Object detection using feature subset selection

Past work on object detection has emphasized the issues of feature extraction and classification, however, relatively less attention has been given to the critical issue of feature selection. The main trend in feature extraction has been representing the data in a lower dimensional space, for example, using principal component analysis (PCA). Without using an effective scheme to select an appropriate set of features in this space, however, these methods rely mostly on powerful classification algorithms to deal with redundant and irrelevant features. In this paper, we argue that feature selection is an important problem in object detection and demonstrate that genetic algorithms (GAs) provide a simple, general, and powerful framework for selecting good subsets of features, leading to improved detection rates. As a case study, we have considered PCA for feature extraction and support vector machines (SVMs) for classification. The goal is searching the PCA space using GAs to select a subset of eigenvectors encoding important information about the target concept of interest. This is in contrast to traditional methods selecting some percentage of the top eigenvectors to represent the target concept, independently of the classification task. We have tested the proposed framework on two challenging applications: vehicle detection and face detection. Our experimental results illustrate significant performance improvements in both cases.     

使用EXCEL进行矿质混合料配合比设计

矿质混合料组成设计的方法很多,有试算法、正规方程法、图解法等。由于正规方程法解算复杂,一般很少使用,但用EXCEL（电子表格）进行解算矩阵方程,则相对准确、快速,所以用例题求解的方式,进行了方程解算的介绍,使矿质混合料配合比设计简单化。     

Arbitrarily 3D Configurable Hygroscopic Robots with a Covalent–Noncovalent Interpenetrating Network and Self‐Healing Ability

Soft materials that can reversibly transform shape in response to moisture have applications in diverse areas such as soft robotics and biomedicine. However, the design of a structurally transformable or mechanically self‐healing version of such a humidity‐responsive material, which can arbitrarily change shape and reconfigure its 3D structures remains challenging. Here, by drawing inspiration from a covalent–noncovalent network, an elaborately designed biopolyester is developed that features a simple hygroscopic actuation mechanism, straightforward manufacturability at low ambient temperature (≤35 °C), fast and stable response, robust mechanical properties, and excellent self‐healing ability. Diverse functions derived from various 3D shapes that can grasp, swing, close–open, lift, or transport an object are further demonstrated. This strategy of easy‐to‐process 3D structured self‐healing actuators is expected to combine with other actuation mechanisms to extend new possibilities in diverse practical applications.     

Large‐Area Compliant,Low‐Cost,and Versatile Pressure‐Sensing Platform Based on Microcrack‐Designed Carbon Black@Polyurethane Sponge for Human–Machine Interfacing

It is a challenge to manufacture pressure‐sensing materials that possess flexibility, high sensitivity, large‐area compliance, and capability to detect both tiny and large motions for the development of artificial intelligence products. Herein, a very simple and low‐cost approach is proposed to fabricate versatile pressure sensors based on microcrack‐designed carbon black (CB)@polyurethane (PU) sponges via natural polymer‐mediated water‐based layer‐by‐layer assembly. These sensors are capable of satisfying the requirements of ultrasmall as well as large motion monitoring. The versatility of these sensors benefits from two aspects: microcrack junction sensing mechanism for tiny motion detecting (91 Pa pressure, 0.2% strain) inspired by the spider sensory system and compressive contact of CB@PU conductive backbones for large motion monitoring (16.4 kPa pressure, 60% strain). Furthermore, these sensors exhibit excellent flexibility, fast response times (<20 ms), as well as good reproducibility over 50 000 cycles. This study also demonstrates the versatility of these sensors for various applications, ranging from speech recognition, health monitoring, bodily motion detection to artificial electronic skin. The desirable comprehensive performance of our sensors, which is comparable to the recently reported pressure‐sensing devices, together with their significant advantages of low‐cost, easy fabrication, especially versatility, makes them attractive in the future of artificial intelligence.     

用硅石生产高纯石英粉新技术

高纯石英粉是宇航、电子工业、电光源管、光学仪器、光纤通讯等高科技产品的基础原材料,要求ＳｉＯ２的纯度在９９．９９％以上。在缺乏有效的提纯技术情况下,只能用自然界优质水晶经简单提纯来满足工业需要。随着科技的进步,尤其是微电子技术的发展,高纯石英粉需求量成倍增长,并且对质量要求也愈来愈高。而天然水晶属于稀有矿产,特别是一、二级水晶已日渐枯竭,寻找水晶的代用品已成当务之急。用硅石生产高纯石英粉涉及地质、岩相、选矿、设备等多个专业,是多学科成果的结晶。一、石英成因的类型简介硅石是以石英为主要成分矿石的总…     

Intra-class low-rank regularization for supervised and semi-supervised cross-modal retrieval

Cross-modal retrieval aims to retrieve related items across different modalities, for example, using an image query to retrieve related text. The existing deep methods ignore both the intra-modal and inter-modal intra-class low-rank structures when fusing various modalities, which decreases the retrieval performance. In this paper, two deep models (denoted as ILCMR and Semi-ILCMR) based on intra-class low-rank regularization are proposed for supervised and semi-supervised cross-modal retrieval, respectively. Specifically, ILCMR integrates the image network and text network into a unified framework to learn a common feature space by imposing three regularization terms to fuse the cross-modal data. First, to align them in the label space, we utilize semantic consistency regularization to convert the data representations to probability distributions over the classes. Second, we introduce an intra-modal low-rank regularization, which encourages the intra-class samples that originate from the same space to be more relevant in the common feature space. Third, an inter-modal low-rank regularization is applied to reduce the cross-modal discrepancy. To enable the low-rank regularization to be optimized using automatic gradients during network back-propagation, we propose the rank-r approximation and specify the explicit gradients for theoretical completeness. In addition to the three regularization terms that rely on label information incorporated by ILCMR, we propose Semi-ILCMR in the semi-supervised regime, which introduces a low-rank constraint before projecting the general representations into the common feature space. Extensive experiments on four public cross-modal datasets demonstrate the superiority of ILCMR and Semi-ILCMR over other state-of-the-art methods.

     

基于四象限高压变频器的水泵机组反向发电探讨

基于四象限电子变频器的水泵机组变频运行方式可以较好地实现水泵机组反向发电的并网,并可根据水头实现无极变频,确保机组始终处于高效区运行,提高发电效率;变频调节具有较高的调节精度和调节速度,可以避免对电网和电机的冲击;变频器的使用可以免去机械变频机组的维护量和占地空间.     

On-road vehicle detection: a review

Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. In these systems, robust and reliable vehicle detection is a critical step. This paper presents a review of recent vision-based on-road vehicle detection systems. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. First, we discuss the problem of on-road vehicle detection using optical sensors followed by a brief review of intelligent vehicle research worldwide. Then, we discuss active and passive sensors to set the stage for vision-based vehicle detection. Methods aiming to quickly hypothesize the location of vehicles in an image as well as to verify the hypothesized locations are reviewed next. Integrating detection with tracking is also reviewed to illustrate the benefits of exploiting temporal continuity for vehicle detection. Finally, we present a critical overview of the methods discussed, we assess their potential for future deployment, and we present directions for future research.     

永磁体对磁致伸缩位移传感器波导丝扭转应变的影响分析

为提高磁致伸缩位移传感器输出电压幅值,对波导丝的扭转应变进行研究.基于电磁学与理论力学相关理论建立了波导丝扭转应变的数学模型及三维有限元仿真模型,对波导丝扭转应变的影响因素进行分析.并进行实验,得出相对应的传感器输出电压变化情况.结果表明,传感器输出电压与波导丝发生的扭转应变量最大值变化趋势一致,两者均随着永磁体充磁、...     

在交通拥堵的隧道火灾中纵向通风的合理送风风速研究

通过数值模拟手段对纵向通风时隧道内的烟气扩散特性进行研究,探讨较低风速时,针对不同火源功率、不同风速作用下,火源上、下游烟气的分层特性及温度分布特性,并在此基础上探讨纵向排烟在拥堵的交通隧道中应用的可能性.研究结果表明:如果起火初期隧道内以较低的纵向风速送风,保证上、下游烟气分层的存在,则纵向通风可用于交通拥堵的隧道.火源功率为5 MW时,该风速约为1.0 m/s;火源功率为20 MW时,较适宜的风速为1.0～1.5 m/s;火源功率为30 MW时,较适宜的风速为1.5 m/s左右.火源功率较大时,应尽早将火源下游附近的人员疏散,以确保安全.