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The detection of space target plays a vital role space science and development. In optical region, coherent LADAR has been widely used to detect space debris and other small space target due to its advantages in high sensitivity, ...
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The detection of space target plays a vital role space science and development. In optical region, coherent LADAR has been widely used to detect space debris and other small space target due to its advantages in high sensitivity, frequency selectivity, strong directionality, and the ability to get multi-dimensional information. However, as the local oscillator (LO) power of coherent LADAR is increased, the quantum noise power of the LO field becomes the dominant noise source of the detection system, and eventually limit the detection range, achieve standard quantum limit (SQL). In this paper, a novel quantum enhanced coherent LADAR has been designed for space target detection, which combines coherent LADAR technology and quantum technology. By applying quantum squeezed state to LADAR receiver, the SQL can be surpassed, and the resolution and sensitivity of LADAR can be improved significantly. This new scheme open up a possibility to use quantum squeezed light in space observation, such as long-range LADAR and small space target detection.
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According to the problem of the autonomous rendezvous and docking (AR&D) mission with a failed micro satellite in a constellation, the technology which can avoid collisions with the constellation and target is studied. Firstly, the safe approach corridor suitable for failed satellite is designed using ellipse cissoids method. Secondly, considering the rotation character of safe corridor the dynamic programming of approach path is achieved according to the satellite safety envelope in the constellation. Meanwhile, autonomous path tracking and docking with revolving object is realized using attitude and orbit coupled control method. Finally the relative dynamics of revolving object, safe approach corridor, and safety envelopes of normal satellites are combined effectively, and the simulation results demonstrate the validity of AR&D with revolving object in various restrictions....
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According to the problem of the autonomous rendezvous and docking (AR&D) mission with a failed micro satellite in a constellation, the technology which can avoid collisions with the constellation and target is studied. Firstly, the safe approach corridor suitable for failed satellite is designed using ellipse cissoids method. Secondly, considering the rotation character of safe corridor the dynamic programming of approach path is achieved according to the satellite safety envelope in the constellation. Meanwhile, autonomous path tracking and docking with revolving object is realized using attitude and orbit coupled control method. Finally the relative dynamics of revolving object, safe approach corridor, and safety envelopes of normal satellites are combined effectively, and the simulation results demonstrate the validity of AR&D with revolving object in various restrictions.
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摘要 :
According to the problem of the autonomous rendezvous and docking (AR&D) mission with a failed micro satellite in a constellation, the technology which can avoid collisions with the constellation and target is studied. Firstly, the safe approach corridor suitable for failed satellite is designed using ellipse cissoids method. Secondly, considering the rotation character of safe corridor the dynamic programming of approach path is achieved according to the satellite safety envelope in the constellation. Meanwhile, autonomous path tracking and docking with revolving object is realized using attitude and orbit coupled control method. Finally the relative dynamics of revolving object, safe approach corridor, and safety envelopes of normal satellites are combined effectively, and the simulation results demonstrate the validity of AR&D with revolving object in various restrictions....
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According to the problem of the autonomous rendezvous and docking (AR&D) mission with a failed micro satellite in a constellation, the technology which can avoid collisions with the constellation and target is studied. Firstly, the safe approach corridor suitable for failed satellite is designed using ellipse cissoids method. Secondly, considering the rotation character of safe corridor the dynamic programming of approach path is achieved according to the satellite safety envelope in the constellation. Meanwhile, autonomous path tracking and docking with revolving object is realized using attitude and orbit coupled control method. Finally the relative dynamics of revolving object, safe approach corridor, and safety envelopes of normal satellites are combined effectively, and the simulation results demonstrate the validity of AR&D with revolving object in various restrictions.
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Researches on China's state-owned enterprises are mainly focused on the reform issues with qualitative approach. This study examines the methods of assignment to the managerial post and motivation-hygiene determinants for executiv...
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Researches on China's state-owned enterprises are mainly focused on the reform issues with qualitative approach. This study examines the methods of assignment to the managerial post and motivation-hygiene determinants for executives between private sector and state-owned enterprises in China through empirical study. From the survey of 305 executives in China, we find that all executives prefer to be assigned by board of directors, executives in private businesses are better motivated than those state-owned enterprises, and further works have to be done to increase motivation of executives in state-owned enterprises.
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This paper overviews and discusses the advance and success gained in die plasma based ion implantation, metal plasma based ion implantation, plasma based high temperature ion implantation, multi-element plasma based complex ion im...
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This paper overviews and discusses the advance and success gained in die plasma based ion implantation, metal plasma based ion implantation, plasma based high temperature ion implantation, multi-element plasma based complex ion implantation andplasma based ion implantation mixing related to our research works recently.
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To solve the problem of finding overlapping communities in heterogeneous networks, this paper proposes a model for finding overlapping communities in heterogeneous networks based on density peak clustering. The model improves the ...
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To solve the problem of finding overlapping communities in heterogeneous networks, this paper proposes a model for finding overlapping communities in heterogeneous networks based on density peak clustering. The model improves the heterogeneous graph attention network, which fully mines for the important information of nodes and meta-paths in information representation from the node level and the semantic level attention mechanisms and performs hierarchical aggregation to obtain heterogeneous graph embedding vectors. It combines the heterogeneous graph attention network with density peak clustering and calculates node density and relative distance through the heterogeneous graph embedding vector to divide community center nodes. Then it also uses the weight information of the node-level attention mechanism to generate a community membership matrix. The experimental results on real datasets show that the model can utilize the diversity of heterogeneous network node information to discover overlapping communities with good stability and accuracy.
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A need for proficient international tourism personnel has been growing for the burgeoning tourism economy all around the world, where as there is a lack of corresponding employees in the global tourism market. Accordingly, this st...
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A need for proficient international tourism personnel has been growing for the burgeoning tourism economy all around the world, where as there is a lack of corresponding employees in the global tourism market. Accordingly, this study intends to investigate internationalization of tourism personnel training mode by carrying out a case study of Macao University of Science and Technology. Guarantee system as well as curriculum, extracurricular projects and university management are discussed. In addition, interviews were conducted to evaluate the implementation of this mode from students' perspectives. The results indicate that students' points of view towards this training mode vary to a significant extent regarding levels of satisfaction. Consequently, for the fulfillment of cultivating highly competent and competitive tourism professionals, countermeasures can be taken by university and faculty, alleviating present defects of this mode pointed out by students, guaranteeing the expected outcomes.
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As a critical component in rotating machinery field, rolling bearings are prone to damage under the working conditions of high speed, heavy load and strong impact, resulting in the reduction of production efficiency or even produc...
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As a critical component in rotating machinery field, rolling bearings are prone to damage under the working conditions of high speed, heavy load and strong impact, resulting in the reduction of production efficiency or even production outage. Therefore, fault diagnosis of rolling bearing plays a significant role in improving the availability of the rotating machinery equipment. The fault recognition rate of the existing fault diagnosis techniques of wavelet packet energy feature is low. Thus, a fault diagnosis approach of bearing is proposed to address this issue in this paper. First, in view of the non-stationary and non-linear properties of the rolling bearing vibration signals, namely, time domain features, frequency domain features, time-frequency domain features and entropy feature are selected to form high-dimensional feature vectors. Second, principal component analysis (PCA) technique with dimension reduction ability is adopted to process high-dimensional features to further remove noise and redundant features and prevent over-fitting. Third, BP neural network is utilized to perform fault diagnosis. Finally, the rolling bearing vibration data of Case Western Reserve University (CWRU) is applied to verify the proposed approach. The diagnosis results shows that the proposed approach has higher fault recognition rate than the traditional wavelet packet energy features based fault diagnosis approach.
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摘要 :
As a critical component in rotating machinery field, rolling bearings are prone to damage under the working conditions of high speed, heavy load and strong impact, resulting in the reduction of production efficiency or even produc...
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As a critical component in rotating machinery field, rolling bearings are prone to damage under the working conditions of high speed, heavy load and strong impact, resulting in the reduction of production efficiency or even production outage. Therefore, fault diagnosis of rolling bearing plays a significant role in improving the availability of the rotating machinery equipment. The fault recognition rate of the existing fault diagnosis techniques of wavelet packet energy feature is low. Thus, a fault diagnosis approach of bearing is proposed to address this issue in this paper. First, in view of the non-stationary and non-linear properties of the rolling bearing vibration signals, namely, time domain features, frequency domain features, time-frequency domain features and entropy feature are selected to form high-dimensional feature vectors. Second, principal component analysis (PCA) technique with dimension reduction ability is adopted to process high-dimensional features to further remove noise and redundant features and prevent over-fitting. Third, BP neural network is utilized to perform fault diagnosis. Finally, the rolling bearing vibration data of Case Western Reserve University (CWRU) is applied to verify the proposed approach. The diagnosis results shows that the proposed approach has higher fault recognition rate than the traditional wavelet packet energy features based fault diagnosis approach.
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摘要 :
As a critical component in rotating machinery field, rolling bearings are prone to damage under the working conditions of high speed, heavy load and strong impact, resulting in the reduction of production efficiency or even produc...
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As a critical component in rotating machinery field, rolling bearings are prone to damage under the working conditions of high speed, heavy load and strong impact, resulting in the reduction of production efficiency or even production outage. Therefore, fault diagnosis of rolling bearing plays a significant role in improving the availability of the rotating machinery equipment. The fault recognition rate of the existing fault diagnosis techniques of wavelet packet energy feature is low. Thus, a fault diagnosis approach of bearing is proposed to address this issue in this paper. First, in view of the non-stationary and non-linear properties of the rolling bearing vibration signals, namely, time domain features, frequency domain features, time-frequency domain features and entropy feature are selected to form high-dimensional feature vectors. Second, principal component analysis (PCA) technique with dimension reduction ability is adopted to process high-dimensional features to further remove noise and redundant features and prevent over-fitting. Third, BP neural network is utilized to perform fault diagnosis. Finally, the rolling bearing vibration data of Case Western Reserve University (CWRU) is applied to verify the proposed approach. The diagnosis results shows that the proposed approach has higher fault recognition rate than the traditional wavelet packet energy features based fault diagnosis approach.
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