Using Technology to Facilitate Collaboration in Community-Based Participatory Research (CBPR)

This study explores the use of Computer-Supported Collaborative Work (CSCW) technologies, by way of a computer-based system called iCohere. This system was used to facilitate collaboration conducting Community-Based Participatory Research (CBPR). Data was gathered from 13 members of a Community Collaborative Board (CCB). Analysis revealed that iCohere served the following functions: facilitating communication, providing a depository for information and resource sharing, and allowing for remote meeting attendance. Results indicated that while iCohere was useful in performing these functions, less expensive technologies had the potential to achieve similar goals if properly implemented. Implications for future research on CSCW systems and CBPR are discussed.     

协同创新视角下的学会建设

学会的基本属性和活动方式与协同创新要求相契合,使其能够在推动协同创新、实施科技创新驱动发展战略中发挥重要作用。协同创新是一个复杂的系统工程,学会在政府、科学家、企业、金融资本等创新活动主体间扮演沟通联系人、协调者、润滑剂的角色,构建跨学科、跨大类学科甚至跨文理界限的学会联盟是协同创新活动发展的必然。为提升学会学术研究、协同创新能力,政府部门、企业、高等院校、科研部门、私人基金会等应支持学会建设向着有利于协同创新的方向发展,学会应进一步推动实体化建设,面向市场,服务社会。     

Parameter Estimation of Autoregressive Models Using the Iteratively Robust Filtered Fast-τ Method

Utilizing time series modeling entails estimating the model parameters and dispersion. Classical estimators for autocorrelated observations are sensitive to presence of different types of outliers and lead to bias estimation and misinterpretation. It is important to present robust methods for parameters estimation which are not influenced by contaminations. In this article, an estimation method entitled Iteratively Robust Filtered Fast? τ(IRFFT) is proposed for general autoregressive models. In comparison to other commonly accepted methods, this method is more efficient and has lower sensitivity to contaminations due to having desirable robustness properties. This has been demonstrated by applying MSE, influence function, and breakdown point criteria.     

Several least-squares problems related to the Hodrick–Prescott filtering

The Hodrick–Prescott (HP) filtering is frequently used in macroeconometrics to decompose time series, such as real gross domestic product, into their trend and cyclical components. Because the HP filtering is a basic econometric tool, it is necessary to have a precise understanding of the nature of it. This article contributes to the literature by listing several (penalized) least-squares problems that are related to the HP filtering, three of which are newly introduced in the article, and showing their properties. We also remark on their generalization.     

一中华优秀传统文化与社会主义核心价值观的内在契合

对于社会主义文化强国建设而言,中华优秀传统文化、社会主义核心价值观是不可或缺的重要话语体系,是国家软实力的显著标志。中华优秀传统文化与社会主义核心价值观在逻辑运演与实践运行上体现出密不可分、水乳交融的内在契合。中华优秀传统文化是社会主义核心价值观的涵养之源,社会主义核心价值观是弘扬中华优秀传统文化的价值导引,中华优秀传统文化与社会主义核心价值观可以实现现实联动。只有寻求中华优秀传统文化与社会主义核心价值观的静态支撑、动态联缀,才能更好构筑"四个全面"战略布局的价值向度,强力推进中华民族伟大复兴中国梦的顺利实现。     

地方政府引导下的集群企业群际协同创新演化博弈分析

随着国内外经济环境的变化,单一集群的竞争优势逐渐弱化。在地方政府引导下,通过集群企业群际协同创新,整合单一分散"小集群",形成整体"大产业"优势,是实现我国产业集群创新发展的重要途径。运用演化博弈理论及方法,构建集群企业群际协同创新的演化博弈模型,从动态角度分析协同创新过程中的地方政府及集群企业行为。博弈结果表明,知识收益系数、成本系数、相互信任程度、群际协作风险系数影响着集群企业创新策略的选择;集群企业可能选择协同创新策略,也可能选择独立创新策略,但只要地方政府不加以限制,集群企业最终会选择协同创新策略。     

大学科技园与地方高新园区协同创新的博弈分析

文章以跨园区协同创新为视角,探讨了大学科技园与地方高新园区协同创新的内涵、创新主体和协同创新过程,并进一步引入演化博弈理论,选择大学与高新园区企业作为大学科技园与地方高新园区的代表,构建两者协同创新的博弈模型。然后,基于博弈模型,进行博弈结果分析,并针对影响博弈结果的三个要素进行博弈策略设计。结果表明,大学与地方高新园区企业选择跨园区协同创新合作的概率与双方在原园区内的初始收益、协同创新投入和溢出系数呈反比,与违约损失呈正比;同时,合理分配双方投入比例、降低溢出系数和提高违约损失至一定额度,均可有效促成合作。文章最后依据以上结论从协同创新的动机、协调和政府支撑三个方面提出了若干对策建议。     

基于住房“过滤”模型的住房福利政策的影响分析

住房“过滤”论近年来主要用于住房福利的研究,文章从我国目前的市场情况出发,建立住房三市场“过滤”模型,分析了“两限房”和经济适用房在处于低级市场并且被低收入者购买、处于中级市场被中级收入者购买等情况下对住房市场的影响;“廉租房”实行实物配租和货币补贴这两种情况下对住房市场的影响,并给出了结论和建议。     

西部地区产学研协同创新效率及特征研究

随着“2011计划”的持续推进,协同创新已经上升到国家战略的层面。利用 RAM模型估算了西部地区协同创新效率,并结合基尼系数、σ收敛和β收敛分析了省际差异度和变动趋势。结果发现：西部地区效率具有非均衡性,这种非均衡性随着时间的推移并没有显著缩小,初期的效率低下状态将会对未来效率产生长期的制约。     

基于EMD的非线性信号自适应分析

根据EMD分解原理,提出通过选择平均包络中的突变点确定自适应滤波器截止分量阶,以此构造时空滤波器组进行非线性信号自适应分析的方法,成功应用于分析波音737飞机涡轮轴振动信号。从噪声中自适应地提取随转速变化的信号分量和低频振动分量,与小波分析方法相比,在轴向位移检测中取得了更为满意的效果。该方法不仅改进了涡轮轴振动信号分析方法,也适用于解决其他非线性信号的分析问题。