This paper investigates the target tracking mission of an Unmanned Aerial Vehicle (UAV) equipped with a camera and a laser module. Firstly, utilizing Deep Neural Network (DNN) and Kernelized Correlation Filters (KCF),...
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This paper investigates the target tracking mission of an Unmanned Aerial Vehicle (UAV) equipped with a camera and a laser module. Firstly, utilizing Deep Neural Network (DNN) and Kernelized Correlation Filters (KCF), target recognition and location in the pixel coordinate system is achieved based on vision. Furthermore, by combining the laser ranging information and the distance estimation algorithm based on image, the distance between the UAV and the target is well estimated. To ensure the target tracking, a PID controller based on the distance error is applied to the UAV. The effectiveness of the system is verified on an actual UAV target tracking scenario.
This paper studies the resilient consensus problem with time-varying adversary attacks and asynchronous events. In the synchronous or asynchronous update case, all the nodes or only a fraction of nodes update their st...
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ISBN:
(数字)9781728113982
ISBN:
(纸本)9781728113999
This paper studies the resilient consensus problem with time-varying adversary attacks and asynchronous events. In the synchronous or asynchronous update case, all the nodes or only a fraction of nodes update their states at each time step, respectively. For the synchronous update case, the nodes under attack are time-varying but do not change after some finite time;for the asynchronous update case, the nodes under attack are time-invariant. For both cases, a resilient consensus can be reached exponentially fast under a network topology condition inspired by the notion of the scrambling matrix and an explicit expression for the convergence rate is provided. Numerical examples are given to validate the theoretical results and to compare the performance with an existing algorithm.
Background: High-altitude pulmonary hypertension(HAPH) is a life-threating condition for animals in high altitude,and disturbance of endothelial nitric oxide(NO) synthesis contributes to its pathogenesis. N-carbamylgl...
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Background: High-altitude pulmonary hypertension(HAPH) is a life-threating condition for animals in high altitude,and disturbance of endothelial nitric oxide(NO) synthesis contributes to its pathogenesis. N-carbamylglutamate(NCG), which enhances arginine synthesis, promotes endogenous synthesis of NO. In this study, we determined the effects of NCG on alleviating HAPH in Holstein heifers that ascended to Tibet(Lhasa, 3,658 m).Methods: Exp. 1, 2,000 Holstein heifers were transported from low elevation(1,027 m) to Lhasa. After being exposed to hypoxia for 1 yr, Holstein heifers were assigned to a healthy group(control, n = 6) with mean pulmonary hypertension(mPAP) < 41 mmHg, and an HAPH affected group(HAPH, n = 6) with mPAP > 49 *** tissues were collected to evaluate histopathological changes and the expression of endothelial nitric oxide synthase(eNOS). Exp. 2, ten healthy heifers and 10 HAPH affected heifers were supplemented with NCG(20 g/d per heifer) for 4 wk. Physiological parameters were determined and blood samples were collected on d-1 and d 28 of the feeding ***: Expression of e NOS in small pulmonary arteriole intima was higher in the healthy than HAPH group(P = 0.006), whereas HAPH group had significantly thicker media and adventitia than healthy group(all P < 0.05). The mRNA of eNOS and protein level of eNOS were higher in the lungs of heifers in the healthy group than in the HAPH group(both P < 0.001), whereas endothelin-1 protein levels were higher in HAPH group than in the healthy group(P = 0.025). NCG supplementation decreased mPAP and ammonia(both P = 0.001), whereas it increased the expression of eNOS, arginine, and plasma NO(all P < 0.05).Conclusions: The expression of eNOS was decreased in Holstein heifers with HAPH. NCG supplementation decreased m PAP through the restoration of eNOS and endogenous NO synthesis.
Utilizing hot carriers for efficient plasmon-mediated chemical reactions (PMCRs) to convert solar energy into secondary energy is one of the most feasible solutions to the global environmental and energy crisis. Findi...
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Utilizing hot carriers for efficient plasmon-mediated chemical reactions (PMCRs) to convert solar energy into secondary energy is one of the most feasible solutions to the global environmental and energy crisis. Finding a plasmonic heterogeneous nanostructure with a more efficient and reasonable hot carrier transport path without affecting the intrinsic plasmonic properties is still a major challenge that urgently needs to be solved in this field. Herein, the mechanism by which plasmon-promoted interatomic hot electron redistribution on the surface of Au 3 Cu alloy nanoparticles promotes the electrocatalytic nitrogen reduction reaction (ENRR) is successfully clarified. The localized surface plasmon resonance (LSPR) effect can boost the transfer of plasmon hot electrons from Au atoms to Cu atoms, trigger the interatomic electron regulation of Au 3 Cu alloy nanoparticles, enhance the desorption of ammonia molecules, and increase the ammonia yield by approximately 93.9 %. This work provides an important reference for rationally designing and utilizing the LSPR effect to efficiently regulate the distribution and mechanism of plasmon hot carriers on the surface of heterogeneous alloy nanostructures.
The authors regret'In the acknowledgments of this manuscript,the Nos.51678035 and 51478041 of the National Naturalscience Foundation of China are *** correct *** 51678053 and 51478041'.The authors would like t...
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The authors regret'In the acknowledgments of this manuscript,the Nos.51678035 and 51478041 of the National Naturalscience Foundation of China are *** correct *** 51678053 and 51478041'.The authors would like to apologize for any inconvenience caused.
Gait analysis based on wearable inertial sensors is conceptually well known, which has potential use in various applications related to gait patterns. However, as such systems are inherently nonlinear, their performan...
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Gait analysis based on wearable inertial sensors is conceptually well known, which has potential use in various applications related to gait patterns. However, as such systems are inherently nonlinear, their performance characteristics with respective to system settings are loosely researched and poorly documented. Literature in this area mainly focuses on improving system accuracy by fusing complex algorithms and additional sensors, against their gold standard counterparts, such as optical motion capture systems and force plates. This paper addresses the issue of how the system accuracy changes as the parameter settings change, and what system accuracy can be obtained by parameter tuning. A conventional feedforward neural network (FNN) is adopted to detect the temporal gait features that are prerequisite for gait analysis, and a six-phase gait model is adopted to give a close examination of human gait. In general, three main parameters are related to the FNN-based detection algorithm, i.e., the number of network layers, the number of neurons in each hidden layer, and the size of sliding window. The roles of these parameters are analyzed, and their effects on system accuracy is evaluated with multi-subject data, to offer some suggestions for parameter tuning and facilitate the system implementation.
In this paper, a new lossless free space method for measuring the complex relative permittivity of dielectric material by reflection method is presented. When this method is used to measure the complex relative permit...
In this paper, a new lossless free space method for measuring the complex relative permittivity of dielectric material by reflection method is presented. When this method is used to measure the complex relative permittivity of dielectric material, there is no multi-value problem. The measurement system used in this method consists of a horn lens antenna and a vector network analyzer(VNA). In this paper, HFSS microwave simulation software is used to simulate the complex relative permittivity measurement method proposed in this paper. The simulation results show that this method can accurately measure the complex relative permittivity of dielectric material.
Capacitive deionization (CDI) is one of the high-efficient technologies for desalination of brackish water. In this paper, a composite electrode with 3D Cu Ni foam (CNF) as current collector and reduced graphene oxide...
Capacitive deionization (CDI) is one of the high-efficient technologies for desalination of brackish water. In this paper, a composite electrode with 3D Cu Ni foam (CNF) as current collector and reduced graphene oxide (rGO) as active material was synthesized, in which graphene oxide was reduced in situ and immobilized on the 3D CNF. Obtained rGO/CNF electrodes were directly employed as anode and cathode in a CDI cell. The effects of different substitution reaction time on the electrodes were investigated by SEM, XRD, Raman and XPS. Results showed that the existence of Cu on CNF could adjust the morphology and the defect content of rGO. The specific capacity of rGO/CNF-1.5 electrode (Note: 1.5 stands for the substitution reaction time) reached 352.5 F·g −1 at 5 mV·s −1 in 1.0 M NaCl electrolyte. During desalination, the rGO/CNF-1.5 electrode has a high salt adsorption capacity (SAC) of 84.6 mg/g in 250 mg/L NaCl solution at 1.2 V, which is 2.23 times higher than that of rGO/NF. The high performance of desalination can be attributed to the formation of electric double layer capacitance and pseudocapacitance . After 20 cycles, the SAC of rGO/CNF-1.5 electrode remains at 77.1 mg/g which is over 91 % of the original SAC.
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