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1.
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VB中实现打印功能的方法 总被引:3,自引:0,他引:3
介绍了在VB开发的应用程序中,实现打印功能的几种方法.这些方法包括:①打印窗口;②通过PRINTER打印;③利用数据报表进行打印;④将打印内容传送于Office组件的Word或Excel,通过Word、Excel打印.同时列出了相关的程序格式. 相似文献
3.
Action calculi, which generalise process calculi such as Petri nets, π-calculusand ambient calculus, have been presented
in terms of action graphs. We here offer linear action graphs as a primitive basis for action calculi. This paper presents the category of embeddings of undirected linear
action graphs without nesting, using a novel form of graphical reasoning which simplifies some otherwise complex manipulations
in regular algebra. The results are adapted in a few lines to directed graphs. This work is part of a long-term search for
a uniform behavioural theory for process calculi.
Received October 2000 / Accepted in revised form April 2001 相似文献
4.
Doratha E Drake 《Information Processing Letters》2003,85(4):211-213
We present a linear time approximation algorithm with a performance ratio of 1/2 for finding a maximum weight matching in an arbitrary graph. Such a result is already known and is due to Preis [STACS'99, Lecture Notes in Comput. Sci., Vol. 1563, 1999, pp. 259-269]. Our algorithm uses a new approach which is much simpler than the one given by Preis and needs no amortized analysis for its running time. 相似文献
5.
J. Dingel 《Formal Aspects of Computing》2002,14(2):123-197
Parallel computers have not yet had the expected impact on mainstream computing. Parallelism adds a level of complexity to
the programming task that makes it very error-prone. Moreover, a large variety of very different parallel architectures exists.
Porting an implementation from one machine to another may require substantial changes. This paper addresses some of these
problems by developing a formal basis for the design of parallel programs in the form of a refinement calculus. The calculus
allows the stepwise formal derivation of an abstract, low-level implementation from a trusted, high-level specification. The
calculus thus helps structuring and documenting the development process. Portability is increased, because the introduction
of a machine-dependent feature can be located in the refinement tree. Development efforts above this point in the tree are
independent of that feature and are thus reusable. Moreover, the discovery of new, possibly more efficient solutions is facilitated.
Last but not least, programs are correct by construction, which obviates the need for difficult debugging. Our programming/specification
notation supports fair parallelism, shared-variable and message-passing concurrency, local variables and channels. The calculus
rests on a compositional trace semantics that treats shared-variable and message-passing concurrency uniformly. The refinement
relation combines a context-sensitive notion of trace inclusion and assumption-commitment reasoning to achieve compositionality.
The calculus straddles both concurrency paradigms, that is, a shared-variable program can be refined into a distributed, message-passing
program and vice versa.
Received July 2001 / Accepted in revised form May 2002 相似文献
6.
7.
This paper deals with the problem of finding graph layerings restricted to a given maximal width. However, other than previous approaches for width-restricted layering, we take into account the space for dummy nodes, which are introduced by edges crossing a layer. The main result is that the problem of finding a width-restricted layering under consideration of dummy nodes is NP-complete even when all regular nodes have the same constant width and all dummy nodes have the same constant width. 相似文献
9.
10.
Summary A derivation of a parallel algorithm for rank order filtering is presented. Both derivation and result differ from earlier designs: the derivations are less complicated and the result allows a number of different implementations. The same derivation is used to design a collection of priority queues. Both filters and priority queues are highly efficient: they have constant response time and small latency.
Anne Kaldewaij received an M.Sc. degree in Mathematics from the University of Utrecht (The Netherlands) and a Ph.D. degree in Computing Science from the Eindhoven University of Technology. Currently, he is associate professor in Computing Science at Eindhoven University. His research includes parallel programming and the design of algorithms and data structures. He enjoys teaching and he has written a number of textbooks on mathematics and programming.
Jan Tijmen Udding received an M.Sc. degree in Mathematics in 1980 and a Ph.D. degree in Computing Science in 1984 from Eindhoven University of Technology. Currently, he is associate professor at Groningen University. His main research interests are mathematical aspects of VLSI, program derivation and correctness, and functional programming. 相似文献