In order to deal with the conflicts between broad spectral region and high resolution in compact spectrometers based on a flat field concave holographic grating and line array CCD, we present a simple and practical method to design a flat field concave holographic grating that is capable of imaging a broad spectral region at a moderately high resolution. First, we discuss the principle of realizing a broad spectral region and moderately high resolution. Second, we provide the practical method to realize our ideas, in which Namioka grating theory, a genetic algorithm, and ZEMAX are used to reach this purpose. Finally, a near-normal-incidence example modeled in ZEMAX is shown to verify our ideas. The results show that our work probably has a general applicability in compact spectrometers with a broad spectral region and moderately high resolution.
Abstract-In HMM risk assessment of network, relationship between the nodes is the key part to compute the state transition matrix. The change of IDS alarm level has property of randomness. To calculate the value of the IDS alarm as the input of HMM is based on the Bayesian algorithm model. Using HMM model, probability of attack successful is computed when length of attack sequence is varied. The experimental evidences show new method is veracity and validity.
When the topology of data network in power grid was destroy, the system still need to provide intrusion tolerance service. The trust values relationship of the nodes in data network need be calculated. The trust value of the upper and lower limit can be deduced and adjusted to eliminate the problem of over-reliance on threshold. And the introduction of confidence values to assess the quality of the trust value. A recursive algorithm is used to obtain the average of the trust data to compute confidence values. The experimental result proves the veracity and validity of the method.
When the topology of data network in power grid was destroy, the system still need to provide intrusion tolerance service. The trust values relationship of the nodes in data network need be calculated. The trust value of the upper and lower limit can be deduced and adjusted to eliminate the problem of over-reliance on threshold. And the introduction of confidence values to assess the quality of the trust value. A recursive algorithm is used to obtain the average of the trust data to compute confidence values. The experimental result proves the veracity and validity of the method.
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