Articoli di riviste sul tema "Churu language"

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.

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.

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.

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%.

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.

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.

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.

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.

The beta distribution model has been applied in many different research environments due to the flexibility of its two parameters. In this research, we fit this probabilistic model for mod- eling a recurring problem confronted for many businesses called the customer churn rate (or churn rate). It represents the proportion of customers who cancel their subscriptions after a given time. We use data from a Brazilian media service company to develop the modeling. The parameters are estimated by the maximum likelihood estimation (MLE) technique. Finally, we perform the MLE technique by considering two programming languages; Ox and R.

Analyzing customers’ characteristics and giving the early warning of customer churn based on machine learning algorithms, can help enterprises provide targeted marketing strategies and personalized services, and save a lot of operating costs. Data cleaning, oversampling, data standardization and other preprocessing operations are done on 900,000 telecom customer personal characteristics and historical behavior data set based on Python language. Appropriate model parameters were selected to build BPNN (Back Propagation Neural Network). Random Forest (RF) and Adaboost, the two classic ensemble learning models were introduced, and the Adaboost dual-ensemble learning model with RF as the base learner was put forward. The four models and the other four classical machine learning models-decision tree, naive Bayes, K-Nearest Neighbor (KNN), Support Vector Machine (SVM) were utilized respectively to analyze the customer churn data. The results show that the four models have better performance in terms of recall rate, precision rate, F1 score and other indicators, and the RF-Adaboost dual-ensemble model has the best performance. Among them, the recall rates of BPNN, RF, Adaboost and RF-Adaboost dual-ensemble model on positive samples are respectively 79%, 90%, 89%,93%, the precision rates are 97%, 99%, 98%, 99%, and the F1 scores are 87%, 95%, 94%, 96%. The RF-Adaboost dual-ensemble model has the best performance, and the three indicators are 10%, 1%, and 6% higher than the reference. The prediction results of customer churn provide strong data support for telecom companies to adopt appropriate retention strategies for pre-churn customers and reduce customer churn.

As healthcare costs rise, hospitals are seeking ways to improve operations. This paper examines the usefulness of free-form notes to solve a classification problem commonly associated with customer churn. The authors show that classifiers which incorporate free-form notes, using natural language processing techniques, are up to 9% more accurate than classifiers that are solely developed using structured data. The authors suggest 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 facilitate smoother handoffs between care providers.

Fault prediction is an important research area that aids software development and the maintenance process. It is a field that has been continuously improving its approaches in order to reduce the fault resolution time and effort. With an aim to contribute towards building new approaches for fault prediction, this paper proposes Entropy Churn Metrics (ECM) based on History Complexity Metrics (HCM) and Churn of Source Code Metrics (CHU). The study also compares performance of ECM with that of HCM. The performance of both these metrics is compared for 14 subsystems of 5different software projects: Android, Eclipse, Apache Http Server, Eclipse C/C++ Development Tooling (CDT), and Mozilla Firefox. The study also analyses the software subsystems on three parameters: (i) distribution of faults, (ii) subsystem size, and (iii) programming language, to determine which characteristics of software systems make HCM or ECM more preferred over others.

This paper investigates the syntactic–pragmatic behavior of two expletive-like elements, namely a and chiru, in Fornese and Cilentano, two Romance varieties spoken in Northern and Southern Italy, respectively. We argue that a and chiru are not bona fide expletive subjects but discourse-pragmatic expletives, which mark zero aboutness or the absence of an aboutness referent in an utterance. The investigation of Fornese and Cilentano points towards the existence of a sub-class of null-subject languages where aboutness as a discourse feature must be structurally satisfied by merging an overt or null topic in the syntactic spine of the clause. In the absence of such an element—for example, in thetic clauses—a discourse-pragmatic expletive is externally merged as a last-resort strategy to satisfy [uAboutness]. We argue that, in these null-subject languages, the satisfaction of the discourse feature [uAboutness] is an LF requirement, which is subject to a parametric choice. We show that, in Fornese, “default” [aboutness] is satisfied in SubjP, which is the canonical syntactic position for overt subjects within a cartographic approach. In Cilentano, on the other hand, [aboutness] is satisfied in a higher position within the C-domain, namely ShiftP, the canonical syntactic position that hosts overt aboutness/shift topics.

Fabrizio Barozzi welcomes us in his office in the Eixample, a characteristic space of the city. An intense activity is perceived in an environment that breathes tranquility and order at the same time. In the waiting area, a sequence of photographs define the work process of the Chur museum, taken from the same point inside the work at different moments of it. Accurate and beautiful. Fabrizio Barozzi nos recibe en su despacho en el Ensanche Barcelonés. Un espacio característico de la ciudad con sus techos altos, luz natural, carpinterías de madera, suelos hidráulicos... Se percibe una intensa actividad en un ambiente que respira a la vez tranquilidad y orden. En la zona de espera una secuencia de fotografías definen el proceso de obra del museo de Chur, realizadas desde un mismo punto en el interior de la obra en distintos momentos de la misma. Precisas y hermosas. La conversación se desarrolla en el piso superior, en una sala revestida con maquetas de trabajo, pero de exquisita manufactura y una claridad ilustrada.

Older adults or third-age learners, despite their age, are growing more enthusiastic about learning English. In Japan, 18.2% of English learners are from the third-age learners' group. This phenomenological study explored the lived experiences of Japanese third-age learners in learning English in Japan's Chubu region. Eight (8) Japanese third-age learners were identified as participants using a purposive sampling technique and inclusion criteria. Results demonstrated that, in essence, their experiences in learning English constituted a complex interplay of three major themes: motivations, adversities, and adaptation. Their experiences represent a profound exploration of self-discovery, intellectual engagement, and the pursuit of meaningful relationships in a globalized society. This linguistic journey highlights the human spirit's ongoing capacity for growth and adaptation, reinforcing the significance of language as a bridge to new horizons and enriching experiences. This study offers valuable insights for Japanese geragogy and other countries with increasing third-age learners, potentially benefiting third-age educators, policymakers, and curriculum designers.

Since the past few years, so-called pre-trained Language Models (PLM) are considered state-of-the-art in the field of Natural Language Processing (NLP) and are thus experiencing widespread and successful application. In addition to traditional supervised Machine Learning (ML) tasks such as spam email or customer churn classification, this technology opens up advanced approaches to unsupervised learning and data analytics in general. One of particular interest is the automatic identification of latent topics within a large collection of texts, also known as Topic Modeling (TM). Such modelling approaches offer great potential, especially for industrial environments as well as the consumer goods market, to explore increasing amounts of data from diverse and constantly growing data sources. As a holistic concept, it can be utilized in a highly targeted and efficient manner for applications through an optimized combination of Artificial Intelligence (AI) and Cloud Computing (CC) systems.

Suppliers and sellers play a crucial role in the ecommerce ecosystem. Sellers and ecommerce firms use social media to increase user engagement, visibility, and sales. Seller ratings are as important as the product ratings on ecommerce platforms to drive buying decisions. Based on sellers' actions on social media, this study examines seller turnover and disengagement on e-commerce platforms. The study has been supported by the justice theory. Seller reviews and ratings from e-commerce platforms and conversations from social media platforms have been gathered. Using natural language processing, machine learning, partial least squares (PLS) path analysis, and statistical inferences, objectives of the study are met. The study offers recommendations for both practitioners and researchers. The sellers must focus more on interaction and communication than marketing. Through a longitudinal analysis, the study also establishes that ecommerce organizations can use seller social media performance as a predictor of future seller churn and disengagement so they can take the necessary remedial action.

San alt seo, cuirtear i láthair taighde a rinneadh ar ghnéithe éagsúla de chur i bhfeidhm Scéim na gCúntóirí Teanga (an Scéim feasta) atá á reáchtáil ag an Roinn Turasóireachta, Cultúir, Ealaíon, Gaeltachta, Spóirt agus na Meán. Cuireann an Scéim, atá ar bun ó bhí 1999 ann, cúntóirí teanga ar fáil do scoileanna Gaeltachta d’fhonn an Ghaeilge a láidriú mar theanga labhartha i measc daltaí scoile sna ceantair sin. Ba é aidhm mhór an tionscadail taighde ná iniúchadh a dhéanamh ar staid reatha na Scéime agus ina dhiaidh sin moltaí chun feabhais a chur ar fáil. Úsáideadh ceistneoirí, agallaimh agus grúpaí fócais le sonraí a bhailiú ó pháirtithe leasmhara na Scéime. San alt seo, dírítear ar shonraí a bhaineann le féiniúlacht agus inspreagadh na gcúntóirí teanga a tháinig chun cinn sna grúpaí fócais ar ghlac 50 cúntóir páirt iontu. I gcomhthéacs na féiniúlachta, is iad na téamaí a d’eascair ó na comhráite ná féindearcadh na gcúntóirí orthu féin, a ról i suíomh na hoibre, agus ról na hoibre a dhéanann siad i dtacú leis an phobal lena mbaineann siad. I dtaca leis an inspreagadh, bhain na téamaí leis an teanga féin, na páistí a mbíonn siad ag obair leo, tacú le céad ghlún eile chainteoirí na Gaeilge agus todhchaí na Gaeltachta. Pléitear ráitis na gcúntóirí i gcomhthéacs na litríochta ar fhéiniúlacht teanga agus inspreagadh múinteoirí teanga, mar aon le cás na Gaeilge agus na Gaeltachta. [In this article we present data from a research project which reviewed various aspects of the implementation of Scéim na gCúntóirí Teanga (The Language Assistants Scheme), which is run by the Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media. The Scheme, established in 1999, provides language assistants to Gaeltacht schools in order to strengthen spoken Irish among pupils in those regions. The main aim of the research was to evaluate the current state of the Scheme and to make recommendations for its enhancement. Questionnaires, interviews and focus groups were used to gather data from the Scheme’s stakeholders. The present article focuses on issues of identity and motivation which were discussed by the 50 language assistants who took part in the focus groups. In relation to identity, the themes that emerged were assistants’ self-image, their role in the workplace, and the role of the work they do to support their own community. As for motivation, the themes were connected to the language itself, the children they work with, supporting the next generation of Irish speakers, and the future of the Gaeltacht. The assistants’ statements are discussed in relation to the literatures on language identity and language teacher motivation, as well as the Irish language and the Gaeltacht.]

The ability of hotels to differentiate themselves from competitors and continue to operate profitably depends on their ability to retain their customers by building long-term and permanent customer relationships. Technological developments in recent years have made it possible for companies to predict their customers’ behavior by accessing their opinions faster and preventing them from churning. Managing customer churn prediction projects has become an important issue today, especially in the hotel industry. Therefore, this research seeks to analyze projects that predict the churn of hotel customers to provide a model to help hotel managers in this field. In this research, an approach based on text mining on customers’ comments in the Persian language is presented, which uses the random forest algorithm for classification that was considered the most effective method to solve this problem. In this model, to increase the efficiency of the proposed method in compare with existing works, the gravitational search algorithm was used to select the useful features, and the differential evolution algorithm was used to adjust the parameters of the classification method. The dataset of this research is the collected data from the customer database on social networks and hotels’ websites, especially the hotels on Kish Island in Iran. The results of this research showed that after the implementation of the preprocessing operations, the method of adjusting the parameters and removing the unimportant features, the model’s accuracy increased significantly. The precision, recall, F1, and accuracy criteria were 0.77, 0.76, 0.76, and 0.77, respectively.

ObjectiveTo clarify the reasons for consultation, advice sought by frontline physicians and relationship between the patient’s pathology and the type of advice provided to guide the future development of telecritical care services.DesignSecondary analysis of transcripts of telephone calls originally recorded for quality control purposes was conducted using a thematic content analysis. The calls were conducted between December 2019 and April 2021 (total cases: 70; total time: ~15 hour).SettingsIntensivists provided consultation services to frontline physicians at secondary care institutions in the Kansai and Chubu regions.ParticipantsNon-intensive care frontline physicians working in five secondary care institutions in the Kansai and Chubu regions and intensivists providing a consultation service (n=26).InterventionsNot applicable.Primary and secondary outcome measuresThe main outcome was the themes emerging from the language used during telephone and video consultations, indicating the gap filled by the telecritical care service.FindingsWe analysed 70 cases and approximately 15 hours of anonymised audio data. We identified the following reasons for consultation: ‘lack of competence in treatment and diagnostic testing’ and ‘lack of access to consultation in their own hospital’. Frontline physicians most often sought advice related to ‘treatment’, followed by ‘patient triage and transfer’, ‘diagnosis’ and ‘diagnostic testing and evaluation’. Regarding the relationship between the patient’s pathology and type of advice provided, the most commonly sought advice by frontline physicians varied based on the patient’s pathology.ConclusionThis study explored the characteristics of 70 telecritical sessions and identified the reasons for and nature of the consultations. These findings can be used to guide the future provision and scale up of telecritical services.

The relationship between customer churn and their complaints is sufficiently contrasted in the telecom sector. Therefore, a key part of a company’s strategy is the measurement of this dissatisfaction. It is important to conduct periodic surveys on complaints in a standard form like the SERVPERF scale because it enables the organization to benchmark. Many of these complaints are stored in the company’s CRM. Our first aim is to define a model to transform CRM customer complaints, expressed in natural language, into SERVPERF scales. In the proposed model, we use the 2-tuple model, which allows computing this linguistic data without losing information. Our second purpose is to implement a prototype to apply the model in a 4G Company. As a practical conclusion, most complaints in this emerging technology (which still has some deficiencies) are related to technical aspects of the services rather than to staff.

This study builds on existing research about churn and community movement, examining if language use on Reddit can be used to determine if people signal their intent to relocate to a new community before they actually do so. Using a computational and semantic approach, we studied the subreddits for the game series Fallout at the time Fallout 76 ( FO76) was released to see if the users of the Fallout 4 ( FO4) subreddit signaled how they would react to the new subreddit. The main difference we found was that those who stay in the FO4 subreddit or use both subreddits on average post more often and create longer posts than those who move to the FO76 subreddit or leave. This adds further evidence to support theories about community as communication, and we suggest this finding can help online community managers identify which users may be about to leave the community, aiding retention and the overall health of the community.

The presence of large amounts of data in information and analytical systems makes it necessary to study them using machine learning and artificial intelligence methods. These models require the definition of tuning parameters related to the specifics of the subject area. The article presents a Cox regression model to solve the problem of customer churn. Cox regression is recognized as a model with high accuracy of predictions in healthcare. Therefore, it is interesting to use the model in other industries. The paper presents the results and comparative analysis of calculations on the Cox model using three tools: Statistical Package for the Social Sciences, programming language R and Russian software – analytical platform Loginom. A distinctive feature of the developed probabilistic model is the determination of the risk of event occurrence in conditions of incomplete data, as well as the identification of indicators that have a significant impact on the degree of its manifestation.

Abstract This article is semi-experiential, written from the vantage point of a critical insider/outsider as the author has no formal degree in Law but her research at the intersections of law and feminism and her teaching experience as a Political Science faculty in a law school, for seven years, mark her as an insider. This specificity or rather ambiguity of her location aids in an act of appropriation and subversion in keeping with the vision of the Feminist Judgments Projects from different parts of the world, to rupture the Law’s/judges’ claim to exclusivity of judging. The key objective of the article is to engage with methodological and epistemological challenges that a feminist rewriter of a judgment has to face in a neo/post-colonial context like contemporary India. The author draws attention to the lack of interdisciplinary perspectives in legal education curriculum and pedagogy in India and argues that reimagining of justice by supplying radical interpretive frameworks requires re-imagination of the system that educates students of law who then enter legal practice in various capacities and roles. The article also locates judicial privilege and hierarchy in everyday practices and technicalities of law insisted upon in courts; exhibited in complexity of legal language and discursive gestures; and the materiality of judicial authority inherent in spatial practices, symbols and monuments.

Bhí iliomad coiste, comhairle, agus coimisiúin a rinne iniúchadh ar an gcóras oideachais Gaeltachta i gcaitheamh na mblianta ó 1926 i leith. Tugadh neamhaird den chuid is mó ar mholtaí na dtuarascálacha éagsúla go dtí gur foilsíodh Curaclam Teanga na Bunscoile (An Chomhairle Náisiúnta Curaclaim agus Measúnachta, 2015) agus an Polasaí don Oideachas Gaeltachta (An Roinn Oideachais agus Scileanna, 2016). Ceadaítear tréimhse tumadh iomlán sa Ghaeilge den chéad uair de réir na moltaí sna cáipéisí sin. Ardaíonn sé seo ceisteanna do scoileanna Gaeltachta maidir le riachtanais oideachais teanga cainteoirí óga Gaeilge na Gaeltachta. Ar chóir múineadh an Bhéarla a thosú go luath do na cainteoirí seo ag aithint go maireann siad i ndomhan ina bhfuil an Béarla ceannasach? Déantar cur síos san alt seo ar an iniúchadh a rinneadh ar na moltaí éagsúla a rinneadh maidir leis an oideachas Gaeltachta agus ar an litríocht ábhartha le fáil amach an bhfuil bonn láidir oideachasúil faoin bpolasaí seo. Mhaígh Ó Duibhir agus Cummins (2012) go n-aistríonn scileanna áirithe teanga, ar nós scileanna litearthachta, ó theanga amháin go teanga eile. Más fíor sin, d’fhéadfaí a mhaíomh gur cuma cé acu teanga go dtéitear i ngleic léi ar dtús mar go n-aistreofar na scileanna ó theanga amháin go dtí an ceann eile. Léiríonn taighde eile le páistí Gaeltachta (7-12 bliain d’aois) ar chainteoirí dúchais iad, go bhfuil stór focal níos fairsinge acu sa Bhéarla ná mar atá sa Ghaeilge (Péterváry, Ó Curnáin, Ó Giollagáin, & Sheahan, 2014). B’fhéidir gur fianaise í seo go bhfuil sealbhú neamhiomlán i gceist do na páistí seo agus go rachadh sé chun sochair dóibh múineadh an Bhéarla a chur siar chun breis ama a thabhairt dóibh bonn níos seasmhaí a chur faoina gcumas Gaeilge. Numerous committees, advisory bodies and commissions have investigated the Gaeltacht education system over the years since 1926. The recommendations of the resulting reports were on the whole ignored until the publication of the Primary Language Curriculum (National Council for Curriculum and Assessment, 2015) and the Policy for Gaeltacht Education (Department of Education and Skills, 2016). According to the recommendations in these documents, a total immersion period in Irish is permitted for the first time. This raises questions for Gaeltacht schools about the language education needs of young Irish speakers in their schools. Should the teaching of English commence early for these speakers recognising that they live in an English dominated world? In this paper, we describe an investigation of the various recommendations that were made about Gaeltacht education and the relevant literature to examine whether there is a strong educational rationale underlying this policy. Ó Duibhir and Cummins (2012) claimed that some linguistic skills, such as literacy skills, transferred from one language to another. If this is the case, it could be claimed that it does not matter which language is encountered first as the skills will transfer from one language to the other. Research by Péterváry, Ó Curnáin, Ó Giollagáin, & Sheahan (2014) involving native Irish-speaking Gaeltacht children (7-12 years) found that the children had a larger vocabulary in English than in Irish. This may be evidence that those children are experiencing incomplete acquisition and that they might benefit from a delay in the introduction of English in order to give them extra time to lay a firmer foundation for their ability in Irish.

Each year, many institutions churn out number of graduating student that must be cleared by different unit through a process called clearance. The traditional method of clearance involves student to physically visits clearance offices; student affairs, bursary, library, sports and registry department to get endorsed for clearance. The traditional method of clearance is time consuming, requires graduating student to physically visit various offices and some key staff may not be available at the time of visit and there is possibility of duplication or loss of data. Thus, the developed online clearance system overcomes the drawback to the traditional method of clearance. The online clearance system was developed using Windows 7 Operation System (OS) as development environment, MySQL for database design, Hypertext Pre-Processor (PHP) for the overall programming and Hypertext Mark-up Language (HTML) couple with Cascading Style Sheet (CSS) for the Graphical User Interface (GUI). A total of 150 student and 50 staff were used to evaluate the developed system for usability, convenience of service delivery and accessibility with 88.1%,89.8% and 95.3% cumulatively affirming that the system is usable, convenient in terms of service delivery and accessible in delivery effective and efficient clearance in a timely manner.

AbstractThe article deals with the question of how to define and understand the concept of a philosophical theatre, in order to apply it productively to performances. To this end, theoretical reflections and the analysis of several productions of Greek tragedies that might qualify as philosophical theatre, are related to each other. Proceeding from Brecht’s ideas on a philosophical theatre, Schiller’s reflections on an aesthetic education and Goethe’s deliberations on Bildung, a first tentative definition of the concept is undertaken. In order to further substantiate the understanding of the concept, the tentative definition is applied to two productions of Greek tragedies that were mounted in order to realize the respective ideas – Brecht’s The Antigone of Sophocles (Chur 1948) and Goethe’s Ion (Weimar 1802). In light of the perspectives opened up by the conclusions regarding the concept, still another production of a Greek tragedy is discussed – namely, Klaus Michael Grüber’s The Bacchae (Berliner Schaubühne 1974), which the director never claimed to be philosophical theatre. Still, from it important insights regarding the concept can be derived that demonstrate its crucial, even if ever-changing meaning.Some of the arguments brought forward by this article have already been published in my book Tragedy’s Endurance (2017).

Exposition (SASATSGS) is a knowledge-based field used to explain the various elements and functions of story description. Morphology is the basis of exposition. The basis of exposition is the subtle units invisible to the language. The expositioners have developed some basic definitions for the creation of panual. The narrative or the story can be constructed by combining the events with the narrative. Through this, the narrator easily reaches the reader. Story programs can be integrated into time and causality. Novelists often rely on programs to build stories. Some people set up story shows in a linear manner in chronological order. Modern novelists have set up programs through causal communication. In this manner, the programmes have been dissolved. The reader with reading experience learns the causal connection and understands the story. Sundara Ramasamy, Jayamohan and Shobashakti have successfully set up the programmes of the story in a time-based series. The reader who reads their novels easily identifies the operating system of the story. In Nakulan's novel Dogs, a causal sequence has been adopted to coordinate the programmes. The reader who reads this could not immediately understand the flow of the story. They are a slightly difficult series. Charu Nivedita's novel 'Dekam' and MG Suresh's 'Spider' are in a causal sequence. Sundara Ramasamy and Shobashakti are seen in their novels in the same programme. Novels are divided into small elements based on the definition review and innovative results are available.

De réir Mháirtín Uí Chadhain, ba é Saunders Lewis an fear liteartha ba mhó cáil sa Bhreatain Bheag sna 1960idí agus ba é an t-údar ba mhó tábhacht ar fad é a bhí ag saothrú a phinn in aon cheann de na teangacha Ceilteacha ag an am. Tá cáil Lewis imithe i bhfad agus i ngearr mar gheall ar an léacht cháiliúil raidió a thug sé uaidh, agus a craoladh ar an BBC, i mí Feabhra 1962. Tynged yr Iaith (Cinniúint na Teanga) ba theideal don léacht iomráiteach sin inar leag sé amach a ghéire is a bhí éigeandáil na teanga sa Bhreatain Bheag ag an am. Chun fuascailt a fháil ar an scéal, mhol sé modhanna úra agóidíochta agus léirsithe chun tathant ar na húdaráis stádas oifigiúil na Breatnaise a threisiú sa saol poiblí. Bhí briathra Lewis ina ndíol spéise do ghluaiseacht na Gaeilge in Éirinn na linne sin, a bhuíochas sin don aistriúchán Gaeilge Bás nó Beatha? a rinne Máirtín Ó Cadhain, agus a d’fhoilsigh Sáirséal agus Dill, in 1963. San aiste seo, déanfar anailís ar aistriúchán sin Uí Chadhain féachaint cén rian a d’fhág teachtaireacht Lewis ar mhodhanna agóidíochta ghluaiseacht na Gaeilge in Éirinn sna 1960idí. Áiteofar gur athraigh Bás nó Beatha? treo agus cur chuige ghníomhaíochas na Gaeilge in Éirinn trí smaointeoireacht Saunders Lewis a chur ar a shúile do chomhluadar ní ba leithne daoine. Breathnófar, go háirithe, ar cén tionchar a bhí ag modhanna léirsithe na Breataine Bige, agus an easumhlaíocht shibhialta go háirithe, ar an eagraíocht Misneach, ar Chonradh na Gaeilge agus ar Ghluaiseacht Chearta Sibhialta na Gaeltachta. Chuige sin, bainfear gaisneas as an dá shaothar le Saunders Lewis a d’aistrigh Ó Cadhain; ba iad sin ‘Aon Teanga don Bhreatain Bheag’, a foilsíodh ar an iris Comhar in 1955, chomh maith le Bás nó Beatha? (1963). Ina theannta sin, cuirfear sampla de scríbhinní polaitiúla Uí Chadhain féin sa mheá, ‘Do na Fíréin’ (1962) agus Gluaiseacht na Gaeilge: Gluaiseacht ar Strae (1970), gan trácht ar an dá dhíolaim aistí Caithfear Éisteacht! (1999) agus Ó Cadhain i bhFeasta (1990).

Coimriú Tá an córas tumoideachais in Éirinn imithe ó neart go neart le leathchéad bliain anuas. Is mór an t-éileamh atá ar an gcineál scolaíochta seo ar fud na tíre, ag leibhéal na bunscoile ach go háirithe. Cé go bhfuil sé tugtha le fios le fada an lá go mbaineann raidhse buntáistí leis an gcóras tumoideachais, is fada an tuiscint againn gur córas casta é le cur i bhfeidhm go rathúil agus maítear go bhfuil dúshláin ar leith le sárú fós sa chóras in Éirinn ar mhaithe leis an tairbhe is fearr a bhaint as. De réir na litríochta, ceann de na gnéithe is dúshlánaí atá roimh mhúinteoirí agus dhaltaí tumoideachais is ea sealbhú na gramadaí agus úsáid chruinn an dara teanga (T2) i measc daltaí. In ainneoin go moltar aiseolas ceartaitheach (AC) a úsáid go córasach sa rang tumoideachais chun botúin ghramadaí na ndaltaí a cheartú, tuairiscítear go mbíonn mearbhall ar mhúinteoirí tumoideachais maidir le conas agus cathain botúin ghramadaí a cheartú, go háirithe le linn theagasc ábharbhunaithe. Ach, is fíorbheag taighde atá curtha i gcrích sa ghort seo i gcomhthéacs na hÉireann. Sa pháipéar reatha, tabharfar léargas ar thaighde cáilíochtúil a rinne iniúchadh ar dhearcthaí múinteoirí agus daltaí maidir le húsáid chórasach AC i suíomhanna tumoideachais lán-Ghaeilge. Bailíodh sonraí taighde ó mhúinteoirí (n=8) trí agallaimh leathstruchtúrtha, ó dhaltaí Rang 5 trí ghrúpaí fócais (n=31) agus bhailigh na taighdeoirí tuilleadh sonraí trí sheisiúin bhreathnóireachta sna seomraí ranga le linn idirghabháil an taighde. Cuirfear na torthaí cáilíochtúla ba shuntasaí i láthair sa pháipéar seo agus pléifear a n-impleachtaí i dtaobh an teagaisc agus an taighde amach anseo. Cuireann an taighde faoi chaibidil le corpas litríochta an ghoirt agus tacóidh sé le múinteoirí agus le daltaí botúin ghramadaí a thapú mar dheiseanna foghlama d’fhonn ardchaighdeán sealbhaithe T2 a chur chun cinn. Abstract Immersion education in Ireland has experienced considerable growth over the past number of decades and strong demand currently exists for this type of schooling on the island. While the literature generously celebrates the benefits associated with immersion education, it is understood that it is a complex and multifaceted system which presents many challenges in its effective implementation. It has been acknowledged that one of the greatest challenges, facing both immersion teachers and students, is the accurate acquisition of the students’ second language. Although a growing body of international research presents oral corrective feedback (CF) as a successful pedagogical approach to enhance L2 accuracy among students, it is well documented that teachers remain uncertain of how or when to correct students’ linguistic errors, during content lessons in particular. Given the paucity of research that exists in this field in Ireland, CF warrants further attention within the Irish language immersion context. In light of this, the current paper explores the prominent qualitative findings which emerged from a research study that investigated teachers’ and students’ perspectives of CF when implemented in a systematic manner in the Irish immersion classroom. To unpack participants’ perspectives, qualitative data were gathered from eight immersion teachers through semi-structured interviews and focus groups with eight Grade 5 class groupings (n=31). Researchers also engaged in regular observation routines in the participating classrooms, which generated further research data. The most significant research findings that emerged from the study are explored in the current paper and stemming from these findings, implications for future research, practice and policy are discussed. It is intended that the current study and paper will contribute to research in Ireland and further afield while also supporting teachers with implementation of CF in a systematic manner in immersion classrooms.

- Anne Booth, W.L. Korthals Altes, Changing economy in Indonesia, Amsterdam: Royal Tropical Institute (General trade statistics, 1822-1949; volume 12a). - Wim van den Doel, Robert Cribb, Historical dictionary of Indonesia. Metuchen, N.J., & London: The Scarecrow Press, 1992. - C.D. Grijns, Kingsley Bolton, Sociolinguistics today; International perspectives. London and New York: Routledge, 1992, 383 pp., Helen Kwok (eds.) - David Henley, Ole Bruun, Asian perceptions of nature: Papers presented at a Workshop, NIAS, Copenhagen, Denmark, October 1991. Copenhagen: Nordic Institute of Asian studies (Nordic Proceedings in Asian studies No. 3), 1992, 261 pp., Arne Kalland (eds.) - Ward Keeler, Jonathon Falla, True love and Bartholomew: Rebels on the Burmese border. Cambridge: Cambridge University Press, 1991. - Elsbeth Locher-Scholten, Mary F. Somers Heidhues, Bangka tin and mentok pepper; Chinese settlement on an Indonesian island. Singapore: Institute of South-east Asian studies, 1992, 296 pp. - Marie Alexandrine Martin, Christin Kocher Schmid, Of people and plants. A botanical ethnography of Nokopo village, Madang and Morobe provinces, Papua New Guinea. Ethnologisches Seminar der Universität und Museum für Völkerkunde, Basel, 1991, 336 pp. - J. Noorduyn, Bernhard Dahm, Regions and regional developments in the Malay-Indonesian world: 6 European Colloquium on Indonesian and Malay studies (ECIMS) June 1987 Passau. Wiesbaden: Harassowitz, 1992, x + 221 pp., maps. - J. Noorduyn, J.N. Sneddon, Studies in Sulawesi Linguistics, Part II, NUSA, Linguistic studies of Indonesian and other languages in Indonesia, volume 33. Jakarta: Baden Penyelenggara Seri Nusa, Universitas Katolik Indonesia Atma Jaya. 1991, x + 115 pp., maps. - Anton Ploeg, Richard Michael Bourke, Taim hangre: Variation in subsistence food supply in the Papua New Guinea highlands, Unpublished PhD thesis, submitted in the department of human geography, The Australian National University, RSPacS, Canberra, 1988, xxiii + 370 pp., maps, tables, figures, appendices. - Anton Ploeg, Maureen A. MacKenzie, Androgenous objects: String bags and gender in central New Guinea. Chur, Switzerland, Harwood Academic Publishers, 1991, xv + 256 pp., maps, figures, bibliography, index. - Nico G. Schulte Nordholt, Jeremy Kemp, Peasants and cities; Cities and peasants; Rethinking Southeast Asian models, Overveen, ACASEA, 1990, 126 pp. - Rudiger Schumacher, Clara Brakel-Papenhuijzen, The Bedhaya court dances of central Java, Leiden/New York/Köln: Brill, 1992, xvi + 349 pp. - Corry M.I. van der Sluys, Carol Laderman, Taming the wind of desire; Psychology, medicine, and aesthetics in Malay Shamanistic performance. University of California Press, 1991, 382 pp. - J.H.F. Sollewijn Gelpke, Geoffrey Irwin, The prehistoric exploration and colonisation of the Pacific. Cambridge: Cambridge University Press 1992, viii + 240 pp. - R.G. Tol, Burhan Magenda, East Kalimantan; The decline of a commercial aristocracy. Ithaca, Cornell University (Cornell Modern Indonesia Project, Monograph Series (publication no. 70)), 1991, viii + 113 pp., maps.

IntroductionDigital technologies can be used as part of paediatric motor rehabilitation to remediate impairment, promote recovery and improve function. However, the uptake of digital technologies in this clinical field may be limited.The aim of this study is to describe and explain digital technology use for paediatric motor rehabilitation. The specific objectives will be: (1) to describe the access to, acceptance of and use of digital technologies as a function of individual factors related to professionals practicing motor rehabilitation with children, and of environmental factors related to paediatric rehabilitation practice and (2) to explain digital technology use with a causal model based on the ‘unified theory of acceptance and use of technology’.Methods and analysisRehaTech4child (Rehabilitation Technologies For children) is a cross-sectional study involving an online survey, that is sponsored by the European Academy of Childhood Disability (EACD). The survey protocol follows the Strengthening the Reporting of Observational Studies in Epidemiology and CHERRIES (Checklist for Reporting Results of Internet E-Surveys) guidelines. The survey includes 43 questions about (1) respondents’ individual and environmental characteristics; (2) the ease of access to digital technologies, and the frequency, type and purpose of use of those technologies and (3) acceptance of technologies and barriers to their use. The survey is intended for professionals involved in paediatric motor rehabilitation. It is disseminated across Europe by the EACD network in 20 languages. Participation is anonymous and voluntary. We aim to include 500 respondents to ensure sufficient precision for the description of study outcomes and to perform stratified analyses by the main determinants.Ethics and disseminationEthics approval was waived by the Brest CHRU Institutional Review Board. The study is conducted according to current French legislation (loi Jardé (n°2012-300)) and the survey is GDPR compliant. Study findings will be presented at national and international meetings and submitted for publication in a peer-reviewed journal.Trial registration numberNCT05176522.

The “Opportunity Gap” and the “Skills Gap” have been the focus of conferences this year. Solutions have been proposed, but none has aligned technology with the cultural capital that exists within an organization to close the gaps. Cultural capital is the accumulation of symbols, language, political knowledge and expertise that senior leaders use to get the job done daily within an organization. Emerging leaders who have not been immersed in this cultural capital, particularly diverse candidates, struggle to identify or find the resources and develop the skills necessary to succeed in an organization. Frequently training dollars are allocated to high-potential candidates who often are able to assimilate these skills quickly, but rarely if ever are they, when at the managerial level, tested on their ability to transfer these skills to others. This inability of high-potential mangers to transfer cultural capital between the different layers of an organization is a real cause of the skills and opportunity gap.In 2012, at a larger retailer in the southern US, we began testing a pilot program for a practical management training in the form of a Licensed Online Open Course (modeled after the MOOC) to determine if managers with access to a structured and disciplined curriculum could have an impact on human capital productivity and increase retention among managers and their followers. The LOOC and its content were created by the Donohue Mentoring System™ (DMS).We concluded that on-the-job training, using the DMS LOOC delivery and mentoring, fosters cultural capital, increased job motivation and satisfaction, and subsequently increased output (productivity) by 10%. Using a survey comprised of 19 questions, we were also able to determine that trust in superior officers increased by 10% and self-assessed value of work increased by 10%. These increases resulted in a reduced employee churn of 50%. As we carried on pilots in 2013, 2014 and 2015 with other large corporations, not for profit and a government, we were surprised to find that the system delivered the same noteworthy results each time. We found that when managers are presented with a technology solution that allows them to train candidates (mentees) and transfer knowledge to their mentees, leadership magic happens, and people engage with each other. What surprised us the most was that no matter the size of the pilot program, mentees for the most part surpassed their mentors’ knowledge pre-program.

Recent Trends and Future of Fog and Edge Computing, Services, and Enabling Technologies Cloud computing has been established as the most popular as well as suitable computing infrastructure providing on-demand, scalable and pay-as-you-go computing resources and services for the state-of-the-art ICT applications which generate a massive amount of data. Though Cloud is certainly the most fitting solution for most of the applications with respect to processing capability and storage, it may not be so for the real-time applications. The main problem with Cloud is the latency as the Cloud data centres typically are very far from the data sources as well as the data consumers. This latency is ok with the application domains such as enterprise or web applications, but not for the modern Internet of Things (IoT)-based pervasive and ubiquitous application domains such as autonomous vehicle, smart and pervasive healthcare, real-time traffic monitoring, unmanned aerial vehicles, smart building, smart city, smart manufacturing, cognitive IoT, and so on. The prerequisite for these types of application is that the latency between the data generation and consumption should be minimal. For that, the generated data need to be processed locally, instead of sending to the Cloud. This approach is known as Edge computing where the data processing is done at the network edge in the edge devices such as set-top boxes, access points, routers, switches, base stations etc. which are typically located at the edge of the network. These devices are increasingly being incorporated with significant computing and storage capacity to cater to the need for local Big Data processing. The enabling of Edge computing can be attributed to the Emerging network technologies, such as 4G and cognitive radios, high-speed wireless networks, and energy-efficient sophisticated sensors. Different Edge computing architectures are proposed (e.g., Fog computing, mobile edge computing (MEC), cloudlets, etc.). All of these enable the IoT and sensor data to be processed closer to the data sources. But, among them, Fog computing, a Cisco initiative, has attracted the most attention of people from both academia and corporate and has been emerged as a new computing-infrastructural paradigm in recent years. Though Fog computing has been proposed as a different computing architecture than Cloud, it is not meant to replace the Cloud. Rather, Fog computing extends the Cloud services to network edges for providing computation, networking, and storage services between end devices and data centres. Ideally, Fog nodes (edge devices) are supposed to pre-process the data, serve the need of the associated applications preliminarily, and forward the data to the Cloud if the data are needed to be stored and analysed further. Fog computing enhances the benefits from smart devices operational not only in network perimeter but also under cloud servers. Fog-enabled services can be deployed anywhere in the network, and with these services provisioning and management, huge potential can be visualized to enhance intelligence within computing networks to realize context-awareness, high response time, and network traffic offloading. Several possibilities of Fog computing are already established. For example, sustainable smart cities, smart grid, smart logistics, environment monitoring, video surveillance, etc. To design and implementation of Fog computing systems, various challenges concerning system design and implementation, computing and communication, system architecture and integration, application-based implementations, fault tolerance, designing efficient algorithms and protocols, availability and reliability, security and privacy, energy-efficiency and sustainability, etc. are needed to be addressed. Also, to make Fog compatible with Cloud several factors such as Fog and Cloud system integration, service collaboration between Fog and Cloud, workload balance between Fog and Cloud, and so on need to be taken care of. It is our great privilege to present before you Volume 20, Issue 2 of the Scalable Computing: Practice and Experience. We had received 20 Research Papers and out of which 14 Papers are selected for Publication. The aim of this special issue is to highlight Recent Trends and Future of Fog and Edge Computing, Services and Enabling technologies. The special issue will present new dimensions of research to researchers and industry professionals with regard to Fog Computing, Cloud Computing and Edge Computing. Sujata Dash et al. contributed a paper titled “Edge and Fog Computing in Healthcare- A Review” in which an in-depth review of fog and mist computing in the area of health care informatics is analysed, classified and discussed. The review presented in this paper is primarily focussed on three main aspects: The requirements of IoT based healthcare model and the description of services provided by fog computing to address then. The architecture of an IoT based health care system embedding fog computing layer and implementation of fog computing layer services along with performance and advantages. In addition to this, the researchers have highlighted the trade-off when allocating computational task to the level of network and also elaborated various challenges and security issues of fog and edge computing related to healthcare applications. Parminder Singh et al. in the paper titled “Triangulation Resource Provisioning for Web Applications in Cloud Computing: A Profit-Aware” proposed a novel triangulation resource provisioning (TRP) technique with a profit-aware surplus VM selection policy to ensure fair resource utilization in hourly billing cycle while giving the quality of service to end-users. The proposed technique use time series workload forecasting, CPU utilization and response time in the analysis phase. The proposed technique is tested using CloudSim simulator and R language is used to implement prediction model on ClarkNet weblog. The proposed approach is compared with two baseline approaches i.e. Cost-aware (LRM) and (ARMA). The response time, CPU utilization and predicted request are applied in the analysis and planning phase for scaling decisions. The profit-aware surplus VM selection policy used in the execution phase for select the appropriate VM for scale-down. The result shows that the proposed model for web applications provides fair utilization of resources with minimum cost, thus provides maximum profit to application provider and QoE to the end users. Akshi kumar and Abhilasha Sharma in the paper titled “Ontology driven Social Big Data Analytics for Fog enabled Sentic-Social Governance” utilized a semantic knowledge model for investigating public opinion towards adaption of fog enabled services for governance and comprehending the significance of two s-components (sentic and social) in aforesaid structure that specifically visualize fog enabled Sentic-Social Governance. The results using conventional TF-IDF (Term Frequency-Inverse Document Frequency) feature extraction are empirically compared with ontology driven TF-IDF feature extraction to find the best opinion mining model with optimal accuracy. The results concluded that implementation of ontology driven opinion mining for feature extraction in polarity classification outperforms the traditional TF-IDF method validated over baseline supervised learning algorithms with an average of 7.3% improvement in accuracy and approximately 38% reduction in features has been reported. Avinash Kaur and Pooja Gupta in the paper titled “Hybrid Balanced Task Clustering Algorithm for Scientific workflows in Cloud Computing” proposed novel hybrid balanced task clustering algorithm using the parameter of impact factor of workflows along with the structure of workflow and using this technique, tasks can be considered for clustering either vertically or horizontally based on value of impact factor. The testing of the algorithm proposed is done on Workflowsim- an extension of CloudSim and DAG model of workflow was executed. The Algorithm was tested on variables- Execution time of workflow and Performance Gain and compared with four clustering methods: Horizontal Runtime Balancing (HRB), Horizontal Clustering (HC), Horizontal Distance Balancing (HDB) and Horizontal Impact Factor Balancing (HIFB) and results stated that proposed algorithm is almost 5-10% better in makespan time of workflow depending on the workflow used. Pijush Kanti Dutta Pramanik et al. in the paper titled “Green and Sustainable High-Performance Computing with Smartphone Crowd Computing: Benefits, Enablers and Challenges” presented a comprehensive statistical survey of the various commercial CPUs, GPUs, SoCs for smartphones confirming the capability of the SCC as an alternative to HPC. An exhaustive survey is presented on the present and optimistic future of the continuous improvement and research on different aspects of smartphone battery and other alternative power sources which will allow users to use their smartphones for SCC without worrying about the battery running out. Dhanapal and P. Nithyanandam in the paper titled “The Slow HTTP Distributed Denial of Service (DDOS) Attack Detection in Cloud” proposed a novel method to detect slow HTTP DDoS attacks in cloud to overcome the issue of consuming all available server resources and making it unavailable to the real users. The proposed method is implemented using OpenStack cloud platform with slowHTTPTest tool. The results stated that proposed technique detects the attack in efficient manner. Mandeep Kaur and Rajni Mohana in the paper titled “Static Load Balancing Technique for Geographically partitioned Public Cloud” proposed a novel approach focused upon load balancing in the partitioned public cloud by combining centralized and decentralized approaches, assuming the presence of fog layer. A load balancer entity is used for decentralized load balancing at partitions and a controller entity is used for centralized level to balance the overall load at various partitions. Results are compared with First Come First Serve (FCFS) and Shortest Job First (SJF) algorithms. In this work, the researchers compared the Waiting Time, Finish Time and Actual Run Time of tasks using these algorithms. To reduce the number of unhandled jobs, a new load state is introduced which checks load beyond conventional load states. Major objective of this approach is to reduce the need of runtime virtual machine migration and to reduce the wastage of resources, which may be occurring due to predefined values of threshold. Mukta and Neeraj Gupta in the paper titled “Analytical Available Bandwidth Estimation in Wireless Ad-Hoc Networks considering Mobility in 3-Dimensional Space” proposes an analytical approach named Analytical Available Bandwidth Estimation Including Mobility (AABWM) to estimate ABW on a link. The major contributions of the proposed work are: i) it uses mathematical models based on renewal theory to calculate the collision probability of data packets which makes the process simple and accurate, ii) consideration of mobility under 3-D space to predict the link failure and provides an accurate admission control. To test the proposed technique, the researcher used NS-2 simulator to compare the proposed technique i.e. AABWM with AODV, ABE, IAB and IBEM on throughput, Packet loss ratio and Data delivery. Results stated that AABWM performs better as compared to other approaches. R.Sridharan and S. Domnic in the paper titled “Placement Strategy for Intercommunicating Tasks of an Elastic Request in Fog-Cloud Environment” proposed a novel heuristic IcAPER,(Inter-communication Aware Placement for Elastic Requests) algorithm. The proposed algorithm uses the network neighborhood machine for placement, once current resource is fully utilized by the application. The performance IcAPER algorithm is compared with First Come First Serve (FCFS), Random and First Fit Decreasing (FFD) algorithms for the parameters (a) resource utilization (b) resource fragmentation and (c) Number of requests having intercommunicating tasks placed on to same PM using CloudSim simulator. Simulation results shows IcAPER maps 34% more tasks on to the same PM and also increase the resource utilization by 13% while decreasing the resource fragmentation by 37.8% when compared to other algorithms. Velliangiri S. et al. in the paper titled “Trust factor based key distribution protocol in Hybrid Cloud Environment” proposed a novel security protocol comprising of two stages: first stage, Group Creation using the trust factor and develop key distribution security protocol. It performs the communication process among the virtual machine communication nodes. Creating several groups based on the cluster and trust factors methods. The second stage, the ECC (Elliptic Curve Cryptography) based distribution security protocol is developed. The performance of the Trust Factor Based Key Distribution protocol is compared with the existing ECC and Diffie Hellman key exchange technique. The results state that the proposed security protocol has more secure communication and better resource utilization than the ECC and Diffie Hellman key exchange technique in the Hybrid cloud. Vivek kumar prasad et al. in the paper titled “Influence of Monitoring: Fog and Edge Computing” discussed various techniques involved for monitoring for edge and fog computing and its advantages in addition to a case study based on Healthcare monitoring system. Avinash Kaur et al. elaborated a comprehensive view of existing data placement schemes proposed in literature for cloud computing. Further, it classified data placement schemes based on their assess capabilities and objectives and in addition to this comparison of data placement schemes. Parminder Singh et al. presented a comprehensive review of Auto-Scaling techniques of web applications in cloud computing. The complete taxonomy of the reviewed articles is done on varied parameters like auto-scaling, approach, resources, monitoring tool, experiment, workload and metric, etc. Simar Preet Singh et al. in the paper titled “Dynamic Task Scheduling using Balanced VM Allocation Policy for Fog Computing Platform” proposed a novel scheme to improve the user contentment by improving the cost to operation length ratio, reducing the customer churn, and boosting the operational revenue. The proposed scheme is learnt to reduce the queue size by effectively allocating the resources, which resulted in the form of quicker completion of user workflows. The proposed method results are evaluated against the state-of-the-art scene with non-power aware based task scheduling mechanism. The results were analyzed using parameters-- energy, SLA infringement and workflow execution delay. The performance of the proposed schema was analyzed in various experiments particularly designed to analyze various aspects for workflow processing on given fog resources. The LRR (35.85 kWh) model has been found most efficient on the basis of average energy consumption in comparison to the LR (34.86 kWh), THR (41.97 kWh), MAD (45.73 kWh) and IQR (47.87 kWh). The LRR model has been also observed as the leader when compared on the basis of number of VM migrations. The LRR (2520 VMs) has been observed as best contender on the basis of mean of number of VM migrations in comparison with LR (2555 VMs), THR (4769 VMs), MAD (5138 VMs) and IQR (5352 VMs).

The purpose of this study is to explore the innovations that creator Sujatha has used in her works and that she has some unique identities in handling language. The explanatory approach approach has been handled based on the thread study of this study. The researcher confirms that Sujatha is also a great creator in the world of Tamil literature. Creators use many elements in their work to convey to the reader the emotions they have received. The creator can be identified by examining those elements. The study aims to identify her uniqueness in Sujatha's work. In Sujata's works, the language structure is better than the plot. His essence has been adopted by later literary men as well. I am learning a lot from Sujatha in the post-modernist Charu Nivedita uirmai magazine. Also says my teacher (p.43). S. Ramakrishnan says of Sujatha's "chopped verses are a forerunner to those like me today".

Software Defect Prediction (SDP) plays an active area in many research domain of Software Quality of Assurance (SQA). Many existing research studies are based on software traditional metric sets and defect prediction models are built in machine language to detect the bug for limited source code line. Inspired by the above existing system. In this paper, defect prediction is focused on predicting defects in source code. The aim of this dissertation is to enhance the quality of the software for precise prediction of defects. So, that it helps the developer to find the bug and fix the issue, to make better use of a resource which reduces the test effort, minimize the cost and improve the quality of software. A new approach is introduced to improve the prediction performance of Bidirectional RNNLM in Deep Neural Network. To build the defect prediction model a defect learner framework is proposed and first it need to build a Neural Language Model. Using this Language Model it helps to learn to deep semantic features in source code and it train & test the model. Based on language model it combined with software traditional metric sets to measure the code and find the defect. The probability of language model and metric set Cross-Entropy with Abstract Syntax Tree (CE-AST) metric is used to evaluate the defect proneness and set as a metric label. For classification the metric label K-NN classifier is used. BPTT algorithm for learning RNN will provide additional improvement, it improves the predictions performance to find the dynamic error.

Software Defect Prediction (SDP) plays an active area in many research domain of Software Quality of Assurance (SQA). Many existing research studies are based on software traditional metric sets and defect prediction models are built in machine language to detect the bug for limited source code line. Inspired by the above existing system. In this paper, defect prediction is focused on predicting defects in source code. The objective of this thesis is to improve the software quality for accurate defect prediction is source code for file level. So, that it helps the developer to find the bug and fix the issue, to make better use of a resource which reduces the test effort, minimize the cost and improve the quality of software. A new approach is introduced to improve the prediction performance of Bidirectional RNNLM in Deep Neural Network. To build the defect prediction model a defect learner framework is proposed and first it need to build a Neural Language Model. Using this Language Model it helps to learn to deep semantic features in source code and it train & test the model. Based on language model it combined with software traditional metric sets to measure the code and find the defect. The probability of language model and metric set Cross-Entropy with Abstract Syntax Tree (CE-AST) metric is used to evaluate the defect proneness and set as a metric label. For classification the metric label K-NN classifier is used. BPTT algorithm for learning RNN will provide additional improvement, it improves the predictions performance to find the dynamic error.

IntroductionPredictors of neurodevelopment among children who are HIV‐exposed uninfected (CHEU) are poorly understood.MethodsMothers with and without HIV and their children were enrolled during 6‐week postnatal care visits across seven sites in Kenya between March 2021 and June 2022. Infant neurodevelopment was assessed using the Malawi Developmental Assessment Tool, including social, language, fine motor and gross motor domains. We used multivariate linear mixed effects models to identify associations between 1‐year neurodevelopment scores, HIV and antiretroviral therapy (ART) exposures, and household factors, adjusted for potential confounders and clustered by the site.ResultsAt 1‐year evaluation, CHEU (n = 709) and children who are HIV‐unexposed uninfected (CHUU) (n = 715) had comparable median age (52 weeks) and sex distribution (49% vs. 52% female). Mothers living with HIV were older (31 vs. 27 years), had lower education (50% vs. 26% primary) and were more likely to be report moderate‐to‐severe food insecurity (26% vs. 9%) (p < 0.01 for all). Compared to CHUU, CHEU had higher language scores (adjusted coeff: 0.23, 95% CI: 0.06, 0.39) and comparable social, fine and gross motor scores. Among all children, preterm birth was associated with lower gross motor scores (adjusted coeff: −1.38, 95% CI: −2.05, −0.71), food insecurity was associated with lower social scores (adjusted coeff: −0.37, 95% CI: −0.73, −0.01) and maternal report of intimate partner violence (IPV) was associated with lower fine motor (adjusted coeff: −0.76, 95% CI: −1.40, −0.13) and gross motor scores (adjusted coeff: −1.07, 95% CI: −1.81, −0.33). Among CHEU, in utero efavirenz (EFV) exposure during pregnancy was associated with lower gross motor scores compared to dolutegravir (DTG) exposure (adjusted coeff: −0.51, 95% CI: −1.01, −0.03). Lower fine and gross motor scores were also associated with having a single or widowed mother (adjusted coeff: −0.45, 95% CI: −0.87, −0.03) or a deceased or absent father (adjusted coeff: −0.81, 95% CI: −1.58, −0.05), respectively.ConclusionsBiologic and social factors were associated with child neurodevelopment. Despite socio‐demographic differences between CHEU and CHUU, 1‐year neurodevelopment was similar. Addressing IPV and food insecurity may provide benefits regardless of maternal HIV status. DTG use was associated with higher neurodevelopmental scores in CHEU, compared to EFV regimens, potentially contributing to a lack of neurodevelopmental difference between CHEU and CHUU.

Déantar cur síos san alt seo ar thaithí cúigear múinteoirí agus príomhoide amháin ar an bhFoghlaim Chomhtháite Ábhar agus Teangacha (FCÁT) a chur i bhfeidhm tríd an tríú teanga i mbunscoileanna lán-Ghaeilge. Tá cáil ar FCÁT mar chur chuige atá éifeachtach leis an dara teanga a theagasc. Is éard atá i gceist le FCÁT, ná go múintear ábhar nó cuid d’ábhar trí mheán an dara teanga nó teanga bhreise. Ba scéim phíolótach cheannródaíoch a bhí sa taighde seo mar go raibh FCÁT á chur i bhfeidhm le foghlaimeoirí óga, ag baint leasa as an tríú teanga i suíomh an tumoideachais lán-Ghaeilge. Chomhtháthaigh na múinteoirí a bhí páirteach sa taighde, teanga Eorpach (An Fhraincis/An Ghearmáinis), leis an bhfoghlaim ábhair in ábhar scoile amháin le linn na scoilbhliana. Bhí réimse rang-ghrúpaí agus ábhar i gceist agus cuireadh múnlaí éagsúla de FCÁT i bhfeidhm ag brath ar inniúlacht na múinteoirí sa sprioctheanga. Bailíodh eolas cáilíochtúil faoi eispéiris na múinteoirí ó cheistneoir agus grúpa fócais. Cé gur taighde ar scála beag atá sa taighde seo, is ábhar taighde nuálach é a thugann léargas ar chuid de na saincheisteanna a bheadh le plé dá mbeadh FCÁT i bhfeidhm i scoileanna lán-Ghaeilge ar bhonn níos leithne amach anseo. Eascraíonn ceisteanna maidir leis na hábhair seo a leanas: inniúlacht múinteoirí sa sprioctheanga, forbairt ghairmiúil leanúnach do mhúinteoirí, torthaí foghlama teanga FCÁT agus soláthar áiseanna do FCÁT. Is í an phríomhcheist a eascraíonn ón taighde ná, cén múnla FCÁT ab fheiliúnaí do shainchomhthéacs na mbunscoileanna lán-Ghaeilge in Éirinn. This article reports the experiences five Irish-medium primary teachers, and one Irish-medium principal of implementing Content and Integrated Learning (CLIL) through a third language in Irish-medium primary schools. CLIL is recognised as an effective approach to second language teaching. It entails the teaching of a subject, or a part of a subject through the medium of a second or an additional language. In this pioneering pilot study CLIL was implemented with young learners through a third language in an Irish-medium immersion setting. The teachers involved in the project integrated a European language (French/German), with content learning in one subject throughout the school year. There were a variety of class groups and subjects involved, and teachers adopted various approaches to CLIL in accordance with their own linguistic proficiency. Data relaying the teachers’ experiences and approaches to CLIL were gathered from a questionnaire and focus group interview. This small scale innovative research provides an insight into prominent questions for discussion if CLIL is to be implemented in Irish-medium schools on a wider basis. Questions arise concerning: language teacher proficiency, continuous professional development for teachers, language learning outcomes for CLIL, and the provision of specifically designed CLIL resources. A key question arising from the study is what model of CLIL would be most suitable for the specific context of Irish-medium primary schools in Ireland.

This short article summarizes my reflections and opinions toward my optional workshops on TOEIC preparation. The workshops have taken place weekly in a self-access center (SAC) in Chubu district, Japan. Many SACs, in fact, offer workshops as a part of their services encouraging learners to enhance their target language proficiency and become more self-regulated and autonomous (Gardner & Miller, 1999; Sekiya, Mynard, & Cooker, 2010). However, few have researched whether SAC workshops are achieving such goals. Thus, I aim to share my perspectives based on my reflections on having instructed the series of workshops for the duration of four semesters. In particular, I will present my three principles to make the workshops attractive and effective: 1) learner development; 2) implications from second-language acquisition (SLA); and 3) guidance on learning resources. I will also illustrate learning resources found to be most popular by my workshop attendees. Finally, I will discuss key elements that may make SAC workshops more meaningful and distinguished as extra-curricular lessons.

Despite being one of the official languages in Switzerland, the phonetic properties of Swiss Standard German (SSG) have been studied insufficiently. Regarding Alemannic (ALM) dialects, most of the available phonetic studies have dealt with consonants rather than vowels. To counteract this general lack of research, this study investigates the long-vowel inventories of four ALM dialects as well as their respective SSG varieties regarding vowel quality. The aim of the study is twofold: on the one hand, it provides the first comparative acoustic analysis of ALM and SSG vowels; on the other hand, it investigates to which extent interference from ALM dialects determines the vowel qualities of SSG varieties. To this end, four male and four female speakers from Bern, Chur, Brig, and Zurich were recorded producing each vowel three times, which resulted in a corpus of 1632 tokens. The results show that ALM vowel quality is basically transferred to the SSG varieties in two dialect regions: Chur and Brig. Instead, in the SSG varieties spoken in Bern and Zurich certain vowel qualities did not match the ALM ones, mostly for <a> that was fronted in the SSG variety of either dialect. Additionally, the Bern SSG <ä> was produced as both [┋ː] and [ӕː], while <o> was realised more in the back.