Focuses on how a method for automated programming (i.e., genetic programming) applies in the computer-aided discovery of algorithms that enhance and extract features from remotely sensed images. Highlighted as a case ...
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Focuses on how a method for automated programming (i.e., genetic programming) applies in the computer-aided discovery of algorithms that enhance and extract features from remotely sensed images. Highlighted as a case study is the use of this method in the problem of extracting pressure ridge features from ERS-1 SAR imagery; a problem for which there has been no known satisfactory solution.
We present a synchronous parallel programming model designed for massively parallel fine grained applications such as cellular automata, finite element methods or partial differential equations. In this model we assum...
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We present a synchronous parallel programming model designed for massively parallel fine grained applications such as cellular automata, finite element methods or partial differential equations. In this model we assume that the number of parallel processes in a program is much larger than the number of processors of the machine on which it is run. We present the computational model and the communication model. We introduce the virtual cellular machine, an abstract machine implementing this programming model which requires means to simulate efficiently the execution of many processes on a single processor; and to use the available communication bandwidth efficiently. Finally, we show an example program written in a prototype language designed for programming the virtual machine.
No significant general-purpose method is currently available to mechanically transform system requirements into a provably equivalent model. The widespread use of such a method represents a necessary step toward high-...
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No significant general-purpose method is currently available to mechanically transform system requirements into a provably equivalent model. The widespread use of such a method represents a necessary step toward high-dependability system engineering for numerous application domains. Current tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The "gap" unfilled by such tools and methods is that the formal models cannot be proven to be equivalent to the requirements. We offer a method for mechanically transforming requirements into a provably equivalent formal model that can be used as the basis for code generation and other transformations. This method is unique in offering full mathematical tractability while using notations and techniques that are well known and well trusted. Finally, we describe further application areas we are investigating for use of the approach.
Routing in mobile ad hoc networks (MANETs) where network topology is highly dynamic is not a trivial task. Routing protocols have been profoundly researched but only three of them have reached the RFC status (AODV[7],...
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Routing in mobile ad hoc networks (MANETs) where network topology is highly dynamic is not a trivial task. Routing protocols have been profoundly researched but only three of them have reached the RFC status (AODV[7], OLSR[5] and TBPRF[6]). On the other hand, the constantly increasing network requirements in terms of bandwidth, robustness, reliability and quality of service for a broad range of multiplatform scenarios demand for fast development and implementation of routing protocols that satisfy specific user and network requirements. However, current practices for protocol development and implementation are costly error-prone and time-consuming, especially when existing knowledge is not properly reused. Generative programming is an attractive solution that makes use of reusable components and is also empowered with the knowledge to automatically assemble them. This paper discusses the design and development of the GP- Pro protocol generator (based on generative programming), for automatic generation of ad hoc routing protocols, according to user requirements expressed by means of a specification language. GP-Pro is designed to be extensible, with the explicit goal of generating a large number of different protocols by different component combinations. GP-Pro addresses the generation of proactive, reactive and position-based routing protocols.
An automated system has been developed by the Industrial Engineering group at IBM's System Products Division plant in Poughkeepsie, N.Y., to TRACK the serialized bases of any product by comparing customized target...
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In this paper, the queueing performance of a type-II hybrid ARQ (automatic Repeat reQuest) scheme in a TDMA system over a Markovian channel is analyzed by assuming infinite queue size. The system of interest can be de...
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If current trends in cellular phone technology, personal digital assistants, and wireless networking are indicative of the future, we can expect our environments to contain an abundance of networked computational devi...
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ISBN:
(纸本)0769522769
If current trends in cellular phone technology, personal digital assistants, and wireless networking are indicative of the future, we can expect our environments to contain an abundance of networked computational devices and resources. We envision these devices acting in an orchestrated manner to meet users' needs, pushing the level of interaction away from particular devices and towards interactions with the environment as a whole. Computation will be based not only on input explicitly provided by the user, but also on contextual information passively collected by networked sensing devices. Configuring the desired responses to different situations will need to be easy for users. However, we anticipate that the triggering situations for many desired automation policies will be complex, unforeseen functions of low-level contextual information. This is problematic since users, though easily able to perceive triggering situations, will not be able to define them as functions of the devices' available contextual information, even when such a function (or a close approximation) does exist. In this paper, we present an alternative approach for specifying the automation rules of a pervasive computing environment using machine learning techniques. Using this approach, users generate training data for an automation policy through demonstration, and, after training is completed, a learned function is employed for future automation. This approach enables users to automate the environment based on changes in the environment that are complex, unforeseen combinations of contextual information. We developed our learning service within Gaia, our pervasive computing system, and deployed it within our prototype pervasive computing environment. Using the system, we were able to have users demonstrate how sound and lighting controls should adjust to different applications used within the environment, the users present, and the locations of those users and then automate those demonstrat
The concept that any "standard" electronic data processing or computing system should be adapted solely through programming to suit a particular business or industry is no longer supportable, except as an in...
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To reconstruct object from its orthographic image, a new method of 3D reconstruction based on image vectorization is presented. A 3D CAD model is automatically acquired from 2D views by means of 2D primitive recogniti...
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Program generators are most naturally specified using a quote/antiquote facility;the programmer writes programs with holes which are filled in, at program generation time, by other program fragments. If the programs a...
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