A media file placing method and device, storage medium and virtual reality apparatus. The method comprises: acquiring first location information of a viewing focus area of a target object in a virtual three-dimensional space for respective first predetermined time periods (S202); acquiring, in a second predetermined time period and according to the first location information, viewing distribution information of the target object in the virtual three-dimensional space (S204), wherein the second predetermined time period comprises the first predetermined time period; generating a target placement location in the virtual three-dimensional space according to the viewing distribution information (S206); and placing a media file at the target placement location in the virtual three-dimensional space (S208). The present solution addresses the technical problem in the art of low placement efficiency of a media file.

In this paper, a new kind of Multi-model Predictive Controller (MMPC) is presented. Multiple models switch MMPC with Kalman filter based on neural network optimization was implemented in a DC/DC converter. Multiple models direct switch was used according to the two modes of the Boost-Buck circuit and different loads condition. Kalman filter was successfully added to the MMPC to transfer the optimal state value to MMPC from the output of the DC/DC circuit. Parameters optimization method is also discussed in the paper when the controller was applied to real model simulation. Simulation result demonstrates that the good performance of MMPC compared with single model predictive control and PID control. With the help of high speed FPGA, it is possible to apply this method to hardware simulation.

In this paper, we present an advanced way to control the DC/DC converter by using predictive control. As the current state of the circuit must be known while using the predictive control, state observer is applied to solve the problem that some variables of DC/DC converter can not be observed. Neural network optimization is used to solve the QP problems in single sample step of predictive control. Simulation results show that this approach can utilize fast converge property of neural network and the new control strategy turns out to be very efficiency.

A control method and apparatus based on virtual reality. The method gives a prompt regarding a movable region to a first object by means of generating the movable region according to the movement request and the positions of other objects in a scene where the first object is located, so that the first object moves according to the prompt, thereby achieving the objective of the first object moving in the movable region of the scene. Since the movable region does not comprise security regions of the other objects in the scene, when moving in the movable region, the first object does not move to the security regions of the other objects in the scene, thereby achieving the technical effect that in a virtual reality system, the first object moves according to the positions of the other objects in the scene, and thus solving the technical problem that in the virtual reality system, due to the movement of the first object to the security regions of the other objects, the first object is too close to the other objects in the scene, such that the first object causes interference on the other objects.

Enantioselective divergent total syntheses of (+)-fawcettimine, (+)-fawcettidine, (+)-lycoflexine, (+)-lycoposerramine Q, (-)-Huperzine Q and (+)-N-oxyhuperzine Q have been described from a common precursor. The syntheses feature a vinylogous Rubottom oxidation and several biomimetic transformations. (C) 2014 Elsevier Ltd. All rights reserved.

In the context of promoting new urbanization in China, urban expansion has been the subject of a consolidated line of research in the past two decades. In this study, we integrate remote sensing, a geographical information system, and spatial analysis techniques to monitor and model urban expansion with a spatially explicit and multi-scale perspective in Wuhan, the megacity in central China. We first extract urban built-up land from medium to high resolution images from 1995 to 2010 and analyze the expansion dynamics at the parcel level. For the exploration of the driving mechanisms underlying urban expansion, 20 explanatory variables are then categorized into three groups: characteristics, density, and proximity. A kernel window is then utilized to filter the extracted urban built-up land map at multiple scales. Moran's I is later used to test the spatial autocorrelation in the percentage of urban built-up land area and the residuals. Finally, a spatial lag model and a spatial error model are applied, to explore the causal factors of urban built-up land. It is revealed that the area of transportation land in Wuhan has increased tremendously, and urban built-up land is less scattered at the micro-scales. Regardless of the scale or model, housing density and gross domestic product (GDP) are positively correlated with the urban built-up land area, whereas the influence of other factors is shown to vary along with the scale or model. The results also confirm the superiority of the spatial regression models, and better fitting is produced with the increase in the scale. In the future, it is anticipated that the interpretation of remote sensing images and spatial analysis techniques will be optimized for better manifestation of intra-urban spatial interaction. In this process, the scale effect is an issue that should not be neglected in future studies of urban expansion. (C) 2014 Elsevier Ltd. All rights reserved.

Highlights • We use spatial metrics including spatial autocorrelation index, Shannon entropy and gravity center migration to characterize the sprawling pattern. • We accommodate and explore the spatio-temporal interactions among different districts or counties when modeling urban sprawl. • We show the impact of population growth, socio-economic and transportation development on the expansion of built-up land. • We highlight the integration of remote sensing, geographical information system, and spatial statistics in characterizing and modeling urban sprawl. Abstract Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly.

A channel multiplexing method for reading array detector signals comprises: dividing array detectors into a number M of groups, at least two detectors being in each group; array coding the read channel to read a number M of row signals and a number N of column signals, which means when a signal is outputted at the detector in row a, column b, the signals of row a and column b are outputted correspondingly; connecting the readout signals of the row and the column to different positions of two transmission lines respectively; determining the source row number and column number of the signal on the basis of the time difference between the time of signal reaching two ends of the transmission line, and marking the source detector from which the signal is generated on the basis of two time differences of the row signal and the column signal. The method avoids the use of multiple electronic channels and thereby reduces the cost of electronic system and technical difficulty of implementation; meanwhile in the channel multiplexing process the use of the weighted resistor network is avoided, so that the replication of the multiplexed signal does not change greatly at different signal connecting points and the requirement of the dynamic range of the back-end readout circuit is lowered.