Active learning enables learners to actively engage in learning. Learning not only transfers material to students for learning, but also encourages greater mental engagement and more extensive student-student and stud...
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The stringent requirements on size and power consumption constrain the conventional hearing aid devices from providing the patients an economic and user friendly solution, specifically for better noise cancellation. W...
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GOMS is a well-known model that has been successfully used in predicting the performance of human-computer interaction, identifying usability problems and improving user-interface design. The focus of GOMS on the indi...
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GOMS is a well-known model that has been successfully used in predicting the performance of human-computer interaction, identifying usability problems and improving user-interface design. The focus of GOMS on the individual user, however, explains why it has not been applied in the groupware context. We were inspired by GOMS to define a model that describes collaborative tasks in a formal way. We illustrate the application of the model by applying it to the design of a collaborative tool for software engineering requirements negotiation.
Although wireless hearing aid systems have been proposed by several research groups, no viable whole-system simulation results have been reported so far for better evaluation of this advanced hearing device. In this p...
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Although wireless hearing aid systems have been proposed by several research groups, no viable whole-system simulation results have been reported so far for better evaluation of this advanced hearing device. In this paper, a system-level simulation using ADStrade is presented based on one of the typical wireless hearing aid architecture. The results show that the wireless hearing aid system function can be simulated and verified. And from these results, we can get a very promising performance which can be used for further design
Distance Learning physically separates the learner from the teacher often forfeiting the traditional support available in a face-to-face model. What are the issues and lessons learned in supporting teachers and learne...
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ISBN:
(纸本)1595930590
Distance Learning physically separates the learner from the teacher often forfeiting the traditional support available in a face-to-face model. What are the issues and lessons learned in supporting teachers and learners in Distance Learning? The panelists will share their experience and lessons learned. Copyright 2005 ACM.
With the increase in adoption of remote work groups and teams working in non-collocated environments, several opportunities for interaction have been lost. Contact with colleagues and discovery of opportunities, previ...
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With the increase in adoption of remote work groups and teams working in non-collocated environments, several opportunities for interaction have been lost. Contact with colleagues and discovery of opportunities, previously easy due to physical proximity, is made harder with distance. In this paper, we describe an agent-based framework to assist users in finding opportunities for interaction that may have been overlooked.
A study of thermal chemical vapor deposition (CVD) grown carbon nanotubes (CNTs) field emitters in a triode amplifier configuration is reported. The CNT transistor characteristics were examined by integrating gate and...
A study of thermal chemical vapor deposition (CVD) grown carbon nanotubes (CNTs) field emitters in a triode amplifier configuration is reported. The CNT transistor characteristics were examined by integrating gate and anode with CNT cathode in two structural forms, utilizing a TEM grid (transmission electron microscope specimen holder) as the gate electrode and a micropatterned CNT with self-aligned gate. The TEM-grid CNT triode displayed clearly gate-controlled current modulation behavior with distinct cutoff, linear, and saturation regions, and a reasonable gate turn-on field of ∼5.4V∕μm despite a large cathode-gate spacing of ∼120μm . The field emission result established the basic transistor characteristics of CNTs in a triode configuration. A CNT triode construct with a self-aligned gated fabrication technique was also developed to realize a monolithic triode structure with shorter gate-cathode spacing, lowering gate voltage, and enhancing emission current. The triode exhibited a significantly lower gate turn-on voltage of ∼40V , and gate-controlled modulation of the emission current. An anode current density of ∼30mA∕cm2 was achieved at a gate voltage of ∼80V and an anode voltage of ∼200V . The dc characteristics for both of the CNT triodes were investigated, including Ia versus Va for different Vg . Moreover, dc parameters such as transconductance, amplification factors, and anode resistance of the triode amplifier were determined. The CNT triodes exhibited useful amplification factor and high output impedance.
This paper describes targeted reaching experiments conducted using a new augmented reality system. Combining a large-workspace immersive virtual environment with physical force feedback, the system distorted subjects&...
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This paper describes targeted reaching experiments conducted using a new augmented reality system. Combining a large-workspace immersive virtual environment with physical force feedback, the system distorted subjects' movements using a viscous curl force field. Following previous experiments using a different robot, half the subjects were constrained to horizontal, planar movements. The remaining subjects performed unconstrained movements throughout the 3D workspace. Examining after-effects as an indication of learning, we found that constrained subjects learned the force field. However, it was difficult to detect whether the unconstrained subjects learned forces of identical magnitude. Our results found that force fields strengths eliciting constrained 2D adaptation have difficulty exhibiting after-effects for unconstrained 3D movements. The increased motor variability for 3D reaching movements requires consideration for future experimental design.
One of the main problems related to regulatory network reconstruction from expression data concerns the small size and low quality of the available dataset. When trying to infer a model from little information it is n...
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One of the main problems related to regulatory network reconstruction from expression data concerns the small size and low quality of the available dataset. When trying to infer a model from little information it is necessary to give much more precedence to generalization, rather than specificity, otherwise, any attempt will be fated to overfitting. In this paper we address this issue by focusing on data sparseness and noisy information, and propose a density estimation technique that achieves regularized curves when data is scarce. We first compare the proposed method with the EM algorithm for mixture models on density estimation problems. Next, we apply the method, together with Bayesian networks, on realistic simulations of static gene networks, and compare the obtained results with the standard discrete Bayesian network model. We intend to demonstrate that adopting a discrete approach is not justifiable when only a small amount of information is available.
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