Syllabic organization and phonetic indices in German stop-lateral clusters

Using articulatory data from five German speakers, we study how segmental sequences under different syllabic organizations respond to perturbations of phonetic parameters in the segments that compose them. Target words contained stop-lateral clusters /bl, gl, kl, pl/ in a word-initial and a cross-word context and were embedded in carrier phrases with different prosodic boundary strengths, i.e., no phrase boundary versus an utterance phrase boundary preceded the target word in the case of word-initial clusters or separated the consonants in the case of cross-word clusters. For word-initial cluster onsets, we find that increasing the lag between two consonants and C1 stop duration leads to earlier vowel initiation and reduced local timing stability across CV and CCV. Furthermore, as the inter-consonantal lag increases, C2 lateral duration decreases. In contrast, for cross-word clusters, increasing the lag between two consonants does not lead to earlier vowel initiation across CV and C#CV and robust local timing stability is maintained across CV and C#CV. Overall, the findings indicate that the effect of phonetic perturbations on the coordination patterns depends on the syllabic organization superimposed on these clusters.

Analisis Metode Representasi Teks Untuk Deteksi Interelasi Kitab Hadis: Systematic Literature Review

Hadith is the second source of reference for Islamic law after the Qur'an, which explains the sentences in the Qur'an which are still global by referring to the provisions of the Prophet Muhammad SAW. Classification of text documents can also be used to overcome the problem of interrelation between the Qur'an and hadith. The problem of interrelation between books of hadith needs to be done because some hadiths in certain hadith books have the same meaning as other hadith books. This study aims to analyze the development of text representation and classification methods suitable to overcome similarity meaning problems in detecting interrelationships between hadith books. The research method used is Systematic Literature Review (SLR) sourced from Google Scholar, Science Direct, and IEEE. There are 42 pieces of literature that have been studied successfully. The results showed that contextual embedding as the newest text representation method considered word context and sentence meaning better than static embedding. As a classification method, the ensemble method has better performance in classifying text documents than using only a single classifier model. Thus, future research can consider using a combination of contextual embedding and ensemble methods to detect interrelationships between books of hadith.

DIAGNOSTICS OF THE DYNAMICS OF THE BASIC CONCEPTIN THE GERMAN LINGUISTIC CULTURE (BASED ON THE BODY OF ORAL TEXTS AND DATA OF THE ASSOCIATIVE EXPERIMENT)

Постановка задачи. Основной задачей исследования является установление динамики содержания базисного концепта Sicherheit (безопасность) в немецкой лингвокультуре. В качестве методов исследования авторы обращаются к анализу дефиниций толковых словарей, анализу сочетаемости исследуемого слова, контекстному анализу, свободному ассоциативному эксперименту. На основе разработанной модели значения авторы сопоставляют лексикографические данные и ассоциативное поле слова-стимула Sicherheit (безопасность) . Результаты. На основе сопоставления полученных данных авторы отмечают, что интегративные признаки, выделенные в сочетаемости лексем и признаки, выделенные в ассоциативном эксперименте, в значительной мере совпадают (‘источники безопасности’, ‘безопасная ситуация в мире / национальная безопасность’, ‘комфорт, стабильность’, ‘личные эмоциональные концепты’, ‘объект / предмет защиты’), хотя и различны в количественном значении. При этом сочетаемость лексемы позволяет говорить о недоверии к возможности стабильной и безопасной ситуации в целом. Однако данные свободного ассоциативного эксперимента, напротив, свидетельствуют об исключительно положительном отношении к исследуемому концепту. Согласно данным корпуса наиболее распространенной категорией является категория уверенность , которая представлена в ассоциативном эксперименте единичной реакцией. Наибольшее количество реакций ассоциативного эксперимента представляют Sicherheit как чувство защищенности от разного вида опасности. Выводы. Для носителей немецкой лингвокультуры концепт Sicherheit (безопасность) понимается как чувство защищенности от опасности, которое могут гарантировать индивиду семья или государственные органы. Гарантом безопасности выступают деньги. Для достижения безопасности необходимо соблюдение различных правил и мер безопасности. Statement of the problem. The aim of the article is to establish the dynamics of the content of the basic concept Sicherheit ( safety ) in German linguistic culture. As the main research methods, the authors turn to the analysis of definitions of explanatory dictionaries, the analysis of the compatibility of the studied word, context analysis, free associative experiment. On the basis of the developed model of meaning, the authors compare the lexicographic data and the associative field of the stimulus word Sicherheit ( safety ). Results. Based on the comparison of the obtained data, the authors note that the integrative features identified in the compatibility of lexemes and the features identified in the associative experiment largely coincide (‘sources of security’, ‘safe situation in the world / national security’, ‘comfort, stability’, ‘personal emotional concepts’, ‘object of protection’, although they are different in quantitative meaning. At the same time, we note that the compatibility of the lexeme allows us to speak of mistrust of the possibility of a stable and safe situation as a whole. However, the data of the free associative experiment, on the contrary, allow us to speak about an extremely positive attitude to the concept under study. According to the corpus, the most common category is the category of confidence, which is represented in the associative experiment by a single reaction. The largest number of reactions in the associative experiment represent Sicherheit as a feeling of protection from various types of danger. Conclusion. For representatives of the German linguistic culture, the concept of Sicherheit ( safety ) is understood as a sense of security from danger, which can be guaranteed to an individual by the family or government authorities. Money is the guarantor of security. To achieve safety, it is necessary to comply with various safety rules and measures.

Analisis Kesalahan dalam Menyelesaikan Soal Cerita Matematika ditinjau dari Gaya Belajar Siswa

This study aims to describe the errors and the causes of errors in solving mathematics word context problem in the topic of absolute value. Based on Newman’s Error Analysis terms of student’s lerning styles. Error analysis must continue to be carried out so that teachers know the types, causes, and solutions to overcome student errors. This type of research is descriptive qualitative.The research subjects of class X MIA 1 SMAN 1 Janapria academic year 2020/2021 were selected by purposive sampling. To deepen the research results, 2 students were selected from each type of learning style. Data collection techniques used are learning style questionnaire, diagnostic tests, and interviews. Data analysis technique used data reduction, data presentation, and conclusion. Based on the results of the data is (i) students with visual learning style and audits mostly made errors in stage of transformation, process skill, and encoding. While students with kinesthetic learning style mostly made errors in stage of comprehension, transformation, process skill, and encoding, (ii) the causes of mistakes for both students with visual, auditory, and kinesthetic learning styles are that students less understanding of the prerequisite lessons, cannot make mathematical models, and not know the steps to solve problems.

Preparing for medical education after the COVID-19 pandemic: insightology in medicine

It is necessary to reflect on the question, “How to prepare for medical education after coronavirus disease 2019 (COVID-19)?” Although we are preparing for the era of Education 4.0 in line with the 4th industrial revolution of artificial intelligence and big data, most measures are focused on the methodologies of transferring knowledge; essential innovation is not being addressed. What is fundamentally needed in medicine is insightful intelligence that can see the invisible. We should not create doctors who only prescribe antispasmodics for abdominal pain, or antiemetic drugs for vomiting. Good clinical reasoning is not based on knowledge alone. Insightology in medicine is based on experience through Bayesian reasoning and imagination through the theory of mind. This refers to diagnosis of the whole, greater than the sum of its parts, by looking at the invisible using the Gestalt strategy. Identifying the missing process that links symptoms is essential. This missing process can be described in one word: context. An accurate diagnosis is possible only by understanding context, which can be done by standing in someone else’s shoes. From the viewpoint of medicine, Education 4.0 is worrisome because people are still clinging to methodology. The subject we should focus on is “human”, not “artificial” intelligence. We should first advance the “insightology in medicine” as a new paradigm, which is the “essence” that will never change even when rare “phenomena” such as the COVID-19 outbreak occur. For this reason, we should focus on teaching insightology in medicine, rather than teaching medical knowledge.

Hatred and trolling detection transliteration framework using hierarchical LSTM in code-mixed social media text

The paper describes the usage of self-learning Hierarchical LSTM technique for classifying hatred and trolling contents in social media code-mixed data. The Hierarchical LSTM-based learning is a novel learning architecture inspired from the neural learning models. The proposed HLSTM model is trained to identify the hatred and trolling words available in social media contents. The proposed HLSTM systems model is equipped with self-learning and predicting mechanism for annotating hatred words in transliteration domain. The Hindi–English data are ordered into Hindi, English, and hatred labels for classification. The mechanism of word embedding and character-embedding features are used here for word representation in the sentence to detect hatred words. The method developed based on HLSTM model helps in recognizing the hatred word context by mining the intention of the user for using that word in the sentence. Wide experiments suggests that the HLSTM-based classification model gives the accuracy of 97.49% when evaluated against the standard parameters like BLSTM, CRF, LR, SVM, Random Forest and Decision Tree models especially when there are some hatred and trolling words in the social media data.

AN EFFICIENT NOVEL APPROACH FOR SOCIETAL COMMUNICATION OF Q&A COMMUNITY SYSTEM USING TOPIC MODELING TECHNIQUES

The emerging trend in technical research is to use customer-generated data collected by community media to probe community opinion and scientific communication on employment and care issues. This review of the collected data, the launch of a question-and-answer social website, is a separate stack for exploring the key factors that influence public preferences for technical knowledge and opinions. by means of a web search engine, topic modeling, and regression data modeling, this study quantified the effect of the response textual and auxiliary functions on the number of votes received with the response. Compared to previous studies based on open estimates, the model results show that Quora users are more likely to only talk about technology. It can fail when the keywords in the query do not match the text content of large documents that contain relevant questions of existing methods, ie. CNNMF and NMF, as well as some restrictions are not enough. Also, users are often not experts and provide ambiguous queries leading to mixed results and encountering problems with existing methods. To address this problem, in this article we propose a Hadoop model, distributed using semantics, non-negative matrix factorization (HDiSANNMF), to find topics for short texts. It effectively incorporates the semantic correlations of the word context into the model, where the semantic connections between words and their context are learned by omitting the grammatical view of the corpus. The researchers are trying to reorganize the main results and present modern techniques for modeling distributed themes to address technologies and platforms with increasing attributes, as well as how much time and space it takes to generate the model. This document briefly describes the structure of public questions and answers around the world and tracks the development of the main topics Housing and employment opportunities for next generation technologies in the world in real time.

A FORGOTTEN CHARACTER OF THE EAST SLAVIC DEMONOLOGY: *КАНТЫСАР (RECONSTRUCTION OF THE FORM AND SEMANTICS OF THE IMAGE)

The paper deals with the etymological analysis of the name of mythological character Царь Хан, from the text of a Ukrainian spell for snake bites. A number of signs encourages to think about, that we deal with the result of division and rethinking of the etymological form *Кантысар, the trace of which is found out in archaic Ukrainian vocabulary of burial ritual. Particularly, here the Lord of Graves, which charges payment with dead for a place under the ground, is mentioned. Further search of the etymological source of this word takes us up to the conclusion about reflection of Alanian *Kanti Sar «Lord of Graves» or «Lord of the Underworld» in the *Кантысар. With taking into account of word context and associated semiotics we can figure out in general terms semantics of character of the *Кантысар and place him on a par with other figures of Slavic demonology, also borrowed from the Iranian source. The adaptation of the stranger mythological figure to the charactersʼ system of Slavic mythology was possible due to functional affinity the *Кантысар to indigenous chthonic personages, identified with the *Кантысар. Сoncomitantly with etymology of the name Кантысар the genesis of an Ukrainian demonic name довгомýд ʻhalf-beast and half-manʼ is defined (< Alanian *dewaga-mand, *dewga-mand ʻobsessed with a daemonʼ).

Profil Kemampuan Komunikasi Matematis Siswa Kelas VIII Pada Penyelesaian Soal Cerita Materi Sistem Persamaan Linear Dua Variabel

This study aims at analyzing students' mathematics communication ability in solving word-context problems in the topic of Linear Equation System with Two Variable and describing students' profiles in each level of mathematics communication ability in solving word-context problems in the topic of Linear Equation System with Two Variable using Polya steps. This study is a descriptive qualitative study involving 20 students of grade 8th. The data collection was conducted by using observation, test, interview, and documentation. The data analysis was conducted in three stages, namely data reduction, data display, and conclusion drawing. The results showed that: (1) Students at the low level of mathematics communication ability were only able to complete some Polya steps. The step of understanding the problem, compiling, and carrying out the plan was done poorly. Whereas the action of checking the answers was not completed. (2) Students at the level of mathematics communication ability can write down steps to understand the problem quite well. However, the stages of devising a plan, carrying out the plan, and re-checking answers cannot be done well. (3) Students at a high level of mathematics communication ability can perform the four steps of Polya even though there are still shortages in doing the calculations to get answers.