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Academic literature on the topic 'Training visivo'

Author: Grafiati

Published: 11 March 2023

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Journal articles on the topic "Training visivo"

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Konukseven, E. Ilhan, M. Ercument Önder, Erkan Mumcuoglu, and Reha Sukru Kisnisci. "Development of a Visio-Haptic Integrated Dental Training Simulation System." Journal of Dental Education 74, no. 8 (August 2010): 880–91. http://dx.doi.org/10.1002/j.0022-0337.2010.74.8.tb04945.x.

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Wei Lou, Wei Lou, Dewen Cheng Dewen Cheng, Luo Gu Luo Gu, Weihong Hou Weihong Hou, and Yongtian Wang Yongtian Wang. "Optical design and evaluation of Alvarez-type vision-training system." Chinese Optics Letters 16, no. 7 (2018): 072201. http://dx.doi.org/10.3788/col201816.072201.

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Glow, Steven D., Vincent J. Colucci, Douglas R. Allington, Curtis W. Noonan, and Earl C. Hall. "Managing Multiple-Casualty Incidents: A Rural Medical Preparedness Training Assessment." Prehospital and Disaster Medicine 28, no. 4 (April 18, 2013): 334–41. http://dx.doi.org/10.1017/s1049023x13000423.

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AbstractObjectiveThe objectives of this study were to develop a novel training model for using mass-casualty incident (MCI) scenarios that trained hospital and prehospital staff together using Microsoft Visio, images from Google Earth and icons representing first responders, equipment resources, local hospital emergency department bed capacity, and trauma victims. The authors also tested participants’ knowledge in the areas of communications, incident command systems (ICS), and triage.MethodsParticipants attended Managing Multiple-Casualty Incidents (MCIs), a one-day training which offered pre- and post-tests, two one-hour functional exercises, and four distinct, one-hour didactic instructional periods. Two MCI functional exercises were conducted. The one-hour trainings focused on communications, National Incident Management Systems/Incident Command Systems (NIMS/ICS) and professional roles and responsibilities in NIMS and triage. The trainings were offered throughout communities in western Montana. First response resource inventories and general manpower statistics for fire, police, Emergency Medical Services (EMS), and emergency department hospital bed capacity were determined prior to MCI scenario construction. A test was given prior to and after the training activities.ResultsA total of 175 firefighters, EMS, law enforcement, hospital personnel or other first-responders completed the pre- and post-test. Firefighters produced higher baseline scores than all other disciplines during pre-test analysis. At the end of the training all disciplines demonstrated significantly higher scores on the post-test when compared with their respective baseline averages. Improvements in post-test scores were noted for participants from all disciplines and in all didactic areas: communications, NIMS/ICS, and triage.ConclusionsMass-casualty incidents offer significant challenges for prehospital and emergency room workers. Fire, Police and EMS personnel must secure the scene, establish communications, define individuals’ roles and responsibilities, allocate resources, triage patients, and assign transport priorities. After emergency department notification and in advance of arrival, emergency department personnel must assess available physical resources and availability and type of manpower, all while managing patients already under their care. Mass-casualty incident trainings should strengthen the key, individual elements essential to well-coordinated response such as communications, incident management system and triage. The practice scenarios should be matched to the specific resources of the community. The authors also believe that these trainings should be provided with all disciplines represented to eliminate training “silos,” to allow for discussion of overlapping jurisdictional or organizational responsibilities, and to facilitate team building.GlowSD, ColucciVJ, AllingtonDR, NoonanCW, HallEC. Managing multiple-casualty incidents: a rural medical preparedness training assessment. Prehosp Disaster Med. 2013;28(4):1-8.

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Caicedo-Quiroz, Rosangela, and Julia Céspedez-Acuña. "HACIA UNA FORMACIÓN DEL TÉCNICO SUPERIOR ENENFERMERÍA DESDE UNA VISION SOCIO-PEDAGOGICA." Identidad Bolivariana 1, no. 1 (January 5, 2017): 22–32. http://dx.doi.org/10.37611/ib1ol122-32.

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Considerations are presented about the formation of the Higher Nursing Technician and the necessary preparation to perform in the social context in actions of health prevention. The ideas constitute a socio-pedagogical modeling proposed from the perspective of the community from a formative intentionality, a epistemological orientation and logical criteria of systematization of the contents and the practice, to identify and monitor, in a preventive manner, the problems of Health; therefore, it seeks to understand how to recognize, reduce or avoid artifices to that social reality is submitted daily, so, in the pedagogical order has three purposes: must know (knowledge), must know how to do: (skills) and must know how to coexist: (values): Its results will be specified in the follow-up of the research from the development of a strategy with the same ends. Keywords: community intervention, school context, community practice, work community and prevention.

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Vailland, Guillaume, Yoren Gaffary, Louise Devigne, Valérie Gouranton, Bruno Arnaldi, and Marie Babel. "Power Wheelchair Virtual Reality Simulator with Vestibular Feedback." Modelling, Measurement and Control C 81, no. 1-4 (December 31, 2020): 35–42. http://dx.doi.org/10.18280/mmc_c.811-407.

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Autonomy and the ability to maintain social activities can be challenging for people with disabilities experiencing reduced mobility. In the case of disabilities that impact mobility, power wheelchairs can help such people retain or regain autonomy. Nonetheless, driving a power wheelchair is a complex task that requires a combination of cognitive, visual and visuo-spatial abilities. In practice, people need to pass prior ability tests and driving training before being prescribed a power wheelchair by their therapist. Still, conventional training in occupational therapy can be insufficient for some people with severe cognitive and/or visio-spatial functions. As such, these people are often prevented from obtaining a power wheelchair prescription from their therapist due to safety concerns. In this context, driving simulators might be efficient and promising tools to provide alternative, adaptive, flexible, and safe training. In previous work, we proposed a Virtual Reality (VR) driving simula-integrating vestibular feedback to simulate wheelchair motion sensations. The performance and acceptability of a VR simulator rely on satisfying user Quality of Experience (QoE). Therefore, our simulator is designed to give the user a high Sense of Presence (SoP) and low Cyber-sickness. This paper presents a pilot study assessing the impact of the vestibular feedback provided on user QoE. Participants were asked to perform a driving task whilst in the simulator under two conditions: with and without vestibular feedback. User QoE is assessed through subjective questionnaires measuring user SoP and cyber-sickness. The results show that vestibular feedback activation increases SoP and decreases cyber-sickness. This study constitutes a mandatory step before clinical trials and, as such, only enrolled people without disabilities.

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Ríos Garit, Jesús, Yanet Pérez Surita, Aurelio Olmedilla Zafra, and Verónica Gómez-Espejo. "Psicología y lesiones deportivas: Un estudio en lanzadores de beisbol." Cuadernos de Psicología del Deporte 21, no. 1 (January 1, 2021): 102–18. http://dx.doi.org/10.6018/cpd.416351.

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Las lesiones constituyen uno de los principales problemas en el deporte debido a las repercusiones negativas sobre la salud y el rendimiento del deportista. Su etiología multifactorial requiere que sean abordadas también desde lo psicológico para comprender su comportamiento de manera integral y lograr mayores impactos en su prevención. La presente investigación se realizó con los lanzadores de béisbol de primera categoría de la provincia de Villa Clara, Cuba, con el propósito de determinar la relación entre las variables psicológicas asociadas al rendimiento del deportista y las lesiones. Se estudiaron un total de 48 lanzadores constituyendo una población heterogénea, integrada por deportistas noveles y de mayor experiencia competitiva. Se aplicó el Cuestionario de Aspectos Deportivos y Lesiones, el Inventario de Ansiedad Rasgo-Estado, el Inventario de Ansiedad Estado en Competición y el Inventario Psicológico de Ejecución Deportiva. Los resultados obtenidos muestran que los lanzadores estudiados presentan una baja percepción de la relación entre variables psicológicas y lesiones, constatando además que en la competición aparecen más lesiones que en los entrenamientos y que los deportistas con antecedentes de lesiones presentan diferencias significativas en el estado de determinadas variables psicológicas en comparación con los lanzadores que no se han lesionado. Estas diferencias se observan en la ansiedad estado en competición, la autoconfianza, el control del afrontamiento negativo, el control de la atención y el control visual e imaginativo. Injuries are one of the main problems in sport due to the negative impact on the health and performance of the athlete. Their multi-causal etiology requires that they also be approached from the psychological to understand their behavior in an integral way and achieve greater impacts in its prevention. The present investigation was carried out with the first category Baseball pitchers of the province of Villa Clara, Cuba, with the purpose of determining the relationship between the psychological variables associated with the athlete's performance and the injuries. A total of 48 pitchers were studied, constituting a heterogeneous population, made up of new athletes with greater competitive experience. The Sports Aspects and Injuries Questionnaire, the Trait-State Anxiety Inventory, the Competing State Anxiety Inventory and the Psychological Inventory of Sports Execution were applied. The results obtained show that the pitchers studied have a low perception of the relationship between psychological variables and injuries, also confirming that in the competition there are more injuries than in training. In addition, the results are displaying that athletes with a history of injuries and within these, the ones that most injuries have suffered, present significant differences in the status of certain psychological variables compared to pitchers who have not been injured. This difference can be observed in competition state anxiety, self-confidence, negative coping control, attention control, and visual and imaginative control. Le lesioni sono uno dei principali problemi negli sport a causa dell'impatto negativo sulla salute e sulle prestazioni dell'atleta. La loro eziologia multifattoriale richiede che vengano affrontati anche dal punto di vista psicologico per comprendere il loro comportamento in modo integrale e ottenere maggiori impatti nella sua prevenzione. La presente indagine è stata condotta con i lanciatori di baseball di prima categoria della provincia di Villa Clara con lo scopo di determinare la relazione tra le variabili psicologiche associate alla prestazione dell'atleta e le lesioni. Sono stati studiati un totale di 48 lanciatori, costituendo una popolazione eterogenea, composta da nuovi atleti con una maggiore esperienza competitiva. Sono stati applicati il questionario sugli aspetti sportivi e sugli infortuni, l'inventario dell'ansia trait-state, l'inventario dell'ansia di stato in competizione e l'inventario psicologico dell'esecuzione sportiva. I risultati ottenuti mostrano che i lanciatori studiati hanno una bassa percezione del rapporto tra variabili psicologiche e infortuni, confermando anche che nella competizione ci sono più infortuni che in allenamento e che gli atleti con una storia di infortuni e al loro interno, quelli che più le lesioni hanno sofferto, presentano differenze significative nello stato di alcune variabili psicologiche rispetto ai lanciatori che non sono stati feriti. Questa differenza può essere osservata in variabili come; l'ansia era in competizione, la fiducia in se stessi, il controllo del coping negativo, il controllo dell'attenzione e il controllo visivo e immaginativo. As lesões são um dos principais problemas do esporte devido ao impacto negativo na saúde e no desempenho do atleta. Sua etiologia multifatorial exige que eles também sejam abordados do ponto de vista psicológico para entender seu comportamento de maneira integral e obter maiores impactos em sua prevenção. A presente investigação foi realizada com a primeira categoria de lançadores de basebol da província de Villa Clara, Cuba, com o objetivo de determinar a relação entre as variáveis psicológicas associadas ao desempenho do atleta e as lesões. Foram estudados 48 lançadores, constituindo uma população heterogênea, composta por novos atletas com maior experiência competitiva. Foram aplicados o Questionário de Aspectos e Lesões Esportivas, o Inventário de Ansiedade Traço-Estado, o Inventário de Ansiedade Estado Competente e o Inventário Psicológico de Execução Esportiva. Os resultados obtidos mostram que os lançadores estudados têm uma baixa percepção da relação entre variáveis psicológicas e lesões, confirmando também que na competição há mais lesões do que nos treinos e que atletas com histórico de lesões e dentro delas, as que mais lesões sofridas apresentam diferenças significativas no status de certas variáveis psicológicas em comparação com lançadores que não foram feridos. Essa diferença pode ser observada na ansiedade do estado de competição, autoconfiança, controle negativo de enfrentamento, controle da atenção e controle visual e imaginativo.

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Przybył, Krzysztof, Piotr Boniecki, Krzysztof Koszela, Łukasz Gierz, and Mateusz Łukomski. "Computer vision and artificial neural network techniques for classification of damage in potatoes during the storage process." Czech Journal of Food Sciences 37, No. 2 (May 10, 2019): 135–40. http://dx.doi.org/10.17221/427/2017-cjfs.

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The research methodology consists of several stages to develop a noninvasive method of identifying the turgor of potato tubers during the storage. During the first stage, a graphic database (set of training data) has been created for selected varieties of potatoes. As a next step, special proprietary software called ’PID system’ was used together with a commercial MATLAB package to extract parameters defining the digital image descriptors. This included: hue space models, shape coefficient and image texture. Thirdly, Artificial Neural Network (ANN) training was conducted with the use of Statistica and MATLAB tools. As a result of the analysis, a neural model has been obtained, which had the greatest classification features.

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Jing Li, Jing Li, and Xueping Luo Jing Li. "Malware Family Classification Based on Vision Transformer." 電腦學刊 34, no. 1 (February 2023): 087–99. http://dx.doi.org/10.53106/199115992023023401007.

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<p>Cybersecurity worries intensify as Big Data, the Internet of Things, and 5G technologies develop. Based on code reuse technologies, malware creators are producing new malware quickly, and new malware is continually endangering the effectiveness of existing detection methods. We propose a vision transformer-based approach for malware picture identification because, in contrast to CNN, Transformer’s self-attentive process is not constrained by local interactions and can simultaneously compute long-range mine relationships. We use ViT-B/16 weights pre-trained on the ImageNet21k dataset to improve model generalization capability and fine-tune them for the malware image classification task. This work demonstrates that (i) a pure attention mechanism applies to malware recognition, and (ii) the Transformer can be used instead of traditional CNN for malware image recognition. We train and assess our models using the MalImg dataset and the BIG2015 dataset in this paper. Our experimental evaluation found that the recognition accuracy of transfer learning-based ViT for MalImg samples and BIG2015 samples is 99.14% and 98.22%, respectively. This study shows that training ViT models using transfer learning can perform better than CNN in malware family classification.</p> <p> </p>

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Su, Chen, Ao Chai, Xikai Tu, Hongyu Zhou, Haiqiang Wang, Zufang Zheng, Jingyan Cao, and Jiping He. "Passive and Active Control Strategies of a Leg Rehabilitation Exoskeleton Powered by Pneumatic Artificial Muscles." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 10 (March 9, 2017): 1759021. http://dx.doi.org/10.1142/s0218001417590212.

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Nerve injury can cause lower limb paralysis and gait disorder. Currently lower limb rehabilitation exoskeleton robots used in the hospitals need more power to correct abnormal motor patterns of stroke patients’ legs. These gait rehabilitation robots are powered by cumbersome and bulky electric motors, which provides a poor user experience. A newly developed gait rehabilitation exoskeleton robot actuated by low-cost and lightweight pneumatic artificial muscles (PAMs) is presented in this research. A model-free proxy-based sliding mode control (PSMC) strategy and a model-based chattering mitigation robust variable control (CRVC) strategy were developed and first applied in rehabilitation trainings, respectively. As the dynamic response of PAM due to the compressed air is low, an innovative intention identification control strategy was taken in active trainings by the use of the subject’s intention indirectly through the estimation of the interaction force between the subject’s leg and the exoskeleton. The proposed intention identification strategy was verified by treadmill-based gait training experiments.

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CAILLAULT, EMILIE, and CHRISTIAN VIARD-GAUDIN. "MIXED DISCRIMINANT TRAINING OF HYBRID ANN/HMM SYSTEMS FOR ONLINE HANDWRITTEN WORD RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 01 (February 2007): 117–34. http://dx.doi.org/10.1142/s0218001407005338.

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Online handwritten word recognition systems usually rely on Hidden Markov Models (HMMs), which are effective under many circumstances, but suffer some major limitations in real world applications. Artificial neural networks (ANN) appear to be a promising alternative, however they failed to model sequence data such as online handwriting due to their variable lengths. As a consequence, by combining HMMs and ANN, we can expect to take advantage of the robustness and flexibility of the HMMs generative models and of the discriminative power of the ANN. Training such a hybrid system is not straightforward, this is why so few attempts are encountered in literature. We compare several different training schemes: maximum likelihood (ML) and maximum mutual information (MMI) criteria in the framework of online handwriting recognition with a global optimization approach defined at the word level. A new generic criterion mixing generative model and discriminant trainings is proposed, it allows to train a multistate TDNN-HMM system directly at the word level. This architecture is based on an analytical approach with an implicit segmentation. To control the implicit segmentation and to initialize correctly the system without bootstrapping with another recognition system, we have defined a process that constraints the segmentation path and a measure called Average Segmentation Rate (ASR). Recognition experiments on the online IRONOFF database demonstrated the interest of the generic training criterion and the control of the implicit segmentation.

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Dissertations / Theses on the topic "Training visivo"

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Cole, Timothy R. "Investigating Augmented Reality Visio-Haptic Techniques for Medical Training." Thesis, Bangor University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.536476.

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Wilkins, Luke. "Vision testing and visual training in sport." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/6313/.

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This thesis examines vision testing and visual training in sport. Through four related studies, the predictive ability of visual and perceptual tests was examined in a range of activities including driving and one-handed ball catching. The potential benefits of visual training methods were investigated (with particular emphasis on stroboscopic training), as well as the mechanisms that may underpin any changes. A key theme throughout the thesis was that of task representativeness; a concept by which it is believed the more a study design reflects the environment it is meant to predict, the more valid and reliable the results obtained are. Chapter one is a review of the literature highlighting the key areas which the thesis as a whole addresses. Chapter’s two to five include the studies undertaken in this thesis and follow the same format each time; an introduction to the relevant research, a methods section detailing the experimental procedure, a results section which statistically analysed the measures employed, and a discussion of the findings with reference to the existing literature. Finally, in chapter six the strengths and limitations of the thesis are considered, before suggestions are made for future studies, and concluding remarks made.

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Gajić, Bojana. "Training strategies for efficient deep image retrieval." Doctoral thesis, Universitat Autònoma de Barcelona, 2021. http://hdl.handle.net/10803/673961.

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En aquesta tesi ens centrem en la recuperació i re-identificació d’imatges. L’entrenament de xarxes neuronals profundes usant funcions de pèrdua basades en rànquing ha esdevingut un estàndard de facto per a les tasques de recuperació i re-identificació. Hi analitzem i aportem propostes de respostes a tres qüestions principals: 1) Quines són les estratègies més rellevants dels mètodes de l’estat de l’art i com es poden combinar per obtenir un millor rendiment? 2) Es pot realitzar un mostreig de mostres negatives restrictiu de manera eficient (O(1)) mentre es proporciona un rendiment millorat respecte al mostreig aleatori simple? 3) Es poden aconseguir objectius de reconeixement i recuperació mitjançant una funció de pèrdua basada en el reconeixement? En primer lloc, en el capítol 4 analitzem la importància d’algunes estratègies de l’estat de l’art relacionades amb la formació d’un model d’aprenentatge profund que abasta l’augment d’imatges, l’arquitectura vertebral i la mineria de tripletes restrictives. A continuació, combinem les millors estratègies per dissenyar una arquitectura profunda senzilla, a més d’una metodologia d’entrenament per a una identificació de persones efectiva i d’alta qualitat. Avaluem àmpliament cada opció de disseny, donant lloc a una llista de bones pràctiques per a la re-identificació de persones. Seguint aquestes pràctiques, el nostre enfocament supera l’estat de l’art, inclosos mètodes més complexos amb components auxiliars, de forma amplia en quatre conjunts de dades de referència. També proporcionem una anàlisi qualitativa de la nostra representació entrenada que indica que, tot i ser compacta, és capaç de captar informació de regions focalitzades i discriminatives, d’una manera semblant a un mecanisme d’atenció implícita. En segon lloc, al capítol 5 abordem el problema del mostreig de mostres negatives restrictiu quan s’entrena un model amb funcions del tipus pèrdua per tripletes. En aquest capítol presentem”Bag of Negatives (BoN)”, un mètode de mineria de mostres negatives ràpid i restrictiu, que proporciona un conjunt, tripleta o parella de mostres d’entrenament potencialment rellevants. BoN és un mètode eficient que selecciona una bossa demostres negatives restringides basat en una nova estratègia d’indexació dispersa (hashing) en línia. Mostrem la superioritat de BoN en front dels mètodes de mineria demostres negatives de l’estat de l’art en termes de precisió i temps d’entrenament en tres grans conjunts de dades. Finalment, al capítol 6 fem la hipòtesi que entrenar un model d’aprenentatge de mètriques maximitzant l’àrea sota la corba ROC (que és una mesura de rendiment típica dels sistemes de reconeixement automàtic) pot induir una classificació implícita adequada per a problemes de recuperació. Aquesta hipòtesi es recolza en el fet que “una corba és rellevant en l’espai ROC si i només si és rellevant a l’espai Precisió/Exhaustivitat (PrecisionRecall)” [17]. Per a provar aquesta hipòtesi, dissenyem una relaxació derivable i aproximada de l’àrea sota la corba ROC.Malgrat la seva simplicitat, la funció de pèrdua basada en àrea sota la corba (AUC), combinada amb ResNet50 com a arquitectura vertebral, aconsegueix els resultats de l’estat de l’art en dos conjunts de dades per a recuperació de mostres a gran escala disponibles públicament. A més, la funció de pèrdua basada en AUC aconsegueix un rendiment comparable a mètodes més complexos, específics de domini, que marquen l’estat de l’art en el problema de la re-identificació de vehicles.
En esta tesis nos centramos en la recuperación y re-identificación de imágenes. El entrenamiento de redes neuronales profundas usando funciones de pérdida basadas en ranking se ha convertido en un estándar de facto para las tareas de recuperación y re-identificación. Analizamos y aportamos propuestas de respuestas a tres cuestiones principales: 1) ¿Cuáles son las estrategias más relevantes de los métodos del estado del arte y cómo se pueden combinar para obtener un mejor rendimiento? 2) ¿Se puede realizar unmuestreo de muestras negativas restrictivo de manera eficiente (O(1)) mientras se proporciona un rendimiento mejorado respecto almuestreo aleatorio simple? 3) ¿Se pueden conseguir objetivos de reconocimiento y recuperación mediante una función de pérdida basada en el reconocimiento? En primer lugar, en el capítulo 4 analizamos la importancia de algunas estrategias del estado del arte relacionadas con la formación de un modelo de aprendizaje profundo que abarca el aumento de imágenes, la arquitectura vertebral y la minería de tripletas restrictivas. A continuación, combinamos las mejores estrategias para diseñar una arquitectura profunda sencilla, además de una metodología de entrenamiento para una identificación de personas efectiva y de alta calidad. Evaluamos ampliamente cada opción de diseño, dando lugar a una lista de buenas prácticas para la re-identificación de personas. Siguiendo estas prácticas, nuestro enfoque supera el estado del arte, incluidos métodos más complejos con componentes auxiliares, de forma amplia en cuatro conjuntos de datos de referencia. También proporcionamos un análisis cualitativo de nuestra representación entrenada que indica que, a pesar de ser compacta, es capaz de captar información de regiones focalizadas y discriminativas, de una manera similar a un mecanismo de atención implícita. En segundo lugar, el capítulo 5 abordamos el problema del muestreo demuestras negativas restrictivo cuando se entrena un modelo con funciones del tipo pérdida por tripletas. En este capítulo presentamos “Bag of Negative (BoN)”, un método de minería de muestras negativas rápido y restrictivo, que proporciona un conjunto, tripleta o pareja de muestras de entrenamiento potencialmente relevantes. BoN es un método eficiente que selecciona una bolsa de muestras negativas restringidas basado en una nueva estrategia de indexación dispersa (hashing) en línea. Mostramos la superioridad de BoN frente a losmétodos de minería demuestras negativas del estado del arte en términos de precisión y tiempo de entrenamiento en tres grandes conjuntos de datos. Finalmente, en el capítulo 6 hacemos la hipótesis de que entrenar un modelo de aprendizaje demétricas maximizando el área bajo la curva ROC (que es una medida de rendimiento típica de los sistemas de reconocimiento automático) puede inducir una clasificación implícita adecuada para tareas de recuperación. Esta hipótesis se apoya en el hecho de que üna curva es relevante en el espacio ROC si y sólo si es relevante en el espacio Precisión / Exhaustividad (PrecisionRecall)-[17]. Para probar esta hipótesis, diseñamos una relajación derivable y aproximada del área bajo la curva ROC. A pesar de su simplicidad, la función de pérdida basada en área bajo la curva (AUC), combinada con ResNet50 como arquitectura vertebral, consigue los resultados del estado del arte en dos conjuntos de datos para recuperación de muestras a gran escala disponibles públicamente. Además, la función de pérdida basada en AUC consigue un rendimiento comparable a métodosmás complejos, específicos de dominio, que marcan el estado del arte en el problema de la reidentificación de vehículos.
In this thesis we focus on image retrieval and re-identification. Training a deep architecture using a ranking loss has become standard for the retrieval and re-identification tasks. We analyze and propose answers on three main issues: 1) What are the most relevant strategies of state-of-the-art methods and how can they be combined in order to obtain a better performance? 2) Can hard negative sampling be performed efficiently (O(1)) while providing improved performance over naïve random sampling? 3) Can recognition and retrieval objectives be achieved by using a recognition-based loss? First, in chapter 4 we analyze the importance of some state of the art strategies related to the training of a deep model such as image augmentation, backbone architecture and hard triplet mining. We then combine the best strategies to design a simple deep architecture plus a training methodology for effective and high quality person re-identification. We extensively evaluate each design choice, leading to a list of good practices for person re-identification. By following these practices, our approach outperforms the state of the art, including more complex methods with auxiliary components, by large margins on four benchmark datasets. We also provide a qualitative analysis of our trained representation which indicates that, while compact, it is able to capture information from localized and discriminative regions, in a manner akin to an implicit attention mechanism. Second, in chapter 5 we address the problem of hard negative sampling when training a model with triplet-like loss. In this chapter we present Bag of Negatives (BoN), a fast hard negative mining method, that provides a set, triplet or pair of potentially relevant training samples. BoN is an efficient method that selects a bag of hard negatives based on a novel online hashing strategy. We show the superiority of BoN against state-of-the-art hard negative mining methods in terms of accuracy and training time over three large datasets. Finally, in chapter 6 we hypothesize that training a metric learning model by maximizing the area under the ROC curve (which is a typical performance measure of recognition systems) can induce an implicit ranking suitable for retrieval problems. This hypothesis is supported by the fact that “a curve dominates in ROC space if and only if it dominates in PR space” [17]. To test this hypothesis, we design an approximated, derivable relaxation of the area under the ROC curve. Despite its simplicity, AUC loss, combined with ResNet50 as a backbone architecture, achieves state-of-the-art results on two large scale publicly available retrieval datasets. Additionally, the AUC loss achieves comparable performance to the more complex, domain specific, state-of-the-art methods for vehicle re-identification.
Universitat Autònoma de Barcelona. Programa de Doctorat en Informàtica

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MATTEO, BARBARA MARIA. "Brain Stimulation for Vision Recovery." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2018. http://hdl.handle.net/10281/199049.

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Il lavoro è compost da tre fasi: 1. La prima fase, attraverso un lavoro di revisione bibliografica, mirava a scoprire lo stato dell'arte nella riabilitazione dell'emianopsia. Dopo aver ottenuto una panoramica di tutte le possibilità di trattamento, si è considerato quale fosse l'approccio più appropriato. Sono stati analizzati 56 articoli che descrivono l'uso di varie tecniche utilizzate per promuovere il recupero del campo visivo. La riabilitazione dell’emianopsia di basa principalmente su due tecniche: "border training" e "blindsight training". Sebbene non sia stata possibile una meta-analisi, i risultati di una valutazione semiquantitativa hanno suggerito che il miglioramento delle abilità visive ottenute è correlato al tipo di riabilitazione utilizzata: la riabilitazione di tipo “border” sembra migliorare la rilevazione degli stimoli visivi, mentre la riabilitazione di tipo “blindsight” sembra migliorare la loro elaborazione. Infine, l'aggiunta della stimolazione elettrica transcranica a corrente continua sembra migliorare gli effetti della riabilitazione del campo visivo. 2. La seconda fase aveva lo scopo di testare in due pazienti emianopici il metodo riabilitativo “blindsight” associandolo all’uso della stimolazione elettrica transcranica a corrente diretta. Il primo paziente è stato sottoposto ad un ciclo di trattamento “blindsight” associato a tDCS seguito da un ciclo di solo trattamento “blindsight”. Il secondo paziente ha subito i due cicli di riabilitazione in ordine inverso. I pazienti hanno mostrato punteggi migliori nelle valutazioni clinico-strumentali, funzionali ed ecologiche quando alla riabilitazione era stata associata la stimolazione elettrica. In questi due casi, la stimolazione elettrica parieto-occipitale ha modulato gli effetti indotti dal trattamento. 3. La terza fase è stata finalizzata a testare il trattamento di stimolazione elettrica su emianopsia utilizzando un disegno di studio appropriato e un campione più ampio. In questa fase l’Università Bicocca ha collaborato con Institute for Medical Psychology dell'Università Otto-von-Guericke. I risultati hanno mostrato che la stimolazione cerebrale con corrente elettrica potrebbe modulare la rete neuronale e questa tecnica potrebbe essere un facilitatore nella riabilitazione dell'emianopsia.
The work was divided into three phases: 1. The first phase was aimed to discover the state-of-art in the rehabilitation of hemianopia. The review work results in an overview of all the chances for treat hemianopia and evaluates which one would be the most appropriate approach. We analysed 56 articles describing the use of various techniques used to promote visual field recovery, but concentrating on two approaches: “border training”, and “blindsight training”. Although no formal meta-analysis was possible, the results of a semi-quantitative evaluation suggested that the improvement in visual skills obtained is related to the type of training used: border rehabilitation seems to improve the detection of visual stimuli, whereas blindsight rehabilitation seems to improve their processing. Finally, the addition of transcranial direct current stimulation seems to enhance the effects of visual field rehabilitation. 2. The second phase was aimed to test in two hemianopic patients the rehabilitation method that looks us more suitable in order to treat hemianopia. The first patient underwent blindsight treatment which was combined with tDCS followed by blindsight training alone. The second patient underwent the two training rounds in reverse order. The patients showed better scores in clinical-instrumental, functional, and ecological assessments after tDCS combined with blindsight rehabilitation rather than rehabilitation alone. In this two-case report parietal-occipital tDCS modulate the effects induced by blindsight treatment on hemianopia. 3. The third phase was aimed to test the most promising treatment using an appropriate study design and a large sample of people. In this phase, we collaborate with the Institute for Medical Psychology at Otto-von-Guericke University. The study results in some consideration about the effectiveness of the current stimulation on hemianopia. The project was aimed at investigating the effects of stimulation with electrical current on hemianopics people by using the different stimulation techniques. The results showed that the brain stimulation with electrical current could effectively re-modulate the neuronal network enabling different way to transport the info to the brain: this technique could have been a facilitator in the hemianopia’s rehabilitation.

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Romero, Adriana. "Assisting the training of deep neural networks with applications to computer vision." Doctoral thesis, Universitat de Barcelona, 2015. http://hdl.handle.net/10803/316577.

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Deep learning has recently been enjoying an increasing popularity due to its success in solving challenging tasks. In particular, deep learning has proven to be effective in a large variety of computer vision tasks, such as image classification, object recognition and image parsing. Contrary to previous research, which required engineered feature representations, designed by experts, in order to succeed, deep learning attempts to learn representation hierarchies automatically from data. More recently, the trend has been to go deeper with representation hierarchies. Learning (very) deep representation hierarchies is a challenging task, which involves the optimization of highly non- convex functions. Therefore, the search for algorithms to ease the learning of (very) deep representation hierarchies from data is extensive and ongoing. In this thesis, we tackle the challenging problem of easing the learning of (very) deep representation hierarchies. We present a hyper-parameter free, off-the-shelf, simple and fast unsupervised algorithm to discover hidden structure from the input data by enforcing a very strong form of sparsity. We study the applicability and potential of the algorithm to learn representations of varying depth in a handful of applications and domains, highlighting the ability of the algorithm to provide discriminative feature representations that are able to achieve top performance. Yet, while emphasizing the great value of unsupervised learning methods when labeled data is scarce, the recent industrial success of deep learning has revolved around supervised learning. Supervised learning is currently the focus of many recent research advances, which have shown to excel at many computer vision tasks. Top performing systems often involve very large and deep models, which are not well suited for applications with time or memory limitations. More in line with the current trends, we engage in making top performing models more efficient, by designing very deep and thin models. Since training such very deep models still appears to be a challenging task, we introduce a novel algorithm that guides the training of very thin and deep models by hinting their intermediate representations. Very deep and thin models trained by the proposed algorithm end up extracting feature representations that are comparable or even better performing than the ones extracted by large state-of-the-art models, while compellingly reducing the time and memory consumption of the model.

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Epperson, Sean T. "Animation within a multimedia training system for night vision goggles." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA294095.

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Thesis (M.S. in Information Technology Management) Naval Postgraduate School, March 1995.
"March 1995." Thesis advisor(s): Kishore Sengupta, Alice Crawford. Bibliography: p. 43-45. Also available online.

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Rae, Sheila M. "The effect of vision training on accommodation and myopia progression." Thesis, Anglia Ruskin University, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.441555.

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Treleaven, Allison Jean. "Improving reading performance in peripheral vision: An adaptive training method." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1460670659.

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Kamolpattana, Supara. "Science museum explainer training : exploring factors that influence visitor-explainer interactions." Thesis, University of the West of England, Bristol, 2016. http://eprints.uwe.ac.uk/28534/.

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There is currently minimal understanding as to how explainer training in Informal Science Institutions (ISIs) incorporates socio-cultural contexts. This thesis investigates this gap in the literature by examining the role of socio-cultural context in explainer training programmes within Informal Science Institutions, through the examination of three research questions. The research employs a mixed methods approach comprising 21 interviews, three international case studies, a questionnaire survey of 600 visitors and 41 explainers, in addition to observations of explainer-visitor interaction. From the international perspective, fifteen experts from 13 countries were interviewed. From the international experts’ viewpoint it was found that socio-cultural context influences the main roles of ISI explainers, and the knowledge and skills associated to success (knowledge of visitor, communication skills and knowledge of scientific content). Additionally, training programmes that provide opportunities for explainers’ active participation and collaboration were highlighted as important. The three case studies incorporated observation of eleven types of training session and questionnaires for explainers (n=55) over three ISIs: the New York Hall of Science (NYSCI) in the USA, Petrosains – the Discovery Centre (Petrosains), in Malaysia and the Natural History Museum (NHM) in the UK. The three case studies reveal detailed information on how socio-cultural context can support explainers’ active participation and collaboration within a training context, as well as the role of techniques such as exploring theory, being an observer, practicing communication, being observed and feedback, and coaching by others within training settings. The case studies also expose the multiple participants who may be involved in training; educators, experienced explainers, peers and visitors, as well as the role of training delivery through discussion and interaction. In the specific context of Thailand 600 visitors and 41 explainers completed questionnaires, six Thai educators were interviewed, and ten explainer-visitor interactions were observed. The Thai educators indicated the role, knowledge and skills required of explainers in the Thai socio-cultural context, and how training supports the personal skill development of explainers. The Thai interview and explainer data also highlights some gaps in Thai explainer training at present, whereby interaction appears mainly between educators and explainers, overlooking the role of experienced explainers or peers. Additionally, organisational policy support directed at ongoing training more strongly featuring social interaction is discussed in terms of its potential shortcomings. At the specific at level of explainer-visitor interaction, visitors are evidenced to have positive attitudes towards explainers in general, though the social interaction between explainer and visitors suggest multiple perceptions of the explainers’ role; activities that are seen to be more likely to generate interaction and that the explainer-visitor relationship is developed through local activities and tools which could be more widely considered in the context of all explainer training. The thesis concludes that socio-cultural context shapes the explainers’ role, the conception of knowledge and skills required for explainers, and the design and delivery of training programmes for explainers in ISIs. The research contributes new knowledge in analysing a range of training practices for explainers in international ISI settings, and how these may be relevant to and potentially include a socio-cultural perspective. It is argued that the role of socio-cultural context in explainer training programmes raised by this thesis should be further explored by ISI educators, in order to divert from a set of practices that may be unduly influenced by a transmission approach.

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Okapuu-von, Veh Alexander. "Sound and vision : audiovisual aspects of a virtual-reality personnel-training system." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=23752.

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This thesis describes a prototype virtual reality (VR) training system. E scSOPE-VR, designed and implemented for Hydro-Quebec by graduate students at McGill University and Ecole Polytechnique de Montreal. The project was motivated by the necessity of providing a realistic training environment for substation operators, while ensuring their safety and the network's integrity at all times.
With the simulator, trainees can carry out all the switching operations necessary for their work in absolute safety, while staying in a realistic environment. A speech-recognition system controls the training session, while audio immersion adds a dimension of realism to the virtual world. An expert-system validates the trainee's operations at all times and a steady-state power-flow simulator recalculates network parameters. The automatic conversion of single-line diagrams enables the construction of three-dimensional models of substation equipment.
The present thesis focuses on the speech command, audio, video and network aspects of the system. A survey of current VR applications and an overview of VR technology are followed by a summary of the E scSOPE-VR project.

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Books on the topic "Training visivo"

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Shankman, Albert L. Vision enhancement training. Santa Ana, CA: Optometric Extension Program, 1988.

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Kraskin, Robert A. Improve your vision. Santa Ana, CA: Optometric Extention Program, 2010.

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Hatfield, Coleman. Visual training: The joy of optometry. Santa Ana, CA: Optometric Extension Program, 1990.

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1923-, Forkiotis Constantine, ed. Essays on vision. Santa Ana, CA: Optometric Extension Program Foundation, 1990.

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Maharaja Sayajirao University of Baroda. Centre of Advanced Study in Education., ed. Teacher education, vision and action. Baroda: Centre of Advanced Study in Education, Faculty of Education and Psychology, M.S. University of Baroda, 2000.

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Seiderman, Arthur. Overlooked: 20/20 is not enough. 3rd ed. Santa Ana, CA: Optometric Extension Program Foundation, 2012.

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M, Beresford Steven, and American Vision Institute, eds. Improve your vision without glasses or contact lenses: The AVI program. New York: Simon & Schuster, 1996.

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Fedorov, Aleksandr. Metody uluchsheniíà zreniíà: Kak izbavitʹsíà ot ochkov. Sankt-Peterburg: Nevskiĭ prospekt, 2001.

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Seiderman, Arthur. 20/20 is not enough: The new world of vision. New York: Fawcett Crest, 1991.

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Seiderman, Arthur. 20/20 is not enough: The new world of vision. New York: Knopf, 1989.

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Book chapters on the topic "Training visivo"

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Sundberg, Molly. "Realizing the Development Vision 2020." In Training for Model Citizenship, 219–54. New York: Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/978-1-137-58422-9_8.

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Ciuffreda, Kenneth J., and Bin Wang. "Vision Training and Sports." In Bioengineering, Mechanics, and Materials: Principles and Applications in Sports, 407–33. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-8887-4_16.

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Vivek, B. S., Konda Reddy Mopuri, and R. Venkatesh Babu. "Gray-Box Adversarial Training." In Computer Vision – ECCV 2018, 213–28. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01267-0_13.

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Yeakley, Celeste Labrunda, and Jeffrey D. Fiebrich. "World Vision-Training the Organization." In Collaborative Process Improvement, 51–63. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119134664.ch4.

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Kataoka, Hirokatsu, Kazushige Okayasu, Asato Matsumoto, Eisuke Yamagata, Ryosuke Yamada, Nakamasa Inoue, Akio Nakamura, and Yutaka Satoh. "Pre-training Without Natural Images." In Computer Vision – ACCV 2020, 583–600. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69544-6_35.

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Faubert, Jocelyn, Olga Overbury, and Gregory L. Goodrich. "A Hierarchy of Perceptual Training in Low Vision." In Low Vision, 471–89. New York, NY: Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4612-4780-7_37.

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Xiong, Yuanhao, and Cho-Jui Hsieh. "Improved Adversarial Training via Learned Optimizer." In Computer Vision – ECCV 2020, 85–100. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58598-3_6.

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Brubaker, S. Charles, Matthew D. Mullin, and James M. Rehg. "Towards Optimal Training of Cascaded Detectors." In Computer Vision – ECCV 2006, 325–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11744023_26.

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Arai, Kohei. "Sports Vision Based Tennis Player Training." In Advances in Intelligent Systems and Computing, 1193–201. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22868-2_83.

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Duke, Simon. "Visits of Goodwill and Training Purposes." In US Defence Bases in the United Kingdom, 15–36. London: Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1007/978-1-349-18482-8_3.

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Conference papers on the topic "Training visivo"

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Shang, Junyuan, Tengfei Ma, Cao Xiao, and Jimeng Sun. "Pre-training of Graph Augmented Transformers for Medication Recommendation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/825.

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Medication recommendation is an important healthcare application. It is commonly formulated as a temporal prediction task. Hence, most existing works only utilize longitudinal electronic health records (EHRs) from a small number of patients with multiple visits ignoring a large number of patients with a single visit (selection bias). Moreover, important hierarchical knowledge such as diagnosis hierarchy is not leveraged in the representation learning process. Despite the success of deep learning techniques in computational phenotyping, most previous approaches have two limitations: task-oriented representation and ignoring hierarchies of medical codes. To address these challenges, we propose G-BERT, a new model to combine the power of Graph Neural Networks (GNNs) and BERT (Bidirectional Encoder Representations from Transformers) for medical code representation and medication recommendation. We use GNNs to represent the internal hierarchical structures of medical codes. Then we integrate the GNN representation into a transformer-based visit encoder and pre-train it on EHR data from patients only with a single visit. The pre-trained visit encoder and representation are then fine-tuned for downstream predictive tasks on longitudinal EHRs from patients with multiple visits. G-BERT is the first to bring the language model pre-training schema into the healthcare domain and it achieved state-of-the-art performance on the medication recommendation task.

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Joy, Mirasol. "Statistical human resource development: the case of bukidnon state university, philippines." In Next Steps in Statistics Education. IASE international Association for Statistical Education, 2009. http://dx.doi.org/10.52041/srap.09503.

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Two trainings on Confirmatory and Exploratory Data Analyses and Data Mining were conducted to enhance capacity of faculty and step up their development in basic and advanced statistical methodological skills, so with their research capability. Training designs were perceptively prepared to address the variability of the participants’ educational status. Issues and challenges raised during the trainings include among others: existing researches are limited and confined only within the parameters of the workplace, wanting for a more in depth and comprehensive research utilizing data mining as a tool, and aggressive collaboration efforts and linkage among funding institutions. The training likewise motivated and enhanced faculty skills in the use of appropriate statistics methods useful in their research undertakings. Initial results revealed a significant increase in the number of quality and collaborative researches consistent with the vision of the university and established linkage from the local support institutions.

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Mwansa, Peter Levison, Ahmad Othman Alshaigy, Dawoud Saleh Madani Almaeeni, Khalifa Ghulam Hussain Qasem, Luiz Rego, Premachandran Nair, and Hussain Ahmed Saeed Baniyas. "Augmented Reality Delivers Differential Value in Safety Assurance on Rigs Onshore Abu Dhabi During Covid-19 Pandemic Courtesy of the Wearable Camera." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/210870-ms.

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Abstract The COVID-19 pandemic posed a real challenge to business continuity of our safety assurance programs, incident investigations and training of young engineers which are traditionally conducted through physical rig site visits. The measures taken to control the spread of the COVID-19 virus meant that physical visits to the rig sites were restricted and during certain times completely stopped. The consequence of such measure meant that the safety assurance program was heavily impacted as the weekly leadership site visits were suspended. This posed a risk of a potential increase in safety incidents. Moreover, only safety critical personnel were allowed at the rig sites meaning that all trainee drilling supervisors and engineers were not allowed to visit the rig sites as part of the COVID-19 control measures. This in turn directly impacted the training program of our young engineers and trainee drilling supervisors for the entire COVID-19 pandemic period – Not Good! The potential risk of an increase in safety incidents due to lack of safety assurance was too great a cost to accept. Therefore, the drilling team started to think differently. A multi-disciplinary brainstorming workshop involving technology providers in the digital space was conducted to discuss possible ways of conducting rig site visit virtually. During this workshop, augmented reality via use of the wearable camera was flagged as a technology ready solution for our challenge. Several subsequent sessions were conducted with ADNOC Onshore IT team to build a business case for the wearable camera. The wearable camera is an intrinsically safe Zone 1 certified fully rugged head-mounted device made for harsh environments. The high-resolution micro display fits just below the user's line of sight and views like a 7" tablet. A business case was put forward and approved to conduct a proof of concept (PoC) to specifically test the ability to conduct remote rig visits, investigations and training programs. The PoC was successfully completed and allowed the team to conduct remote rig visits, audits, investigations and training programs with the "touch and feel" of being at the rig site – a paradigm shift in the way we run our business.

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Chuang, Hsiu-Min, Yang Liu, and Akio Namiki. "Vision-based batting training system." In 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS). IEEE, 2017. http://dx.doi.org/10.1109/cbs.2017.8266105.

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Kim, Jongsung, and Myunggyu Kim. "Smart vision system for soccer training." In 2015 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2015. http://dx.doi.org/10.1109/ictc.2015.7354543.

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Izard, Santiago González, Juan A. Juanes Méndez, Francisco J. García-Peñalvo, Marcelo Jiménez López, Francisco Pastor Vázquez, and Pablo Ruisoto. "360° vision applications for medical training." In TEEM 2017: 5th International Conference Technological Ecosystems for Enhancing Multiculturality. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3144826.3145405.

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Lee, Ju-Hee, and Je-Won Kang. "Relation Enhanced Vision Language Pre-Training." In 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2022. http://dx.doi.org/10.1109/icip46576.2022.9897623.

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Kubozono, Ryusuke, Yunan He, Osamu Fukuda, Nobuhiko Yamaguchi, Hiroshi Okumura, and Anik Nur Handayani. "Vision-Based Robot Hand Using Open Source Software." In 2020 4th International Conference on Vocational Education and Training (ICOVET). IEEE, 2020. http://dx.doi.org/10.1109/icovet50258.2020.9230275.

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Miyata, Ryosuke, Yunan He, Osamu Fukuda, Nobuhiko Yamaguchi, Hiroshi Okumura, and Anik Nur Handayani. "Vision-based Control for Open-source Mobile Robots." In 2020 4th International Conference on Vocational Education and Training (ICOVET). IEEE, 2020. http://dx.doi.org/10.1109/icovet50258.2020.9230321.

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Al-Abdulwahed, Khalid, and Nouf Al-Ashwan. "Female Vocational Training." In SPE Middle East Oil & Gas Show and Conference. SPE, 2021. http://dx.doi.org/10.2118/204528-ms.

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Abstract The development of any country lies in all members of society in a country, the old generation to the younger and new ones. After launching the vision of 2030 pillars, the circle of women barriers becomes wider and unlimited in the field of employment. In order to merge women in the oil and gas industry, the first milestone must be considered is creating opportunities in the labour market alongside educating and training them to acquire great learning and hone skills that qualify the women to be in the industrial workforce. It will widely contribute to the socio-economic change in a country. The female has individual skills and capabilities that the companies’ needs to achieve its business objectives. The institutes which are fundamentally structured; can open another facility which is targeted the female vocational and technical training based on the same assets (strategies & policies). Another way to do so is through collaboration with international vocational institutions, local female universities and colleges. These days there is no doubt that the oil and gas companies are critically needed for the local talents and diversity of its range. As an example, SPSP has planned to inaugurate a new female vocational & technical center, in the meantime will offer a major source of job opportunities for well trained and qualified young Saudi women that how we encourage and retain more Saudi female to the petroleum energy sector. The training programs will include Health & Safety, and Electrical Diploma. There is a lack of trained and qualified Saudi female technical workforce at the industry sector. To solve this problem, the education and the labour sectors must work simultaneously to empower the female in this field. Many companies need to retool the female candidates from functional roles such as HR or Finance to target them into practice hands-on roles. To sum up, as Vision 2030 of rewarding opportunities to the women stated, ‘’ we are directing significant investment toward unlocking their talents and supporting their contribution to the Kingdom’s economic growth.’’ Business leaders should call for an action to increase female’s opportunity at the energy sector side by side the government’s efforts in the female vocational training programs.

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Reports on the topic "Training visivo"

1

Waggett, Michael L. Night Vision Goggles Computer Based Training. Fort Belvoir, VA: Defense Technical Information Center, April 1999. http://dx.doi.org/10.21236/ada398875.

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Beck, Richard R. Training Tomorrow's Navy: The Impact of Joint Vision 2010 on Training Naval Forces. Fort Belvoir, VA: Defense Technical Information Center, February 1997. http://dx.doi.org/10.21236/ada325148.

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Joralmon, DeForest Q. Multimedia Development for Night Vision Device Aircrew Training. Fort Belvoir, VA: Defense Technical Information Center, October 1995. http://dx.doi.org/10.21236/ada303615.

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Reising, Jack D., and Elizabeth L. Martin. Distance Estimation Training with Night Vision Goggles Under Low Illumination. Fort Belvoir, VA: Defense Technical Information Center, January 1995. http://dx.doi.org/10.21236/ada291338.

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Trautman, Edward, William Little, and Michael Mittleman. A Survey of Fleet Opinions Regarding Unaided Vision Training Topics. Fort Belvoir, VA: Defense Technical Information Center, December 1990. http://dx.doi.org/10.21236/ada233619.

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Лаврентьєва, Олена Олександрівна. Methodological Approaches To Vocational Training Organization. IASHE, 2017. http://dx.doi.org/10.31812/0564/2557.

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Questions of entity and maintenance of the concept "vocational training" are considered in the article. Author shows distinction of approaches to interpretation of vocational training, technical and vocational training; opens genesis; characterizes features of institutions of vocational training at school, after-school and professional levels. In article the existing determination is analyzed and the authoring vision of classification of methodological approaches in the organization of vocational training is given; the approaches of strategic and tactical levels are revealed.

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McKnight, Katherine, Nitya Venkateswaran, Jennifer Laird, Rita Dilig, Jessica Robles, and Talia Shalev. Parent Teacher Home Visits: An Approach to Addressing Biased Mindsets and Practices to Support Student Success. RTI Press, September 2022. http://dx.doi.org/10.3768/rtipress.2022.op.0077.2209.

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Research has shown educators’ implicit biases to be a key factor in creating and perpetuating disparities in students’ experiences of schooling, learning, and longer-term outcomes, including job opportunities, wealth, and health. Current school reform and transformation efforts are aimed at addressing institutionalized racism in school policies, practices, and cultural systems by implementing implicit bias training for teachers and staff. In this paper, we explain how a school home visits program, Parent Teacher Home Visits (PTHV), is a promising intervention for counteracting implicit biases and improving outcomes for families and students. The PTHV “relational” home visit model focuses on promoting mutually supportive and accountable relationships between educators and families. We present data from a study examining the experiences of 107 educators and 68 family members who participated in PTHV, showing how educators shifted their deficit assumptions about families and students. Although the PTHV model was not created to address implicit biases, we found that the key components of these home visits align with strategies that psychological research has demonstrated effectively counteracting implicit biases and reducing discriminatory behaviors.

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Anderson, Gretchen M., Craig A. Vrana, Joseph T. Riegler, and Elizabeth L. Martin. Integration of a Legacy System with Night Vision Training System (NVTS). Fort Belvoir, VA: Defense Technical Information Center, August 2002. http://dx.doi.org/10.21236/ada408580.

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9

Niall, Keith K., Jack D. Reising, Elizabeth L. Martin, and Marcus H. Gregory. Distance Estimation with Night Vision Goggles: A Direct Feedback Training Method. Fort Belvoir, VA: Defense Technical Information Center, June 1997. http://dx.doi.org/10.21236/ada328758.

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Estrada, Arthur, Patricia A. LeDuc, Larry C. Woodrum, Terri L. Rowe, Elizabeth G. Stokes, and John S. Crowley. A Comparison Study of Peripheral Vision-Restricting Devices Used for Instrument Training. Fort Belvoir, VA: Defense Technical Information Center, March 2005. http://dx.doi.org/10.21236/ada431147.

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