Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Distribution Patterns of Soil Properties in a Rural Mediterranean Area in Northeastern Spain

Soil properties on the Cap de Creus Peninsula, NE Spain depend primarily on scarce agricultural practices and early abandonment. In the study area, 90% of which is mainly covered by Cistus shrubs, 8 environments representing variations in land use/land cover and soil properties at different depths were identified. In each environment variously vegetated areas were selected and sampled. The soils, collected at different depths, were classified as Lithic Xerorthents according to the United States Department of Agriculture system of soil classification (USDA-NRCS 1975). Differences in soil properties were largely found according to the evolution of the plant canopy and the land use history. To identify underlying patterns in soil properties related to environmental evolution, factor analysis was performed and factor scores were used to determine how the factor patterns varied between soil variables, soil depths and selected environments. The three-factor model always accounted for 80% of the total variation in the data at the different soil depths. Organic matter was the more relevant soil property at 0–2 cm depth, whereas active minerals (silt and clay) were found to be the most relevant soil parameters controlling soil dynamics at the other depths investigated. Results showed that vineyards and olive tree soils are poorly developed and present worse conditions for mineral and organic compounds. Analysis of factor scores allowed independent assessment of soils, depth and plant cover and demonstrated that soils present the best physico-chemical characteristics under Erica arborea and meadows. In contrast, soils under Cistus monspeliensis were less nutrient rich and less well structured

A Method for Sky-Condition Classification from Ground-Based Solar Radiation Measurements

Identification of clouds from satellite images is now a routine task. Observation of clouds from the ground, however, is still needed to acquire a complete description of cloud conditions. Among the standard meteorologicalvariables, solar radiation is the most affected by cloud cover. In this note, a method for using global and diffuse solar radiation data to classify sky conditions into several classes is suggested. A classical maximum-likelihood method is applied for clustering data. The method is applied to a series of four years of solar radiation data and human cloud observations at a site in Catalonia, Spain. With these data, the accuracy of the solar radiation method as compared with human observations is 45% when nine classes of sky conditions are to be distinguished, and it grows significantly to almost 60% when samples are classified in only five different classes. Most errors are explained by limitations in the database; therefore, further work is under way with a more suitable database

Om fabriquernes nytta och nödwändighet uti ett land

Invocatio: I.H.W.N.

Om fabriquernes nytta och nödwändighet uti ett land

Painovuosi nimekkeestä.

Identification of Races of Selected Isolates of Uromyces appendiculatus from Minas Gerais (Brazil) Based on the new international classification system

Twelve single-pustule isolates of Uromyces appendiculatus, the etiological agent of common bean rust, were collected in the state of Minas Gerais, Brazil, and classified according to the new international differential series and the binary nomenclature system proposed during the 3rd Bean Rust Workshop. These isolates have been used to select rust-resistant genotypes in a bean breeding program conducted by our group. The twelve isolates were classified into seven different physiological races: 21-3, 29-3, 53-3, 53-19, 61-3, 63-3 and 63-19. Races 61-3 and 63-3 were the most frequent in the area. They were represented by five and two isolates, respectively. The other races were represented by just one isolate. This is the first time the new international classification procedure has been used for U. appendiculatus physiological races in Brazil. The general adoption of this system will facilitate information exchange, allowing the cooperative use of the results obtained by different research groups throughout the world. The differential cultivars Mexico 309, Mexico 235 and PI 181996 showed resistance to all of the isolates that were characterized. It is suggested that these cultivars should be preferentially used as sources for resistance to rust in breeding programs targeting development lines adapted to the state of Minas Gerais.

A Survey and Classification of Software Testing Tools

Software testing is one of the essential parts in software engineering process. The objective of the study was to describe software testing tools and the corresponding use. The thesis contains examples of software testing tools usage. The study was conducted as a literature study, with focus on current software testing practices and quality assurance standards. In the paper a tool classifier was employed, and testing tools presented in study were classified according to it. We found that it is difficult to distinguish current available tools by certain testing activities as many of them contain functionality that exceeds scopes of a single testing type.

Charta öfver Åland

1 kartta : käsinvär. ; 41,5 x 71,5 cm, lehti 46 x 74,7 cm.

Financier’s credit risk: A Performance-Based Classification Model

The purpose of this study is to view credit risk from the financier’s point of view in a theoretical framework. Results and aspects of the previous studies regarding measuring credit risk with accounting based scoring models are also examined. The theoretical framework and previous studies are then used to support the empirical analysis which aims to develop a credit risk measure for a bank’s internal use or a risk management tool for a company to indicate its credit risk to the financier. The study covers a sample of Finnish companies from 12 different industries and four different company categories and employs their accounting information from 2004 to 2008. The empirical analysis consists of six stage methodology process which uses measures of profitability, liquidity, capital structure and cash flow to determine financier’s credit risk, define five significant risk classes and produce risk classification model. The study is confidential until 15.10.2012.

Vårt land, vårt land

Laulusolisti ilmoittaa nimensä alkukuulutuksessa; kuulutus epäselvä.