Crop Phenology Estimation Using a Multitemporal Model and a Kalman Filtering Strategy

In this letter, a new approach for crop phenology estimation with remote sensing is presented. The proposed methodology is aimed to exploit tools from a dynamical system context. From a temporal sequence of images, a geometrical model is derived, which allows us to translate this temporal domain into the estimation problem. The evolution model in state space is obtained through dimensional reduction by a principal component analysis, defining the state variables, of the observations. Then, estimation is achieved by combining the generated model with actual samples in an optimal way using a Kalman filter. As a proof of concept, an example with results obtained with this approach over rice fields by exploiting stacks of TerraSAR-X dual polarization images is shown.

Optimal model through identified frequencies of a masonry building structure with wooden floors

The paper presents the analysis of an important historical building: the Saint James Theater in the city of Corfù (Greece) actually used as the Municipality House. The building, located in the center of the city, is made of carves stones and is characterized by a stocky shape and by the presence of wooden floors. The study deals with the structural identification of such structure through the analysis of its ambient vibrations recorded by means of accelerometers with high accuracy. A full dynamic testing was developed using ambient vibrations to identify the main modal parameters and to make a non-destructive characterization of this building. The results of these dynamic tests are compared with the modal analysis of a complex finite element (FE) simulation of the structure. This analysis may present several problems and uncertainties for this stocky building. Due to the presence of wooden floors, the local modes can be highly excited and, as a consequence, the evaluation of the structural modal parameters presents some difficulties.

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Estimation of the Proportion of Underachieving Students in Compulsory Secondary Education in Spain: An Application of the Rasch Model

There are very few studies in Spain that treat underachievement rigorously, and those that do are typically related to gifted students. The present study examined the proportion of underachieving students using the Rasch measurement model. A sample of 643 first-year high school students (mean age = 12.09; SD = 0.47) from 8 schools in the province of Alicante (Spain) completed the Battery of Differential and General Skills (Badyg), and these students' General Points Average (GPAs) were recovered by teachers. Dichotomous and Partial credit Rasch models were performed. After adjusting the measurement instruments, the individual underachievement index provided a total sample of 181 underachieving students, or 28.14% of the total sample across the ability levels. This study confirms that the Rasch measurement model can accurately estimate the construct validity of both the intelligence test and the academic grades for the calculation of underachieving students. Furthermore, the present study constitutes a pioneer framework for the estimation of the prevalence of underachievement in Spain.

MODEL COUNTRIES IN POLITICAL ANALYSIS. Is Turkey a Model for State-Building in the Arab World? Jean Monnet Occasional Paper No. 10/2014

This study analyzes the Turkish case as a model country for the state-building processes in the Arab world in the aftermath of the Arab revolts that took place in Tunisia, Egypt and Libya. To this end, it deals with the Turkish case in three phases: the founding of the Turkish Republic, political developments until 2002, and the post-2002 Justice and Development Party period. The study focuses on state-society relations manifested in the form of a secular-religious cleavage intertwined with problematic civil-military relations. Each phase of Turkey’s history is compared to cleavages and civil-military relations in Egypt, Tunisia and Libya. After analyzing the constitution-making processes in the latter three countries following the Arab revolts, the study concludes by discussing the viability of the Turkish model in the light of Turkey’s search for a new constitution.

NLCHECK: Stata module to check linearity assumption after model estimation

nlcheck is a simple diagnostic tool that can be used after fitting a model to quickly check the linearity assumption for a given predictor. nlcheck categorizes the predictor into bins, refits the model including dummy variables for the bins, and then performs a joint Wald test for the added parameters. Alternative, nlcheck uses linear splines for the adaptive model. Support for discrete variables is also provided. Optionally, nlcheck also displays a graph of the adjusted linear predictions from the original model and the adaptive model

The demand for light duty trucks: the Wharton EFA Motor Vehicle Demand Model (Mark II). Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume III: appendices to the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

Revisions to the Wharton EFA Automobile Demand Model (Mark I). Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume II: simulation analysis using the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume I: the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

A useful method for model-building /

AD 266 222.

Demand-price-trade model of KASM3: technical documentation /

On cover: Korean Agricultural Sector Study.