Curvedness feature constrained map matching for low-frequency probe vehicle data

Map matching method is a fundamental preprocessing technique for massive probe vehicle data. Various transportation applications need map matching methods to provide highly accurate and stable results. However, most current map matching approaches employ elementary geometric or topological measures, which may not be sufficient to encode the characteristic of realistic driving paths, leading to inefficiency and inaccuracy, especially in complex road networks. To address these issues, this article presents a novel map matching method, based on the measure of curvedness of Global Positioning System (GPS) trajectories. The curvature integral, which measures the curvedness feature of GPS trajectories, is considered to be one of the major matching characteristics that constrain pairwise matching between the two adjacent GPS track points. In this article, we propose the definition of the curvature integral in the context of map matching, and develop a novel accurate map matching algorithm based on the curvedness feature. Using real-world probe vehicles data, we show that the curvedness feature (CURF) constrained map matching method outperforms two classical methods for accuracy and stability under complicated road environments.     

基于改进K-SVD字典学习方法的地震数据去噪

为实现更好的地震数据去噪技术,笔者引入一种新的算法:快速迭代收缩阀值法(FISTA),通过FISTA和K-奇异值分解(K-SVD)不断迭代更新K-SVD字典,利用更新得到的K-SVD字典对地震数据进行稀疏表示,去除稀疏系数中较小的数值,使数据中的随机噪声得到压制。对层状模型合成地震记录,Marmousi模型合成地震记录以及实际地震数据进行对比实验,得出FISTA算法较OMP算法能更好地提高地震数据的信噪比,同时有效地保护了反射信号。     

Research Progress and Prospect on Reactivation of Ancient Landslides

The ancient landslide has endured long-term slope evolution which results in its complicated material and special rock-soil properties. The risk of ancient landslide reactivation is substantially increasing due to the increase of intensified human engineering activities and the frequency of extreme weather events. Many ancient landslides have been reactivated all over the world and led to serious fatalities and severe damage to many important engineering facilities such as transportation and hydropower engineering projects. On the basis of the analysis of the research situation about the ancient landslides at home and abroad, the main research advances were summarized including the regional developing laws and recognizing of the ancient landslides, the mechanics properties of ancient landslide body and related sliding zone, reactivation mechanism of ancient landslides, reactivating process and modeling analysis of ancient landslides, early recognization of ancient landslide reactivation, etc. To meet the demands of disaster prevention and reduction, three key scientific issues were put forward to be solved: ①automaticaly establishing the methodology and identification criterions for recognition of ancient landslide; ②revealing the reactivation mechanism of ancient landslide based on a new strength theory; ③establishing the early rapid recognition method and predictive model for ancient landslide reactivation. Solving the above mentioned scientific theory and methodology will facilitate the planning and site selection of major projects as well as the disaster prevention and reduction in ancient landslide developing areas.     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

A geometric-based approach for road matching on multi-scale datasets using a genetic algorithm

Object matching is used in various applications including conflation, data quality assessment, updating, and multi-scale analysis. The objective of matching is to identify objects referring to the same entity. This article aims to present an optimization-based linear object-matching approach in multi-scale, multi-source datasets. By taking into account geometric criteria, the proposed approach uses real coded genetic algorithm (RCGA) and sensitivity analysis to identify corresponding objects. Moreover, in this approach, any initial dependency on empirical parameters such as buffer distance, threshold of spatial similarity degree, and weights of criteria is eliminated and, instead, the optimal values for these parameters are calculated for each dataset. Volunteered geographical information (VGI) and authoritative data with different scales and sources were used to assess the efficiency of the proposed approach. According to the results, in addition to an efficient performance in various datasets, the proposed approach was able to appropriately identify the corresponding objects in these datasets by achieving higher F-Score.     

测井地质学前世、今生与未来——写在《测井地质学·第二版》出版之时

测井地质学以地质学和测井学的方法理论为指导,综合运用各种测井信息,来解决基础地质和石油地质的地质问题。经过数十年发展,测井地质学在油气勘探开发各个环节得到广泛应用。非常规油气的兴起使得测井地质学正面临多重挑战和全新探索,亟需建立针对非常规油气的测井地质学综合方法理论体系。本文以《测井地质学·第二版》出版为契机,系统归纳了测井地质学的起源及发展历程、主要研究内容和研究方法流程。然后总结了测井资料与地震、地质信息的匹配性,并分析了不同探测特性测井方法纵向分辨率区间特征。在此基础上评述了测井地质学在井旁构造解析、沉积学特征研究、层序地层划分、地应力方向判别及大小计算、井壁裂缝识别与评价、烃源岩评价以及非常规油气“七性关系”综合评价当中的应用。但由于测井资料的负载能力有限性、测井与地质信息属性不对应性以及测井资料本身的多解性,使得测井地质学在测井—地质转换、非常规油气测井评价及其与人工智能融合方面还存在一定的问题。因此加强基础岩石物理研究,挖掘测井曲线中包含的地质信息,并与人工智能相结合,将拓展测井地质学研究的精度和广度,从而使其未来可更好地应用至非常规油气测井评价等实践工作中。     

基于脑电信号评价情绪状态及听觉激励对改善情绪的研究

如何从脑活动数据中发现具有生物学意义的知识及规律,正成为当今神经信息学理论与实践研究的热点与难点.基于脑电的情绪识别和情绪及其脑机制的关联研究已经成为神经工程和生物医学工程领域的热门课题.本研究基于脑电信号评价情绪状态,尝试借助脑电耳机来监测"毫无头绪"的脑电波,重点开展了听觉激励对改善焦虑情绪状态的实验研究.借助特定中国古风纯音乐产生听觉信号激励,激发出被试者平静放松的情绪状态,从而改善焦虑,发现音乐和情绪之间可能存在的关系.将来在BCI技术研究的基础之上,情绪识别可以进一步满足患有特定疾病（ALS症、脑瘫、脑干中风、脊髓损伤等）的患者人群的某些更高级的需求,即通过脑电分析出其对事物的喜好度,比如音乐的选择,从而设计出更加友善和智能的BCI系统,在医疗康复领域具有很好的应用前景.     

基于镜像图的LRC和CRC偏差结合的人脸识别

为了提高人脸识别率及更好地显示人脸特征,本文提出了一种基于镜像图的LRC和CRC偏差结合的人脸识别方法.该方法首先生成一种镜像人脸,再通过融合原始人脸和镜像人脸形成新的混合训练样本,最后利用LRC和CRC偏差结合进行人脸识别.新方法增加了训练样本的数目,克服了由于光照和姿态等外部因素带来的影响.实验结果表明,镜像图与LRC和CRC偏差结合的人脸识别方法提高了人脸识别的准确性.     

低剖面紧凑的圆盘加载单极子天线

本文介绍了一种低剖面小型化圆盘加载单极子天线.通过盘加载的方式,在中心频率5.8 GHz处,首先将单极子天线的剖面从大约12.9 mm（0.25λ₀）降低到2 mm（0.039λ₀）,实现了低剖面的特性.加载在单极子天线上方的圆盘,尺寸大概为21 mm（0.41λ₀）,因此天线具有结构紧凑的特点.接着,为了使天线具有良好的匹配,在加载圆盘四周加入4个接地通孔,并且在馈电端口加入集总电感.最终,天线在中心工作频率5.8 GHz处实现了反射系数-15 dB的匹配性能.     

基于图像处理的自动野外救援系统设计

针对野外救援的不及时性,结合人工智能等技术的应用,提出了一种新的自动野外救援系统.人类在野外和海上活动中受困后,除了依靠自身能力和装备进行求生之外,外部的有效及时救援是提高生存几率的关键.自动野外救援系统,由自动报警装置、手动报警装置实现报警,触发整个系统的运行.自动救援装置可以通过定位模块实现定位,通过执行器移动到随身装置附近实现救援,随身装置还可以发出信标导引信号;自动救援装置还可以通过传感器检测信标,通过相位检测技术等计算待救者的坐标并规划路径,实现更精准的定位与救援.