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Copyright of Ḥawliyyaẗ Kulliyyaẗ Al-Adāb: Ǧāmiʿaẗ Binī Sūwaīf is the property of Beni Suef University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Context. Using the composition relation is one of the most effective and commonly used ways to specialize classes in object-oriented programming. Objective. Problems arise when “redundant” attributes are detected in an inner class, which are not necessary for solving the tasks of a specialized class. To work with such attributes, the inner class has corresponding program methods, whose usage not only does not solve the tasks of the specialized class, but can lead to errors in its work. The purpose of this work is to remove “redundant” attributes from the inner class, as well as all methods of the class directly or indirectly (through other methods) using these attributes. Method. A mathematical model of the inner class was developed, which allowed us to identify “redundant” elements of the class. The method of internal class transformation is proposed, which, based on the analysis of the class code, provides the developer with information to make a decision about “redundant” attributes, and then in the automated mode gradually removes and transforms the class elements. Result. To approbate the proposed solutions, a software product Composition Converter was developed. Experiments were carried out to compare the conversion of classes in “manual” and automated modes. The results showed a multiple reduction of conversion time in the automated mode. Conclusions. The proposed method of automated transformation of the inner class according to the tasks of the outer class when implementing composition allows to significantly reduce the time or the number of errors when editing the code of the inner class. The method can be used for various object-oriented languages. [ABSTRACT FROM AUTHOR]

Complex Arabic sentences, especially those containing Arabic psychological verbs, follow a common underlying structure characterized by two essential components: the predicate and the subject. In addition, there are two optional elements: the head and the complement. These sentences, rooted in basic noun phrases (NPs), can be expanded within the predicate, subject, or complement, resulting in compound structures. This study aims to develop a syntactic analyzer for parsing complex sentences containing Arabic psychological verbs. To achieve this, we will use the dictionary generated from the lexicon-grammar table of Arabic psychological verbs, which contains all lexical, syntactic, semantic, and transformational information related to these verbs. Then, we will extend an existing analyzer to recognize and label all grammatical structures within complex sentences containing Arabic psychological verbs. Finally, we will evaluate the efficiency of this analyzer through tests on different texts and corpora. [ABSTRACT FROM AUTHOR]

Introduction. Historic cities face the issues of sustainable development, especially city centres that have high cultural value. One of the most important topics is ensuring connectivity and accessibility as road and street networks in historic centres have their own characteristics: narrow alleys, high density of buildings, vehicles, pedestrian flows and a variety of public activities. In this aspect, there is the research interest to assess current condition of streets in the historic centres to make informed decisions about their reconstruction in order to create a flexible, comfortable and safe public environment.Materials and methods. Selecting Aleppo city as the object of study, analyzing the current situation of general plan and infrastructure of the city using GIS maps, open public data and information provided by local municipality of the city and through applying (LOS-Level of Service) method which is designed for analyzing transportation networks in this case in the historic city centre.Results. A classification of the streets of the historic city centre was developed, which is designed due to pedestrian ratios, taking into account hierarchy that considers the valuable heritage objects that are located near the studied streets that attract visitors. As a final result a method was suggested for the purpose of ranking level of street services from A to F and the classification of streets according to their values.Conclusions. Identified streets that require reconstruction solutions to improve the quality of the urban environment, with the aim of creating comfortable and safe conditions for pedestrians, while ensuring the accessibility of the urban infrastructure, taking into account its historical value.

Copyright of Studies in Contrastive Grammar / Studii de Gramatica Contrastiva is the property of Universitatea din Pitesti and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article offers a holistic analysis of the prefabricated sentence c’est ça. Firstly, an interactional analysis is carried out in a variety of professional and private ordinary social situations, through a quantitative and qualitative approach, based on phenomena specific to spoken language such as the organization of turntaking and multimodality. Secondly, the article examines c’est ça in dialogues from recent novels, from a syntactic perspective, focusing more particularly on the relationships between pragmatic values, punctuation and discourse markers. Finally, some uses of c’est ça are contrasted between oral speech and written representation of speech.

Focusing on section I, 35 and I, 36 of Friedrich Nietzsche's Human, All Too Human, as well as other related works, this paper examines Nietzsche's evaluation of François de La Rochefoucauld's psychological observation in the latter's maxims. It argues that, in Nietzsche's view, La Rochefoucauld's perspicacity in detecting moral psychology is crystallized both in the form of maxim and the messages derived from psychological observation that are conveyed in the maxims. It contends that the readers' reactions to these maxims also render their passions and desires tangible and intelligible for La Rochefoucauld's and Nietzsche's observations of their psyche. Furthermore, by exploring Nietzsche's contrasting assessments of La Rochefoucauld's maxims, we can also illuminate his own theory of moral psychology. [ABSTRACT FROM AUTHOR]

Abstract Syntactic analysis and semantic plausibility provide important cues to build the meaningful representation of sentences. The purpose of this research is to explore the age-related differences in the use of syntactic analysis and semantic plausibility during sentence comprehension under different working memory load conditions. A sentence judgment task was implemented among a group of older and younger adults. Semantic plausibility (plausible, implausible) and syntactic consistency (consistent, inconsistent) were manipulated in the experimental stimuli, and working memory load (high, low) was varied by manipulating the presentation of the stimuli. The study revealed a stronger effect of semantic plausibility in older adults than in younger adults when working memory load was low. But no significant age difference in the effect of syntactic consistency was discovered. When working memory load was high, there was a stronger effect of semantic plausibility and a weaker effect of syntactic consistency in older adults than in younger adults, which suggests that older adults relied more on semantic plausibility and less on syntactic analysis than younger adults. The findings indicate that there is an age-related increase in the use of semantic plausibility, and a reduction in the use of syntactic analysis as working memory load increases. [ABSTRACT FROM AUTHOR]

In this paper, a new technique of feature extraction is proposed, which is considered an essential part of natural language processing. Feature extraction is the process of transformation of the unstructured text to a format which is recognizable by computers. This means a transformation to a vector of numbers. The study evaluates and compares the performance of three methods: M1, which is the baseline method TfIdf; M2, which combines TfIdf with POS tags; and M3, a novel technique called MDgwPosF that incorporates weighted TfIdf values based on word depths and the relative frequency of POS tags. The primary focus of the study is to assess and compare the performance of these methods, with particular emphasis on evaluating how M3 performs in comparison with M1 and M2. Two different datasets and feed-forward, LSTM and GRU neural networks were used in this study. The results showed that the feed-forward model with the proposed method MDgwPosF in moderate topology achieved the best performance across various measures. The dataset created automatically performed better than the manual dataset. The differences between methods and topologies were not statistically significant. Statistically significant differences between the classification models were proven. The MDgwPosF method achieved higher accuracy compared to the baseline TfIdf, indicating that incorporating additional information into the vector can enhance the performance of TfIdf. [ABSTRACT FROM AUTHOR]

Purpose. Natural language text processing techniques are used to solve a wide range of tasks. One of the most difficult tasks when working with natural language texts for different languages is to find certain indicators for further determining its authorship. The problem is still relevant due to the lack of a unified tool or method for working with texts in different languages. Working with texts in Ukrainian requires taking into account its peculiarities of word and sentence construction to obtain the best result. The main purpose of this article is to analyze the existing methods of text processing, their features and effectiveness in working with texts of different languages. Methodology. Natural language text processing methods are systematized by type and format, according to the tools and approaches used. For each method, its features, effectiveness, scope, and limitations are considered. The means of system analysis were used to form the final characterization of the method, taking into account its purpose and capabilities. Findings. The study of methods has revealed the following ones used for the intellectual analysis of texts in different languages, their scope, effectiveness in working with different languages, strengths and weaknesses. This will make it possible to choose an effective toolkit for working with Ukrainian texts. It has been established that intelligent text processing is a complex task that requires an individual approach to each language to take into account its peculiarities and obtain the best result. Originality. The basis for choosing an effective method for working with Ukrainian-language texts is formed, the existing methods of intellectual text processing, their application features, capabilities and efficiency in working with texts of different languages are analyzed and systematized. Practical value. The work allowed us to identify the most promising, effective and appropriate methods of intellectual analysis of natural language texts in order to use them for processing Ukrainian-language texts in the future.

This study explores the comprehensive analysis of the morpheme "-ra" in Persian, a topic that has not been extensively studied despite its importance. Traditionally, "-ra" has been considered a definite/specific direct object marker. However, non-canonical occurrences of "-ra" on adverbs, extracted subjects from embedded clauses, obligatory appearances on extracted DPs from indirect object positions, and DPs extracted from PPs complement positions raise questions about its role as an accusative case marker and the mechanism for case assignment in these constructions.The analysis of the morpheme "-ra" in Persian is of significant importance due to its widespread usage and syntactic/semantic variations beyond its canonical role as a definite/specific direct object marker. Understanding the comprehensive distribution and features of "-ra" is crucial for unraveling the intricate syntactic and semantic properties of Persian. Despite previous attempts to analyze this morpheme, no comprehensive framework has been proposed thus far that can account for all its syntactic/semantic distributions and capture its various non-canonical occurrences. This study aims to address this gap by providing a detailed investigation into the syntactic behavior and case assignment mechanisms associated with "-ra" in Persian. By delving into these aspects, we can shed light on the intricate nature of this morpheme and contribute to the broader understanding of Persian syntax and case marking phenomena

ABSTRACT: The main objective of this study is to identify and analyse grammatical errors (syntactic and morphological) in the Spanish version of the novel Ocultación by the Saudi writer Raja Alem and the possible causes that have led the translator to make such errors. The analysis will focus on those syntactic and morphological errors that have affected the accuracy of the transfer in certain passages of the work. Our working methodology consists of comparing the Spanish translation of the novel with its Arabic original to identify the possible errors noted and their effect on the accuracy of the translation, accompanied by explanatory comments and followed by our proposals for such errors. For this, the work relies on the typology of grammatical errors developed by Nord (1991) and Hurtado Albir (2017). RESUMEN: El objetivo principal de este trabajo es identificar y analizar los desaciertos gramaticales (sintácticos y morfológicos) en la versión española de la novela Ocultación de la escritora saudí Raja Alem y las causas posibles que han llevado a la traductora a incurrir en tales desaciertos. El análisis se centrará en aquellos desaciertos sintácticos y morfológicos que han afectado a la precisión del trasvase en ciertos pasajes de la obra. Nuestra metodología de trabajo consiste en cotejar la traducción al español de la novela con su original árabe para identificar los posibles desaciertos señalados y su efecto sobre la exactitud de la traducción, acompañados de comentarios aclarativos y seguidos por nuestras propuestas para dichos desaciertos. Para ello, el trabajo se apoya en la tipología de los errores gramaticales desarrollados por Nord (1991) y Hurtado Albir (2017).

The focus of the study is to find out the potential identity of null arguments in Punjabi. However, the paper provides different patterns of interpretations of null arguments present in Punjabi by keeping in view the propositions of Takahashi (2012, July). The special focus is given on the phenomenon named as Argument Ellipsis (AE), which is used as syntactically mediated process for investigating the relationship of verbal agreement and scrambling with AE in null argument language Punjabi. It was observed that AE in Punjabi licenses the null arguments on direct and indirect objects, subjects and selected PPs. The study finds out by observing and manipulating different configurations of subject-object agreement in Punjabi that there is no role critically played by verbal agreement in order to restrict AE. The research also specifies that scrambling approach for licensing is also not reliable predictor for AE in Punjabi. However, bare nouns approach is more appropriate for the analysis of AE in Punjabi as the bare nouns license the sloppy interpretations, which are marked either indefinite or definite nouns for null arguments in Punjabi. This approach can be tested for further cross-linguistic examination of AE, and hopefully it would be regarded as the only underlying cause of argument ellipsis for future studies.

This article offers a holistic analysis of the prefabricated sentence c'est ça. Firstly, an interactional analysis is carried out in a variety of professional and private ordinary social situations, through a quantitative and qualitative approach, based on phenomena specific to spoken language such as the organization of turntaking and multimodality. Secondly, the article examines c'est ça in dialogues from recent novels, from a syntactic perspective, focusing more particularly on the relationships between pragmatic values, punctuation and discourse markers. Finally, some uses of c'est ça are contrasted between oral speech and written representation of speech. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Tikrit University for Humanities is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Сложные предложения составляют огромную часть нашего ежедневного общения. Более того, они могут представлять такие типы отношений между предложениями, что последовательность простых предложений просто не может передать, поскольку они могут воспроизводить различные типы семантических и логических отношений. Хотя сложное предложение является полипредикативной структурой, которая организована на основе паратаксиса и не включает в себя элементы зависимости, связь между предложениями координат часто бывает асимметричной (при этом первое предложение играет ведущую роль в предложении). Данная статья посвящена анализу составных предложений, представленных в рассказе «Соловей и роза», с точки зрения их типа, структуры, соединительных устройств и используемых семантических отношений, а также их стилистическая ценность.

[Display omitted] Studies confirm that significant biases exist in online recommendation platforms, exacerbating pre-existing disparities and leading to less-than-optimal outcomes for underrepresented demographics. We study issues of bias in inclusion and representativeness in the context of healthcare information disseminated via videos on the YouTube social media platform, a widely used online channel for multi-media rich information. With one in three US adults using the Internet to learn about a health concern, it is critical to assess inclusivity and representativeness regarding how health information is disseminated by digital platforms such as YouTube. Leveraging methods from fair machine learning (ML), natural language processing and voice and facial recognition methods, we examine inclusivity and representativeness of video content presenters using a large corpus of videos and their metadata on a chronic condition (diabetes) extracted from the YouTube platform. Regression models are used to determine whether presenter demographics impact video popularity, measured by the video's average daily view count. A video that generates a higher view count is considered to be more popular. The voice and facial recognition methods predicted the gender and race of the presenter with reasonable success. Gender is predicted through voice recognition (accuracy = 78%, AUC = 76%), while the gender and race predictions use facial recognition (accuracy = 93%, AUC = 92% and accuracy = 82%, AUC = 80%, respectively). The gender of the presenter is more significant for video views only when the face of the presenter is not visible while videos with male presenters with no face visibility have a positive relationship with view counts. Furthermore, videos with white and male presenters have a positive influence on view counts while videos with female and non − white group have high view counts. Presenters' demographics do have an influence on average daily view count of videos viewed on social media platforms as shown by advanced voice and facial recognition algorithms used for assessing inclusion and representativeness of the video content. Future research can explore short videos and those at the channel level because popularity of the channel name and the number of videos associated with that channel do have an influence on view counts. [ABSTRACT FROM AUTHOR]

Introduction. Working with graphic images is an essential element of almost any modern computer-aided design systems. The result of neural network, including deep image processing, can be recognition of the belonging classes of objects present on them. Objects of the real world require large expenditures for the development and implementation of highly specialized computer vision systems. In recent years, there has been an improvement of the quality characteristics obtained in the field of technical vision. This is made possible by artificial neural networks. The article deals with the recognition of a flat, black and white flowchart image. These are two-dimensional images or their selected parts, which are displayed in an arbitrary graphic format by system means on a computer monitor screen. Basic block diagram shapes: rectangle, rhombus, parallelogram, circle, ellipse (oval), etc. The purpose of the article is to solve the problem of graphic image recognition. The systems for the recognition of graphic images include modern systems of computer-aided design, management and document management. The article has formed a basic set of training and test images of block diagram nodes. Neural network models are proposed to improve the detection accuracy of block diagram nodes based on fully connected and convolutional neural networks. Results. The basic procedures of the block diagram image recognition algorithm were partially tested at the software level, and allow us to conclude the effectiveness of the proposed structural methods. A comparative analysis of neural network and syntactic structural approaches for solving this problem is carried out. Conclusions. Two methods of recognizing flat graphic figures and recognizing connections between figures in flowcharts are proposed: a method of recursive traversal of all branches of the tree of the current union of connections between figures and the figures themselves, and also a study was carried out for the created neural network in PyTorch to solve this problem using trained neural network methods.

Basic syntactic analysis refers to sentence-level syntactic analysis. In the process of developing the Mat Link English–Chinese machine translation system, the Generalized Maximum Likelihood Ratio algorithm was improved, and a basic English syntax analyzer for English–Chinese translation was designed and implemented. The analyzer approves the structure of the analysis table with a variety of export products, introduces the character mapping function to realize the automatic recognition of the sentence boundary, uses the children of the same level to describe the grammatical structure of the sentence, and realizes the proverb from the original sentence to the target sentence stage conversion. Finally, through the analysis of example sentences, the design concept and working process of the basic grammar are explained.

The current study aims at analyzing the syntax of Arabic-English intra-sentential code-switching within verb phrase boundaries and finding out how this type of code-switching is performed. Particularly, this study investigates the speakers' maintenance of their Arabic syntactic structure ant word order while inserting English constituents at verb phrase level. In addition, it examines the effect of the originated patterns on Arabic structural rules and examines the validity of equivalence constraint provided by Poplack in Arabic-English intra-sentential code-switching. To this end, a qualitative approach is operated to gather the research data; the qualitative data are collected from Facebook chats and comments between Jordanian university students while they are communicating on Facebook. Then, conversational analysis technique is used to analyze the syntactic aspects of VP patterns of intra-sentential Arabic-English code-switching. Furthermore, clarification of some grammatical differences between Arabic and English is provided along with analysis. The findings showed that there are thirteen patterns performed within VPs despite the grammatical differences between the two languages. These patterns sometimes violate the grammatical rules of English. Meanwhile, the grammatical rules of Arabic are not affected by intra-sentential code-switching performed within VPs. That means Jordanian Arabic-English code-mixing violates the universal constraint of 'equivalence' proposed by Poplack (1980). The study provides a potential theoretical implication for the Arabic Language Academies in the Arab World by encouraging them to cooperate to carefully ponder the implications of this code-mixing, and they should coin Arabic words for all new English terms, especially those related to the technological and scientific innovations. [ABSTRACT FROM AUTHOR]

New sentiment words in product reviews are valuable resources that are directly close to users. The data processing of new sentiment word extraction can provide information service better for users and provide theoretical support for the related research of edge computing. Traditional methods for extracting new sentiment words generally ignored the context and syntactic information, which leads to the low accuracy and recall rate in the process of extracting new sentiment words. To tackle the mentioned issue, we proposed a data processing method based on sequence labeling and syntactic analysis for extracting new sentiment words from product reviews. Firstly, the probability that the new word is a sentiment word is calculated through the location rules derived from the sequence labeling result, and the candidate set of new sentiment words is obtained according to the probability. Then, the candidate set of new sentiment words is supplemented with the method of matching appositive words based on edit distance. Finally, the final set of new sentiment words is collected through fine-grained filtering, including the calculation of point mutual information and difference coefficient of positive and negative corpus (DC-PNC). The experimental results illustrate the effectiveness of new sentiment words extracted by the proposed method which can obviously improve the accuracy and recall rate of sentiment analysis. [ABSTRACT FROM AUTHOR]

This research aims to identify the types of sentences and to identify the functions of sentences found in Love One Another Poem. The researcher used theories about syntax from [1]theory and [2] theory to identify the types of sentences and the functions of sentences. The source of the data is taken from a poem written by Kahlil Gibran and titled Love One Another. The method used in this research is the qualitative analysis method proposed by [3] All the data could not be used in mathematical sequences. This method includes several steps, such as collecting, identifying, analyzing, examining and drawing conclusions. Syntax Tree Editor, an application language program, is employed to support the data analysis. The results show that there are two types of sentences used in the poem Love One Another; they are three simple sentences (30%) and seven compound sentences (70%). The functions of sentences are six imperative sentences (60%) and four exclamatory sentences (40%). The imperative function is dominant. [ABSTRACT FROM AUTHOR]

Copyright of Linguistica is the property of Linguistica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Approximately 15% of all cancer deaths among women worldwide is due to breast cancer. Mammography is one of the most useful methods for the early detection of this disease. Over the last decade, several papers were published reporting the usage of different computer‐aided diagnosis systems using pattern recognition techniques as a second opinion to obtain a more accurate diagnosis. However, the theory of formal languages has not been explored in this field. In this context, the main contribution of this study is to present the usage of a new syntactic approach that is able to classify breast masses found in mammograms as benign or malignant. The experimental tests were performed using a dataset that contains 111 images from different sources. The grammar‐based classifiers achieved accuracy values ranging from 89% to 100% depending on the features and the model employed. Furthermore, to achieve a feature dimension reduction, a feature selection technique based on the Gini importance of each feature was employed. Additionally, we compared the obtained results with the grammar‐based classifiers to the more traditional classifiers used in this research area, such as artificial neural networks, support vector machines, k‐nearest neighbors, and random forest. The best result achieved by the grammar‐based classifiers was approximately 10% higher, in terms of accuracy, than the best results produced by the traditional classifiers, showing the strength of this grammatical approach. [ABSTRACT FROM AUTHOR]

Copyright of Online Journal of Art & Design is the property of Online Journal of Art & Design and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the development of a new generation of information technology, such as big data and cognitive intelligence, we are in the postmodern era of artificial intelligence. Currently, the manufacturing industry is in the critical period of transitioning to smart manufacturing, but the cognitive capabilities of devices in smart factories are still scarce. Knowledge Graph (KG) is one of the key technologies of cognitive intelligence, which opens a new path for the horizontal integration of intelligent manufacturing. Therefore, this paper proposes and builds a manufacturing equipment information query system based on KG. Firstly, a large amount of heterogeneous data that contains vast devices information is obtained from the network. Secondly, the conditional random fields (CRF) algorithm is used to extract the entity name, product place, and company name of the device, and then the relationship between the device entities is identified by calculating the similarity and Chinese syntax analysis. In the validation section, we use to the map of Neo4j graph database, when we input a name of a device in the search box, the system can return a relational graph node. In addition, the shortest path optimization algorithm is used to calculate the similarity between nodes in the search process to achieve the recommendation of similar node information.

Trajectory classification is a hot topic in the field of spatiotemporal data mining. Existing models exert spatial or temporal computation on trajectory data, which require huge efforts and are often time consuming and lack of efficiency. This article proposes a model to classify unknown ship trajectories through a syntax recognition approach. By using the background semantic information in the rasterized sea chart, the model transforms the ship trajectories into symbolic sentences containing both spatiotemporal and semantic information, and reduces their scale. The class feature is expressed as a context-free grammar and the data classification is implemented through syntax parsing. The parsing requires less computation and is more efficient. Experiments are carried out to verify the model's practicability, and the results show that it is valid and effective.

Users of forums, social networks and news portals now have the opportunity to publicly express their opinions on current political events, social issues, or their everyday lives. The analysis of opinion expression, which primarily represented a research topic in the field of language learning, has now become an important research challenge in the field of computational linguistics, which provides relevant solutions for various companies and organizations. The aim of this article is to analyse messages by which users of the social network Twitter reacted to an incident in which Emmanuel Macron was slapped in the face by a man as he went out to meet the public. We analysed the tweets that express agreement, disagreement and a neutral attitude towards the action. The analysis includes 80 tweets and refers to the textual, syntactic and lexical levels. The results show that tweets expressing disagreement have a typical declarative or exclamatory form, simple sentence structure and include explicit vocabulary expressing the author’s opinion (shameful, disrespectful). Tweets demonstrating agreement are more likely to have an exclamatory form, simple sentence structure and include an explicit term (well done, deserve a slap). Opinion-neutral tweets, on the other hand, are more likely to be formulated as declarative sentences with complex sentence structure and do not include an explicit term expressing the author’s opinion. The presented method is established on basic grammatical criteria (number of sentences, sentence structure, sentence form, keywords), which can also be applied to computational analysis of large collections of texts. In the future, the presented model could be applied to investigate various political, societal or healthcare challenges (elections, corruption or pandemic issues).

Objective: The study sought to develop and evaluate neural natural language processing (NLP) packages for the syntactic analysis and named entity recognition of biomedical and clinical English text.Materials and Methods: We implement and train biomedical and clinical English NLP pipelines by extending the widely used Stanza library originally designed for general NLP tasks. Our models are trained with a mix of public datasets such as the CRAFT treebank as well as with a private corpus of radiology reports annotated with 5 radiology-domain entities. The resulting pipelines are fully based on neural networks, and are able to perform tokenization, part-of-speech tagging, lemmatization, dependency parsing, and named entity recognition for both biomedical and clinical text. We compare our systems against popular open-source NLP libraries such as CoreNLP and scispaCy, state-of-the-art models such as the BioBERT models, and winning systems from the BioNLP CRAFT shared task.Results: For syntactic analysis, our systems achieve much better performance compared with the released scispaCy models and CoreNLP models retrained on the same treebanks, and are on par with the winning system from the CRAFT shared task. For NER, our systems substantially outperform scispaCy, and are better or on par with the state-of-the-art performance from BioBERT, while being much more computationally efficient.Conclusions: We introduce biomedical and clinical NLP packages built for the Stanza library. These packages offer performance that is similar to the state of the art, and are also optimized for ease of use. To facilitate research, we make all our models publicly available. We also provide an online demonstration (http://stanza.run/bio). [ABSTRACT FROM AUTHOR]

Aspect-level sentiment classification aims to predict sentiment polarities for different aspect terms within the same sentence or document. However, existing methods rely heavily on modeling the semantic relevance of an aspect term and its context words, and ignore the importance of syntax analysis to a certain extent. Consequently, this may cause the model to pay attention to the context word which is used to describe other aspect terms. In this paper, we propose a model which analyze sentences both syntactically and semantically. At the same time, we propose a simple and effective fusion mechanism to make the integration of aspect information and context information more adequately. We conduct extensive experiments on the SemEval 2014 benchmark datasets, and the results show that our model achieves a new state- of-the-art performance. [ABSTRACT FROM AUTHOR]

Background/Objectives: There is no attempt to investigate the relationships between dependency and markedness even though the syntactic roles in language are decided by dependency relations and markers. The main objective of this study was to understand markedness beyond syntactical tables and propose a syntax graph with various syntax structures to verify the relationship between dependence of proposed markers. Methods/Statistical analysis: The methodology involved enquiry into the origin and development of dependency relations, starting from their definition, abstraction, and usage in syntactic structures through graphical presentations. Findings: This study revealed that dependency relations denoted by the markers can be classified into two types of dependencies according to their syntactic functions: implicit and explicit. Eventually, this markedness can be presented through syntax graphs of various syntactic structures to validate the functions of the markers and dependency relations. Improvements/Applications: This paper presents a reasonable method to define dependency relations based on the markedness and the valence theory of the predicate. This approach provides a systematic view to define dependency relations for natural language processing. The implementation of syntax graphs is a future research project. [ABSTRACT FROM AUTHOR]