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The assignment of the observations to speci c clusters can be stored as a separate column or a series of columns in the table by selecting the Generate clusters as column(s) option. In the case of agglomerative hierarchical clustering and k-means clustering, a single column will be generated, whereas for fuzzy k-means clustering, the software will generate one column per cluster containing the membership score for each cluster. Having speci ed the type of clustering required, clicking on the Cluster button will generate the clusters and the results will be summarized in the results area. Figures B.46 B.48 illustrate agglomerative hierarchical clustering, k-means clustering, and fuzzy k-means clustering, respectively. When the agglomerative hierarchical clustering is selected, the results are displayed as a dendrogram describing the hierarchical organization of the data, as shown in Fig. B.46. A vertical line dissects the dendrogram, thus creating clusters of observations to the right of the vertical line. A rectangle is placed around each cluster, and space permitting, a number indicating the size of the cluster is annotated on the right. When the data set has a label variable, clusters with only a single observation are replaced by the label s value (space permitting). The cutoff is interactive; it can be moved by clicking on the square towards the bottom of the cutoff line and moving it to the left or right. Moving the line changes the distance at which the clusters are generated, and hence the number of clusters will change as the cutoff line moves. If the Generate clusters as column(s) option is selected, the column in the data table describing the cluster membership will also change.

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Network transparency. By using the IIOP protocol, an ORB can interconnect with any ORB located elsewhere on the network. Remote callback support. CORBA allows objects to receive asynchronous event notification from other objects. Dynamic invocation interface. CORBA clients can both use static and dynamic methods invocations. They either statically define their method invocations through stubs at compile time, or have the opportunity to discover objects methods at runtime. With those advantages, some key factors, which affected the success of CORBA evident while implementing CORBA-based distributed applications, are as follows: High initial investment. CORBA-based applications require huge investments in regard to new training and the deployment of architecture, even for small-scale applications. Availability of CORBA services. The Object services specified by the OMG are still lacking as implementation products. Scalability. Due to the tightly coupled nature of the connectionoriented CORBA architecture, very high scalability expected in enterprise applications may not be achieved. However, most of those disadvantages may be out of date today. The Internet community for the development of Intranet and Extranet applications has acknowledged using CORBA with IIOP and Java as their tools of choice. Sun has already released its JDK 1.4 (Java development kit), which includes a full-featured CORBA implementation and also a limited set of services.

Installing MySQL Separately If not installed with Linux, MySQL can also be installed separately. It is recommended that you install MySQL by using its RPM files. The RPM files can be downloaded from

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Sometimes it makes sense to name an entire row or column. Often, a worksheet is used to store information that you enter over a period of time. The sheet in Figure 3-6 is an example of such a worksheet. If you create a name for the data in column B, you need to modify the name s reference each day you add new data. The solution is to name the entire column.

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/********************************************************************************** calcStochasticVolSpread : calculates the value of a call spread option on two stocks. [in]: double price1 : price of stock 1 double price2 : price of stock 2 double X : strike price double rate : risk-free interest rate double Vbar1 : mean-reversion level for stock 1 double Vbar2 : mean-reversion level for stock 2 double div1 : dividend yield of stock 1 double div2 : dividend yield of stock 2 double alpha1 : mean reversion rate of the variance for stock 1 double alpha2 : mean reversion rate of the variance for stock 2 double T : time to maturity (in years) double eta1 : volatility of the variance of stock 1 double eta2 : volatility of the variance of stock 2 double R : correlation (symmetric) matrix int M : number of simulations int N : number of time steps [out]: spread call price (double) **********************************************************************************/ double SpreadOption::calcStochasticVolSpread(double price1, double price2, double X, double rate, double Vbar1, double Vbar2, double div1, double div2, double alpha1, double alpha2, double T, double eta1, double eta2, SymmetricMatrix& R, int M, int N) { N = 1; // No path dependency

The satellite ground track is the trace of the points of the Earth overflown by the satellite. This concept is important to understand which part of the Earth is seen by the satellite when it moves along its trajectory. The ground track is obtained by the vector combination of the absolute satellite velocity projected onto the subsatellite point and the Earth velocity of this subsatellite point. From kinematic considerations, it can be shown that, in an Earth-fixed reference frame, a satellite that accomplishes N + m/q revolutions per day (N, m, q are integers) has a ground track that repeats itself after a time period (Prep) having completed (qN + m) revolutions, such that: Prep = (qN + m) Porb = (N+ m/q) Pnod where: Porb Pnod = = = satellite orbital period between two successive ascending passes at the equator = 2 ( + M) (s) nodal (or draconitic) period of the ascending node sideral rotation rate of the Earth = 2 ( ) (s) 2 /86 164 (rad/s)

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