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Aiming at the disadvantages of edge detail loss and false edges in conventional Canny algorithm, this paper proposes an optimized Canny edge detection algorithm for edge detection of core image by combining self-adaption smooth filtering and self-adaptive threshold value. The algorithm, which retains the advantages of high signal to noise ra- tio, accurate positioning, single edge single response and etc in conventional Canny algorithm, has stronger de-noising ca- pability and better edge-detection effect. The experiment results indicate that the improved algorithm can perform self- adaptive edge-detection on the core image and create a clear coherent detected edge of image which can display the edge feature better.

The technologies on digital characterization of reservoir microscopic pore structure are very important during the process of oilfield development. Firstly, the definition of microscopic pore structure is elaborated. Secondly, six technologies on digital characterization of microscopic pore structure that are adopted by the scholars at home and abroad are concluded. Lastly, the novel technologies on digital characterization of microscopic pore structure is prospected. And the spatial distribution of microscopic pore structure is so complicated that other advanced technologies should be adopted during the process of research.

Designing an interactive virtual navigation system needs consideration of compositive features such as modelling, movement control and object selection. Those features are key to meet end user requirements. Current virtual navigation systems are not beneficial to popularize in the case of development environment, methods and technologies. That is because such systems have limited application area and costs. Proprietary development environment result in limited selection in system components while new development technologies are unlikely to be accepted as staggering capital costs. In this paper, we propose a feasible scheme and development environment to design an interactive virtual navigation system for creating and utilizing digital campus models. Furthermore, the scheme also captures user interactivities via mouse and keyboard for further controls and selections in virtual campus. By adequate consideration of user preferences and personalities, this system benefits in portability, flexibility; has a high degree of standardization and lower cost.

In quantitative geological modeling with an artificial neural network approach, time information can be considered as input variable to better describe dynamic evolution patterns of reservoir parameters. Such approach requires independent programming to implements 4D reservoir modeling systems and thus introduces a new research area with great development potential. This paper is dedicated to implement a 4D reservoir modeling system by neural network. It explains the development process with detailed activities vary from determine the execution process and organization structure at one extreme to determine the sequence diagram at the other extreme. Between two extremes besides analyzing essential object class functions, UML modeling language has been used to define the use case model, static structure model and dynamic behavior model. It has practical meaning for further development of eastern oil field in China.

This paper discusses the concept and the latest development of Component Object Technology at first. Then it studies the Component Object Technology for developing Material and Energy Statistical Analysis System(MESAS) with support from software framework in detail. This approach may benefit on software development circles, reduce development costs, and strengthen the transplantation and maintenance as well as achieves software reusability.

The knowledge of the flow behavior of metals during hot deformation is of great importance in determining the optimum forming conditions. In this paper, the flow stress of 00Cr17Ni14Mo2 (ANSI 316L) austenitic stainless steel in elevated temperature is measured with compression deformation tests. The temperatures at which the steel is compressed are 800-1100°C with strain rates of 0.01-1s-1. A mathematical regression model is proposed to describe the flow stress and the validation of the model is conducted also. The proposed model can be used to predict the corresponding flow stress-strain response of 00Cr17Ni14Mo2 stainless steel in elevated temperature for the numerical simulation and design of forming process.

The /spl beta/ chip is a 32 b floating-point processor with 64-matrix parallel computing units using CMOS 0.35 /spl mu/m technology. The /spl beta/ chip is intended for use as a DSP coprocessor in a PC environment or in other computational-intensive applications. Such applications include digital filter (FIR, IIR), matrix multiplication, nonlinear polynomial calculations, DCT, DFT, video compression, and 3D graphics. In each computing unit (CU), all calculations are in the logarithm domain except some special instructions. The absolute error using the logarithm operation is less than 1 LSB in IEEE 32 b floating-point format. There is a 128/spl times/32 b memory (cache) in each CU. The total memory (cache) is 32 kB on the chip. There are three I/O buses on the chip; input data bus, output data bus and host control bus. The average sustained performance can reach 10 GFLOPS.

A speech signal is sampled to form a sequence of speech data and segmented into segments. The envelope of each segment is detected to form an envelope segment. Each datum of the segment is divided by each datum of the envelope segment to form a de-envelope segment which is transformed into spectral components. Dominant frequencies are determined for the spectral components with greatest magnitudes. Envelope coefficients are generated by fitting a polynomial function to the segment. Phase parameters are generated representing a phase of each of the dominant spectral components. The dominant frequencies, the envelope coefficients and the phase parameters are generated as compressed speech data for each voiced segment. For each unvoiced segment, a carrier frequency, an amplitude and at least one sideband frequency of an amplitude modulation component are generated as the compressed speech data.

A speech signal is sampled to form a sequence of speech data. The sequence of speech data is segmented into overlapping segments. Speech coefficients are generated by fitting each segment to a nonlinear predictive coding equation. The nonlinear predictive coding equation includes a linear predictive coding equation with linear terms, and additionally includes at least one cross term that is proportional to a product of two or more of the linear terms. If the segment is voiced, a sinusoidal term is included in the nonlinear predictive coding equation and sinusoidal parameters are generated. Otherwise, a noise term is included in the nonlinear predictive coding equation. The speech coefficients, a voiced bit, and, if the segment is voiced, the sinusoidal parameters are included as compressed speech data.