YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.     

Structure-sensitive semantic matching for aggregate question answering over knowledge base

Aggregate question answering essentially returns answers for given questions by obtaining query graphs with unique dependencies between values and corresponding objects. Word order dependency, as the key to uniquely identify dependency of the query graph, reflects the dependencies between the words in the question. However, due to the semantic gap caused by the expression difference between questions encoded with word vectors and query graphs represented with logical formal elements, it is not trivial to match the correct query graph for the question. Most existing approaches design more expressive query graphs for complex questions and rank them just by directly calculating their similarities, ignoring the semantic gap between them. In this paper, we propose a novel Structure-sensitive Semantic Matching(SSM) approach that learns aligned representations of dependencies in questions and query graphs to eliminate their gap. First, we propose a cross-structure matching module to bridge the gap between two modalities(i.e., textual question and query graph). Then, we propose an entropy-based gated AQG filter to remove the structural noise caused by the uncertainty of dependencies. Finally, we present a two-channel query graph representation that fuses the semantics of abstract structure and grounding content of the query graph explicitly. Experimental results show that SSM could learn aligned representations of questions and query graphs to eliminate the gaps between their dependencies, and improves up to 12% (F1 score) on aggregation questions of two benchmark datasets.     

Categorical observers for metamerism

A method is proposed to generate categorical colour observer functions (individual colour matching functions) for any field size based on the CIE 2006 system of physiological observer functions. The method combines proposed categorical observer techniques of Sarkar et al with a physiologically-based individual observer model of Asano et al and a clustering technique to produce the optimal set of categorical observers. The number of required categorical observers varies depending on an application with as many as 50 required to predict individual observers' matches when a laser projector is viewed. However, 10 categorical observers are sufficient to represent colour-normal populations for personalized colour imaging. The proposed and recommended categorical observers represent a robust and inclusive technique to examine and quantify observer metamerism in any application of colorimetry.     

喷油方式对斜齿轮齿面温度的影响

为探讨喷油方式对齿面温度的影响，以斜齿轮为研究对象，通过CFD仿真和试验研究不同喷油方式对斜齿轮齿面温度的影响。针对斜齿轮喷油润滑过程的特点，分析其齿面摩擦生热量，简化轮齿喷油润滑计算模型，并基于CFX进行齿面对流换热仿真研究，得到了不同喷油方式下的齿面温度；基于功率开放式斜齿轮试验平台，对不同喷油方式下的齿面温度进行了试验测量，与仿真计算结果进行对比分析。结果表明：在高速重载斜齿轮传动系统中，啮出侧喷油润滑的方式比啮入侧喷油润滑方式的冷却降温效果要好。     

Fundamental Evaluation of Power Supply and Rectifiers for Wireless Power Transfer Using Magnetic Resonant Coupling

This paper provides a fundamental analysis of a power supply and rectifiers for wireless power transfer using magnetic resonant coupling (MRC). MRC enables efficient wireless power transfer over middle‐range transfer distances. MRC for wireless power transfer should operate at a high frequency in the industry science medical band, such as 13.56 MHz, because the size of the transfer device decreases at higher transfer frequencies. Therefore, the output frequency of the power supply on the transmitting side should be 13.56 MHz. In addition, the rectifier on the receiving side is operated at a high frequency. This paper focuses on the reflected power in the power supply and rectifiers. Thus, the parametric design method is clarified for the power supply, including a low‐pass filter to match the output, the impedance of the power supply with the characteristic impedance of the transmission line. In addition, the effects on the rectifiers of silicon carbide and gallium nitride diodes are confirmed by performing an experiment and a loss analysis.     

Stereo matching cost computation based on nonsubsampled contourlet transform

A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost.     

Preparation of CaO granules using the granulation method

ABSTRACT

Improving the hydration resistance of CaO particle in manufacturing and application of free CaO-containing materials has practical significance. In this study, CaO granules was made from Ca(OH)₂ particles, which were fabricated by the granulation method. The results showed that the hydration resistance of the CaO granules which was prepared under 1700?r?min^?1 was the best, the CaO granules was sintered well in calcination process, the shell of CaO granules was relatively dense, which improves the hydration resistance of CaO granules, and the rate of hydration weight increment was 0.58% after placed in the air for 20 days under a temperature of 10–14°C and a relative humidity of 57–81%.     

基于振动实测的非均质地层钻头失效分析与对策

四川盆地作为国内页岩气开发的重点区域,通过近几年的不断攻关和实践,机械钻速得到了提高,但由于受地层复杂、可钻性差、非均质性强等地质因素的影响,导致井下钻柱系统不良振动剧烈,容易出现钻头损坏严重、钻速较低等问题,严重影响了钻井时效。为了解决上述难题,以该盆地涪陵工区上二叠统龙潭组—中二叠统茅口组为例,采用井下振动高频测量工具的实测手段,测量了钻头—钻柱系统的动态振动加速度参数,结合地层的岩性和矿物组分分析,研究钻头失效原因与对策,并开展了现场试验。研究结果表明:①在非均质地层中钻进的钻头—钻柱系统产生了大于40 m/s~2的高幅值瞬时冲击振动,高幅值的瞬时冲击是导致钻头先期失效的主要原因;②提出了抑制高幅值的瞬时冲击振动采用"减振+增压"工具组合和避免井下工具共振的钻井参数;③采用钻井新参数的试验井比邻井的高幅值瞬时振动降低了17%,单只钻头进尺增加24%,钻头工作环境得到了较大的改善,钻头使用数量减少。结论认为,该研究成果能够有效地改善钻头—钻柱系统的振动状态,有利于达成延长钻头使用寿命的目标。