The maturing of telecommunication technologies has ushered in a whole new era of applications and services in the health care environment. Teleworking, teleconsultation, multimedia conferencing and medical data distri...
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The maturing of telecommunication technologies has ushered in a whole new era of applications and services in the health care environment. Teleworking, teleconsultation, multimedia conferencing and medical data distribution are rapidly becoming commonplace in clinical practice. As a result, a set of problems arises, concerning data confidentiality and integrity. Public computer networks, such as the emerging ISDN technology, are vulnerable to eavesdropping. Therefore it is important for telemedicine applications to employ end-re-end encryption mechanisms securing the data channel from unauthorized access or modification. We propose a network access and encryption system that is both economical and easily implemented for integration in developing or existing applications, using well-known and thoroughly tested encryption algorithms. Public-key cryptography is used for session-key exchange, while symmetric algorithms are used for bulk encryption. Mechanisms for session-key generation and exchange are also provided.
A 1.5V resistive fuse for image smoothing and segmentation using bulk-driven MOSFETs is presented. The circuit switches on only if the differential voltage applied across its input terminals is less than a set voltage...
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A 1.5V resistive fuse for image smoothing and segmentation using bulk-driven MOSFETs is presented. The circuit switches on only if the differential voltage applied across its input terminals is less than a set voltage;it switches off if the differential voltage is higher than the set value. The useful operation range of the circuit is 0.4V with a supply voltage of 1.5V and threshold voltages of V-Tn = 0.828V and V-Tp = -0.56V for n and g channel MOSFETs, respectively.
Increasingly, feedback of measured run-time information is being used in the optimization of computation execution. Because of this, the need for a model relating the static view of a computation to its runtime varian...
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New shift-invariant distortion-invariant Synthetic Aperture Radar (SAR) filters for detection are described. They employ new modified Minimum Noise and Correlation Energy (MINACE) filters. Test results are provided fo...
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New shift-invariant distortion-invariant Synthetic Aperture Radar (SAR) filters for detection are described. They employ new modified Minimum Noise and Correlation Energy (MINACE) filters. Test results are provided for real SAR data with 360 degrees aspect views of two different objects and for 100 real SAR clutter chips (natural and man-made) that passed the second stage of the Lincoln laboratory's SAR processor. We obtained high detection rates P-D=100% and few false alarms P-FA less than or equal to 0.82% using only three filters per object class. The shift-invariance of the filters allow their use as adjuncts for all stages (detection, discrimination, classification) of a SAR image processor. Classification results are also briefly reported. Copyright (C) 1996 Pattern Recognition Society.
A system for specification and proof of distributed programs is presented. The method is based directly on the partial order of local states (poset) and avoids the notions of time and simultaneity. Programs are specif...
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A system for specification and proof of distributed programs is presented. The method is based directly on the partial order of local states (poset) and avoids the notions of time and simultaneity. Programs are specified by documenting the relationship between local states which are adjacent to each other in the poset. Program properties are defined by stating properties of the poset. Many program properties can be expressed succinctly and elegantly using this method because poset properties inherently account for varying processor execution speeds. The system utilizes a proof technique which uses induction on the complement of the causally precedes relation and is shown to be useful in proving poset properties. We demonstrate the system on three example algorithms: vector clocks, mutual exclusion, and direct dependency clocks.
In this paper, we present a new system to segment and label CT/MRI Brain slices using feature extraction and unsupervised clustering. In this technique, each voxel is assigned a feature pattern consisting of a scaled ...
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ISBN:
(纸本)0780341236
In this paper, we present a new system to segment and label CT/MRI Brain slices using feature extraction and unsupervised clustering. In this technique, each voxel is assigned a feature pattern consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is then assigned to a specific region using a two-stage neural network system. The first stage is a self-organizing principal components analysis (SOPCA) network that is used to project the feature vector onto its leading principal axes found by using principal components analysis. This step provides an effective basis for feature extraction. The second stage consists of a self-organizing feature map (SOFM) which will automatically cluster the input vector into different regions. The optimum number of regions (clusters) is obtained by a model fitting approach. Finally, a 3D connected component labeling algorithm is applied to ensure region connectivity. Implementation and performance of this technique are presented. Compared to other approaches, the new system is more accurate in extracting 3D anatomical structures of the brain, and can be apdated to real-time imaging scenarios.
This paper describes a procedure for stereo video production using model-based processing of both left and right channels of a stereoscopic image sequence. The proposed scheme uses an original video and the first / ba...
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Increasingly, feedback of measured run-time information is being used in the optimization of computation execution. This paper introduces a model relating the static view of a computation to its run-time variance that...
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Increasingly, feedback of measured run-time information is being used in the optimization of computation execution. This paper introduces a model relating the static view of a computation to its run-time variance that is useful in this context. A notion of uncertainty is then used to provide bounds on key scheduling parameters of the run-time computation. To illustrate the relationship between fidelity in measured information and minimum schedulable, grain size, we apply the bounds to three existing parallel architectures for the case of run-time variance caused by monitoring intrusion. We also outline a hybrid static-dynamic scheduling paradigm-SEDIA-that uses the model of uncertainty to optimize computation for execution in the presence of run-time variance from sources other than monitoring intrusion.
A large collection of texts may be reached through the Internet and this provides a powerful platform from which common-sense knowledge may be gathered. This paper presents a system that contains a core knowledge base...
In a dedicated mixed-machine heterogeneous computing (HC) system, an application program may be decomposed into subtasks, then each subtask assigned to the machine where it is best suited for execution. Subtask data r...
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In a dedicated mixed-machine heterogeneous computing (HC) system, an application program may be decomposed into subtasks, then each subtask assigned to the machine where it is best suited for execution. Subtask data relocation is defined as selecting the sources for their needed data items. This study focuses on theoretical issues for data relocation using a stochastic HC model. It is assumed that multiple independent subtasks of an application program can be executed concurrently on different machines whenever possible. A stochastic model for HC is proposed, in which the computation times of subtasks and communication times for inter-machine data transfers can be random variables. The optimization problem for finding the optimal matching, scheduling, and data relocation schemes to minimize the total execution time of an application program is defined based on this stochastic HC model. The optimization criteria and search space for the above optimization problem are described. It is proven that a greedy algorithm based approach will generate the optimal data relocation scheme with respect to any fixed matching and scheduling schemes. This result indicates that a greedy algorithm based approach is the best strategy for developing data relocation heuristics in practice.
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