openssl源碼
The OpenSSL Project is a collaborative effort to develop a robust, commercial-grade, full-featured, and Open Source toolkit implementing the Secure Sockets Layer (SSL v2/v3) and Transport Layer Security (TLS) protocols as well as a full-strength general purpose cryptography library. The project is managed by a worldwide community of volunteers that use the Internet to communicate, plan, and develop the OpenSSL toolkit and its related documentation.
We introduce a sub-cell WENO reconstruction method to evaluate spatial derivatives in the high-order ADER scheme. The basic idea in our reconstruction is to use only r stencils to reconstruct the point-wise values of solutions and spatial derivatives for the 2r-1 th order
ADER scheme in one dimension, while in two dimensions, the dimension-by-dimension sub-cell reconstruction approach for spatial derivatives is employed. Compared with the original ADER scheme of Toro and Titarev (2002) [2] that uses the direct derivatives of reconstructed polynomials for solutions to evaluate spatial derivatives, our method not only reduces greatly the computational costs of the ADER scheme on a given mesh,
but also avoids possible numerical oscillations near discontinuities, as demonstrated by a number of one- and two-dimensional numerical tests. All these tests show that the 5th-order ADER scheme based on our sub-cell reconstruction method achieves the desired accuracy, and is essentially non-oscillatory and computationally cheaper for problems with discontinuities.
Connecting 32-bit controlled applications
in the industrial, commercial and consumer
markets is fast becoming a necessity rather
than an option. Many new applications, such
as remote data collection, home automation
and networked appliances, require secure,
high-performance connectivity at an
economical price. Freescale Semiconductor
gives design engineers the flexibility to choose
the right 32-bit microcontroller from a broad
portfolio of ColdFire? embedded controllers.
Reconstruction- and example-based super-resolution
(SR) methods are promising for restoring a high-resolution
(HR) image from low-resolution (LR) image(s). Under large
magnification, reconstruction-based methods usually fail
to hallucinate visual details while example-based methods
sometimes introduce unexpected details. Given a generic
LR image, to reconstruct a photo-realistic SR image and
to suppress artifacts in the reconstructed SR image, we
introduce a multi-scale dictionary to a novel SR method
that simultaneously integrates local and non-local priors.
The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local
area. The non-local prior enriches visual details by taking
a weighted average of a large neighborhood as an estimate
of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate
that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
Accurate pose estimation plays an important role in solution of simultaneous localization and mapping (SLAM) problem, required for many robotic applications. This paper presents a new approach called R-SLAM, primarily to overcome systematic and non-systematic odometry errors which are generally caused by uneven floors, unexpected objects on the floor or wheel-slippage due to skidding or fast turns.The hybrid approach presented here combines the strengths of feature based and grid based methods to produce globally consistent high resolution maps within various types of environments.
The understanding of electrical system design has become increas-
ingly important, not only to the electrical designer, but to safety, plant
and project engineers as well. With the advent of high energy costs, plant
and project engineers have needed to become more aware of electrical
systems. Both safety and energy efficiency will be covered in this text
along with practical application problems for industrial and commercial
electrical design.