The role of learning and knowledge in adapting to climate change: a case study of Norwegian municipalities

Coping with climate change includes the role of learning and knowledge. Taking a process perspective, this article analyses how municipal officers in the Oslo region of Norway are acquiring knowledge and building competence for adapting to climate change. The article illustrates the interaction between elements of experiential learning, transformative learning and social learning as bases for adapting to emerging climate changes; each being necessary and none alone being sufficient. Their importance differs according to how profound the changes in knowledge and competence are. Experiential learning and transformative learning are stronger under single-loop learning whereas social learning might emerge as more important under triple-loop learning. Because of the uncertainties of climate change, the central government might be wise not to issue detailed regulations for adaptation by municipalities.     

Ecological Landscape Planning: A gaming approach in education

An understanding of the complex problems of land-use competition requires an appreciation of natural processes, cultural values, economic imperatives and political agendas. This integrated understanding is an important component of the study programme for higher education students seeking a professional qualification in landscape architecture. A repertoire of game templates is introduced as an initial step in formulating a conceptual framework for the curriculum/games designer to explore the potential of play in ecological landscape planning. The concepts of social action space, permissible action space and motivational action space are used to investigate the qualities of each template for further game design development. The abstraction of these concepts may assist the designer to move beyond the usability of games into viewing their value as a learning method.     

Short-Term Relay Quality Prediction Algorithm Based on Long and Short-Term Memory

The fraction defective of semi-finished products is predicted to optimize the process of relay production lines, by which production quality and productivity ar...     

Blended Learning – ein innovatives Weiterbildungskonzept für die Technische Chemie

The ever‐increasing and ever‐changing challenges of the job market require professionals to constantly attend extra occupational education programs. Professionals furthermore express their desire for a compatibility of family and work. Therefore, a general concept for extended vocational training in the field of natural science and technology was developed based on blended learning. As an example, the concept was implemented and tested on the basis of the extended vocational training course “tc‐compact^BL” in Chemical Technology.     

泵并联运行流量增量的影响因素与并联运行设计的初探

通过对福建LNG接收站现有管路特性曲线和3台海水泵并联运行流量-扬程曲线的形状进行分析,分析了影响泵并联运行时流量增量的因素,以及泵并联运行时可能出现的过载问题,在此基础上提出了福建LNG接收站工艺海水泵并联运行设计时应该注意的问题,为并联运行工艺海水泵的设计和选型提供参考。     

Scalability of assessments of wiki-based learning experiences in higher education

In recent years, the focus on higher education learning has shifted from knowledge to skills, with interpersonal skills likely being the most difficult to assess and work with. Wikis ease open collaboration among peers. A number of these skills can be objectively assessed by using wikis in an educational environment: collaborative writing, conflict resolution, group management, leadership, etc. However, when the number of students increases, their interactions usually increase at a higher rate. Under these circumstances, traditional assessment procedures suffer from scalability problems: manually evaluating in detail the information stored in a wiki to retrieve objective metrics becomes a complex and time-consuming task. Thus, automated tools are required to support the assessment of such processes. In this paper we compare seven case studies conducted in Computer Science courses of two Spanish universities: Cádiz and Seville. We comment on their different settings: durations, milestones, contribution sizes, weights in the final grade and, most importantly, their assessment methods. We discuss and compare the different methodologies and tools used to assess the desired skills in the context of each case study.     

不确定性X-Y定位平台PID控制方法研究

X-Y定位平台属于强耦合非线性系统,且由于结构复杂性及外界干扰,当前测量水平难以获得其精确的数学模型,提出基于自适应神经网络的PID控制策略。考虑到X-Y定位平台系统精确的数学模型难以获得,利用神经网络良好的学习能力来逼近系统未知非线性模型,设计神经网络控制器;为了保证神经网络在学习的初期阶段的控制精度,设计PID控制器来进行辅助补偿控制;为加快学习速度,提高运动控制的实时性,设计变学习率的优化算法来实现神经网络权值的在线调整。试验结果验证了所提控制方法的有效性。     

基于PU学习的链接预测方法

基于分类的链接预测方法中,由于链接未知节点对的大规模性与不确定性,选择可靠负例成为构造链接预测分类器的难点问题.为此,文中提出基于正例和无标识样本(PU)学习的链接预测方法.首先,提取节点对的拓扑信息以构造样本集.再利用社区结构确定候选负例的分布,基于分布进行多次欠采样,获得多个候选负例子集,集成多个负例集与正例集中构建的分类器选择可靠负例.最后基于正例与可靠负例构造链接预测分类器.在4个网络数据集上的实验表明文中方法预测结果较优.     

基于多尺度高斯核的分布式正则化回归学习算法

针对工业、信息等领域出现的基于较大规模、非平稳变化复杂数据的回归问题,已有算法在计算成本及拟合效果方面无法同时满足要求.因此,文中提出基于多尺度高斯核的分布式正则化回归学习算法.算法中的假设空间为多个具有不同尺度的高斯核生成的再生核Hilbert空间的和空间.考虑到整个数据集划分的不同互斥子集波动程度不同,建立不同组合系数核函数逼近模型.利用最小二乘正则化方法同时独立求解各逼近模型.最后,通过对所得的各个局部估计子加权合成得到整体逼近模型.在2个模拟数据集和4个真实数据集上的实验表明,文中算法既能保证较优的拟合性能,又能降低运行时间.