Grammar Rules Research Articles

Valence generalization across nonrecurring structures.

Semantically meaningless letter strings correlated with affective attributes (US) can become evaluatively conditioned stimuli (CS). Jurchiș et al. (2020) recently demonstrated CS-US correlations may influence evaluations toward previously unseen strings when the latter are grammatically congruent with CS. We replicated those authors' findings in a modified extension (Experiment 1; N = 108), where emotional faces (US) were correlated with letter strings (CS) constructed from familiar (English) and unfamiliar (Phoenician) alphabets. CS-US trials were sandwiched by evaluations of strings that never appeared as CS but were constructed using similar grammar rules. Although CS and evaluated strings never overlapped, their individual elements (letters) recurred between phases. Element recurrence was controlled for in a second replication (Experiment 2; N = 140), where participants viewed Phoenician (/English) strings during conditioning and English (/Phoenician) strings during evaluations. We found credible evidence for valence generalization across strings from different alphabets but parallel grammars, suggesting the latter had been perceived as 'functionally equivalent' (Tonneau, 2004b). We provide support for this claim in a third study (Experiment 3; N = 79), where participants underwent a 'free selection' 2AFC discrimination task with sample and comparison strings taken from different alphabets. Increasing frequencies of grammar-congruent discriminations suggested strings were becoming functionally equated along overlapping grammar rules. We speculate how 'rules' which inform how elements are organized relative to each another can be abstracted and generalized across without specifying elemental properties (Spaulding, 1912). (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Ontologically correct taxonomies by construction

Taxonomies play a central role in conceptual domain modeling, having a direct impact in areas such as knowledge representation, ontology engineering, and software engineering, as well as knowledge organization in information sciences. Despite this, there is little guidance on how to build high-quality taxonomies, with notable exceptions being the OntoClean methodology, and the ontology-driven conceptual modeling language OntoUML. These techniques take into account the ontological meta-properties of types to establish well-founded rules on the formation of taxonomic structures. In this paper, we show how to leverage the formal rules underlying these techniques in order to build taxonomies which are correct by construction. We define a set of correctness-preserving operations to systematically introduce types and subtyping relations into taxonomic structures. In addition to considering the ontological micro-theory of endurant types underlying OntoClean and OntoUML, we also employ the MLT (Multi-Level Theory) micro-theory of high-order types, which allows us to address multi-level taxonomies based on the powertype pattern. To validate our proposal, we formalize the model building operations as a graph grammar that incorporates both micro-theories. We apply automatic verification techniques over the grammar language to show that the graph grammar is sound, i.e., that all taxonomies produced by the grammar rules are correct, at least up to a certain size. We also show that the rules can generate all correct taxonomies up to a certain size (a completeness result).

The Role of the “Recipient” in Arabic Grammatical Heritage: A Study in the Light of some Modern Approaches

This research aims at defining the role of the “recipient” in the Arabic grammatical heritage in order to highlight the level of the Ancient Arabic Grammar studies in dealing with the verbal position in general, and the recipient in particular – as he has been described as an important element in the conversational position. Moreover, this paper aims to know the extent of availability of this ancient study of linguistic concepts, which were considered as one of the innovations of modern linguistic studies in their both literary and linguistic aspects. This research also attempts to highlight the role of the active Recipient and its manifestation in the process of discursive communication, directing the speech, and how the elements of the external context work with the internal ones in achieving the understanding, in general, and the understanding of the recipient, in particular, and in the success of the communicative process between the parties of discourse.The current research concluds, in its extrapolating a set of grammatical provisions in the books of grammatical heritage, that the recipient was present in the minds of ancient grammarians as they were building and directing grammar rules, such as defining or undefining grammatical components, preposing them or postposing and deleting them or mentioning. It is not surprising becaused the real function of language,which is creating communication, cannot be realized without the presence of a recipient. Keywords: Role, the recipient, Arabic grammar, Forming constructions, the benefit (understanding), the security of confusion, Modern approaches.

Influence of Social Media Chat on English Writing Skills of the Students

The advancements in technology have cast a shadow on people belonging to all walks of life.The life of youth is incomplete without the use of technology. Mobile phones have become a necessity in their lives. Invent of internet gifted mobile phones with many new applications e.g. WhatsApp,Twitter, Snapchat, etc. WhatsApp is the easiest and the most user-friendly application among all has gained tremendous importance in the lives of youth. WhatsApp users are rising each day as every new invention comes up with many advantages as well as disadvantages. The present study attempts to study the effects of WhatsApp messenger on formal writing of students by using a mixed research design i.e. two research tools have been used for the collection of data, one is quantitative in the form of a questionnaire whereas the other one is qualitative like the assessment of students essays.Resultantly, it was found that the language they use in texting while using WhatsApp messenger often deviates from the spelling and grammar rules of a standard language. It was observed that the informal style of writing developed due to excessive use of WhatsApp is reflected even in the formal writing of the students. The linguistic expressions used over WhatsApp by most of the students affect their writing skills negatively

Anuvaad

Machine Translation is best alternative to traditional manual translation. The corpus of Sanskrit literature includes a rich tradition of philosophical and religious texts as well as poetry, music, drama, scientific, technical and other texts. Due to the modernization of tradition and languages, Sanskrit is not on everyone's lips. Translation makes it convenient for users to understand the unknown text. This paper presents a language Machine Translation System from Hindi to Sanskrit and Sanskrit to Hindi using a rule-based technique. We developed a machine translation tool 'anuvaad' which translates Sanskrit prose text into Hindi & vice versa. We also developed bi-lingual corpora to deal with Sanskrit and Hindi grammar rules and text applied rule based method to perform the translation. The experimental results on different 110 examples show that the proposed anuvaad tool achieves overall 93% accuracy for both types of translations. The objective of our work is to ensure confidentiality and multilingual support, which can be tedious and time consuming in case of manual translation.

Language Code Mixing in the Discourse of IT Companies

The mixing of English with national languages in business communication is a consequence of global processes: the development of transnational corporations, modern technologies, the intensification of communication flows and the dominance of English in intercultural communication. Mixing and switching of language codes is quite often observed in the corporate media discourse of IT companies. For organizations in this sphere, English is the main language of business communication, but its use goes beyond professional slang and terminology, creating characteristic forms of language codes mixing. The purpose of the research presented in the article is to identify and analyze situations of mixing English and Russian in the corporate media discourse of IT companies. The research material was corporate media texts in Russian and English posted on the pages of official websites, corporate blogs and in the social networks Twitter and Facebook. In the analyzed texts in Russian, English inclusions (phrases, individual words and their parts) are often observed to denote work programs and tools, corporate events. As part of the professional slang of IT professionals, English words are transmitted using the Cyrillic alphabet and in accordance with the rules of Russian grammar. The influence of English on Russian media discourse in the IT field is also observed in the expansion of the meanings of some words. In Russian media texts, there are also phrases that are not typical for the Russian language, but represent a literal translation of English phrases. English-language sentences are used in Russian texts as mottos or slogans of the company, as congratulations or advice. As a result of the content analysis of the selected media texts, it was also found that along with the English language, the values typical for the discourse of American corporations are being borrowed. It was found that the value dominants of the corporate discourse of IT companies are change and progress, success, equality, partnership.

The positive outcomes and challenges experienced by Modern Foreign Language teachers in Oman

ABSTRACT This paper focuses on the positive outcomes and the challenges that teachers experienced after the introduction of the English primary curriculum reform of grades 3 and 4 in Omani state schools. Three focus group interviews were conducted with English teachers (n = 15) in three regions (Muscat, AL Sharqia South and AL Dahira regions). Although the findings indicated that progress had been achieved in introducing shared writing, reading time, vocabulary and grammar rules in grades 3 and 4 reform, a number of challenges were also identified. Teachers’ views about much of the content of the compulsory school textbook in relation to the choice of topics, the development of the productive skills, the lack of resources, and problems with assessment, were overwhelmingly negative. Furthermore, it seems that curriculum reform was not adequately underpinned by theoretical principles.

The Analysis of Problem Posing Skills about Integers of Prospective Primary School Mathematics Teachers Who Have Experienced in Problem Posing

This study aims to analyze the problem-posing skills of primary school mathematics teacher candidates with problem-posing experience and their views on problem posing. The case study, one of the qualitative studies, was used in the study. The study group is ten prospective elementary mathematics teachers who were selected using the purposive sampling method and are in their third year in the academic years 2020-2021 Teaching Mathematics in Primary Schools Major at a private university in Istanbul.The data collection process consists of two stages: 9 problem-posing drafts in total for performance evaluation prepared by examining the literature and obtaining an expert opinion and semi-structured interview forms with three questions. The participants were asked to pose problems on the subject of integers. The problems were evaluated and analyzed by the researchers and two mathematics teachers according to the problem-posing evaluation criteria developed by the researchers. As a result of the findings obtained in the performance determination phase of the study, it was determined that the participants posed more successful problems in the case of structured problem posing. It was determined that some of the problems were not problematic; they were prepared without paying attention to grammar rules, the sentences were not in a clear and logical framework that the middle school students could understand. The numbers were not used according to a certain logic pattern to make the problem solvable. Some problem situations were left unanswered. In the second stage of the study, the data obtained through semi-structured interviews with the primary school mathematics prospective teachers were analyzed using content analysis. In examining the research findings, the main issues are what the participants pay attention to in problem setting, whether they emphasize problem setting in the instructional process, whether problem setting is necessary for each student, and whether anxiety occurs in problem setting.

Intelligence System for Multi-Language Recognition

Language classification systems are used to classify spoken language from a particular phoneme sample and are usually the first step of many spoken language processing tasks, such as automatic speech recognition (ASR) systems Without automatic language detection, spoken speech cannot be properly analyzed and grammar rules cannot be applied, causing failures Subsequent speech recognition steps. We propose a language classification system that solves the problem in the image field, rather than the sound field. This research identified and implemented several low-level features using Mel Frequency Cepstral Coefficients, which extract traits from speech files of four languages (Arabic, English, French, Kurdish) from the database (M2L_Dataset) as the data source used in this research. A Convolutional Neuron Network is used to operate on spectrogram images of the available audio snippets. In extensive experiments, we showed that our model is applicable to a range of noisy scenarios and can easily be extended to previously unknown languages, while maintaining classification accuracy. We released our own code and extensive training package for language classification systems for the community. CNN algorithm was applied in this research to classify and the result was perfect, as the classification accuracy reached 97% between two languages if the sample length was only one second, but if the sample length was two seconds, the classification accuracy reached 98%. While the classification among three languages, the classification accuracy reached 95% if the sample length was only one second, but if the sample length was two seconds, the classification accuracy reached 96%.

قراءةٌ ناقدةٌ لبحثٍ وكتابٍ في (الاحتجاج بالحديث النَّبويِّ في الدَّرس النَّحويِّ).

This research is a critique made against a book addressed to one of the issues related to grammar rules. It was stated in the chapter of hearing named the evidence of citation and rejection; and part of this was concerned with the Prophetic Hadith. The earliest grammarians showed less refusal or rare or lacking rejection against citation while some latest of them raised the issue and said that the earliest adopted abstention doctrine. However, the author had overcome the issue by producing this book; and mentioned three doctrines in terms of rejection issue; supported those of approved doctrine and desired cancel of abstention doctrine. In examining the book, I found that some judgments were made on issues without supported realities as well as other judgments on issues without basis. The author of the book was influenced by the emotion and favor which was appeared in the presentation and discussion. Therefore, I decided ultimately to write my remarks and criticism against the author’s presentation, judgments and chapters of the book.

ANALYSIS OF STUDENTS’ WORDS MISTAKE IN SKRIPSI EXAMINATION

This research purposes to find out what type of words mistake made by the students and the causes of mistake made by the students in skripsi examination especially in English Education Study Program. This research is a qualitative research by using documentation and interview as intruments. The researcher used audio recording in documentation to record the students' proposal seminar performance and the researcher asked some questions in interview by using the audio recording to record the students' answers. The researcher selected 6 students in a class as a sample. This data collection involved 6 students of English Education Study Program who finished their skripsi examination. The result of this research indicate that the common mistake are made by the students during skripsi examination such us hard to apply grammar rule, limited number of vocabulary, and not perfect in pronounciation and intonation. Also, the result of this research indicate the causes of students mistake during skripsi examination namely communication apprehension, test anxiety, lecturer’s characteristic, and psychological factors.

Thavathiru Kundrakudi Adigalar's paraphrase of Thirukkural

The purpose behind Thavathiru Kundrakkudi Adigalar's paraphrase of Thirukkural is to spread the fame of Thirukkural through the world and enable the people worldwide to drink the divine nectar of Thirukkural. It is also to help the people to practically apply the essense of Thirukkural to day-to-day practical life without distorting its meaning. Kundrakkudi Adigalars simple as well as clear paraphrase covers politics, life, commerce, Vriddhashram, agriculture, day today practical life style. The purpose of this essay is to present these aspects before you. Adigalar has presented this in short sentences with appropriate similes without deviating from the rules of grammar, with guidelines to the administrators and quotes from many famous books. His summary clearly shows that this world will turn into a place of bliss when it follows the path shown by Thirukkural whereby the sufferings will plunge into nothingness.

한국 학습자의 중국어 비교문 오류 분석

This article analyzes the types and causes of comparative sentence errors in Korean learners learning Chinese. Because there are many differences in grammar and rules between Korean and Chinese comparative sentence, which are the mother tongue, repetitive and continuous expression errors occur in Korean learners learning Chinese. The types and causes were divided into four major categories and analyzed.<BR> First, it is an error in the use of degree adverbs used in comparative predicates. This error is the most widespread error for Korean learners. Second, it is an analysis of errors in the complements of comparative sentences. Third, word order errors in comparative sentences were analyzed. When negative adverbs, temporal adverbs, relative adverbs, and adjectives are used in Chinese comparative sentences, Korean learners learning Chinese are accustomed to the word order flexibility of Korean comparative sentence. Fourth, we looked at the types of errors that occur in the correspondence and connection between words used in Chinese comparative sentences and in the use of comparative sentence components.<BR> It is very important to study the grammar function and rule theory existing in Chinese comparative sentences. And it is more meaningful to apply this theoretical study to the actual Chinese learning field. Analysis of comparative sentence error expression of Korean learners learning Chinese is a combination of theory and practice that examines actual expressions based on theory.

Machine Learning Technique to Detect and Classify Mental Illness on Social Media Using Lexicon-Based Recommender System.

The emergence of social media has allowed people to express their feelings on products, services, films, and so on. The feeling is the user's view or attitude towards any topic, object, event, or service. Overall, feelings have always influenced people's decision-making. In recent years, emotions have been analyzed intensively in natural language, but many problems still have to be watched. One of the most important problems is the lack of precise classification resources. Most of the research into feeling gradation is concerned with the issue of polarity grading, although, in many practical applications, this relatively grounded feeling measure is insufficient. Design methods are therefore essential, which can accurately classify feelings into a natural language. The principal goal of the research is to develop an overflow of grammatical rules-based classification of Indian language tweets. In this work, three main challenges are identified to classify feelings in Indian language tweets and possible methods for tackling such issues. Firstly, it has been found that the informal nature of tweets is crucial for the classification of feelings. Based on the tweets, the mental illness of the person has been classified. Therefore, to categorize Indian language tweets, a combination of grammar rules based on adjectives and negations is proposed. Secondly, people often express their feelings with slang words, abbreviations, and mixed words. A technique called field tags is used to include nongrammatical arguments such as slang words and diverse words. Thirdly, if a tweet is more complex, the morphological richness of the Indian language results in a loss of performance. The grammar rules are embedded in N-gram techniques and machine learning methods. These methods are grouped into three approaches, which functionally predict Indian language tweets with syntactic words.

An Analysis on Students’ Speaking Ability of Procedure Text at Senior High School

This research discusses the students’ speaking ability of Procedure Text at the Second Grade Students of SMA Tri Bhakti Pekanbaru. The objective of the research is to know the students’ speaking ability in procedure text and to find out which aspectt is the most dominant problem for the students in speaking. The design of this research was qualitative research. The result of data was students’ comprehension score was 3.15 because most of them understood the directions on the speaking test well and they also conveyed the procedure text sequentially using the simple present tense correctly so that the listener could understand them although there were several problems. Students’ fluency score was 3.15 because most of the students’ present the procedure text fluently and smoothly even though some students stammered and paused several times. Students’ grammar score was 3.13 because most of them were good at arranging their sentences correctly according to the grammar rules using the simple present tense even though they made some mistakes. The students' pronunciation score was 2.86 because some students had difficulty in pronouncing some words and there were some confusions with the listener, although not all students did so. Students’ vocabulary score was 2.92 because some students had problem with vocabulary mastery and use inappropriate vocabulary, but overall the students have sufficient vocabulary to express tips simply related to the topic. In conclusion, the students' speaking ability on procedure text is in a good category.

Arapçadan Türkçeye Geçmiş İnsana Ait Özellikler İle İlgili Benzer Kelimelerin İncelenmesi

Language is the element that provides communication between people basically. With the developing of the conversation between people, variations are observed in the language. The main effective factors in the increase of this interaction are religion, trade, education and wars. For these and similar reasons, people who met each other exchanged words. Although it is desired to make language simplification studies today, the use of familiar and stereotyped words could not be stopped. Turkey has been a home to many civilizations due to its geographical location. Due to this cosmopolitan historical structure, the place of foreign words in Turkish vocabulary is undeniable. There are transitions to Turkish from Arabic, as well as from French and Persian. With Islam, there has been an interaction between Arabic and Turkish languages and word transitions have been experienced. The aim of the study is to classify and examine similar words related to human characteristics that have been transferred from Arabic to Turkish. In line with the purpose, word transitions between the two languages were investigated and the basis for the study was prepared. In addition, the transition between words was structurally attached to the grammar rules and caused sound events. In the study, the sound events in question are given in detail in tabular form. The study was conducted with a holistic approach and descriptive method. As a result of the study, 139 words with human characteristics, which were transferred from Arabic to Turkish, were determined. These words are classified into 16 different categories. During the transition, 31 words have undergone sound changes. 108 words are exactly the same. The study is unique at the point of classification of human words and determination of structural changes, and it is a source for later researchers. Key words: Arabic, Turkish, language, foreign word, interaction

Error Analysis on Efl Students’ Essay Writing (Fourth Semester Students of STMIK Sinar Nusantara Surakarta)

This research was finding out the errors made by English Foreign Language students in the essay writing using James’ error analysis. This study was qualitative descriptive research with 30 respondents. The data were collected by students’ mini research report which was then analyzed by observation and classification using Corder’s algorithm. It basically consists of three major stages: recognition, description, and explanation. Finally, the result was classified by using James’ four grammatical error categories. It was found out that there were 200 (100%) grammatical errors containing omission as many as 51 errors (25.5%), addition as many as 18 errors (9%), misformation as many as 105 errors (52.5%), and misordering as many as 26 errors (13%). An error correction activity was also conducted in order to decrease the errors. The result after the treatment was quite significant in which the total number of grammatical errors was decreasing from 200 to 92 containing Omission ( 22.9%), Addition ( 8.7%), Mis-formation ( 60.8%), and Mis-ordering ( 7.6%). The main causes of the errors are the lack of the students' understanding on the target language’s grammar rules and their tendency of using their first language’s grammar rules.

LEARNERS TYPOLOGY: LANGUAGE ACQUIRERS VS LANGUAGE LEARNERS

Krashen’s Monitor Model has been arousing considerable debates for many years and learningacquisition distinction described by the author has become the subject of criticism from both researchers and teachers. But the controversy which is revealed in the Monitor Model and in the follow up literature is not resolved yet. Moreover, scholars and language teachers provide ample justification to foster this hot discussion. We have carried out literature study, introspective and retrospective analysis to examine our own experience as a teacher and as a language learner, and have studied cases described by many other language teachers in a number of teachers’ forums from 15 professional network groups. It is shown that individual learner differences are the key factor which should be taken into consideration when describing the process of second or foreign language mastering. Language learning and language acquisition should not be opposed to each other as they present different means of developing language skills used by different learners. As a result, some learners demonstrate process of language learning characterised by careful grammar rule studying and benefit from error correction, while others develop language skill through subconscious acquisition. Thus, we state that learners fall into two types: language learners and language acquirers whose individual differences predetermine the way learners study the language. The type of a leaner defines the peculiarity of language skill development.

Inducing Vascular Grammars for Anomaly Classification in Brain Angiograms.

As machine learning is used to make strides in medical diagnostics, few methods provide heuristics from which human doctors can learn directly. This work introduces a method for leveraging human observable structures, such as macroscale vascular formations, for producing assessments of medical conditions with relatively few training cases, and uncovering patterns that are potential diagnostic aids. The approach draws on shape grammars, a rule-based technique, pioneered in design and architecture, and accelerated through a recursive subgraph mining algorithm. The distribution of rule instances in the data from which they are induced is then used as an intermediary representation enabling common classification and anomaly detection approaches to identify indicative rules with relatively small data sets. The method is applied to seven-tesla time-of-flight angiography MRI (n = 54) of human brain vasculature. The data were segmented and induced to generate representative grammar rules. Ensembles of rules were isolated to implicate vascular conditions reliably. This application demonstrates the power of automated structured intermediary representations for assessing nuanced biological form relationships, and the strength of shape grammars, in particular for identifying indicative patterns in complex vascular networks.

A Combined Text-Based and Metadata-Based Deep-Learning Framework for the Detection of Spam Accounts on the Social Media Platform Twitter

Social networks have become an integral part of our daily lives. With their rapid growth, our communication using these networks has only increased as well. Twitter is one of the most popular networks in the Middle East. Similar to other social media platforms, Twitter is vulnerable to spam accounts spreading malicious content. Arab countries are among the most targeted, possibly due to the lack of effective technologies that support the Arabic language. In addition, as a complex language, Arabic has extensive grammar rules and many dialects that present challenges when extracting text data. Innovative methods to combat spam on Twitter have been the subject of many current studies. This paper addressed the issue of detecting spam accounts in Arabic on Twitter by collecting an Arabic dataset that would be suitable for spam detection. The dataset contained data from premium features by using Twitter premium API. Data labeling was conducted by flagging suspended accounts. A combined framework was proposed based on deep-learning methods with several advantages, including more accurate, faster results while demanding less computational resources. Two types of data were used, text-based data with a convolution neural networks (CNN) model and metadata with a simple neural networks model. The output of the two models combined identified accounts as spam or not spam. The results showed that the proposed framework achieved an accuracy of 94.27% with our combined model using premium feature data, and it outperformed the best models tested thus far in the literature.