Examining CO ₂ Model Observation Residuals Using ACT?America Data

Examining document model residuals to provide feedback during Information Retrieval evaluation

Abstract Evaluation of document models for text based Information retrieval is crucial for developing document models that are appropriate for specific domains. Unfortunately, current document model evaluation methods for text retrieval provide no feedback, except for an evaluation score. To improve a model, we must use trial and error. In this article, we examine how we can provide feedback in...

Observation Centric Sensor Data Model

Management of sensor data requires metadata to understand the semantics of observations. While e-science researchers have high demands on metadata, they are selective in entering metadata. The claim in this paper is to focus on the essentials, i.e., the actual observations being described by location, time, owner, instrument, and measurement. The applicability of this approach is demonstrated i...

Adjusting Shape Parameters Using Model-Based Optical Flow Residuals

We present a method for estimating the shape of a deformable model using the least-squares residuals from a model-based optical flow computation. This method is built on top of an estimation framework using optical flow and image features, where optical flow affects only the motion parameters of the model. Using the results of this computation, our new method adjusts all of the parameters so th...

The Effect of Observation Data Sampling Methods on Infiltration Areas by Maximum Entropy Model

Statistical modeling methods are based on multivariate regression methods and require the presence and absence location of data for the construction of the model. In most cases, there is no trustworthy absence data. Therefore, other methods that are based only on the presence of the phenomenon are used. Considering the importance of modeling - saving time and cost and the probable prediction of...

Examining Health Disparities Using Data Science.