We discuss a representational scheme used in a hybrid natural language processing system. The system is called SYMCON (Symbolic and Connectionist), and as its name implies, it consists of subsystems of different natur...
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We discuss a representational scheme used in a hybrid natural language processing system. The system is called SYMCON (Symbolic and Connectionist), and as its name implies, it consists of subsystems of different nature. SYMCON is being developed primarily for the task of word sense disambiguation (WSD). In order to disambiguate different word senses, all the necessary information (e.g., syntactic and semantic information) must firstly be represented in a machine tractable manner. Furthermore, the representations must be effective for the different subsystems in the hybrid SYMCON system to cooperate and work as whole. The representational scheme plays a crucial part in the development of the hybrid system. The system organisation of SYMCON is overviewed. Then important issues of the distributed representational scheme based on microfeatures are discussed in detail.
A decentralized dynamic routing controller design strategy is proposed for large-scale traffic networks. The strategy is based on the overlapping decompositions method and can be used for large-scale networks which ha...
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A decentralized dynamic routing controller design strategy is proposed for large-scale traffic networks. The strategy is based on the overlapping decompositions method and can be used for large-scale networks which have more than two overlapping subnetworks and/or have more than one node in the overlapping part. The controller obtained by the proposed approach is decentralized in the sense that all online computations can be done locally at the individual nodes without any information transfer from the other nodes. The controller satisfies all the routing control constraints and it avoids any looping. The controller also clears the queues in finite time in the absence of external arrivals and it keeps the queue lengths bounded in the presence of external arrival rates which do not exceed a certain maximum rate.
This paper investigates the use of artificial neural networks for determining the voltage stability limit of a power system during contingencies. Different neural network architectures are trained with data containing...
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This paper investigates the use of artificial neural networks for determining the voltage stability limit of a power system during contingencies. Different neural network architectures are trained with data containing a variety of load patterns, generation patterns, generator voltage pattern and transformer tap ratio settings, via economic minimization. Tests are conducted on a neural network selected based on training performance. studies are conducted on the New England 39 bus system. The work is an enhancement of previous work by the authors and provides criteria for possible extension of the stability limit. It is concluded that the selected neural network architecture gives reasonably accurate predictions of the collapse point with potential for improving the stability margin.
Reports the result of a set of computer experiments carried out to enhance a digital image. The authors use a special line-weight function, which is a combination of zero- and second-order Hermite functions. The autho...
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Reports the result of a set of computer experiments carried out to enhance a digital image. The authors use a special line-weight function, which is a combination of zero- and second-order Hermite functions. The authors are motivated by the physiological evidence reported in Young (1987) that visual receptive fields in the primate eye are shaped like the sum of a Gaussian function and its Laplacian. This function can also be derived mathematically when the contrast sensitivity experiments in psychophysics are posed as an eigenvalue problem. The authors show that higher order Hermite terms play a significant role in image enhancement. The experimental results with one- and two-dimensional data show that the proposed function has extremely good localisation capability (i.e., the points marked by the operator is as close as possible to the center of the true edge).
This paper presents an empirical data modeling approach for a class of systems called quasi-linear. In addition, state estimation based on the identified system and the design of a robust feedback controller for a com...
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This paper presents an empirical data modeling approach for a class of systems called quasi-linear. In addition, state estimation based on the identified system and the design of a robust feedback controller for a complex industrial application are included. A drum boiler steam generator system is selected as a prototype example of this class of nonlinear dynamic systems to be identified and to be controlled in a deterministic and stochastic environment. Simulation results indicate that the resulting controller shows a significant improvement over existing proportional-integral (PI) control, including reduced transient response, time delay tolerance and also robustness against full load range (large steam flow changes), for different characteristics exhibited by the input (feedwater) valve. The prominent feature of this method is that no specific model information is initially required throughout the identification and control of the nonlinear plant, and hence the method is suitable for both identifying and controlling of the critical industrial processes.
From a user's perspective, VCR functions of variable-rate fast-forward and rewind are desirable features in many video applications. To implement VCR-like operations, the video server should be able to access nonc...
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ISBN:
(纸本)0780325591
From a user's perspective, VCR functions of variable-rate fast-forward and rewind are desirable features in many video applications. To implement VCR-like operations, the video server should be able to access noncontiguous segments of a video object without additional overhead. In this paper, we propose prime round-robin (PRR) placement scheme, which achieves uniform load-balance of disks for fast-forward and rewind as well as normal play operation. In addition, we analyse the performance of the placement scheme in terms of miss ratio and load-balance. Moreover, we have confirmed that the proposed scheme is viable by experiments for the visual effect of implementing VCR operations.
The input scaling factors in a fuzzy control system are often used as a transformation from the real input data to the desired space. Sometimes, they are tuned for better performance just as the coefficients in a PID ...
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ISBN:
(纸本)0780325591
The input scaling factors in a fuzzy control system are often used as a transformation from the real input data to the desired space. Sometimes, they are tuned for better performance just as the coefficients in a PID controller. Theoretically, they are constant and should be adjusted for better performance while the operating point is changed. In this paper, the authors suggest nonlinear mapping functions to substitute the role of input scaling factors. The results show how the nonlinear mapping function work and the performance could be better by proper adjustment. It is also noticed that such mapping will change the shapes of the membership functions. That means one need not tune every membership function of linguistic variables, and just choosing a proper nonlinear mapping function could achieve the same effects. The authors use an inverted pendulum system to verify the results.
Many classes of simulation models require both arbitrary spatial and temporal precision and must address the complexities of a multitude of asynchronous pair-wise interactions occurring among a dynamic non-uniform dis...
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Many classes of simulation models require both arbitrary spatial and temporal precision and must address the complexities of a multitude of asynchronous pair-wise interactions occurring among a dynamic non-uniform distribution of numerous spatial components. Current discrete-event simulation methodologies do not adequately represent the spatial relationships present in many physical systems, additionally, alternative simulation strategies based on activity scanning methodologies, while potentially capable of providing the arbitrary precision required, typically offer the unacceptable computational complexities of O(N/sup 2/). A method to redress these issues is offered and discussed. The method presented dynamically sectors the trajectory space based on the number of spatial objects occupying a portion of the trajectory space (i.e. object space density). Additionally, the theoretical computational complexity associated with identifying spatial conflicts will be better than O(N/sup 2/) for a nonuniform distribution of N spatial objects. Preliminary data which supports theoretical arguments are offered.
Segmentation of images obtained from magnetic resonance (MR) imaging techniques is an important step in the analysis of MR images of the human body. The multi-spectral nature of MRI has been exploited in the past to o...
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Segmentation of images obtained from magnetic resonance (MR) imaging techniques is an important step in the analysis of MR images of the human body. The multi-spectral nature of MRI has been exploited in the past to obtain better performance in the segmentation process. The new emerging field of artificial neural networks promises to provide improved solutions for the pattern classification of medical images. The authors present the application of a learning vector quantization (LVQ) neural network for the multispectral supervised classification of MR images. The authors have modified the LVQ for better and more accurate classification. The authors compare the results using multispectral images to those with a single slice image. This comparison shows that the authors' method is insensitive to the gray-level variation of MR images between different slices. Also, a comparison with the classical maximum likelihood classifier (MLC) demonstrates the superiority of the authors' LVQ ANN approach.
This paper describes a computer vision system to count moving vehicles on roads. The system operates on a road image sequence captured during a time period and computes the total number of vehicles which passed the ro...
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ISBN:
(纸本)0780325591
This paper describes a computer vision system to count moving vehicles on roads. The system operates on a road image sequence captured during a time period and computes the total number of vehicles which passed the road during the period. Vehicle counting is accomplished by tracking vehicle movements within a tracking zone. The system consists of four image processing modules: (i) road structure extraction, (ii) vehicle detection, (iii) vehicle speed measurement, and (iv) vehicle movement tracking. The system limits the search area for vehicle detection using the road structure information and adjusts the vehicle movement tracking zone based on vehicle speeds. The primary feature of the system is efficient use of acquired knowledge about the road structure and vehicle speeds. The system was tested on a sequence of images of a road that has a medium-level traffic volume.
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