Analysis of Test Methods for Parts to Follow Relative Requirements

Testing the parts of mechanical products and ensuring their accuracy to the design requirements are essential to products’ quality, market competitiveness and manufacturers’ maximum economical benefits from these products. One of the latest subjects of study in the area of precision measurement is the testing of parts to follow the relative requirements, viz. design requirements for the size tolerance of size features and related geometrical tolerances of the central feature, including the envelope requirement, maximum material requirement and least material requirement. The article analyzes test methods for parts to follow the envelope requirement or maximum material requirement, as well as further requirements of geometrical tolerances for its central feature. The method is effective in improving product quality and rejecting unqualified parts.

Optimal choice of parameters for particle swarm optimization

The constriction factor method (CFM) is a new variation of the basic particle swarm optimization (PSO), which has relatively better convergent nature. The effects of the major parameters on CFM were systematically investigated based on some benchmark functions. The constriction factor, velocity constraint, and population size all have significant impact on the per- formance of CFM for PSO. The constriction factor and velocity constraint have optimal values in practical application, and im- proper choice of these factors will lead to bad results. Increasing population size can improve the solution quality, although the computing time will be longer. The characteristics of CFM parameters are described and guidelines for determining parameter values are given in this paper.

Analysis on Changes of Basic Climatic Elements and Extreme Events in Xinjiang, China during 1961-2010

By using the observation data from 89 weather stations in Xinjiang during 1961-2010, this paper analyzed the basic climatic elements including temperature, precipitation, wind speed, sunshine duration, water vapor pressure, and dust storm in the entire Xinjiang and the subareas: North Xinjiang, Tianshan Mountains, and South Xinjiang. The results indicate that from 1961 to 2010 the annual and seasonal mean temperatures in the entire Xinjiang show an increasing trend with the increasing rate rising from south to north. The increasing rate of annual mean minimum temperature is over twice more than that of the annual mean maximum temperature, contributing much to the increase in the annual averages. The magnitude of the decrease rate of low-temperature days is larger than the increase rate of high-temperature days. The increase of warm days and warm nights and the decrease of cold days and cold nights further reveal that the temperature increasing in Xinjiang is higher. In addition, annual and seasonal rainfalls have been increasing. South Xinjiang experiences higher increase in rainfall amounts than North Xinjiang and Tianshan Mountains. Annual rainy days, longest consecutive rainy days, the daily maximum precipitation and extreme precipitation events, annual torrential rain days and amount, annual blizzard days and amount, all show an increasing trend, corresponding to the increasing in annual mean water vapor pressure. This result shows that the humidity has increased with temperature increasing in the past 50 years. The decrease in annual mean wind speed and gale days lessen the impact of dust storm, sandstorm, and floating dust events. The increase in annual rainy days is the cause of the decrease in annual sunshine duration, while the increase in spring sunshine duration corresponds with the decrease in dust weather. Therefore, the increase in precipitation indicators, the decrease in gales and dust weather, and the increasing in sunshine duration in spring will be beneficial to crops growth.

Optimal Power Allocation for Multiuser Underlay Cognitive Radio Networks under QoS and Interference Temperature Constraints

Power allocation is an important issue for Cognitive Radio Networks(CRNs),since it needs to consider the Quality of Service(QoS) for Secondary Users(SUs) while maintaining the interference power to Primary User(PU) below the Interference Temperature(IT) threshold. In this paper, based on Euclidean projection, we propose a distributed power control algorithm with QoS requirements to minimise the total power consumption of SUs under the time-varying channel scenario. Considering the maximum transmit power constraints and the minimum signal to interference plus noise constraints for each SU, together with the IT constraints for each PU, the power allocation problem is transformed into a convex optimization problem without auxiliary variables, and is solved by the Lagrangian dual method with less information exchange.Simulation results demonstrate that the proposed scheme is superior to the Iterative Water-Filling Algorithm(IWFA).

Profit Optimization of External Cylindrical Grinding

This article presents a study on profit optimization of external cylindrical grinding. In the optimization problem, the influences of several grinding process parameters such as the initial grinding wheel diameter, the wheel life, the total dressing depth as well as the effect of many cost components were investigated. A model for determination of optimum exchanged grinding wheel diameter was proposed. With this optimum diameter, a new and effective way of using the grinding wheel was proposed.

Abnormal activity detection for surveillance video synopsis

Video synopsis is an effective and innovative way to produce short video abstraction for huge video archives,while keeping the dynamic characteristic of activities in the original video.Abnormal activity,as the critical event,is always the main concern in video surveillance context.However,in traditional video synopsis,all the normal and abnormal activities are condensed together equally,which can make the synopsis video confused and worthless.In addition,the traditional video synopsis methods always neglect redundancy in the content domain.To solve the above-mentioned issues,a novel video synopsis method is proposed based on abnormal activity detection and key observation selection.In the proposed algorithm,activities are classified into normal and abnormal ones based on the sparse reconstruction cost from an atomically learned activity dictionary.And key observation selection using the minimum description length principle is conducted for eliminating content redundancy in normal activity.Experiments conducted in publicly available datasets demonstrate that the proposed approach can effectively generate satisfying synopsis videos.

The Problem of Timan on the Precise Order of the Best Approximations of Multivariate Functions

The problem of Timan on finding a necessary and sufficient condition for is solved. The condition is that

Recovery of band limited functions via cardinal splines

The main result of this paper asserts that if a function f is in the class Bπ,p, 1 <p < ∞; that is, those p-integrable functions whose Fourier transforms are supported in the interval [ - π, π], then f and its derivatives f(j) j = 1, 2, …, can be recovered from its sampling sequence{f(k)} via the cardinal interpolating spline of degree m in the metric ofL q(?)), 1 <p=q < ∞, or 11 <p=q < ? ∞.

On symplectic self-adjointness of Hamiltonian operator matrices

Symplectic self-adjointness of Hamiltonian operator matrices is studied, which is important to symplectic elasticity and optimal control. For the cases of diagonal domain and off-diagonal domain, necessary and sufficient conditions are shown. The proofs use Frobenius-Schur factorizations of unbounded operator matrices.Under additional assumptions, sufficient conditions based on perturbation method are obtained. The theory is applied to a problem in symplectic elasticity.

Passive source localization using importance sampling based on TOA and FOA measurements

Passive source localization via a maximum likelihood （ML） estimator can achieve a high accuracy but involves high calculation burdens, especially when based on time-of-arrival and frequency-of-arrival measurements for its internal nonlinearity and nonconvex nature. In this paper, we use the Pincus theorem and Monte Carlo importance sampling （MCIS） to achieve an approximate global solution to the ML problem in a computationally efficient manner. The main contribution is that we construct a probability density function （PDF） of Gaussian distribution, which is called an important function for efficient sampling, to approximate the ML estimation related to complicated distributions. The improved performance of the proposed method is at- tributed to the optimal selection of the important function and also the guaranteed convergence to a global maximum. This process greatly reduces the amount of calculation, but an initial solution estimation is required resulting from Taylor series expansion. However, the MCIS method is robust to this prior knowledge for point sampling and correction of importance weights. Simulation results show that the proposed method can achieve the Cram6r-Rao lower bound at a moderate Gaussian noise level and outper- forms the existing methods.

Some results on pointwise second-order necessary conditions for stochastic optimal controls

The purpose of this paper is to derive some pointwise second-order necessary conditions for stochastic optimal controls in the general case that the control variable enters into both the drift and the diffusion terms.When the control region is convex, a pointwise second-order necessary condition for stochastic singular optimal controls in the classical sense is established; while when the control region is allowed to be nonconvex, we obtain a pointwise second-order necessary condition for stochastic singular optimal controls in the sense of Pontryagin-type maximum principle. It is found that, quite different from the first-order necessary conditions,the correction part of the solution to the second-order adjoint equation appears in the pointwise second-order necessary conditions whenever the diffusion term depends on the control variable, even if the control region is convex.

KUHN-TUCKER NECESSARY CONDITIONS FOR (h, ψ)-MULTIOBJECTIVE OPTIMIZATION PROBLEMS

Five kinds of cones are introduced, which are used to establish the constraints qualifications, under which the generalized Kuhn-Tucker necessary conditions are developed for a class of generalized (h,φ)-differentiable single-objective and multiobjective programming problems by using Motzkin's alternative theorem and Ben-Tal generalized algebraic operations.

OPTIMAL CONTROL OF GROWTH RATE FOR A CLASS OF POPULATION SYSTEMS

In this paper,we discuss the optimal control of growth rate for a class of population systems governed by nonlinear degenerate parabolic equations.Given an ap-propriate cost functional,we prove the existence of the optimal growth rate and give some necessary conditions for optimal growth rate.

Parameters optimum matching of pure electric vehicle dual-mode coupling drive system

As an important development direction of pure electric vehicle drive system,the distributed drive system has the advantages of compact structure,high transmission efficiency,and flexible control,but there are some serious problems such as high performance requirements to the drive motors,complex control strategies,and poor reliability.To solve these problems,a two motors dual-mode coupling drive system has been developed at first,which not only has the capacity of two-speed gear shifting,but also can automatically switch between the distributed drive and the centralized drive by means of modes change control.So,the performance requirements to the drive motors can be reduced,the problem of abnormal running caused by the fault of unilateral distributed drive systems also can be resolved by replacing the drive mode with centralized drive.Then,the system parameters primary and the optimum matching under the principle of efficiency optimization have been carried out,which makes the drive system achieve predetermined functions and meet the actual demands of different operating statuses.At last,the economic comparison of a pure electric vehicle installation with a dual-mode coupling drive sytem,a single-motor centralized drive system or a dual-motor distributed drive system in the simulation conditions has been completed.Compared with other systems,the driving range of the electric vehicle driven by the designed system is significantly increased,which proves the better efficiency and application value of the system.

A NECESSARY AND SUFFICIENT CONDITION FOR A POINT TO BE A GLOBAL MAXIMIZER OF ACONSTRAINED OPTIMIZATION

It is difficult to judge whether a given point is a global maximizer of an unconstrained optimization problem. This paper deals with this problem by considering global information via integral and gives a necessary and sufficient condition judging whether a given point is a global maximizer of an unconstrained optimization problem. An algorithm is offered under such a condition and finally two test problems are verified via the offered algorithm.

AMERICAN OPTION PRICING UNDER GARCH DIFFUSION MODEL: AN EMPIRICAL STUDY

The GARCH diffusion model has received much attention in recent years, as it describes financial time series better when compared to many other models. In this paper, the authors study the empirical performance of American option pricing model when the underlying asset follows the GARCH diffusion. The parameters of the GARCH diffusion model are estimated by the efficient importance sampling-based maximum likelihood （EIS-ML） method. Then the least-squares Monte Carlo （LSMC） method is introduced to price American options. Empirical pricing results on American put options in Hong Kong stock market shows that the GARCH diffusion model outperforms the classical constant volatility （CV） model significantly.

On Stabilization of It Stochastic Time-Varying Systems

The stabilization with receding horizon control （RHC） of It5 stochastic time-varying systems is studied in this paper. Based on monotonically non-increasing of optimal cost and stochastic Lyapunov stability theory, a necessary and sufficient stabilization condition on the terminal weighting matrix is proposed, which guarantees the mean-square stability of the closed-loop system. The explicit receding horizon controller is obtained by employing stochastic maximum principle. Simulations demonstrate the effectiveness of the proposed method.