曝气池中气液两相流粒子图像测速技术

在粒子图像测速原理的基础上研究了基于快速傅立叶变换的粒子图像测速算法，并编制算法程序进行验证。通过试验研究了气液两相流在曝气池试验装置中的流动情况，应用粒子图像测速技术对装置中3种状态下气液两相流的运动参量进行测量，获得了各种流体运动参数，并应用粒子图像测速程序进行计算分析。试验结果表明当气液两相流处于状态3时，气泡在装置中具有最长的停留时间和较大的速度紊动强度，氧转移速率和效率大大提高，这为曝气池选型提供了依据。     

兆瓦级锂冷空间核反应堆电源方案设计与研发进展

空间核反应堆电源因具有能量密度大、输出功率高、持续时间长、环境适应性强等优势,是未来大功率长寿期航天任务及深空探测任务能源供应的优选路线.本文在分析兆瓦级空间堆电源研发需求与选型特点的基础上,提出并设计了一套兆瓦级小型锂冷空间堆电源技术方案,该方案采用锂冷反应堆与布雷顿发电系统耦合,具有轻量化、长寿命等特点.本文针对该方案梳理了所涉及的关键技术,介绍了在技术分析论证、相关验证样机和实验平台研制的进展情况,并在此基础上提出我国未来发展大功率空间堆电源的建议.     

火星探测轨道的数值分析

对2009年10月发射嫦娥02星进行环火星探测的过渡轨道进行初步搜索分析.提出发射时机和运载火箭选型的意见,并从轨道机动的角度提出对探测器设计的基本要求.     

遗传算法与最小元素法相结合在物流中心选址中的应用

针对单一品种货物的物流中心的选址问题，采用一种将单亲遗传算法与最小元素法相结合的方法来处理此类问题，并且对遗传算法做了相应的改进，为了避免遗传算法的“早熟”现象，提高收敛速度，采用优化初始种群，自动调整交叉率和变异率的方法。采用这种混合算法的好处是削弱遗传算法的随机性，加快收敛，使算法的效率得到了提高。     

法国科学家利用电化学技术使浸在海水中的舷窗不受污染

采用光学系统工作的深海观测设备所遇到的难题之一，便是观测口上容易结一层生物膜，影响视线。为避免此类污染物的形成，法国国家科学研究中心(CNRS)和“电化学接口和系统试验室”(LISE)的研究人员，合作开发出一种很有前途的电化学保护技术。其原理是采用海水的受控电解，在需要保护的观测孔上产自由氯。有了这种环保的方法，深海摄     

基于有限差分的直接顶稳定性影响因素的数值模拟分析

基于有限差分计算方法,利用flac2d有限差分数值模拟软件,在不考虑节理间距的情况下对不同结构参数和不同力学参数的直接顶垮落过程进行数值模拟;分析直接顶力学参教、结构参数与直接顶稳定性的数值关系;并得出了直接顶的力学参数和结构参数对直接顶稳定性的影响结果,为制定岩层控制措施,支架选型及支护参数以及直接顶的稳定性分类提供一定的理论依据.     

基于挑战——响应的安全协议分析

安全协议的本质是协议主体采用密码学方法通过挑战一响应来对协议其他方的存在做出判断，同时完成一些数据如会话密钥的协商．大部分国内外现有的分析方法或者采用状态检测等定理证明技术，或者采用认证逻辑等推理技术，存在着分析能力与可操作性之间的矛盾．为了解决这个问题，文中提出一种新的安全协议保密性和关联性的分析方法，该方法基于线空间模型理论给出了协议保密目标和认证目标的形式化定义，采用认证逻辑作为基础分析手段．保密性分析被分解为显式泄密和隐性泄密两种情况，其中隐性泄密分析依赖于关联性的判断，而关联性的分析被总结为Strand的存在关系和参数一致性分析的问题．新的分析方法既具有线空间模型的分析能力，又具有认证逻辑的易用性．     

马氏体相变的形核机制

利用透射电子显微镜原位拉伸实验观察Ｆｅ－ＮｉＶ－Ｃ合金中α马氏体的形核过程，并利用原位冷却跟踪实验证实所观察到的特殊的位错组态是马氏体核胚，在相变过程中，一个核胚转变为一个小叶片，一群平行的叶片组成一个大马氏体片。马氏体相变过程是往复切变过程，相邻核胚往往以相反的方向切变，采用约化胞方法确定观察到的马氏体核胚的晶体结构为面心正交，采用马氏体形核机制解释了马氏体核胚晶体结构。晶体学分析证实了所提出的     

汽车动力学控制系统研究进展

汽车动力学控制系统(VDC)是采用电子控制技术提高汽车主动安全性能的重要研究成果，是当前汽车动力学的主要的研究领域。通过对这一核心技术的研究，系统总结了VDC研究的关键问题：系统建模、控制策略、控制算法、控制器的开发研究、故障保护等，并提出了这一领域进一步研究的方向。     

基于FPGA的音频分析系统实现

采用Altera公司的FPGA芯片EP2C20作为控制和运算核心，实现对频率范围在20Hz～20kHz的音频信号分析和测试。采用FFT算法对音频信号进行频谱分析和计算处理，实现失真度分析，并完成信号总功率、各分量频率、周期等参数分析测量。采用TFT-LCD作为显示终端，能够直观显示功率谱曲线和各测试参数值。通过软件分析对比测试发现，该系统实时性强，测量准确度高，误差优于0．3％，可以有效完成音频信号分析和处理。     

理想解法与灰色关联度相结合的宜居城市评价决策模型研究——以四川省地级市为例

本文设计了宜居城市评价指标体系、通过构建理想方法和灰色关联度的决策模型来评价城市适宜度.并以四川省10个地级市为例进行了城市人居适宜度的评价、排序和分析.     

The futility of decision making research

We have each spent more than 50 years doing research that has had little impact. Even more lamentable is that our field, judgment and decision making (JDM), has on the whole had little impact during that span. We attribute that failure to the use of methodologies that emphasize testing models rather than looking for differences in behavior. The “cognitive revolution” led the field astray, toward the goal of studying model fit rather than comparing observable results. With modeling as the goal, experimentation was stultified. Simple tasks became dominant. Although a poor metaphor for real decision making, the gambling paradigm has lasted forever because the inputs to the decision are known to the researcher and thus easily modeled.     

Using a heterogeneous multinomial probit model with a neural net extension to model brand choice

The multinomial probit model introduced here combines heterogeneity across households with flexibility of the (deterministic) utility function. To achieve flexibility deterministic utility is approximated by a neural net of the multilayer perceptron type. A Markov Chain Monte Carlo method serves to estimate heterogeneous multinomial probit models which fulfill economic restrictions on signs of (marginal) effects of predictors (e.g., negative for price). For empirical choice data the heterogeneous multinomial probit model extended by a multilayer perceptron clearly outperforms all the other models studied. Moreover, replacing homogeneous by heterogeneous reference price mechanisms and thus allowing price expectations to be formed differently across households also leads to better model performance. Mean utility differences and mean elasticities w.r.t. price and price deviation from reference price demonstrate that models with linear utility and nonlinear utility approximated by a multilayer perceptron lead to very different implications for managerial decision making. Copyright © 2007 John Wiley & Sons, Ltd.     

Patient participation in the clinical encounter and clinical practice guidelines: The case of patients’ participation in a GRADEd world

It is widely acknowledged that the patient's perspective should be considered when making decisions about how her care will be managed. Patient participation in the decision making process may play an important role in bringing to light and incorporating her perspective. The GRADE framework is touted as an evidence-based process for determining recommendations for clinical practice; i.e. determining how care ought to be managed. GRADE recommendations are categorized as “strong” or “weak” based on several factors, including the “values and preferences” of a “typical” patient. The strength of the recommendation also provides instruction to the clinician about when and how patients should participate in the clinical encounter, and thus whether an individual patient's values and preferences will be heard in her clinical encounter. That is, a “strong” recommendation encourages “paternalism” and a “weak” recommendation encourages shared decision making. We argue that adoption of the GRADE framework is problematic to patient participation and may result in care that is not respectful of the individual patient's values and preferences. We argue that the root of the problem is the conception of “values and preferences” in GRADE – the framework favours population thinking (e.g. “typical” patient “values and preferences”), despite the fact that “values and preferences” are individual in the sense that they are deeply personal. We also show that tying the strength of a recommendation to a model of decision making (paternalism or shared decision making) constrains patient participation and is not justified (theoretically and/or empirically) in the GRADE literature.     

Criterion-referenced judgemental forecasting models

Human judgements are usually made with reference to a criteria such as cost or profit. When making a judgement model for such a decision, the ideal is for the model to yield near-optimal results in terms of the criteria. This article starts with the theory behind concave criteria and then develops a mathematical argument which gives guidance to judgemental model building. This guidance departs from the conventional wisdom of using only R-squared in model selection.     

Evaluation of the going-concern status for companies: An ensemble framework-based model

Issuing a going-concern opinion is a difficult and complex task for auditors. The auditors have to take into account different critical factors in order to make the right decision based on information obtained from the auditing process. This study adopts the so-called “random forest” approach (based on the ensemble method) to assist auditors in making such a decision. To investigate the corresponding effect of the proposed approach, we conduct a series of experiments and a performance comparison. The results show that the random forest method outperforms the baseline methods in terms of the accuracy rate, ROC area, kappa value, type II error, precision, and recall rate. The proposed approach is proven to be more accurate and stable than previous methods.     

不完全信息下多属性决策的证据推理方法

针对权系数未知、属性值具有缺失的不完全信息下多属性决策问题,给出了一种基于证据推理的方法。该方法通过对决策矩阵的规范化处理、不同属性下焦元的确定及评价值计算,获得证据的基本概率分配,然后利用证据合成,并通过信任区间的计算与排序,获得整个方案集的排序。最终,实例表明了该方法的有效性和可行性。     

Decision‐Based Forecast Evaluation of UK Interest Rate Predictability

This paper illustrates the importance of density forecasting and forecast evaluation in portfolio decision making. The decision‐making environment is fully described for an investor seeking to optimally allocate her portfolio between long and short Treasury bills, over investment horizons of up to 2 years. We examine the impact of parameter uncertainty and predictability in bond returns on the investor's allocation and we describe how the forecasts are computed and used in this context. Both statistical and decision‐based criteria are used to assess the predictability of returns. Our results show sensitivity to the evaluation criterion used and, in the context of investment decision making under an economic value criterion, we find some potential gain for the investor from assuming predictability. Copyright © 2015 John Wiley & Sons, Ltd.     

资源型供应链议价的双体博弈分析

利用双体博弈理论,对资源型供应链中的议价问题展开研究。通过建立一定市场结构对应的双体博弈模型,分析影响议价结果的因素,探索供应商的竞争优势及其最优议价策略。研究结果对现实资源型供应链中存在的特有现象提供了理论解释,并表明和描述了下游企业的权威及其外部机会对议价结果的重要影响。研究结果不仅为企业决策提供了理论指导,而且为最大化资源的效能和促使相关企业承担社会责任起到积极作用。     

Impact of corrections for dynamic selection bias on forecasts of retention behavior

We investigate the impact of corrections for dynamic selection bias on forecasting accuracy in a multi‐period stay/leave model. While corrections for selection bias are needed for consistent coefficient estimates, they do not necessarily produce more accurate forecasts than uncorrected techniques. Theorem 1 shows that, apart from estimation errors, a shrinkage principle applies: the heterogeneity restriction imposed by uncorrected and combination techniques improves accuracy for forecasting individuals that leave, and hurts accuracy for forecasting individuals that stay. This has important implications for decision making because of the potential for asymmetric losses. We also present an illustrative empirical application and results from Monte Carlo experiments. We find that differences in relative accuracy vary directly with the degree of selection bias and inversely with the percentage of the initial population that stays. Copyright © 2007 John Wiley & Sons, Ltd.