通讯机构：
[Hongli Liu] C;College of Electrical and Information Engineering, Hunan University, Changsha 410082, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
deep learning;facial landmark detector;fatigue driving recognition;multi-scale
摘要：
<jats:p>Fatigue driving behavior recognition in all-weather real driving environments is a challenging task. Accurate recognition of fatigue driving behavior is helpful to improve traffic safety. The facial landmark detector is crucial to fatigue driving recognition. However, existing facial landmark detectors are mainly aimed at stable front face color images instead of side face gray images, which is difficult to adapt to the fatigue driving behavior recognition in real dynamic scenes. To maximize the driver’s facial feature information and temporal characteristics, a fatigue driving behavior recognition method based on a multi-scale facial landmark detector (MSFLD) is proposed. First, a spatial pyramid pooling and multi-scale feature output (SPP-MSFO) detection model is built to obtain a face region image. The MSFLD is a lightweight facial landmark detector, which is composed of convolution layers, inverted bottleneck blocks, and multi-scale full connection layers to achieve accurate detection of 23 key points on the face. Second, the aspect ratios of the left eye, right eye and mouth are calculated in accordance with the coordinates of the key points to form a fatigue parameter matrix. Finally, the combination of adaptive threshold and statistical threshold is used to avoid misjudgment of fatigue driving recognition. The adaptive threshold is dynamic, which solves the problem of the difference in the aspect ratio of the eyes and mouths of different drivers. The statistical threshold is a supplement to solve the problem of driver’s low eye threshold and high mouth threshold. The proposed methods are evaluated on the Hunan University Fatigue Detection (HNUFDD) dataset. The proposed MSFLD achieves a normalized mean error value of 5.4518%, and the accuracy of the fatigue driving recognition method based on MSFLD achieves 99.1329%, which outperforms that of state-of-the-art methods.</jats:p>
期刊：
Journal of Luminescence,2021年240:118419 ISSN：0022-2313
通讯作者：
Weiping Zhou<&wdkj&>Chunlin Ma
作者机构：
[Zhou, Weiping] Nanchang Univ, Sch Mat Sci & Engn, Nanchang 330031, Jiangxi, Peoples R China.;[Zhai, Zhangyin; Ma, Chenyu; Ma, Chunlin] Huaiyin Normal Univ, Sch Phys & Elect Elect Engn, Huaian 223001, Peoples R China.;[Tan, Weishi] Hunan City Univ, Coll Informat & Elect Engn, All Solid State Energy Storage Mat & Devices Key, Yiyang 413002, Peoples R China.
通讯机构：
[Weiping Zhou; Chunlin Ma] S;School of Materials Science and Engineering, Nanchang University, Nanchang, 330031, People's Republic of China<&wdkj&>School of Physics and Electronic Electrical Engineering, Huaiyin Normal University, Huaian, 223001, People's Republic of China
关键词：
Emission spectroscopy;Ferroelectricity;High temperature applications;Phase structure;Piezoelectric ceramics;Solid state reactions;Temperature sensors;Titanium oxides;0.92(na0.5bi0.5)TiO3–0.08 (ba0.90ca0.10)(ti0.92sn0.08)O3: sm3+;Lead-free ferroelectric ceramics;Lead-free piezoelectric ceramic;Non-contact;Optical temperature sensing;Optical thermometry;Photoluminescence properties;Photoluminescence temperature;Solid state reaction method;Temperature dependent;Photoluminescence
作者机构：
[张赛文; 邓亚琦; 王冲; 冷潇泠; 张光富; 文兵; 邓杨保; 谭伟石; 田野; 李稳国] School of Information and Electronics Engineering, Hunan City University, Yiyang;413000, China;All-solid-state Energy Storage Materials and Devices Key Laboratory of Hunan Province, Hunan City University, Yiyang;[张赛文; 邓亚琦; 王冲; 冷潇泠; 张光富; 文兵; 邓杨保; 谭伟石; 田野; 李稳国] 413000, China<&wdkj&>All-solid-state Energy Storage Materials and Devices Key Laboratory of Hunan Province, Hunan City University, Yiyang;[张赛文; 邓亚琦; 王冲; 冷潇泠; 张光富; 文兵; 邓杨保; 谭伟石; 田野; 李稳国] 413000, China
通讯机构：
[Deng, Y.] S;[Deng, Y.] A;All-solid-state Energy Storage Materials and Devices Key Laboratory of Hunan Province, China;School of Information and Electronics Engineering, China
关键词：
单分子定位显微;多测量矢量;压缩感知;超分辨成像;稀疏贝叶斯学习
摘要：
在超分辨荧光显微成像技术中，单分子定位显微方法是被广泛应用的技术之一。根据荧光显微成像原理构造多测量矢量压缩感知模型（Multiple Measurement Vector-Compressed Sensing, MMV-CS），并采用多重稀疏贝叶斯学习算法进行求解，来实现超分辨荧光图像重建。分析了有效像元大小、荧光分子生成的光子数和背景信号泊松化噪声对重建结果的影响，以及在图像进行分块处理时算法运行时间的分析。模拟和实验计算分析表明，当点扩展函数的标准差在160 nm时，有效像元大小在120、160、200 nm能取得较好的重构效果，而在60 nm时效果较差。探测器收集的光子数越多，重构效果越好，随着背景信号光子数增加时，离得越近的样品结构越不能分辨。在同样的分块处理情况下，MMV-CS比同伦算法(L1-Homotopy, L1-H）和凸优化算法(CVX)分别快一个数量级和三个数量级，因此，在研究三维超分辨荧光显微成像时，MMV-CS算法在运行时间上具有更大的优势。 In the super-resolution microscopy imaging technology, single molecule localization microscopy is one of the widely used techniques. In this paper, in order to achieve super-resolution fluorescence image reconstruction, a multiple measurement vector Compressed sensing (MMV-CS) model was established based on the principle of fluorescence microscopic imaging, and the multiple sparse Bayesian learning algorithm was applied in problem solving. The effects of the effective pixel size, the number of photons generated by fluorescent molecules and the Poisson noise of fluorescence and background signal on the reconstruction results were analyzed. The running time of the algorithm was analyzed with the image subdivided into smaller patches. The results of simulation and experimental calculation show that when the standard deviation of the point spread function is 160 nm, the effective pixel size at 120 nm, 160 nm and 200 nm can achieve good reconstruction effect, while the pixel size at 60 nm results in poor effect. Better reconstruction image quality is achieved with more photons collected by the detector. As the background signal photons increase, the sample structure becomes indistinguishable when the distance is too close. Under the same subdivided condition, MMV-CS is one order of magnitude faster than the Homotopy (L1-H) algorithm and three orders of magnitude faster than the convex optimization algorithm (CVX), which has greater advantages in terms of running time for the application of MMV-CS in 3D super-resolution fluorescence microscopy.
通讯机构：
[Chengfeng Long; Xiaoyong Tang] S;School of Information and Intelligence Science and Technology, Hunan Agricultural University, Changsha, China<&wdkj&>School of Computer and Communications Engineering, Changsha University of Science and Technology, Changsha, China
摘要：
Considering the issue with respect to the high data redundancy and high cost of information collection in wireless sensor nodes, this paper proposes a data fusion method based on belief structure to reduce attribution in multi-granulation rough set. By introducing belief structure, attribute reduction is carried out for multi-granulation rough sets. From the view of granular computing, this paper studies the evidential characteristics of incomplete multi-granulation ordered information systems. On this basis, the positive region reduction, belief reduction and plausibility reduction are put forward in incomplete multi-granulation ordered information system and analyze the consistency in the same level and transitivity in different levels. The positive region reduction and belief reduction are equivalent, and the positive region reduction and belief reduction are unnecessary and sufficient conditional plausibility reduction in the same level, if the cover structure order of different levels are the same the corresponding equivalent positive region reduction. The algorithm proposed in this paper not only performs three reductions, but also reduces the time complexity largely. The above study fuses the node data which reduces the amount of data that needs to be transmitted and effectively improves the information processing efficiency.
期刊：
Materials Research Express,2021年8(6):066102 ISSN：2053-1591
作者机构：
[Wang, Xingyu; Wang, Xiaoxiong; Zhou, Weiping; Tan, Weishi] Nanjing Univ Sci & Technol, Sch Sci, Nanjing 210094, Peoples R China.;[Ma, Chunlin] Huaiyin Normal Univ, Sch Phys & Elect Elect Engn, Huaian 223001, Peoples R China.;[Tan, Weishi] Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413002, Peoples R China.;Nanchang Univ, Sch Mat Sci & Engn, Nanchang 330031, Jiangxi, Peoples R China.
关键词：
Binary alloys;Defects;Ferromagnetism;Magnesia;Magnesium metallography;Magnetic properties;Oxide minerals;Saturation magnetization;Semiconductor quantum wells;Vanadium alloys;Vanadium metallography;X ray diffraction analysis;X ray photoelectron spectroscopy;Composite defects;First principle calculations;High resolution X ray diffraction;Implanted samples;Intrinsic defects;MgO single crystals;Room temperature ferromagnetism;Synergistic effect;Nitrogen compounds
摘要：
<jats:title>Abstract</jats:title>
<jats:p>N-implanted MgO single crystals were prepared and their magnetic properties were studied. High Resolution x-ray diffraction, photoluminescence, and x-ray photoelectron spectroscopy measurements confirmed that both intrinsic defects (Mg vacancies, oxygen vacancies) and extrinsic defects (N-related defects) were presented in the implanted samples. Ferromagnetism was detected in the samples. The saturation magnetization (<jats:italic>Ms</jats:italic>) of the samples increases with the concentrations of Mg vacancies and N-related defects. We conclude that the enhanced <jats:italic>M</jats:italic>s should be ascribed to the synergistic effects of intrinsic and extrinsic defects. The magnetic properties of various composite defects were also studied by first principle calculations. The results suggest that the ferromagnetism is mainly originated from the configurations of V<jats:sub>Mg</jats:sub> (Mg vacancy)+N<jats:sub>O</jats:sub> (N substituting for O).</jats:p>
期刊：
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING,2021年2021(1):1-19 ISSN：1687-1472
通讯作者：
Deng, Shuguang(cbwchj@126.com)
作者机构：
[Qin, Hua; Tan, Yue; Cao, Buwen; Deng, Shuguang] Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Peoples R China.;[Qin, Hua; Tan, Yue; Cao, Buwen; Deng, Shuguang] Hunan City Univ, Key Lab City Comp & IoT, Yiyang 413000, Peoples R China.;[Qin, Hua; Tan, Yue; Cao, Buwen; Deng, Shuguang] Engn Res Ctr DongTing Lake Reg Ecol Environm Inte, Yiyang 413000, Peoples R China.
通讯机构：
[Shuguang Deng] C;College of Information and Electronic Engineering, Hunan City University, Yiyang, China<&wdkj&>Key Laboratory of City Computing and IoT, Hunan City University, Yiyang, China<&wdkj&>Engineering Research Center of DongTing Lake Regional Ecological Environment Intelligent Monitoring and Disaster Prevention and Mitigation, Yiyang, China
关键词：
Software defined sensor network;Cluster;Node mobility;Centralization
作者机构：
[Wang, Haiou; Zhang, Hui; Huo, Dexuan; Wang, Yan] Hangzhou Dianzi Univ, Inst Mat Phys, Key Lab Novel Mat Sensor Zhejiang Prov, Hangzhou 310018, Peoples R China.;[Tan, Weishi] Hunan City Univ, Coll Informat & Elect Engn, All Solid State Energy Storage Mat & Devices Key, Yiyang 413002, Peoples R China.;[Tan, Weishi] Nanjing Univ Sci & Technol, Dept Appl Phys, Key Lab Soft Chem & Funct Mat, Minist Educ, Nanjing 210094, Peoples R China.
通讯机构：
[Haiou Wang] K;[Weishi Tan] A;Key Laboratory of Novel Materials for Sensor of Zhejiang Province, Institute of Material Physics, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China<&wdkj&>All-solid-state Energy Storage Materials and Devices Key Laboratory of Hunan Province, College of Information and Electronic Engineering, Hunan City University, Yiyang 413002, People's Republic of China<&wdkj&>Key Laboratory of Soft Chemistry and Functional Materials, Ministry of Education, Department of Applied Physics, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China
期刊：
Journal of Circuits, Systems and Computers,2021年30(16):2150301 ISSN：0218-1266
通讯作者：
Wangdong Yang
作者机构：
[Yang, Wangdong] College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, P. R. China;[Cao, Buwen; Zhou, Honglie; He, Chenjun] College of Information and Electronic Engineering, Hunan City University, Yiyang 413000, P. R. China;[Xiao, Sainan] College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, P. R. China<&wdkj&>College of Information and Electronic Engineering, Hunan City University, Yiyang 413000, P. R. China
通讯机构：
[Wangdong Yang] C;College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, P. R. China
关键词：
Color;Colorimetry;License plates (automobile);Quality control;Background objects;Effectiveness and efficiencies;License plate localizations;Localization performance;Projection analysis;Real world situations;Realtime processing;Variable illumination;Image enhancement
