In this article, we define two single-variable functions SVF1 and SVF2, then discuss partial differentiation of real binary functions by dint of one variable function SVF1 and SVF2. The main properties of partial differentiation are shown .
Several Integrability Formulas of Some Functions, Orthogonal Polynomials and Norm Functions
In this article, we give several integrability formulas of some functions including the trigonometric function and the index function . We also give the definitions of the orthogonal polynomial and norm function, and some of their important properties .
Path planning plays an extremely important role in the design of LAVs (Loitering Air Vehicles) to accomplish the air combat task fleetly and reliably. The planned path should ensure that LAVs reach the destination along the optimal path with minimum probability of being found and minimal consumed fuel. Traditional methods tend to find local best solutions due to the large search space. So it takes a lot of time and consumes a lot of computing resources. In this paper, a new young intelligent algorithm-fireworks algorithm is introduced, and EFWA (enhanced fireworks algorithm)-its enhanced version is used to find the optimal solution. At the same time, the battlefield prior knowledge is fully utilized to predict the existence space of the potential optimal trajectory. Greatly the search space reduced, plan planning efficiency is significantly improved. Path planning method effectiveness in this paper has further been improved compared with FACPSO. Moreover, the EFWA on prior knowledge performs well on the application of dynamic path planning when the threats cruise randomly than FAC-PSO.
In this paper we focus on integrated Reconnaissance/Strike LAV, in order to reveal the evolution regularity when group LAVs combats cooperatively. The evolution of cooperative behavior of group LAVs, which is described with finite state machine, can be regarded as a conversion process of a LAV in different task states, using the rate equation for probability analysis. Then based on the missions of integration of reconnaissance, attack, and damage effectiveness evaluation, we build the model of finite state machine based on behavior state transition. Solved with Runge-Kutta method. We can analyze how the key technology quota of LAV impact on the operational effectiveness of Group LAVs.the fractional order control approach.
Hao Pan, Han-Bing Wang, Yi-Bin Yu, Bing-Chao Cheng, Xiao-Yu Wang and Ying Li
Advantages of the supercritical fluid (SCF) process compared to the conventional solution stirring method (CSSM) in the preparation of daidzein-hydroxypropyl-β-cyclodextrin (HPβCD) complexes were investigated. Formation of daidzein/ HPβCD inclusion complexes was confirmed by Fourier transformed-infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), X-ray diffraction (XRD) and scanning electron microscopy (SEM). Particle size, inclusion yield, drug solubility and dissolution of daidzein/HPβCD complexes were evaluated. Compared to CSSM, the SCF process resulted in higher inclusion yield and higher solubility. Also, extended dissolution of daidzein from the SCF processed HPβCD inclusion complexes was observed, with only 22.94 % released in 45 min, compared to its rapid release from those prepared by CSSM, with 98.25 % drug release in 15 min. This extended release of daidzein from SCF prepared inclusion complexes was necessary to avoid drug precipitation and improve drug solubilisation in the gastrointestinal tract. The results showed that the SCF process is a superior preparation method for daidzein-hydroxypropyl-β-cyclodextrin complexes.
Li Bing-jie, Zhao Jia-hong, Wang Xu, Mohamode Amuer and Wang Zhi-liang
As the air flow control system has the characteristics of delay and uncertainty, this research designed and achieved a practical air flow control system by using the hydrodynamic theory and the modern control theory. Firstly, the mathematical model of the air flow distribution of the system is analyzed from the hydrodynamics perspective. Then the model of the system is transformed into a lumped parameter state space expression by using the Galerkin method. Finally, the air flow is distributed more evenly through the estimation of the system state and optimal control. The simulation results show that this algorithm has good robustness and anti-interference ability
Purpose of the article Knowledge has been considered as the strategic assets and become the source of competitive advantage in organizations. Knowledge management thus receives the extraordinary attention from the top management. Many organizational factors have influences on knowledge management practices. This paper attempts to explore the empirical relationship between knowledge management and organizational culture in the specific situation of China’s commercial banking industry. Methodology/methods The relationship between knowledge management and organizational culture is quantitatively investigated by surveying bank managers. The scale of SECI modes is used to measure knowledge management process and the scale of Denison Organizational Culture Survey (DOCS) is used to measure organizational culture. We explore the underlying relationship by employing the statistical analyses such as correlation, regression and structural equation modeling. Scientific aim The research aims at testing the relationship between knowledge management and organizational culture, and furthermore if there exist linkages between cultural traits and SECI modes. Findings The results of the empirical study confirm the great and positive effect that organizational culture has on knowledge management. Different cultural traits contribute to different SECI modes. Conclusions For obtaining successful knowledge management practices in organizations, it is better to concern about the relationship between knowledge management and organizational culture. The limitation in the paper is the sampling size, which will be solved by an industry-wide survey in our future research.
Accurate tide height is crucial for the safe navigation of large deep-draft ships when they enter and leave the port. We have proposed an accurate forecasting method for the tide heights from the observation data and neural networks, which can easily calculate the tidal window period of large deep-draft ships’ navigation through long channels at high tide. Moreover, an artificial neural network is established for the tide height from the observation of tide heights before their current time node. For an ideal forecast, the neural network was optimized for one year with the tide height data of Huanghua Port. In case of large ships, their tidal characteristics of channels for are complex. A new method is proposed for the observation of multiple stations and artificial neural networks of each observation station. When ships are navigating through the port, the tide height is predicted from the observed data and forecast tide heights of multiple observation stations. Thus, a valid tidal window period is secured when the ships enter the port. Comparative analysis of the ship’s tidal window period with that of the measured one can lead us to conclude that the forecasted data has a strong correlation with the measurement. So, our proposed algorithm can accurately predict the tide height and calculate the node timing when the ship enters and depart the port. Finally, these results can be applied for the safe navigation of large deep-draft ships when the port is at high tide.