An adaptive mesh method with variable relaxation time

Moving mesh partial differential equations have been widely used in the last decade for solving differential equations exhibiting large solution variations such as shock waves and boundary layers.In this paper, we have applied a dynamic adaptive method for solving time-dependent differential equations. The mesh velocities are governed by an equation in which a relaxation time is employed to move nodes in such a way that they remain concentrated in regions of rapid variation of the solution. A numerical example involving a blow-up problem shows the advantage of using a variable relaxation time over a fixed one.     

CALIMERA: A new early time series classification method

Early time series classification is a variant of the time series classification task, in which a label must be assigned to the incoming time series as quickly as possible without necessarily screening through the whole sequence. It needs to be realized on the algorithmic level by fusing a decision-making method that detects the right moment to stop and a classifier that assigns a class label. The contribution addressed in this paper is twofold. Firstly, we present a new method for finding the best moment to perform an action (terminate/continue). Secondly, we propose a new learning scheme using classifier calibration to estimate classification accuracy. The new approach, called CALIMERA, is formalized as a cost minimization problem. Using two benchmark methodologies for early time series classification, we have shown that the proposed model achieves better results than the current state-of-the-art. Two most serious competitors of CALIMERA are ECONOMY and TEASER. The empirical comparison showed that the new method achieved a higher accuracy than TEASER for 35 out of 45 datasets and it outperformed ECONOMY in 20 out of 34 datasets.     

Experimental measurement of the quantum geometric tensor using coupled qubits in diamond

Geometry and topology are fundamental concepts, which underlie a wide range of fascinating physical phenomena such as topological states of matter and topological defects. In quantum mechanics, the geometry of quantum states is fully captured by the quantum geometric tensor. Using a qubit formed by an NV center in diamond, we perform the first experimental measurement of the complete quantum geometric tensor. Our approach builds on a strong connection between coherent Rabi oscillations upon parametric modulations and the quantum geometry of the underlying states. We then apply our method to a system of two interacting qubits, by exploiting the coupling between the NV center spin and a neighboring ¹³C nuclear spin. Our results establish coherent dynamical responses as a versatile probe for quantum geometry, and they pave the way for the detection of novel topological phenomena in solid state.     

A new method to estimate a first-order plus time delay model from step response

In this paper an identification method to estimate the parameters of a first-order plus time delay model is proposed. Such a method directly obtains these parameters using a new linear regression equation. No iterations in calculation are needed. Moreover, a simple true/false criterion to establish if the hypothesis on the process type is correct can be easily derived. The proposed method shows an acceptable robustness to disturbances and measurement noise as it is confirmed by several simulated experiments.     

基于引用时序特征的唤醒专利识别研究

唤醒专利是特殊类型的专利,由于技术内涵的超前性,在生命周期的早期阶段,处于罕有引用的休眠状态;在经历多年的沉寂后,随着技术发展和市场变化,最终受到关注并获得高引用而被唤醒;作为大器晚成的专利类型,唤醒专利尚未受到足够重视,亟待开展深入的研究工作。选取无线通信网络领域的专利作为研究样本,基于专利引用的时序特征分析,研究构建唤醒专利的识别方法;运用该识别方法筛选唤醒专利,剖析其典型特征,研究提出利用唤醒专利特征,分析和监测相关技术的发展趋势。     

中国风能技术发明专利维持时间影响因素研究

在梳理我国风能技术发明专利发展演变趋势基础上,以维持时间为衡量指标,本文认为中国风能技术发明专利质量低于国外专利质量。通过选取1985年-2013年无效专利为样本,作者运用多元线性回归模型重点研究中国风能技术发明专利维持时间的影响因素问题,发现:选取的六个自变量中,影响力度最大的是年费,影响力从大到小依次排列的是年费、专利族大小、发明人数、科研院所或个人、专利审查时间。根据多元线性回归模型的结果,作者提出了增加我国风能技术发明专利维持时间、提高我国风能技术专利质量的对策和建议。     

STS史学研究的时空交错线性方法——兼析《科技与社会大事总览》的体例结构

以大型学术文献《科技与社会大事总览》为案例,从STS研究的史学视角,从横向联系观察每个STS断面的要素与结构,从纵向时序串接诸多STS断面系列,以历史的惯性、刚性、必然性、规律性透视每片STS,在历史的横向剖切与纵向流动的立体交错与时空融合中进行判断及选择,在至高的历史耸立中俯瞰STS的广阔范阈和历史联系,并力图通过线性的、量化的、模式化的方法予以剖解。     

大学组织复杂性的历史演进——基于复杂性理论的视角

近年来,组织复杂性问题已经成为现代组织管理研究领域新的研究热点,对大学组织复杂性的探讨也初现端倪。从历史的角度对大学组织复杂性进行探讨,无疑有助于我们对大学组织的复杂性有更深入的认识。本文从时间不可逆性与大学组织复杂性发展、大学职能复杂性发展、知识演进复杂性与大学生学习方式的变化等方面对大学组织复杂性作了比较系统的历史扫描和论述。应该说,这种探讨的角度比较新,对大学组织复杂特性的揭示也比较深入。     

非吸收椭球形粒子尺度分布反演的一种新方法

研究了非吸收椭球形粒子尺度分布的反演问题.对于连续消光谱,得到了尺度分布与消光系数之间一个新的变换关系.对于离散消光谱,给出了基于Gamma分布展开的粒子尺度分布函数的级数表示,其中展开系数可通过求解相应的约束线性方程组来确定.在某种给定的反演精度下,实施积分所需的最短应测量波长与最小可反演粒径成正比.数值试验表明,本文所发展的解析技术是有效的,可容忍消光谱约5%的随机误差.     

A new method for performance evaluation of bit decoding algorithms using statistics of the log likelihood ratio

This paper presents a new method for the performance evaluation of bit decoding algorithms. The method is based on estimating the probability density function (pdf) of the bit log likelihood ratio (LLR) by using an exponential model. It is widely known that the pdf of the bit LLR is close to the normal density. The proposed approach takes advantage of this property to present an efficient algorithm for the pdf estimation. The moment matching method is combined with the maximum entropy principle to estimate the underlying parameters. We present a simple method for computing the probabilities of the point estimates for the estimated parameters, as well as for the bit error rate. The corresponding results are used to compute the number of samples that are required for a given precision of the estimated values. It is demonstrated that this method requires significantly fewer samples as compared to the conventional Monte-Carlo simulation.