论伟大建党精神培育时代新人的逻辑依据、价值意蕴及实践指南

从理论上看,培育时代新人在育人目标、文化基因、培育内容上契合伟大建党精神。从现实场域上看,伟大建党精神对时代新人的培育在认知、行为、意志、情感各方面都具有重要的引领作用,是塑造青年学生坚定理想信念、强化使命担当、增强奋斗精神、厚植忠党为民的根本遵循与应然之义。从实践指南上看,强化学校教育主阵地作用、结合现实用好“社会大课堂”、创新互联网育人新模式、构建多元主体育人大格局是伟大建党精神培育时代新人的提升路径。

Walsh Spectral Characteristics and the Auto-Correlation Function Characteristics of Forming Orthomorphic Permutations of Multi-Output Functions

Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalized Walsh spectrum of multi-output functions and the auto-correlation function of multi-output functions to investigate the Walsh spectral characteristics and the auto-correlation function characteristics of orthormophic permutations, several results are obtained.

Biometric feature extraction using local fractal auto-correlation

Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme： （i） using two-dimensional Gabor filter to extract the texture features of biometric images; （ii） calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and （iii） linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach.

SPEECH ENHANCEMENT BASED ON DYNAMIC NOISE ESTIMATION WITHIN AUTO-CORRELATION DOMAIN

Most noise suppression algorithms of single channel use the mean of noisy segments to estimate the characteristics of noise spectrum, ignoring the estimation of noise in speech segments. Therefore, when the energy level of noise varies with the time, the performance of removing noise will be degraded. To solve this problem, a speech enhancement approach based on dynamic noise estimation within correlation domain was proposed. This method exploits the characteristics that noise energy mainly concentrates on 0 th order correlation coefficients, signal is auto correlated but signal and noise, noise and noise are uncorrelated, then estimates and decomposes the noise, thus helps to solve the above mentioned problem. The results of recognition experiments on speech signals of 15 Chinese cities’ names corrupted by noise of exhibition hall shows, this approach is better than SS (Spectral Subtraction) method, adapts better to the variances of energy levels of speech signal corrupted by noise, has some practicability to improve the robustness of recognition systems under noisy environment.

ECSRE Analysis on Late Comer Strategy for Folk Custom Eco-tourism of Southeast Chongqing in the New Normal State

The development of late comers in the new normal state is a practical and urgent issue to be tackled by underdeveloped areas of China in current situation.The development strategy of late comers is economic development strategy different from economically developed areas.Five element strategic analysis model(ECSRE) stresses intrinsic features of things,which is favorable for making clear weakness of late comers and suitable for southeast Chongqing.With the aid of the ECSRE,on the basis of analyzing resources and external conditions,this paper made an in-depth analysis on late comer strategy for southeast Chongqing from the perspective of industry pattern attribute,development stages,individual characters and thinking pattern of decision-makers.It stresses regional cooperation,unified restriction,dislocation characteristics,institutional simulation and innovation and improving policy system,to stimulate strengths of late comers,so as to promote long-term rapid and sustainable development of folk custom eco-tourism in southeast Chongqing.

Chrestenson Spectrum and Auto-Correlation Function of Inverse Permutations of Quick Trickle Permutations

In this paper, a sufficient and necessary condition of quick trickle permutations is given from the point of inverse permutations. The bridge is built between quick trickle permutations and m-value logic functions. By the methods of the Chrestenson spectrum of m-value logic functions and the auto-correlation function of m-value logic functions to investigate the Chrestenson spectral characteristics and the auto-correlation function charac- teristics of inverse permutations of quick trickle permutations, a determinant arithmetic of quick trickle permutations is given. Using the results, it becomes easy to judge that a permutation is a quick trickle permutation or not by using computer. This gives a new pathway to study constructions and enumerations of quick trickle permutations.

Cyclic-Auto-Correlation Based Timing Estimation Algorithm for Time-Frequency Overlapping Multi-Carrier Signals

In recent years,the time-frequency overlapping multi-carrier signal has been a novel and valuable topic in blind signal processing,especially in the non-cooperative receiving field.But there is little related research in public published papers.This paper proposes two timing estimation algorithms,which are non-data-aided and based on the cyclic auto-correlation function.In order to evaluate the performance of the proposed algorithms,the theoretical bound of the timing estimation is derived.According to the analyses and simulation results,the effectiveness of the proposed algorithms has been demonstrated.It shows that MethodⅠhas better performance than MethodⅡ.However,MethodⅡdoes not need prior information,so it has a wider range of applications.

Monitoring Bridge Deformation Using Auto-Correlation Adjustment Technique for Total Station Observations

Bridges are omnipresent in every society and they affect its human, social, ecological, economical and cultural aspects. This is why a durable and safe usage of bridges is an imperative goal of structural management. Measurement and monitoring have an essential role in structural management. The benefits of the information obtained by monitoring are apparent in several domains. In deformation analysis, the functional relationship between the acting forces and the resulting deformations should be established. If time depending observations are given, a regression could be used as a functional model. In case of stochastic model uncorrelated observations with identical variance are assumed. Due to the high sampling rate, a small time difference arises between two observations. Thus the assumed stochastic model is not suitable. The calculation has to be effected by means of auto-correlated observations. This paper investigates an integrated monitoring system for the estimation of the deformation (i.e., static, quasi-static) behavior of bridges from total station observations and studies the effect of autocorrelation technique on the accuracy of the estimated parameters and variances. The results have shown that autocorrelation technique is reduced the standard deviation of X&Y-direction about 6.7% to 29.4% and 6.5% to 15.5% of the original value, respectively, but the situation was differ in Z direction;the standard deviation in vertical component Z was increased.

Fingerspelling Recognition by Hand Shape Using Higher-Order Local Auto-Correlation Features

The fingerspelling recognition by hand shape is an important step for developing a human-computer interaction system. A method of fingerspelling recognition by hand shape using HLAC （higher-order local auto-correlation） features is proposed. Furthermore, in order to use HLAC features more effectively, the use of image processing techniques： reducing an image resolution, dividing an image, and image pre-processing techniques, is also proposed. The experimental results show that the proposed method is promising.

基于消解“新土客冲突”的广州城中村更新策略--以广州市石马村北约为例

文章以广州市石马村北约为例,剖析“新土客冲突”现象的原因和表现,结合社会融合的理念,提出治理优化意见和空间更新策略,通过相关制度优化和一系列公共空间的干预措施,解决制度不公、文化差异、经济差异、资源匮乏等问题,重塑城中村公共空间,重构城中村居民生活方式,以促进村中本地居民与外来人口之间的良好社会关系,从而消解“新土客冲突”,为城中村更新提供新的思路和方法。

孔子“有教无类”教育思想的审辨式反思及其高等教育实践意蕴

“有教无类”是孔子提出的重要教育思想命题,通过对该命题的审辨式反思,其内在的思想内涵可从三个不同的角度进行审视,即教育公平视角下的“有教无类”,复性教育视角下的“有教无类”,训诂批判视角下的“有教无类”。无论站在哪个角度来看,“有教无类”实际上主要蕴含着人们对教育公平的向往与追求,体现为一种应然的教育价值,是教育者进行教育活动的重要内生动力,其实践意蕴主要表现为教师对学生独立人格的充分尊重和对学生的关爱与宽容,但“有教无类”并不是没有选择性的教育,教欲无类,须教而有类。

新媒体视域下红色文化的四维传播路径研究

红色文化是极具中国特色的先进文化,具有十分显著的育人价值。将红色文化融入高校思想政治教育,有助于坚定青年学生理想信念、涵养爱党爱国情怀、旗帜鲜明反对历史虚无主义,以及提升思想政治教育的吸引力和实效性,对培养堪当民族复兴重任的时代新人具有重要意义。在新媒体视域下,红色文化的传播路径还不够完善,存在传播环境“娱乐化”、传播形式“碎片化”、传播内容被“边缘化”及传播行为“失范化”等问题。规范新媒体视域下红色文化的传播,提升红色文化的育人实效,促进红色文化的可持续发展,可以从塑造环境、创新内容、完善执行和健全监督这4个维度进行。

一种新颖的彩色水印图像几何失真校正算法

几何攻击是制约水印技术实用性的重要因素,当图像经过旋转、缩放和DA转换等几何变换后,绝大多数水印算法的检测器将失效。该文提出一种新的基于计算机视觉理论的图像空域特征重同步算法,首次采用图像的corner中心角和corner中心距离对水印图像几何失真进行失真校正。实验证明,算法性能良好、校正精度高、可以有效地校正大强度几何失真。

结合空域不变量的变换域零水印二次检测方案

利用变换域水印技术对诸如压缩、滤波等信号处理具有较好鲁棒性的优点,结合空域中对几何变换具有抵抗力的常量来构造与检测零水印。实验证明,方案对剪切、数模转换处理、滤波、噪声、JPEG压缩、旋转等图像处理具有较强的鲁棒性。

基于角点特征值和视差梯度约束的角点匹配

提出了一种基于角点特征值的角点匹配快速算法,并利用视差梯度约束去除误匹配的结果。首先把提取角点时得到的角点特征值作为匹配的一个约束,提高了基于灰度相关的角点粗匹配运算的速度,然后利用视差梯度约束对粗匹配的结果进行求精运算,去除误匹配的结果,实验结果证明了该算法的有效性。

一种自适应的Harris角点检测算法

分析Harris角点检测算子的实现原理及其不足,提出一种基于图像分块和邻近角点剔除策略的自适应Harris角点检测算法,检症测出的角点均匀分布,有效避免了角点聚簇现象。实验结果表明,该算法检测出的角点分布更均匀合理,能很好地适应图像拼接等实际应用。

基于字符角点信息的车牌定位方法

车牌定位是车牌识别的基础.文中提出了一种准确快速的车牌定位方法.该方法利用三级阈值,由粗到细,首先剔除大量非角点像素,提高角点的定位速度,用大阈值突出显示车牌区域的角点,再根据车牌纹理的角点特性,利用滑动窗粗选车牌区域,然后对粗选车牌区域用小阈值,对车牌区域进行精确定位.试验证实该方法的车牌定位准确率达到98%,平均耗时约20ms.

一种快速的亚像素图像配准算法

图像超分辨率重建是在现有红外探测器基础上提升空间分辨率的一种有效方法。超分辨率图像重建是利用一组相互之间存在亚像素位移的低分辨率图像构造出一幅高分辨率的图像,快速、高精度估计图像间的位移是其关键技术之一。提出了一种用于超分辨率重建的亚像素配准算法,算法由特征检测、像素级配准和亚像素级配准三个处理过程组成。在特征检测过程,首先采用梯度算子对图像进行边缘检测,然后对边缘点进行角点预检测,排除非角点像素点,之后再进行Harris角点检测,大大减少了计算量;在像素级配准过程,用NCC算法进行像素级配准,用统计方法去除误匹配点对;在亚像素级配准过程,先对像素级匹配点的邻域进行插值放大,再进行亚像素匹配,误匹配点剔除,相对偏移量计算。对提出的算法进行了仿真实验,结果显示本算法的速度较类似算法速度有较大的提高。

基于B样条的改进型Harris角点检测算法

在研究Harris角点检测算法时发现由于该算法采用高斯低通滤波进行平滑,因而对一些图像进行角点提取时,存在角点信息丢失和位置偏移等现象,而B样条函数可以收敛于高斯函数,并具有良好的逼近能力和紧支性等一些优秀的性质,从而基于B样条函数提出了一种改进的Harris角点提取方法。实验表明,该方法对提取角点非常有效。

基于局部方向分布的角点检测及亚像素定位

提出了一种基于局部方向分布的角点检测与定位算法.该算法主要由两步组成,首先利用绝对角点能量和相对角点能量进行角点检测,然后使用最小二乘技术拟合支撑像素方向线的交点得到角点的亚像素位置.实验结果表明,相对于常见的角点检测算法,基于局部方向分布的算法不仅具有更高的定位精度,同时对噪音也有较强的鲁棒性.