整体性正骨正体法概论

整体性正骨正体法是整体观人、待人和施治的一种方法。在认识论上,强调人一身而天地,人既独立于天地时空,又联系于天地时空。故在方法论上,凡诊断、施治,外则要观气候、地理、时令,要因地、因时而辨证施治,内则要观人察心,因人而异、因心理而异辨证施治。人是一个有机的统一整体,身心整体而成人,没有孤立的人体,没有孤立于人体之外的心理,

德沃金的法律理论起源与自由主义思想

德沃金具有公认的世界性学术地位,但在有关他的法律理论起源问题研究上却存在极大分歧。如果从德沃金直接研究的自由主义问题着手加以研究,则有助于进一步厘清他的法律理论起源问题。基于捍卫自由主义传统的问题意识,德沃金提出了"自由主义平等观"的核心观念,建构了法律原则论和法律解释论等自由主义法律理论体系。正是在"自由主义平等观"的提出与论证过程中,德沃金动用了各种理论资源来捍卫自由主义传统,从而使他的理论起源问题看来复杂而实则简单,理论体系问题看似断裂而实则统一。

略论马克思学说的整体性维度——对马克思主义原理课程改革的思考

针对马克思主义基本原理课程体系的调整,笔者在阐述马克思学说的建构意图、马克思学说三部分的内在关联以及马克思学说逻辑结构的基础上提出了用一种整体性的眼光来看待马克思学说的观点。也就是传统的“三分式”的解读方法加上一个整体性的维度。由此,我们应该用一种“整体解读法”来指导马克思主义理论的教学和科研。

GLOBAL CONVERGENCE OF A CLASS OF OPTIMALLY CONDITIONED SSVM METHODS

This paper explores the convergence of a class of optimally conditioned self scaling variable metric (OCSSVM) methods for unconstrained optimization. We show that this class of methods with Wolfe line search are globally convergent for general convex functions.

IMPROVED FXLMS ALGORITHM BASED ON ADAPTIVE NOTCH FILTER APPROACH

An improved algorithm is presented to identify the secondary path based on the adaptive notch filter approach. Since the interference from the narrow band excitation signal is suppressed by the adaptive notch filter, the convergent speed of the on-line control path identification process is significantly improved. As a result, the controller performance is greatly enhanced. Besides the algorithm development, some important factors, such as the influence of reference signal on the controller convergent speed, are also discussed. The effectiveness of the algorithm is verified by experimental results.

A Characterization of Existence of Global Solutions for Some Fourth-order Wave Equations

The initial boundary value problem for the fourth-order wave equation u_(tt)+△~2u+u=|u|^(p-1)u is considered.The existence and uniqueness of global weak solutions is obtained by using the Galerkin method and the concept of stable set due to Sattinger.

Effective goaf gas capture design at Ravensworth Underground Mine

This paper highlights a reliable goaf gas capture system developed and used at Ravensworth Under-ground Mine since its trial in 2009. The method utilises horizontal holes drilled from underground sites and connected to an underground gas pipeline. This system incorporates a gas suction and flaring plant designed specifically for this method. The current method has captured effectively a total longwall, and adjacent goaf gas accounts for over 85%. The design of the holes drilled has been the success of the gas flow reliability. The flow is extraordinarily consistent and predictable. The management of the under-ground pipeline determines the overall reliability of flow. The design has resulted in Ravensworth Man-agement being confident to remove a gas bearing bleeder roadway and still manage the existing tailgate roadway for allowing access as required. The reduction of CO2 equivalent emissions recorded is approx-imately 0.35 ？ 106 tons annually. This design has further improvements to be added to allow use at any other site with gas in the overlying strata.

Enhance Mining System Reliability through System Integration Approach

The reliability of mining systems is generally low due to their harsh working conditions. Currently, efforts for improving mining system reliability are often made in isolation. This practice could substantially limit the effectiveness of the efforts on overall reliability improvement of the mining system. To enhance the overall reliability of mining systems, an integrated improvement approach is necessary. In this paper, we developed a framework for integrated mining system reliability improvement to address this issue. In this framework, there are five major components including data integration, business process integration, hardware integration, software integration and analysis/decision integration, but we only focus on the integrated reliability analysis which is important to the analysis/decision integration. The reliability analysis considers the interactions between machines, and the impacts of design, operation, maintenance, automation and working environment on the overall system reliability. These multiple interactions present a big challenge to accurate reliability prediction. In this paper, we for the first time systematically investigated integrated reliability analysis approaches for dealing with this challenge using novel models and methods, including covariate hazard models, intelligent reliability prediction approach and complex system modeling methods. While these models and methods have found some successful applications in other industries, they in general have not been effectively used for the reliability analysis of mining systems. Our study results show that the system integration approach is applicable to mining systems and can be used for developing a computer aided integration system for the implementation of the integrated reliability improvement approach.

Mechanism of Integrative Body-Mind Training

Integrative Body-Mind Training（IBMT） originates from ancient Eastern tradition.The method stresses no effort to control thoughts,but instead a state of restful alertness that allows a high degree of awareness of the body,breathing,and external instructions.A series of studies indicates that IBMT improves attention and self-regulation through interaction between the central（brain） and the autonomic（body） nervous systems.The present review mainly summarizes the recent results of IBMT studies and proposes how it changes the state of brain and body to lead to positive outcomes.Future directions in this field are also discussed.

AN ADAPTIVE TRUST REGION METHOD FOR EQUALITY CONSTRAINED OPTIMIZATION

In this paper, a trust region method for equality constrained optimizationbased on nondifferentiable exact penalty is proposed. In this algorithm, the trail step ischaracterized by computation of its normal component being separated from computation of itstangential component, i.e., only the tangential component of the trail step is constrained by trustradius while the normal component and trail step itself have no constraints. The other maincharacteristic of the algorithm is the decision of trust region radius. Here, the decision of trustregion radius uses the information of the gradient of objective function and reduced Hessian.However, Maratos effect will occur when we use the nondifferentiable exact penalty function as themerit function. In order to obtain the superlinear convergence of the algorithm, we use the twiceorder correction technique. Because of the speciality of the adaptive trust region method, we usetwice order correction when p = 0 (the definition is as in Section 2) and this is different from thetraditional trust region methods for equality constrained optimization. So the computation of thealgorithm in this paper is reduced. What is more, we can prove that the algorithm is globally andsuperlinearly convergent.

A ROBUST SQP METHOD BASED ON A SMOOTHING APPROXIMATE PENALTY FUNCTION FOR INEQUALITY CONSTRAINED OPTIMIZATION

A robust SQP method, which is analogous to Facchinei’s algorithm, is introduced. The algorithm is globally convergent. It uses automatic rules for choosing penalty parameter, and can efficiently cope with the possible inconsistency of the quadratic search subproblem. In addition, the algorithm employs a differentiable approximate exact penalty function as a merit function. Unlike the merit function in Facchinei’s algorithm, which is quite complicated and is not easy to be implemented in practice, this new merit function is very simple. As a result, we can use the Facchinei’s idea to construct an algorithm which is easy to be implemented in practice.

图形图像处理课程架构研究

图形图像处理课程是非常重要的软件类基础课程,对于计算机学习来说具有重要意义。文章从分析课题背景入手,阐述了整体性学习法在图形图像处理课程中的具体运用,给出课程设计与实施具体方法策略,以促进图形图像处理课程教学质量的提升,科学、合理地设计课程结构,在有限的时间内帮助学生掌握基础知识,提升技能水平,重塑学习自信心,提高解决问题的能力,为学生后续专业课程的学习打下良好基础。

HASM-AD Algorithm Based on the Sequential Least Squares

The HASM(high accuracy surface modeling) technique is based on the fundamental theory of surfaces,which has been proved to improve the interpolation accuracy in surface fitting.However,the integral iterative solution in previous studies resulted in high temporal complexity in computation and huge memory usage so that it became difficult to put the technique into application,especially for large-scale datasets.In the study,an innovative model(HASM-AD) is developed according to the sequential least squares on the basis of data adjustment theory.Sequential division is adopted in the technique,so that linear equations can be divided into groups to be processed in sequence with the temporal complexity reduced greatly in computation.The experiment indicates that the HASM-AD technique surpasses the traditional spatial interpolation methods in accuracy.Also,the cross-validation result proves the same conclusion for the spatial interpolation of soil PH property with the data sampled in Jiangxi province.Moreover,it is demonstrated in the study that the HASM-AD technique significantly reduces the computational complexity and lessens memory usage in computation.