A new wave of innovations in psychology: High intellectual and creative educational multimedia technologies.

This article describes high intellectual and creative educational multimedia technologies (HICEMTs), which will constitute one of the innovative breakthroughs in science and technology of the 21st century and will lead to a new wave of innovations in psychology. HICEMTs appear at the intersection of many subdisciplines of psychology (including general, cognitive, developmental, educational, personality, media, cyber, and applied), education, and multimedia. The general and specific nature of HICEMTs is considered. The importance of HICEMTs is discussed from technological, economic, societal, educational, and psychological perspectives. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

与时俱进 顽强创新 提高层次

以亲身经历记述了学校如何从一所名不见经传的普通中等职业学校发展成为一所大专层次的普通高等职业技术学院。多年来 ,学校坚持了以需求和发展的观点看职教 ,以顽强和创新的精神办职教 ,走产、学、研一体化的办学道路和以人为本的教育理念 ,与时俱进、开拓创新 ,办出了自己的特色。     

TIME-REVERSIBILITY, IDENTIFIABILITY AND INDEPENDENCE OF INNOVATIONS FOR STATIONARY TIME SERIES

Abstract. Weiss ( J. Appl. Prob. 12 (1975) 831–36) has shown that for causal autoregressive moving-average (ARMA) models with independent and identically distributed (i.i.d.) noise, time-reversibility is essentially unique to Gaussian processes. This result extends to quite general linear processes and the extension can be used to deduce that a non-Gaussian fractionally integrated ARMA process has at most one representation as a moving average of i.i.d. random variables with finite variance. In the proof of this uniqueness result, we use a time-reversibility argument to show that the innovations sequence (one-step prediction residuals) of an ARMA process driven by i.i.d. non-Gaussian noise is typically not independent, a result of interest in deconvolution problems. Further, we consider the case of an ARMA process to which independent noise is added. Using a time-reversibility argument we show that the innovations of the ARMA process with added independent noise are independent if and only if both the driving noise of the process and the added noise are Gaussian.     

Computation and Characterization of Autocorrelations and Partial Autocorrelations in Periodic ARMA Models

This paper studies correlation and partial autocorrelation properties of periodic autoregressive moving-average (PARMA) time series models. An efficient algorithm to compute PARMA autocovariances is first derived. An innovations based algorithm to compute partial autocorrelations for a general periodic series is then developed. Finally, periodic moving averages and autoregressions are characterized as periodically stationary series whose autocovariances and partial autocorrelations, respectively, are zero at all lags that exceed some periodically varying threshold.     

MAXIMUM LIKELIHOOD ESTIMATION OF AUTOCOVARIANCE MATRICES FROM REPLICATED SHORT TIME SERIES

Abstract. The maximum likelihood estimation of an autocovariance matrix based on replicated observations of stationary times series is considered. A sufficient condition for the existence of the estimate, when the sample covariance matrix is singular, is given. An iterative method for its computation is proposed: it is based on some spectral decompositions of Toeplitz matrices. Simulation results show the superiority of the estimate over the usual empirical sample autocovariance matrix.     

基于网上研究院的报告管理系统

介绍在网上研究院的基础上开发的报告管理系统,对技术报告管理、检测报告管理过程中的审批流程以及工作流进行了介绍。     

Using Relative Preference mapping (RPM) to identify innovative flavours for 3-blend plant-based milk alternatives in different test locations

The methods available to identify innovations in flavour can be limiting and sometimes long and expensive. Relative Preference Mapping (RPM) was developed as a quick and easy way to identify innovations in wine flavour at wine show consumer day events. There is no report on the use of the RPM method with other non-wine products, neither is there a report on using RPM in a laboratory setting. This study compared the results for consumer preferences for plant-based milk alternatives using RPM methodology carried out in a typical laboratory-based CLT setting and a social setting. In both test locations, ninety (90) regular consumers of plant-based milk alternatives completed the test. The aim was to determine if innovative new flavours of plant-based milk alternatives can be identified from within a set of laboratory-formulated prototypes of three-blend plant-based milk alternatives. In this study, commercially available dairy milk, which was sweetened in the laboratory was used as the reference product. A popular plant-based milk alternative was included in the product test set to provide an internal reference for the laboratory formulated prototypes. From the study, the RPM method was able to highlight an area of innovation where two of the 3-blend prototypes were loaded together with the commercial plant-based milk alternative in the 2D consensus map generated from Generalized Procrustes Analysis (GPA). When the liking scores from the T-map scale axis in the social and laboratory settings were compared using ANOVA, the liking scores were higher in the social setting than in the laboratory setting. This observation, however, did not change interpretations about flavour innovations highlighted in the 2D map. The RPM method was consistent in highlighting the same products as innovations when used in both test locations. The findings support the use of RPM as a useful tool to determine innovative product flavours and can be used consistently in two different test locations.     

以科学发展观提升包钢科技创新竞争力

在打造新包钢的实践中,要落实科学的发展观,分析科技创新大环境,为提高包钢核心竞争力,提出了强化科技创新理念,培养创新人才,转变创新体制与机制的发展思路.     

ARMA MODELLING WITH NON-GAUSSIAN INNOVATIONS

Abstract. The problem of modelling time series driven by non-Gaussian innovations is considered. The asymptotic normality of the maximum likelihood estimator is established under some general conditions. The distribution of the residual autocorrelations is also obtained. This gives rise to a potentially useful goodness-of-fit statistic. Applications of the results to two important cases are discussed. Two real examples are considered.     

On the Shoulders of Giants: Co-location with Dominant Firms in the Emerging Fiber Optics Industry

In this study we investigate the location choices of start-ups and established firms relative to dominant firms in the US fiber optics industry from 1976 to 1994. We test the propensity to co-locate with dominant firms and whether proximity to a dominant firm impacts the strategic choices made by start-ups and established firms. Contrary to our predictions, we find that both start-ups and established firms are equally likely to co-locate with dominant firms. We also find that start-ups exhibit greater new product adoption rates and greater product-line breadth than established firms. This implies that start-ups are relatively more likely to realize greater strategic gains with entry into emerging markets.