Bibliografie tematiche / Churu language

Letteratura scientifica selezionata sul tema "Churu language"

Autore: Grafiati
Pubblicato: 25 luglio 2024
Ultima modifica: 31 luglio 2024

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Articoli di riviste sul tema "Churu language"

1

Cooper, Ilay. "The painted walls of Churu, Jhunjhunu and Sikar districts of Rajasthan". South Asian Studies 2, n. 1 (gennaio 1986): 21–35. http://dx.doi.org/10.1080/02666030.1986.9628342.

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Abhinav S. Thorat, Et al. "Optimizing Churn Identification in Telecommunications Using Natural Language Processing and XG Boost Machine Learning Paradigm". International Journal on Recent and Innovation Trends in Computing and Communication 11, n. 9 (5 novembre 2023): 4226–32. http://dx.doi.org/10.17762/ijritcc.v11i9.9873.

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With the increasing competition in the telecom sector, accurate churn prediction has become indispensable for service providers seeking to retain customers. This research paper introduces a novel approach that combines Machine Learning (ML) and Natural Language Processing (NLP) and specifically leveraging the XGBoost algorithm, to enhance the precision and efficiency of churn prediction in the telecom industry. The integration of NLP enables the extraction of meaningful insights from diverse data sources, while XGBoost, a powerful gradient boosting algorithm, is employed to build a robust predictive model for identifying potential churners. A machine learning method called the XGBoost churn prediction model is utilized in the telecom industry to forecast client churn. To construct a predictive model that can precisely identify consumers prone to churn, XGBoost is essentially an ensemble method based on gradient-enhanced trees. Several telecom carriers have used this model to understand their consumers better and identify issues that can contribute to churn. It has been used to predict churn in the telecom sector accurately. The model has been tested for accuracy and effectiveness in identifying factors and forecasting customer attrition. These evaluations' findings indicate that the XGBoost model is a trustworthy and precise method for forecasting customer attrition in the telecom industry.
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Kahnami, Leila, Julia Young, Jason Brophy, Lena Serghides, Ari Bitnun e Mary Lou Smith. "59 Perinatal Risk Factors and Cognitive Outcomes in Children HIV-Exposed, Uninfected". Journal of the International Neuropsychological Society 29, s1 (novembre 2023): 55–56. http://dx.doi.org/10.1017/s1355617723001418.

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Objective:Children who are HIV-exposed uninfected (CHEU) are at risk of neurodevelopmental impairments due to perinatal HIV and antiretroviral therapy exposure as well as additional health and psychosocial burdens. There is limited understanding of the impact of perinatal risk factors on long-term outcomes of CHEU. The present study investigated the association between perinatal risk factors and the intellectual and language abilities in CHEU and children who are HIV-unexposed uninfected (CHUU).Participants and Methods:CHEU and CHUU, 6 to 10 years, of age underwent neurodevelopmental assessments through the Kids Imaging and Neurocognitive Development (KIND) study at the Hospital for Sick Children in Toronto, Canada between January 2020 and August 2022. CHUU were recruited from the community with similar sociodemographic backgrounds based on residential area in Toronto and parental income levels. Measures of Full-Scale IQ (FSIQ), Verbal Comprehension (VCI), Visual Spatial skills (VSI), Fluid Reasoning (FRI), Working Memory (WMI), and Processing Speed (PSI) were evaluated with the Wechsler Intelligence Scale for Children - Fifth Edition. Core Language, Receptive Language, and Expressive Language skills were assessed with the Clinical Evaluation of Language Fundamentals - Fifth Edition. Perinatal risk factors included birthweight, birth complications (e.g., premature rupture of membranes, jaundice, etc.), maternal smoking and alcohol use during pregnancy, and NICU admission. Analyses of variance and chi-square tests were performed to investigate group differences and multiple regression analyses tested the relation between neurodevelopmental measures and birth factors. Significance was held at p <0.05.Results:36 CHEU (21 female, 8.74 ±1.56 years) and 26 CHUU (12 female, 8.53 ±1.50 years) children were included. For both groups, mean standardized scores of the cognitive abilities assessed were in the average range. CHEU had significantly lower birth weight than CHUU, but there were no differences between these groups with respect to maternal smoking and alcohol use, birth complications or NICU admission. There were no between group differences identified for the intellectual and language abilities. In the CHEU group, birthweight was significantly associated with lower VCI, WMI, and expressive language. In the CHUU group, prenatal alcohol and smoking exposure was associated with lower VCI scores. Birth complications were associated with lower WMI, PSI, and FSIQ scores.Conclusions:In this interim analysis, perinatal risk factors impacted neurodevelopmental outcomes of CHEU and CHUU differently. While the groups did not differ in frequency of birth complications and maternal smoking and alcohol use, these factors negatively impacted aspects of intellectual ability in the CHUU group. CHEU with lower birthweight are at greater risk of working memory and language difficulties, supporting the need for early interventions and close neuropsychological follow-up of this population throughout childhood.
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Almuqren, Latifah, Fatma S. Alrayes e Alexandra I. Cristea. "An Empirical Study on Customer Churn Behaviours Prediction Using Arabic Twitter Mining Approach". Future Internet 13, n. 7 (5 luglio 2021): 175. http://dx.doi.org/10.3390/fi13070175.

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With the rising growth of the telecommunication industry, the customer churn problem has grown in significance as well. One of the most critical challenges in the data and voice telecommunication service industry is retaining customers, thus reducing customer churn by increasing customer satisfaction. Telecom companies have depended on historical customer data to measure customer churn. However, historical data does not reveal current customer satisfaction or future likeliness to switch between telecom companies. The related research reveals that many studies have focused on developing churner prediction models based on historical data. These models face delay issues and lack timelines for targeting customers in real-time. In addition, these models lack the ability to tap into Arabic language social media for real-time analysis. As a result, the design of a customer churn model based on real-time analytics is needed. Therefore, this study offers a new approach to using social media mining to predict customer churn in the telecommunication field. This represents the first work using Arabic Twitter mining to predict churn in Saudi Telecom companies. The newly proposed method proved its efficiency based on various standard metrics and based on a comparison with the ground-truth actual outcomes provided by a telecom company.
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Malleswari, M., R. J. Manira, Praveen Kumar e Murugan . "Comparative Analysis of Machine Learning Techniques to Identify Churn for Telecom Data". International Journal of Engineering & Technology 7, n. 3.34 (1 settembre 2018): 291. http://dx.doi.org/10.14419/ijet.v7i3.34.19210.

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Big data analytics has been the focus for large scale data processing. Machine learning and Big data has great future in prediction. Churn prediction is one of the sub domain of big data. Preventing customer attrition especially in telecom is the advantage of churn prediction. Churn prediction is a day-to-day affair involving millions. So a solution to prevent customer attrition can save a lot. This paper propose to do comparison of three machine learning techniques Decision tree algorithm, Random Forest algorithm and Gradient Boosted tree algorithm using Apache Spark. Apache Spark is a data processing engine used in big data which provides in-memory processing so that the processing speed is higher. The analysis is made by extracting the features of the data set and training the model. Scala is a programming language that combines both object oriented and functional programming and so a powerful programming language. The analysis is implemented using Apache Spark and modelling is done using scala ML. The accuracy of Decision tree model came out as 86%, Random Forest model is 87% and Gradient Boosted tree is 85%.
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Sonawane, Vijay R., Abhinav S. Thorat, Jaya R. Suryawanshi, Ravindra G. Dabhade, Megharani Patil e Bhausaheb Musmade. "Churn Identification and Prediction from a Large-Scale Telecommunication Dataset Using NLP". International Journal on Recent and Innovation Trends in Computing and Communication 11, n. 7 (1 settembre 2023): 39–46. http://dx.doi.org/10.17762/ijritcc.v11i7.7828.

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The identification of customer churn is a major issue for large telecom businesses. In order to manage the data of current customers as well as acquire and manage new customers, every day, a substantial volume of data gets generated. Therefore, it's crucial to identify the causes of client churn so that the appropriate steps can be taken to lower it. Numerous researchers have already discussed their efforts to combine static and dynamic approaches in order to reduce churn in big data sets, but these systems still have many issues when it comes to actually identifying churn. In this paper, we suggested two methods, the first of which is churn identification and using Natural Language Processing (NLP) methods and machine learning techniques, we make predictions based on a vast telecommunication data set. The NLP process involves data pre-processing, normalization, feature extraction, and feature selection. For feature extraction, we employ unique techniques like TF-IDF, Stanford NLP, and occurrence correlation methods, have been suggested. Throughout the lesson, a machine learning classification algorithm is used for training and testing. Finally, the system employs a variety of cross validation techniques and training and evaluating Machine learning algorithms. The experimental analysis shows the system's efficacy and accuracy.
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Green, Freddy, Christopher du Plooy, Andrea M. Rehman, Raymond T. Nhapi, Marilyn T. Lake, Whitney Barnett, Nadia Hoffman et al. "Language outcomes of preschool children who are HIV-exposed uninfected: An analysis of a South African cohort". PLOS ONE 19, n. 4 (10 aprile 2024): e0297471. http://dx.doi.org/10.1371/journal.pone.0297471.

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Introduction There are approximately 16 million children who are HIV-exposed and uninfected (CHEU) worldwide. Studies suggest that CHEU are at risk for developmental impairment in infancy, particularly in language domains. However, there is limited research examining neurocognitive function in CHEU older than 2 years, including important pre-school years. This study aimed to investigate associations between HIV exposure without infection and neurocognitive outcomes and to determine risk factors for neurodevelopment in CHEU at age 3–4 years. Methods The Drakenstein Child Health Study is a South African population-based birth cohort which enrolled women in pregnancy with ongoing follow up. Neurocognitive outcomes were assessed in children at 3.5 years by trained assessors blinded to HIV status including general cognitive function, language, and memory, measured using the Kaufmann Assessment Battery for Children, Second Edition (KABC-II). Data were compared between CHEU and children who were HIV-unexposed uninfected (CHUU) using multivariable logistic and linear regression, including testing for effect modification; sex-stratified risk factor analyses were performed. Results A total of 497 children were included (97 [20%] CHEU; 400 [80%] CHUU; 50% male), with a mean age of 3.5 years (range 3.4–3.6). Groups had similar birth and household characteristics, although mothers of CHEU were older, on average. Overall, CHEU had lower expressive language scores compared to CHUU on unadjusted and adjusted analyses (effect size: -0.23 [95% CI -0.45, -0.01]). There were no group differences in general cognitive or memory function (p>0.05). On sex-stratified analyses, male CHEU were found to have higher odds of suboptimal cognitive development compared to male CHUU (aOR 2.28 [95% CI 1.06, 4.87], p = 0.034). Several other factors including birthweight, maternal education, maternal ART duration and HIV viral load during pregnancy were associated with cognition, memory, or expressive language outcomes in CHEU, dependent on child sex. Interpretation The findings suggest that perinatal HIV exposure continues to be associated with impaired language development across the preschool years, highlighting the importance of targeting early interventions to optimise language outcomes. Further, the results suggest the importance of demographic, biological and HIV-related variables influencing developmental outcomes in CHEU. The greater risk of suboptimal cognitive development in male CHEU requires investigation around sex-specific mechanisms.
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Zatonatska, Tetiana, Yana Fareniuk e Viktor Shpyrko. "Churn Rate Modeling for Telecommunication Operators Using Data Science Methods". Marketing and Management of Innovations 14, n. 2 (2023): 163–73. http://dx.doi.org/10.21272/mmi.2023.2-15.

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The telecommunication company functioned in the market with extremely high competitiveness. Attracting new customers needs 5-10 times more expenses than maintaining an existing one. As a result, effective customer churn management and analysis of the reasons for customer churn are vital tasks for telecommunication operators. As a result, predicting subscriber churn by switching on the competitors becomes very important. Data Science and machine learning create enormous opportunities for solving this task to evaluate customer satisfaction with company services, determine factors that cause disappointment, and forecast which clients are at a greater risk of abandoning and changing services suppliers. A company that implements data analysis and modelling to develop customer churn prediction models has an opportunity to improve customer churn management and increase business results. The purposes of the research are the application of machine learning models for a telecommunications company, in particular, the construction of models for predicting the user churn rate and proving that Data Science models and machine learning are high-quality and effective tools for solving the tasks of forecasting the key marketing metrics of a telecommunications company. Based on the example of Telco, the article contains the results of the implementation of various models for classification, such as logistic regression, Random Forest, SVM, and XGBoost, using Python programming language. All models are characterised by high quality (the general accuracy is over 80%). So, the paper demonstrates the feasibility and possibility of implementing the model to classify customers in the future to anticipate subscriber churn (clients who may abandon the company’s services) and minimise consumer outflow based on this. The main factors influencing customer churn are established, which is basic information for further forecasting client outflow. Customer outflow prediction models implementation will help to reduce customer churn and maintain their loyalty. The research results can be useful for optimising marketing activity of managing the outflow of consumers of companies on the telecommunication market by developing effective decisions based on data and improving the mathematical methodology of forecasting the outflow of consumers. Therefore, the study’s main theoretical and practical achievements are to develop an efficient forecasting tool for enterprises to control outflow risks and to enrich the research on data analysis and Data Science methodology to identify essential factors that determine the propensity of customers to churn.
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Li, Feng, Yujun Hu e Lingling Wang. "Case-Based Teaching for Python Language Under the Background of Big Data". WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS 19 (6 luglio 2022): 153–60. http://dx.doi.org/10.37394/23209.2022.19.15.

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This paper proposes a new teaching method for the Python language programming course, which can better enable students to understand and use in the background of big data. Python is an open-source programming language with a community-based model. In this paper, firstly, various functions are described in Python Language. Additionally, different application areas are presented in this paper, such as transportation logistics, urban management, biomedical field, smart power grid, energy field, and commercial field. Finally, bank customer churn as case-based teaching is introduced can improve the students’ confidence in their future studies.
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Scharf, Peter M. "Pāṇini Re-interpreted. By Charu Deva Shastri". Historiographia Linguistica 18, n. 2-3 (1 gennaio 1991): 399–402. http://dx.doi.org/10.1075/hl.18.2-3.20sch.

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Tesi sul tema "Churu language"

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Joshi, Apoorva. "Trajectory-based methods to predict user churn in online health communities". Thesis, University of Iowa, 2018. https://ir.uiowa.edu/etd/6152.

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Online Health Communities (OHCs) have positively disrupted the modern global healthcare system as patients and caregivers are interacting online with similar peers to improve quality of their life. Social support is the pillar of OHCs and, hence, analyzing the different types of social support activities contributes to a better understanding and prediction of future user engagement in OHCs. This thesis used data from a popular OHC, called Breastcancer.org, to first classify user posts in the community into the different categories of social support using Word2Vec for language processing and six different classifiers were explored, resulting in the conclusion that Random Forest was the best approach for classification of the user posts. This exercise helped identify the different types of social support activities that users participate in and also detect the most common type of social support activity among users in the community. Thereafter, three trajectory-based methods were proposed and implemented to predict user churn (attrition) from the OHC. Comparison of the proposed trajectory-based methods with two non-trajectory-based benchmark methods helped establish that user trajectories, which represent the month-to-month change in the type of social support activity of users are effective pointers for user churn from the community. The results and findings from this thesis could help OHC managers better understand the needs of users in the community and take necessary steps to improve user retention and community management.
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Chur-Hansen, Anna. "An investigation of the English language proficiency and academic and clinical performance of University of Adelaide Medical School undergraduates / Anna Chur-Hansen". Thesis, 1998. http://hdl.handle.net/2440/19261.

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Author's revision to her thesis is in envelope on back page.
Copies of author's previously published works inserted.
Bibliography: leaves 472-502.
xvi, 502 leaves : ill. ; 30 cm.
The first aim of this thesis is to investigate the English language proficiency of several cohorts of undergraduate medical students enrolled at the University of Adelaide, South Australia, employing both quantitative and qualitative measures. The second is to consider the influence of students' English language proficiency upon their academic and clinical performance. The thesis puts forward recommendations for future teaching and learning strategies and research opportunities in the medical education arena.
Thesis (Ph.D.)--University of Adelaide, Dept. of Psychiatry, 1998
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Libri sul tema "Churu language"

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Cimarrón, Juan Bautista Añapa. Chachi: Lala'cha'kuinda, naa na chumu juhua ju'bain, naa chaibain. Esmeraldas, Ecuador: Indio Hilfe Ediciones, 2003.

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2

Ludwig, Andreas W. Die deutsche Urkundensprache Churs im 13. und 14. Jahrhundert: Graphemik, Phonologie und Morphologie. Berlin: W. de Gruyter, 1989.

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3

O, So-jŏng. Oegugin ŭi Hanʼgugŏ haksŭp esŏ onŭn munjechŏm e taehan yŏnʼgu: Churo Yŏngŏkwŏn oegugin ŭl chungsim ŭro. [Korea: s.n.], 1986.

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4

Graubünden, Institut für Kulturforschung, a cura di. Schrift, Schriftgebrauch und Textsorten im frühmittelalterlichen Churrätien: Vorträge des internationalen Kolloquiums vom 18. bis 20. Mai 2006 im Rätischen Museum in Chur. Basel: Schwabe, 2008.

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5

H, McLeod Susan, e Soven Margot, a cura di. Writing across the curriculum: A guide to developing programs. Newbury Park, Calif: Sage Publications, 1992.

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Ryder, Randall J. Reading and learning in content areas. 3a ed. New York: J. Wiley & Sons, 2003.

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Ryder, Randall J. Reading and learning in content areas. New York: Merrill, 1994.

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Chubu hogen ko (Nihon Retto hogen sosho). Yumani Shobo, 1996.

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Ludwig, Andreas W. Die Deutsche Urkundensprache Churs Im 13. und 14. Jahrhundert: Graphemik, Phonologie und Morphologie. de Gruyter GmbH, Walter, 2011.

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10

Churo diccionario chapaco: Modismos, vulgarismos y metaplasmos de la región. Tarija, Bolivia: Equipo Editorial, 2008.

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Capitoli di libri sul tema "Churu language"

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"Poll of Chur students concerning their language background". In Languages in Contact, 355–68. Amsterdam: John Benjamins Publishing Company, 2011. http://dx.doi.org/10.1075/z.166.16app.

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Ramsey, Gregory W., e Sanjay Bapna. "Predicting Patient Turnover". In Computational Methods and Algorithms for Medicine and Optimized Clinical Practice, 108–32. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8244-1.ch006.

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Predicting patient turnover within health services is beneficial for resource planning. In this chapter, patient turnover is viewed as a form of customer churn. As such, the authors examine whether free-form notes are useful for solving the classification problem typically associated with customer churn. The authors show that classifiers which incorporate free-form notes, using natural language processing techniques, are up to 11% more accurate than classifiers that are solely developed using structured data. In addition, the authors show that free-form notes aggregated for each account perform better than treating each note separately. It is suggested that hospitals and chronic disease management clinics can use structured data and free-form notes from electronic health records to predict which patients are likely to cease receiving care from their facilities. Classification tools for predicting patient churn are of interest to hospital administrators; such information can aid in resource planning and facilitates smoother handoffs between care providers.
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Plumb, May Helena, Alejandra Dubcovsky, Moisés García Guzmán, Brook Danielle Lillehaugen e Felipe H. Lopez. "Growing a Bigger Linguistics Through a Zapotec Agenda". In Decolonizing Linguistics, 363–80. Oxford University PressNew York, 2024. http://dx.doi.org/10.1093/oso/9780197755259.003.0017.

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Abstract The Ticha Project is a digital endeavor focused on knowledge repatriation and language reclamation, guided by a Zapotec agenda that centers Zapotec goals and authority. This decolonial practice forges a collaborative, reciprocal scholarship where Zapotec and non-Native experts work together in pursuit of overlapping goals, forming an interdisciplinary community which resists the individualism of academia and draws strength from an inclusive Zapotec collective. In this chapter the authors detail Ticha’s working philosophy through two interrelated projects: (1) Caseidyneën Saën, an e-book of pedagogical materials focused on Colonial Zapotec documents, and (2) the Conversatorios, workshops led by and for Zapotec individuals that serve as important sites of Indigenous knowledge production. The authors challenge readers to find their own community-centered agenda and to grow a bigger linguistics by embracing deeply localized research. Ticha Project na teiby zeiny guieb lo bi (ni na “digital”) ni yzicy xcal nanën quën xtizhën na. Rcazën gyenën teiby ni izhiu par ra Bunyza, ra ni bsanne ra xauzanën, Bunyzado, danoën. Rcazën gyicy ni nanën ni bzuca Dizhtily loën, chiru danoën Bunyza gyieneën gualnezh quën ra buny nan ni queity na ra Bunyza gacneën saën gyenën ropta rseinyën, chiru gyeinychieën teiby guezh nan ni sutyep lo ni rseidyrëng yu rseidy sutyepneën saën rataën. Lo teiby xnez gyets xte Ticha re rniën xa na xjab xtenën, chiru ygwiën lo styop ra zeiny ni cagyienyën ni ngabne sani: (1) Caseidyneën Saën na teiby gyets rseidy ni na teiby xnez gyets guieb lo bi (ni na “e-book”) ni rseidy nazh ra gyets Dizhzado, chiru (2) chi bdop ra Bunyza bgwe dizh nii bzub xliet xa na gal nan xte ra Bunyza. Ra ni cagyual nde rnabën load ual gacbe xii rcaz lazhad ganad tyen chile subru guecy ni racbe buny yu rseidy nezbag laty gunyberuad xai na lazhad.
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Sroka, Jakub. "Wujek GOOGLE ma dziś próbę chóru – o ludycznych technikach wprowadzania i utrwalania słownictwa na lekcjach języka obcego". In Ludyczność w (glotto)dydaktyce. Wydawnictwo Uniwersytetu Łódzkiego, 2020. http://dx.doi.org/10.18778/8220-114.7.07.

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The article presents the ludic technics the author uses during introducing and consolidating vocabulary in a foreign language classes. It provides a description of what these methods are about, how they were created, under what circumstances they could be used and what didactics could achieve thanks to them. The Conclusions show relevant reflections about using several introducing and consolidating vocabulary technics, comments and suggestions for teachers that will help them in the implementation task with the use of chosen methods.
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"Fire in the house". In Stirring the Pot of Haitian History, a cura di Mariana Past e Benjamin Hebblethwaite, 39–60. Liverpool University Press, 2021. http://dx.doi.org/10.3828/liverpool/9781800859678.003.0004.

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This chapter explains how the ceremony at Bwa Kayiman—the Vodou ceremony of August 22, 1791, that set the Haitian revolution into motion—was able to come about. The ruling class of powerful landowners and French commissioners was theoretically unified; the class of free people—whether white, mixed race or black—was supposed to be in their fold so that their profiteering would churn on undisturbed. The revolution exploded when the ruling class could no longer balance competing interests and when the lower classes refused to participate in the conspiracy any longer. Trouillot traces the roots of discontent in Saint-Domingue to the class struggles between the French aristocracy, bourgeoisie and workers in eighteenth century enlightenment France. He also sheds light on the reverberations that French class conflicts had in Saint-Domingue. In the late 1780s, the local landowners began clamoring for free market control over where their products could be sold. France had exclusive purchasing privileges over the colony’s output. By 1790, this major rift emerged between French commissioners and the local landowners. At the same time, a deep rupture appeared between whites and free people of mixed race when racist whites rejected Ogé and Chavannes’s demands of greater equality for mixed race people. Instead of cultivating their coalition with mixed race people, the ruling class sent 1,500 white soldiers and 3,000 black recruits to crush the movement of the people of mixed race. The ruling class’s traditional coalition was severed in various places. The leaders of the enslaved population saw the power they had when properly armed; they detected the conflict among the whites and the whites versus mixed race people; and they received and transmitted the exciting news of equality proclaimed by the rising French revolutionaries. Underneath this political quicksand, the enslaved population had established the cornerstones of an indigenous culture: farming, Vodou religion and the Creole language. The small plots that enslaved people were encouraged to cultivate for food and the small income they generated created a passion for agrarian independence. Vodou gave enslaved people the conviction they needed to fight, as well as a means of organization and cultural preservation. The Creole language provided a foundation for a common culture. The chapter closes with an analysis of the maroon culture of runaways and rebels and why it was unable to secure widespread independence. Finally, it introduces the geographic and demographic realities that favored an uprising in the northern plains of Haiti.
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Atti di convegni sul tema "Churu language"

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Hidey, Christopher, e Sarthak Sarthak. "Compute-Efficient Churn Reduction for Conversational Agents". In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track. Stroudsburg, PA, USA: Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.emnlp-industry.28.

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Abbet, Christian, Meryem M’hamdi, Athanasios Giannakopoulos, Robert West, Andreea Hossmann, Michael Baeriswyl e Claudiu Musat. "Churn Intent Detection in Multilingual Chatbot Conversations and Social Media". In Proceedings of the 22nd Conference on Computational Natural Language Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/k18-1016.

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