What you always wanted to know about networking but were afraid to ask! * How networks and the Internet work * How to build coherent, cost-effective network infrastructures * How to design networks for maximum reliability and availability * What you need to know about data center and application networking * How to secure networks against today?s threats and attacks * How to take advantage of the latest mobility technologies * How virtualizing networks can help businesses leverage their network investments even further * How to combine messaging, calendaring, telephony, audio, video, and web conferencing into a unified communications architecture
標簽： networking networks always afraid
上傳時間： 2013-12-25
上傳用戶：fandeshun
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.
標簽： 高精度格式
上傳時間： 2016-01-13
上傳用戶：ccsdcczd
32feet.NET is a shared-source project to make personal area networking technologies such as Bluetooth, Infrared (IrDA) and more, easily accessible from .NET code. Supports desktop, mobile or embedded systems. 32feet.NET is free for commercial or non-commercial use. If you use the binaries you can just use the library as-is, if you make modifications to the source you need to include the 32feet.NET License.txt document and ensure the file headers are not modified/removed. The project currently consists of the following libraries:- Bluetooth IrDA Object Exchange Bluetooth support requires a device with either the Microsoft, Widcomm, BlueSoleil, or Stonestreet One Bluetopia Bluetooth stack. Requires .NET Compact Framework v3.5 or above and Windows CE.NET 4.2 or above, or .NET Framework v3.5 for desktop Windows XP, Vista, 7 and 8. A subset of functionality is available for Windows Phone 8 and Windows Embedded Handheld 8 in the InTheHand.Phone.Bluetooth.dll library.
上傳時間： 2016-07-06
上傳用戶：magister2016
Dynasty 350, 700 208/575 Volt Models W/Auto-Line Maxstar 350, 700 File: TIG (GTAW) Including Optional Cart And Cooler CE And Non-CE Models
上傳時間： 2017-03-11
上傳用戶：zosoong
ESP8266 AT指令手冊示例，物聯網使用廣泛，參考此文檔可進行快速開發。
上傳時間： 2018-06-05
上傳用戶：dear920
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.
標簽： Super-resolution Multi-scale Dictionary Single Image for
上傳時間： 2019-03-28
上傳用戶：fullout
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.
標簽： localization environments challenging Resilient mapping R-SLAM and in
上傳時間： 2019-09-15
上傳用戶：zhudx2007
atlab code for Non-negative Factorization of the Occurrence Tensor from Financial Contracts https://arxiv.org/pdf/1612.03350.pdf,
標簽： tensor_n
上傳時間： 2020-01-01
上傳用戶：dawn1818
atlab code for Non-negative Factorization of the Occurrence Tensor from Financial Contracts https://arxiv.org/pdf/1612.03350.pdf, which
標簽： tensor
上傳時間： 2020-01-01
上傳用戶：dawn1818
The recent developments in full duplex (FD) commu- nication promise doubling the capacity of cellular networks using self interference cancellation (SIC) techniques. FD small cells with device-to-device (D2D) communication links could achieve the expected capacity of the future cellular networks (5G). In this work, we consider joint scheduling and dynamic power algorithm (DPA) for a single cell FD small cell network with D2D links (D2DLs). We formulate the optimal user selection and power control as a non-linear programming (NLP) optimization problem to get the optimal user scheduling and transmission power in a given TTI. Our numerical results show that using DPA gives better overall throughput performance than full power transmission algorithm (FPA). Also, simultaneous transmissions (combination of uplink (UL), downlink (DL), and D2D occur 80% of the time thereby increasing the spectral efficiency and network capacity
標簽： Full-Duplex Cells Small
上傳時間： 2020-05-27
上傳用戶：shancjb
