德语“手”字熟语的认知转喻解读

传统观点认为,有些熟语是无理据的固定搭配。认知语言学则认为,作为语言系统的重要组成部分,熟语是人类认知活动的产物,因而其意义存在一定的理据。基于认知转喻的德语"手"字熟语研究表明,德语熟语的理据可以通过人类的认知模式获得识解。

从“手形”字族浅析汉字部件探源教学

本文以“手形”字族为例,浅析部件探源教学对具有象形性、写意性特点的汉字的教学启示,以帮助留学生有效提高学习汉字的能力,加强对中国传统文化的掌握。强调汉字探源教学对减少汉字书写偏误有一定作用,也可为汉字教学实践提供参考。

含有“手”字的成语

形容不够节约，随便浪费财物——大手大脚。 形容重归于好——握手言和（欢）。 形容做事有把握，毫不费力——手到擒来。 形容聪明能干——心灵手巧。 形容熟练——得心应手。

《龙龛手镜》所收切身字对译梵音考

切身字为梵汉对音时所造的译音专用字,其对于汉字学和音韵学研究具有重要价值。《龙龛手镜》集中收录了部分切身字。本文利用《大正新修大藏经》及《新编大藏全咒》等考释出18个切身字所对译的梵文音节。

浅析日语“手”的构词法及意义

日语中由「手」字构成的「熟語」的数量很多.说「手」字是日语汉字中构词能力极强的一个汉字大概不算言过.「手」字和各种不同词性的词结合构成「熟語」后,有的仍保留着「手」字的词义;有的丝毫没有「手」字的词义.「手」在「熟語」中有时占主要地位,而有时在「熟語」中只起辅助作用.

Wavelet transform and gradient direction based feature extraction method for off-line handwritten Tibetan letter recognition

To improve the recognition accuracy of off-line handwritten Tibetan characters the local gradient direction histograms based on the wavelet transform are proposed as the recognition features.First for a Tibetan character sample image the first level approximation component of the Haar wavelet transform is calculated.Secondly the approximation component is partitioned into several equal-sized zones. Finally the gradient direction histograms of each zone are calculated and the local direction histograms of the approximation component are considered as the features of the character sample image.The proposed method is tested on the recently developed off-line Tibetan handwritten character sample database.The experimental results demonstrate the effectiveness and efficiency of the proposed feature extraction method.Furthermore compared with the detail components the approximation component contributes more to the recognition accuracy.

浑身太极——学习陈鑫《太极拳推原解》

阅读陈鑫文章，确实要下一番功夫。就说此篇文章，很多人对该文的标题就不理解，有的人以为排印时丢了一个“手”字，应为“太极拳推手原解”。其实错矣，原文就是如此。

浑身太极——学习陈鑫《太极拳推原解》

阅读陈鑫文章,确实要下一番工夫。就说此篇文章,很多人对该文的标题就不理解,有的人以为排印时丢了一个“手”字,为“太极拳推手原解”。其实错矣,原文就是如此。“太极拳“不用解释,“推原解”怎么讲？是“太极拳推、原解”,还是“太极拳推原,解”？而这个“推”又是啥意思？

Kernel principal component analysis network for image classification

In order to classify nonlinear features with a linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network（ KPCANet） is proposed. First, the data is mapped into a higher-dimensional space with kernel principal component analysis to make the data linearly separable. Then a two-layer KPCANet is built to obtain the principal components of the image. Finally, the principal components are classified with a linear classifier. Experimental results showthat the proposed KPCANet is effective in face recognition, object recognition and handwritten digit recognition. It also outperforms principal component analysis network（ PCANet） generally. Besides, KPCANet is invariant to illumination and stable to occlusion and slight deformation.

AN ADAPTIVELY TRAINED KERNEL-BASED NONLINEAR REPRESENTOR FOR HANDWRITTEN DIGIT CLASSIFICATION

In practice, retraining a trained classifier is necessary when novel data become available. This paper adopts an incremental learning procedure to adaptively train a Kernel-based Nonlinear Representor (KNR), a recently presented nonlinear classifier for optimal pattern representation, so that its generalization ability may be evaluated in time-variant situation and a sparser representation is obtained for computationally intensive tasks. The addressed techniques are applied to handwritten digit classification to illustrate the feasibility for pattern recognition.

OBLIQUE PROJECTION REALIZATION OF A KERNEL-BASED NONLINEAR DISCRIMINATOR

Previously, a novel classifier called Kernel-based Nonlinear Discriminator (KND) was proposed to discriminate a pattern class from other classes by minimizing mean effect of the latter. To consider the effect of the target class, this paper introduces an oblique projection algorithm to determine the coefficients of a KND so that it is extended to a new version called extended KND (eKND). In eKND construction, the desired output vector of the target class is obliquely projected onto the relevant subspace along the subspace related to other classes. In addition, a simple technique is proposed to calculate the associated oblique projection operator. Experimental results on handwritten digit recognition show that the algorithm performes better than a KND classifier and some other commonly used classifiers.

An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration

This paper presents a methodology for off-line handwritten Chinese character recognition based on mergence of consecutive segments of adaptive duration. The handwritten Chinese character string is partitioned into a sequence of consecutive segments, which are combined to implement dissimilarity evaluation within a sliding window whose durations are determined adaptively by the integration of shapes and context of evaluations. The average stroke width is estimated for the handwritten Chinese character string, and a set of candidate character segmentation boundaries is found by using the integration of pixel and stroke features. The final decisions on segmentation and recognition are made under minimal arithmetical mean dissimilarities. Experiments proved that the proposed approach of adaptive duration outperforms the method of fixed duration, and is very effective for the recognition of overlapped, broken, touched, loosely configured Chinese characters.

Principles of the roof cut short-arm beam mining method (110 method) and its mining-induced stress distribution

Since the 1960 s, mining science and technology in China has experienced two technical innovations, i.e.the ‘‘Masonry Beam Theory(MBT)" and ‘‘Transfer Rock Beam Theory(TRBT)". Based on those theories, the conventional mining method(being called the 121 mining method) was established, consisting of excavating two tunnels with a pillar left for mining a working panel. However, with increasing mining depth,engineering geological disasters in the underground caverns have been frequently encountered. In addition, the use of the coal-pillar mining results in a large amount of coal resources unexploited. In order to address the problems above, the ‘‘Roof Cut Short-Arm Beam Theory(RCSBT), being called the 110 mining method)" was proposed by He Manchao in 2008. The 110 mining method features the mining of one coal seam panel, excavating necessarily only one roadway tunnel and leaving no pillars. Realization of the 110 mining method includes the following steps:(1) directional pre-splitting roof cutting,(2) supporting the roof by using high Constant Resistance Large Deformation bolt/cable(CRLD), and(3) blocking gangue by hydraulic props. This paper presents an overview of the principles, techniques and application of the 110 mining method. Special emphasis is placed on the numerical simulation of the geostress distribution found in the mining panel using the 110 method compared to that of the 121 method. In addition, the stress distribution on the ‘‘short beam" left by the roof cutting when performing the 110 method was also investigated using both numerical simulation and theoretical formulation.

Offline Handwritten Characters Recognition Using Moments Features and Neural Networks

In this paper we revise the moment theory for pattern recognition designed, to extract patterns from the noisy character datas, and develop unconstrained handwritten. Amazigh character recognition method based upon orthogonal moments and neural networks classifier. We argue that, given the natural flexibility of neural network models and the extent of parallel processing that they allow, our algorithm is a step forward in character recognition. More importantly, following the approach proposed, we apply our system to two different databases, to examine the ability to recognize patterns under noise. We discover overwhelming support for different style of writing. Moreover, this basic conclusion appears to remain valid across different levels of smoothing and insensitive to the nuances of character patterns. Experiments tested the effect of set size on recognition accuracy which can reach 97.46%. The novelty of the proposed method is independence of size, slant, orientation, and translation. The performance of the proposed method is experimentally evaluated and the promising results and findings are presented. Our method is compared to K-NN （k-nearest neighbors） classifier algorithm; results show performances of our method.

New Media and the Changes in the Communication Paradigm

With the emergence of the new digital platforms, a diversified number of approaches and providers cannot damage too much a rather crowded info sphere. What may come as a general challenge is the ＂performance＂ amateurs who have the devices, the will but not the skills to become reliable communicators. Good training and an expanded concern for the accuracy of messages should distinguish between fact and fiction, and between information and opinion. The smart phone, the iPod, the lap top, or the tablet has expanded the means of communication. They have also diversified the types of messages circulated. The traditional main stream media outlets are facing a mounting competition from the social networks populated with the folk journalists, albeit, and non-professionals. Basic training of all those willing to come into the communication ring and regulations may concern not only the professionals but also the amateurs, and it may be ways to get over what seems to be a deadlock.

New Changes of Mobile Banking Industry and Mobile Terminal-Bank Account Problem Solving Model in the Digital Era

In the digital era, the mobile-empowered customers have new power in the palms of their hands, which means that their shoppingand buying behaviors are being totally transformed by the ability to buy anything at any time from any place. Bank account is the base camp ofmoney in economic activity, therefore who wins the mobile terminal who embraces bank accounts, who embraces bank accounts who achievesthe world, for the winner can master customer resource and business foundation. This passage focuses on the issue that how to create bankaccounts on mobile terminal for mobile banking industry in the digital era, introduced the developing background of mobile banking industry,analyzed the main challenges mobile banking industry faces, and finally concluded a workable mobile terminal-bank account problem solvingmodel from strategy level, technical level and marketing level.

CLINICAL OBSERVATION ON ACUPOINT DIGITAL PRESSING FOR TREATING IRRITABLE SYMPTOMS AND SIGNS OF POSTOPERATION OF MYOPORTHOSIS

Objective: To explore a new effective approach for treatment of the local irritable symptoms and signs resulted from myoporthosis operation. Methods: 263 cases of radial keratotomy outpatients were divided into control group (n=49, 90 eyes) and treatment group (n=214, 412 eyes). Patients of control group were treated with 0.5% Chloramphenicol eye drops, 3 times daily, 1-2 drops/time, and with 0.5% Erythromycine eye ointment every night. In treatment group, patients were treated with acupoint and hand reflection area digital pressing method except with the same eye drops and eye ointment. Body acupoints used were Cuanzhu (BL 2), Yuyao (EX HN 4), Sizhukong (TE 23), Sibai (ST 2) and Taiyang (EX HN 5). The hand reflex areas used were Eye Area, Liver Area, Kidney Area, Spleen Area, Heart Area and Lung Area. Five days constituted a therapeutic course. Results: Following 3 courses (15 days) of treatment, the markedly effective rate and total effective rate of treatment group and control group were 74.51% and 38.89%, 94.17% and 66.67% respectively. There was a significant difference between two groups in the total effective rate (P<0.05), showing the therapeutic effect of treatment group being better than that of control group. Conclusion: Acupoint digital pressing is rather effective in treatment of myoporthosis post operation irritable symptoms and signs.

Research on Recognition Method of Handwritten Numerals Segmentation based on B-P Neural Network

We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary, image of zip code box and message of the two characters binary image： analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements.

Research on Recognition Method of Handwritten Numerals Segmentation based on B-P Neural Network

We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characters binary image; analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements.