“Words”and“Meaning”in the Horizon of Philosophical Hermeneutics

The article holds that the problem of the relationship between"words"and"meaning"has always been the philosophical proposition.Through analyzing the relationship between"words"and"meaning"and probing into"disoourse","text"and"space-time history",the author thinks that the interpreters'preconceptions,preexistence,pre-structure and different perspectives have resulted in diverse forms of interpretations,and the being of each kind of form has its own rationality.Moreover,the process in which the interpreters interpret"words","discourse","text"and"history"is also the process to interpret themselves.Nevertheless,being able to say and being unable to say are soaked in the whole process of interpretation,and,as a result,human beings will always be confronted with a kind of"say and cannot say"embarrassment.

Sentiment Analysis Using E-Commerce Review Keyword-Generated Image with a Hybrid Machine Learning-Based Model

In the context of the accelerated pace of daily life and the development of e-commerce,online shopping is a mainstreamway for consumers to access products and services.To understand their emotional expressions in facing different shopping experience scenarios,this paper presents a sentiment analysis method that combines the ecommerce reviewkeyword-generated imagewith a hybrid machine learning-basedmodel,inwhich theWord2Vec-TextRank is used to extract keywords that act as the inputs for generating the related images by generative Artificial Intelligence(AI).Subsequently,a hybrid Convolutional Neural Network and Support Vector Machine(CNNSVM)model is applied for sentiment classification of those keyword-generated images.For method validation,the data randomly comprised of 5000 reviews from Amazon have been analyzed.With superior keyword extraction capability,the proposedmethod achieves impressive results on sentiment classification with a remarkable accuracy of up to 97.13%.Such performance demonstrates its advantages by using the text-to-image approach,providing a unique perspective for sentiment analysis in the e-commerce review data compared to the existing works.Thus,the proposed method enhances the reliability and insights of customer feedback surveys,which would also establish a novel direction in similar cases,such as social media monitoring and market trend research.

Target acquisition performance in the presence of JPEG image compression

This paper presents an investigation on the effect of JPEG compression on the similarity between the target image and the background,where the similarity is further used to determine the degree of clutter in the image.Four new clutter metrics based on image quality assessment are introduced,among which the Haar wavelet-based perceptual similarity index,known as HaarPSI,provides the best target acquisition prediction results.It is shown that the similarity between the target and the background at the boundary between visually lossless and visually lossy compression does not change significantly compared to the case when an uncompressed image is used.In future work,through subjective tests,it is necessary to check whether this presence of compression at the threshold of just noticeable differences will affect the human target acquisition performance.Similarity values are compared with the results of subjective tests of the well-known target Search_2 database,where the degree of agreement between objective and subjective scores,measured through linear correlation,reached a value of 90%.

A Brief Analysis of Ambiguity of Words' Meaning in Translation

As you can see from the title,we try to provide a brief analysis of ambiguity of words' meaning in translation practice,namely,what is ambiguity of a meaning of a word and how it is caused,and how it affects translation.What effective methods are available to help us achieve a successful translation? Although a perfect solution for the problems presented by the ambiguity of words' meaning is difficult to find,we try to do what it can to contribute to the solution and draw people's attention to those problems.

On How to Guess Meanings of Unknown Words in Reading Materials the Importance of Context

While reading plays a very important role in English study, many English language learners find it very difficult to fully comprehend some reading materials on account of many unknown words in them. This essay mainly discusses one technique of guessing meanings of new words according to context clues, thus emphasizing the importance of context.

Enhanced Image Captioning Using Features Concatenation and Efficient Pre-Trained Word Embedding

One of the issues in Computer Vision is the automatic development of descriptions for images,sometimes known as image captioning.Deep Learning techniques have made significant progress in this area.The typical architecture of image captioning systems consists mainly of an image feature extractor subsystem followed by a caption generation lingual subsystem.This paper aims to find optimized models for these two subsystems.For the image feature extraction subsystem,the research tested eight different concatenations of pairs of vision models to get among them the most expressive extracted feature vector of the image.For the caption generation lingual subsystem,this paper tested three different pre-trained language embedding models:Glove(Global Vectors for Word Representation),BERT(Bidirectional Encoder Representations from Transformers),and TaCL(Token-aware Contrastive Learning),to select from them the most accurate pre-trained language embedding model.Our experiments showed that building an image captioning system that uses a concatenation of the two Transformer based models SWIN(Shiftedwindow)and PVT(PyramidVision Transformer)as an image feature extractor,combined with the TaCL language embedding model is the best result among the other combinations.

Cultural Image of Animal Words

This paper,after introducing the definition and forms of cultural image,focuses on the detailed comparison and analysis of cultural image of animal words both in English and in Chinese from four aspects,that is,same animal word,same cultural image;same animal word,different cultural images;different animal words,same cultural image;different animal words,different cultural images.

The Meaning of Words Depends on the Context

This paper starts with stating the importance of context in understanding the meaning of words through the aspects as extra linguistic and linguistic context,which is followed by the analysis of the function of context in defferent time, place, situation and to different people. The purpose is to try and present the actual use of context in our daily life and enhance our awareness of the importance of the role of context.

The Special Meaning of Color Words in Chinese and Western Culture

In Chinese and western culture,color words are both as many as the sands in the Ganges river and stars in the blue sky.And its meanings have something in common and also something that is different.To find out the same points and differentias and to avoid mistakes in intercommunication,the writer will analysis the meanings of some main color words and makes an explain for the differences from the aspect of culture between Chinese and western countries by the means of comparison and analysis.After the analysis,the writer discovers that the meanings of the colors are basically different except the purple,and which are deeply affected by their each culture.And the meanings of them would change in the situation of intercommunication.Therefore,we should use these words properly.

Some Symbolic Meanings of Color Words in Chinese and English Cultures

In Chinese and English languages, there are very abundant words that can describe different colors. Not only should we pay attention to their basic meanings, but also should pay attention to their profound symbolic meanings. Because the symbolic meanings of color words often have different characteristics in different national languages, some characteristics even form people to the advocating and taboo to the colors after being guided, stretched and transferred by people. The big difference of the symbolic meanings of color between different cultures is due to the different nations, different cultures, different historical backgrounds, and different aesthetic psychologies. It is sanctified by usage in the sediment of history and the development of society. It is a kind of enduring culture phenomenon. From the angle of comparison between Chinese and English cultures, this essay attempts to probe into the development of different cultures has the impact on symbolic meanings of color words.

A Study of the Negative Influence of English Loan Words from Chinese Origin on the Image of Chinese People——Taking “Tuhao”“Dama” and “Guanxi” for examples

With the increasing Chinese influence on the international language English, words like "tuhao" and "dama" have been included into the Oxford Dictionary. Some loan words from China have undermined the image of Chinese people. This paper, by taking"tuhao","dama"and"guanxi"for examples, analyzes the impact of these new loan words in English on the image of Chinese people. The result shows these words have negative influence on the image of Chinese people. Therefore, countermeasures should be taken to strengthen the spread of China's positive image.

The Mythological Battles Around the World The Images and Meanings of International Dragon-Slayers

Dragons and dragon slayers belong to a system ofsemiology.They are images with messages.Differentcultures in the world have assigned to these imageshistorical limits,conditions of use,and introducedmultiple meanings into them.Dragons do not exist,therefore dragon slayers do not either.However,they have become an artificial existence in most cul-tures,and this existence have passed from a closed,silent existence to an oral state,open to appropria-tion by society,for there is no regulation,either nat-ural or not,which forbids imagination.Few symbols saturate human civilization sobroadly and thoroughly as those of the dragon:proudly flicking its tail across the tapestries

A Discussion On the Range of Meaning of English Words──An Approach to English Words Learning

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基于主题词向量中心点的K-means文本聚类算法

K-means由于其时间复杂度低运行速度快一直是最为流行的聚类算法之一,但是该算法在进行聚类时需要预先给出聚类个数和初始类中心点,其选取得合适与否会直接影响最终聚类效果。该文对初始类中心和迭代类中心的选取进行大量研究,根据决策图进行初始类中心的选择,利用每个类簇的主题词向量替代均值作为迭代类中心。实验表明,该文的初始点选取方法能够准确地选取初始点,且利用主题词向量作为迭代类中心能够很好地避免噪声点和噪声特征的影响,很大程度上地提高了K-means算法的性能。

基于改进K-means与机器视觉的档案数据分析技术

为了提升医疗信息系统对健康档案数据的分析效率,文中采用图像采集、降噪、配准与差分等技术提取医疗图像信息,进而有效提升信息系统的数据采集效率。同时还对传统的K-means算法加以改进,并提出了一种基于类间、类内距离的聚类初始化评价指标体系(BWP),将其应用于采集到的档案数据中,以实现快速的聚类分析。将所提算法在CUDA计算平台上进行了实现,测试结果表明,该方法的聚类精度和运行效率较现有算法均有显著提升。此外,改进后K-means算法的正确聚类样本数量占比提升了4.88%,高于现有的主流指标体系,且当聚类数k的取值为16或32时,运行时间大幅降低。

结合Lee滤波的NL-Means声呐图像滤波方法

声呐图像中存在的散斑噪声不仅极大地影响了图像质量,还对图像的后续分割、增强、边缘检测等增加了很多负面影响.针对这一问题,提出了结合Lee滤波的NL-Means算法:先用Lee滤波算法对声呐图像进行一次滤波,再用滤波后的图像计算NL-Means算法中的权重部分的权值,最后用NL-Means算法结合该权重进行滤波.改进的滤波方法避免了权重计算过程中由于噪声的影响而使导致权重偏小的问题,精确了NL-Means算法中的权重分配.实验证明,改进方法对声呐图像的散斑噪声不仅有更好的抑制效果,还提升了图像的质量.

Segmentation of High Spatial Resolution Remote Sensing Images of Mountainous Areas Based on the Improved Mean Shift Algorithm

Using conventional Mean Shift Algorithm to segment high spatial resolution Remote sensing images of mountainous areas usually leads to an unsatisfactory result, due to its rich texture information. In this paper, we propose an improved Mean Shift Algorithm in consideration of the characteristics of these images. First, images were classified into several homogeneous color regions and texture regions by conducting variance detection on the color space. Next, each homogeneous color region was directly segmented to generate the preliminary results by applying the Mean Shift Algorithm. For each texture region, we conduct a high-dimensional feature space by extracting information such as color, texture and shape comprehensively, and work out a proper bandwidth according to the normalized distribution density. Then the bandwidth variable Mean Shift Algorithm was applied to obtain segmentation results by conducting the pattern classification in feature space. Last, the final results were obtained by merging these regions by means of the constructed cost functions and removing the oversegmented regions from the merged regions. It has been experimentally segmented on the high spatial resolution remote sensing images collected by Quickbird and Unmanned Aerial Vehicle(UAV). We put forward an approach to evaluate the segmentation results by using the segmentation matching index(SMI). This takes into consideration both the area and the spectrum. The experimental results suggest that the improved Mean Shift Algorithm outperforms the conventional one in terms of accuracy of segmentation.

Improved Non-Local Means Algorithm for Image Denoising

Image denoising technology is one of the forelands in the field of computer graphic and computer vision. Non-local means method is one of the great performing methods which arouse tremendous research. In this paper, an improved weighted non-local means algorithm for image denoising is proposed. The non-local means denoising method replaces each pixel by the weighted average of pixels with the surrounding neighborhoods. The proposed method evaluates on testing images with various levels noise. Experimental results show that the algorithm improves the denoising performance.

Improved Weight Function for Nonlocal Means Image Denoising

The nonlocal means( NLM) has been widely used in image processing. In this paper,we introduce a modified weight function for NLM denoising, which will compute the nonlocal similarities among the pre-processing pixel patches instead of the commonly used similarity measure based on noisy observations. By the law of large number,the norm for the pre-processing pixel patches is closer to the norm of the original clean pixel patches,so the proposed weight functions are more optimized and the selected similar patches are more accurate. Experimental results indicate the proposed algorithm achieves better restored results compared to the classical NLM's method.

Color image segmentation using mean shift and improved ant clustering

To improve the segmentation quality and efficiency of color image,a novel approach which combines the advantages of the mean shift(MS) segmentation and improved ant clustering method is proposed.The regions which can preserve the discontinuity characteristics of an image are segmented by MS algorithm,and then they are represented by a graph in which every region is represented by a node.In order to solve the graph partition problem,an improved ant clustering algorithm,called similarity carrying ant model(SCAM-ant),is proposed,in which a new similarity calculation method is given.Using SCAM-ant,the maximum number of items that each ant can carry will increase,the clustering time will be effectively reduced,and globally optimized clustering can also be realized.Because the graph is not based on the pixels of original image but on the segmentation result of MS algorithm,the computational complexity is greatly reduced.Experiments show that the proposed method can realize color image segmentation efficiently,and compared with the conventional methods based on the image pixels,it improves the image segmentation quality and the anti-interference ability.