Sentences In Order Research Articles

The nature of syntactic relations reflected by word order in sentences in the novels

The topicality of the problem investigated is caused by necessity of studying the syntactic system of languages which is in line with main trends in modern linguistics. The aim of the research is to study the nature of syntactic relations expressed by word order in sentences in speech of authors and characters in the work of the 20th century American writer J.D. Salinger ‘The Catcher in the Rye’ and the work of the 21st century American writer L. Groff ‘Fates and Furies’. The following objectives of the study contribute to the achievement of the aim: to consider the rules of word order in a sentence in English; to study the works devoted to the study of syntax of a sentence; to analyze the syntactic structure of sentences in authors’ and characters’ speech in the novels «The Catcher in the Rye» by J.D. Salinger and «Fates and Furies» by L. Groff.

Determining the Composition Functions of Persian Non-standard Sentences in Terminology using a Deep Learning Fuzzy Neural Network Model

Organizations can enhance the speed of well-informed decision-making by correctly understanding and using data. Since there is a tremendous gap between the speed of data processing and data generation in the world, exploring data mining in the digital world becomes inevitable. In the Persian language, similar to other languages, with the expansion of communications through social networks, the spelling of words has become abridged and the engagement of foreign loan words and emoticons has been increasing on a daily basis. Given the richness of Persian and its typographical-grammatical similarities to Arabic, research in Persian can be applied to other akin languages as well. In this regard, the current study deals with data mining of Persian non-standard sentences in order to find the function of each word in the sentence. The volume of computation might be limited in traditional methods of natural language processing for each factor contributing to functions. That is because the minimum number of computations is (5 × number of words 9) + (5 × number of words 15). Therefore, this study adopted the Gated Recurrent Unit (GRU) method to process such computations. The newly proposed method reinforces the results of word function identification by using two categories of independent and dependent Persian language functions as well as five factors contributing to the functions of words in sentences as five output gates. Meanwhile, the values of the training tables in this method are fuzzy, where the center-of-gravity method is adopted to decide on the values as well as to reduce the complexity and ambiguity of such computations on the probability of each event occurring. Therefore, the new method is briefly called fuzzy GRU. The results show that the proposed algorithm achieves 80 % reduction in the amount of calculations per gate of updates and reinforcement is approximately 2 % up from 67 % in standard sentences to 69 % of the non-standard sentences.

ANALISA LAPORAN KEUANGAN PADA PT HOLCIM INDONESIA Tbk

The purpose of this study is to determine the company's financial performance and ability To pay short-term obligations and obligations of PT Holcim Indonesia Tbk for the 2017-2018 period. This research includes quantitative and descriptive research, namely research that uses a calculation process and decomposes sentences in order to provide a clear picture of the problem under study. The results of research at PT Holcim Indonesia Tbk can be concluded that the liquidity ratio which includes the current ratio and the quick ratio for the 2017-2018 period can be concluded that the company has a poor level of liquidity because the yield value of liquidity is <1%. For the solvency ratio for the 2017-2018 period, which includes a debt to asset ratio owned by the company of 0.6%, it can be stated that it is not good because it exceeds 0.5% of the set standard and the company's debt to equity ratio of 1.9% can be stated to be not good. because more than 1% of the standards are set and it can be concluded from the results of research on solvency ratios, it can be concluded that the company's ability to pay its obligations is still far from being expected to finance debt that is in the company and it can be said that it is not good.

Meta analisis Pengaruh Model Pembelajaran Kooperatif Tipe Scramble Terhadap Hasil Belajar Siswa di Sekolah Dasar

This study aim ed to re-analyze the effect of scramble learning model to improve student s’ learning outcomes at elementary schools. Scramble learning model refers to a game of arranging the scrambled words and letters in order to form a certain meaningful word . Scramble learning can train students to be creative to arrang e random words and sentences in order. This study utilized a meta-analysis method. At t he first stage, the researcher formulate d the problem, then , sought the existing and relevant research to be analyzed. The technique of data collection in this study was a non-test, namely the documentary analysis method , by searching for electronic journals on Google Scholar with the criteria of comparative journals or articles. There were 11 articles that fulfilled the criteria for th is research . The results of the journal analysis indicated that scramble learning model c ould improve the students' cognitive learning outcomes . This was proved by the average difference of the results of the pre-test and post-test which was 24.9 . To strengthen the results , thes e data were tested by IBM SPSS statistical program 16 for windows with a paired sample T-test . Based on the result of this test , it was revealed that H 1 wa s accepted which implied that the scramble learning model ha d an effect on student s’ learning outcomes with the value of sig 0.00 <0.05.

Factors Affecting the Use of Community Service Sentence Orders among Magistrates as Alternative to Imprisonment in Kinondoni Municipality, Tanzania

This paper is based on a study that attempted to explore factors affecting the use of community service sentence orders as alternative to imprisonment in Kinondoni Municipality, Tanzania. The study was based on the ground that, while a growing number of empirical studies have revealed that prison sentence is not a human rights friendly kind of punishment in a civilized country like Tanzania, disappointingly it remains the most preferred and utilized penalty by most courts. Subsequently, thousands of convicted minor and non-recidivist criminals continued to be sentenced toprisons .Therefore, it is apparent that the community service sentence which was perceived as one of the effective alternatives to imprisonment, remains under-utilized ,resulting into prisons congestions . This study, therefore, explored factors affecting the use of community service sentence orders among magistrates as alternative to imprisonment in Tanzania. The qualitative approach guided by interpretive paradigm and exploratory design in formed this paper. The study consisted of twenty (20) participants who were purposively selected from seven courts of law .The participants included community service officers and magistrates. The in-depth interview was used to capture primary data while secondary data were captured using documentary review. The collected data were analyzed using thematic analysis .The findings revealed that there is lack of confidence of the general public and the courts on community service as a form of punishment since it is perceived to be lenient kind of punishment. Also the limited public awareness on the existence of community service sentence, limited knowledge on the eligibility criteria for community service offenders and corruptions were identified as major factors affecting the use of community service sentence. In light of the findings ,this paper recommends that social workers as human rights advocates should aggressively conduct awareness raising campaigns against overreliance of imprisonment by some magistrates as a form of punishment particularly for petty and non-recidivist offenders .The government should allocate adequate budget to facilitate regular trainings with honorable magistrates to remind them the available options including the use of community service sentence. There is also need of increasing funding to the Community Service Department to facilitate smooth implementation of the community service orders.

The role of grammar in transition-probabilities of subsequent words in English text.

Sentence formation is a highly structured, history-dependent, and sample-space reducing (SSR) process. While the first word in a sentence can be chosen from the entire vocabulary, typically, the freedom of choosing subsequent words gets more and more constrained by grammar and context, as the sentence progresses. This sample-space reducing property offers a natural explanation of Zipf's law in word frequencies, however, it fails to capture the structure of the word-to-word transition probability matrices of English text. Here we adopt the view that grammatical constraints (such as subject-predicate-object) locally re-order the word order in sentences that are sampled by the word generation process. We demonstrate that superimposing grammatical structure-as a local word re-ordering (permutation) process-on a sample-space reducing word generation process is sufficient to explain both, word frequencies and word-to-word transition probabilities. We compare the performance of the grammatically ordered SSR model in reproducing several test statistics of real texts with other text generation models, such as the Bernoulli model, the Simon model, and the random typewriting model.

HETEROGLOSSIA: ANOTHER SFG-BASED APPROACH TO TREATMENT OF WORD ORDER AS A MEANS FOR EXPRESSING MODALITY IN VIETNAMESE

The paper first introduces heteroglossia – a development of Systemic Functional Grammar (SFG) in Hallidayan Systemic Functional Linguistics (SFL) school before suggesting possible uses of heteroglossia in present-day studies of language, with particular focus on the role of word order in sentences of Vietnamese, a typical isolating language. The change of word order is considered a means for expressing modality, as shown in several interesting examples in Vietnamese, which proves that SFG and heteroglossia as its variant is an effective approach for exploring the role of word order in Vietnamese.

Are Conditional Sentence Orders Used Differently for Indigenous Offenders? A Comparison of Sentences and Outcomes in Canada

Conditional sentence orders (CSOs) were introduced in Canada in 1996, largely as a mechanism to address the overreliance on incarceration. This sentencing option is particularly relevant for Indigenous individuals who have been vastly overrepresented in custodial settings. Despite being in place for over twenty years, little is known about the use and effectiveness of CSOs. The current study examined the use and outcomes of CSOs for Indigenous (n = 749) and non-Indigenous offenders (n = 1,625) in one Canadian province. Specifically, the length of CSO, frequency and type of optional conditions, number of breaches, and rates of reoffending were compared between the two groups. Results from a logistic regression, controlling for risk relevant co-variates, indicated that Indigenous individuals tended to receive shorter CSOs compared to Caucasian individuals. However, Indigenous individuals were 35% more likely than Caucasian individuals to be convicted of a breach and more likely to incur multiple breaches while on a CSO. Despite the differences in the rates of breaches, the likelihood of reoffending over a two-year period was equivalent across the two groups. Although the reasons for breach were not available for the current study, future research should investigate this further to determine whether increased breach rates for Indigenous individuals are the result of more rule-violating behaviour, an inequity in the fairness of the conditions applied to Indigenous versus Caucasian individuals, or whether it is possible that breaches are over-detected and convicted at a higher rate for Indigenous individuals. Greater awareness of the underlying mechanisms related to increased breach rates affords the opportunity to ensure that CSOs are consistently implemented, something which will contribute to achieving the objective of successful diversion from imprisonment.

LiSSS: A New Corpus of Literary Spanish Sentences for Emotions Detection

In this work we present a new corpus in the area of Computational Creativity (CC), the Literary Sentiment Sentence Spanish Corpus (LiSSS). We address this corpus of literary sentences in order to evaluate algorithms of sentiment classication. We have constitute it by manually classifying its sentences in ve emotions: Love, Fear, Happiness, Anger and Sadness/Pain. We also present some baseline classication algorithms applied on our corpus. The LiSSS corpus will be available to the community as a free resource to evaluate or create CC algorithms.

The Verb “ha” in Laki Language from the Perspective of the Head-complement Parameter; A Typological Approach

The present article examined the function of one of Greenberg's implicational universals in the Laki language from a typological point of view and studied the word order in sentences with adposition in this language. In data analysis, the unique function of the verb “ha” became the main focus of the research. The analyses illustrated that, unlike other verbs of this language, in the sentences with adposition, in some grammatical features, this verb has the character of verb-final. In order to study this phenomenon, the article first identified and determined different linguistic elements that are the source of this unique function in different contexts. Then, referring to some important explanations of language typology, it explained the cause of this linguistic phenomenon and indicated that some motivation or forces are involved in explaining the different behavior of the verb “ha”.

Determining the importance of sentence position for automatic text summarization

The methods of Automatic Extractive Summarization (AES) uses the features of the sentences of the original text to extract the most important information that will be considered in summary. It is known that the first sentences of the text are more relevant than the rest of the text (this heuristic is called baseline), so the position of the sentence (in reverse order) is used to determine its relevance, which means that the last sentences have practically no possibility of being selected. In this paper, we present a way to soften the importance of sentences according to the position. The comprehensive tests were done on one of the best AES methods using the bag of words and n-grams models with the with DUC02 and DUC01 data sets to determine the importance of sentences.

METHOD OF NAHWU IN ARABIC LEARNING

Language is very important and the impression that Nahwu is a difficult science to learn, especially by Muslims. As one of the basic sciences in Arabic, Nahwu's science cannot be ignored because without Nahwu's knowledge, Arabic will become chaotic and the order of words and sentences will be disorganized. Therefore, in learning Arabic, it is important to know Nahwu's knowledge, even though this method of teaching science is quite widely practiced by nahwu teachers, but students continue to face difficulties in learning it. Therefore, it is necessary to use suitable teaching methods and appropriate steps and subject matter that must be prioritized to be taught to students, so as to facilitate them in learning Nahwu science. The function of the learning method is one tool to achieve the goal. By using methods accurately the teacher will be able to achieve the learning objectives. When goals are formulated so that students have certain skills, the methods used must be adapted to the goals. Language learning methods, including Arabic, have evolved over time along with the development of the underlying theories, the results of research and experimentation in language teaching, as well as the development of the demands of the community's needs in the language field.

Psychometric Analysis of the Prospective and Retrospective Memory Questionnaire

Para poder cuantificar e investigar científicamente las quejas mnésicas de los pacientes, se hace necesario contar con un instrumento adaptado y que presente análisis psicométricos adecuados. El objetivo del presente trabajo fue estudiar propiedades psicométricas de una versión argentina del Cuestionario de Memoria Prospectiva y Retrospectiva. Para ello se administró el Cuestionario de Memoria Prospectiva y Retrospectiva de forma individual a 192 participantes sanos con más de 27 puntos en el Mini Mental State Examination. La media de edad fue de 39.67 años (DE = 12.3). La media de escolaridad fue de 14.5 años (DE = 2.72). A un subgrupo de participantes (n = 45) denominado Subgrupo A, también se les administraron pruebas de memoria prospectiva y retrospectiva. El Índice Global del Cuestionario presentó una distribución normal. Según el análisis factorial exploratorio se estableció la extracción de un factor que explicó el 35.19 % de la varianza. El coeficiente α de Cronbach fue de .87. La confiabilidad estimada por el método de la división por mitades fue de .73 y de .84 luego de la corrección con la fórmula de Spearman-Brown. No hubo correlación significativa entre las respuestas del cuestionario y los test de memoria retro y prospectiva en el subgrupo A. Estos resultados permiten concluir que el Cuestionario de Memoria Prospectiva y Retrospectiva presenta adecuados índices de confiabilidad y una estructura de un solo factor. Si bien no se asocia con el rendimiento objetivo en pruebas de memoria, muestra ser apropiado para el registro de las quejas subjetivas de los pacientes en la región de estudio.

Sentence Embedding Based Semantic Clustering Approach for Discussion Thread Summarization

Huge data on the web come from discussion forums, which contain millions of threads. Discussion threads are a valuable source of knowledge for Internet users, as they have information about numerous topics. The discussion thread related to single topic comprises a huge number of reply posts, which makes it hard for the forum users to scan all the replies and determine the most relevant replies in the thread. At the same time, it is also hard for the forum users to manually summarize the bulk of reply posts in order to get the gist of discussion thread. Thus, automatically extracting the most relevant replies from discussion thread and combining them to form a summary are a challenging task. With this motivation behind, this study has proposed a sentence embedding based clustering approach for discussion thread summarization. The proposed approach works in the following fashion: At first, word2vec model is employed to represent reply sentences in the discussion thread through sentence embeddings/sentence vectors. Next, K-medoid clustering algorithm is applied to group semantically similar reply sentences in order to reduce the overlapping reply sentences. Finally, different quality text features are utilized to rank the reply sentences in different clusters, and then the high-ranked reply sentences are picked out from all clusters to form the thread summary. Two standard forum datasets are used to assess the effectiveness of the suggested approach. Empirical results confirm that the proposed sentence based clustering approach performed superior in comparison to other summarization methods in the context of mean precision, recall, and F-measure.

Paraphrase thought: Sentence embedding module imitating human language recognition

Sentence embedding is an important research topic in natural language processing. It is essential to generate a good embedding vector that fully reflects the semantic meaning of a sentence in order to achieve an enhanced performance for various natural language processing tasks, such as machine translation and document classification. Thus far, various sentence embedding models have been proposed, and their feasibility has been demonstrated through good performances on tasks following embedding, such as sentiment analysis and sentence classification. However, because the performances of sentence classification and sentiment analysis can be enhanced by using a simple sentence representation method, it is not sufficient to claim that these models fully reflect the meanings of sentences based on good performances for such tasks. In this paper, inspired by human language recognition, we propose the following concept of semantic coherence, which should be satisfied for a good sentence embedding method: similar sentences should be located close to each other in the embedding space. Then, we propose the Paraphrase-Thought (P-thought) model to pursue semantic coherence as much as possible. Experimental results on three paraphrase identification datasets (MS COCO, STS benchmark, SICK) show that the P-thought models outperform the benchmarked sentence embedding methods.

Auditory neural tracking and lexical processing of speech in noise: Masker type, spatial location, and language experience.

The present study investigated how single-talker and babble maskers affect auditory and lexical processing during native (L1) and non-native (L2) speech recognition. Electroencephalogram (EEG) recordings were made while L1 and L2 (Korean) English speakers listened to sentences in the presence of single-talker and babble maskers that were colocated or spatially separated from the target. The predictability of the sentences was manipulated to measure lexical-semantic processing (N400), and selective auditory processing of the target was assessed using neural tracking measures. The results demonstrate that intelligible single-talker maskers cause listeners to attend more to the semantic content of the targets (i.e., greater context-related N400 changes) than when targets are in babble, and that listeners track the acoustics of the target less accurately with single-talker maskers. L1 and L2 listeners both modulated their processing in this way, although L2 listeners had more difficulty with the materials overall (i.e., lower behavioral accuracy, less context-related N400 variation, more listening effort). The results demonstrate that auditory and lexical processing can be simultaneously assessed within a naturalistic speech listening task, and listeners can adjust lexical processing to more strongly track the meaning of a sentence in order to help ignore competing lexical content.

Relative Clause Formation in Akan Proverbs and Sentences: Similarities and Differences

This paper discusses relative clause formation in Akan proverbs and normal sentences with particular attention to their similarities and differences. It explores the comparison of the relative clauses in Akan sentences and other specialized genres such as the proverbs. The paper further analyzes the relative clause occurring in both sentence and proverb structures in order to establish sameness and dichotomy in the syntactic uniqueness in both structures. Purposive sampling technique was employed to select the proverbs for this study. In all, twenty-three (23) proverbs were selected for the study. The study adopted the functional grammar approach in the analysis. The study revealed that the relative clause formation in some Akan proverbs and Akan normal sentences has both overt and covert antecedent noun phrases (ANPs). The headless antecedent noun phrase which is seen as a pronominal also undergoes binary mutation in order to account for the antecedent noun phrase and the relativizer which introduces the relative clause. There are also differences in the syntactic positions of the relative clause more especially the sentence structure type. Finally, there is a difference in the syntactic position of the resumptive pronouns in both structures.

AL-ĀYĀT AL-QUR’ĀNIYYAH ‘ALĀ ḌAU’ ‘ILM AL-AṢWĀT WA AṠARUHA FI AL-MA’NĀ

&#x0D; This paper deals with a very specific problem in term of the relationship between sound and its meaning in the Qur’an. As a scripture revealed with Arabic language as its medium, the Qur’an often uses some words or sentences that have an intimate relation between its meaning and the way of its expression. It means that the sounds which construct those words or sentences have a huge rule to determine meaning, and therefore, a single word or sentence which is expressed by using different voices may produce different meaning. This paper shows that the Qur’an has a very intimate relation between sounds which construct words or sentences and their meaning. It covers some parts of segmental and suprasegmental phonemes discussion in linguistics tradition, including the preference of phonemes, intonation, stress, juncture and so on. This research based on library research, a research proceed by gathering some facts from various books, articles, and other literatures related to the subject. This research combines semantic and phonological approach with analytic description method. From this research, it is found that the words or sentences of the Qur’an have some ways to express its voices or phonemes which construct words and sentences in order to show certain meaning. It means that some words or sentences of the Qur’an produce certain meaning based on the preference of its phonemes or voices.

Jutustajateksti muutlikkus Fjodor Dostojevski romaani „Vennad Karamazovid“ eestikeelsetes tõlgetes / Changeability of the narrator’s text in the Estonian translations of Fyodor Dostoyevsky's novel The Brothers Karamazov

Jutustajateksti muutlikkus Fjodor Dostojevski romaani „Vennad Karamazovid“ eestikeelsetes tõlgetes / Changeability of the narrator’s text in the Estonian translations of Fyodor Dostoyevsky's novel The Brothers Karamazov

Modern Multi-Document Text Summarization Techniques

Text Summarization is the technique in which the source document is simplified, valuable information is distilled and an abridged version is produced. Over the last decade, the focus has shifted from single document to multi-document summarization and despite significant progress in the domain, challenges such as sentence ordering and fluency remain. In this paper, a thorough comparison of the several multi-document text summarization techniques such as Machine Learning based, Graph based, Game-Theory based and more has been presented. This paper in its entirety condenses and interprets the numerous approaches, merits and limitations of these techniques. The Benchmark datasets of this domain and their features have also been examined. This survey aims to distinguish the various summarization algorithms based on properties that prove to be valuable in the generation of highly consistent, rational, summaries with reduced redundancy and information richness. The conclusions presented by this paper can be utilized to identify the advantages of these papers which will help future researchers in their study of this domain and ensure the provision of important data for further analysis in a more systematic and comprehensive manner. With the aid of this paper, researchers can identify the areas that present some scope for improvement and thereafter come up with novel or possibly hybrid techniques in Multi-Document Summarization.