A systematic methodology for quantitative structure-activity relationship (QSAR) development in environmental toxicology is provided. The methodology is summarized in a strategy with six sequential steps. The strategy rests on two cornerstones, namely (1) the use of statistical design to select a series of representative compounds (the so-called training set) on which to base a QSAR, and (2) the multivariate modelling of the relationship between physicochemical and biological properties of the training set compounds. The first step of the strategy is the division of chemicals into classes of structurally similar compounds. Briefly, steps 2 to 6 are: (2) physico-chemical and structural characterization of the compounds in a class, (3) selection of a training set of representative compounds, (4) biological testing of the selected training set, (5) QSAR model development, and (6) experimental validation of the QSAR and predictions for non-tested compounds. The thesis summarizes the results obtained from the application of the strategy to the class of halogenated aliphatic compounds. Biological measurements were made in four biological test systems, reflecting acute toxicity, mutagenicity, relative cytotoxicity and genotoxicity. QSARs were developed relating each biological endpoint to the structural descriptors of the compounds. Multivariate PLS modelling was used in the data analysis. The developed QSARs were used for predicting the biological activity pattern of the non-tested compounds in the class. These predictions may be used as a starting point for a priority ranking for further biological testing of these compounds. The strategy has not been developed solely for establishing QSARs for the halogenated aliphatics class. On the contrary, this work is intended to demonstrate a generally applicable QSAR methodology. / <p>Diss. (sammanfattning) Umeå : Umeå universitet, 1991</p> / digitalisering@umu

A term weighting scheme measures the importance of a term in a collection. A document ranking model uses these term weights to find the rank or score of a document in a collection. We present a series of cluster-based term weighting and document ranking models based on the TF-IDF and Okapi BM25 models. These term weighting and document ranking models update the inter-cluster and intra-cluster frequency components based on the generated clusters. These inter-cluster and intra-cluster frequency components are used for weighting the importance of a term in addition to the term and document frequency components. In this thesis, we will show how these models outperform the TF-IDF and Okapi BM25 models in document clustering and ranking.

Information retrieval aims to extract from a large collection of data a subset of information that is relevant to user’s needs. In this study, we are interested in information retrieval in Arabic-Language text documents. We focus on the Arabic language, its morphological features that potentially impact the implementation and performance of an information retrieval system and its unique characters that are absent in the Latin alphabet and require specialized approaches. Specifically, we report on the design, implementation and evaluation of the search functionality using the Vector Space Model with several weighting schemes. Our implementation uses the ISRI stemming algorithms as the underlying stemming technique and the general Arabic stop word list for building inverted indices for Arabic-language documents. We evaluate our implementation on a corpus consisting of selected technical papers published in Arabic-language journals. We use the Open Journal Systems (OJS) from the Public Knowledge Project as a repository for the corpus used in the evaluation. We evaluate the performance of our implementation of the search using a classic recall/precision approach and compare it to one of the default multilingual search functions supported in the OJS. Our experimental analysis suggests that stemming is an effective technique for searches in Arabic-language texts that improves the quality of the information retrieval system.

Wildfire is a destructive and devastating phenomenon experienced all around the world, which is predicted to increase in frequency and geographical range as climate change continues throughout the 21st century and beyond. This paper used a GIS approach to analyse the expected change in wildfire geographical range by 2050 using a Global Climate Model of the worst case scenario. After new wildfire-prone regions were identified, an analysis of these regions was undertaken regarding human-risk to ignition, currently the largest cause of wildfire outbreaks. This was performed using a ranking system of variables known to increase the human-risk, namely rural exodus, density of agricultural machinery, prevalence of tobacco smoking, and camping tourism popularity. The results were in consensus with the scientific community regarding the effect of climate change on the geographical range of wildfire outbreaks, and identified Europe as a key area of future concern. Within Europe, Austria was seen as having the highest risk to human-ignition. This could be of utmost importance to European, especially Austrian, management agencies as they look to restrict the future impact of climate change on their communities. This paper serves as an example of how spatiotemporal patterns of extreme weather events and climate change can be projected using GIS. / Skogsbrand är ett destruktivt och förödande fenomen över hela världen och förutspås att öka i frekvens och geografisk utbredning med förändrade klimatförutsättningar under det tjugoförsta århundradet och framöver. Den här studien har använt GIS som metod för att analysera den förväntade förändringen av skogsbränders geografiska utbredning år 2050, baserat på värsta scenariot framtaget i en global klimatmodellering. Efter att nya skogsbrandsbenägna regioner identifierats, gjordes en analys av regionerna avseende mänskliga faktorer som ökar risken för antändning, för närvarande den största orsaken till skogbrandssutbrott. Riskanalyserna utfördes med ett rankingsystem av variabler som är kända för att öka risken, nämligen avfolkning av landsbygden, densitet av jordbruksmaskiner, förekomsten av tobaksrökning, och campingturismens popularitet. Studiens resultat stämmer överens med vetenskapliga studier avseende klimatförändringens effekter på geografisk utbredning av skogbrandssutbrott. I studien identifierades Europa som ett nyckelområde för framtida risker. Inom Europa hade Österrike den högsta risken för mänsklig antändning. Resultatet kan vara av yttersta vikt för europeiska, särskilt österrikare, förvaltningsorgan som försöker att begränsa den framtida inverkan av klimatförändringar på deras samhällen. Den här studien är ett exempel på hur rumsliga fördelningsmönster av extrema väderförhållanden och klimatförändringar kan projiceras genom att använda GIS.

kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 object model and provides a framework for creating and using kernel-based algorithms. The package contains dot product primitives (kernels), implementations of support vector machines and the relevance vector machine, Gaussian processes, a ranking algorithm, kernel PCA, kernel CCA, and a spectral clustering algorithm. Moreover it provides a general purpose quadratic programming solver, and an incomplete Cholesky decomposition method. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

Talentingų jaunųjų krepšininkų atranka – viena svarbiausių šiuolaikinio rengimo problemų. 9-16 metų amžius yra vienas jautriausių, kuomet atsiskleidžia įgimti fiziniai gebėjimai bei įgyjama naujų mokėjimų, leidžiančių siekti gerų sportinių rezultatų. Vis dėlto objektyvios fizinio ir techninio pajėgumo vertinimo sistemos Lietuvoje dar nėra. Žaidimų sporte vyraujantis kriterinis vertinimas kartais stokoja objektyvumo, todėl ieškodami tikslesnio vertinimo būdų, kėlėme probleminį klausimą: Kokios gi yra jaunųjų krepšininkų fizinio išsivystymo ir fizinio bei techninio parengtumo vertinimo normos, galinčios padėti vykdyti rengimo kontrolę bei atranką? Remiantis probleminiu klausimu buvo apibrėžtas tyrimo objektas – jaunųjų krepšininkų fizinis išsivystymas, funkcinis pajėgumas bei lokomociniai gebėjimai. Atsižvelgiant į pasirinktos temos aktualumą bei mokslinę problemą buvo siekiama šio tikslo – įvertinti jaunųjų krepšininkų fizinį išsivystymą, funkcinį pajėgumą bei lokomocinius gebėjimus, pateikiant normines vertinimo skales. Siekiant užsibrėžto tikslo, magistro darbe buvo keliami šie pagrindiniai tyrimo uždaviniai: ištirti 9-16 metų amžiaus žaidėjų fizinį išsivystymą, funkcinį pajėgumą ir lokomocinius gebėjimus. Sudaryti santykinės padėties matų – procentilių ranginę skalę, kuri leistų vertinti 9-16 metų amžiaus krepšininkų fizinį išsivystymą bei lokomocinių gebėjimų lygį. Modifikuoti metimų į krepšį testo rezultatų skaičiavimą, pateikiant norminio vertinimo skales... [toliau žr. visą tekstą] / One of the most important problems in modern athletes training is the selection process of talented young basketball players. The age of 9-16 is one of the most sensitive periods when innate physical abilities are revealing and new skills are gained for achievement of high sport results in the future. However, Lithuania does not have an objective system for physical and technical capacity evaluation yet. Evaluation under certain criteria in sports games lacks objectivity at times that is why to seek for more precise evaluation methods we have raised the question: what are the evaluation norms of young basketball players’ physical development and physical as well as technical preparedness that will help to develop athletes’ training control and selection? Considering the problem, research object was settled as follows – young basketball players’ physical development, functional capacity, and locomotor skills. In view of relevance of chosen topic and scientific problem, it was aimed to evaluate young basketball players’ physical development, functional capacity, and locomotor skills when introducing rating scales. To follow the aim those were the main tasks in this master thesis: to research physical development, functional capacity, and locomotor skills of young basketball players of age 9-16; to form ratio position measurements-percentile ranking scale that allows evaluating the level of physical development and locomotor skills of basketball players of age 9-16; to modify... [to full text]

The transfer pricing, literature indicates that an investigation of some aspects of this subject could usefully be undertaken in order to contribute to the understanding of transfer pricing in both domestic and international markets. This study aims at exploring the current state of transfer pricing practice and establishing the importance attached to the ranking of transfer pricing determinants (i. e. objectives and environmental variables) and the extent to which the ranking varies across markets, industry, and according to the transfer pricing method used. It also seeks to discover interrelationship among the transfer pricing determinants in order to produce a reduced set of basic factors. Lastly, it aims at evaluating the relationship between transfer pricing determinants and transfer pricing methods and at discovering a means of predicting the latter from the company's perception of the relative importance of these determinants. To achieve the above objectives, an empirical study covering both domestic and international markets was undertaken in UK companies. The conclusions are concerned with transfer pricing policy, methods currently used, and problems apparent in practice. The overall ranking-by survey respondents of the transfer pricing determinants is given as well as the results of tests of certain hypotheses which relate to this ranking. The transfer pricing determinants used in the survey for domestic and international. markets (twelve and twenty respectively) have been reduced by Factor Analysis to four and six factors. The study made use of the results to obtain measures of the ranking of discovered factors. Finally, the relationship between the transfer pricing determinants and transfer pricing methods was quantitatively evaluated in the form of a set of classification functions by using Multi-Discriminant Analysis. The classification functions are able to predict the transfer pricing method actually used in companies with an acceptable degree of success. The study's results have been reviewed with a small number of senior managers who are involved in establishing transfer pricing policy within their companies.

Ranking queries are widely used in data exploration, data analysis and decision making scenarios. While most of the currently proposed ranking techniques focus on deterministic data, several emerging applications involve data that are imprecise or uncertain. Ranking uncertain data raises new challenges in query semantics and processing, making conventional methods inapplicable. Furthermore, the interplay between ranking and uncertainty models introduces new dimensions for ordering query results that do not exist in the traditional settings. This dissertation introduces new formulations and processing techniques for ranking queries on uncertain data. The formulations are based on marriage of traditional ranking semantics with possible worlds semantics under widely-adopted uncertainty models. In particular, we focus on studying the impact of tuple-level and attribute-level uncertainty on the semantics and processing techniques of ranking queries. Under the tuple-level uncertainty model, we introduce a processing framework leveraging the capabilities of relational database systems to recognize and handle data uncertainty in score-based ranking. The framework encapsulates a state space model, and efficient search algorithms that compute query answers by lazily materializing the necessary parts of the space. Under the attribute-level uncertainty model, we give a new probabilistic ranking model, based on partial orders, to encapsulate the space of possible rankings originating from uncertainty in attribute values. We present a set of efficient query evaluation algorithms, including sampling-based techniques based on the theory of Markov chains and Monte-Carlo method, to compute query answers. We build on our techniques for ranking under attribute-level uncertainty to support rank join queries on uncertain data. We show how to extend current rank join methods to handle uncertainty in scoring attributes. We provide a pipelined query operator implementation of uncertainty-aware rank join algorithm integrated with sampling techniques to compute query answers.

In this study, Turkey&rsquo / s Internet visibility will be analyzed based on data to be collected from multiple different resources (such as / Google, Yahoo, Altavista, Bing and AOL). Analysis work will involve inspection of DNS queries, Web crawling and some other similar techniques. Our goal is to investigate global Internet and find webs that has common pattern of representing Internet visibility of Turkey and compare their characteristics with other webs&#039 / on the world and discover their similarities and differences.

Thesis (Ph. D.)--University of Missouri-Columbia, 2004. / Typescript. Vita. Includes bibliographical references (leaves 159-165). Also available on the Internet.