用CIS实时检测液位的系统

圆柱形透明容器中液体使透射光会聚,空气使透射光发散。将CIS放在液柱透镜的焦线上,则CIS接收到的液体段透射光比空气段透射光强得多。液位不断升高,则CIS接收到强光的像元数不断增加,经后续信号处理可获得圆柱形透明容器中的实时液位。当液位变化范围在CIS高度范围内时,用CIS就可实时检测透明容器中的液位。此方法简单可靠,在200mm的检测范围内,实测了18个液位,平均液位误差0.185mm,最大液位误差0.66mm。     

非制冷长波红外焦平面列阵现状

文章介绍了非制冷测辐射热计和铁电陶瓷焦平面列阵的现状，包含8万个非制冷氧化钒红外探测器的焦平面列阵已制成热像仪，系统的噪声等效温差（NETD）为0．04℃，不需要制冷和机械调制入射辐射。多晶硅热敏电阻和硅p－n结温差电堆焦平面列阵的研究工作取得了进展，用溅射和化学汽相淀积技术已制成128×128元硅薄膜测辐射热计焦平面列阵，单元探测器的探测率为1×109cmHzW－1；128×128元温差电堆焦平面列阵的NETD为0．5℃。利用热释电效应和介电常数温度变化的铁电陶瓷焦平面列阵制成的热像仪，NETD已达到0．047℃。     

单片式PtSi肖特基势垒IR—ITCCD焦平面列阵

本文介绍了PtSi肖特基势垒IRCCD的工作原理,评述了国外硅化物肖特基势垒红外焦平面列阵的发展,重点阐述了已制成的64×64、128×128元PtSi肖特基势垒IR-ITCCD焦平面列阵的结构与设计思想。     

128×128 element PtSi infrared CCD image sensor

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Head injuries in lateral impact collisions

Individual non-minor injuries (Abbreviated Injury Scale (AIS) ≥ 2) to the head that occurred to belted and unbelted drivers and front seat passengers on the struck side of impacted vehicles were examined. Injury type, injury combination, collision severity in relation to type of injury as well as contact sources were assessed. Forty-eight percent of injuries were moderate in severity (AIS 2). The most common type of injury was the diffuse brain injury, typically marked by a short period of unconsciousness, which occurred in collisions of lower severity than focal brain and skull fracture injuries. One-hundred and five out of 216 (48.6%) of contact sources for all injury types originated from outside the vehicle and such exterior sources were more likely to result in high severity injuries. Thirty percent of injuries resulted from head contacts with other vehicles. The most frequent vehicle interior contact source was the side window glass. Diffuse injuries tended to occur independently of other injury types and were more likely to originate from an interior rather than exterior contact. Preventative measures for head injury reduction in lateral collisions are discussed. Overall, the data show that proposed and present European and U.S. lateral impact test methods do not address many head injury problems such as those included in this study.     

Computing camera focal length by zooming a single point

In this paper we present a novel simple procedure to compute the focal length of a camera. The method is based on zooming in and out only a single point. The same approach allows computing the principal point when only two points are available on a pair of images surveyed with a different focal length. Experimental results show that the method is as accurate as classical full calibration methods. Moreover, its application to augmented reality produces more accurate results than those obtained when the simple pin-hole model is considered.     

The application of focal species knowledge to landscape design in agricultural lands using the ecological neighbourhood as a template

The focal species approach to nature conservation provides a method for identifying management actions required to meet the needs of the most vulnerable species in a landscape with respect to the threatening processes responsible for their decline. For each threat, a focal species is identified as the one with the most critical requirement pertaining to the threat. With multiple threats, the resulting suite of focal species can be regarded as a “focal community”, whose combined needs are used to address a range of management actions. In this paper, the critical requirements of a focal community of resident land birds are identified with respect to the threats arising from the loss, fragmentation and degradation of habitat in the central wheat-belt of Western Australia. This knowledge of their critical requirements is then used to guide a landscape design procedure for the enhancement of bird habitat in the Gabbi Quoi Quoi sub-catchment of Western Australia. The landscape design procedure is framed against the concept of the ecological neighbourhood, where the necessary size, spatial arrangement, area of influence and connectivity of existing landscape elements are used as a starting point for habitat restoration and re-vegetation.     

基于边界自适应SMOTE和Focal Loss函数改进LightGBM的信用风险预测模型

针对信用风险评估中数据集不平衡影响模型预测效果的问题,提出一种基于边界自适应合成少数类过采样方法（BA-SMOTE）和利用Focal Loss函数改进LightGBM损失函数的算法（FLLightGBM）相结合的信用风险预测模型。首先,在边界合成少数类过采样（Borderline-SMOTE）的基础上,引入自适应思想和新的插值方式,使每个处于边界的少数类样本生成不同数量的新样本,并且新样本的位置更靠近原少数类样本,以此来平衡数据集;其次,利用Focal Loss函数来改进LightGBM算法的损失函数,并以改进的算法训练新的数据集以得到最终结合BA-SMOTE方法和FLLightGBM算法建立的BA-SMOTE-FLLightGBM模型;最后,在Lending Club数据集上进行信用风险预测。实验结果表明,与其他不平衡分类算法RUSBoost、CUSBoost、KSMOTE-AdaBoost和AK-SMOTE-Catboost相比,所建立的模型在G-mean和AUC两个指标上都有明显的提升,提升了9.0%~31.3%和5.0%~14.1%。以上结果验证了所提出的模型在信用风险评估中具有更好的违约预测效果。