试论制造企业总生产计划的建立

生产计划系统是一个包括需求预测、总生产计划、中期生产计划、生产作业计划、材料计划等相关计划职能,并以生产控制信息的迅速反馈连接构成的复杂系统。而生产计划系统中,总生产计划的建立尤其重要,本文一方面从总生产计划的概念、制定方法、影响因素等角度出发,剖析了总生产计划这一概念,同时也结合本企业的实践提出了具体执行过程中需要注意的问题。

Science Letters:Visual odometry for road vehicles—feasibility analysis

Estimating the global position of a road vehicle without using GPS is a challenge that many scientists look forward to solving in the near future. Normally, inertial and odometry sensors are used to complement GPS measures in an attempt to provide a means for maintaining vehicle odometry during GPS outage. Nonetheless, recent experiments have demonstrated that computer vision can also be used as a valuable source to provide what can be denoted as visual odometry. For this purpose, vehicle motion can be estimated using a non-linear, photogrametric approach based on RAndom SAmple Consensus (RANSAC). The results prove that the detection and selection of relevant feature points is a crucial factor in the global performance of the visual odometry algorithm. The key issues for further improvement are discussed in this letter.

Comparing dynamical systems concepts and techniques for biomechanical analysis

Traditional biomechanical analyses of human movement are generally derived from linear mathematics.While these methods can be useful in many situations,they do not describe behaviors in human systems that are predominately nonlinear.For this reason,nonlinear analysis methods based on a dynamical systems approach have become more prevalent in recent literature.These analysis techniques have provided new insights into how systems(1) maintain pattern stability,(2) transition into new states,and(3) are governed by short-and long-term(fractal) correlational processes at different spatio-temporal scales.These different aspects of system dynamics are typically investigated using concepts related to variability,stability,complexity,and adaptability.The purpose of this paper is to compare and contrast these different concepts and demonstrate that,although related,these terms represent fundamentally different aspects of system dynamics.In particular,we argue that variability should not uniformly be equated with stability or complexity of movement.In addition,current dynamic stability measures based on nonlinear analysis methods(such as the finite maximal Lyapunov exponent) can reveal local instabilities in movement dynamics,but the degree to which these local instabilities relate to global postural and gait stability and the ability to resist external perturbations remains to be explored.Finally,systematic studies are needed to relate observed reductions in complexity with aging and disease to the adaptive capabilities of the movement system and how complexity changes as a function of different task constraints.

Alternative 3D Modeling Approaches Based on Complex Multi-Source Geological Data Interpretation

Due to the complex nature of multi-source geological data, it is difficult to rebuild every geological structure through a single 3D modeling method. The multi-source data interpretation method put forward in this analysis is based on a database-driven pattern and focuses on the discrete and irregular features of geological data. The geological data from a variety of sources covering a range of accuracy, resolution, quantity and quality are classified and integrated according to their reliability and consistency for 3D modeling. The new interpolation-approximation fitting construction algorithm of geological surfaces with the non-uniform rational B-spline(NURBS) technique is then presented. The NURBS technique can retain the balance among the requirements for accuracy, surface continuity and data storage of geological structures. Finally, four alternative 3D modeling approaches are demonstrated with reference to some examples, which are selected according to the data quantity and accuracy specification. The proposed approaches offer flexible modeling patterns for different practical engineering demands.

Accuracy Validation for Medical Image Registration Algorithms:a Review

Accuracy validation is essential to clinical application of medical image registration techniques. Registration validation remains a challenging problem in practice mainly due to lack of 'ground truth'. In this paper, an overview of current validation methods for medical image registration is presented with detailed discussion of their benefits and drawbacks. Special focus is on non-rigid registration validation. Promising solution is also discussed.

Measuring Herbage Mass by Non-Destructive Methods： A Review

Accurate assessment of herbage mass （HM） in pasture is a key to budgeting forage in grazing systems worldwide. Different non-destructive techniques to measuring pasture yield are commented. The methods compared include visual estimations, manual and electronic pasture meters and remote sensing. All methods are associated with a moderate to high error, showing that some indirect methods of yield estimation are appropriate under most appropriate because many factors as climate variations, soil certain conditions. In general terms, no method was found as the characteristics, plant phenology, pasture management and species composition must be taken into account to make local calibrations from a general model. Best results were found modifying general methods under local calibrations and under local conditions. In order to give farmers the best method to manage adequately their own grazing systems, researchers must select the most suitable technique considering the scale of operation, the desired accuracy and the resources available.

C-LOG： A Chamfer distance based algorithm for localisation in occupancy grid-maps

A novel algorithm for localising a robot in a known two-dimensional environment is presented in this paper. An occupancy grid representing the environment is first converted to a distance function that encodes the distance to the nearest obstacle from any given location. A Chamfer distance based sensor model to associate observations from a laser ranger finder to the map of the environment without the need for ray tracing, data association, or feature extraction is presented. It is shown that the robot can be localised by solving a non-linear optimisation problem formulated to minimise the Chamfer distance with respect to the robot location. The proposed algorithm is able to perform well even when robot odometry is unavailable and requires only a single tuning parameter to operate even in highly dynamic environments. As such, it is superior than the state-of-the-art particle filter based solutions for robot localisation in occupancy grids, provided that an approximate initial location of the robot is available. Experimental results based on simulated and public domain datasets as well as data collected by the authors are used to demonstrate the effectiveness of the proposed algorithm.

Fortified Financial Forecasting Models Based on Non-Linear Searching Approaches

The paper＇s aim is how to forecast data with variations involving at times series data to get the best forecasting model. When researchers are going to forecast data with variations involving at times series data （i.e., secular trends, cyclical variations, seasonal effects, and stochastic variations）, they believe the best forecasting model is the one which realistically considers the underlying causal factors in a situational relationship and therefore has the best ＂track records＂ in generating data. Paper＇s models can be adjusted for variations in related a time series which processes a great deal of randomness, to improve the accuracy of the financial forecasts. Because of Na＇fve forecasting models are based on an extrapolation of past values for future. These models may be adjusted for seasonal, secular, and cyclical trends in related data. When a data series processes a great deal of randomness, smoothing techniques, such as moving averages and exponential smoothing, may improve the accuracy of the financial forecasts. But neither Na＇fve models nor smoothing techniques are capable of identifying major future changes in the direction of a situational data series. Hereby, nonlinear techniques, like direct and sequential search approaches, overcome those shortcomings can be used. The methodology which we have used is based on inferential analysis. To build the models to identify the major future changes in the direction of a situational data series, a comparative model building is applied. Hereby, the paper suggests using some of the nonlinear techniques, like direct and sequential search approaches, to reduce the technical shortcomings. The final result of the paper is to manipulate, to prepare, and to integrate heuristic non-linear searching methods to serve calculating adjusted factors to produce the best forecast data.

A nonparametric estimation of the infection curve

Predicting the future course of an epidemic depends on being able to estimate the current numbers of infected individuals.However,while back-projection techniques allow reliable estimation of the numbers of infected individuals in the more distant past,they are less reliable in the recent past.We propose two new nonparametric methods to estimate the unobserved numbers of infected individuals in the recent past in an epidemic.The proposed methods are noniterative,easily computed and asymptotically normal with simple variance formulas.Simulations show that the proposed methods are much more robust and accurate than the existing back projection method,especially for the recent past,which is our primary interest.We apply the proposed methods to the 2003 Severe Acute Respiratory Syndorme(SARS) epidemic in Hong Kong.

Code-aided Interference Suppression in Direct Sequence Spread Spectrum Systems with Eigenvector Sign Spreading Code

For direct sequence spread spectrum (DSSS) communication systems suffering interference, it is known that code-aided interference suppression technique outperforms all of the previous linear or nonlinear methods. In this paper, we proposed an improved code-aided technique which can improve the system performance greatly by using the eigenvector sign (EVS) spreading sequence which depends on the statistical characteristics of the interference and the thermal noise.