As a new unsupervised learning technique, manifold learning has captured the attention of many researchers in the field of machine learning and cognitive sciences. The major algorithms include Isometric mapping (ISOMA...
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As a new unsupervised learning technique, manifold learning has captured the attention of many researchers in the field of machine learning and cognitive sciences. The major algorithms include Isometric mapping (ISOMAP) and Locally Linear Embedding (LLE). The approaches can be used for discovering the intrinsic dimensions of nonlinear high-dimensional data effectively and aim researchers to analyze the data better. How to quantitatively analyze the relationship between the intrinsic dimensions and the observation space, however, has fewer reports. And thus further works in manifold learning may have suffered some difficulties. The paper focuses on two kinds of manifold learning algorithms (ISOMAP, LLE), and discusses magnification factors and principal spread directions from the observation space to the intrinsic low-dimensional space. Also the corresponding algorithm is proposed. Experiments show the effectiveness and advantages of the research.
Security critical systems must perform at the required security level, make effective use of available resources, and meet end-users expectations. Balancing these needs, and at the same time fulfilling budget and time...
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Security critical systems must perform at the required security level, make effective use of available resources, and meet end-users expectations. Balancing these needs, and at the same time fulfilling budget and time-to-market constraints, requires developers to design and evaluate alternative security treatment strategies. In this paper, the authors presented a development framework that utilizes Bayesian belief networks (BBN) and aspect-oriented modeling (AOM) for a cost-benefit trade-off analysis of treatment strategies. AOM allows developers to model pervasive security treatments separately from other system functionality. This eases the trade-off by making it possible to swap treatment strategies in and out when computing return on security investments (RoSI). The trade-off analysis is implemented using BBN, and RoSI is computed by estimating a set of variables describing properties of a treatment strategy. RoSI for each treatment strategy is then used as input to choice of design.
We present two approaches for automatically segmenting the spinal cord/canal from native CT images of the thorax region containing the spine. Different strategies are included to handle images where only part of the s...
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We are interested by contributing to stochastic problems of which the main distinction is that some tasks may create other tasks. In particular, we present a first approach which represents the problem by an acyclic g...
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We are interested by contributing to stochastic problems of which the main distinction is that some tasks may create other tasks. In particular, we present a first approach which represents the problem by an acyclic graph, and solves each node in a certain order so as to produce an optimal solution. Then, we detail a second algorithm, which solves each task separately, using the first approach, and where an on-line heuristic computes the global actions to execute when the state of a task changes.
Program affordability needs to be built-in at the initial concept formulation stage. For NASA's space exploration vision this is critical for long range sustainability of human presence in space. What is often ove...
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ISBN:
(纸本)1563477270
Program affordability needs to be built-in at the initial concept formulation stage. For NASA's space exploration vision this is critical for long range sustainability of human presence in space. What is often overlooked in the initial concept formulation of a large scale system endeavor such as NASA's Constellation program is the hidden cost of maintaining requisite operational safety margins and redundancy through adequate supply chain logistics. Ensuring adequate supply chain logistics necessitates the integration of operations and maintenance cycles. What enables this integration is the coordination and reconciliation across multiple equipment types of system health features and logistical information such as: (1) prognostic drivers from Integrated Vehicle Health Monitoring (IVHM) systems producing proactive condition-based "maintain me" demands, (2) maintenance management systems tracking usage and producing scheduled maintenance demands, (3) unscheduled maintenance demands resulting from any trouble reports entered by human observers of conditions missed by the IVHM system, and (4) implicit maintenance demands resulting from mission plans which require assignment of vehicular/robotic assets and consequently require assurance of the assigned assets' fitness for the intended tasks. In this paper we discuss how Coordinated Multi-source Maintenance on Demand (CMMD) technology, which is being is transitioned to the USMC Coherent Analytical Computing Environment (CACE) program and the Joint Strike Fighter Program, can be applied to the NASA domain, and its benefits in terms of mission affordability, operations efficiency and system health effectiveness. Using concepts derived from CMMD, we discuss the kind of IVHM capabilities needed to optimize multiple, parallel, yet inter-linked, operations-maintenance cycles, thereby optimizing program affordability while meeting specific mission supportability requirements across a broad range of mission scenarios.
engineering a large software project involves tracking the impact of development and maintenance changes on the software performance. An approach for tracking the impact is regression benchmarking, which involves auto...
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engineering a large software project involves tracking the impact of development and maintenance changes on the software performance. An approach for tracking the impact is regression benchmarking, which involves automated benchmarking and evaluation of performance at regular intervals. Regression benchmarking must tackle the nondeterminism inherent to contemporary computersystems and execution environments and the impact of the nondeterminism on the results. On the example of a fully automated regression benchmarking environment for the mono open-source project, we show how the problems associated with nondeterminism can be tackled using statistical methods.
This paper describes a comprehensive prototype of large-scale fault adaptive embedded software developed for the proposed Fermilab BTeV high energy physics experiment. Lightweight self-optimizing agents embedded withi...
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This paper describes a comprehensive prototype of large-scale fault adaptive embedded software developed for the proposed Fermilab BTeV high energy physics experiment. Lightweight self-optimizing agents embedded within Level 1 of the prototype are responsible for proactive and reactive monitoring and mitigation based on specified layers of competence. The agents are self-protecting, detecting cascading failures using a distributed approach. Adaptive, reconfigurable, and mobile objects for reliablility are designed to be self-configuring to adapt automatically to dynamically changing environments. These objects provide a self-healing layer with the ability to discover, diagnose, and react to discontinuities in real-time processing. A generic modeling environment was developed to facilitate design and implementation of hardware resource specifications, application data flow, and failure mitigation strategies. Level 1 of the planned BTeV trigger system alone will consist of 2500 DSPs, so the number of components and intractable fault scenarios involved make it impossible to design an 'expert system' that applies traditional centralized mitigative strategies based on rules capturing every possible system state. Instead, a distributed reactive approach is implemented using the tools and methodologies developed by the Real-Time Embedded systems group.
The Real Time Embedded systems (RTES) project was created to study the design and implementation of high-performance, heterogeneous, and fault-adaptive real time embedded systems. The driving application for this rese...
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This research proposes to modernize a legacy software system by using Web services as the main building blocks of the software reengineering. For this purpose, a legacy theorem proof checking and derivation tool calle...
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This research proposes to modernize a legacy software system by using Web services as the main building blocks of the software reengineering. For this purpose, a legacy theorem proof checking and derivation tool called Bertie3 is reengineered in terms of service-oriented architecture, service-oriented componentization, and external data representation and serialization. With the Web services of derivation checking engines and first-order markup languages, a minimal amount of development time can be spent working on well-known and well-developed components. More time can be spent updating the features that make the tool unique. This case study shows that modernizing a software system with Web services will allow the business components of the system to be easily expanded and integrated with other application components for future demands.
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