学科规训制度在中国的形成及发展趋势

学科规训制度是学科本身所固有,并使学科成员学科化与专业化的一系列规范。中国的学科规训制度源于西学东渐,其形成的标志是蔡元培的北京大学改革与五四新文化运动。当代学科规训的主要内容为教学规训与研究规训。学科规训制度的发展趋势是学科规训内容的完善与学科规训制度的科学化。明确学科规训的内容对大学学科建设与学生培养无疑具有重要的指导意义。     

土木工程专业应用型人才培养专业规范研究

高等教育的大众化发展,以及社会和地方经济建设对不同类型人才的需求,要求高校对人才培养选择科学的培养体系,文章对土木工程专业应用型人才培养规范的几点思考。     

施工质量与上行噪声关系的探讨

良好的施工质量才能保证网络高质量的双向传输,分析HFC网络上行信道的噪声来源,提出控制用户噪声、规范布线、线缆接头处理、接地防雷的正确方法,以提高施工质量,合理布局网络结构则要注意设备指标的一致、设备基本电平的配值、分配系统的反向衰减要大致相同,以防止噪声的侵入.     

On the computation of spherical Bessel functions of complex arguments

In this short paper, problems with existing algorithms for computing spherical Bessel functions of complex arguments are reported. As a remedy, a revised algorithm based on the recurrence is proposed. The upper and lower limits for the starting order that can be used in the backward recurrence to reach a desired accuracy are given. The proposed algorithm is stable and is capable of computing a wide range of arguments approaching machine accuracy.     

Resolution enhancement of nondestructive testing from B‐scans

This article presents an approach to extend our previous work of the minimum‐weighted norm method in computerized tomography. In particular concentrating on applications of ultrasonic nondestructive testing, the resolution enhancement in the image reconstruction from B‐scans is achieved. To combat the degradation problem due to physical focus of finite‐sized ultrasonic transducer and incompleteness of B‐scan data, a profile‐oriented prior knowledge about the object being detected is incorporated in the image reconstruction, in the form of weighted summation of specific basis functions. Each basis function is characterized by an image of coherent illumination pattern associated with a specific measuring time and a specific measuring position. From the demonstrations with both simulated and experimental data values, this technique proves a great potential in improving the image quality. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 185–193, 2012     

Stochastic stability and stabilization of a class of piecewise‐homogeneous Markov jump linear systems with mixed uncertainties

This paper investigates the stochastic stability and stabilization problem for a general class of uncertain, continuous‐time Markov jump linear systems (MJLSs). The system under consideration is a piecewise‐homogenous Markovian structure subject to piecewise‐constant time‐varying transition rates (TRs). The time variation of the TRs is characterized by a high‐level Markovian signal, which is independent from the low‐level Markovian mechanism that governs the switching between the system dynamics. It is assumed that the structure is subject to mixed uncertainties in the form of additive norm‐bounded terms. The uncertainties help to consider the effect of imperfections induced by modeling errors for the system dynamics and the TRs of Markovian signals of both levels. This new uncertain, two‐level Markovian jump linear system is a more general model than the existing ones and is applicable to more practical situations. Besides, it is capable of being specialized to uncertain piecewise‐homogeneous MJLS with arbitrarily varying TRs, as well as the uncertain time‐homogeneous MJLS. The stability/stabilizability of this system is first examined by constructing a Lyapunov function which depends on both switching signals. Then, based on the analysis results, the corresponding robust controller gains are synthesized through solving a set of linear matrix inequalities (LMIs). Finally, simulation results for an industrial stirred tank reactor (CSTR) are used to demonstrate the applicability and potentials of the proposed theoretical method. Comparative simulations are also provided to show the superiority of the presented approach to the existing ones. Copyright © 2016 John Wiley & Sons, Ltd.     

Nuclear norm regularized coding with local position-patch and nonlocal similarity for face hallucination

Learning-based face hallucination methods have received much attention and progress in past few decades. Specially, position-patch based approaches have been proposed to replace the probabilistic graph-based or manifold learning-based ones. As opposed to the existing patch based methods, where the input image patch matrix is converted into vectors before combination coefficients calculation, in this paper, we propose to directly use the image matrix based regression model for combination coefficients computation to preserve the essential structural information of the input patch matrix. For each input low-resolution (LR) patch matrix, its combination coefficients over the training image patch matrices at the same position can be computed. Then the corresponding high-resolution (HR) patch matrix can be obtained with the LR training patches replaced by the corresponding HR ones. The nonlocal self-similarities are finally utilized to further improve the hallucination performance. Various experimental results on standard face databases indicate that our proposed method outperforms some state-of-the-art algorithms in terms of both visual quantity and objective metrics.     

互联网+时代中经济新常态的思考

新常态理念指的是不追求不具备比较价值的经济高增长,其实质是在尊重客观经济规律的基础上作出的前瞻性指引,是从政治角度对既往政策的修正,也是对未来经济发展状态的一种主动描述.     

Impact of alcohol checks and social norm on driving under the influence of alcohol (DUI)

This study investigated the influence of alcohol checks and social norm on self-reported driving under the influence of alcohol above the legal limit (DUI). The analysis was based on the responses of 12,507 car drivers from 19 European countries to the SARTRE-4 survey (2010). The data were analysed by means of a multiple logistic regression-model on two levels: (1) individual and (2) national level.