Purpose: The analysis of syndrome distribution and the association between symptom((signs))-syndrome in chronic gastritis (CG) patients can provide references for research about Traditional Chinese Medicine (TCM) diag...
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ISBN:
(纸本)9781849195386
Purpose: The analysis of syndrome distribution and the association between symptom((signs))-syndrome in chronic gastritis (CG) patients can provide references for research about Traditional Chinese Medicine (TCM) diagnosis and treatment of CG. Method: This paper applies the investigation method of clinical epidemiology, adopts probability statistics method and comes up with the concept of associated density to conduct association analysis of symptom-syndrome. Result: In the distribution of syndromes patients who have a single syndrome occupy 64.7% of the whole sample;some symptoms have been selected out, of which the associated density is more than 0.6. Conclusion: Through this comparison of the values, we found the obvious one-way relationship of the symptoms (signs) and syndromes, and the results are in line with traditional Chinese medicine theory. This method effectively complements and supports traditional Chinese medicine point of view and hypothesis.
A covariance matching method for continuous-time errors-in-variables system identification from discrete-time data is analyzed. The asymptotic normalized covariance matrix, valid for a large number of data and a small...
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Electrochemical dual layer capacitors, also known by their market names Supercapacitors and Ultracapacitors are perspective technology for many uses, for instance in power saving circuits for electric propulsion syste...
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Electrochemical dual layer capacitors, also known by their market names Supercapacitors and Ultracapacitors are perspective technology for many uses, for instance in power saving circuits for electric propulsion systems, short-term energy storage systems, systems for extending battery lifetime and other similar uses. Although they can be used connected directly to a power converter DC link, in most cases they are connected to the DC link through a separate power converter. In use, such an EDLC and power converter assembly, due to EDLC specifics, must reliably operate in numerous operating points, unlike a typical power electronic converter. Such a power converter operation entails many control issues. Some of them are considered in this paper.
This paper presents a novel method for Bayesian bearing-only tracking. Unlike the classical approaches, which involve using Gaussian distribution, the tracking procedure is completely covered with the von Mises distri...
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ISBN:
(纸本)9781467317375
This paper presents a novel method for Bayesian bearing-only tracking. Unlike the classical approaches, which involve using Gaussian distribution, the tracking procedure is completely covered with the von Mises distribution, including state representation, transitional probability, and measurement model, since it captures and models well the peculiarities of directional data. The state is represented with a mixture of von Mises distributions, thus offering advantages of being able to model multimodal distributions, handle nonlinear state transition and measurement models, and to completely cover the whole state space, all with a modest number of parameters. The tracking procedure is solved by convolution with a von Mises distribution (prediction step) and multiplication with a mixture representing the measurement model (update step). Since in the update step the number of mixture components grows exponentially, a method is presented for component reduction of a von Mises mixture. Furthermore, a closed-form solution is derived for quadratic Rényi entropy of the von Mises mixture. The algorithm is tested and compared to a particle filter representation in a speaker tracking scenario on a synthetic data set and real-world recordings. The results supported the proposed approach and showed similar performance to the particle filter.
In this work, we propose a recursive local linear estimator (RLLE) for identification of nonlinear autoregressive systems with exogenous inputs, along with an analysis of its strong consistency and asymptotical mean s...
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The effects of the source/drain (S/D) to gate overlap on the electrical characteristics of pentacene organic thin-film transistors (OTFTs) are reported. The S/D to gate overlap dimension was varied by adjusting the ga...
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This paper is concerned with the finite-horizon recursive filtering problem for a class of nonlinear time-varying systems with missing measurements. The missing measurements are modeled by a series of mutually indepen...
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Two-axis pan and tilt systems are widely used in surveillance applications for high accuracy positioning of sensor payloads such as cameras and laser pointers. In order to develop advanced control algorithms to improv...
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Two-axis pan and tilt systems are widely used in surveillance applications for high accuracy positioning of sensor payloads such as cameras and laser pointers. In order to develop advanced control algorithms to improve the performance of these systems, a model of the system must be developed. This model should include the dynamics of the system to include effects such as compliance and account for friction effects in the drive. This paper discusses the development of the overall model of the system using National Instruments LabVIEW, and in particular, the models for friction and the drive train that will be used.
The dynamic nature of a system gives rise to dynamical features of epidemic spreading, such as oscillation and bistability. In this paper, by studying the epidemic spreading in growing networks, in which susceptible n...
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The dynamic nature of a system gives rise to dynamical features of epidemic spreading, such as oscillation and bistability. In this paper, by studying the epidemic spreading in growing networks, in which susceptible nodes may adaptively break the connections with infected ones yet avoid being isolated, we reveal a phenomenon, epidemic reemergence, where the number of infected nodes is incubated at a low level for a long time and then erupts for a short time. The process may repeat several times before the infection finally vanishes. Simulation results show that all three factors, namely the network growth, the connection breaking, and the isolation avoidance, are necessary for epidemic reemergence to happen. We present a simple theoretical analysis to explain the process of reemergence in detail. Our study may offer some useful insights, helping explain the phenomenon of repeated epidemic explosions.
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