Knowledge policies and universities in developing countries: Inclusive development and the “developmental university”

This paper links development approaches with innovation systems theory and social inclusion concerns. In exploring the relationship between development and knowledge, we propose a sequential analytical model that considers values, facts and policies as a coherent whole. This allows us to go deeper into the question of how policies for promoting the production and use of knowledge able to foster different facets of social inclusion can be formulated and implemented. We propose to call such policies “democratization of knowledge policies”; they are one of the means to achieve inclusive development. We provide examples of how these policies work in practice, and explore how the university, a vital part of any national innovation system, can play a role in the emergence and consolidation of the democratization of knowledge. Universities that embrace that role may be considered developmental universities. They fulfill it in great part by providing effective incentives to include in their research agendas the kind of problems whose solutions can lead to an enhancement of social inclusion. However, developmental universities cannot function in isolation. It is argued that their effectiveness depends on the rise of a sustained and strong demand that is able to put knowledge at the direct service of shared social goals, among which diminishing inequality is particularly important. The paper presents a case in Uruguay that illustrates an ongoing transformation towards a developmental university.     

The idiosyncrasy and dynamism of technological innovation across industries: patent citation analysis

In general, the structural and behavioral patterns of technological innovation are idiosyncratic across industrial sectors and dynamic over time. Yet, despite voluminous amounts of previous research, patterns of innovation are hard to standardize or theorize. The objectives of this article are two-fold. One is to investigate distinctive and changing patterns of technological innovation across industries and observe dynamic trends over time. The other is to identify patterns of relationships among industries and examine the roles of respective industries. To this end, the U.S. Patent and Trademark Office (PTO) patent database was used and patent citation analysis applied. The idiosyncratic differences among industrial sectors are highlighted, especially between conventional manufacturing sectors and science-based sectors. We also found changing trends in technological knowledge flows across industries.     

基于机器学习的开放创新社区创意识别方法研究

目的 探索基于机器学习的开放创新创意识别方法,解决创意识别过程中存在的耗时长、效率低、成本高等问题。方法 从用户特征、用户参与度和创意内容特征三个方面构建评估模型,以OpenIDEO社区为研究对象,采集数据并进行数据清洗和数据转化映射,最后进行多种机器学习算法的参数优化,并以F1值为选择标准,选择分类效果最佳的算法作为分类模型。结果 运用KNN、SVM、决策树、随机森林四种机器学习算法分析OpenIDEO数据,随机森林算法通过参数优化取得了最大的F1值（0.919 09）,同时对于验证数据,该算法同样可以取得较好的分类效果。结论 应用机器学习方法对开放式创新社区中的创意进行识别,具有较高的可行性和有效性,可以大大降低社区在创意筛选中的投入,提高创新效率,优化社区生态。     

企业核心能力与组织创新及组织学习互动模式

从知识的视角揭示了企业核心能力、组织创新与组织学习三者之间的内在互动关系,为处理好这三者之间的关系,提高组织学习绩效,促进组织创新与核心能力的培育和提升紧密结合提供了理论依据.     

生存困境里的不懈求索——存在论视域中的斯佳丽的形象

斯佳丽的生活历程很大程度上是为其所生存的环境所塑造而成的。她在时代的大变迁下随着时代的变化而改变其性格和行事方式。从本质上看，她是一个不断求索与进取的形象，在新旧交替的时代里发展出新的人生，但同时，她为达目的也时常不择手段，从而导致其精神生活某种形式上的崩塌，所以，综合起来，她是那个时代女性生存的典型代表，有着浓厚的文化意义。     

The Complementary Dynamic Effects of Clusters and Networks

Over the past decades, researchers and policymakers around the world have been paying attention to the concept of clusters of related firms, industries and institutions, with a view to the presumably positive effects of clustering for learning, innovation and the productivity of firms. More recently, a network approach to learning and innovation emerged, which emphasizes strategic, preferential, repeated and at the same time temporary knowledge exchange (i.e. dynamic cooperation) between firms and other organizations. This may, however, go at the expense of the attention for the important, different and complementary learning effects of the mainly spatial process of concentration and clustering of related firms, industries and institutions. This paper argues that clusters and networks are two separate concepts that both merit attention, especially—albeit not exclusively—with a view to learning, knowledge development and innovation. A first argument is that spatial clustering has quite different effects for the development of knowledge, learning and innovation in and by firms, as compared with network settings. A second point is that in some cases, clustering yields a governance advantage over networks. Taking into account the risks of cognitive, technological, organizational and institutional lock-in associated with both processes, this paper concludes that both clustering and networking have advantages and disadvantages for the firms involved. The two concepts are potential dynamic complements, as clustering and networking have different but complementary effects for learning, although they are also static substitutes, as firms may opt to switch between the two processes, for example, leaving a local or regional cluster to engage in a network endeavor at a higher spatial scale.     

An integrated database and expert system for failure mechanism identification: Part I—automated knowledge acquisition

An integrated database and expert system has been developed for identifying the failure mechanism of mechanical components. The system comprises six major modules: database and management system, case maintenance; knowledge acquisition and editing; expert system; explanation and test-recommendation facilities; and user interface. Part I of a two-part paper details the knowledge acquisition and editing module, as presented here. Part II describes the remaining modules and also gives test results [9]. The method used for automated knowledge acquisition is an inductive learning algorithm, which was modified from PRISM [2] to handle noisy and missing data. Using the algorithm, a total of 48 rules were induced from 477 training examples gathered for the identification of 15 different failure mechanisms such as brittle fracture, fatigue, and stress corrosion cracking. Fifty-nine attributes were used to distinguish one failure mechanism from the others. They include pitted, beach marks, microvoids, etc. The knowledge editing function is provided to allow the verification of induced rules by the human expert.