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regardless of whether edges are directed or undirected Therefore, Sinnen and Sousa [176, 178] propose the utilization of hyperedges to represent bus-like topologies in contention aware scheduling A hypergraph (ie, a graph containing hyperedges) is a generalization of the undirected graph, where edges hyperedges can be incident on more than two vertices (Berge [21]) De nition 72 (Hyperedge and Hypergraph) Let V be a nite set of vertices A hyperedge H is a subset consisting of two or more vertices of V, H V, |H| > 1 A hypergraph HG is a pair (V, H) of a nite set of vertices V and a nite set of hyperedges H Note that an undirected edge is a hyperedge incident on exactly two vertices and an undirected graph can be considered a hypergraph containing only such edges Figure 75 visualizes the difference between a 4-vertices undirected graph, fully connected, and a 4-vertices hypergraph, with one hyperedge In both graphs, every vertex is adjacent to every other vertex Switches The above discussed shortcomings of the undirected topology graph and their solutions permit the improved representation of static networks and the incorporation of bus topologies However, the modeling of dynamic networks in general has not been addressed yet Since dynamic networks are widely employed in parallel systems (Section 22), the approximation of these networks as fully connected is not appropriate The essential component of a dynamic network is he switch, which signi cantly determines the network s characteristic So while the above improvements target the edges of the topology model, switches are incorporated into the graph by means of a new vertex type a switch vertex In other words, a vertex in the topology graph.

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Select Copy and a dialog appears, as if you re creating a brand-new user, asking for name, logon name, and so on However, the rest of the properties of the original user are copied to the new target user A cool feature of Copy is that properties that were user-speci c, such as the user pro le roaming path or home locations, are replaced with the new user s name, provided that the last part of the path matches the logon name Using the Add to a Group option is a quick way to add a user to a group, and the Disable Account option just disables he account You will probably use Reset Password quite a lot Other options are available for moving the user to a new location, but you can do this most easily by just dragging and dropping the object to put it in its new location Select the All Tasks menu options to perform group policy con guration to see Resultant Set of Policy (RSOP), which is explored fully in 21, Group Policy When you select the properties for a user, select multiple objects at once by holding down Shift to select a contiguous set of objects or Ctrl to select individual objects While you select the multiple objects, some context menu items are available, such as Move, Disable/Enable, Add to Group, and Delete Select Properties to modify some attributes of the users en masse Not all attributes are available, but most of the General, Account, Address, Pro le, and Organizational tab options are available, as shown in Figure 12-29 On the Pro le tab, use %username% to set a home folder location or roaming pro le for multiple users.

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The Black Scholes and binomial pricing models were originally developed for valuing traded options with relatively short lives and are based on complex mathematical formulas Option values derived under these models are sensitive to both the expected stock volatility and the expected dividend yield Exhibit 398 illustrates the relative effect of changes in expected volatility and dividend rates using a generalized Black-Scholes option-pricing model Software packages that include option pricing models are readily available from numerous oftware vendors As demonstrated in Exhibit 398, option values increase as expected volatility increases, and option values decrease as expected dividend yield increases It is interesting to note that in instances where higher expected volatility is coupled with higher dividend yields, the binomial model generally produces higher option values than the Black-Scholes model due primarily to increased sensitivity to compounded dividend yields in the binomial model Nevertheless, FASB Statement No 123 permits the use of either model (i) Expected Volatility Volatility is the measure of the amount that a stock s price has uctuated (historical volatility) or is expected to uctuate (expected volatility) during a speci ed period Volatility is expressed as a percentage; a stock with a volatility of 25 percent would be expected to have its annual rate of return fall within a range of plus or minus 25 percentage points of its expected rate about two-thirds of the time For example, if a stock currently trades at $100 with a volatility of 25 percent and an expected rate of return of 12 percent, after one year the stock price should fall within the range of $87 to $137 approximately two-thirds of the time (using simple interest for illustration) Stocks with high volatility provide option holders with greater economic up-side potential and, accordingly, result in higher option values under the Black Scholes and binomial option pricing models FASB Statement No 123 suggests that estimating expected future volatility should begin with calculating historical volatility over the most recent period equal to the expected life of the options Thus, if the weighted-average expected life of the options is six years, historical volatility should be calculated for the six years immediately preceding the option grant FASB Statement No 123 provides an illustrative example for calculating historical volatility Companies should modify historical stock volatility to the extent that recent experience indicates that the future is reasonably expected to differ from the past Although historical averages may be the best available indicator of expected future volatility for some mature companies, there are legitimate exceptions including: (1) a company whose common stock has only recently become publicly traded with little, if any, historical data on its stock price volatility, (2) a company with only a few years of public trading history where recent experience indicates that the stock has generally become less volatile, and (3) a company that sells off a line of business with signi cantly different volatility than the remaining line of business In such cases, it is appropriate for companies to adjust historical volatility for current circumstances or use the average volatilities of similar companies until a longer series of historical data is available FASB Statement No 123 does not allow for a company with publicly traded stock to ignore volatility simply because its stock has little or no trading history A company with only publicly traded debt is not considered a public company under FASB Statement No 123 Subsidiaries of public companies are considered public companies for purposes of applying FASB Statement No 123 s provisions (ii) Expected Dividends The assumption about expected dividends should be based on publicly available information While standard option pricing models generally call for expected dividend yield, the model may be modi ed to use an expected dividend amount rather than a yield If a company uses expected payments, any history of regular increases in dividends should be considered For example, if a company s policy has been to increase dividends by approximately three percent per year, its estimated option value should not assume a xed dividend amount throughout the expected life of the option Some companies with no history of paying dividends might reasonably expect to begin paying small dividends during the expected lives of their employee stock options These companies may use an average of their past dividend yield (zero) and the mean dividend yield of an appropriately comparable peer group.

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It is also known as Denso Barcode, QRCode, Quick Response Code, JIS X 510, ISO/IEC18004 QR Code is a kind of 2-D (two-dimensional) symbology developed by Denso Wave (a division of Denso Corporation at the time) and released in 1994 with the primary aim of being a symbol that is easily interpreted by scanner equipment QR Code is capable of handling all types of data, such as numeric and alphabetic characters, Kanji, Kana, Hiragana, symbols, binary, and control codes The symbol versions of QR Code range from Version 1 to Version 40 Each version has a different module configuration or number of modules (the module refers to the black and white dots that make up QR Code) "Module configuration" refers to the number of modules contained in a symbol, commencing with Version 1 (21 x 21 modules) up to Version 40 (177 x 177 modules).

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