Migration, Ethnicity and Privilege

Representation assumes that those who govern have knowledge of those for whom they govern. It is easy to presume knowledge of the “other”, but as we know this can be based in prejudice, cultural difference, or simply misinformation or simplification. Usually our explorations of this process have focused on populations identified as disadvantaged, disempowered or somehow “non-privileged”. However, the research process outlined here has revealed previously unexplored diversity within a population commonly described as privileged suggesting that good governance requires alertness to presuming to know both the unprivileged and the privileged. The research approach outlined in this paper has used a blend of historical reappraisal and qualitative techniques focusing on a population who have been conceptualized as doubly privileged. This population focus is that of older British; post World War II male migrants in South Australia. These people have been conceptualized as privileged because they are male, and they were part of the preferred ethnic group that Australian politicians and policy makers favoured post WW2. However, review of the historical data and qualitative interviews with some of these men show that the accepted narrative of a homogenous pre-WW2 British origin population is over simplistic. The historical research suggests that the presumption that post WW2 British migrant men were coming into an homogenous, privileging environment in migrating to SA is both ahistorical and crude. Furthermore the belief that post WW2 British migrant men were ethnically homogenous is undermined by the qualitative research, that reveals that their presumed homogeneity is much more fluid and nuanced than dominant conceptualisations have allowed. The impact of core ethnicities that continue to exist and compete in Britain, the social class focus and economic commodification of migrants in the machinations of powerful players in the state of South Australia all confound homogenizing, simplistic knowing of British migrant men in this state. Generically these findings caution social researchers with regard to presuming to know so called “privileged” populations as well as presumed non-privileged groups.     

Clustering patents using non-exhaustive overlaps

Patent documents are unique external sources of information that reveal the core technology underlying new inventions.Patents also serve as a strategic data source that can be mined to discover state-of-the-art technical development and subsequently help guide R&D investments.This research incorporates an ontology schema to extract and represent patent concepts.A clustering algorithm with non-exhaustive overlaps is proposed to overcome deficiencies with exhaustive clustering methods used in patent mining and technology discovery.The non-exhaustive clustering approach allows for the clustering of patent documents with overlapping technical findings and claims,a feature that enables the grouping of patents that define related key innovations.Legal advisors can use this approach to study potential cases of patent infringement or devise strategies to avoid litigation.The case study demonstrates the use of non-exhaustive overlaps algorithm by clustering US and Japan radio frequency identification (RFID) patents and by analyzing the legal implications of automated discovery of patent infringement.     

调节大豆籽粒生育的生理生态因素

大豆籽粒是生殖生长时期植株光合产物主要存储库,鼓粒灌浆期籽粒的生长发育以及干物质积累的过程直接影响大豆的产量。因此,研究大豆籽粒的生长发育及其影响因素对提高产量至关重要。影响大豆籽粒生长发育的因素很多,从源库的改变、外界温度、光照、水分供应以及二氧化碳的浓度的影响,酶活性、内源物质含量的调节以及植物激素的调控等方面予以综述。参64。     

Automatic patent document summarization for collaborative knowledge systems and services

Engineering and research teams often develop new products and technologies by referring to inventions described in patent databases. Efficient patent analysis builds R&D knowledge, reduces new product development time, increases market success, and reduces potential patent infringement. Thus, it is beneficial to automatically and systematically extract information from patent documents in order to improve knowledge sharing and collaboration among R&D team members. In this research, patents are summarized using a combined ontology based and TF-IDF concept clustering approach. The ontology captures the general knowledge and core meaning of patents in a given domain. Then, the proposed methodology extracts, clusters, and integrates the content of a patent to derive a summary and a cluster tree diagram of key terms. Patents from the International Patent Classification (IPC) codes B25C, B25D, B25F (categories for power hand tools) and B24B, C09G and H011 (categories for chemical mechanical polishing) are used as case studies to evaluate the compression ratio, retention ratio, and classification accuracy of the summarization results. The evaluation uses statistics to represent the summary generation and its compression ratio, the ontology based keyword extraction retention ratio, and the summary classification accuracy. The results show that the ontology based approach yields about the same compression ratio as previous non-ontology based research but yields on average an 11% improvement for the retention ratio and a 14% improvement for classification accuracy.     

Operationalising “Double-Loop” Learning in Service Organisations: A Systems Approach for Creating Knowledge

Learning organisation literature has widely discussed the connections between “double-loop” learning and its significance to organisational performance, but paying little attention to tools and systems that can operationalise “double-loop” learning in organisations. This paper investigates the impact of applying a systems approach for service operations design, expressed as the Vanguard Method (Seddon, Freedom from command and control: a better way to make the work work, 2003), in order to activate “double-loop” learning in service organisations. Two case studies were conducted in the banking mortgage operations and adults’ social care services in the UK, using the dimensions of the learning organisation questionnaire (DLOQ), semi-structured interviews, observations, and documents. The findings of the cross-case analysis support the link of applying the Vanguard Method with operationalising “double-loop” learning through three main factors, namely systematic-operations improvement, organisational capacity development, and outside-in mode of work; that are all embedded into the seven dimensions of the DLOQ. The value of this paper is the introduction of a service operations design tool that can activate “double-loop” learning performance in the fast changing knowledge era. It also provides an impetus for service organisations to creatively influence employees’ competencies to effectively improve internal systems.     

美国东北部早熟和晚熟玉米杂交种年际间产量稳定性

玉米是美国东北部奶牛业的主要能量来源，杂交种的选择是提高玉米产量、降低生产成本的关键和前提。连续5年在美国麻省大学农学实验站的典型砂壤土耕地上进行试验，结合当地气象部门提供的生育期间玉米的生长期生长度日数和降雨量，对3个早熟杂交种和3个晚熟杂交种的产量进行了年际间稳定性比较。结果表明：产量与年际间气候条件无关，无论是青贮饲料产量还是穗棒产量，晚熟品种的产量均高于早熟品种（2001年杂交种E409L）。5年平均晚熟品种的青贮饲料产量和穗棒产量分别比早熟品种高出10．9％和8．0％。相同年份品种间产量存在差异，同一品种年际间产量差异显著。低温年份，相对冷凉的生育前期和温热的生育后期不利于美国东北部玉米生产。生育期间较高的降雨量有利于青贮产量的形成。选择种植晚熟品种是该区农民提高玉米产量、降低生产成本的有效途径。只有热量多且雨量充沛的年份才有利于玉米产量潜力的挖掘。有关某种玉米基因型对当地气候适应性方面的知识，将有利于育种者选择有价值的种质资源。表6，参17。     

Best weight pattern evaluation based security constrained power dispatch algorithm

This paper presents a methodology which determines the allocation of power demand among the committed generating units while minimizes number of objectives as well as meets physical and technological system constraints. The procedure considers two decoupled problems based upon the dependency of their goals on either active power or reactive power generation. Both the problems have been solved sequentially to achieve optimal allocation of active and reactive power generation while minimizes operating cost, gaseous pollutants emission objectives and active power transmission loss with consideration of system operating constraints along with generators prohibited operating zones and transmission line flow limits. The active and reactive power line flows are obtained with the help of generalized generation shift distribution factors （GGDF） and generalized Z-bus distribution factors （GZBDF）, respectively. First problem is solved in multi-objective framework in which the best weights assigned to objectives are determined while employing weighting method and in second problem, active power loss of the system is minimized subject to system constraints. The validity of the proposed method is demonstrated on 30-bus IEEE power system.     

Multiple Correspondence Analysis via Polynomial Transformations of Ordered Categorical Variables

We present an alternative approach to Multiple Correspondence Analysis (MCA) that is appropriate when the data consist of ordered categorical variables. MCA displays objects (individuals, units) and variables as individual points and sets of category points in a low-dimensional space. We propose a hybrid decomposition on the basis of the classical indicator super-matrix, using the singular value decomposition, and the bivariate moment decomposition by orthogonal polynomials. When compared to standard MCA, the hybrid decomposition will give the same representation of the categories of the variables, but additionally, we obtain a clear association interpretation among the categories in terms of linear, quadratic and higher order components. Moreover, the graphical display of the individual units will show an automatic clustering.