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In the Components selection box, select the six screw instances, the two washers, and the two nuts. In the Features selection box, select the in-context feature or features that are associated with the Smart Component.
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Filtering, when combined with grouping, can be a problem. Are the row restrictions applied before the group by or after the group by Some databases use nested queries to properly filter before or after the group by. SQL, however, uses the having clause to filter the groups. At the beginning of this chapter you saw the simplified order of the SQL select statement s execution. A more complete order is as follows: 1. The from clause assembles the data from the data sources. 2. The where clause restricts the rows based on the conditions. 3. The group by clause assembles subsets of data. 4. Aggregate functions are calculated. 5. The having clause filters the subsets of data. 6. Any expressions are calculated. 7. The order by sorts the results. Continuing with the RawData sample table, the following query removes from the analysis any grouping having an average of less than 25:
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Triggers are special stored procedures that are attached to a table and fire when certain datamodification operations hit that table. Two types of triggers exist: instead of and after. They differ both in their timing and in how they handle the data-modification operation. An instead of trigger always causes the insert, update, or delete operation to be canceled. The SQL command submitted to SQL Server is discarded by the instead of trigger; the code within the instead of trigger is executed instead of the submitted SQL command, hence the name. The instead of trigger might be programmed to repeat the requested operation so that it looks like it went through, or it could do something else altogether. The problem with the instead of trigger is that it reports back one row affected when in fact nothing is written to the database. There is no error warning because the instead of trigger works properly; however, the operation doesn t go through.
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When searching for newsgroups, if you notice a little yellow rectangular icon to the left of a newsgroup, you know it s one you ve already subscribed to. Therefore, there s no need to add it to your list again.
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An analog signal is a continuous function of time [4,5]. Telecommunication started out as telephony, in which a microphone (or transmitter, mouthpiece) produces an electrical analog signal, whose variations in time approximate the variations in air pressure produced by the talker s speech. A receiver (or earpiece) reconverts the electrical speech signal into air-pressure variations that are heard by the listener. The pressure variations of acoustic speech are complex and not easily described. Average acoustic speech contains frequencies from 35 Hz to 10,000 Hz. Most of the speech power is concentrated between 100 Hz and 4000 Hz. For good-quality telephony, only the frequencies between 300 and 3400 Hz need to be transmitted. Analog communication channels in the network, which historically have been designed primarily for speech transmission, therefore accommodate this range of voiceband frequencies (Fig. 1.4-1). Two-Wire and Four-Wire Circuits. Analog circuits can be two-wire or fourwire. Subscriber lines are two-wire circuits, consisting of a pair of insulated copper wires that transfer signals in both directions. Most analog trunks are fourwire circuits, consisting of two unidirectional two-wire circuits, one for each direction of transmission. In the diagrams of this section, circuits are shown as in Fig. 1.4-2. The arrows indicate the directions of transmission. In general, bidirectional circuits (two- or four-wire) are shown as in (a), and a note indicates whether the circuit is
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Fig. 11.7 Figure 11.7 shows a standard dartboard. You throw six darts at the board, completely at random, except that you are accurate enough to get them all actually on the board. You do not score any bullseyes, and doubles and trebles do not count (so that '7', 'double 7' and 'treble 7' all count the same). What is the chance that two of them will stick in the same segment
Security and Active Directory
E. Eugene Schultz University of California Berkley Lab Denial of Service Attacks Windows 2000 Security Steven D. Schwaitzberg Tufts-New England Medical Center Medical Care Delivery Kathy Schwalbe Augsburg College Project Management Techniques Mark Shacklette The University of Chicago Unix Operating System P. M. Shankar Drexel University Propagation Characteristics of Wireless Channels John Sherry Purdue University History of the Internet Carolyn J. Siccama University of Massachusetts Lowell Internet2 Judith C. Simon The University of Memphis Java Law Enforcement Law Firms Robert Simon George Mason University Middleware Nirvikar Singh University of California, Santa Cruz Digital Economy Clara L. Sitter University of Denver Library Management Robert Slade Consultant Computer Viruses and Worms Erick D. Slazinski Purdue University Structured Query Language (SQL) Mark Smith Purdue University Supply Chain Management Technologies Lee Sproull New York University Online Communities Charles Stein eld Michigan State University Click-and-Brick Electronic Commerce Electronic Commerce and Electronic Business Edward A. Stohr Stevens Institute of Technology Online Analytical Processing (OLAP) Dianna L. Stone University of Central Florida Human Resources Management David Stotts University of North Carolina at Chapel Hill Perl
Time
In this quadrature form, the in-phase signal component is represented by ak cos ( t/2T ) cos 2 fc t, where cos ( t/2T ) is described as sinusoidal symbol weighting and ak depends on the data through Eq. (7.4.4). Similarly, the quadrature signal component is given by bk sin ( t/2t) sin 2 fc t, where sin( t/2T ) is a sinusoidal symbol weighting and bk also depends on the data through Eq. (7.4.4). At rst examination of Eq. (7.4.4), it might appear that ak and bk can change every T seconds, because the data bit value dk can certainly change every T seconds. However, because of the continuous-phase constraint, as ensured by Eq. (7.4.2), ak can change sign only at the zero crossings of sin( t/2T ), and bk can change sign only at the zero crossings of sin( t/2T ). Thus, the symbol weighting in either the in-phase or quadrature channel is a half-cycle sinusoidal pulse of duration 2T seconds with alternating sign. As with OQPSK, the two channels of this modulator are offset by T seconds. Therefore, we can consider MSK modulation to be a form of OQPSK having sinusoidal symbol weighting on the quadrature channels and a special relationship between the source data stream dk and the binary values applied to the quadrature channels. For steady-signal reception in AWGN, the BER performance for MSK is exactly the same as for OQPSK and QPSK. The composition of the MSK waveform is shown in Fig. 7.22. As with OQPSK, MSK is an offset constant-envelope modulation, but MSK has the additional advantage that it is phase continuous, and therefore even the 90 shifts of OQPSK are eliminated. In fact, it is readily seen from Eqs. (7.4.1) and (7.4.2) that in each T -second interval, the phase of the signal moves ahead of or behind the carrier phase at a constant rate for a total excursion of exactly /2 radians over the interval. The phase continuity of MSK results in a signal spectrum with tails somewhat lower than those of OQPSK. The power spectral density G(f ) for MSK modulation is given [Pro01] by 16A2 T cos 2 f T 2 G(f ) = 2 1 16f 2 T 2 where A is the amplitude of the MSK signal. Figure 7.23 shows the normalized power density spectra for BPSK, QPSK, OQPSK, and MSK. As can be seen in the gure, MSK has lower sidelobes than QPSK or OQPSK, but the main lobe of the MSK spectrum is broader. At the 3-dB power points, the MSK main lobe is about 30 per cent wider than that of QPSK. GMSK. Murota and Hirade [Mur81] observed that the MSK signal spectrum could be made even more compact, and the spectral skirts lowered further, by implementing the modulation in its direct FM form with a low-pass lter applied to the data stream before modulation. This technique provides a smoothing of the phase transitions at symbol boundaries; and because the ltering is done before modulation, the constant-envelope property of the signal is preserved. The speci c lter characteristic proposed by Murota and Hirade is the Gaussian low-pass lter. This modulation technique, shown in Fig. 7.24, is called Gaussian ltered MSK or simply Gaussian MSK (GMSK). The rapid roll-off achievable with Gaussian lters provides spectra that are more compact than that of strict-sense MSK. Because the transform of a Gaussian function is also Gaussian, the impulse response of the premodulation lter is Gaussian. The tails of the Gaussian time-domain function remain above zero, and this results in some intersymbol interference. The choice of roll-off characteristic for the Gaussian lter involves a trade-off between spectral con nement and performance
Part V
This indicates that the time evolution of the momentum is given by the Lorentz force. Since we are not considering the total force on the right-hand side, but just the external force, the electron momentum here clearly cannot be the true momentum. It is called the quasimomentum or crystal momentum. As described below, these two governing equations are solved self-consistently, and sequentially with the Poisson equation in Monte Carlo simulations using a single-particle approach, or a collective approach as with the BTE. For such Bloch electrons, with the modulated plane-wave functions, the E(k) relationship is no longer perfectly parabolic and the equienergy surfaces are not exactly spherical. However, invoking the effective mass theorem, they are approximately so near the band edges. The details of the effective mass are described next. We start by considering the time derivative of the electron velocity given by semiclassical dynamics, in order to determine the acceleration of the electrons.
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