基于推理注意力机制的二阶段网络图像修复

现有的图像修复方法在处理大面积缺失或高度纹理化的图像时，通常会产生扭曲的结构或与周围区域不一致的模糊纹理，无法重建合理的图像结构。为此，提出了一种基于推理注意力机制的二阶段网络图像修复方法。首先通过边缘生成网络生成合理的幻觉边缘信息，然后在图像补全网络完成图像的重建工作。为了进一步生成视觉效果更逼真的图像，提高图像修复的精确度，在图像补全网络采用推理注意力机制，有效控制了生成特征的不一致性，从而生成更有效的信息。所提方法在多个数据集上进行了实验验证，结果表明该图像修复方法的结构相似性指数达到了88.9%，峰值信噪比达到了25.56 dB，与现有的图像修复方法相比，该方法具有更高的图像修复精确度，生成的图像更逼真。     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

考虑不确定性的大坝监测信息异常诊断方法及应用

大坝监测资料分析是一个充满不确定性的复杂非线性问题,常规的分析方法较少考虑监测信息中的不确定性问题,导致分析结果的合理性存疑。因此,基于信息熵理论的重要指标——近似熵研究大坝监测信息中的不确定性问题,利用实际监测数据选取近似熵算法的关键参数,进而评估大坝的运行状态。通过分析混凝土坝坝顶水平位移和土石坝测压管水位,发现近似熵算法能在若干监测信息不确定性条件下较有效地识别大坝监测数据的异常。     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

基于改进模糊有色Petri网的综合能源系统能耗动态过程模型及应用

针对综合能源系统在供能过程中的能耗动态特点,通过改进的Petri网方法,根据特定的建模规则,建立了一种基于改进模糊有色Petri网的综合能源系统能耗动态过程模型,并在Stateflow平台上利用实际算例进行了仿真分析。结果表明,所建模型合理、有效,有一定的分析计算特性和图形化表现能力,为进一步对系统需求侧规划和多能设备的合理匹配提供了理论基础和技术支持。     

三维圆弧型井眼轨道设计模型的拟解析解

为了研究三维圆弧型井眼轨道设计方程组是否存在解析解以及如何有效求解，使用消去法从多元非线性方程组中推导出其中的某个未知数满足一个特征多项式方程，并且证明了该方程组的拟解析解可以由特征多项式方程的实数根和已知设计参数构成的解析公式计算得到；如果极点多项式非恒等于0，则当特征多项式次数不超过5时，如果有解则为解析解，否则为数值解。通过使用C++类实现多项式加减法、乘法的计算方法，提出了多项式实数根的分隔算法、并用二分法快速求解出多项式全部实数根的计算方案。该方法在数学上经严格推导，计算方案简洁、稳健，在三维井眼轨道设计、智能钻井定向控制中具有应用价值。     

借鉴逻辑学方法提高临床思维能力

目的：正确的临床决策必须遵循逻辑规律。本文旨在剖析用逻辑学方法提高临床思维训练的可行性。方法：进行临床医学和逻辑学的跨学科整合研究，重点探讨三类常用逻辑方法：演绎法、归纳法和溯因推理法在临床实践中的应用。 结果：发现演绎、溯因和归纳推理分别对应于：①评估临床资料；②提出诊断假设和③完善初步诊断这三种临床思维活动。发现并概括临床思维和医疗实践中包含的逻辑规律，有助于提高思维的准确性、有效性和清晰性。结论：掌握临床思维的逻辑规律，并在中针对性地加以应用，有助于培养医生的思维和决策能力。