A reflected feature space for CART

We present an algorithm for learning oblique decision trees, called HHCART(G). Our decision tree combines learning concepts from two classification trees, HHCART and Geometric Decision Tree (GDT). HHCART(G) is a simplified HHCART algorithm that uses linear structure in the training examples, captured by a modified GDT angle bisector, to define splitting directions. At each node, we reflect the training examples with respect to the modified angle bisector to align this linear structure with the coordinate axes. Searching axis parallel splits in this reflected feature space provides an efficient and effective way of finding oblique splits in the original feature space. Our method is much simpler than HHCART because it only considers one reflected feature space for node splitting. HHCART considers multiple reflected feature spaces for node splitting making it more computationally intensive to build. Experimental results show that HHCART(G) is an effective classifier, producing compact trees with similar or better results than several other decision trees, including GDT and HHCART trees.     

Adoption and permanence planning in Scotland: Impact of the Adoption and Children (Scotland) Act 2007 on key processes and timescales

Adoption and permanence planning has been a key feature of Scotland's policy in relation to children and young people who are “looked after.” Although policy and law has significantly developed in recent years, there has been comparatively little research on permanence processes in Scotland. This paper outlines key findings from the first comprehensive study of permanence planning in Scotland. It examines the process for two cohorts of children where adoption or other types of permanence orders were made. The children were selected under the long standing Adoption (Scotland) Act 1978 and the more recent Adoption and Children (Scotland) Act 2007. In total, 300 cases were examined, analysing data from the children's first contact with services through to the order made by the Scottish Courts. This paper pays particular attention to the timescales found at key stages under the two sets of legislation and asks what difference the change in legislation has made.     

考虑消费者双重偏好的低碳供应链减排策略研究

为了削弱传统零售商在渠道博弈中的垄断地位，制造商尝试建立在线渠道与零售商展开竞争。本文在考虑消费者低碳偏好的基础上，又将消费者的渠道偏好进行区分，通过不同决策模式的对比及数值算例分析，寻求低碳供应链最优的减排边界。研究表明：1分散决策时，制造商的低碳决策会受消费者渠道偏好的影响；集中决策时，制造商的低碳决策保持不变。2不同决策模式的减排边界由渠道偏好决定，渠道偏好较大时，分散决策的减排边界更高；渠道偏好较低时，集中决策的减排边界更高；渠道偏好中立时，两者的减排边界相同。3制造商可以通过升级低碳技术、实行低碳化管理等方式降低减排成本，同时通过低碳产品认证、广告宣传等方式提高消费者对低碳产品的认可程度。     

基于交叉效率DEA与群体共识的区间乘性语言偏好关系群决策

针对区间乘性语言偏好关系群决策问题，提出了一种基于交叉效率DEA和群体共识的群决策方法。首先，提出乘性语言偏好关系导出函数的定义，并构建产出导向的DEA模型，证明了一致性乘性语言偏好关系的DEA效率得分与排序向量之间存在比例关系。在此基础上，建立基于理想值的交叉效率DEA模型，提出乘性语言偏好关系的通用排序方法。同时，基于群体共识建立目标规划模型来计算各语言偏好关系的权重系数。最后，利用Monte Carlo随机模拟的方法对群体语言偏好空间进行统计分析，得到群决策期望排序向量及其可信度。算例分析表明本文方法能够有效的避免信息损失，具有较强的适用性和较高的可信度。     

Career Decision State and Assessment of RIASEC Interest Structure

The career decision state (CDS) was studied in relation to RIASEC (Realistic, Investigative, Artistic, Social, Enterprising, Conventional) profiles in Self-Directed Search results among college students (86 women, 27 men). Three CDS dimensions measured by the Career State Inventory (CSI; certainty, satisfaction, and clarity) were examined as predictors of RIASEC primary and secondary constructs. Significant, albeit modest, zero-order correlations (p < .05) emerged between clarity and 3 secondary constructs (i.e., consistency, commonness, and coherence). Results of regression analyses indicated that CSI dimensions predicted 1 secondary construct (i.e., commonness).     

Racial/Ethnic Minority Community College Students' Critical Consciousness and Social Cognitive Career Outcomes

A need exists to better understand how racial/ethnic minority students' critical consciousness development in response to marginalization may be involved in their educational and career development. We therefore examined the link between critical consciousness development and career decision self-efficacy and career outcome expectations among racial/ethnic minority community college students. Following social cognitive career theory's conceptual pillars, we developed a testable model integrating critical consciousness and social cognitive variables. This model was tested with 135 racially and ethnically diverse community college students. Data analysis included path analyses and tests of model fit using structural equation modeling. Results suggested that (a) higher critical agency is linked to higher career decision self-efficacy and outcome expectations and (b) critical action and reflection have a bidirectional link and predict higher critical agency. Implications for research and practice aiming to close educational and career gaps among racial/ethnic minorities are discussed.     

Names and naming in adoption: Birth heritage and family‐making

In this article, we consider the significance and practices of names and naming in adoption to develop understanding of the issue amongst scholars, policymakers, adoption practitioners, and adoption communities. Research on the topic of names and adoption is scarce and focused mostly on international and domestic adoptions in the United States. We draw on the research literature to critically explore names and naming in adoption through two recurrent and related themes. The first is “birth heritage,” where names, forenames especially, are shown to be important in the approach taken by adopters to their child's birth family and cultural identity. The second theme is “family‐making,” where namesaking and homogeneity of surname emerge, amongst others, as strategies to create, sustain, and display “family.” In gathering together for the first time an otherwise scattered, disparate body of research, our article showcases names and naming as illuminating distillations of key contemporary challenges experienced by families formed through adoption. We conclude our article by considering emergent gaps in existing knowledge and understanding about names, naming, and adoption that might usefully be addressed, to inform professional advice and familial decisions about names, and enhance outcomes for adoptees and their families.     

基于遗传算法的装备采购决策优化研究

在装备采购中，由于需求单位地域分布和担负的任务各不相同，对装备的品种、数量、时限要求也就不一样，如何使装备采购科学化、合理化，是一个涉及多变量、多目标的复杂系统问题。在综合考虑装备采购各项因素的基础上，构建多约束条件下的多目标模糊指派模型，提出了基于遗传算法的解决方案，最后通过案例进行仿真实验，验证该算法的可行性和有效性，解决了采用传统优化方法难以解决的装备采购优化决策问题。     

存在议价能力和副产品协同生产的制造商最优产量决策

考虑由环保型制造商和处理厂构成的两级供应链结构，其中上游制造商进行主产品的生产，而下游处理厂通过对废料加工进行副产品的生产。基于供应链成员之间存在不同议价能力的情形，构建了上游制造商将产生的废料给下游进行处理的协同生产模式，给出了主产品的均衡产量决策和废料的最优交易价格以及制造商关于废料的最优处理策略。研究结果表明，制造商的废料处理策略取决于消费者对副产品产量的敏感程度。当消费者对副产品产量较敏感（不敏感）时，制造商会选择自己处理废料（给处理厂进行加工）。此外，随着制造商议价能力的上升，制造商的均衡利润上升，而处理厂的均衡利润下降。最后发现本文的基本结论在随机产出环境下依然稳健。