分布学习的教学技术

远程通信工具加上人工智能和虚拟真实技术正在使得传统的远程教育转变为一种新的教学范例,称为分布学习。分布学习源于对分布认知科学进行的研究。该文首先简要阐述了分布学习的若干概念,之后着重对构成分布学习作为新教育方式而出现的4种新的教学技术:知识网络、虚拟共同体(社会)、综合性环境和“感官沉浸”分别作了详细探讨,结语对分布学习存在的物质条件和认知理念等作了小结。     

Timing issues in distributed testing

The objective of conformance testing is to determine whether an implementation under test (IUT) conforms to its specification. In distributed test architecture where there are multiple remote testers, the objective can be complicated by the fact that testers may encounter controllability and observability problems during the application of a test sequence. A certain amount of work has been done in the area of generating test sequence that is free from these problems. However, few researchers investigate them from the aspect of test execution. This work studies the test execution phase when test sequences are applied to the imple- mentation and it is pointed out that controllability and observability problems can be resolved if and only if the test system im- plements some timing constraints. When determining these constraints, the dynamic time information during test is taken into account, which reduces the test execution time and improves test efficiency further.     

Broker:一种分布式系统的体系结构模式

采用Broker模式可以解决分布式系统构造的复杂性和软件开发人员需求之间的矛盾。Broker模式封装了分布式计算的组件通信机制，为开发人员提供了远程对象的透明性。今天的B／S、C／S结构甚至Web Services都是Broker模式的具体应用。     

实时数据平台在火电厂中的应用实例

本文介绍了实时数据平台的功能，以及在某火电厂中的具体应用，包含应用方案、主要功能和应用的实际情况等方面的内容。     

鹤鸣观小流域不同土地利用方式的产流产沙特征

针对日益加剧的四川紫色土地区水土流失情况，本文选取四川省南部县鹤鸣观小流域为研究区，分析了流域不同土地利用方式（荒地、灌木林、坡耕地、梯地、林地等）的产流产沙特征及其与降雨的关系以及减水减沙效益。结果表明，该流域不同土地利用方式的次降雨产流产沙特征差异显著，在各类土地利用方式中，荒地的径流系数最大，林地最小，坡耕地的侵蚀模数最大，林地最小；其径流系数与侵蚀模数与次降雨量、降雨强度有一定的相关性；水保措施起到了较好的减水减沙效果，其中林草措施减水减沙效益最好，坡改梯次之，但坡改梯能提高农业产量，经济效益较好。因此，在四川紫色土地区，宜采用生物林草措施与坡改梯相结合的水土保持措施，在坡度较陡的地方退耕还林，在缓坡地带坡改梯。本文为紫色土地区水土流失特征的研究以及水土保持措施的选定提供了一定的依据，为进一步构建小流域分布式侵蚀产沙模型奠定了基础。     

The role of big data in smart city

The expansion of big data and the evolution of Internet of Things (IoT) technologies have played an important role in the feasibility of smart city initiatives. Big data offer the potential for cities to obtain valuable insights from a large amount of data collected through various sources, and the IoT allows the integration of sensors, radio-frequency identification, and Bluetooth in the real-world environment using highly networked services. The combination of the IoT and big data is an unexplored research area that has brought new and interesting challenges for achieving the goal of future smart cities. These new challenges focus primarily on problems related to business and technology that enable cities to actualize the vision, principles, and requirements of the applications of smart cities by realizing the main smart environment characteristics. In this paper, we describe the state-of-the-art communication technologies and smart-based applications used within the context of smart cities. The visions of big data analytics to support smart cities are discussed by focusing on how big data can fundamentally change urban populations at different levels. Moreover, a future business model of big data for smart cities is proposed, and the business and technological research challenges are identified. This study can serve as a benchmark for researchers and industries for the future progress and development of smart cities in the context of big data.     

The evolution of local production systems: the emergence of the “invisible mind” and the evolutionary pressures towards more visible “minds”

The aim of this paper is to propose an explanation of the changes of dynamic matching between systemic properties of local production systems (LPS) and characteristics of the competitive environment. An evolutionary sequence travelled during the last three decades by Italian LPS is identified and an explanation of long-term dynamics is based on how information flows and knowledge are structured within a local environment. The “traditional” pattern of interlocking behaviours of different agents is defined as cognitive architecture, which evolutionarily emerges as invisible mind. Evolutionary pressures lead new patterns of relationships and interlocking behaviours, which we define as a tendency for more visible “minds” to assert themselves.     

Testing the cluster hypothesis in distributed information retrieval

How to merge and organise query results retrieved from different resources is one of the key issues in distributed information retrieval. Some previous research and experiments suggest that cluster-based document browsing is more effective than a single merged list. Cluster-based retrieval results presentation is based on the cluster hypothesis, which states that documents that cluster together have a similar relevance to a given query. However, while this hypothesis has been demonstrated to hold in classical information retrieval environments, it has never been fully tested in heterogeneous distributed information retrieval environments. Heterogeneous document representations, the presence of document duplicates, and disparate qualities of retrieval results, are major features of an heterogeneous distributed information retrieval environment that might disrupt the effectiveness of the cluster hypothesis. In this paper we report on an experimental investigation into the validity and effectiveness of the cluster hypothesis in highly heterogeneous distributed information retrieval environments. The results show that although clustering is affected by different retrieval results representations and quality, the cluster hypothesis still holds and that generating hierarchical clusters in highly heterogeneous distributed information retrieval environments is still a very effective way of presenting retrieval results to users.     

电子图书及新的业务模型对高等院校图书馆的影响分析

本文分析了电子图书技术对高等院校图书馆的现实意义。虽然我们正处于电子图书馆发展的初级阶段，但业务模型、标准及支持技术正处于对图书馆业务产生极大影响的发展时期。因此，图书馆和管理人员必须完全了解这样的趋势，以便能够在其工作范围内有效地应用创新成果。     

The effectiveness of the GoKoan e-learning platform in improving university students’ academic performance

The GoKoan e-learning platform supports face-to-face training in an educational community. Its aim is to optimise the way and the time of study in order to improve academic performance. To evaluate the GoKoan platform’s effectiveness as a tool for improving academic performance, an experimental study was carried out using a sample of 171 university students enrolled in the psychology degree programme who were randomly assigned to the two different conditions (the experimental group: traditional learning + e-learning with the GoKoan platform; and the control group: traditional learning without e-learning). The findings showed that using GoKoan had a positive impact on the students’ academic performance (d = 0.39, 95 % CI [0.08, 0.69]). The results highlight the importance of blended learning in improving students’ learning performance. Other aspects of its effectiveness (e.g, the levels achieved in student learning outcomes) will be considered in future studies.