Cultural differences in disability attitudes significantly impact perceptions of and interactions with persons with disabilities. This study explored the multidimensional disability attitudes of the international college student’s towards persons with disabilities and their attitudes toward educational accommodations. The researcher also examined the relationship between these variables and the following demographic factors: sex, age, country of origin, religion, college major, and level of college study. The study is a cross-sectional survey design. The effective sample of the study was 211 enrolled undergraduate and graduate international students at Southern Illinois University Carbondale. These scales were used for data collection: (a) Multidimensional Attitudes Scale toward Persons with Disabilities (MAS), (b) General Attitudes toward College Educational Accommodation; (c) Marlowe-Crowne Social Desirability Scale; and (d) a demographic questionnaire. In this study, descriptive analyses and a multiple regression analysis computed to analyze all test measures and demographic variables. The results of this study provide information about the international student’s general attitude towards disability as well as the extent in which demographic variables may shape attitudes. In the first hypothesis only contact with person with disability was a significant predictor of the attitudes F1, 174 = 22.324, p < .001, R2 = .114. In the second hypothesis contact with person with disability and attitudes predicted general attitudes towards accommodation; F2, 173 = 7.101, p = .006, R2 = .076. All demographic factors dropped out of the models. A series of exploratory analyses was computed uncovered some potential demographic predictors of attitudes towards accommodation. This information may assist faculty and administrators to provide disability education interventions that may increase positive attitudes toward disability and people with disabilities. This may consequently enhance positive interactions of international students with persons with disabilities within and outside the university environment.

Understanding and managing change is a strategic objective for many organisations to successfully compete in a market place; as a result, organisations are leveraging their data asset and implementing data warehouses to gain business intelligence necessary to improve their businesses. Data warehouses are expensive initiatives, one-half to two-thirds of most data warehousing efforts end in failure. In the absence of well-formalised design methodology in the industry and in the context of the debate on data architecture in data warehousing, this thesis examines why multidimensional and relational data models define the data architecture landscape in the industry. The study develops a number of propositions from the literature and empirical data to understand the factors impacting the choice of logical data model in data warehousing. Using a comparative case study method as the mean of collecting empirical data from the case organisations, the research proposes a conceptual model for logical data model adoption. The model provides a framework that guides decision making for adopting a logical data model for a data warehouse. The research conceptual model identifies the characteristics of business requirements and decision pathways for multidimensional and relational data warehouses. The conceptual model adds value by identifying the business requirements which a multidimensional and relational logical data model is empirically applicable.

The concentration on healthcare information technology has never been determined than it is today. This awareness arises from the efforts to accomplish the extreme utilization of Electronic Health Record (EHR). Due to the greater mobility of the population, EHR will be constructed and continuously updated from the contribution of one or many EPRs that are created and stored at different healthcare locations such as acute Hospitals, community services, Mental Health and Social Services. The challenge is to provide healthcare professionals, remotely among heterogeneous interoperable systems, with a complete view of the selective relevant and vital EPRs fragments of each patient during their care. Obtaining extensive EPRs at the point of delivery, together with ability to search for and view vital, valuable, accurate and relevant EPRs fragments can be still challenging. It is needed to reduce redundancy, enhance the quality of medical decision making, decrease the time needed to navigate through very high number of EPRs, which consequently promote the workflow and ease the extra work needed by clinicians. These demands was evaluated through introducing a system model named SVSEPRS (Searching and Viewing Segments of Electronic Patient Records Service) to enable healthcare providers supply high quality and more efficient services, redundant clinical diagnostic tests. Also inappropriate medical decision making process should be avoided via allowing all patients‟ previous clinical tests and healthcare information to be shared between various healthcare organizations. Multidimensional data model, which lie at the core of On-Line Analytical Processing (OLAP) systems can handle the duplication of healthcare services. This is done by allowing quick search and access to vital and relevant fragments from scattered EPRs to view more comprehensive picture and promote advances in the diagnosis and treatment of illnesses. SVSEPRS is a web based system model that helps participant to search for and view virtual EPR segments, using an endowed and well structured Centralised Multidimensional Search Mapping (CMDSM). This defines different quantitative values (measures), and descriptive categories (dimensions) allows clinicians to slice and dice or drill down to more detailed levels or roll up to higher levels to meet clinicians required fragment.

This study surveyed floristic composition and distribution of weed vegetation in Mituo County. 206 relevés were surveyed according to relevé method. A total of 140 species belonging to 32 families of the vascular plants were recorded. The weed communities were classified with nonmetric multidimentional scaling, two-way indicator species analysis, tabular comparison method, fidelity and synoptic table analysis. Discriminate analysis was used to evaluate the distinctness of classification unitsal vegetation classification system was made using Braun-Blanquet approach of floristic-sociological classification in lower levels and physiognomic-sociological classification in higher levels. In floristic-sociological classification, assication is the basic unit, and it should be grouped into higher units (alliance) by floristic composition. The results showed 1 formation class, 2 formations in phsiogonomic units, and 4 alliances, 6 associations in floristic units: I. Lower montane-lowland weed vegetation formation A. Echinochloa colona alliance a. Echinochloa colona association b. Trianthemum portulacastrum association c. Panicum maximum association B. Dichanthium aristatum alliance d. Dichanthium aristatum association C. Eriochloa procera alliance e. Eriochloa procera association II. Sand dune vegetation formation D. Ipomoea pescaprae subsp. brasiliensis alliance f. Ipomoea pescaprae subsp. brasiliensis association

Please read the abstract in the section 00front of this document. / Dissertation (MEng (Electronic Engineering))--University of Pretoria, 2006. / Electrical, Electronic and Computer Engineering / unrestricted

Data warehouses are being used in many applications since quite a long time. Traditionally, new data in these warehouses is loaded through offline bulk updates which implies that latest data is not always available for analysis. This, however, is not acceptable in many modern applications (such as intelligent building, smart grid etc.) that require the latest data for decision making. These modern applications necessitate real-time fast atomic integration of incoming facts in data warehouse. Moreover, the data defining the analysis dimensions, stored in dimension tables of these warehouses, also needs to be updated in real-time, in case of any change. In this thesis, such real-time data warehouses are defined as dynamic data warehouses. We propose a data model for these dynamic data warehouses and present the concept of Hierarchical Hybrid Multidimensional Data Space (HHMDS) which constitutes of both ordered and non-ordered hierarchical dimensions. The axes of the data space are non-ordered which help their dynamic evolution without any need of reordering. We define a data grouping structure, called Minimum Bounding Space (MBS), that helps efficient data partitioning of data in the space. Various operators, relations and metrics are defined which are used for the optimization of these data partitions and the analogies among classical OLAP concepts and the HHMDS are defined. We propose efficient algorithms to store summarized or detailed data, in form of MBS, in a tree structure called DyTree. Algorithms for OLAP queries over the DyTree are also detailed. The nodes of DyTree, holding MBS with associated aggregated measure values, represent materialized sections of cuboids and tree as a whole is a partially materialized and indexed data cube which is maintained using online atomic incremental updates. We propose a methodology to experimentally evaluate partial data cubing techniques and a prototype implementing this methodology is developed. The prototype lets us experimentally evaluate and simulate the structure and performance of the DyTree against other solutions. An extensive study is conducted using this prototype which shows that the DyTree is an efficient and effective partial data cubing solution for a dynamic data warehousing environment.

<p>Abstract</p><p>In this thesis, a measurement system was set to perform comprehensive measurements on RF power amplifiers. Data obtained from the measurements is then processed mathematically to obtain three dimensional graphs of the basic parameters affected or generated by nonlinearities of the amplifier i.e. gain, efficiency and distortion. Using a class AB amplifier as the DUT, two sets of signals – both swept in power level and frequency - were generated to validate the method, a two-tone signal and a WCDMA signal. The three dimensional plot gives a thorough representation of the behavior of the amplifier in any arbitrary range of spectrum and input level. Sweet spots are consequently easy to detect and analyze. The measurement setup can also yield other three dimensional plots of variations of gain, efficiency or distortion versus frequencies and input levels. Moreover, the measurement tool can be used to plot traditional two dimensional plots such as, input versus gain, frequency versus efficiency etc, making the setup a practical tool for RF amplifiers designers.</p><p>The test signals were generated by computer then sent to a vector signal generator that generates the actual signals fed to the amplifier. The output of the amplifier is fed to a vector signal analyzer then collected by computer to be handled. MATLAB® was used throughout the entire process.</p><p>The distortion considered in the case of the two-tone signals is the third order intermodulation distortion (IM3) whereas Adjacent Channel Power Ratio (ACPR) was considered in the case of WCDMA.</p>

Abstract In this thesis, a measurement system was set to perform comprehensive measurements on RF power amplifiers. Data obtained from the measurements is then processed mathematically to obtain three dimensional graphs of the basic parameters affected or generated by nonlinearities of the amplifier i.e. gain, efficiency and distortion. Using a class AB amplifier as the DUT, two sets of signals – both swept in power level and frequency - were generated to validate the method, a two-tone signal and a WCDMA signal. The three dimensional plot gives a thorough representation of the behavior of the amplifier in any arbitrary range of spectrum and input level. Sweet spots are consequently easy to detect and analyze. The measurement setup can also yield other three dimensional plots of variations of gain, efficiency or distortion versus frequencies and input levels. Moreover, the measurement tool can be used to plot traditional two dimensional plots such as, input versus gain, frequency versus efficiency etc, making the setup a practical tool for RF amplifiers designers. The test signals were generated by computer then sent to a vector signal generator that generates the actual signals fed to the amplifier. The output of the amplifier is fed to a vector signal analyzer then collected by computer to be handled. MATLAB® was used throughout the entire process. The distortion considered in the case of the two-tone signals is the third order intermodulation distortion (IM3) whereas Adjacent Channel Power Ratio (ACPR) was considered in the case of WCDMA.

Pattern discovery in large binary relations has been extensively studied. An emblematic success in this area concerns frequent itemset mining and its post-processing that derives association rules. In this case, we mine binary relations that encode whether some properties are satisfied or not by some objects. It is however clear that many datasets correspond to n-ary relations where n > 2. For example, adding spatial and/or temporal dimensions (location and/or time when the properties are satisfied by the objects) leads to the 4-ary relation Objects x Properties x Places x Times. Therefore, we study the generalization of association rule mining within arbitrary n-ary relations: the datasets are now Boolean tensors and not only Boolean matrices. Unlike standard rules that involve subsets of only one domain of the relation, in our setting, the head and the body of a rule can include arbitrary subsets of some selected domains. A significant contribution of this thesis concerns the design of interestingness measures for such generalized rules: besides a frequency measures, two different views on rule confidence are considered. The concept of non-redundant rules and the efficient extraction of the non-redundant rules satisfying the minimal frequency and minimal confidence constraints are also studied. To increase the subjective interestingness of rules, we then introduce disjunctions in their heads. It requires to redefine the interestingness measures again and to revisit the redundancy issues. Finally, we apply our new rule discovery techniques to dynamic relational graph analysis. Such graphs can be encoded into n-ary relations (n ≥ 3). Our use case concerns bicycle renting in the Vélo'v system (self-service bicycle renting in Lyon). It illustrates the added-value of some rules that can be computed thanks to our software prototypes.

Le calcul de motifs dans de grandes relations binaires a été très étudié. Un succès emblématique concerne la découverte d'ensembles fréquents et leurs post-traitements pour en dériver des règles d'association. Il s'agit de calculer des motifs dans des relations binaires qui enregistrent quelles sont les propriétés satisfaites par des objets. En fait, de nombreux jeux de données se présentent naturellement comme des relations n-aires (avec n > 2). Par exemple, avec l'ajout de dimensions spatiales et/ou temporelles (lieux et/ou temps où les propriétés sont enregistrées), la relation binaire Objets x Propriétés est étendue à une relation 4-aire Objets x Propriétés x Lieux x Temps. Nous avons généralisé le concept de règle d'association dans un tel contexte multi-dimensionnel. Contrairement aux règles usuelles qui n'impliquent que des sous-ensembles d'un seul domaine de la relation, les prémisses et les conclusions de nos règles peuvent impliquer des sous-ensembles arbitraires de certains domaines. Nous avons conçu des mesures de fréquence et de confiance pour définir la sémantique de telles règles et c'est une contribution significative de cette thèse. Le calcul exhaustif de toutes les règles qui ont des fréquences et confiances suffisantes et l'élimination des règles redondantes ont été étudiés. Nous proposons ensuite d'introduire des disjonctions dans les conclusions des règles, ce qui nécessite de retravailler les définitions des mesures d'intérêt et les questions de redondance. Pour ouvrir un champ d'application original, nous considérons la découverte de règles dans des graphes relationnels dynamiques qui peuvent être codés dans des relations n-aires (n ≥ 3). Une application à l'analyse des usages de bicyclettes dans le système Vélo'v (système de Vélos en libre-service du Grand Lyon) montre quelques usages possibles des règles que nous savons calculer avec nos prototypes logiciels. / Pattern discovery in large binary relations has been extensively studied. An emblematic success in this area concerns frequent itemset mining and its post-processing that derives association rules. In this case, we mine binary relations that encode whether some properties are satisfied or not by some objects. It is however clear that many datasets correspond to n-ary relations where n > 2. For example, adding spatial and/or temporal dimensions (location and/or time when the properties are satisfied by the objects) leads to the 4-ary relation Objects x Properties x Places x Times. Therefore, we study the generalization of association rule mining within arbitrary n-ary relations: the datasets are now Boolean tensors and not only Boolean matrices. Unlike standard rules that involve subsets of only one domain of the relation, in our setting, the head and the body of a rule can include arbitrary subsets of some selected domains. A significant contribution of this thesis concerns the design of interestingness measures for such generalized rules: besides a frequency measures, two different views on rule confidence are considered. The concept of non-redundant rules and the efficient extraction of the non-redundant rules satisfying the minimal frequency and minimal confidence constraints are also studied. To increase the subjective interestingness of rules, we then introduce disjunctions in their heads. It requires to redefine the interestingness measures again and to revisit the redundancy issues. Finally, we apply our new rule discovery techniques to dynamic relational graph analysis. Such graphs can be encoded into n-ary relations (n ≥ 3). Our use case concerns bicycle renting in the Vélo'v system (self-service bicycle renting in Lyon). It illustrates the added-value of some rules that can be computed thanks to our software prototypes.