Aspect-Level Sentiment Analysis Based on Deep Learning

In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also greatly improve the performance of models.However,previous studies did not take into account the relationship between user feature extraction and contextual terms.To address this issue,we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method.To be specific,we design user comment feature extraction(UCFE)to distill salient features from users’historical comments and transform them into representative user feature vectors.Then,the aspect-sentence graph convolutional neural network(ASGCN)is used to incorporate innovative techniques for calculating adjacency matrices;meanwhile,ASGCN emphasizes capturing nuanced semantics within relationships among aspect words and syntactic dependency types.Afterward,three embedding methods are devised to embed the user feature vector into the ASGCN model.The empirical validations verify the effectiveness of these models,consistently surpassing conventional benchmarks and reaffirming the indispensable role of deep learning in advancing sentiment analysis methodologies.

Analysis of the Role of Syntactic Complexity in Students’ Reading Comprehension: A Teacher’s Perspective

This study examines the role of the syntactic complexity of the text in the reading comprehension skills of students.Utilizing the qualitative method of research,this paper used structured interview questions as the main data-gathering instruments.English language teachers from Coral na Munti National High School were selected as the respondents of the study.Finding of the study suggests that the syntactic complexity of the text affects the reading comprehension of the students.Students found it challenging to understand the message that the author conveyed if he or she used a large number of phrases and clauses in one sentence.Furthermore,the complex sentence syntactic structure was deemed the most challenging for students to understand.To overcome said challenges in comprehending text,various reading intervention programs were utilized by teachers.These interventions include focused or targeted instruction and the implementation of the Project Dear,suggested by the Department of Education.These programs were proven to help students improve their comprehension as well as their knowledge in syntactical structure of sentences.This study underscores the importance of selecting appropriate reading materials and implementing suitable reading intervention programs to enhance students’comprehension skills.

A Comparative Analysis of Syntactic Complexity in Applied Linguistics Abstracts Written by Chinese Novice Writers and Native English Advanced Writers

The rhetorical structure of abstracts has been a widely discussed topic, as it can greatly enhance the abstract writing skills of second-language writers. This study aims to provide guidance on the syntactic features that L2 learners can employ, as well as suggest which features they should focus on in English academic writing. To achieve this, all samples were analyzed for rhetorical moves using Hyland’s five-rhetorical move model. Additionally, all sentences were evaluated for syntactic complexity, considering measures such as global, clausal and phrasal complexity. The findings reveal that expert writers exhibit a more balanced use of syntactic complexity across moves, effectively fulfilling the rhetorical objectives of abstracts. On the other hand, MA students tend to rely excessively on embedded structures and dependent clauses in an attempt to increase complexity. The implications of these findings for academic writing research, pedagogy, and assessment are thoroughly discussed.

Aspect-Level Sentiment Analysis Incorporating Semantic and Syntactic Information

Aiming at the problem that existing models in aspect-level sentiment analysis cannot fully and effectively utilize sentence semantic and syntactic structure information, this paper proposes a graph neural network-based aspect-level sentiment classification model. Self-attention, aspectual word multi-head attention and dependent syntactic relations are fused and the node representations are enhanced with graph convolutional networks to enable the model to fully learn the global semantic and syntactic structural information of sentences. Experimental results show that the model performs well on three public benchmark datasets Rest14, Lap14, and Twitter, improving the accuracy of sentiment classification.

Drop weight impact analysis of GFRP tubes with hollow glass particle-filled matrix

Protecting occupants or payloads in crashes and blasts is of utmost importance in both moving and immobile structures.One way of achieving this is by using a sacrificial energy absorber.Composite tubes have been studied as potential energy absorbers due to their ability to fail progressively under axial compression.In this study,the energy absorption capability of these tubes is enhanced by adding hollow glass particles to the matrix.Drop-weight tests are performed on composite tubes,and a digital image correlation(DIC)-based technique is used to capture their load-displacement behaviour.This eliminates the use of electronic data acquisition systems,load cells,and accelerometers.The load-displacement curves of the tubes are obtained from the DIC-based technique and examined to understand their crushing behaviour.Although the mean crush load shows a drop,an increase in crush length is noticed.The specific energy absorbed by the tubes improves with an increase in GMB volume fraction.The addition of 0.1,0.2,0.3 and 0.4 vol fractions of GMB results in the specific energy absorption increasing by6.6%,14.7%,24%and 36.6%,respectively,compared to neat glass fibre-epoxy tubes.Visual examination of the tubes and comparison with tubes subject to quasi-static compression is also performed.

科技英语翻译中的句法分析

科技英语作为独立文体，有它自身的词法和句法特征。科技英语词汇和术语往往在某一特定技术领域或专业内得以界定，在构词上有一定的专业脉络可循，每一专业几乎都有自己的词汇和术语系统，词法体现出较强的专业属性。科技英语的句法则带有一定的普遍性。不管何种专业，表...

Ambiguity in our daily language usage in both English and Chinese

Ambiguity is a unique linguistic feature and is caused by many factors. This paper first introduces the definitions of ambiguity and then mainly illustrates ambiguity in our daily language usage in both English and Chinese from phonetic level and syntactic level. People can learn the relationships among those levels and grasp the rule of learning language. Thus, people can realize the complexity and importance of using language and know that it is not easy to express ideas accurately.

Vague Language of Journalistic English in Syntactic Level

Vagueness is a natural character of language. Vagueness of journalistic English exists in lexical level and syntactic level as well. Lexical vagueness in journalistic English is usually resulted from the indefinite meaning of words, while in syntactic level, it may be resulted from the combined use of vague words or the employment of some sentence patterns. This thesis aims to help readers to understand journalistic English from the perspective of vague language.

Stylistic Characteristics of English Legal Texts

The characteristics of authority and standard in Legal English decide the significance of the translation about legal English texts. This thesis presents the stylistic features of legal English. It is hoped that translators would be able to understand legal English accurately.

Stylistic Features of Syntax in English Journal Blogs

Blog, a new genre of internet communication, has its own unique syntactic features. With Halliday's stylistic analytical pattern, the writer analyzed the samples from the perspectives of linguistic description to reveal the sentence patterns used in the journal blogs. The results show that blog language displays many of the properties of both spoken and written language.

Words for Fearful Symmetry:A Stylistic Analysis of The Tyger

It studies William Blake’s poem The Tyger on a basis of the theories of modern stylistics and discusses the meaning realization of the poem from the phonological features, the lexical and syntactic features, and the semantic features.

Oral Fossilization Phenomena of Vocational College Non-English Majors

This thesis sets out to classify the fossilized errors made by the subjects from lexical and syntactic levels respectively,through the empirical experiment and questionnaire.

Similarity measure of sedimentary successions and its application in inverse stratigraphic modeling

This paper presents a unique and formal method of quantifying the similarity or distance between sedimentary facies successions from measured sections in outcrop or drilled wells and demonstrates its first application in inverse stratigraphic modeling. A sedimentary facies succession is represented with a string of symbols, or facies codes in its natural vertical order, in which each symbol brings with it one attribute such as thickness for the facies. These strings are called attributed strings. A similarity measure is defined between the attributed strings based on a syntactic pattern-recognition technique. A dynamic programming algorithm is used to calculate the similarity. Inverse stratigraphic modeling aims to generate quantitative 3D facies models based on forward stratigraphic modeling that honors observed datasets. One of the key techniques in inverse stratigraphic modeling is how to quantify the similarity or distance between simulated and observed sedimentary facies successions at data locations in order for the forward model to condition the simulation results to the observed dataset such as measured sections or drilled wells. This quantification technique comparing sedimentary successions is demonstrated in the form of a cost function based on the defined distance in our inverse stratigraphic modeling implemented with forward modeling optimization.

L2 Syntactic Alignment in the Reading-Writing Integrated Continuation Task: Evidence From Chinese EFL Learners’ Description of Motion Events

This study investigated how the mode in which the reading-writing integrated continuation task was conducted modulates the effects of second language(L2) syntactic alignment, through the English motion event construction with manner verbs. Ninety Chinese students were assigned to either of the two experimental groups or a control group, and they all experienced a pretest, an alignment phase and a posttest. In the alignment phase, the two experimental groups completed a reading-writing integrated continuation task but in different modes. For the multi-turn mode,participants reconstructed a picture story by continuing the episodes extracted from the story with one episode presented and continued at a time;for the single-turn mode, the first half of the same picture story was presented as a chunk, and then participants read and continued it. Results show that L2 learners aligned with the target structure in completing the story, and the alignment effect was retained in the posttest conducted after a delay of two weeks. Moreover, syntactic alignment was modulated by task mode with the multi-turn group exhibiting stronger immediate and longterm alignment effects. We conclude that the continuation task is a fruitful context for L2 structural alignment, and the magnitude of alignment effect hinges on interactive intensity.

Stylistic Analysis of Whitman'S Poem O Captain!My Captain!

The poem O Captain! My Captain! is a good poem written by the great American poet, Walt Whitman. It is a eulogy written on the death of Abraham Lincoln. In this poem the poet expresses his sadness at the death of the great leader and expresses his great love of his beloved leader. This paper is to have a stylistic analysis of the poem by observing its phonological, lexical, semantic and syntactic features.

SUBDIVIDING VERBS TO IMPROVE SYNTACTIC PARSING

This paper proposes a new way to improve the performance of dependency parser: subdividing verbs according to their grammatical functions and integrating the information of verb subclasses into lexicalized parsing model. Firstly,the scheme of verb subdivision is described. Secondly,a maximum entropy model is presented to distinguish verb subclasses. Finally,a statistical parser is developed to evaluate the verb subdivision. Experimental results indicate that the use of verb subclasses has a good influence on parsing performance.

Improved head-driven statistical models for natural language parsing

Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other semantic information such as semantic collocation and semantic category. Some improvements on this distinctive parser are presented. Firstly, "valency" is an essential semantic feature of words. Once the valency of word is determined, the collocation of the word is clear, and the sentence structure can be directly derived. Thus, a syntactic parsing model combining valence structure with semantic dependency is purposed on the base of head-driven statistical syntactic parsing models. Secondly, semantic role labeling(SRL) is very necessary for deep natural language processing. An integrated parsing approach is proposed to integrate semantic parsing into the syntactic parsing process. Experiments are conducted for the refined statistical parser. The results show that 87.12% precision and 85.04% recall are obtained, and F measure is improved by 5.68% compared with the head-driven parsing model introduced by Collins.

Effects of sphere size on the microstructure and mechanical properties of ductile iron–steel hollow sphere syntactic foams

The effects of sphere size on the microstructural and mechanical properties of ductile iron–steel hollow sphere（DI–SHS） syntactic foams were investigated in this study. The SHSs were manufactured by fluidized-bed coating via the Fe-based commercial powder–binder suspension onto expanded polystyrene spheres（EPSs）. Afterwards, the DI–SHS syntactic foams were produced via a sand-mold casting process. The microstructures of specimens were investigated by optical microscopy, scanning electron microscopy（SEM）, and energy-dispersive X-ray spectroscopy（EDS）. The microscopic evaluations of specimens reveal distinct regions composed of the DI matrix, SHS shells, and compatible interface. As a result, the microstructures and graphite morphologies of the DI matrix depend on sphere size. When the sphere size decreases, the area fractions of cementite and graphite phases are observed to increase and decrease, respectively. Compression tests were subsequently conducted at ambient temperature on the DI–SHS syntactic foams. The results reveal that the compression behavior of the syntactic foams is enhanced with increasing sphere size. Furthermore, the compressed specimens demonstrate that microcracks start and grow from the interface region.

Effects of particle size,bimodality and heat treatment on mechanical properties of pumice reinforced aluminum syntactic foams produced by cold chamber die casting

In recent years,metal matrix syntactic foams(MMSFs)have become highly attractive owing to their unique physical,microstructural and mechanical features.Due to their promising potential for different industrial areas like automotive,aviation,and defense,these advanced engineering materials can also be evaluated as serious alternatives to particle reinforced metallic composites and conventional metallic foams.Differently from previously reported laboratory scaled techniques in the literature,this experimental effort focuses on the feasibility of MMSF manufacturing via a fully automated and industrial-based cold chamber die casting technique.Accordingly,1-2 mm,2-4 mm,and bimodal(50vol.%)natural-based pumice filled aluminum syntactic foams were manufactured utilizing a purpose-made casting machine.Physical,macroscopic,and microscopic examinations show that all of the fabricated samples display perfect matrix/filler harmony.Average density levels of fabricated syntactic foams range between 1.50 and 1.80 g·cm^(-3) depending upon the pumice particles size interval.To assess mechanical responses,quasi-static compression tests were performed.Furthermore,half of the foam samples were subjected to heat treatment to explore possible influences of aging on the compressive features and damage modes.Results indicate that although the heat treatment enhances the compressive strength,plateau stress,and energy absorption properties of the fabricated foams,it changes damage mode of the samples by causing brittle dominant deformation.

University Learning and Anti-Plagiarism Back-End Services

Plagiarism refers to the use of other people’s ideas and information without acknowledging the source.In this research,anti-plagiarism software was designed especially for the university and its campuses to identify plagiarized text in students’written assignments and laboratory reports.The proposed framework collected original documents to identify plagiarized text using natural language processing.Our research proposes a method to detect plagiarism by applying the core concept of text,which is semantic associations of words and their syntactic composition.Information on the browser was obtained through Request application programming interface by name Url.AbsoluteUri,and it is stored in a centralized Microsoft database Server.A total of 55,001 data samples were collected from 2015 to 2019.Furthermore,we assimilated data from a university website,specifically from the psau.edu.sa network,and arranged the data into students’categories.Furthermore,we extracted words from source documents and student documents using the WordNet library.On a benchmark dataset consisting of 785 plagiarized text and 4,716 original text data,a significant accuracy of 90.2%was achieved.Therefore,the proposed framework demonstrated better performance than the other available tools.Many students mentioned that working on assignments using the framework was suitable because they were able to work on the assignments in harmony,as per their timeframe and from different network locations.The framework also recommends procedures that can be used to avoid plagiarism.