Theoretical variance #1 (Theo1) has been developed at NIST to improve the estimation of long-term frequency stability. Its square-root (Theo1-dev) has two significant improvements over the Allan deviation /spl sigma//...
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Theoretical variance #1 (Theo1) has been developed at NIST to improve the estimation of long-term frequency stability. Its square-root (Theo1-dev) has two significant improvements over the Allan deviation /spl sigma//sub y/(/spl tau/) (Adev) in estimating long-term frequency stability, in that: (1) it can evaluate frequency stability at averaging times 50% longer than those of Adev; and (2) it can estimate frequency stability with greater confidence than any other estimator. We discuss a method for determining the exact confidence intervals of Theo1, particularly useful for small sample sizes, using analytic techniques. The confidence intervals of Theo1 are narrower and less skewed (more symmetric) than confidence intervals based on chi-square.
This paper proposes a rapid application development framework for creating mobile Web services supported by a dynamic workflow engine that displays an interface depending on a specified workflow. The model leverages o...
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This paper proposes a rapid application development framework for creating mobile Web services supported by a dynamic workflow engine that displays an interface depending on a specified workflow. The model leverages on existing reference architectures, and open source standards, to create an interoperable, flexible and easy to implement development framework for creating mobile Web services. Our model is generic in nature to allow the development of Web services for a diverse range of scenarios. The dynamic workflow engine, residing on the client allows for easy updates on the server, and again caters to a diverse set of applications on the client side. The rapid application development model for mobile Web services proposed in this paper has been applied to a field service solution workflow and details on the implementation at both the client and the server are provided.
Considerable progress has been made in a linear optics approach to quantum computing but a number of challenges remain. It is shown that the quantum Zeno effect can be used to suppress the failure events that would ot...
Considerable progress has been made in a linear optics approach to quantum computing but a number of challenges remain. It is shown that the quantum Zeno effect can be used to suppress the failure events that would otherwise occur in these devices, which would make them deterministic and eliminate the need for ancilla photons and high‐efficiency detectors. The photons behave like non‐interacting fermions in the limit of a strong Zeno effect, which gives rise to a new paradigm for quantum computation.
Transactions have traditionally been applied to database systems in order to guarantee data consistency in the face of failures. We propose to expand the role of transactions into a general model for application recov...
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Transactions have traditionally been applied to database systems in order to guarantee data consistency in the face of failures. We propose to expand the role of transactions into a general model for application recovery. To achieve this goal, we use dynamic metaprogramming in order to inject the transactional recovery code at runtime, thus ensuring the system's portability through the use of a standard execution environment. Since this recovery method does not require programmer intervention, but, rather, transforms the code automatically, we believe it can potentially simplify the design and implementation of self-healing autonomic systems and reduce the potential for failure in large-scale distributed applications, thus realizing a central tenet of autonomic computing.
Leveraging grid computing technology, i.e. the visualization of distributed computing and data resources such as processing, network bandwidth and storage capacity to create a single system image, we present a Grid Ai...
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Leveraging grid computing technology, i.e. the visualization of distributed computing and data resources such as processing, network bandwidth and storage capacity to create a single system image, we present a Grid Air Quality Forecast System (G-AQFS). The modeling system consists of meteorological and dispersion models coupled in cascade. The computational workflow of the modeling system is defined by means of DAGs (direct acyclic graph). A simple system is presented to manage and schedule the computational grid resources. As case study the system has been applied over Salento area, in the Apulia region (South-eastern Italy), to simulate ground level ozone concentration. Model predictions have been compared with field measurements, with reasonable results.
One of the important issues about using renewable energy is the integration of dispersed generation in the distribution networks. Previous experience has shown that the integration of dispersed generation can improve ...
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ISBN:
(纸本)1860433650
One of the important issues about using renewable energy is the integration of dispersed generation in the distribution networks. Previous experience has shown that the integration of dispersed generation can improve voltage profile in the network, decrease loss etc. but can create safety and technical problems as well, This work report the application of the instantaneous space phasors and the instantaneous complex power in observing performances of the distribution networks with dispersed generators in steady state. New IEEE apparent power definition, the so called Buccholz-Goodhue apparent power, as well as new proposed power quality (oscillation) index in the three-phase distribution systems with unbalanced loads and dispersed generators, are applied. Results obtained from several case studies using IEEE 34 nodes test network are presented and discussed.
In This work the efficient algorithm for optimal cargo transport of N types of containers with limited ship capacity, minimizing the transport costs, is being developed. It can be applied for transport planning on a v...
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In This work the efficient algorithm for optimal cargo transport of N types of containers with limited ship capacity, minimizing the transport costs, is being developed. It can be applied for transport planning on a voyage route with multiple loading ports and multiple ports of discharge. The problem is solved with network optimization approach that can be seen as the minimum cost multicommodity flow problem (MCMCF). The implemented algorithm is able to find appropriate load planning sequence and to ensure minimal loading, discharging and transshipment costs, but with fulfillment of cargo demands in a number of destination ports on the voyage route. Application of this efficient tool may significantly reduce transport costs and ensure maximal possible profit. It may improve the operation process in maritime transport technology.
We consider security and trust issues in providing a fully open environment for global-scale roaming and mobility of commercial services across different mobile network domains. A delegation-based dynamic trust framew...
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We consider security and trust issues in providing a fully open environment for global-scale roaming and mobility of commercial services across different mobile network domains. A delegation-based dynamic trust framework is proposed as a solution. For scalable online service provisioning and business transactions, we suggest that service providers and consumers delegate selected tasks of security and trust management to trusted business partners who already have established reputations in the market. Then, we endorse dynamic, on-demand establishment of trust relationships amongst the delegates for broad availability of services across business boundaries. In order to address security concerns of service providers and consumers, security functions for trust, credibility, credential, and accountability management are incorporated into the framework. Finally, we show how the framework can be applied to 3G network environments.
The computation of optimal ∞ controllers with a prescribed order is important for their real-time implementation. This problem is well-known to be non-convex, and only algorithms that compute upper bounds on the glob...
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ISBN:
(纸本)0780383354
The computation of optimal ∞ controllers with a prescribed order is important for their real-time implementation. This problem is well-known to be non-convex, and only algorithms that compute upper bounds on the global optimal value are known. We present a method to compute lower bounds by re-formulating the problem as a robust analysis problem, where the controller variables are the "uncertain" parameters. This allows to apply the wide spectrum of robust analysis techniques to the fixed order controller design problem. The solution to the robust analysis problem is a global lower bound on the optimal closed loop ∞ performance. We construct a family of robust analysis problems and relax them to convex optimization problems using the S-procedure. The optimal values of this family converge from below to the globally optimal fixed order ∞-norm. This allows verification of global optimality of controllers. The number of complicating variables in our robust analysis problem is small if we optimize over a few controller parameters. The technique is therefore computationally feasible for optimization over few controller variables, e.g. PID-tuning of systems with large Mc-Millan degree. The method is applied to the tuning of two controller parameters of a 4-block ∞ design of an active suspension system, with a Mc-Millan degree of the plant of 27.
We proposed a novel method to extract a feature from time-series data by principal components analysis (PCA) with time-delay embedding, and showed its usefulness in pattern recognition. We first resampled from the ori...
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We proposed a novel method to extract a feature from time-series data by principal components analysis (PCA) with time-delay embedding, and showed its usefulness in pattern recognition. We first resampled from the original time series data and constructed a new data with time-delay embedding. Then we applied PCA to the new data to get a pseudo principal component (PPC), which now represents the newly constructed data and hence the original time series data as well. The PPC was used as a feature vector for the original data, and the pattern classification of was performed upon PPC. In order to improve the performance of the classification, we incorporated with the continuous wavelet transform (CWT) to the newly constructed data before we take the PPCs. The results showed that the new method is useful for classification tasks of time series data, and that the performance is improved when well combined with the CWT technique.
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