企业用户云服务技术选择行为

如何选择最佳云服务方案,是企业决定采纳云服务之后所面临的一个重要决策。为了解决云服务技术选择问题,从业务流程的视角出发,以模块化系统理论为基础,提出一个流程模块化、IT可拆解性及安全风险如何影响云服务技术选择的研究模型。采用问卷调查和计量经济学的普通最小二乘法OLS进行实证分析。研究结果表明:流程模块化和IT可拆解性对云服务技术选择的抽象程度有显著的正向影响,即流程模块化程度IT可拆解性越高的企业,越倾向于选择抽象程度高的云服务,如软件即服务SaaS;而流程模块化程度和IT可拆解性越低的企业,越倾向于选择抽象程度低的云服务,如基础设施即服务IaaS。同时,安全风险会正向调节流程模块化和IT可拆解性对云服务技术选择的抽象程度的影响。     

突发事件应急管理中的情景适应度研究

在突发事件的处置过程中,每个阶段对情景的确定决定了突发事件应急管理的工作方式和决策制定的指向性,从而影响整体应急管理工作的总体决策判断。本文主要针对突发事件应急情景选取问题,由粗到细的采用具有语义接近范围的情景适应度方式和情景属性云匹配方式进行情景确定问题的收敛,从而能够相对精确的确定应急处置过程中的情景,为系统决策提供支持。     

云计算在高校校园网资源管理中的应用

校园网以云计算为核心架构，可以实现基础设施与实际应用的分离，解决校园网面临的资源共享、设备更新、管理统一等问题，促进教师的教学和科研工作，丰富学生的学习和生活，并为资源的存储和安全提供的保障。     

Arranging sensations: smell and taste in augmented and virtual reality

The development of digital taste and smell underscores the importance of cultural dimensions of bodily perception in augmented reality (AR) and virtual reality (VR) devices. This can be seen in Vocktail and Season Traveller, two digital devices incorporating taste and smell. Vocktail is an AR technology that augments the experience of drinking water, or even air, through the electrical stimulation of tastebuds and the manipulation of color and smell. Season Traveller is a VR game in which the user moves through four seasonal landscapes. It uses wind, odor, and temperature in addition to the more standard audio-visual displays. The cultural dimensions of these devices can be examined using phenomenological terms. They instigate perceptual circuits, and call on and create sedimented habits. Although VR and AR are often thought of in terms of their similitude to reality, understanding Vocktail and Season Traveller this way illustrates the world-creating dimension of multisensory devices. These technologies structure and shift thresholds of taste and smell, reworking past perceptual styles and habits to develop new perceptual experiences. In so doing, Season Traveller and Vocktail throw to the fore questions about the conditions according to which people exercise their senses in digitally dominated environments.     

桌面云技术在高校计算机类实验室建设中的应用

计算机软硬件技术更新换代速度越来越快.各学校计算机实验室拥有大量计算机，每年需要不少实验运行经费进行软硬件升级换代，因此应构建全新的实验室建设方案，降低实验室建设及维护成本，减轻教师工作强度，提高实验教学效果.通过桌面云技术把各种教学资源放到云平台上，师生用多种终端设备通过网络访问云端资源，可有效改善教学的时空环境，解决了传统实验室计算机更新换代快、实验环境扩展性差、维护管理复杂等问题.     

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

Summary.  Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalized) linear models, (generalized) additive models, smoothing spline models, state space models, semiparametric regression, spatial and spatiotemporal models, log-Gaussian Cox processes and geostatistical and geoadditive models. We consider approximate Bayesian inference in a popular subset of structured additive regression models, latent Gaussian models , where the latent field is Gaussian, controlled by a few hyperparameters and with non-Gaussian response variables. The posterior marginals are not available in closed form owing to the non-Gaussian response variables. For such models, Markov chain Monte Carlo methods can be implemented, but they are not without problems, in terms of both convergence and computational time. In some practical applications, the extent of these problems is such that Markov chain Monte Carlo sampling is simply not an appropriate tool for routine analysis. We show that, by using an integrated nested Laplace approximation and its simplified version, we can directly compute very accurate approximations to the posterior marginals. The main benefit of these approximations is computational: where Markov chain Monte Carlo algorithms need hours or days to run, our approximations provide more precise estimates in seconds or minutes. Another advantage with our approach is its generality, which makes it possible to perform Bayesian analysis in an automatic, streamlined way, and to compute model comparison criteria and various predictive measures so that models can be compared and the model under study can be challenged.     

On evaluating interactive statistical program packages

Most statistical computing for data analysis has come to depend upon statistical program packages. In recent years, interactive computing has become widespread both on large time-sharing systems and on mini-computers. This paper identifies ways in which interactive statistical software packages differ from batchoriented software and discusses evaluation considerations pertaining specifically to interactive packages.     

Computation of finite population parameters and approximate probability values for multi-response randomized block permutation procedures (mrbp)

An algorithm is presented for computing the finite population parameters and the approximate probability values associated with a recently-developed class of statistical inference techniques termed multi-response randomized block permutation procedures (MRBP).     

Statisticians Can Matter

Statisticians fall far short of their potential as guides to enlightened decision making in business. Two important explanations are: (1) Decision makers are often more easily convinced by concrete examples, however fragmentary and misleading, than by competent statistical analysis. (2) The effective use of statistics in the process of decision making requires hard thinking by decision makers, thinking that cannot be delegated entirely to the statistical specialist. Modern developments in interactive statistical computing may help to reduce the force of these limitations on exploitation of statistics; used properly, computing can encourage, almost force, the student or business user of statistics to think statistically.     

The Consistent System

The Consistent System (CS) is an interactive computer system for researchers in the behavioral and policy sciences and in fields with similar requirements for data management and statistical analysis. The researcher is not expected to be a programmer. The system offers a wide range of facilities and permits the user to combine them in novel ways. In particular, tools for statistical analysis may be used in combination with a powerful relational subsystem for data base management. This paper gives an overview of the objectives, capabilities, status, and availability of the system.