Role Based Access Control (RBAC) is the most widely used advanced access control model deployed in a variety of organizations. To deploy an RBAC system, one needs to first identify a complete set of roles, including p...
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Scaffolding students in open-ended learning environments (OELEs) is a difficult challenge. The open-ended nature of OELEs allows students to simultaneously pursue, modify, and abandon any of a large number of both sho...
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Scaffolding students in open-ended learning environments (OELEs) is a difficult challenge. The open-ended nature of OELEs allows students to simultaneously pursue, modify, and abandon any of a large number of both short-term and long-term approaches to completing their tasks. To overcome these challenges, we have recently developed coherence analysis, which focuses on students' ability to interpret and apply the information available in the OELE. This approach has yielded valuable dividends: by characterizing students according to the coherence of their behavior, teachers and researchers have access to easily-calculated, intuitive, and actionable measures of the quality of students' problem-solving processes. The next step in this line of research is to develop a framework for using coherence analysis to adaptively scaffold students in OELEs. In this paper, we present our initial ideas for this work and propose guidelines for the construction of a scaffolding framework.
This paper presents a formulation of a nonlinear model predictive controller for steering of a nuclear reaction in a pressurized water reactor via control rod displacement. The predictive model, based on point kinetic...
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This paper presents our recent work with the Generalized Intelligent Framework for Tutoring (GIFT) for authoring tutors and training systems in concert with already developed external applications that provide a wide ...
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This paper presents our recent work with the Generalized Intelligent Framework for Tutoring (GIFT) for authoring tutors and training systems in concert with already developed external applications that provide a wide variety of educational experiences. In this paper, we describe our efforts to extend the GIFT system to develop metacognitive tutoring support for UrbanSim, a turnbased simulation environment for learning about counterinsurgency operations. We discuss specific extensions to GIFT as well as the links we have developed between GIFT and UrbanSim to track player activities. Additionally, we discuss a conversational approach that we are designing to interpret players' strategies and provide feedback when they adopt suboptimal approaches for their counterinsurgency operations.
Deep networks like the convolutional neural network and its variants usually learn hierarchical features from labeled images, which is very expensive to obtain. How can we find an unsupervised way to effectively extra...
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ISBN:
(纸本)9781509006212
Deep networks like the convolutional neural network and its variants usually learn hierarchical features from labeled images, which is very expensive to obtain. How can we find an unsupervised way to effectively extract deep and abstract features from images without annotations? Even from large qualities of images with noise? In this paper, we propose a robust deep neural network, named as stacked convolutional denoising auto-encoders (SCDAE), which can map raw images to hierarchical representations in an unsupervised manner. Our network is elaborately designed to fit for the visual recognition tasks. It is established by stacking the denoising auto-encoders. Unlike the prior works, in the training phase, the auto-encoders are trained patch-wisely so that the latent features can be applied to powerful regularizers for better representation;in the inference phase, the denoising auto-encoders are stacked convolutionally, hence the generated feature maps in the higher layers can preserve the coherent structures within the features in the lower layers. To achieve better performance, we apply whitening to each layer to sphere the input features. Our network is evaluated on the challenging image datasets MNIST, CIFAR-10 and STL-10 and demonstrates superior performance to the state-of-the-art unsupervised networks.
Minimally invasive robotic surgery techniques are becoming popular thanks to their enhanced patient benefits, including shorter recovery time, better cosmetic results and reduced discomforts. Less invasive procedures ...
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The purpose of this paper was to expand upon an existing eye detection algorithm and to innovate an acceptable and practical solution aimed for hands-free computer *** overall goal was to create a cost-efficient real-...
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The purpose of this paper was to expand upon an existing eye detection algorithm and to innovate an acceptable and practical solution aimed for hands-free computer *** overall goal was to create a cost-efficient real-time application which aids the physically disabled by allowing navigation through the Microsoft Windows operating system using only their *** primary focus was to develop and algorithm with both a high degree of efficiency and accuracy without the use of any specialized equipment or *** concluded approximately 97% accuracy in low lit environments and 99% accuracy in well-lit environments when calibrated *** accuracy and efficiency decrease when executing in a poorly lit environment,or in a poorly calibrated system.
Data deduplication is an attractive technology to reduce storage space for increasing vast amount of duplicated and redundant data. In a cloud storage system with data deduplication, duplicate copies of data will be e...
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Data deduplication is an attractive technology to reduce storage space for increasing vast amount of duplicated and redundant data. In a cloud storage system with data deduplication, duplicate copies of data will be eliminated and only one copy will be kept in the storage. To protect the confidentiality of sensitive data while supporting deduplication, the convergent encryption technique has been proposed to encrypt the data before outsourcing. However, the issue of keyword search over encrypted data in deduplication storage system has to be addressed for efficient data utilization. This paper firstly proposes two constructions which support secure keyword search in this scenario. In these constructions, the integrity of the data can be realized by just checking the convergent key, without other traditional integrity auditing mechanisms. Then, two extensions are presented to support fuzzy keyword search and block-level deduplication. Finally, security analysis is given.
In Human computer Interaction (HCI), one of the recent research areas is Hand Gesture Recognition (HGR). In hand gesture recognition, finger identification and fingertip detection is a challenging work. Because of the...
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In Human computer Interaction (HCI), one of the recent research areas is Hand Gesture Recognition (HGR). In hand gesture recognition, finger identification and fingertip detection is a challenging work. Because of the enormous applications like sign language, human robot interaction, gesture based applications this area is gaining researchers' attention. In this paper, a novel approach of finger identification named as 4Y model, is proposed. This model is based on geometric calculations and general biometric features. The experimental result for the model gives up to 92% accuracy based on its inputs.
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