How to assess, plan and teach fiction and poetry 2 : key stage two, primary 4-7. 'Cómo evaluar, planificar y enseñar ficcion y poesía : etapa clave 1, primaria 1-3'.

Puede servir como referencia, cómo guía pedagógica o, bien cómo un recurso de estrategias y actividades prácticas utilizadas por los profesores en el aula. Describe los elementos de la estructura del texto y los rasgos más comunes del lenguaje poético y narrativo, define las características específicas de cada uno de estos géneros literarios, y las formas que adquieren textos y poesías. Se señala el modelo de lectura compartida y guiada como el más idóneo para la enseñanza y el aprendizaje de estos contenidos, pues permite a los alumnos actividades cómo hacer preguntas, comparar y reflexionar sobre lo que están leyendo.

Key stage two history. The study book.

Para alumnos de primaria. Da toda la información importante, de la forma más clara y concisa posible, para aprender y desarrollar conocimientos de historia. Actividades divertidas tratan de hacer el aprendizaje más ameno.

Drama : english key stage two : Scottish levels C-E.

Se valora el papel que desempeña el teatro en el nivel educativo de primaria, no sólo como una forma de arte por derecho propio,sino también como una disciplina aprovechada como medio de aprendizaje de otras áreas del curriculo (lengua, desarrollo personal y social). Este libro del profesor se divide en varias secciones y se acompaña de actividades para los alumnos y actividades de evaluación y de hojas de trabajo fotocopiables.

Materials and their properties : science key stage two : Scottish levels C-E.

Se propone a los niños del nivel educativo de primaria, la realización de actividades prácticas para que exploren e investiguen las propiedades, la composición y los cambios que sufren los distintos tipos de materiales que se les ofrecen (metal, papel, plástico,etc). También se les anima a que, siguiendo los pasos de una investigación científica, realicen experimentos con ellos. Se acompaña el libro de hojas fotocopiables y actividades de evaluación para el profesor.

Improvement of classification accuracy for stochastic discrimination - Multi-class classification

In this paper, an improved stochastic discrimination (SD) is introduced to reduce the error rate of the standard SD in the context of multi-class classification problem. The learning procedure of the improved SD consists of two stages. In the first stage, a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. In the second stage, the standard SD is modified by (i) restricting sampling in the important space; and (ii) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but smaller variance than that of standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples axe provided to demonstrate the effectiveness of the proposed improved SD.

An effective approach for land-cover classification from airborne lidar fused with co-registered data

Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

Construction of neurofuzzy models for imbalanced data classification

We propose a new class of neurofuzzy construction algorithms with the aim of maximizing generalization capability specifically for imbalanced data classification problems based on leave-one-out (LOO) cross validation. The algorithms are in two stages, first an initial rule base is constructed based on estimating the Gaussian mixture model with analysis of variance decomposition from input data; the second stage carries out the joint weighted least squares parameter estimation and rule selection using orthogonal forward subspace selection (OFSS)procedure. We show how different LOO based rule selection criteria can be incorporated with OFSS, and advocate either maximizing the leave-one-out area under curve of the receiver operating characteristics, or maximizing the leave-one-out Fmeasure if the data sets exhibit imbalanced class distribution. Extensive comparative simulations illustrate the effectiveness of the proposed algorithms.

EFFECT of TYPES of NOZZLES on SPRAY DEPOSITION on TWO SOYBEAN VARIETIES IN STAGE V3

The effect of application with different nozzle types and volume rates on spray deposition in the V3 stage of two soybean cultivars was evaluated. The experiments were conducted in the Facultad de Ciencias Agronomicas of the UNESP-Botucatu/SP. The nozzles evaluated were an air induced flat fan nozzle (Al 11015 at 150 L ha(-1), Al 11002 at 200 and 250 L ha(-1)), a twin flat fan nozzle (TJ 60 11002 at 150, 200 and 250 L ha(-1)), and a cone nozzle (TX 6 at 150 L ha(-1), TX 8 at 150 L ha(-1) and TX 10 at 250 L ha(-1)). To evaluate spray deposition on the plants, a tracer (Brilliant Blue FD&C-1) was added. The experimental design was random blocks with four replications. Deposition on plants was determined by absorbancy reading in 630 nm wavelength. The data were adjusted to a calibration curve and transformed into deposited spray volume in mL. The relationship deposition per unit of dry matter was adjusted to a regression curve (Gompertz model). In cultivar CD 208, the highest deposit was for the larger volumes and for the treatment TX 8 200 L ha(-1). The most uniform treatments were all the nozzles with the volume 150 L ha(-1) and the TJ60 nozzle for 200 1, ha(-1). In cultivar CD 216, the greatest spray depositions were achieved with the treatments Al at 200 and 250 L ha(-1) and TJ 60 at 250 L ha(-1), and the most uniform treatments were the TX 6 and TJ60 nozzles for the volume150 L ha(-1).

The first zoeal stage of two species of Grapsidae (Decapoda, Brachyura) and a key to such larvae from the Brazilian coast

First zoeal stages of the grapsinid Goniopsis cruentata (Latreille, 1803) and the sesarminid Aratus pisonii (H. Milne Edwards, 1837), are described and illustrated. Grapsinae zoeae can be distinguished from the other grapsid larvae by the absence of lateral spines on the carapace and the reduction of the antennal exopod to a small seta. A key to the first zoeal stage of the Brazilian coast Grapsidae is provided.

Two-way regionalized classification of multivariate datasets and its application to the assessment of hydrodynamic dispersion

Zones of mixing between shallow groundwaters of different composition were unravelled by two-way regionalized classification, a technique based on correspondence analysis (CA), cluster analysis (ClA) and discriminant analysis (DA), aided by gridding, map-overlay and contouring tools. The shallow groundwaters are from a granitoid plutonite in the Funda o region (central Portugal). Correspondence analysis detected three natural clusters in the working dataset: 1, weathering; 2, domestic effluents; 3, fertilizers. Cluster analysis set an alternative distribution of the samples by the three clusters. Group memberships obtained by correspondence analysis and by cluster analysis were optimized by discriminant analysis, gridded memberships as follows: codes 1, 2 or 3 were used when classification by correspondence analysis and cluster analysis produced the same results; code 0 when the grid node was first assigned to cluster 1 and then to cluster 2 or vice versa (mixing between weathering and effluents); code 4 in the other cases (mixing between agriculture and the other influences). Code-3 areas were systematically surrounded by code-4 areas, an observation attributed to hydrodynamic dispersion. Accordingly, the extent of code-4 areas in two orthogonal directions was assumed proportional to the longitudinal and transverse dispersivities of local soils. The results (0.7-16.8 and 0.4-4.3 m, respectively) are acceptable at the macroscopic scale. The ratios between longitudinal and transverse dispersivities (1.2-11.1) are also in agreement with results obtained by other studies.

Bone mineral density in healthy female adolescents according to age, bone age and pubertal breast stage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.

An inter-comparison between a VIS/IR and a MW satellite-based methods for cloud detection and classification

This thesis is aimed to assess similarities and mismatches between the outputs from two independent methods for the cloud cover quantification and classification based on quite different physical basis. One of them is the SAFNWC software package designed to process radiance data acquired by the SEVIRI sensor in the VIS/IR. The other is the MWCC algorithm, which uses the brightness temperatures acquired by the AMSU-B and MHS sensors in their channels centered in the MW water vapour absorption band. At a first stage their cloud detection capability has been tested, by comparing the Cloud Masks they produced. These showed a good agreement between two methods, although some critical situations stand out. The MWCC, in effect, fails to reveal clouds which according to SAFNWC are fractional, cirrus, very low and high opaque clouds. In the second stage of the inter-comparison the pixels classified as cloudy according to both softwares have been. The overall observed tendency of the MWCC method, is an overestimation of the lower cloud classes. Viceversa, the more the cloud top height grows up, the more the MWCC not reveal a certain cloud portion, rather detected by means of the SAFNWC tool. This is what also emerges from a series of tests carried out by using the cloud top height information in order to evaluate the height ranges in which each MWCC category is defined. Therefore, although the involved methods intend to provide the same kind of information, in reality they return quite different details on the same atmospheric column. The SAFNWC retrieval being very sensitive to the top temperature of a cloud, brings the actual level reached by this. The MWCC, by exploiting the capability of the microwaves, is able to give an information about the levels that are located more deeply within the atmospheric column.

Inter- and intraobserver reliability of the COFAS end-stage ankle arthritis classification system

End-stage ankle arthritis should have an appropriate classification to assist surgeons in the management of end-stage ankle arthritis. Outcomes research also requires a classification system to stratify patients appropriately.

The postoperative COFAS end-stage ankle arthritis classification system: interobserver and intraobserver reliability

End-stage ankle arthritis is operatively treated with numerous designs of total ankle replacement and different techniques for ankle fusion. For superior comparison of these procedures, outcome research requires a classification system to stratify patients appropriately. A postoperative 4-type classification system was designed by 6 fellowship-trained foot and ankle surgeons. Four surgeons reviewed blinded patient profiles and radiographs on 2 occasions to determine the interobserver and intraobserver reliability of the classification. Excellent interobserver reliability (κ = .89) and intraobserver reproducibility (κ = .87) were demonstrated for the postoperative classification system. In conclusion, the postoperative Canadian Orthopaedic Foot and Ankle Society (COFAS) end-stage ankle arthritis classification system appears to be a valid tool to evaluate the outcome of patients operated for end-stage ankle arthritis.