卷积积分和拉普拉斯变换在一阶电路中的应用

电路的任意激励的零状态响应,可以用卷积积分和拉普拉斯交换的方法求解。本文通过两个一阶电路的实例,阐述了两种方法的应用特点。     

Theory and techniques of data mining in CGF behavior modeling

For the large quantity of data,rules and models generated in the course of computer generated forces (CGFs) behavior modeling,the common analytical methods are statistical methods based on the tactical rules,tactical doctrine and empirical knowledge.However,from the viewpoint of data mining,we can find many of these analytical methods are also each-and-every different data mining methods.In this paper,we survey the data mining theory and techniques that have appeared in the course of CGF behavior modeling f...     

Action categorization with modified hidden conditional random field

In this paper, we present a method for action categorization with a modified hidden conditional random field (HCRF). Specifically, effective silhouette-based action features are extracted using motion moments and spectrum of chain code. We formulate a modified HCRF (mHCRF) to have a guaranteed global optimum in the modelling of the temporal action dependencies after the HMM pathing stage. Experimental results on action categorization using this model are compared favorably against several existing model-based methods including GMM, SVM, Logistic Regression, HMM, CRF and HCRF.     

Stochastic approximation learning for mixtures of multivariate elliptical distributions

Most of the current approaches to mixture modeling consider mixture components from a few families of probability distributions, in particular from the Gaussian family. The reasons of these preferences can be traced to their training algorithms, typically versions of the Expectation-Maximization (EM) method. The re-estimation equations needed by this method become very complex as the mixture components depart from the simplest cases. Here we propose to use a stochastic approximation method for probabilistic mixture learning. Under this method it is straightforward to train mixtures composed by a wide range of mixture components from different families. Hence, it is a flexible alternative for mixture learning. Experimental results are presented to show the probability density and missing value estimation capabilities of our proposal.     

A compensation cost analysis of service-aggregate transaction for DTNs clients

Clients from Delay Tolerant Networks (DTNs) might encounter overtime exceptions when they aggregate autonomic commercial web service references to form an all-or-nothing transaction. Such exceptions may cause extra overhead—“compensation cost” when aborting transactions. Regarding the delay-related characteristics of DTNs, this paper models the expected compensation cost (ECC) for the schedulings of commit-requests, presents a calculability analysis for quantitative ECC prediction, and explores the limitation of ECC’s probabilistic prediction accordingly. The analysis is based on the timed-2PC plus compensation (t2PC+) protocol and the multi-step price tag pattern, which is verified conditionally by simulation tests through randomly-chosen severely-fluctuant samplings of compensation cost and delays. The ultimate target of this work is to demonstrate the high complexity, and in particular, the uncertainty of ECC predictions due to the randomicity of DTNs’ delays.     

Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains

This study presents monthly estimates of groundwater anomalies in a large river basin dominated by extensive floodplains, the Negro River Basin, based on the synergistic analysis using multisatellite observations and hydrological models. For the period 2003-2004, changes in water stored in the aquifer is isolated from the total water storage measured by GRACE by removing contributions of both the surface reservoir, derived from satellite imagery and radar altimetry, and the root zone reservoir simulated by WGHM and LaD hydrological models. The groundwater anomalies show a realistic spatial pattern compared with the hydrogeological map of the basin, and similar temporal variations to local in situ groundwater observations and altimetry-derived level height measurements. Results highlight the potential of combining multiple satellite techniques with hydrological modeling to estimate the evolution of groundwater storage.     

Towards inverse modeling of turbidity currents: The inverse lock-exchange problem

A new approach is introduced for turbidite modeling, leveraging the potential of computational fluid dynamics methods to simulate the flow processes that led to turbidite formation. The practical use of numerical flow simulation for the purpose of turbidite modeling so far is hindered by the need to specify parameters and initial flow conditions that are a priori unknown. The present study proposes a method to determine optimal simulation parameters via an automated optimization process. An iterative procedure matches deposit predictions from successive flow simulations against available localized reference data, as in practice may be obtained from well logs, and aims at convergence towards the best-fit scenario. The final result is a prediction of the entire deposit thickness and local grain size distribution. The optimization strategy is based on a derivative-free, surrogate-based technique. Direct numerical simulations are performed to compute the flow dynamics. A proof of concept is successfully conducted for the simple test case of a two-dimensional lock-exchange turbidity current. The optimization approach is demonstrated to accurately retrieve the initial conditions used in a reference calculation.     

A new package for simulating periodic boundary conditions in MODFLOW and SEAWAT

Modeling of coastal groundwater systems is a challenging problem due to their highly dynamic boundary conditions and the coupling between the equations for groundwater flow and solute transport. A growing number of publications on aquifers subject to tides have demonstrated various modeling approaches, ranging from analytical solutions to comprehensive numerical models. The United States Geological Survey code SEAWAT has been a popular choice in studies of this type. Although SEAWAT allows the incorporation of time-variant boundary conditions, the implementation of tidal boundaries is not straightforward, especially when a seepage face develops during falling tide. Here, a new package is presented, called the periodic boundary condition (PBC) package, that can be incorporated into MODFLOW and SEAWAT to overcome the difficulties encountered with tidal boundaries. It dynamically updates the boundary conditions for head and concentration during the simulation depending on a user-defined tidal signal and allows for the development of a seepage face. The package has been verified by comparing it to four different published models of tidally influenced groundwater systems of varying complexity. Excellent agreement was obtained in all cases. The new package is an important extension to the existing capabilities of MODFLOW and SEAWAT with respect to simulating periodic boundary conditions.