We investigate the statistical nature of holographic gas, which may represent the quasi-particle excitations of a strongly correlated gravitational system. We find that the holographic entropy can be obtained by modif...We investigate the statistical nature of holographic gas, which may represent the quasi-particle excitations of a strongly correlated gravitational system. We find that the holographic entropy can be obtained by modifying degeneracy. We calculate thermodynamical quantities and investigate stability of the holographic gas. When applying to cosmology, we find that the holographic gas behaves as holographic dark energy, and the parameter c in holographic dark energy can be calculated from our model. Our model of holographic gas generally predicts c 〈 1, implying that the fate of our universe is phantom-like.展开更多
This paper aims to examine and analyse the level of intra-industry trade on economy of ASEAN. These data obtained from the accurate and reliable source of ASEAN Trade Statistics databases. The importance of intra-indu...This paper aims to examine and analyse the level of intra-industry trade on economy of ASEAN. These data obtained from the accurate and reliable source of ASEAN Trade Statistics databases. The importance of intra-industry and measurement is also described. Moreover, the linkage of intra-industry trade and investment liberalization under the ASEAN Economic Community （AEC） is also explained. The effective enhancement schemed to increase the competitiveness of specific industries had been proposed to enhance ASEAN to be efficient production hub and network of region that lead to the ultimate goal of single market. The further studies can be applied to construct and estimate the econometric model and forecasting technique to confirm the empirical results.展开更多
This article used the Cluster analysis of statistical method to separate China＇s 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985...This article used the Cluster analysis of statistical method to separate China＇s 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985 to 2007. The categories were high, moderate and low energy consumption areas and they had significant differences in energy consumption. Based on this classification, the authors analyzed the influencing factors of energy consumption in the three areas by means of panel data econometric model. The results showed that the influencing factors were obviously different. In order to support national goal of energy conservation and emission reduction, the energy measures and policies should be distinctly taken.展开更多
Traditional methods for plan path prediction have low accuracy and stability. In this paper, we propose a novel approach for plan path prediction based on relative motion between positions(RMBP) by mining historical f...Traditional methods for plan path prediction have low accuracy and stability. In this paper, we propose a novel approach for plan path prediction based on relative motion between positions(RMBP) by mining historical flight trajectories. A probability statistical model is introduced to model the stochastic factors during the whole flight process. The model object is the sequence of velocity vectors in the three-dimensional Earth space. First, we model the moving trend of aircraft including the speed(constant, acceleration, or deceleration), yaw(left, right, or straight), and pitch(climb, descent, or cruise) using a hidden Markov model(HMM) under the restrictions of aircraft performance parameters. Then, several Gaussian mixture models(GMMs) are used to describe the conditional distribution of each moving trend. Once the models are built, machine learning algorithms are applied to obtain the optimal parameters of the model from the historical training data. After completing the learning process, the velocity vector sequence of the flight is predicted by the proposed model under the Bayesian framework, so that we can use kinematic equations, depending on the moving patterns, to calculate the flight position at every radar acquisition cycle. To obtain higher prediction accuracy, a uniform interpolation method is used to correct the predicted position each second. Finally, a plan trajectory is concatenated by the predicted discrete points. Results of simulations with collected data demonstrate that this approach not only fulfils the goals of traditional methods, such as the prediction of fly-over time and altitude of waypoints along the planned route, but also can be used to plan a complete path for an aircraft with high accuracy. Experiments are conducted to demonstrate the superiority of this approach to some existing methods.展开更多
基金supported by National Natural Science Foundation of China under Grant No. 10525050a "973" Project under Grant No. 2007CB815401
文摘We investigate the statistical nature of holographic gas, which may represent the quasi-particle excitations of a strongly correlated gravitational system. We find that the holographic entropy can be obtained by modifying degeneracy. We calculate thermodynamical quantities and investigate stability of the holographic gas. When applying to cosmology, we find that the holographic gas behaves as holographic dark energy, and the parameter c in holographic dark energy can be calculated from our model. Our model of holographic gas generally predicts c 〈 1, implying that the fate of our universe is phantom-like.
文摘This paper aims to examine and analyse the level of intra-industry trade on economy of ASEAN. These data obtained from the accurate and reliable source of ASEAN Trade Statistics databases. The importance of intra-industry and measurement is also described. Moreover, the linkage of intra-industry trade and investment liberalization under the ASEAN Economic Community （AEC） is also explained. The effective enhancement schemed to increase the competitiveness of specific industries had been proposed to enhance ASEAN to be efficient production hub and network of region that lead to the ultimate goal of single market. The further studies can be applied to construct and estimate the econometric model and forecasting technique to confirm the empirical results.
文摘This article used the Cluster analysis of statistical method to separate China＇s 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985 to 2007. The categories were high, moderate and low energy consumption areas and they had significant differences in energy consumption. Based on this classification, the authors analyzed the influencing factors of energy consumption in the three areas by means of panel data econometric model. The results showed that the influencing factors were obviously different. In order to support national goal of energy conservation and emission reduction, the energy measures and policies should be distinctly taken.
基金Project supported by the National Natural Science Foundation of China(No.71573184)the National Key Scientific Instrument and Equipment Development Project(No.2013YQ490879)the Special Program of Office of China Air Traffic Control Commission(No.GKG201403004)
文摘Traditional methods for plan path prediction have low accuracy and stability. In this paper, we propose a novel approach for plan path prediction based on relative motion between positions(RMBP) by mining historical flight trajectories. A probability statistical model is introduced to model the stochastic factors during the whole flight process. The model object is the sequence of velocity vectors in the three-dimensional Earth space. First, we model the moving trend of aircraft including the speed(constant, acceleration, or deceleration), yaw(left, right, or straight), and pitch(climb, descent, or cruise) using a hidden Markov model(HMM) under the restrictions of aircraft performance parameters. Then, several Gaussian mixture models(GMMs) are used to describe the conditional distribution of each moving trend. Once the models are built, machine learning algorithms are applied to obtain the optimal parameters of the model from the historical training data. After completing the learning process, the velocity vector sequence of the flight is predicted by the proposed model under the Bayesian framework, so that we can use kinematic equations, depending on the moving patterns, to calculate the flight position at every radar acquisition cycle. To obtain higher prediction accuracy, a uniform interpolation method is used to correct the predicted position each second. Finally, a plan trajectory is concatenated by the predicted discrete points. Results of simulations with collected data demonstrate that this approach not only fulfils the goals of traditional methods, such as the prediction of fly-over time and altitude of waypoints along the planned route, but also can be used to plan a complete path for an aircraft with high accuracy. Experiments are conducted to demonstrate the superiority of this approach to some existing methods.
