No / Several studies have concluded that the use of nurses’ time and energy is often not optimized. Given widespread migration of nurses from developing to developed countries, it is important for human resource planning to know whether nursing education in developing countries is associated with more exaggerated patterns of inefficiency. Objectives First, to describe nurses’ reports on tasks below their skill level. Second, to examine the association between nurses’ migratory status (domestically trained nurse or foreign trained nurse from a developing country) and reports on these tasks. Design The Registered Nurse Forecasting Study used a cross-sectional quantitative research design to gather data from 33,731 nurses (62% response rate) in 486 hospitals in Belgium, England, Finland, Germany, Greece, Ireland, the Netherlands, Norway, Poland, Spain, Sweden and Switzerland. Methods For this analysis, nurse-reported information on migratory status and tasks below their skill level performed during their last shift was used. Random effects models estimated the effect of nurses’ migratory status on reports of these tasks. Results 832 nurses were trained in a developing country (2.5% of total sample). Across countries, a high proportion of both domestically trained and foreign trained nurses from developing countries reported having performed tasks below their skill level during their last shift. After adjusting for nurses’ type of last shift worked, years of experience, and level of education, there remained a pronounced overall effect of being a foreign trained nurse from a developing country and an increase in reports of tasks below skill level performed during the last shift. Conclusion The findings suggest that there remains much room for improvement to optimize the use of nurses’ time and energy. Special attention should be given to raising the professional level of practice of foreign trained nurses from developing countries. Further research is needed to understand the influence of professional practice standards, skill levels of foreign trained nurses from developing countries and values attached to these tasks resulting from previous work experiences in their home countries. This will allow us to better understand the conditions under which foreign trained nurses from developing countries can optimally contribute to professional nursing practice in developed country contexts. / Dr McIntosh is a member of the the RN4CAST Consortium.

De plus en plus d'intérêt est porté au recrutement d'infirmières formées à l’étranger dans plusieurs pays, surtout dans le contexte actuel de pénurie de ressources. Toutefois, il n’existe peu d’écrits sur leur expérience d’intégration ainsi que les facteurs favorisant leur rétention. L'objectif de cette thèse est d'explorer les facteurs explicatifs de la réussite de l'intégration et de la rétention des infirmières diplômées hors Québec (DHQ) dans le système de santé québécois. Cette étude s'est concentrée sur trois processus clefs, à savoir le programme de formation d'appoint, ou programme d'Intégration à la profession infirmière au Québec CWA0B0 (volet 1), la période de probation en emploi (volet 2) et la rétention en emploi des infirmières DHQ (volet 3). Afin d'explorer ceux-ci, un devis mixte, alliant entretiens individuels, groupes de discussion et questionnaires auto-administrés a été adopté. Ultimement, cette thèse a permis l'avancement des connaissances quant à l'intégration des professionnels de la santé immigrants. En effet, cette étude a permis de comprendre le processus d'intégration, définir les sous-processus qu'il sous-entend et proposer un modèle conceptuel adapté aux transitions qui leur sont associées. De surcroit, cette étude est la première à s'intéresser aux facteurs explicatifs de la réussite au programme de transition de pratique et à examiner les effets du recrutement actif sur l'intégration et la rétention à court et moyen terme des infirmières immigrantes. Enfin, elle explore la question de l'importance des différences de valeurs dans la réussite du processus d'intégration et de la rétention, arrivant au constat que leur importance a été largement surévaluée dans les études antérieures. / A shortage of qualified nurses within Quebec has spurred the recruitment of foreign-educated nurses (IENs). Despite this increased interest, foreign-educated nurses face numerous obstacles during their integration into the workplace as evidence by the high attrition rates for both full and part-time hires throughout the Quebec healthcare system. The objective of this thesis is to explain the factors underlying the successful integration and retention of foreign-educated nurses in order to formulate recommendations for the many actors involved throughout the transitional period. The study concentrates on three key phases: 1) the bridging program (Intégration à la profession infirmière au Québec CWA0B0); 2) the probationary period following initial employment; and lastly 3) the employment retention of foreign-educated nurses. A combination of methods was leveraged to investigate the above issues, including individual interviews, group discussions, and self-administered questionnaire. The study first outlines the difficulties associated with the successful integration and retention of foreign-educated nurses in western countries followed those specific to the Quebec healthcare system. Finally, the work examines how socio-demographic characteristics, workplace characteristics, external environment, and psychosocial factors can influence the success of the integration process.

The main purpose of recruiting is to find a job candidate who meets the demands of formal and informal competence at the same time as the candidate should be seen as the right person to the right place. Several job advertisements in the areas of finance and administration has at least two years of work experience as a demand before individuals can be seen as an appropriate job-candidate, hence it becomes a sort of “catch-22” for graduates with no prior work experience. The purpose of this study is to create a better understanding for recruiters’ approach and attitude to hiring individuals who only have a university degree. Our aim is to get an insight into what recruiters’ believe newly examines contributions are to organizations’, how these candidates can increase their chances of reaching an employment and further obtain a deeper understanding of the recruitment process in its various stages. In order to answer our research questions, we used an inductive approach with a qualitative methodology. We conducted semi-structured interviews with recruiters on six different companies to obtain as much depth in our understanding as possible. During our study we have found that recruiter has a positive approach towards hiring graduates without professional experience, however, it differs on the services level. We have created an awareness of that new graduates will contribute with current knowledge and a lot of energy to support business development and modernization. Graduates with no experience can increase their chances in the recruitment process, for example by lowering the threshold for employers in different ways. They should spend time on their applications and sharpen the arguments why he or she is right for the position. We do further refer to our sixth chapel to take note of all conclusions, this because we find difficulties in presenting them briefly.

L’ampleur du phénomène du retour des jeunes diplômés marocains formés à l’étranger et la rareté des contributions scientifiques restent les principaux catalyseurs de s’aventurier dans cette démarche de recherche. Dans cette perspective, nous avons opté pour une étude centrée sur la réussite de la mobilité internationale des jeunes diplômés marocains formés à l’étranger par le biais des représentations sociales. Elle a pour enjeu d’enrichir les avancées de recherches sur la mobilité internationale, et d’apporter des réponses pratiques et tangibles aux nombreuses questions qui se posent au sein du monde des entreprises et des affaires.Notre question de départ se compose de deux volets principaux. Le premier s’intéresse à la compréhension du contenu de la représentation sociale de la réussite de la mobilité internationale de notre population d’étude. Le deuxième volet propose de déterminer les variables qui expliquent cette réussite. Pour répondre à la problématique de ladite recherche, nous avons subdivisé cette étude en deux parties. La première éclaire les théories et concepts inspirés de disciplines variées. Elle traite, par la suite, de la formulation des hypothèses et la présentation du modèle de recherche. La deuxième partie met en exergue les apports empiriques au travers de deux études d’investigation. Primo, nous avons réalisé une étude qualitative menée auprès de trente-deux responsables d’entreprises et experts opérant dans le monde des affaires au Maroc. Secundo, nous avons effectué une étude quantitative destinée aux jeunes diplômés marocains formés à l’étranger. En définitive, nous avons obtenu deux cents quatre-vingt seize réponses à notre questionnaire.Les résultats de notre recherche apportent de diverses implications managériales, notamment sur le plan de la compréhension de la substance de la réussite des jeunes diplômés formés à l’étranger et la détermination des facteurs les plus significatifs expliquant cette réussite. / The magnitude of the return of young Moroccan graduates trained and scarce scientific contributions remain the main catalyst to adventurer in this research process. In this perspective, we opted for a study focusing on the success of the international mobility of young Moroccan graduates trained through social representations. Its challenge to enrich advanced research on international mobility and to provide practical and tangible answers to the many questions that arise in the business world.Our initial question consists of two main components. The first is interested in understanding the content of the social representation of the success of the international mobility of our study population. The second proposes to determine the variables that explain this success. To address the issue of such research, we divided the study into two parts. The first illuminates the theories and concepts inspired from various disciplines. It deals later, the formulation of hypotheses and the presentation of the research model. The second part highlights the empirical knowledge through two field studies. First, we conducted a qualitative study of thirty-two companies and consultants working in the business world leaders in Morocco. Second, we conducted a quantitative study for young Moroccan graduates trained. Ultimately, we got two hundred ninety-six responses to our questionnaire.The results of our research provide various managerial implications, especially in terms of understanding the essence of successful graduates trained and determination of the most significant factors behind this success.

With the rising popularity of online and hybrid learning, this study explores an innovative method to improve students’ learning experiences with Electrical and Computer Engineering lab equipment by employing cutting-edge technologies in augmented reality (AR) and artificial intelligence (AI). Automatic object detection component, aligned with AR application, is developed to recognize equipment, including multimeter, oscilloscope, wave generator, and power supply. The deep neural network model, namely MobileNet SSD v2, is implemented in the study for equipment recognition. We used object detection API from TensorFlow (TF) framework to build the neural network model. When a piece of equipment is detected, the corresponding augmented reality (AR) based tutorial will be displayed on the screen. In this study, a tutorial for multi-meter is implemented. In order to provide users an intuitive and easy-to-follow tutorial, we superimpose virtual models on the real multimeter. In addition, images and web links are added in the tutorial to facilitate users with a better learning experience. Unity3D game engine is used as the primary development tool to merge both framework systems and build immersive scenarios in the tutorial.

The main aim of the thesis is an appraisal of the stream Oslava which belongs to the Náměšť nad Oslavou region with the focus on flood control of the town. The thesis asseses current state of the stream with respect to the state of riverbed, bulwark of the stream and evaluation of the capacity of the stream channel. Calculation water surface profiles have been made by usage of the 1D mathematical model HEC-RAS for selected N-year flows. The capacity of flows and objects in the given period has been detected. There is also a map of the water runoffs included and possible solutions of how to protect the area surrounding the stream are proposed. The thesis was complemented with hydroecological monitoring of the stream channel - the HEM analysis 2014.

This non-experimental, descriptive, quantitative survey attempted to evaluate IMCI implementation in the eThekwini district of KwaZulu -Natal. The study focused on IMCI implementation by IMCI trained registered nurses, health facility support and follow-up and supervision. The research population comprised of all IMCI trained registered nurses working in health facilities in the eThekwini district. The convenient sample consisted of 40 research subjects. Data was collected by means of an interview schedule and a checklist, and analysed using Microsoft Excel 2007. Findings of the study revealed that many of the IMCI trained registered nurses were unable to assess, classify and treat the sick child comprehensively and consistently. The recommended follow-up visit at six weeks after completion of IMCI training, and lack of on-going supervision remains an area of concern. Recommendations were that district or clinic supervisors can enhance the skills of IMCI trained registered nurses through recommended follow-up visits and on-going supervision and the provision of updated IMCI chart booklets. / Health Studies / M.A. (Public Health)

Les modèles de langue pré-entraînés ont montré leur efficacité dans beaucoup de tâches de traitement de la langue naturelle. Ces modèles peuvent capter des régularités générales d'une langue à partir d'un grand ensemble de textes, qui sont utiles dans la plupart des applications en traitement de langue naturelle. Dans ce mémoire, nous étudions les problèmes de dialogue, i.e. générer une réponse à un énoncé de l'utilisateur. Nous exploitons les modèles de langue pré-entraînés pour traiter différents aspects des systèmes de dialogue. Premièrement, les modèles de langue pré-entraînés sont entraînés and utilisés dans les systèmes de dialogue de différentes façons. Il n'est pas clair quelle façon est la plus appropriée. Pour le dialogue orienté-tâche, l’approche de l'état de l'art pour le suivi de l'état de dialogue (Dialogue State Tracking) utilise BERT comme encodeur et empile un autre réseau de neurones récurrent (RNN) sur les sorties de BERT comme décodeur. Dans ce cas, seul l'encodeur peut bénéficier des modèles de langue pré-entraînés. Dans la première partie de ce mémoire, nous proposons une méthode qui utilise un seul modèle BERT pour l'encodeur et le décodeur, permettant ainsi un ajustement de paramètres plus efficace. Notre méthode atteint une performance qui dépasse l'état de l'art. Pour la tâche de génération de réponses dans un chatbot, nous comparons 4 approches communément utilisées. Elles sont basées sur des modèles pré-entraînés et utilisent des objectifs et des mécanismes d'attention différents. En nous appuyant sur des expérimentations, nous observons l'impact de deux types de disparité qui sont largement ignorées dans la littérature: disparité entre pré-entraînement et peaufinage, et disparité entre peaufinage et génération de réponse. Nous montrons que l'impact de ces disparités devient évident quand le volume de données d’entraînement est limité. Afin de remédier à ce problème, nous proposons deux méthodes qui réduisent les disparités, permettant d'améliorer la performance. Deuxièmement, même si les méthodes basées sur des modèles pré-entraînés ont connu de grands succès en dialogue général, nous devons de plus en plus traiter le problème de dialogue conditionné, c'est-à-dire dialogue en relation à une certaine condition (qui peut désigner un personnage, un sujet, etc.). Des chercheurs se sont aussi intéressés aux systèmes de chatbot avec des habiletés de conversation multiples, i.e. chatbot capable de confronter différentes situations de dialogues conditionnés. Ainsi, dans la seconde partie de ce mémoire, nous étudions le problème de génération de dialogue conditionné. D'abord, nous proposons une méthode générale qui exploite non seulement des données de dialogues conditionnées, mais aussi des données non-dialogues (textes) conditionnées. Ces dernières sont beaucoup plus faciles à acquérir en pratique. Ceci nous permet d'atténuer le problème de rareté de données. Ensuite, nous proposons des méthodes qui utilisent le concept d'adaptateur proposé récemment dans la littérature. Un adaptateur permet de renforcer un système de dialogue général en lui donnant une habileté spécifique. Nous montrons que les adaptateurs peuvent encoder des habiletés de dialogue conditionné de façon stricte ou flexible, tout en utilisant seulement 6% plus de paramètres. Ce mémoire contient 4 travaux sur deux grands problèmes de dialogue: l'architecture inhérente du modèle de dialogue basé sur des modèles de langue pré-entraînés, et l'enrichissement d'un système de dialogue général pour avoir des habiletés spécifiques. Ces travaux non seulement nous permettent d'obtenir des performances dépassant de l'état de l'art, mais aussi soulignent l'importance de concevoir l'architecture du modèle pour bien correspondre à la tâche, plutôt que simplement augmenter le volume de données d'entraînement et la puissance de calcul brute. / Pre-trained language models (LMs) have shown to be effective in many NLP tasks. They can capture general language regularities from a large amount of texts, which are useful for most applications related to natural languages. In this thesis, we study the problems of dialogue, i.e. to generate a response to a user's utterance. We exploit pre-trained language models to deal with different aspects of dialogue systems. First, pre-trained language models have been trained and used in different ways in dialogue systems and it is unclear what is the best way to use pre-trained language models in dialogue. For task-oriented dialogue systems, the state-of-the-art framework for Dialogue State Tracking (DST) uses BERT as the encoder and stacks an RNN upon BERT outputs as the decoder. Pre-trained language models are only leveraged for the encoder. In the first part of the thesis, we investigate methods using a single BERT model for both the encoder and the decoder, allowing for more effective parameter updating. Our method achieves new state-of-the-art performance. For the task of response generation in generative chatbot systems, we further compare the 4 commonly used frameworks based on pre-trained LMs, which use different training objectives and attention mechanisms. Through extensive experiments, we observe the impact of two types of discrepancy: pretrain-finetune discrepancy and finetune-generation discrepancy (i.e. differences between pre-training and fine-tuning, and between fine-tuning and generation), which have not been paid attention to. We show that the impact of the discrepancies will surface when limited amount of training data is available. To alleviate the problem, we propose two methods to reduce discrepancies, yielding improved performance. Second, even though pre-training based methods have shown excellent performance in general dialogue generation, we are more and more faced with the problem of conditioned conversation, i.e. conversation in relation with some condition (persona, topic, etc.). Researchers are also interested in multi-skill chatbot systems, namely equipping a chatbot with abilities to confront different conditioned generation tasks. Therefore, in the second part of the thesis, we investigate the problem of conditioned dialogue generation. First, we propose a general method that leverages not only conditioned dialogue data, but also conditioned non-dialogue text data, which are much easier to collect, in order to alleviate the data scarcity issue of conditioned dialogue generation. Second, the concept of Adapter has been recently proposed, which adapts a general dialogue system to enhance some dialogue skill. We investigate the ways to learn a dialogue skill. We show that Adapter has enough capacity to model a dialogue skill for either loosely-conditioned or strictly-conditioned response generation, while using only 6% more parameters. This thesis contains 4 pieces of work relating to the two general problems in dialogue systems: the inherent architecture for dialogue systems based on pre-trained LMs, and enhancement of a general dialogue system for some specific skills. The studies not only propose new approaches that outperform the current state of the art, but also stress the importance of carefully designing the model architecture to fit the task, instead of simply increasing the amount of training data and the raw computation power.

Attracting and retaining strong faculty members in dental schools have long been challenges in the United States. Faced with an emerging crisis in the availability and quality of dental educators, many researchers have focused on analyzing data and trends related to this subject. Even though there are substantial studies that provide a picture of why domestic dentists choose to become dental educators, there are no dedicated studies investigating why foreign-educated dentists want to become dental educators. This distinct area is of particular importance as we witness increasing diversity of patients and an increased need for a more diverse health care workforce. The purpose of this study was to analyze the reasons why foreign-educated dentists became dental educators in United States and furthermore, at University of the Pacific Arthur A. Dugoni School of Dentistry in San Francisco, California. The research data was collected by means of surveys and in-depth interviews of foreign-trained faculty and IDS graduates on staff at Pacific. The data analysis was performed using descriptive statistics for the survey and a process of thematic analysis for interviews. The surveys' analysis yielded the following six factors that most positively influenced foreign-educated dentists in deciding to embrace a career as an academic educator: (1) Intellectual challenges and stimulation; (2) Opportunity to always be on the cutting edge; (3) Interest in science, new discovery, exploration; (4) Opportunity for regular interaction with other faculty dentists; (5) Desire to be a teacher. (6) Collegial environment of the university. There were two most negative factors identified, as follows: (1) Income differential compared to private practice; (2) Pressure to generate income for the university. Corroborated by analysis of the interviews, the following themes emerged: (1) Drive for research; (2) Desire to be on cutting edge. (3) Desire to share knowledge through teaching; (4) Social and personal factors and perceptions with emphasis on mentors' influence; (5) Negative influence of salary difference with respect to private practitioners. The findings of this study were similar to the available studies on foreign-trained dentists and to most of the studies already done on domestically trained dentists. The major factors found were comparable with the up-to-date literature. The elevated research drive, the intellectual challenges, the work environment, the desire to teach, and the mentors' influence were among those which mirrored almost perfectly the other studies. Some fine differences were found for foreign-trained dentists, such as a lighter financial burden caused by smaller student debt and the irrelevance of military practice experience. The study provides a number of suggestions for enhancing the recruiting and retaining process for dental academia: (1) Support and enhance the research capacity of dental schools; (2) Create structures to develop mentors; (3) Invest to build prestige; (4) Find creative ways to offset lower salaries; (5) Foster a pleasant academic working environment; (6) Use international activities to recruit international dentists. The study revealed factors that have been influential in participants' decisions to choose an academic career, in general and at Pacific. It is hoped that this study will be a useful reference in the increasingly difficult endeavor of adding and retaining world-class dental educators.

Eftersom samhället blir allt mer datadrivet revolutionerar användningen av AI och maskininlärning sättet företag fungerar och utvecklas på. Denna studie utforskar användningen av AI, Big Data och Natural Language Processing (NLP) för att förbättra affärsverksamhet och intelligens i företag. Huvudsyftet med denna avhandling är att undersöka om den nuvarande klassificeringsprocessen hos värdorganisationen kan upprätthållas med minskade driftskostnader, särskilt lägre moln-GPU-kostnader. Detta har potential att förbättra klassificeringsmetoden, förbättra produkten som företaget erbjuder sina kunder på grund av ökad klassificeringsnoggrannhet och stärka deras värdeerbjudande. Vidare utvärderas tre tillvägagångssätt mot varandra och implementationerna visar utvecklingen inom området. Modellerna som jämförs i denna studie inkluderar traditionella maskininlärningsmetoder som Support Vector Machine (SVM) och Logistisk Regression, tillsammans med state-of-the-art transformermodeller som BERT, både Pre-Trained och Fine-Tuned. Artikeln visar att det finns en avvägning mellan prestanda och kostnad vilket illustrerar problemet som många företag, som Valu8, står inför när de utvärderar vilket tillvägagångssätt de ska implementera. Denna avvägning diskuteras och analyseras sedan mer detaljerat för att utforska möjliga kompromisser från varje perspektiv i ett försök att hitta en balanserad lösning som kombinerar prestandaeffektivitet och kostnadseffektivitet. / As society is becoming more data-driven, Artificial Intelligence (AI) and Machine Learning are revolutionizing how companies operate and evolve. This study explores the use of AI, Big Data, and Natural Language Processing (NLP) in improving business operations and intelligence in enterprises. The primary objective of this thesis is to examine if the current classification process at the host company can be maintained with reduced operating costs, specifically lower cloud GPU costs. This can improve the classification method, enhance the product the company offers its customers due to increased classification accuracy, and strengthen its value proposition. Furthermore, three approaches are evaluated against each other, and the implementations showcase the evolution within the field. The models compared in this study include traditional machine learning methods such as Support Vector Machine (SVM) and Logistic Regression, alongside state-of-the-art transformer models like BERT, both Pre-Trained and Fine-Tuned. The paper shows a trade-off between performance and cost, showcasing the problem many companies like Valu8 stand before when evaluating which approach to implement. This trade-off is discussed and analyzed in further detail to explore possible compromises from each perspective to strike a balanced solution that combines performance efficiency and cost-effectiveness.