Collaboration Across Borders: Moving Beyond Positionality

Discussions about collaborative spaces in postcolonial feminist and geographical analyses have often hinged on questions of positionality, reflexivity and identity, largely in relation to the politics of representation. Such approaches have often led to an impasse, especially in fieldwork-based feminist research, where reflexivity has mainly focused on examining the identities of the individual researcher rather than on the ways in which those identities intersect with institutional, geopolitical and material aspects of their positionality. This kind of identity-based reflexivity does not distinguish systematically between the ethical, ontological and epistemological aspects of fieldwork dilemmas; it also fails to adequately address how our ability to align our theoretical priorities with the concerns of communities whose struggles we want to advance is connected to the opportunities, constraints and values embedded in our academic institutions. This article takes this discussion forward by arguing for a postcolonial and transnational feminist praxis that focuses explicitly and deliberately on (a) conceptualising and implementing collaborative efforts that insist on crossing multiple and difficult borders; (b) the sites, strategies and skills deployed to produce such collaborations; and (c) the specific processes through which such collaborations can find their form, content and meaning. To ground this discussion, I draw upon two collaborative initiatives that I have begun recently in the state of Uttar Pradesh, north India.     

Relevance vector machine‐based response surface for slope reliability analysis

A new computing method is proposed for reliable analysis. The limit state function is implicit and nonlinear in reliability analysis of slopes and is difficult to apply by traditional reliability methods, especially in large‐scale project applications. Relevance vector machines (RVMs) are capable of approximating the limit state function without the need for additional assumptions regarding the function form, as opposed to traditional polynomial response surfaces. RVMs were adapted to obtain the limit state function. We propose an RVM‐based response surface method combined with the first‐order reliability method for slope reliability analysis and describe its step‐by‐step implementation. The reliability index obtained from the proposed method shows excellent agreement with traditional response surface method results. Copyright © 2017 John Wiley & Sons, Ltd.     

固体矿产勘查报告章节层次及其关联性分析

从固体矿产勘查报告编写提纲所要求的各章节的主要内容出发,在分析勘查报告各章节主要层次的基础上,进一步分析了各章节内部及章节间的关联性,同时指出认识并遵循这种层次和关联性,可以有效避免报告编写时章节层次设置的不合理和编制内容的重复,并促进报告编制质量和水平的提高。     

济南市长清区五峰山—张夏一带土壤元素与植物元素相关性分析

在济南市长清区五峰山-张夏一带选取植物样及相应的土壤样进行化验,采用线性回归的分析方法,计算出相关系数,判断其相关性,对此工作区农作物的适宜种植性具有指导作用。     

Building more realistic reservoir optimization models using data mining - A case study of Shelbyville Reservoir

In this paper, we promote a novel approach to develop reservoir operation routines by learning from historical hydrologic information and reservoir operations. The proposed framework involves a knowledge discovery step to learn the real drivers of reservoir decision making and to subsequently build a more realistic (enhanced) model formulation using stochastic dynamic programming (SDP). The enhanced SDP model is compared to two classic SDP formulations using Lake Shelbyville, a reservoir on the Kaskaskia River in Illinois, as a case study. From a data mining procedure with monthly data, the past month’s inflow (Q_t−1), current month’s inflow (Q_t), past month’s release (R_t−1), and past month’s Palmer drought severity index (PDSI_t−1) are identified as important state variables in the enhanced SDP model for Shelbyville Reservoir. When compared to a weekly enhanced SDP model of the same case study, a different set of state variables and constraints are extracted. Thus different time scales for the model require different information. We demonstrate that adding additional state variables improves the solution by shifting the Pareto front as expected while using new constraints and the correct objective function can significantly reduce the difference between derived policies and historical practices. The study indicates that the monthly enhanced SDP model resembles historical records more closely and yet provides lower expected average annual costs than either of the two classic formulations (25.4% and 4.5% reductions, respectively). The weekly enhanced SDP model is compared to the monthly enhanced SDP, and it shows that acquiring the correct temporal scale is crucial to model reservoir operation for particular objectives.     

基于极限位移准则和变形预测的滑坡变形潜势分析

为准确掌握库区滑坡变形潜势,在变形监测成果统计基础上,首先利用极限位移准则开展滑坡现状变形潜势分析;然后以相关向量机为理论基础,通过优化处理保证其参数最优性,构建滑坡变形预测模型,并以预测结果开展滑坡变形潜势的发展趋势评价;最后结合两种分析结果,实现滑坡综合变形潜势分析。结果表明,不同监测点的现状变形潜势状态存在一定差异,由不利原则可知,现状变形潜势等级为Ⅳ级,潜势程度属严重状态;滑坡变形仍会进一步增加,变形潜势趋于不利方向发展。综合两种分析结果可知,滑坡变形潜势处于不利状态,后期失稳可能性较大,应加强灾害防治,避免成灾损失。     

统一地址赋能社会治理的关键技术

统一地址的概念于近些年才被提出,其主要本质和意义是在充分尊重现有各部门行业标准地址的基础上,作为社会治理要素有效关联融合的"桥梁",为摸清底数、精准施策等精细治理工作提供支撑,是测绘地理信息技术在社会治理数字化、智能化领域的创新应用.本文针对统一地址在建设过程中的关键技术进行初步研究,并简单介绍了杭州市的实际应用情况.     

基于EM算法优化相关向量机的BDS-3超快速钟差预报

提出一种基于EM算法优化相关向量机(RVM)的BDS-3超快速钟差预报算法。首先,利用组合MAD法预处理钟差数据,并进行一次差分计算;然后,利用钟差一次差分数据对RVM模型进行训练,通过EM算法迭代求取模型的超参数;最后,利用优化后的RVM模型进行数据预测,将钟差一次差分预测值还原,得到钟差预报值。采用iGMAS中心提供的实测BDS-3超快速钟差数据进行预报实验,并将本文模型与QP模型、SA模型及iGMAS超快速钟差预报产品(ISU-P)结果进行对比分析。结果表明,对于6 h、12 h和24 h预报,本文模型预报BDS-3卫星钟差数据的平均精度均优于0.61 ns;与ISU-P、QP模型和SA模型相比,本文模型预报24 h时精度分别提升64.1%、50.0%和49.2%。