MySQL claims to be the world s most popular open source database, and with good
reason. It is free, runs on a wide variety of platforms, is relatively simple, easy to
configure and performs well even under significant load. By comparison to some other
popular database management systems, configuring it is quite simple, but there are still a
sufficiently wide variety of security-relevant configuration issues to make securing it a
challenge.
Ordinal Representation for Biometric Patterns.
Very helpful in Large number of object to be compared. its sort of ranking based comparison.not quantitative
CRFsuite is a very fast implmentation of the Conditional Random Fields (CRF) algorithm. It handles tens of thousands sentences in merely one second.
In comparison to CRF++, CRFSuite yields substantially better efficiency performance
MATSNL is a package of MATLAB M-files for computing wireless sensor node lifetime/power budget and solving optimal node architecture choice problems. It is intended as an analysis and simulation tool for researchers and educators that are easy to use and modify. MATSNL is designed to give the rough power/ lifetime predictions based on node and application specifications while giving useful insight on platform design for the large node lifetime by providing side-by-side comparison across various platforms. The MATSNL code and manual can be found at the bottom of this page. A related list of publications describing the models used in MATSNL is posted on the ENALAB part of the 2 project at http://www.eng.yale.edu/enalab/aspire.htm
MATSNL is a package of MATLAB M-files for computing wireless sensor node
lifetime/power budget and solving optimal node architecture choice problems. It is intended
as an analysis and simulation tool for researchers and educators that are easy to use and
modify. MATSNL is designed to give the rough power/ lifetime predictions based on node
and application specifications while giving useful insight on platform design for the large
node lifetime by providing side-by-side comparison across various platforms.
本書是英文版，但內(nèi)容非常不錯(cuò)，本書目錄如下：
Table of Contents
SIP—Understanding the Session Initiation Protocol, Second Edition
Foreword to the First Edition
Preface to - the Second Edition
Preface to - the First Edition
Chapter 1 - SIP and the Internet
Chapter 2 - Introduction to SIP
Chapter 3 - SIP Clients and Servers
Chapter 4 - SIP Request Messages
Chapter 5 - SIP Response Messages
Chapter 6 - SIP Header Fields
Chapter 7 - Related Protocols
Chapter 8 - comparison to H.323
Chapter 9 - Wireless and 3GPP
Chapter 10 - Call Flow Examples
Chapter 11 - Future Directions
Appendix A - Changes in the SIP Specification from RFC 2543 to RFC 3261
Collection of key-value pairs.
TDictionary represents a generic collection of key-value pairs.
This class provides a mapping from a collection of keys to a collection of values. When you create a TDictionary object, you can specify various combinations of initial capacity, equality operation, and initial content.
You can add a key that is associated with a corresponding value with the Add or AddOrSetValue methods. You can remove entries with Remove or Clear, which removes all key-value pairs. Adding or removing a key-value pair and looking up a key are efficient, close to O(1), because keys are hashed. A key must not be nil (though a value may be nil) and there must be an equality comparison operation for keys.
You can test for the presence or keys and values with the TryGetValue, ContainsKey and ContainsValue methods.
The Items property lists all Count dictionary entries. You can also set and get values by indexing the Items property. Setting the value this way overwrites any existing value.
The class TObjectDictionary inherits from TDictionary and provides an automatic mechanism for freeing objects removed from dictionary entries.
Before delving into the details of orthogonal frequency division multiplexing (OFDM), relevant
background material must be presented first. The purpose of this chapter is to provide the necessary
building blocks for the development of OFDM principles. Included in this chapter are reviews of stochastic
and random process, discrete-time signals and systems, and the Discrete Fourier Transform (DFT). Tooled
with the necessary mathematical foundation, we proceed with an overview of digital communication
systems and OFDM communication systems. We conclude the chapter with summaries of the OFDM
wireless LAN standards currently in existence and a high-level comparison of single carrier systems versus
OFDM.
Visible light communications (VLC) is the name given to an optical wireless
communication system that carries information by modulating light in the visible spectrum
(400–700 nm) that is principally used for illumination [1–3]. The communications signal
is encoded on top of the illumination light. Interest in VLC has grown rapidly with the
growth of high power light emitting diodes (LEDs) in the visible spectrum. The
motivation to use the illumination light for communication is to save energy by exploiting
the illumination to carry information and, at the same time, to use technology that is
“green” in comparison to radio frequency (RF) technology, while using the existing
infrastructure of the lighting system.
Current field forecast verification measures are inadequate, primarily because they compress the comparison
between two complex spatial field processes into one number. Discrete wavelet transforms (DWTs) applied to
analysis and contemporaneous forecast fields prove to be an insightful approach to verification problems. DWTs
allow both filtering and compact physically interpretable partitioning of fields. These techniques are used to
reduce or eliminate noise in the verification process and develop multivariate measures of field forecasting
performance that are shown to improve upon existing verification procedures.
