Learning model obtained with the Response Modeling
Matrix of Polynomials Model based Polynomial Dictionary Learning Method for Acoustic Impulse Response Modeling
... dictionary learning, sparse represen- tation, acoustic modeling, denoising ...tionary learning algorithms [2]. Dictionary learning methods usually employ a two-step alternating optimization ...
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Modeling of permanent magnets: Interpretation of parameters obtained from the Jiles–Atherton hysteresis model
... computed model parameters, M S , a, a , k, and c, which represent the saturation magnetization, the effective domain density, the mean exchange coupling between the effective domains, the flexibility of domain ...
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Experiences Obtained with Integration of Student Response Systems for iPod Touch and iPhone into e‑Learning Environments
... knowledge that is otherwise hard to obtain. SRS can identify students who are lagging behind for extra attention, and they are useful tools for scaffolding peer-assisted learning in large classes. The teacher ...
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Modeling Household Car Ownership using Ordered Response Model
... logit model and ordered logistic regression model to analyze the car ...logit model and the order relationship of the car ownership, the sequential response model is adopted, and ...
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A comparison of single and multiple response machine learning algorithms for species distribution modeling
... individual basis. For moths with very low abundance, it is difficult to distinguish between informative and misinformative occurrences, and with few records to consult; a prediction is difficult at best. The distribution ...
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Toward a model of multiple paths to language learning: response to commentaries
... language learning environment that differs from the initial learning context in specified ...language learning will necessarily converge with basic research on domain general processes such as ...
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Identifying Learning Disabilities in the Context of Response to Intervention: A Hybrid Model
... Conclusions Although RTI models have been implemented in many schools and districts over the past 20 years (Jimerson et al., 2007), there are still issues that require further attention. In the identification area, it is ...
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Mathematical and statistical model misspecifications in modeling immune response in renal transplant recipients
... mathematical model and statistical model misspecifications in the context of least squares methodology using a BKV model and both clinical and simulated ...error model; we consider different ...
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A Hybrid Data Mining Model to Improve Customer Response Modeling in Direct Marketing
... A response model predicts if a customer is going to respond to a product offering or ...to model customer response. In response modeling customers are partitioned in to two ...
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Modeling of Deadband Function of Governor Model and its Effect on Frequency Response Characteristics
... governor/turbine model is investigated. For this purpose, IEEEG1 model is used to study the frequency response of the steam ...frequency response, it is even worth in case of ignoring the ...
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Comparison of Debris Flow Characteristics Obtained by Using Video Materials and Modeling
... the obtained results with the calculated values using various ...applied model of the transport-shear process of debris flow formation developed by ...the obtained debris flow discharges with results ...
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Modeling the effect of glacier recession on streamflow response using a coupled glacio hydrological model
... hydrology model. The model subdivides a watershed into uniform cells (typ- ically with a spatial resolution of 10–150 m) to capture the spatial variability of the physical characteristics of the wa- tershed ...
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Modeling as a Learning Method
... basic model with the three ways to produce ATP, so those data aren’t very informative for this study, aside from the fact that everyone at least drew the ...
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Modeling Adaptive Learning: R&D Strategies in the Model of Nelson & Winter (1982)
... Learning following this stronger sens can only be present if firms can generalize from their past experience in order to anticipate the value of each considered strategy before using it. This possibility is ...
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Prediction of Combine Harvester Performance Using Hybrid Machine Learning Modeling and Response Surface Methodology
... Uncontrolled learning algorithm to train the centers and width of the main functions Assignment of weights related to the connections between hidden and output layers ...and model the behavior of the ...
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Statistical Modeling of Human Response Times for Task Modeling in HCI.
... faster response rates but with occasional mishaps that still result in extremely longer response ...subjects’ response times become faster while showing a more stable and less erratic shape ...
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Modeling runoff response to land-use changes using the SWAT model in the Mundaú watershed, Brazil
... Considering the division of the sub-basins, the SWAT is based on the concept of area necessary for the formation of a watercourse. On the other hand, the subdivision in HRU's is made from similar characteristics of soil ...
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An Error Modeling Framework for the Sun Azimuth Obtained at a Location with the Hour Angle Method
... error modeling framework for the errors result in the process of determining the sun azi- muth using the hour angle method; namely random errors, is ...Gauss-Markov model is used to represent the errors in ...
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R-splines for response surface Modeling
... plate spline modeling. R-splines arose in the context of attempting to modify the thin plate spline to allow for a greater number of explanatory variables in the model. R-splines are splines t with a ...
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Modeling forced-choice response formats
... by modeling’, in contrast to measurement by ...Item Response Theory (IRT). Several item response models have been developed recently to infer measurement from forced-choice ...IRT model (Brown ...
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