Applied Mechanics and Materials Vols. 121-126

Abstract: Based on the possible leak place on the tank of organic solvent, author had developed three equipments of stopping tank from leaking on the pipeline wall, breaking off between the pipelines or pipeline joint breaking off from tank wholly，which can be stopped tank from leaking as quickly, reliably, conveniently as possible. After simulation test of pressure, three equipments of stopping tank from leaking performed very well, and subjected to atmospheric pressure tank of organic solvent, as a result, these equipments can be used to deal with leaking for solvent tank at emergency case.

Abstract: Ontology learning is a series method and technology of semi-automatic ontology construction, which uses various data sources to create or expand in-built ontology by semi-automatic method to build a new ontology. Existing ontology construction methods are to collect a large number of conceptual terms based on a large number of field text and background corpus, and then to select field concepts to construct a body. The proposed Cluster-Merge algorithm is to use k-means clustering algorithm in the field document at first, then according to document clustering results to construct body by themself, at last accoring to the ontology similarity for ontology merging to get final output ontology. The experiment may prove that Cluster-Merge algorithm can improve the body resulting recall and precision.

Abstract: Differentiated services architecture is receiving wide attention as a framework for providing different levels of service in the industrial control networks.Traditional networks are designed with no traffic differentiation; all traffic mission-critical and non-mission-critical is treated equally.In indutrial networks, it becomes important to make sure that mission-critical applications do not suffer. QoS (Quality-of-Service) solutions, available in common network devices, try to provide traffic differentiation and predictable performance for mission critical applications.In this paper we propose a novel Quality of Service provisioning approach, appropriate for trusted industrial networks. This method, based on the real-time system reconfiguration, exploits the system monitoring information, along with quality parameters from the SLAs and experience from previous executions.The presented QoS provisioning process proposes a set of actions based on application specific policies, which are closely coupled with particular SLAs in order to provide the required QoS level for the application. Furthermore, We study applies the methodology using OPNET simulation products to compare and contrast the performance of a new application in an environment with and without IP QoS solutions.

Abstract: The Differential Quadrature Method（abbreviated as DQM）is easy to be implemented by computers to solve many problems in engineering mechanics. In the field of pipe vibration methods are mainly finite element method , finite difference calculus and so on. In the formation of coefficient matrix these methods need to calculate a large number of numerical integration , resulting in low efficiency, while we can use matlab to program, taking the advantage of easy programming of DQM, after establishing mathematical model of the pipe conveying fluid .The program designed in this paper can be a very good solution to pipe nature frequency.After obtaining the nature frequency, we have analyzed the relationship between pipe length and nature frequency and have found out the critical value of the pipe length. The method can also be applied to engineering filed related .

Abstract: A new method about the air temperature reconstruction based on the block correction interpolation was put forward. Its theoretical basis is the principles of thermodynamics relations and ultrasonic temperature measurement. The frequency of ultrasonic generator is 40 KHz. Because of the one-to-one relationship between gas temperature and gas velocity, the gas temperature field can be reconstructed through the rebuilding of velocity field. As the distance between the generator and receiver is known, so the average speed on the path can be obtained by detecting the ultrasonic transit-time. After obtaining the average speed of many paths in the field, the correction of the measured data can be done by using the block correction interpolation technology. And through the mathematical analysis software, the reconstruction of the measured field was given.

Abstract: There are many factors that effect the quality of the heat transfer printing products. The CRT in prepress is the most important factor. In this paper, the color ladder segmentation is spaced at 5. The color of the CRT is tested with X-RITE color monitor optiomizer. According to the data and the curve, the function model of color characteristic features is set up. We made the common test plates which is to verify the error of the function model. As a result, The range of color error in the heat transferring printing is reduced. The color management profile is put forward, the quality of transferring printing is improved. A reference is provided for the color management in the heat transfer printing.

Abstract: With the rapid social development, information technology has become a kind of background information society culture. Modern information technology in mathematics teaching, widely used, can be changed for fun, experience dull knowledge acquisition, Change to move, static highlight the importance and break through the difficulty, Change single for multivariate, increase the knowledge the density, Feedback timely, facilitate teachers adjusting teaching behavior. This paper mainly discusses PowerPoint and Matlab7 software in the teaching of mathematics applying.

Abstract: The aim of this research is to propose and compare the in-process detection systems of the cutting states of the continuous chip, the broken chip and the chatter for the carbon steel in CNC turning process by utilizing the sensor fusion, which are the force sensor, the sound sensor, the accelerometer sensor and the acoustic emission sensor. The new six parameters proposed for the inputs of the neural network systems, which are the enegy spectral densities of three dynamic cutting forces, sound signal, accelation signal, and the standard deviation of acoustic emission signal. All signals of parameters have been integrated via the different neural network systems by using the pattern recognition and the percertron technique to detect the cutting states, which are. Among the cutting states of chip formation and chatter, the broken chip is required for the reliable and stable cutting system. The experimentally obtained results showed that the in-process detection system using the neural network with the pattern recognition technique can be effectively used to detect the cutting states with the higher accuracy and reliability more than the one with the perceptron technique.

Abstract: The entity semantic representation model (ESRM), which considers an entity as a set of attributes and corresponding values, is very useful for various applications. This paper proposes an approach for extracting new attributes and values from related unstructured documents. In our approach, the extraction process is formulated as the sequence labeling task. According to the predefined entity structure, the labeled data for training annotator are achieved automatically. The CRFs based annotator is trained to annotate the sentence which maybe contains the new attributes and values. And then, in terms of a decision process with scoring algorithm, new attributes and values are identified and fill into the predefined entity representation model. The experiments show that the proposed method improves the performance of extraction with a higher accuracy.

Abstract: The automatic classification of erythrocyte is critical to clinic blood-related disease treatment in Medical Image Computer Aided Diagnosing(MICAD). After 3D height field recovered from the varied shading, the depth map of each point on the surfaces is applied to calculate Gaussian curvature and mean curvature, which are used to produce surface type label image. Accordingly the surface is segmented into different parts through multi-scale bivariate polynomials function fitting. The count of different surface types is used to design a classifier for training and classifing the red blood cell by means of support vector machine and particle swarm optimization. The experimental result shows that this approach is easily to implement and promising.