贵州省道真县大塘铝土矿矿石特征

本次对大塘铝土矿研究区进行矿石类型划分,对其矿物、化学成分等进行研究,得出矿石特征及成因。矿石矿物以铝矿物为主,隐晶、豆状、粒屑结构等,块状构造,其主要化学成分为Al2O3、SiO2、Fe2O3、TS、TiO2。铝土矿石赋存层位为大竹园组,属Ⅳ-Ⅴ级品,产于遭受长期风化剥蚀的古陆边缘,为古风化壳沉积型矿床。     

Effect of CO2 and O2 Mixed Injection on the Decarburization and Manganese Retention in High-Mn Twinning-Induced Plasticity Steels

Metallurgical and Materials Transactions B - In order to achieve decarburization and manganese retention simultaneously, CO2 was introduced in the smelting process of high-Mn twinning-induced...     

考虑孤岛现象的储能系统奇次谐波频谱分析

为了实现对电力储能系统的协调控制能力,提出基于孤岛现象的储能系统奇次谐波频谱分析方法,构建多类型储能系统的奇次谐波检测模型,在孤岛现象作用下进行储能系统的低频成分抑制,将总储能中的低频成分指派给蓄电池,根据储能系统奇次谐波分量,进行超级电容器之间的功率分配,获取能量型储能系统奇次谐波频谱分量,采用波动平抑策略,在考虑孤岛现象作用下,基于模型预测控制算法进行储能系统奇次谐波频谱分析和特征提取,实现功率型超级电容器储能之间的功率优化分配。仿真结果表明,采用该方法进行储能系统奇次谐波频谱特征提取的准确性较好,提高了储能系统的协调控制能力,储能功率得到提升。     

基于操作风险的双模式传感器管理方法

基于风险理论研究同时面向目标检测和跟踪任务的传感器管理方法.首先,定义目标检测风险和目标跟踪风险,并分别给出计算方法;其次,以目标检测风险最小化为目标函数建立传感器部署模型,以目标检测风险和目标跟踪风险之和最小化为目标函数建立传感器调度模型,且该调度发生在前面传感器部署模型建立的传感器网络之上;然后,针对模型的求解,同时为克服基本人工蜂群算法易陷入局部最优的缺点,提出改进的双向轮盘赌-粒子群-蜂群算法;最后,通过仿真验证模型和算法的有效性.     

1961—2016 年西宁市极端降水事件变化特征

为研究西宁市极端降水事件变化规律,利用西宁气象站 1961—2016 年逐日降水量序列资料,计算得出年总降水量、5 日最大降水量、极端降水量、日降水强度、持续降雨日数及大雨日数等 6 个极端降水指标的年际序列,应用线性倾向估计法、滑动平均法、Mann － Kendall 非参数检验法、Morlet小波分析、相关性分析等方法分析各极端降水指标的变化趋势、变化周期及各指标间变化一致性。结果表明,近 56 年间西宁市各极端降水指标呈波动式增加趋势,其中 PＲCPTOT 的增加趋势显著,而其余各指标变化趋势不显著; PＲCPTOT、ＲX5day、Ｒ95 及 SDII 序列在整个研究时段内均存在明显的突变现象,其中在 1960 年代后期及 1970 年代中期 ＲX5day 与 Ｒ95 发生了一致的突变,在 1980年代末和 1990 年代初,PＲCPTOT、ＲX5day 与 SDII 发生了一致的突变; 在近 56 年间各极端降水指标的振荡变化均存在明显的主周期,其中除 SDII 外,从 1990 年代开始各指标多存在约 11—13 年的主周期,SDII 及 CWD 的振荡变化均在整个研究时段上存在 40 年及 29 年左右的主周期; 各极端降水指标与总降水量均呈一致的正相关性,对总降水量的变化具有较好的指示作用,ＲX5day、Ｒ95、SDII 及 Ｒ20mm 四个指标相互之间均存在显著的正相关性。研究结果可为区域水资源规划及洪旱灾害防御提供参考。     

Research on the Pedestrian Re-Identification Method Based on Local Features and Gait Energy Images

The appearance of pedestrians can vary greatly from image to image, and different pedestrians may look similar in a given image. Such similarities and variabilities in the appearance and clothing of individuals make the task of pedestrian re-identification very challenging. Here, a pedestrian re-identification method based on the fusion of local features and gait energy image (GEI) features is proposed. In this method, the human body is divided into four regions according to joint points. The color and texture of each region of the human body are extracted as local features, and GEI features of the pedestrian gait are also obtained. These features are then fused with the local and GEI features of the person. Independent distance measure learning using the cross-view quadratic discriminant analysis (XQDA) method is used to obtain the similarity of the metric function of the image pairs, and the final similarity is acquired by weight matching. Evaluation of experimental results by cumulative matching characteristic (CMC) curves reveals that, after fusion of local and GEI features, the pedestrian reidentification effect is improved compared with existing methods and is notably better than the recognition rate of pedestrian re-identification with a single feature.     

Threshold Filtering Semi-Supervised Learning Method for SAR Target Recognition

The semi-supervised deep learning technology driven by a small part of labeled data and a large amount of unlabeled data has achieved excellent performance in the field of image processing. However, the existing semi-supervised learning techniques are all carried out under the assumption that the labeled data and the unlabeled data are in the same distribution, and its performance is mainly due to the two being in the same distribution state. When there is out-of-class data in unlabeled data, its performance will be affected. In practical applications, it is difficult to ensure that unlabeled data does not contain out-of-category data, especially in the field of Synthetic Aperture Radar (SAR) image recognition. In order to solve the problem that the unlabeled data contains out-of-class data which affects the performance of the model, this paper proposes a semi-supervised learning method of threshold filtering. In the training process, through the two selections of data by the model, unlabeled data outside the category is filtered out to optimize the performance of the model. Experiments were conducted on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset, and compared with existing several state-of-the-art semi-supervised classification approaches, the superiority of our method was confirmed, especially when the unlabeled data contained a large amount of out-of-category data.     

安全性视角下的老年家具设计

目的探析老年家具设计的原则与方法,并立足于安全视角展开生理安全与心理安全层面的具体分析。方法结合当前老龄化社会的实际,提出老年群体对家具的现实需求,接着对老年群体的总体特征进行分析,总结老年人家具设计的功能性与安全设计的关系,提出功能性与生理安全、功能性与心理安全的相互联系,再深入探究老年家具安全性设计在尺寸、色彩、材料等方面的具体实践,并独立出人性化、艺术性等方面的设计细节,对餐饮区、卧室区和会客区的老年家具设计进行分析,并提出了更高层面的艺术化创新方向。结论从老年群体的整体特点进行分析,设计出符合老年人特点的家具,既可以给老年人的日常使用带来便利,降低因身体不便带来的使用困难,又可以给老年人带来一定的成就感,创造出舒适安详的居住环境。     

结合模型集成与特征融合的图像拷贝检测

基于内容的图像拷贝检测关键在于提取的图像特征能够针对不同形式的图像拷贝攻击具有不变性。现实中拷贝攻击手段变化多样,且存在很多相似图像的干扰,目前并没有任何一种图像特征可以对抗所有不同形式的图像攻击。现有方法虽然在图像特征表示上做了很多改进,但都局限于单个特征表示。因此从特征融合的角度对提取特征进行增强,基于卷积神经网络融合图像高层特征以及低层特征以实现特征多样性,集成ImageNet预训练分类模型以及提出的距离度量模型以实现特征互补性。度量模型针对该类问题在预训练模型的基础上通过学习合适的距离度量来对抗由于图像编辑引起的特征差异,拉近拷贝图像与原始图像在特征空间的距离。实验结果表明,结合模型集成和多层深度特征融合的方式可以有效增强特征的鲁棒性,相比单一特征的检测效果提升十分明显。     

基于多目标遗传算法的LoRa参数匹配优化

从工程应用角度出发,需要LoRa无线传输系统兼备系统功耗低、传输距离短、系统稳定性好的特点,优化设计匹配参数是提高LoRa传输性能的重要途径。以LoRa无线通信的能耗最低、最远传输距离最大以及系统的鲁棒性最强为优化目标,以SF、BW、CR等参数的有效取值为约束条件,采用线性加权的方法将多目标优化问题转换为单目标问题,求出最优解。仿真和实际测试结果表明,遗传算法应用于LoRa的参数匹配具有可行性和有效性。