'Driving people crazy': A geography of boy racers in Christchurch, New Zealand

Abstract:   So-called 'boy racers' form a subculture, which is subject to ongoing public scrutiny and media attention, usually negative. This study aimed to deconstruct the term 'boy racer' and to explore the subculture in detail, within the context of Christchurch, New Zealand, using a phenomenological ethnographic approach. This included conducting semistructured interviews and observing the activities of participants. Results show the subculture has a relatively diverse membership and a range of associated behaviours, activities and attitudes. Moreover, performances within the subculture are linked to place, and are seen by other members of the community as threats to normative boundaries.     

海底双相随机介质声反射的SVM神经网络分类识别研究

考虑海底沉积介质为双相介质,为了更好地模拟实际海底底质的不均匀性,将随机介质理论引入双相介质理论。首先,通过基于随机-双相介质理论的高阶有限差分数值技术模拟计算海底底质分别为泥质砂、泥、泥质砾时的地震反射波信号。然后利用小波变换分别求取不同底质的一次反射波的包络作为其特征向量,最后利用基于粒子群智能算法优化的支持向量机神经网络对这些反射波信号进行分类识别。为了进一步考察所用方法的抗噪能力,对正演得到的海底底质反射波信号分别加入10%、30%、50%的高斯白噪音之后再进行分类,支持向量机仍然取得了较好的分类预测效果。基于上述正演模拟及分类识别方法的论证,提出了一套行之有效的微机软件模拟海底沉积物分类识别的一般化流程,这将有利于开展海底沉积物反射特征的进一步研究。     

Least‐square support vector machine applied to settlement of shallow foundations on cohesionless soils

This paper examines the potential of least‐square support vector machine (LSVVM) in the prediction of settlement of shallow foundation on cohesionless soil. In LSSVM, Vapnik's ε‐insensitive loss function has been replaced by a cost function that corresponds to a form of ridge regression. The LSSVM involves equality instead of inequality constraints and works with a least‐squares cost function. The five input variables used for the LSSVM for the prediction of settlement are footing width (B), footing length (L), footing net applied pressure (P), average standard penetration test value (N) and footing embedment depth (d). Comparison between LSSVM and some of the traditional interpretation methods are also presented. LSSVM has been used to compute error bar. The results presented in this paper clearly highlight that the LSSVM is a robust tool for prediction of settlement of shallow foundation on cohesionless soil. Copyright © 2008 John Wiley & Sons, Ltd.     

基于EEMD和ARIMA的海温预测模型研究

类型丰富、时空分辨率高的海洋探测数据,为信号分解和机器学习算法的应用提供了可能。本文针对如何建立有效的海温预测模型这一问题,使用高时空分辨率的海表温度(SST)融合产品,引入信号处理领域的集合经验模态分解(EEMD)和机器学习领域的自回归积分滑动平均模型(ARIMA)。首先利用最适于分解自然信号的EEMD方法,将海温数据分解成多个确定频率的序列;再利用ARIMA分别对各个频率的序列进行预测,最后将各个序列的预测结果进行组合。该方法在丰富数据的支撑下,比以往直接使用海温数据所建立的预测模型精度更高,为更好地进行海温预测提供了新方法。     

高光谱影像概率分类向量机分类方法研究

从分析基于支持向量机和相关向量机的高光谱影像分类方法的优势和不足出发,将基于概率分类向量机的方法用于高光谱影像分类试验。在贝叶斯理论框架下,概率分类向量机为基函数权值引入截断Gauss先验概率分布,使得不同类别的基函数权值具有不同符号的先验分布,并利用EM算法进行参数推断,得到足够稀疏的概率模型,弥补了相关向量机选取错误类别的样本作为相关向量的不足,从而有效地提高了模型的分类精度和稳定性。OMIS和PHI影像分类试验表明,概率分类向量机能够很好地应用在高光谱影像分类。     

Ecological Modernization or Aristocratic Conservation? Exploring the Impact of Affluence on Carbon Emissions at the Local Level

Social scientists have debated how affluence impacts carbon emissions at the national level. We conduct an exploratory study at the subnational level to expose another dimension of the affluence–emissions debate. Based on the notion of aristocratic conservation, we hypothesize that affluence is positively related to carbon emissions from consumption activities but negatively related to emissions from production activities. We test these hypotheses using county-level data in the United States for the year 2002. A spatial regression analysis demonstrates that median household income is positively associated with consumption-based emissions; nevertheless, we find evidence of an environmental inequality Kuznets curve in the relationship between median household income and production-based emissions. This finding suggests that the wealthiest counties are able to displace certain types of emissions, specifically those related to energy and industrial production. We discuss the theoretical and political implications of these results.     

基于支撑向量机概率输出的高光谱影像混合像元分解

提出利用支撑向量机(SVM)后验概率来分解高光谱影像的混合像元,通过支撑向量机的输出值转化为两两配对的后验概率,再由两两配对的概率值求得多类后验概率,并以像元所属类别的后验概率作为地物的组分信息。实验结果表明,该方法能较好地估计出混合像元的组分比。     

高分一号遥感影像地质灾害信息提取方法研究

山区地质灾害发生频繁,受灾范围大,危害严重。提取地质灾害信息、估算受灾情况,对救灾工作极为重要。传统的遥感人工解译方法速度慢、效率低;计算机自动解译速度快但解译精度受影像质量影响大,大范围地区很难建立起普适性的解译模型。本文利用洮南市西部高分一号遥感数据,结合DEM生成三维影像,建立解译标志,解译基础地质信息,分析地质灾害成因;根据研究区泥石流地质灾害的主要影像特征,提取影像的分类属性,基于面向对象的分类方法,建立信息提取模型,快速提取出地质灾害敏感区域;再进行人机交互,精确提取出地质灾害的类型和范围,通过野外验证,该方法十分可靠,为大范围地质灾害信息快速提取和灾后救援提供科学依据。     

爆破扰动下TBM隧洞时滞型岩爆特征及影响机制研究

时滞型岩爆的发生通常具有很强的随机性,会对施工安全造成巨大的威胁,而开挖扰动、爆破扰动等均会对潜在时滞型岩爆区产生不同程度的影响。依托某隧道掘进机（TBM）引水隧洞,采用理论分析和对比分析法研究了拆机洞爆破开挖期间K54+000—K54+700段发生的5次时滞型岩爆,发现：（1）强烈岩爆和中等岩爆区位于缓倾断层附近,围岩发育短小隐节理和含充填的细密节理,轻微岩爆距断层远或位于正断层附近,除含充填的细密节理外,均至少发育1条含充填物的倾向SW的陡倾结构面;（2）TBM法开挖隧洞时滞型岩爆滞后爆破时间更长,滞后工作面距离更远,且爆破对TBM隧洞的扰动作用相对较小;（3）爆破扰动使得潜在时滞型岩爆区围岩失稳变得容易,从而加速了时滞型岩爆的进程。研究成果可为TBM隧洞时滞型岩爆的预警与防控提供参考。     

Drainage density changes during rainfall

Observations of stream behaviour during rainfall indicate that previous notions of a simple expanding and contracting network need review and refinement. In a small rural catchment near Armidale, N.S.W. changes in flowing stream length during rainfall have been depicted on flow length graphs which indicate a varied network response to similar rainfall amounts. Channel flow phenomena include discontinuous flow, the generation of flow points within the channel and movement of water downslope from saturated depression sources. Localized physical controls have a significant effect on stream growth which is a sensitive indicator of the catchment response to rainfall. During rapid changes in stream length total flowing length and discharge are highly correlated. A model of the pattern of network expansion and contraction involves several phases of flow contraction.