On Translation of Long Sentences Based on the Novel-Of Time and the River

Of Time and the River is a famous novel written by American novelist–Thomas Wolfe who was a major American novelist of the early 20th century.His books are well received among Chinese readers.In the novel—Of Time and the River,we can find Wolfe’s frequent use of long sentences.In this paper,the skills of translating long sentences and the ways of analyzing sentence structures are discussed by several examples selected from the novel.Based on my own translation,we can find the importance of sentence structure analysis in translating long sentences.

A Study on the Focuses and Fronts of International Second Language Acquisition Researches -Statistical Analysis of the Articles Published in Language Learning(2012-2016)

Keywords word frequency and co-word analysis are adopted in an attempt to to investigate the focuses and fronts of inter-national second language acquisition(SLA) researches by analyzing the key words in articles published in the internationally re-nowned SLA academic journal Language Learning from 2012 to 2016. It is found that the best researched topics in SLA are vocabu-lary acquisition, explicit knowledge, form-focused teaching, language use, and so on, among which learner's language attracts themost attention. In terms of research methods, they become more diversified and interdisciplinary, as empirical studies take a domi-nant position and experiments still play a leading role, displaying an interdisciplinary feature.

The Comparison of Two Chinese Versions(CUV and TCV) of Bible from the Perspective of Skopos Theory

Bible has a lot of Chinese versions, among which The Chinese Union Version(CUV) and Today's Chinese Version(TCV) are most popular. The skopos of CUV is for Chinese Christians while the skopos of TCV is not just for Chinese Christians but also for the non-believers. Different target readers decide different skopos of translation. The comparison of CUV and TCV of this essay will focus on the word choices and sentence patterns to illustrate the point. Concerning the word choice, CUV uses a lot of classical words that are hard for readers today to understand. As to the sentence pattern, CUV version is generally literal translation to be loyal to God. On the contrary, because of different skopos, TCV version is very free translation. We can not deny the fact that TCV using free translation is under the influence of Nida whose dynamic equivalence is influential during the1970s especially in the Bible translation. However, from the prospective of Vermeer's theory, the prime skopos of TCV is to help non-believers understand and be willing to read Bible. Strange sentences and vague meanings will prevent them from go on reading it. Since I am also a Christian, at the end of the essay I will illustrate the limitation of both versions from a Christian's perspective.

A study of clinical psychological nursing research hotspots in China and variation trends based on word frequency analysis and visualization analysis

Objective: To analyze clinical psychological nursing research hotspots in China and variation trends in order to provide reference points on the current state of development of clinical psychological nursing and future research hotspots.Method: Clinical psychological nursing research literature sourced from Wanfang Data for the three periods of 2007-2009, 2010-2012, and 2013-2015 were selected as the research sample. A bibliographic co-occurrence analysis system(BICOMB software) was used to perform keyword word frequency analysis and generate a keyword co-occurrence matrix. In addition, Ucinet software's Netdraw tool was used to create visualized network diagrams.Results: A total of 27890 articles were retrieved, and word frequency analysis revealed that the highestfrequency keywords consisted of anxiety, depression, the elderly, expectant women, coronary heart disease, diabetes, breast cancer, perioperative period, quality of life, and psychological intervention.Research hotspot analysis revealed that consistent hotspots comprised anxiety, depression, health education, and perioperative period; expectant women became a hotspot during 2010-2012, and quality of life and efficacy became hotspots during 2013-2015.Conclusions: In addition to the care process, clinical psychological nursing research hotspots in China have increasingly included the effectiveness of psychological nursing and impact on patient quality of life. In addition, research hotspots have been influenced by the incidence of illnesses and people's health consciousness.

Next Words Prediction and Sentence Completion in Bangla Language Using GRU-Based RNN on N-Gram Language Model

We use a lot of devices in our daily life to communicate with others. In this modern world, people use email, Facebook, Twitter, and many other social network sites for exchanging information. People lose their valuable time misspelling and retyping, and some people are not happy to type large sentences because they face unnecessary words or grammatical issues. So, for this reason, word predictive systems help to exchange textual information more quickly, easier, and comfortably for all people. These systems predict the next most probable words and give users to choose of the needed word from these suggested words. Word prediction can help the writer by predicting the next word and helping complete the sentence correctly. This research aims to forecast the most suitable next word to complete a sentence for any given context. In this research, we have worked on the Bangla language. We have presented a process that can expect the next maximum probable and proper words and suggest a complete sentence using predicted words. In this research, GRU-based RNN has been used on the N-gram dataset to develop the proposed model. We collected a large dataset using multiple sources in the Bangla language and also compared it to the other approaches that have been used such as LSTM, and Naive Bayes. But this suggested approach provides excellent exactness than others. Here, the Unigram model provides 88.22%, Bi-gram model is 99.24%, Tri-gram model is 97.69%, and 4-gram and 5-gram models provide 99.43% and 99.78% on average accurateness. We think that our proposed method profound impression on Bangla search engines.

Aspect-Based Sentiment Classification Using Deep Learning and Hybrid of Word Embedding and Contextual Position

Aspect-based sentiment analysis aims to detect and classify the sentiment polarities as negative,positive,or neutral while associating them with their identified aspects from the corresponding context.In this regard,prior methodologies widely utilize either word embedding or tree-based rep-resentations.Meanwhile,the separate use of those deep features such as word embedding and tree-based dependencies has become a significant cause of information loss.Generally,word embedding preserves the syntactic and semantic relations between a couple of terms lying in a sentence.Besides,the tree-based structure conserves the grammatical and logical dependencies of context.In addition,the sentence-oriented word position describes a critical factor that influences the contextual information of a targeted sentence.Therefore,knowledge of the position-oriented information of words in a sentence has been considered significant.In this study,we propose to use word embedding,tree-based representation,and contextual position information in combination to evaluate whether their combination will improve the result’s effectiveness or not.In the meantime,their joint utilization enhances the accurate identification and extraction of targeted aspect terms,which also influences their classification process.In this research paper,we propose a method named Attention Based Multi-Channel Convolutional Neural Net-work(Att-MC-CNN)that jointly utilizes these three deep features such as word embedding with tree-based structure and contextual position informa-tion.These three parameters deliver to Multi-Channel Convolutional Neural Network(MC-CNN)that identifies and extracts the potential terms and classifies their polarities.In addition,these terms have been further filtered with the attention mechanism,which determines the most significant words.The empirical analysis proves the proposed approach’s effectiveness compared to existing techniques when evaluated on standard datasets.The experimental results represent our approach outperforms in the F1 measure with an overall achievement of 94%in identifying aspects and 92%in the task of sentiment classification.

Markedness and UG in Chinese Children's Acquisition of One-word and Negative Sentences

Thepresentstudyisaninvestigationandanalysisoftherelationshipbetweenmarkednessandfirstlanguageacquisitionsequence,asshowninthecasesofone-wordandnegativesentences.Hereourobjectivesaretoargueforthepriorityofunmarkednessovermarkednessintheacquisitionsequ...

Mapping theme trends and knowledge structures for human neural stem cells:a quantitative and co-word biclustering analysis for the 2013-2018 period

Neural stem cells,which are capable of multi-potential differentiation and self-renewal,have recently been shown to have clinical potential for repairing central nervous system tissue damage.However,the theme trends and knowledge structures for human neural stem cells have not yet been studied bibliometrically.In this study,we retrieved 2742 articles from the PubMed database from 2013 to 2018 using "Neural Stem Cells" as the retrieval word.Co-word analysis was conducted to statistically quantify the characteristics and popular themes of human neural stem cell-related studies.Bibliographic data matrices were generated with the Bibliographic Item Co-Occurrence Matrix Builder.We identified 78 high-frequency Medical Subject Heading(MeSH)terms.A visual matrix was built with the repeated bisection method in gCLUTO software.A social network analysis network was generated with Ucinet 6.0 software and GraphPad Prism 5 software.The analyses demonstrated that in the 6-year period,hot topics were clustered into five categories.As suggested by the constructed strategic diagram,studies related to cytology and physiology were well-developed,whereas those related to neural stem cell applications,tissue engineering,metabolism and cell signaling,and neural stem cell pathology and virology remained immature.Neural stem cell therapy for stroke and Parkinson’s disease,the genetics of microRNAs and brain neoplasms,as well as neuroprotective agents,Zika virus,Notch receptor,neural crest and embryonic stem cells were identified as emerging hot spots.These undeveloped themes and popular topics are potential points of focus for new studies on human neural stem cells.

NUMERICAL ANALYSIS OF THREE-DIMENSIONAL FLUID FLOW AND HEAT TRANSFER IN TIG WELD POOL WITH FULL PENETRATION WU Chuansong,CAO Zhenning,WU Lin Harbin Institute of Technology,Harbin,China

A model is established to analyze three-dimensional fluid flow and heat transfer in TICweld pools with full penetration.It considers the deformation of the molten pool surfaceat the condition of full penetrated workpieees,takes the are pressure as the drivingforce of the pool surface deformation,and determines the surface configuration of weldpool based on the dynamic balance of arc pressure,pool gravity and surface tension atdeformed weld pool surface. The SIMPLER algorithm is used to calculate the fluid flowfield and temperature distribution in TIG weld pools of stainless steel workpieces.TIGwelding experiments are made to verify the validity of the model.It shows the calculatedresults by the model are in good agreement with experimental measurements. professor,Dept of Welding Engineering,Harbin Institute of Technology,Harbin 150006,China

The Response Time Analysis of Digital Broadcasting System

Digital broadcasting system has become a high-light of research on computer application. To respond to the changes of the playbill in the broadcasting system in real time, the response time of the system must be studied. There is scarcely the research on this area currently. The influence factors in the response time are analyzed; the model on the response time of the system service is built; how the influence factors affect the response time of the system service is validated; and four improvement measures are proposed to minimize the response time of system service.

Cloning and Sequence Analysis of a Cysteine Proteinase Inhibitor Gene from Seedless Litchi

[Objective] This study aimed to clone and analyze the cysteine proteinase inhibitor gene from seedless litchi. [Method] According to the EST se- quence of cysteine proteinase inhibitor in constructed SSH snhtraetive library of seedless litchi abortion, nucleotide sequence of the cysteine proteinase inhibitor gene was obtained by using RACE technology and analyzed by using bioinformatics software. [ Result ] A cysteine protease inhibitor gene was obtained with the sequence of 635 bp containing a 321 bp open reading frame. It was predicted that the erlcoded protein contained 106 amino acids with conserved domain of cysteine proteinase inhibitor and had relatively high homology with the cysteine proteinase inhibitor gene of several species, [ Conclusion] This study laid the foundation for further ex- ploring the physiological functions of this cysteine proteinase inhibitor gene in plants.

A New Approach of Time Series Variation Based on Power Links and Field Association Words

This paper has proposed a new methodology extracting stability classes of field association words depending on automatically power link analysis to enhance the precision of decision tree. In this paper, we have studied the effects of the time variation based on the frequencies of specific words called field association words that connected to documents using power link in a specific period. The stability classes have referred to the popularity of field association words based on the change of time in a given period. The new approach has evaluated by conducting experiments simulating results of 1575 files (about 5.16 MB). Based on these experiments, it has turned out that, the F-measure for ascending, stable and descending classes have achieved 93.6%, 99.8% and 75.7%, respectively. These results mean that F-measure was increasing by 12%, 4% and 34% than traditional methods because of the power link analysis.

The hot issues of studies in China on digital information resources: Based on co-word analysis

With the SPSS and the help of factor method and hierarchical clustered method,journal articles on digital information resources(DIR) from CNKI in the past ten years are analyzed with a co-word analytical method in this paper. The hot issues of studies on DIR and the relationship between those subjects are analyzed in this investigation as well.

Understand the Customer Preference of Different Market Segments from Online Word of Mouth: Evidence from the China Auto Industry

With the explosive growth of social media, manufacturers and marketers are increasingly using public opinions in social media for their business decision making. This article aims to understand the customer preference of different market segments from online word of mouth. Using the real data collected from the leading online community of China auto and the ordered Logit model, we find that from the viewpoint of car types, the price is the most important factor for the customer satisfaction. However, from the viewpoint of price range, the price is no more the most important factor for the customer satisfaction. From both viewpoints, the results are similar that different car attributes have different weights on satisfaction. Our findings will make the car manufacturers and marketers come away with a more detailed understanding of the mindset of Chinese consumer groups, and keep a competitive advantage in the fierce China auto market.

Research status and hotspots of economic evaluation in nursing by co-word clustering analysis

Objective:The aim of this study is to discover research status and hotspots of economic evaluation(EE)in nursing area using co-word cluster analysis.Methods:Medical Subject Heading(MeSH)term“cost–benefit analysis”was searched in PubMed and nursing journals were limited by the function of filter.The information of author,country,year,journal,and keywords of collected paper was extracted and exported to Bicomb 2.0 system,where high-frequency terms and other data could be further mined.SPSS 19.0 was used for cluster analysis to generate dendrogram.Results:In all,3,020 articles were found and 10,573 MeSH terms were detected;among them,1,909 were MeSH major topics and generated 42 high-frequency terms.The consequence of dendrogram showed seven clusters,representing seven research hotspots:skin administration,infection prevention,education program,nurse education and management,EE research,neoplasm patient,and extension of nurse function.Conclusions:Nursing EE research involved multiple aspects in nursing area,which is an important indicator for decision-making.Although the number of papers is increasing,the quality of study is not promising.Therefore,further study may be required to detect nurses’knowledge of economic analysis method and their attitude to apply it into nursing research.More nursing economics course could carry out in nursing school or hospitals.

基于Bag-of-words和Hash编码的近似重复图像检测算法

针对近似重复图像检测的传统算法存在检测效率和准确率不够高的缺点,提出了基于Bag-of-words和哈希编码的近似重复图像检测算法。该算法首先利用Bag-of-words把一幅图像表示成一个500维的特征向量;然后,利用主成分分析(PCA)和尺度不变特征转换(SIFT)进行特征降维,并利用Hash编码技术对特征进行编码;最后,利用动态距离度量技术实现近似重复图像的检测。实验结果表明,利用该算法进行近似重复图像检测是完全可行的,在准确度和查全率之间做到了较好的平衡,查准率可达90%～95%,查全率可达70%～80%。

2011—2015年国际应用行为分析热点研究——以《Journal of Applied Behavior Analysis》为例

为了探究应用行为分析在国外的研究成果和动态,利用共词分析的原理对2011—2015年JABA刊文的关键词进行了分析,结果显示近五年国外应用行为分析研究热点有自闭症谱系障碍、功能分析、区别性强化、口语行为、进食障碍等。对这些热点进行分类,探讨了各领域所处的研究地位,最后提出我国学界不仅要加强应用行为分析在特殊儿童问题行为管理和干预中的运用,也要把它推广到其他领域。

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.