業(yè)務(wù)管理：包括客房預(yù)訂、入住登記、續(xù)住、換房、轉(zhuǎn)賬、其他服務(wù)提供、留言板、意見簿、走客結(jié)賬、欠費(fèi)結(jié)算。 ¯ 查詢統(tǒng)計(jì)：包括歷史單據(jù)、預(yù)訂表、在住客人表、換房查詢、轉(zhuǎn)賬查詢、日經(jīng)營(yíng)狀況、月收入狀況、客房利用率、實(shí)時(shí)房態(tài)。-system design focus of this chapter describe the development of small PowerBuilder 9.0 Rooms Management System process, through the study of this chapter, readers should be familiar with PowerBuilder 9.0 TreeView control and the right mouse button menu of use, master GroupBox, SingleLineEdit, CommandButton, RadioButton, PictureButton controls such as the similarities and differences to further understanding of data objects window displays various occasions the application. System to complete the task Macr system maintenance include : corporate information, the operator management, change passwords, management succession, dictionary management. Macr basic information : Rooms management system for the basic information management (including new, modify or delete), which is the basic informat
Description
The art galleries of the new and very futuristic building of the Center for Balkan Cooperation have the form of polygons (not necessarily convex). When a big exhibition is organized, watching over all of the pictures is a big security concern. Your task is that for a given gallery to write a program which finds the surface of the area of the floor, from which each point on the walls of the gallery is visible. On the figure 1. a map of a gallery is given in some co-ordinate system. The area wanted is shaded on the figure 2.
The code performs a number (ITERS) of iterations of the
Bailey s 6-step FFT algorithm (following the ideas in the
CMU task parallel suite).
1.- Generates an input signal vector (dgen) with size
n=n1xn2 stored in row major order
In this code the size of the input signal
is NN=NxN (n=NN, n1=n2=N)
2.- Transpose (tpose) A to have it stored in column
major order
3.- Perform independent FFTs on the rows (cffts)
4.- Scale each element of the resulting array by a
factor of w[n]**(p*q)
5.- Transpose (tpose) to prepair it for the next step
6.- Perform independent FFTs on the rows (cffts)
7.- Transpose the resulting matrix
The code requires nested Parallelism.
A certification path is an ordered list of certificates starting with a certificate issued by the relying
party s trust root, and ending with the target certificate that needs to be validated. Certification
path validation procedures are based on the algorithm supplied in ITU-T Recommendation X.509
and further defined in Internet Engineering task Force (IETF) Request for Comments (RFC)
3280. Certification path processing verifies the binding between the subject distinguished name
and/or subject alternative name and the subject public key defined in the target certificate. The
binding is limited by constraints, which are specified in the certificates that comprise the path,
and inputs that are specified by the relying party. To ensure secure interoperation of PKI-enabled
applications, the path validation must be done in accordance with the X.509 and RFC 3280
specifications. This document provides the test assertions and the test cases for testing path
validation software against these specifications.
The potential of solving real-time demanding industrial applications, using vision-based
algorithms, drastically grew due to an increasing availability of computational power.
In this thesis a novel real-time, vision-based Blackjack analysis system is presented. The
embedding of the vision algorithms in a compound system of other information sources such
as an electronic chip tray, reduces the vision task to detect cards and chips. Robust results
are achieved by not just analyzing single frames but an image stream regarding game-ß ow
informations. The requirements for such a system are a highly robust and adaptive behav-
ior. This is motivated by the vital interest of casino entrepreneurs in a 100 statistical
analysis of their offered gambling in order to support the business plan, measuring table
and dealer performance and give accurate player rating. Extensive experiments show the
robustness and applicability of the proposed system.
face detection
Face detection can be regarded as a more general case of face localization In face localization, the task is to find the locations and sizes of a known number of faces (usually one). In face detection, one does not have this additional information.
Early face-detection algorithms focused on the detection of frontal human faces, whereas newer algorithms attempt to solve the more general and difficult problem of multi-view face detection. That is, the detection of faces that are either rotated along the axis from the face to the observer (in-plane rotation), or rotated along the vertical or left-right axis (out-of-plane rotation),or both.
