一种基于抽取LMS的距离旁瓣抑制方法

在噪声雷达中，传统相关处理方法的距离旁瓣受到时宽带宽积的限制，在有限相关处理时间内得到的距离旁瓣较高，会造成微弱目标被强目标、杂波旁瓣淹没的现象。提出一种基于抽取最小均方（Least Mean Square,LMS）滤波的噪声雷达旁瓣抑制方法，将LMS滤波器的系数作为距离压缩结果，从而获取较低的距离旁瓣。对该方法的性能进行了理论分析，并通过数字仿真验证了算法的有效性和理论分析的正确性。     

地表移动带范围内建构筑物安全可靠性分析

地表建构筑物位于在生产矿山地表开采移动范围内，如果按照一般圈定地表移动范围原则判断建构筑物的安全可靠性，结果是不安全或者预留保安矿柱可保证安全。为分析地表移动带范围内建构筑物安全可靠性，采用FLAC3D软件建立数值模拟模型，对矿区地表移动进行分析研究，并结合建构筑物的破坏等级评判标准，可以更加合理地判断地表移动范围内建构筑物的安全可靠性，对存在相似条件的矿山具有一定的借鉴意义。     

宁夏红寺堡盆地隐伏古隆起成因机制及其对区域沙漠化的影响

目前对于青藏高原东北缘活动构造研究多集中于活动断裂带的活动性,而对夹持于其间的沉积盆地构造格架及活动性研究甚少。以夹持于烟筒山断裂与牛首山—罗山断裂之间的宁夏红寺堡盆地为研究对象,采用重力资料重处理解译、音频大地电磁测深(AMT)和地震勘探相结合,揭示红寺堡盆地隐伏构造特征,并进一步采用盆山一体化思路分析隐伏构造的成因机制及其对区域沙漠化的控制作用。结果表明:青藏高原在中新世末发生强烈的NE向推挤、扩展和隆升,红寺堡盆地由坳陷盆地转变为挠曲盆地; 在青藏高原NE向扩展的影响下,烟筒山断裂发生强烈的逆冲作用,古生代—中生代基底逆冲于古近系—新近系之上,受构造变形影响的最新地层为中新统彰恩堡组; 红寺堡盆地内的隐伏古隆起呈NW—SE向,与烟筒山构造带具有相同的构造动力学背景,受青藏高原NE向扩展影响形成于中新世末,并且至今仍具有活动性; 隐伏古隆起周缘断裂的活动破坏了地表稳定性、蓄水能力和地表植被,导致区域沙漠化呈现有规律的NW—SE向带状展布。该研究成果对于宁夏红寺堡盆地区域稳定性评价及沙漠化的综合治理具有现实指导意义。     

A low power and low phase-noise 91~96 GHz VCO in 90 nm CMOS

This paper reports a 94 GHz CMOS voltage-controlled oscillator (VCO) using both the negative capacitance (NC) technique and series-peaking output power and phase noise (PN) enhancement technique. NC is achieved by adding two variable LC networks to the source nodes of the active circuit of the VCO. NMOSFET varicaps are adopted as the required capacitors of the LC networks. In comparison with the conventional one, the proposed active circuit substantially decreases the input capacitance (C_in) to zero or even a negative value. This leads to operation (or oscillation) frequency (OF) increase and tuning range (TR) enhancement of the VCO. The VCO dissipates 8.3 mW at 1 V supply. The measured TR of the VCO is 91~96 GHz, close to the simulated (92.1~96.7 GHz) and the calculated one (92.2~98.2 GHz). In addition, at 1 MHz offset from 95.16 GHz, the VCO attains an excellent PN of – 98.3 dBc/Hz. This leads to a figure-of-merit (FOM) of ?188.5 dBc/Hz, a remarkable result for a V- or W-band CMOS VCO. The chip size of the VCO is 0.75 × 0.42 mm², i.e. 0.315 mm².     

Highly Bendable and Rotational Textile Structure with Prestrained Conductive Sewing Pattern for Human Joint Monitoring

Human joints have respective ranges of motion and joint forces corresponding to each kind of joint; this necessitates considerations of the characteristics of human joints to fabricate wearable strain sensors conformable to the human body, and capable of precisely monitoring complex motions of the human body. In the present study, the “all textile‐based highly stretchable structure” that is capable of precisely sensing motions (folding and rotation) of the human joints (finger, wrist, elbow, spine, and knee) is fabricated by optimizing patterns (straight, blind, and zigzag) of conductive yarns employed as the conductive part of the strain sensor, and several textile substrates (braided elastic fabric, knit fabric, and woven fabric), having preferable elasticity and conformability employed for the fabrication of strain sensors suitable for human joints. In particular, the technology, enabling the prestraining of textile substrate, is exploited to fabricate a strain sensor that is capable of outputting selective signals corresponding to the folding motion of the spinal joint over a predetermined angle of motion, and the gait pattern of the wearer of the sensor, attached to his or her knee joint doing folding and rotational motions, is analyzed.     

NiMo/Cu-nanosheets/Ni-foam composite as a high performance electrocatalyst for hydrogen evolution over a wide pH range

We designed and fabricated non-precious and highly efficient electrocatalysts of nickelmolybdenum/copper-nanosheets/nickel-foam composites (NiMo/Cu-NS/NF) by step electrodepositions, combining with chemical oxidation method. The catalysts were charaterized by means of SEM, XRD and XPS spectra. Their electrocatalytic activities were assessed by hydrogen evolution reactions (HER) over a wide pH range, where acidic, neutral and alkaline electrolytes were used, respectively. Benefiting from the unique midlayer Cu nanosheets (NS) architecture and optimum Mo–Ni composition at the surface layer which led to high electronic conductivity and large electrochemically active surface area (ECSA), the NiMo/Cu-NS/NF-2 catalyst displayed superior electrocatalytic activities with low overpotentials of η₁₀ = 43, 86 and 89 mV in 0.5 M H₂SO₄, 1.0 M PBS and 1.0 M KOH electrolyte, respectively. Especially in the acidic condition, it exhibited the best electrocatalytic activity with smaller Tafel slope of 54 mV dec^?1 and higher exchange current density of 1.93 mA cm^?2.     

Facial expression recognition of intercepted video sequences based on feature point movement trend and feature block texture variation

Facial Expression Recognition (FER) is an important subject of human–computer interaction and has long been a research area of great interest. Accurate Facial Expression Sequence Interception (FESI) and discriminative expression feature extraction are two enormous challenges for the video-based FER. This paper proposes a framework of FER for the intercepted video sequences by using feature point movement trend and feature block texture variation. Firstly, the feature points are marked by Active Appearance Model (AAM) and the most representative 24 of them are selected. Secondly, facial expression sequence is intercepted from the face video by determining two key frames whose emotional intensities are minimum and maximum, respectively. Thirdly, the trend curve which represents the Euclidean distance variations between any two selected feature points is fitted, and the slopes of specific points on the trend curve are calculated. Finally, combining Slope Set which is composed by the calculated slopes with the proposed Feature Block Texture Difference (FBTD) which refers to the texture variation of facial patch, the final expressional feature are formed and inputted to One-dimensional Convolution Neural Network (1DCNN) for FER. Five experiments are conducted in this research, and three average FER rates 95.2%, 96.5%, and 97% for Beihang University (BHU) facial expression database, MMI facial expression database, and the combination of two databases, respectively, have shown the significant advantages of the proposed method over the existing ones.