS, and describes its solution to model selection and visualization. It then presents the usefulness of D2MS model selection in two case studies of discovering medical knowledge in hospital data—on meningitis and stomach cancer—using three data mining methods of decision trees, conceptual clustering, and rule induction.     

双束强辐照对氧化物弥散强化铁素体型合金强化相稳定性影响

采用双束复合辐照装置,研究了He存在条件下,强辐照对长期时效后的ODS合金中强化相(Y2O3)的稳定性和辐照损伤特征的影响。实验结果表明:双束强辐照下,ODS合金中强化相不稳定,发生聚集长大并造成附近基体中Ti、Y浓度增高,导致空洞尺寸和空洞肿胀增加,并对这一结果从理论上进行解释。     

Full Band Monte Carlo Study for Two-Dimensional Hole Transport in Strained Si p-MOSFETs

Transport properties of the two-dimensional hole gas in inversion layer of strained Si/SiGe p-MOSFETs are investigated using the full-band Monte Carlo simulator based on the nonlocal pseudopotential calculation. The hole mobility is significantly enhanced by the strain in the case of Ge content of ≥20%. Moreover, we also present the high-field transport characteristics of 2D holes. In contrast to the low-field mobility, the hole saturation velocity does not significantly enhanced by the strain.     

Parametric Feature Detection

Most visual features are parametric in nature, including, edges, lines, corners, and junctions. We propose an algorithm to automatically construct detectors for arbitrary parametric features. To maximize robustness we use realistic multi-parameter feature models and incorporate optical and sensing effects. Each feature is represented as a densely sampled parametric manifold in a low dimensional subspace of a Hilbert space. During detection, the vector of intensity values in a window about each pixel in the image is projected into the subspace. If the projection lies sufficiently close to the feature manifold, the feature is detected and the location of the closest manifold point yields the feature parameters. The concepts of parameter reduction by normalization, dimension reduction, pattern rejection, and heuristic search are all employed to achieve the required efficiency. Detectors have been constructed for five features, namely, step edge (five parameters), roof edge (five parameters), line (six parameters), corner (five parameters), and circular disc (six parameters). The results of detailed experiments are presented which demonstrate the robustness of feature detection and the accuracy of parameter estimation.     

Image retrieval using efficient local-area matching

We present an efficient and accurate method for retrieving images based on color similarity with a given query image or histogram. The method matches the query against parts of the image using histogram intersection. Efficient searching for the best matching subimage is done by pruning the set of subimages using upper bound estimates. The method is fast, has high precision and recall and also allows queries based on the positions of one or more objects in the database image. Experimental results showing the efficiency of the proposed search method, and high precision and recall of retrieval are presented. Received: 20 January 1997 / Accepted: 5 January 1998     

Human-like natural behavior generation based on involuntary motions for humanoid robots

Human behaviors consist of both voluntary and involuntary motions. Almost all behaviors of task-oriented robots, however, consist solely of voluntary motions. Involuntary motions are important for generating natural motions like those of humans. Thus, we propose a natural behavior generation method for humanoid robots that is a hybrid generation between voluntary and involuntary motions. The key idea of our method is to control robots with a hybrid controller that combines the functions of a communication behavior controller and body balancing controllers. We also develop a wheeled inverted pendulum type of humanoid robot, named “Robovie-III”, in order to generate involuntary motions like oscillation. By applying our method to this robot and conducting preliminary experiments, we verify its validity. Experimental results show that the robot generates both voluntary and involuntary motions.     

Thermodynamic evaluation of the phase equilibria and glass-forming ability of the Fe–Si–B system

A thermodynamic study has been carried out on the Fe–Si–B ternary system, which is important in the development of transformer core materials and Ni-based filler metals. A regular solution approximation based on the sublattice model was adopted to describe the Gibbs energy for the individual phases in the binary and ternary systems. Thermodynamic parameters for each phase were evaluated by combining the experimental results from differential scanning calorimetry with literature data. The evaluated parameters enabled us to obtain reproducible calculations of the isothermal and vertical section diagrams. Furthermore, the glass-forming ability of this ternary alloy was evaluated by introducing thermodynamic quantities obtained from the phase diagram calculations into Davies–Uhlmann kinetic formulations. In this evaluation, the time–temperature-transformation (TTT) curves were obtained, which are a measure of the time required to transform to the minimum detectable mass of crystal as a function of temperature. The critical cooling rates calculated on the basis of the TTT curves enabled us to evaluate the glass-forming ability of this ternary alloy. The results show good agreement with the experimental data in the compositional amorphization range.     

Preparation and Property of Acrylic Acid Rare Earth Complex and Its Hydrosilylation

Acrylic acid rare earth complex was prepared. Its chemical composition was determined by chemical and elemental analysis, and its structure as well as properties was characterized using IR, Fluorescence and UV spectrum, and its solubility was also investigated. Meanwhile a kind of elastic functional polymer with rare earth units in the side chains was produced. It is confirmed by IR spectrum that the Si-H bonds really react with acrylic acid rare earth.