9 resultados para Landowners--Virginia--Arlington County--Maps.

em Helda - Digital Repository of University of Helsinki


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It is demanding for children with visual impairment to become aware of the world beyond their immediate experience. They need to learn to control spatial experiences as a whole and understand the relationships between objects, surfaces and themselves. Tactile maps can be an excellent source of information for depicting space and environment. By means of tactile maps children can develop their spatial understanding more efficiently than through direct travel experiences supplemented with verbal explanations. Tactile maps can help children when they are learning to understand environmental, spatial, and directional concepts. The ability to read tactile maps is not self-evident; it is a skill, which must be learned. The main research question was: can children who are visually impaired learn to read tactile maps at the preschool age if they receive structural teaching? The purpose of this study was to develop an educational program for preschool children with visual impairment, the aim of which was to teach them to read tactile maps in order to strengthen their orientation skills and to encourage them to explore the world beyond their immediate experience. The study is a multiple case study describing the development of the map program consisting of eight learning tasks. The program was developed with one preschooler who was blind, and subsequently the program was implemented with three other children. Two of the children were blind from birth, one child had lost her vision at the age of two, and one child had low vision. The program was implemented in a normal preschool. Another objective of the pre-map program was to teach the preschooler with visual impairment to understand the concept of a map. The teaching tools were simple, map-like representations called pre-maps. Before a child with visual impairment can read a comprehensive tactile map, it is important to learn to understand map symbols, and how a three-dimensional model changes to a two-dimensional tactile map. All teaching sessions were videotaped; the results are based on the analysis of the videotapes. Two of the children completed the program successfully, and learned to read a tactile map. The two other children felt happy during the sessions, but it was problematic for them to engage fully in the instruction. One of the two eventually completed the program, while the other developed predominantly emerging skills. The results of the children's performances and the positive feedback from the teachers, assistants and the parents proved that this pre-map program is appropriate teaching material for preschool children who are visually impaired. The program does not demand high-level expertise; also parents, preschool teachers, and school assistants can carry out the program.

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A composition operator is a linear operator that precomposes any given function with another function, which is held fixed and called the symbol of the composition operator. This dissertation studies such operators and questions related to their theory in the case when the functions to be composed are analytic in the unit disc of the complex plane. Thus the subject of the dissertation lies at the intersection of analytic function theory and operator theory. The work contains three research articles. The first article is concerned with the value distribution of analytic functions. In the literature there are two different conditions which characterize when a composition operator is compact on the Hardy spaces of the unit disc. One condition is in terms of the classical Nevanlinna counting function, defined inside the disc, and the other condition involves a family of certain measures called the Aleksandrov (or Clark) measures and supported on the boundary of the disc. The article explains the connection between these two approaches from a function-theoretic point of view. It is shown that the Aleksandrov measures can be interpreted as kinds of boundary limits of the Nevanlinna counting function as one approaches the boundary from within the disc. The other two articles investigate the compactness properties of the difference of two composition operators, which is beneficial for understanding the structure of the set of all composition operators. The second article considers this question on the Hardy and related spaces of the disc, and employs Aleksandrov measures as its main tool. The results obtained generalize those existing for the case of a single composition operator. However, there are some peculiarities which do not occur in the theory of a single operator. The third article studies the compactness of the difference operator on the Bloch and Lipschitz spaces, improving and extending results given in the previous literature. Moreover, in this connection one obtains a general result which characterizes the compactness and weak compactness of the difference of two weighted composition operators on certain weighted Hardy-type spaces.

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In this thesis a manifold learning method is applied to the problem of WLAN positioning and automatic radio map creation. Due to the nature of WLAN signal strength measurements, a signal map created from raw measurements results in non-linear distance relations between measurement points. These signal strength vectors reside in a high-dimensioned coordinate system. With the help of the so called Isomap-algorithm the dimensionality of this map can be reduced, and thus more easily processed. By embedding position-labeled strategic key points, we can automatically adjust the mapping to match the surveyed environment. The environment is thus learned in a semi-supervised way; gathering training points and embedding them in a two-dimensional manifold gives us a rough mapping of the measured environment. After a calibration phase, where the labeled key points in the training data are used to associate coordinates in the manifold representation with geographical locations, we can perform positioning using the adjusted map. This can be achieved through a traditional supervised learning process, which in our case is a simple nearest neighbors matching of a sampled signal strength vector. We deployed this system in two locations in the Kumpula campus in Helsinki, Finland. Results indicate that positioning based on the learned radio map can achieve good accuracy, especially in hallways or other areas in the environment where the WLAN signal is constrained by obstacles such as walls.

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This poster describes a pilot case study, which aim is to study how future chemistry teachers use knowledge dimensions and high-order cognitive skills (HOCS) in their pre-laboratory concept maps to support chemistry laboratory work. The research data consisted of 168 pre-laboratory concept maps that 29 students constructed as a part of their chemistry laboratory studies. Concept maps were analyzed by using a theory based content analysis through Anderson & Krathwohls' learning taxonomy (2001). This study implicates that novice concept mapper students use all knowledge dimensions and applying, analyzing and evaluating HOCS to support the pre-laboratory work.

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In the study, the potential allowable cut in the district of Pohjois-Savo - based on the non-industrial private forest landowners' (NIPF) choices of timber management strategies - was clarified. Alternative timber management strategies were generated, and the choices and factors affecting the choices of timber management strategies by NIPF landowners were studied. The choices of timber management strategies were solved by maximizing the utility functions of the NIPF landowners. The parameters of the utility functions were estimated using the Analytic Hierarchy Process (AHP). The level of the potential allowable cut was compared to the cutting budgets based on the 7th and 8th National Forest Inventories (NFI7 and NFI8), to the combining of private forestry plans, and to the realized drain from non-industrial private forests. The potential allowable cut was calculated using the same MELA system as has been used in the calculation of the national cutting budget. The data consisted of the NIPF holdings (from the TASO planning system) that had been inventoried compartmentwise and had forestry plans made during the years 1984-1992. The NIPF landowners' choices of timber management strategies were clarified by a two-phase mail inquiry. The most preferred strategy obtained was "sustainability" (chosen by 62 % of landowners). The second in order of preference was "finance" (17 %) and the third was "saving" (11 %). "No cuttings", and "maximum cuttings" were the least preferred (9 % and 1 %, resp.). The factors promoting the choices of strategies with intensive cuttings were a) "farmer as forest owner" and "owning fields", b) "increase in the size of the forest holding", c) agriculture and forestry orientation in production, d) "decreasing short term stumpage earning expectations", e) "increasing intensity of future cuttings", and f) "choice of forest taxation system based on site productivity". The potential allowable cut defined in the study was 20 % higher than the average of the realized drain during the years 1988-1993, which in turn, was at the same level as the cutting budget based on the combining of forestry plans in eastern Finland. Respectively, the potential allowable cut defined in the study was 12 % lower than the NFI8-based greatest sustained allowable cut for the 1990s. Using the method presented in this study, timber management strategies can be clarified for non-industrial private forest landowners in different parts of Finland. Based on the choices of timber managemet strategies, regular cutting budgets can be calculated more realistically than before.

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The factors affecting the non-industrial, private forest landowners' (hereafter referred to using the acronym NIPF) strategic decisions in management planning are studied. A genetic algorithm is used to induce a set of rules predicting potential cut of the landowners' choices of preferred timber management strategies. The rules are based on variables describing the characteristics of the landowners and their forest holdings. The predictive ability of a genetic algorithm is compared to linear regression analysis using identical data sets. The data are cross-validated seven times applying both genetic algorithm and regression analyses in order to examine the data-sensitivity and robustness of the generated models. The optimal rule set derived from genetic algorithm analyses included the following variables: mean initial volume, landowner's positive price expectations for the next eight years, landowner being classified as farmer, and preference for the recreational use of forest property. When tested with previously unseen test data, the optimal rule set resulted in a relative root mean square error of 0.40. In the regression analyses, the optimal regression equation consisted of the following variables: mean initial volume, proportion of forestry income, intention to cut extensively in future, and positive price expectations for the next two years. The R2 of the optimal regression equation was 0.34 and the relative root mean square error obtained from the test data was 0.38. In both models, mean initial volume and positive stumpage price expectations were entered as significant predictors of potential cut of preferred timber management strategy. When tested with the complete data set of 201 observations, both the optimal rule set and the optimal regression model achieved the same level of accuracy.