Impacts of essential elements of management on IT application maturity — A perspective from firms in China

This paper explores the impacts of essential elements of management on IT application maturity (ITAM). A game theoretical model is established to show that a firm's IT application maturity should match with its essential elements of management. In order to further validate the analytical result, a data set with 137 firms was collected via a survey instrument. Using reliability and factor analysis on the dataset, a four-dimension measurement construct of IT application maturity is proposed together with a three-dimension measurement construct of essential elements of management. Empirical analysis is then conducted to address research questions on the impacts of essential elements of management on IT application maturity. It is found that while a firm's strategic cooperation capability has no significant effect on IT application maturity, its internal coordination capability positively influences all four dimensions of IT application maturity. For the firm's execution capability, although it shows no significant effect on the overall IT application maturity, it does positively affect the technology and man-machine synergy dimensions of IT application maturity. The findings of this study offer practical guidance for organizations to better align their IT application maturity with essential elements of management.     

文本相似度的计算

文本相似度的计算在数字图书馆系统里有着广泛的应用前景。该文采用余弦系数和向量空间模型计算文本的相似度,并给出了实现的方法。     

Simultaneous estimation and factor selection in quantile regression via adaptive sup-norm regularization

Some regularization methods, including the group lasso and the adaptive group lasso, have been developed for the automatic selection of grouped variables (factors) in conditional mean regression. In many practical situations, such a problem arises naturally when a set of dummy variables is used to represent a categorical factor and/or when a set of basis functions of a continuous variable is included in the predictor set. Complementary to these earlier works, the simultaneous and automatic factor selection is examined in quantile regression. To incorporate the factor information into regularized model fitting, the adaptive sup-norm regularized quantile regression is proposed, which penalizes the empirical check loss function by the sum of factor-wise adaptive sup-norm penalties. It is shown that the proposed method possesses the oracle property. A simulation study demonstrates that the proposed method is a more appropriate tool for factor selection than the adaptive lasso regularized quantile regression.     

气相色谱法测定卷烟烟气中烟碱的影响因素

为提高气相色谱法测定卷烟烟气中烟碱含量的准确性,依据行业标准YC/T156-2001对各种影响因素进行了考察,发现标准品配置方法、纯度是主要影响因素。根据试验结果,确定了用直接称重法制作标准工作曲线,采用校正标样的气相色谱法测定卷烟烟气中的烟碱。结果表明,改进后方法的准确度高、检测结果稳定,监测卷烟的测定结果与标定值基本一致。     

辐射防护的生物学基础--辐射生物效应

人类必须研究电离辐射的生物效应，以保护其自身及其它物种免受电离辐射的有害影响，同时在应用中最大限度地获取利益，辐射生物效应，作为辐射防护的生物学基础，一直受到国内外辐射防护界的极大关注。本文就辐射防护密切相关的辐射随机效应，辐射致癌概率，小剂量照射效应及组织权重因子等进行简要讨论。     

一种光照模型的简化算法

本文给出了在微机上实现真实感图形显示的一种简化算法，提出一种对该算法所带来的误差进行补偿的方法．     

Learning a decision maker's utility function from (possibly) inconsistent behavior

When modeling a decision problem using the influence diagram framework, the quantitative part rests on two principal components: probabilities for representing the decision maker's uncertainty about the domain and utilities for representing preferences. Over the last decade, several methods have been developed for learning the probabilities from a database. However, methods for learning the utilities have only received limited attention in the computer science community.

A promising approach for learning a decision maker's utility function is to take outset in the decision maker's observed behavioral patterns, and then find a utility function which (together with a domain model) can explain this behavior. That is, it is assumed that decision maker's preferences are reflected in the behavior. Standard learning algorithms also assume that the decision maker is behavioral consistent, i.e., given a model of the decision problem, there exists a utility function which can account for all the observed behavior. Unfortunately, this assumption is rarely valid in real-world decision problems, and in these situations existing learning methods may only identify a trivial utility function. In this paper we relax this consistency assumption, and propose two algorithms for learning a decision maker's utility function from possibly inconsistent behavior; inconsistent behavior is interpreted as random deviations from an underlying (true) utility function. The main difference between the two algorithms is that the first facilitates a form of batch learning whereas the second focuses on adaptation and is particularly well-suited for scenarios where the DM's preferences change over time. Empirical results demonstrate the tractability of the algorithms, and they also show that the algorithms converge toward the true utility function for even very small sets of observations.     

Design of a Medical Non‐Linear Drilling Device: The Influence of Twist and Wear on the Fatigue Behaviour of NiTi Wires Subjected to Bending Rotation

This paper considers fundamental and experimental aspects associated with the engineering design of a medical, non‐linear drilling device which exploits shape memory pseudoelasticity of NiTi wires. For this application it is important that the NiTi wires have a good fatigue resistance. This is why the present authors have previously determined the influence of various parameters on cyclic life, crack growth and stress state of pseudoelastic wires subjected to bending rotation fatigue. The actual drilling device has to withstand twist in addition to bending rotation because the free rotation is constrained by friction between the drill head and the bone material. In addition, friction between the wire and a NiTi guiding tube results in wear and this may well promote fatigue crack nucleation. In this paper, we explain the function of the medical drill. We then report results on the effect of the additional parameters (1) twist and (2) wear on the fatigue life of thin pseudoelastic NiTi wires. We finally discuss the implications of our experimental results for the design process of the medical drilling device.     

Probabilistic risk analysis of corrosion associated failures in cast iron water mains

This paper proposes a method using probabilistic risk analysis for application to corrosion associated failures in grey cast iron water mains. External corrosion reduces the capacity of the pipeline to resist stresses. When external stresses exceed the residual ultimate strength, pipe breakage becomes imminent, and the overall reliability of a water distribution network is reduced. Modelling stresses and external corrosion acting on a pipe involves uncertainties inherent in the mechanistic/statistical models and their input parameters. Monte Carlo (MC) simulations were used to perform the probabilistic analysis. The reduction in the factor of safety (FOS) of water mains over time was computed, with a failure defined as a situation in which FOS becomes smaller than 1. The MC simulations yielded an empirical probability density function of time to failure, to which a lognormal distribution was fitted leading to the derivation of a failure hazard function. A sensitivity analysis revealed that the contribution of corrosion parameters to the variability of time to failure was more significant than the combined contributions of all other parameters. Areas where more research is needed are identified.