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Then the temperature compensation circuit as shown in Figure 7.45(b) is adapted. The gate voltage Vg is also increased as the temperature is increases. Consequently the decreased gain of the MOSFET due to temperature is compensated for by the increase of gain due to the increase of the gate voltage.
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If you decide you need to update a user s information or change the privileges assigned, you can do so from the Properties window. Here are the steps for doing that: 1. Either double-click the user account in the list or select the user account and click the Properties button. The Account Properties window appears, as shown in Figure 17-5.
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ssembly configurations enable you to control many things, including part configurations, suppression, visibility, color, and assembly feature sizes. They also allow you to control assembly layout sketch dimensions, mate values, suppression states, and several other items. What you will learn in this chapter about assembly configurations builds on the information in 10, which discusses part configurations. In this chapter, you will also learn how design tables are used in conjunction with SolidWorks assemblies. Display States are a better performance alternative to using configurations to control visibility of parts in assemblies. I discuss Display State options at length in this chapter.
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100. Kuranouchi, S.; Konagai, M. 1995. Characterization of ZnO/CdS/CuInSe2 thin- lm solar cells by deep-level transient spectroscopy. Jpn. J. Appl. Phys. 34:2350 2351. 101. Bhattacharya, R. N.; Chen, J.; Spagnol, P.; Huang, J. Y.; Ren, Z. F. 2004. Superconductor Bi-oxide lms via an electrodeposition process. Supercond. Sci. Technol. 17:120 124. 102. Chen, J.; Bhattacharya, R. N. 2003. Growth of 1 2 m thick biaxially textured Bi-2212 lms on (1 0 0) LaAlO3 single crystal substrates by electrodeposition. Physics C 399:171 177. 103. Bhattacharya, R. N.; Banerjee, D.; Wen, J. G.; Padmanabhan, R.; Wang, Y. T.; Chen, J.; Ren, Z. F.; Hermann, A. M.; Blaugher, R. D. 2002. Structural studies of electrodeposited and sprayed thallium-oxide lms. Supercond. Sci. Technol. 15:1288 1294. 104. Blaugher, R. D.; Bhattacharya, R. N.; Chen, J.; Padmanabhan, R. 2002. Alternative HTS coated conductors. Physica C 382:72 79. 105. Bhattacharya, R. N.; Xing, Z.; Wu, J. Z.; Chen, J.; Yang, S. X.; Ren, Z. F.; Blaugher, R. D. 2002. Superconducting thallium oxide and mercury oxide lms. Physica C 377:327 332. 106. Bhattacharya, R. N.; Wu, H. L.; Wang, Y.-T.; Blaugher, R. D.; Yang, S. X.; Wang, D. Z.; Ren, Z. F.; Tu, Y.; Verebelyi, D.T.; Christen, D. K. 2000. Improved electrodeposition process for the preparation of superconducting thallium oxide lms. Improved electrodeposition process for the preparation of superconducting thallium oxide lms. Physica C 333:59 64. 107. Bhattacharya, R. N.; Feldmann, M.; Larbalestier, D.; Blaugher, R. D. 2001. Electrodeposition process for the preparation of superconducting thallium oxide lms. IEEE Trans. Appl. Supercond. 11:3102 3105. 108. Bhattacharya, R. N.; Blaugher, R. D.; Ren, Z. F.; Li, W.; Wang, J. H.; Paranthaman, M.; Verebelyi, D. T.; Christen, D. K. 1998. Superconducting thallium oxide lms by electrodeposition method. Physica C 304:55 65. 109. Bhattacharya, R. N.; Blaugher, R. D.; Ren, Z. F.; Li, W.; Wang, J. H.; Paranthaman, M.; Verebelyi, D. T.; Christen, D. K. 1998. Superconducting epitaxial (TlBi)0.9Sr1.6 Ba0.4Ca2Cu3Ag0.2Ox lm from an electrodeposited precursor. Electrochemi. SolidState Lett. 1:165 167. 110. Phok, S.; Bhattacharya, R. N. 2006. Effect of samarium doping on electrodeposited CeO2 thin lm. Physica Status Solidi (a) 203:3734 3742. 111. Bhattacharya, R. N.; Phok, S.; Spagnol, P.; Chaudhuri, T. 2006. Electrodeposited biaxially textured buffer layer for YBa2Cu3O7 (YBCO) superconductor oxide lms. J. Electrochem. Soc. 153:C273 C276. 112. Trovarelli, A. 1996. Catalytic properties of CeO2 and CeO2-containing materials. Catal. Rev. Sci. Eng. 38:439 520. 113. Rodriguez, J. A.; Jirsak, T.; Freitag, A.; Hanson, J. C.; Larese, J. Z.; Chaturvedi, S. 1999. Interaction of SO2 with CeO2 and Cu/CeO2 catalysts: Photoemission, XANES and TPD studies. Catal. Lett. 62:113 119. 114. Izu, N.; Murayama, N.; Shin, W.; Matsubara, I.; Kanzaki, S. 2004. Resistive oxygen sensors using cerium oxide thin lms prepared by metal organic chemical vapor deposition and sputtering. Jpn. J. Appl. Phys. 43:6920 6924.
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When you select an object, handles appear on the border. Drag a handle to retains the resize an object. Dragging a corner handle while pressing object s original proportions.
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The treatment of individuals in DAML1OIL is, however, very different from that in OIL. In the rst place, DAML1OIL relies wholly on RDF for assertions on the type (class) of an individual or a relationship between a pair of individuals. In the second place, DAML1OIL treats individuals occurring in the ontology (in oneOf constructs or hasValue restrictions) as true individuals (i.e. interpreted as single elements in the domain of discourse) and not as primitive concepts as is the case in OIL. Moreover, there is no unique name assumption: in DAML1OIL it is possible to explicitly assert that two individuals are the same or different, or to leave their relationship unspeci ed. This treatment of individuals is very powerful, and justi es intuitive inferences that would not be valid for OIL, for example, that persons all of whose countries of residence are Italy are kinds of person that have at most one country of residence: Unfortunately, the combination of individuals with inverse roles is so powerful that no practical decision procedure (for satis ability/ subsumption) is currently known, and there is no implemented system that can provide sound and complete reasoning for the whole DAML1OIL language. In the absence of inverse roles, however, a tableaux algorithm has been devised (Horrocks and Sattler, 2001), and in the absence of individuals, DAML1OIL ontologies can exploit implemented DL systems via a translation into SHIQ similar to the one described for OIL. It would, of course, also be possible to translate DAML1OIL ontologies into SHIQ using the disjoint primitive concept of interpretation of individuals adopted by OIL, but in this case reasoning with individuals would not be sound and complete with respect to the semantics of the language.
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Once the Toolbox Browser is turned on, you can use it by expanding the Task Pane at the right of the SolidWorks graphics window and clicking the Design Library, which looks like a stack of books. In this panel, you will see the Toolbox screw symbol. Expand icons until you find the fastener or other hardware that you are looking for, and then drag the part into the assembly.
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See 1 to find out what the minimum requirements are for a Windows Vista graphics card. Then see 8 to learn how to install drivers for a graphics card on your PC.
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OntoExtract builds on a core natural language analysis engine. The engine supports analysis of natural language texts and generates lightweight, domain speci c ontologies of these texts while utilizing already existing knowledge from a central data repository. OntoExtract utilizes highly expressive querying of RDF data and schema information, using RQL, which is being developed by the ICS-FORTH institute in Greece. Sesame (described in the previous chapter), is used for the repository management. The Sesame data repository can be questioned through the access layer and edited with the OntoEdit ontology editor described in 7. The overall extraction process, shown in Figure 6.1, is typically iterative, with a user initiating the process by providing a location to analyse for seedontology generation, together with some parameters that de ne the extent of the Internet domain to be analysed. From each page containing natural language text, lightweight ontologies are produced and automatically submitted to the Sesame repository for storage. The statements that are
(4) Termination rule. Stop iterating when both 1 - Ill < E and J J V h J J 6, 1 W < for some predetermined tolerance levels, for example, E = S = lop3. Note that this algorithm attempts to improve the numerical properties by avoiding the possibly poorly conditioned matrix VTV. If either t or V is kept fixed, it is not difficult to show that the algorithm converges under fairly general assumptions. A convergence proof for fixed t is contained in the proof of Lemma 8.3. For fixed V , convergence of the location step can easily be proved if W ( T ) is monotone decreasing and w(r)r is monotone increasing. Assume for simplicity that V = I and let p ( ~be an indefinite integral of w(r)r. Then p( Jx- ti) is convex as a ) function o f t , and minimizing ave{p( /x ti)} is equivalent to solving (8.38). As in Section 7.8, we define comparison functions. Let ~i = Iyi/ = Jxi- t(")/, where t(m) the current trial value and the index i denotes the ith observation. is Define the comparison functions u such that i
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