دانلود و نمایش مقالات مرتبط با Skill acquisition::صفحه 1
بلافاصله پس از پرداخت دانلود کنید

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

نتیجه جستجو - Skill acquisition

تعداد مقالات یافته شده: 4
ردیف عنوان نوع
1 Automated Vision-Based Microsurgical Skill Analysis in Neurosurgery Using Deep Learning: Development and Preclinical Validation
تجزیه و تحلیل خودکار مهارتهای میکروجراحی مبتنی بر بینایی در جراحی مغز و اعصاب با استفاده از یادگیری عمیق: توسعه و اعتبار پیش بالینی-2021
- BACKGROUND/OBJECTIVE: Technical skill acquisition is an essential component of neurosurgical training. Educational theory suggests that optimal learning and improvement in performance depends on the provision of objective feedback. Therefore, the aim of this study was to develop a vision-based framework based on a novel representation of surgical tool motion and interactions capable of automated and objective assessment of microsurgical skill.
- METHODS: Videos were obtained from 1 expert, 6 intermediate, and 12 novice surgeons performing arachnoid dissection in a validated clinical model using a standard operating microscope. A mask region convolutional neural network framework was used to segment the tools present within the operative field in a recorded video frame. Tool motion analysis was achieved using novel triangulation metrics. Performance of the framework in classifying skill levels was evaluated using the area under the curve and accuracy. Objective measures of classifying the surgeons skill level were also compared using the ManneWhitney U test, and a value of P < 0.05 was considered statistically significant.
- RESULTS: The area under the curve was 0.977 and the accuracy was 84.21%. A number of differences were found, which included experts having a lower median dissector velocity (P [ 0.0004; 190.38 mse1 vs. 116.38 mse1), and a smaller inter-tool tip distance (median 46.78 vs. 75.92; P [ 0.0002) compared with novices.
- CONCLUSIONS: Automated and objective analysis of microsurgery is feasible using a mask region convolutional neural network, and a novel tool motion and interaction representation. This may support technical skills training and assessment in neurosurgery.
Key words: Artificial intelligence | Computer vision | Convolutional neural network | Mask RCNN | Microsurgery | Motion-analysis | Neurosurgery
مقاله انگلیسی
2 Electroencephalographic evidence for a reinforcement learning advantage during motor skill acquisition
شواهد الکتروانسفالوگرافی برای مزیت یادگیری تقویتی در حین کسب مهارت حرکتی-2020
The feedback that we receive shapes how we learn. Previous research has demonstrated that quantitative feedback results in better performance than qualitative feedback. However, the data supporting a quantitative feedback advantage are not conclusive and further little work has been done to examine the mechanistic neural differences that underlie the relative benefits of quantitative and qualitative feedback. To address these issues, participants learned a simple motor task in quantitative and qualitative feedback conditions while electroencephalographic (EEG) data were recorded. We found that participants were more accurate and had a larger neural response – the feedback related negativity - when qualitative feedback was provided. Our data suggest that qualitative feedback is more advantageous than quantitative feedback during the early stages of skill acquisition. Additionally, our findings support previous work suggesting that a reinforcement learning system within the human medial-frontal cortex plays a key role in motor skill acquisition.
Keywords: Feedback | EEG | Learning | Reinforcement learning | Motor learning | ERP | Supervised learning | FRN
مقاله انگلیسی
3 The tourism experience-led length of stay hypothesis
گردشگری تجربه منجر طول فرضیه اقامت-2017
Even given the continuing interest of both academia and industry to understand what accounts for the length of stay (LOS) of tourists, explanatory variables have mostly been limited to socio-demographic and trip characteristics overlooking the influence of the holiday experience despite it being a major reason why tourism is embarked on. Departing from previous studies, this study proposed and tested an experience-led length of stay hypothesis employing a zero truncated negative binomial regression model. It was revealed that tourism experience significantly explains the variations in tourists’ LOS with self development, recreational engage ments, hospitality, weather and sanitation identified as specific determinants. The findings also provide support for age, nationality, travel party size, budget, number of international trips, and risk taking behaviour as significant determinants of LOS. With these observations in mind, the study offers practical insights for sustaining tourists’ length of stay as well as propositions for future research on the tourism experience-led length of stay hypothesis. Management implications: Provision of positive memorable experiences in the domains of self development, recreation, hospitality, weather and aesthetics is one way to ensure that tourists stay longer. Specifically, need exits for destination management organisations and service providers to step up efforts in maintaining sanitation at the destination, especially at attraction sites and tourism-related premises. They can do this by ensuring regular cleaning, providing well-designated trash cans and disposing of sewage properly. In addition, a diverse of novel activities should be made available to tourists to sustain their interest and prolong their stay. Activity engagements that allow for skill acquisition such as volunteerism, cultural immersion (i.e. food bazaars) and co-creation of services are recommended.
Keywords: Backpackers | Ghana | Negative binomial | Length of stay | Tourism experience
مقاله انگلیسی
4 Continual curiosity-driven skill acquisition from high-dimensional video inputs for humanoid robots
گرفتن مهارت مداوم کنجکاوی از ورودی های ویدئویی با ابعاد بزرگ برای ربات های انسان نما-2017
Article history:Received in revised form 12 October 2014 Accepted 2 February 2015Available online 12 February 2015Keywords: Reinforcement learning Artificial curiositySkill acquisitionSlow feature analysis Continual learning Incremental learning iCubIn the absence of external guidance, how can a robot learn to map the many raw pixels of high-dimensional visual inputs to useful action sequences? We propose here Continual Curiosity driven Skill Acquisition (CCSA). CCSA makes robots intrinsically motivated to acquire, store and reuse skills. Previous curiosity-based agents acquired skills by associating intrinsic rewards with world model improvements, and used reinforcement learning to learn how to get these intrinsic rewards. CCSA also does this, but unlike previous implementations, the world model is a set of compact low-dimensional representations of the streams of high-dimensional visual information, which are learned through incremental slow feature analysis. These representations augment the robot’s state space with new information about the environment. We show how this information can have a higher- level (compared to pixels) and useful interpretation, for example, if the robot has grasped a cup in its field of view or not. After learning a representation, large intrinsic rewards are given to the robot for performing actions that greatly change the feature output, which has the tendency otherwise to change slowly in time. We show empirically what these actions are (e.g., grasping the cup) and how they can be useful as skills. An acquired skill includes both the learned actions and the learned slow feature representation. Skills are stored and reused to generate new observations, enabling continual acquisition of complex skills. We present results of experiments with an iCub humanoid robot that uses CCSA to incrementally acquire skills to topple, grasp and pick-place a cup, driven by its intrinsic motivation from raw pixel vision. 2015 Elsevier B.V. All rights reserved.
Keywords:Reinforcement learning | Artificial curiosity | Skill acquisition | Slow feature analysis | Continual learning | Incremental learning | iCub
مقاله انگلیسی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 2785 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 2785 :::::::: افراد آنلاین: 77