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tude A polyline (also called a linestring) consists of a connected sequence of line segments, and can be represented by a list containing the coordinates of the endpoints of the segments, in sequence We can approximately represent an arbitrary curve by polylines, by partitioning the curve into a sequence of segments This representation is useful for two-dimensional features such as roads; here, the width of the road is small enough relative to the size of the full map that it can be considered two dimensional Some systems also support circular arcs as primitives, allowing curves to be represented as sequences of arcs We can represent a polygon by listing its vertices in order, as in Figure 2322 The list of vertices speci es the boundary of a polygonal region In an alternative representation, a polygon can be divided into a set of triangles, as shown in Figure 232 This process is called triangulation, and any polygon can be triangulated The complex polygon can be given an identi er, and each of the triangles into which it is divided carries the identi er of the polygon Circles and ellipses can be represented by corresponding types, or can be approximated by polygons List-based representations of polylines or polygons are often convenient for query processing Such non- rst-normal-form representations are used when supported by the underlying database So that we can use xed-size tuples (in rst-normal form) for representing polylines, we can give the polyline or curve an identi er, and can represent each segment as a separate tuple that also carries with it the identi er of the polyline or curve Similarly, the triangulated representation of polygons allows a rst-normal-form relational representation of polygons The representation of points and line segments in three-dimensional space is similar to their representation in two-dimensional space, the only difference being that points have an extra z component Similarly, the representation of planar gures such as triangles, rectangles, and other polygons does not change much when we move to three dimensions Tetrahedrons and cuboids can be represented in the same way as triangles and rectangles We can represent arbitrary polyhedra by dividing them into tetrahedrons, just as we triangulate polygons We can also represent them by listing their faces, each of which is itself a polygon, along with an indication of which side of the face is inside the polyhedron.

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Computer-aided-design (CAD) systems traditionally stored data in memory during editing or other processing, and wrote the data back to a le at the end of a session of editing The drawbacks of such a scheme include the cost (programming complexity, as well as time cost) of transforming data from one form to another, and the need to read in an entire le even if only parts of it are required For large designs, such as the design of a large-scale integrated circuit, or the design of an entire airplane, it may be impossible to hold the complete design in memory Designers of objectoriented databases were motivated in large part by the database requirements of CAD

2 Some references use the term closed polygon to refer to what we call polygons, and refer to polylines as open polygons

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In Table 13-1, we list the Laplace transforms of some elementary functions that are frequently seen in electrical engineering When a function f (t) has a given Laplace transform F(s), we say that we have a Laplace transform pair and write f (t) F(s)

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The McGraw Hill Companies, 2001

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systems Object-oriented databases represent components of the design as objects, and the connections between the objects indicate how the design is structured The objects stored in a design database are generally geometric objects Simple two-dimensional geometric objects include points, lines, triangles, rectangles, and, in general, polygons Complex two-dimensional objects can be formed from simple objects by means of union, intersection, and difference operations Similarly, complex three-dimensional objects may be formed from simpler objects such as spheres, cylinders, and cuboids, by union, intersection, and difference operations, as in Figure 233 Three-dimensional surfaces may also be represented by wireframe models, which essentially model the surface as a set of simpler objects, such as line segments, triangles, and rectangles Design databases also store nonspatial information about objects, such as the material from which the objects are constructed We can usually model such information by standard data-modeling techniques We concern ourselves here with only the spatial aspects Various spatial operations must be performed on a design For instance, the designer may want to retrieve that part of the design that corresponds to a particular region of interest Spatial-index structures, discussed in Section 2335, are useful for such tasks Spatial-index structures are multidimensional, dealing with two- and three-dimensional data, rather than dealing with just the simple one-dimensional ordering provided by the B+ -trees Spatial-integrity constraints, such as two pipes should not be in the same location, are important in design databases to prevent interference errors Such errors often occur if the design is performed manually, and are detected only when a prototype is being constructed As a result, these errors can be expensive to x Database support for spatial-integrity constraints helps people to avoid design errors, thereby keeping the design consistent Implementing such integrity checks again depends on the availability of ef cient multidimensional index structures.

f (t) u(t) tn, eat cos t sin t cosh at sinh at (t) e at u(t) e at f (t) t f (t) f (at) df dt d2 f dt 2

The McGraw Hill Companies, 2001

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