A numerical study of a thin-wire probe inside a slotted rectangular cavity is presented in this work. The results obtained with the 3-D full-wave method of moments based code FEKO is compared to the computations in Ra...
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A numerical study of a thin-wire probe inside a slotted rectangular cavity is presented in this work. The results obtained with the 3-D full-wave method of moments based code FEKO is compared to the computations in Ramani, V (2004). The motivation for this study stems from the wide usage of high power RF excitations in electronic systems. Electromagnetic coupling and interference [Christopoulos C. et al., 2001] in electronic devices (computers, sensors, control and communication devices, etc.) is of increasing concern due to the presence of both intentional and un-intentional internal/external electromagnetic sources. After the preliminary comparison of results we introduce a finite conductivity into the walls of the cavity to resemble more practical problems for simulations with FEKO.
In this paper we report on how aspect-oriented programming (AOP), using AspectJ, can be employed to automatically and efficiently instrument contracts and invariants in Java. The paper focuses on the templates to inst...
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In this paper we report on how aspect-oriented programming (AOP), using AspectJ, can be employed to automatically and efficiently instrument contracts and invariants in Java. The paper focuses on the templates to instrument preconditions, postconditions, and class invariants, and the necessary instrumentation for compliance-checking to the Liskov substitution principle.
A mobile multi-agent system is proposed to create solutions for the university course timetabling problem. It is composed of four kinds of agents: (mobile) Course Agents, and (stationary) Signboard, Publisher and Inte...
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The discovery of the association between terms and a specified topic is a difficult task. A new data mining technique, topic-oriented mining and reasoning, is presented for this task. The technique consists of two thr...
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The discovery of the association between terms and a specified topic is a difficult task. A new data mining technique, topic-oriented mining and reasoning, is presented for this task. The technique consists of two threads: pattern mining and pattern reasoning. Pattern mining means the automatic discovery of interesting user topic models. A novel topic structure is presented for this thread. Pattern reasoning means the utilization and maintenance of the interesting user topic models to determine if an input data is relevant to the specified topic. The innovation for this thread is the use of meta-knowledge for the discovered knowledge. In this way the system can trace errors to update inadequate subtopics in the user topic model. The experimental results show that all objectives we expect for the topic-oriented model are achievable.
Evolutionary computation (EC) has been successfully applied to a wide range of design problems. There has also been an abundant amount of work in applying interactive ECs in the design of displays, robot behavior, bit...
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Evolutionary computation (EC) has been successfully applied to a wide range of design problems. There has also been an abundant amount of work in applying interactive ECs in the design of displays, robot behavior, bitmaps, etc. In the EC literature, one can also see a number of successful design applications of distributed ECs. However, to date, there has been no research in the area of interactive distributed ECs. In this paper, we present an interactive distributed evolutionary algorithm (IDEA) for the design of simple emoticons. We will discuss two ways that our IDEA is currently being used including the areas of EC education and Human Factors.
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.
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