中国各地区实现现代化时间测算

论文概述了现代化五大研究流派核心思想 ,对现代化内涵进行集合式表述。设定与求解了中国现代化的目标函数 ,并测算了中国各地区传统现代化的实现程度 ,研究表明传统的英克尔斯现代化指标体系存在重大缺陷。设计现代化评价的指标体系 ,对中国各地区现代化相对进程进行了排序与分析 ,最后 ,测算出中国各地区率先实现现代化的具体时间。

帧间角点匹配的积分时间实时测算方法

在阐述积分时间测算原理基础上,对测算算法的误差源及残差进行了分析,并定量分析了残差对成像质量的影响,利用50组样本数据通过MATLAB仿真验证了采用Harris角点特征检测算法来实现帧间图像像移ΔL的亚像元精确计算的有效性,采用角点阈值优化及先验知识剔除误匹配点相结合的策略,有效降低特征角点检测及匹配计算时效,减少了运算数据量,对已匹配角点亚像元定位计算,仿真结果表明ΔL计算精度优于0.2个像元可满足测算方法在轨使用需求。最后结合实时测算方法应用特点给出了TDI探测器型高分辨率空间遥感相机成像参数的建议,为测算方法的在轨应用提供设计参考。采用高频面阵CMOS测速相机进行积分时间实时测算的方法能有效解决目标高程数据未知情况下,摄影点斜距无法精确获得的问题,方法具备低成本及星上可行性,同时能够弥补像移失配所导致的像质下降现象,有利于TDI探测器型高分辨率空间遥感相机成像性能的提升。

An Improved Fuzzy Predictive Control Algorithm and Its Application to an Industrial CSTR Process

A finite horizon predictive control algorithm, which applies a saturated feedback control law as its local control law, is presented for nonlinear systems with time-delay subject to input constraints. In the algorithm, N free control moves, a saturated local control law and the terminal weighting matrices are solved by a minimization problem based on linear matrix inequality （LMI） constraints online. Compared with the algorithm with a nonsaturated local law, the presented algorithm improves the performances of the closed-loop systems such as feasibility and optimality. This model predictive control （MPC） algorithm is applied to an industrial continuous stirred tank reactor （CSTR） with explicit input constraint. The simulation results demonstrate that the presented algorithm is effective.

FPGA-based High-precision Measurement Algorithm for the Ultrasonic Echo Time of Flight

Based on the evaluation of advantages and disadvantages of high-precision digital time interval measuring algorithms, and combined with the principle of the typical time-difference ultrasonic flow measurement, the requirements for the measurement of echo time of flight put forward by the ultrasonic flow measurement are analyzed. A new high-precision time interval measurement algorithm is presented, which combines the pulse counting method with the phase delay interpolation. The pulse counting method is used to ensure a large dynamic measuring range, and a double-edge triggering counter is designed to improve the accuracy and reduce the counting quantization error. The phase delay interpolation is used to reduce the quantization error of pulse counting for further improving the time measurement resolution. Test data show that the systexn for the measurement of the ultrasonic echo time of flight based on this algorithm and implemented on an Field Programmable Gate Army（FleA） needs a relatively short time for measurement, and has a measurement error of less than 105 ps.

Comparisons between unsteady sediment-transport modeling

The comparative study between unsteady flow models in alluvial streams shows a chaotic residue as for the choices of a forecasting model. The difficulty resides in the choice of the expressions of friction resistance and sediment transport. Three types of mathematical models were selected. Models of type one and two are fairly general, but require a considerable number of boundary conditions, which related to each size range of sediments. It can be a handicap during rivers studies which are not very well followed in terms of experimental measurements. Also, the use of complex models is not always founded. But then, the model of type three requires a limited number of boundary conditions and solves only a system of three equations at each time step. It allows a considerable saving in calculating times.

Non-classical Algorithm for Time Series Prediction of the Range of Economic Phenomena With Regard to the Interaction of Financial Market Indicators

The aim of the article is to present non-clasical copyrighted algorithm for prediction of time series, presenting macroeconomic indicators and stock market indices. The algorithm is based on artificial neural networks and multi-resolution analysis （the algorithm is based on Daubechies wavelet）. However, the main feature of the algorithm, which gives a good quality of the forecasts, is all included in the series analysis division into, a few partial under-series and prediction dependence on a number of other economic series. The algorithm used for the prediction, is copyrighted algorithm, labeled M.H-D in this article. Application of the algorithm was performed on a series presenting WIG 20. The forecast of WIG 20 was conditional on trading the Dow Jones, DAX, Nikkei, Hang Seng, taking into account the sliding time window. As an example application of copyrighted model, the forecast of WIG 20 for a period of two years, one year, six month was appointed. An empirical example is described. It shows that the proposed model can predict index with the scale of two years, one year, a half year and other intervals. Precision of prediction is satisfactory. An average absolute percentage error of each forecast was： 0.0099%---for two-year forecasts WIG 20; 0.0552%--for the annual forecast WIG 20; and 0.1788%---for the six-month forecasts WIG 20.

Numerical and Dimensional Analysis for Prediction of Line Heating Residual Deformations

Line heating process is a very complex phenomenon as a variety of factors affects the amount of residual deformations. Numerical thermal and mechanical analysis of line heating for prediction of residual deformation is time consuming. In the present work dimensional analysis has been presented to obtain a new relationship between input parameters and resulting residual deformations during line heating process. The temperature distribution and residual deformations for 6 mm, 8 mm, 10 mm and 12 mm thick steel plates were numerically estimated and compared with experimental and published results. Extensive data generated through a validated FE model were used to find co-relationship between the input parameters and the resulting residual deformation by multiple regression analysis. The results obtained from the deformation equations developed in this work compared well with those of the FE analysis with a drop in the computation time in the order of 100 (computational time required for FE analysis is around 7 200 second to 9 000 seconds and where the time required for getting the residual deformation by developed equations is only 60 to 90 seconds).

Efficient fast mode decision using mode complexity for multi-view video coding

The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduced in coding system, which hinders practical application of MVC. An efficient fast mode decision method using mode complexity is proposed to reduce the computational complexity. In the proposed method, mode complexity is firstly computed by using the spatial, temporal and inter-view correlation between the current macroblock(MB) and its neighboring MBs. Based on the observation that direct mode is highly possible to be the optimal mode, mode complexity is always checked in advance whether it is below a predefined threshold for providing an efficient early termination opportunity. If this early termination condition is not met, three mode types for the MBs are classified according to the value of mode complexity, i.e., simple mode, medium mode and complex mode, to speed up the encoding process by reducing the number of the variable block modes required to be checked. Furthermore, for simple and medium mode region, the rate distortion(RD) cost of mode 16×16 in the temporal prediction direction is compared with that of the disparity prediction direction, to determine in advance whether the optimal prediction direction is in the temporal prediction direction or not, for skipping unnecessary disparity estimation. Experimental results show that the proposed method is able to significantly reduce the computational load by 78.79% and the total bit rate by 0.07% on average, while only incurring a negligible loss of PSNR(about 0.04 d B on average), compared with the full mode decision(FMD) in the reference software of MVC.

Detection of Selfish Behavior in Wireless Ad Hoc Networks Based on CUSUM Algorithm

The cumulative sum （CUSUM） algorithm is proposed to detect the selfish behavior of a node in a wireless ad hoc network. By tracing the statistics characteristic of the backoff time between successful transmissions, a wireless node can distinguish if there is a selfish behavior in the wireless network. The detection efficiency is validated using a Qualnet simulator. An IEEE 802.11 wireless ad hoc network with 20 senders and 20 receivers spreading out randomly in a given area is evaluated. The well-behaved senders use minimum contention window size of 32 and maximum con- tention window size of I 024, and the selfish nodes are assumed not to use the binary exponential strategy for which the contention window sizes are both fixed as 16. The transmission radius of all nodes is 250 m. Two scenarios are investigated： a single-hop network with nodes spreading out in 100 m^100 m, and all the nodes are in the range of each other; and a multi-hop network with nodes spreading out in 1 000 m~ 1 000 m. The node can monitor the backoff time from all the other nodes and run the detection algorithms over those samples. It is noted that the threshold can significantly affect the detection time and the detection accuracy. For a given threshold of 0.3 s, the false alarm rates and the missed alarm rates are less than 5%. The detection delay is less than 1.0 s. The simulation results show that the algorithm has short detection time and high detection accuracy.

A Precise Localization Method for a High Speed Mobile Robot Using iGS and Dual Compass

This paper proposes a precise localization algorithm for a quickly moving mobile robot.In order to localize a mobile robot with active beacon sensors,a relatively long time is needed,since the distance to the beacon is measured by transmitting time of the ultrasonic signal.The measurement time does not cause a high error rate when the mobile robot moves slowly.However,with an increase of the mobile robot’s speed,the localization error becomes too high to use for accurate mobile robot navigation.Therefore,in this research into high speed mobile robot operations,instead of using two active beacons for localization,an active beacon and dual compass are utilized to localize the mobile robot.This new approach resolves the high localization error caused by the speed of the mobile robot.The performance of the precise localization algorithm is verified by comparing it to the conventional method through real-world experiments.

Modelling and Predictive Control of a Buck-Boost DC-DC Converter

A predictive current control algorithm for the Buck-Boost DC-DC converter is presented in this paper. The continuous time model of the system is properly introduced, then, by imposing a proper PWM modulation pattern, its discrete time model is achieved. This last one is successfully employed in determining the steady state locus of the Buck-Boost converter, both in CCM （continuous conduction mode） and DCM （discontinuous conduction mode）. A novel continuous time equivalent circuit of the converter is introduced too, with the aim of determining a ripple free representation of the state variables of the system, over both transient and steady state operation. Then, a predictive current control algorithm, suitable in both CCM and DCM, is developed and properly checked by means of computer simulations. The corresponding results have highlighted the effectiveness of the proposed modelling and of the predictive control algorithm, both in CCM and DCM.

AN IMPROVED GN ALGORITHM OF NETWORK COMMUNITY DETECTION METHOD

.GN algorithm has high classification accuracy on community detection, but its time complexity is too high. In large scale network, the algorithm is lack of practical values. This paper puts forward an improved GN algorithm. The algorithm firstly get the network center nodes set, then use the shortest paths between center nodes and other nodes to calculate the edge betweenness, and then use incremental module degree as the algorithm terminates standard. Experiments show that, the new algorithm not only ensures accuracy of network community division, but also greatly reduced the time complexity, and improves the efficiency of community division.

Prediction of Temperature Daily Profile by Stochastic Update of Backpropagation through Time Algorithm

The authors will examine prediction of temperature daily profile using various modifications of BPTT （backpropagation through time algorithm） done by stochastic update in the artificial RCNN （recurrent neural networks）. The general introduction was provided by Salvetti and Wilamowski in 1994 in order to improve probability of convergence and speed of convergence. This update method has also one another quality, its implementation is simple for arbitrary network topology. In stochastic update scenario, constant number of weights/neurons is randomly selected and updated. This is in contrast to classical ordered update, where always all weights/neurons are updated. Stochastic update is suitable to replace classical ordered update without any penalty on implementation complexity and with good chance without penalty on quality of convergence. They have provided first experiments with stochastic modification on BP （backpropagation algorithm） used for artificial FFNN （feed-forward neural network） in detail described in the article ＂Stochastic Weight Update in the Backpropagation Algorithm on Feed-Forward Neural Networks＂ presented on the conference IJCNN （International Joint Conference of Neural Networks） 2010 in Barcelona. The BPTT on RCNN uses the history of previous steps stored inside of the NN that can be used for prediction. They will describe exact implementation on the RCNN, and present experiment results on temperature prediction with recurrent neural network topology. The dataset used for temperature prediction consists of the measured temperature from the year 2000 till the end of February 2011. Dataset is split into two groups： training dataset, which is provided to network in learning phase, and testing dataset, which is unknown part of dataset to NN and used to test the ability of NN to predict the temperature and the ability of NN to generalize the model hidden in the temperature profile. The results show promising properties of stochastic weight update with toy-task data, and the higher complexity of the temperature daily profile prediction.

奇妙的“恒星钟”

经常仰望星空的朋友们。不知道你们注意到没有，仙后座的中间星(仙后座y)、小熊座的北极星和大熊座北斗七星的斗柄第三星(玉衡星)，这三颗星的视位置几乎在一条直线上(下文简称为“三星直线”)。这条三星直线与北极星下方的地平线时而平行时而相交，根据二者的交角，可以很方便地测算时间，它们组成了一架奇妙而精密的天然“恒星钟”。

铁路通道能力计算和运输提效的实践与应用

就目前来看,铁路运输企业需重点研究如何通过有限的通道能力提高运输效率是有效解决运输瓶颈的主要方式之一,进而实现“精准”提效。通过对铁路区段通过能力和车站作业能力的理论研究和计算,可科学判断出各阶段铁路线的运输组织能力,进而为铁路各专业资源配置,关键瓶颈问题的解决提供理论依据。

A time-series modeling method based on the boosting gradient-descent theory

The forecasting of time-series data plays an important role in various domains. It is of significance in theory and application to improve prediction accuracy of the time-series data. With the progress in the study of time-series, time-series forecasting model becomes more complicated, and consequently great concern has been drawn to the techniques in designing the forecasting model. A modeling method which is easy to use by engineers and may generate good results is in urgent need. In this paper, a gradient-boost AR ensemble learning algorithm (AREL) is put forward. The effectiveness of AREL is assessed by theoretical analyses, and it is demonstrated that this method can build a strong predictive model by assembling a set of AR models. In order to avoid fitting exactly any single training example, an insensitive loss function is introduced in the AREL algorithm, and accordingly the influence of random noise is reduced. To further enhance the capability of AREL algorithm for non-stationary time-series, improve the robustness of algorithm, discourage overfitting, and reduce sensitivity of algorithm to parameter settings, a weighted kNN prediction method based on AREL algorithm is presented. The results of numerical testing on real data demonstrate that the proposed modeling method and prediction method are effective.

Time synchronization and ranging under unknown positions and velocities

The process to achieve time synchronization and ranging for a network of mobile nodes is raising a concern among researchers, and hence a variety of joint time synchronization and ranging algorithms have been proposed in recent years. However, few of them handle the case of all-node motion under unknown positions and velocities. This study addresses the problem of determining ranging and time synchronization for a group of nodes moving within a local area. First, we examined several models of clock discrepancy and synchronous two-way ranging. Based upon these models, we present a solution for time synchronization with known positions and velocities. Next, we propose a functional model that jointly estimates the clock skew, clock offset, and time of flight in the absence of a priori knowledge for a pair of mobile nodes. Then, we extend this model to a network-wide time synchronization scheme by way of a global least square estimator. We also discuss the advantages and disadvantages of our model compared to the existing algorithms, and we provide some applicable scenarios as well. Finally, we show that the simulation results verify the validity of our analysis.

Study on Lag time Model of Fire Plume under a Sloped Ceiling

It is known that there is a lag time for smoke plume induced by fires transporting from a fire origin to the location of interest underneath an unconfined and flat ceiling.This lag behavior of smoke plume also exists for a fire under a sloped ceiling,and is fundamental to estimate the activation time of a fire detector or other fire extinguishing system.This study focuses on the lag time of smoke plume under a sloped ceiling.Based on the weak-plume theory at early-fire phase and previous studies concerning the fire plume characteristics under a sloped ceiling,a calculation method on lag time of fire plume transporting is presented in theory.Meanwhile,two dimensionless equations predicting the lag time of fire plume for steady fire and unsteady fire are proposed respectively.Furthermore,the critical time calculation equation is also proposed to determine the applicability of quasi-steady assumption for a time-dependent fire.