作者机构:
[张光富; 谭伟石; 张赛文; 文兵] School of Information and Electronic Engineering, Hunan City University, Yiyang;413000, China;All-Solid-State Energy Storage Materials and Devices Key Laboratory of Hunan Province, Yiyang;[张光富; 谭伟石; 张赛文] 413000, China<&wdkj&>All-Solid-State Energy Storage Materials and Devices Key Laboratory of Hunan Province, Yiyang;[张光富; 谭伟石; 张赛文; 文兵] 413000, China
作者机构:
[文兵; 邓杨保; 张赛文; 陈德鹏; 邓曙光; 张光富] All-solid-state Energy Storage Materials and Devices Key Laboratory of Hunan Province, College of Information and Electronic Engineering, Hunan City University, Yiyang;413000, China;[韦家谋] Key Laboratory for Micro-/Nano-Optoelectronic Devices of Ministry of Education, School of Physics and Electronics, Hunan University, Changsha;410082, China;[文兵] 413000, China<&wdkj&>Key Laboratory for Micro-/Nano-Optoelectronic Devices of Ministry of Education, School of Physics and Electronics, Hunan University, Changsha
通讯机构:
[Deng, Y.] A;All-solid-state Energy Storage Materials and Devices Key Laboratory of Hunan Province, China
作者机构:
[张林成] Hunan City University, College of Information and Electronic Engineering, Hunan, Yiyang, 413000, China;[原源; 周聪; 李广场] Engineering Research Center of Nuclear Technology Application (East China Institute of Technology), Ministry of Education, Jiangxi, Nanchang, 330013, China;[汤井田; 蒋奇云] Key Laboratory ofMetallogenic Prediction of Nonferrous Metals, Ministry of Education, Central South University, Hunan, Changsha, 410083, China;[黄凤林; 李广场] Zhejiang Huadong Engineering Safety Technology Co., LTD, Zhejiang, Hangzhou, 311122, China
期刊:
Journal of Applied Physics,2022年132(18):183907 ISSN:0021-8979
通讯作者:
Haiou Wang
作者机构:
[Wang, Haiou; 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 L, 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;Key Laboratory of Novel Materials for Sensor of Zhejiang Province, Institute of Material Physics, Hangzhou Dianzi University , Hangzhou 310018, China
摘要:
The magnetic properties, critical behavior, and magnetocaloric effect of perovskite NdMnO3 are studied. The Nd ordering is induced by the Mn ferromagnetic component with antiferromagnetic coupling with each other and then magnetization reversal occurs due to Mn moments reorientation induced by the ordering Nd moments, which explains the phenomenon of negative magnetization at low temperatures. The critical behavior of NdMnO3 is studied using Kouvel-Fisher and self-consistent methods. The results show that the Kouvel-Fisher method is reliable and critical exponents are coming out as beta = 0.462 for T-C = 11.15 K, gamma = 1.041 for T-C = 11.42 K, delta = 3.252 by critical isotherm analysis. Magnetic exchange distance may decay as J ( r ) & AP; r - 4.563, that is, somewhere between the three-dimensional Heisenberg model and the mean field model. Remarkably, three temperature transitions and the corresponding three extremum values including positive and negative entropy change are observed in NdMnO3, which is different from previous reports on NdMnO3. A positive entropy change as 3.82 J/kg K at 10-15 K for mu(0)& UDelta;H = 50 kOe and a negative entropy change as -0.557 J/kg K at around 8 K for mu(0)& UDelta;H = 5 kOe are found, which can be put down to a fast magnetization change of NdMnO3 because of the Nd moments ordering and Mn moments reorientation. Besides, an entropy change of 1.22 J/kg K is found for mu(0)& UDelta;H = 50 kOe at 80-85 K, which is corresponding to the Mn ferromagnetic ordering temperature. The relative cooling power of NdMnO3 reaches 105.9 J/kg, making it a promising candidate in the field of magnetic refrigeration. Published under an exclusive license by AIP Publishing.
作者机构:
[Su, Kunpeng; Zhang, Hui; Wang, Haiou; Yang, Dexin; Huang, Shuai; Huo, Dexuan; Wang, Yan] Hangzhou Dianzi Univ, Inst Mat Phys, Key Lab Novel Mat Sensor Zhejiang Prov, Hangzhou 310018, Peoples R China.;[Ni, Shenya] Zhejiang Univ, Interdisciplinary Lab Mech, Hangzhou 310013, 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, Minist Educ, Dept Appl Phys, Key Lab Soft Chem & Funct Mat, Nanjing 210094, Peoples R China.
通讯机构:
[Haiou Wang; Dexuan Huo] K;Key Laboratory of Novel Materials for Sensor of Zhejiang Province, Institute of Material Physics, Hangzhou Dianzi University, Hangzhou, China<&wdkj&>Key Laboratory of Novel Materials for Sensor of Zhejiang Province, Institute of Material Physics, Hangzhou Dianzi University, Hangzhou, China
期刊:
International Journal of Intelligent Systems,2022年37(12):11299-11318 ISSN:0884-8173
通讯作者:
Rong Tan<&wdkj&>Rong Tan Rong Tan Rong Tan
作者机构:
[Tan, Rong; Si, Wen] Shanghai Business Sch, Dept IoT Engn, Shanghai, Peoples R China.;[Yang, Gelan] Hunan City Univ, Dept Informat Sci & Engn, Yiyang, Peoples R China.
通讯机构:
[Rong Tan; Rong Tan Rong Tan Rong Tan] D;Department of IoT Engineering, Shanghai Business School, Shanghai, China
关键词:
center of pressure;fall detection;IoT system;security strategy;smart home
摘要:
In the field of motion monitoring in smart home, the 5G technology can be applied to Internet of Things systems for facilitating our daily life. In this paper, a comprehensive study on the fall detection system based on 5G network is presented. Starting with analyzing the moving stability, a wearable foot pressure measurement system is devised. Furthermore, the center of pressure during moving is computed by using the pressure data. Besides, the signal transmitting security issue is also considered. The physical layer security authentication and the cross-layer encryption are employed and integrated within the security strategy. As a case study, we evaluate the proposed method on fall detection tasks in smart home and the experimental results establish strong evidence of a satisfying performance.
通讯机构:
[Hongli Liu] C;College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
关键词:
deep learning;facial landmark detector;fatigue driving recognition;multi-scale
摘要:
Abstract: 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. Keywords: deep learning; facial landmark detector; fatigue driving recognition; multi-scale
作者机构:
[Ou, Yun] Hunan Univ Sci & Technol, Hunan Prov Key Lab Hlth Maintenance Mech Equipmen, Xiangtan 411201, Peoples R China.;[Wu, Yingying; Ou, Yun] Hunan Univ Sci & Technol, Sch Mat Sci & Engn, Xiangtan 411201, Peoples R China.;[Peng, Jinlin] Hunan City Univ, Coll Informat & Elect Engn, All Solid State Energy Storage Mat & Devices Key, Yiyang 413002, Peoples R China.
通讯机构:
[Jinlin Peng] A;[Yun Ou] H;Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan 411201, China<&wdkj&>School of Materials Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, 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, China
关键词:
misfit strain;PIN-PMN-PT;electrocaloric effect;ferroelectric thin films
摘要:
Abstract: xPb(In1/2Nb1/2)O3-(1−x−y)Pb(Mg1/3Nb2/3)O3−yPbTiO3 (PIN–PMN–PT) bulks possess excellent electromechanical coupling and dielectric properties, but the corresponding epitaxial PIN–PMN–PT thin films have not yet been explored. This paper adopts a nonlinear thermodynamics analysis to investigate the influences of misfit strains on the phase structures, electromechanical properties, and electrocaloric responses in epitaxial PIN–PMN–PT thin films. The misfit strain–temperature phase diagram was constructed. The results reveal that the PIN–PMN–PT thin films may exist in tetragonal c-, orthorhombic aa-, monoclinic M-, and paraelectric PE phases. It is also found that the c-M and aa-PE phase boundaries exhibit a superior dielectric constant ε 11 which reached 1.979 × 106 with um = −0.494%, as well as the c-M phase boundary showing a large piezoelectric response d15 which reached 1.64 × 105 pm/V. In comparison, the c-PE and M-aa phase boundaries exhibit a superior dielectric constant ε33 over 1 × 105 around um = 0.316% and the piezoelectric response d33 reached 7235 pm/V. The large electrocaloric responses appear near the paraelectric- ferroelectric phase boundary. These insights offer a guidance for experiments in epitaxial PIN–PMN–PT thin films. Keywords: misfit strain; PIN–PMN–PT; electrocaloric effect; ferroelectric thin films