Mapping the Characteristics of a 'Good' Play Therapist.

In this pilot study, concept mapping, a methodological approach combining qualitative and quantitative analytic strategies, was used to identify the therapist qualities, competencies, and skills necessary for effective play therapy outcomes as perceived by a sub-sample of 28 experienced play therapists who are members of the Association for Play Therapy (APT). The clusters associated with the therapeutic relationship and facilitative skills (e.g., empathy, warmth, and genuineness) were rated as the most essential skills to possess and also as the most difficult to develop. In contrast, the clusters associated with play therapy interventions and theories were rated as the least important skills to possess but as the easiest to acquire. The findings are discussed, with implications for therapeutic practice, research, and policy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Determining the characteristics of systems with multiple inputs and multiple outputs

A simple and computationally efficient method of determining the transfer function and other characteristics of systems with multiple inputs and multiple outputs (MIMO systems) described by autoregression equations is proposed. The method is based on the use of the discrete Fourier transformation. The algorithm is highly suitable for computer implementation. The efficiency and simplicity of the method are illustrated using the example of a system with three inputs and three outputs. The proposed concept may be applied to systems described by the autoregression sliding mean.     

Practice characteristics that lead to 21st century learning outcomes

Abstract The key research question for this study was to ask whether or not innovative teaching practices would lead to the development of learning outcomes essential for preparing the younger generation for the challenges of life in the knowledge society of the 21st century, and if so, how are the pedagogical features related to the different learning outcomes. Preliminary analyses of the case study data collected from the SITES M2 Study in Hong Kong reveal that where the development of more significant learning gains were observed, the cases possess characteristics additional to the criteria defined in the Study for selection of innovation. More importantly, it was found that the impact of the pedagogical practices was not determined simply by the aggregation of characteristics of the practices per se , nor on the technologies used, but on whether 'empowerment' permeates the curriculum goal and process. Further, this paper claims that these affective and socio-cognitive learning outcomes are more important as preparation for lifelong learning in the 21st century than 'knowledge management competencies'.     

具有多重焦点的波带透镜的设计

本文提出了一种新型的具有多重焦点的波带透镜的概念及其设计方法。可提供某些特定的光场分布,而且具有性能稳定、微型化和可实际制作等特点。     

MIMO链路ad hoc网络传输调度算法

针对MIMO链路ad hoc网络中已有传输调度算法未充分利用MIMO空间复用能力的问题,提出了一种新的传输调度算法.该算法通过考虑MIMO的多流接收能力而有效地减小了调度帧长,通过合理安排节点分配顺序使得节点分配的数据流比较平均,同时,该算法通过允许节点发送多个数据流而高效利用了MIMO的空间复用能力.推导分析了传输调度算法的通过量和时延性能,结果表明,与已有算法相比,采用文中算法可以提高网络的通过量,减小网络的平均时延和最大时延.     

多特征自适应融合的粒子滤波跟踪算法

针对跟踪过程中目标形态不断变化或部分遮挡导致鲁棒性差的问题,提出一种基于多特征自适应融合的粒子滤波跟踪算法.该算法从视觉特征集中选取了描述能力强的2种特征,并将其按照与目标模型的多尺度相似度进行线性融合;为了减小跟踪漂移,通过计算当前目标模型与初始目标模型的多尺度相似度自适应地更新目标模型.大量仿真实验结果表明,文中算法可以鲁棒地跟踪到部分遮挡和形态变化的运动目标.     

异类传感器实时信息融合的STMHM算法

异类传感器实时信息融合由于两类设备的数据率不同和数据误差的限制,一直未得到有效解决,提出一种空时二维多假设模型(STMHM)算法来解决该问题。设计的融合数据模型,将异类传感器的测量数据映射在二维直角坐标系下;按照新的融合数据模型分别构建两类传感器的目标量测空间和融合空间;设计量测空间时间初始化方法和目标实体空间的滤波算法;通过仿真验证表明:该算法能够实现异类传感器的信息融合,初次融合成功的确认时间在3～5个主动传感器扫描周期。     

基于两电极体系的水质检测分析平台设计

为实现对水质的多参数检测,设计了一个基于两电极体系的水质检测分析平台。该检测平台通过最小化极化电流的思想,采用辅助电极面积远大于工作电极的电极参数,设计了基于两电极体系的集成电极和软硬件系统,摈弃了传统三电极体系的参比电极,同时克服了传统三电极体系容易污染样品的缺点,能实现电化学工作站的诸多功能。本研究在该检测平台上开展了水样的电导率(EC)、pH和重金属浓度的检测研究,获得了较好的结果,可用于实验室及工业现场的水质监测。     

ExtJS框架下表格组件的应用与改进

在油田措施效果评价系统开发中,使用了ASP.NET技术并结合ExtJS框架,设计并实现了一个基于B/S模式的Web应用系统,解决开发中的技术问题,着重对ExtJS中的表格组件进行了改进和扩展,实现了同时显示锁定部分表格列与支持多行表头的复杂表格,对系统中常用的几种表格形态及深入应用作了介绍与分析。     

软件定义车联网中缓存辅助的NOMA功率分配方案研究

由于对丰富多媒体服务的需求日益增长,车联网需要提供海量的设备连接以满足高频谱效率和低延迟的需求。软件定义网络（SDN）、缓存和非正交多址接入（NOMA）被认为是有效解决这些关键挑战的潜在技术。针对软件定义车联网,提出了一种缓存辅助的NOMA功率分配方案。首先,针对车联网中车辆总是处于高速运动状态的特点,提出了一种新的簇头选择算法,到达的道路交通将借助SDN进行预测,实现自适应车辆分簇。其次,引入了缓存辅助的NOMA方案,每个车辆在文件缓存阶段使用NOMA原理缓存和请求文件。再次,针对双Nakagami-m衰落条件下的两个簇头车辆通信场景,提出了一种最优功率分配策略,将优化问题公式化为找到每辆车的最佳功率曲线,从而最大化地在每辆车上成功解码目标文件的概率。最后,数值仿真和理论分析表明,所提缓存辅助NOMA功率分配方案,性能明显优于传统的NOMA和缓存辅助的OMA。