這是sun公司的程序員考試書籍（英文版的pdf）
還有模擬考試安裝盤，和視頻！我將稍后發布！
READ THIS AGREEMENT CAREFULLY. IF YOU AGREE TO ALL THE TERMS AND CONDITIONS SET FORTH BELOW AND ARE WILLING TO BE LEGALLY BOUND BY THEM, PRESS THE I AGREE BUTTON TO CONTINUE WITH THE SETUP. IF YOU DO NOT AGREE TO SUCH TERMS AND CONDITIONS, PRESS THE I DON T AGREE BUTTON TO ABORT THE INSTALLATION.
Beginning with an introduction to 802.11b in general, 802.11 Security gives you a broad basis in theory and practice of wireless security, dispelling some of the myths along the way. In doing so, they provide you with the technical grounding required to think about how the rest of the book applies to your specific needs and situations. If you are a network, security, or systems engineer, or anyone interested in deploying 802.11b--based systems, you ll want this book beside you every step of the way.
The JICQ is the bureau area which JAVA writes according to "Customer s Machine/Server"(C/S) mode message solid hour correspond by letter tool system, the system adopted the SQL Server2000 of Microsoft company as a backstage database, the system passes a JDBC interview database. The system is divided into the server procedure and customer s procedure two parts, server and customer adoption "Transmission Control Protocol"(TCP), connect a word (Socket) conjunction through a set, the adoption "User Datagram Protocol "(UDP) of the customer s, pass a data report a set to connect a word (DatagramSocket) establishment a conjunction. The system has customer registration, customer to register, increase good friend, delete good friend and send out and receive news etc. function.
a non-sharing smart pointer class that can be used with STL containers such as std::map, vector, list, set, and deque. The smart pointer has an assignment operator and greater than operator that call the target object s operator.
亞定方程組求解：If serial correlation is found, you may have misspecified your model and
should return to your theory for a better representation of the data generating
process. This possibility is quite likely and should be taken seriously.
This program demonstrates some function approximation capabilities of a Radial Basis Function Network.
The user supplies a set of training points which represent some "sample" points for some arbitrary curve. Next, the user specifies the number of equally spaced gaussian centers and the variance for the network. Using the training samples, the weights multiplying each of the gaussian basis functions arecalculated using the pseudo-inverse (yielding the minimum least-squares solution). The resulting network is then used to approximate the function between the given "sample" points.
