Indiana University-Purdue University Indianapolis (IUPUI) / During the latter half of the nineteenth and in the early twentieth century, the Indianapolis Wholesale District (IWD) operated as a local and regional commercial hub. Analysis of the IWD’s relationship with the railroad network in Indiana points to a widening of trade, yet regional focus due to transportation restrictions. The growth and subsequent specialization of wholesale trading in the district catered to primarily local and regional audiences. Examining the physical presence of the IWD in downtown Indianapolis uncovers the built environment of a midwestern business district. This research project argues for the local and regional significance of the Indianapolis Wholesale District. Additionally, this thesis demonstrates the need to pursue the overlap in specialization, the morphology of warehouses, and transportation development to understand a business district as part of a larger process of American economic development.

Dans cette thèse, nous nous sommes intéressés à l'analyse des données de simulation issues du modèle agro-hydrologique TNT. Les objectifs consistaient à élaborer des méthodes d'analyse des résultats de simulation qui replacent l'utilisateur au coeur du processus décisionnel, et qui permettent d'analyser et d'interpréter de gros volumes de données de manière efficace. La démarche développée consiste à utiliser des méthodes d'analyse multidimensionnelle interactive. Tout d'abord, nous avons proposé une méthode d'archivage des résultats de simulation dans une base de données décisionnelle (i.e. entrepôt de données), adaptée au caractère spatio-temporel des données de simulation produites. Ensuite, nous avons suggéré d'analyser ces données de simulations avec des méthodes d'analyse en ligne (OLAP) afin de fournir aux acteurs des informations stratégiques pour améliorer le processus d'aide à la prise de décision. Enfin, nous avons proposé deux méthodes d'extraction de skyline dans le contexte des entrepôts de données afin de permettre aux acteurs de formuler de nouvelles questions en combinant des critères environnementaux contradictoires, et de trouver les solutions compromis associées à leurs attentes, puis d'exploiter les préférences des acteurs pour détecter et faire ressortir les données susceptibles de les intéresser. La première méthode EC2Sky, permet un calcul incrémental et efficace des skyline en présence de préférences utilisateurs dynamiques, et ce malgré de gros volumes de données. La deuxième méthode HSky, étend la recherche des points skyline aux dimensions hiérarchiques. Elle permet aux utilisateurs de naviguer le long des axes des dimensions hiérarchiques (i.e. spécialisation / généralisation) tout en assurant un calcul en ligne des points skyline correspondants. Ces contributions ont été motivées et expérimentées par l'application de gestion des pratiques agricoles pour l'amélioration de la qualité des eaux des bassins versants agricoles, et nous avons proposé un couplage entre le modèle d'entrepôt de données agro-hydrologiques construit et les méthodes d'extraction de skyline proposées. / This thesis concerns the analysis of simulation data generated by the agrohydrological model TNT. Our objective is to develop analytical methods for massive simulation results. We want to place the user at the heart of the decision-making process, while letting him handle and analyze large amounts of data in a very efficient way. Our first contribution is an original approach N-Catch, relying on interactive multidimensional analysis methods for archiving simulation results in a decisional database (i.e. data warehouse) adapted to the spatio-temporal nature of the simulation data. In addition, we suggest to analyze the simulation data with online analytical methods (OLAP) to provide strategic information for stakeholders to improve the decision making process. Our second contribution concern two methods for computing skyline queries in the context of data warehouses. These methods enable stakeholders to formulate new questions by combining conflicting environmental criteria, to find compromise solutions associated with their expectations, and to exploit the stakeholder preferences to identify and highlight the data of potential interest. The first method EC2Sky, focuses on how to answer efficiently and progressively skyline queries in the presence of several dynamic user preferences despite of large volume of data. The second method HSky, extends the skyline computation to hierarchical dimensions. It allows the user to navigate along the dimensions hierarchies (i.e. specialize / generalize) while ensuring the online computation of associated skylines. Finally, we present the application of our proposals for managing agricultural practices to improve water quality in agricultural watersheds. We propose a coupling between the agro-hydrological data warehouse model N-Catch and the proposed skyline computation methods.

This project attempts to break down categorization and systems of thought based on opposing qualities. Instead, disparate elements are considered to work together to increase their individual properties by creating a new property - a condition comprised of the individual elments yet also surpassing them. The word "hybrid" is appropriated to describe the nature of this investigation - the renovation of a turn-of-the-century warehouse building into a multi-use building. The project attempts to describe how a building that contains a range of disparate programmatic elements can go beyond each element's exclusivity to produce a condition in which the resultant is greater than the sum of the individual parts. The project looks at breaking down specific delimitors of adjacent programmatic elements and promotes cross-fertilization between them with the intended result of blurring the seams that separate one from the other. The intent is to investigate, through a series of minimal moves dictated by the conditions of the site and program, whether a condition of richer and more varied experience can be achieved and, as a result, provide a start for defining a condition of architectural hybridity. Due to the size of the building that is investigated, this project focuses on two areas of the building, the insertion of a courtyard and the insertion of a fissure, or crack. The point of these investigations is to provide a tactical solution for the specificities of this particular site while at the same time implying a larger, global strategy that not only infers the remainder of this building but includes similar building types in other locations.

政府事業單位重要的任務之一，在於擬定相關管理與營運的政策，因此有關於營運面的相關資訊，就成為重要的決策依據。除此之外來自民意單位質詢，彈性相當大，範圍包含了整個事業業務，因此對於決策資訊需求，往往都是包羅萬象千變萬化的，因此如何快速且正確地取得營運資訊，便成為各單位一嚴峻的考驗，而目前以報表為基礎的營運決策模式，已經漸漸無法符合變動性日增的決策需求，而資料倉儲與多維度模型的設計，正可符合快速變動的決策資訊需求。 本論文將透過對於個案組織的深入質化訪談，進一步建立個案組織的業務流程，並且透過對於個案組織業務內容的深入瞭解，對於其政策制訂之相關決策點、參考資訊、資訊流做詳細的分析，以便針對對決策資訊的來源與性質，找出相對應的屬性、維度與事實。如此一來，便可發現資料倉儲的設計，必須以流程模型為基礎，並且透過模型的指引，設計適合用戶業務內容的資料倉儲與資料模型，並且為未來組織轉型時的配適，提供最大的彈性。

A set of technical issues are addressed related to benchmarking best practice behavior in warehouses. In order to identify best practice, first performance needs to be measured. There are a variety of tools available to measure productivity and efficiency. One of the most common tools is data envelopment analysis (DEA). Given a system that consumes inputs to generate outputs, previous work has shown production theory can be used to develop basic postulates about the production possibility space and to construct an efficient frontier which is used to quantify efficiency. Beyond inputs and outputs warehouses typically have practices (techniques used in the warehouse) or attributes (characteristics of the environment of the warehouse including demand characteristics) which also influence efficiency. Previously in the literature, a two-stage method has been developed to investigate the impact of practices and attributes on efficiency. When applying this method, two issues arose: how to measure efficiency in small samples and how to identify outliers. The small sample efficiency measurement method developed in this thesis is called multi-input / multi-output quantile based approach (MQBA) and uses deleted residuals to estimate efficiency. The outlier detection method introduces the inefficient frontier. Both overly efficient and overly inefficient outliers can be identified by constructing an efficient and an inefficient frontier. The outlier detection method incorporates an iterative procedure previously described, but has not been implemented in the literature. Further, this thesis also discusses issues related to selecting an orientation in super efficiency models. Super efficiency models are used in outlier detection, but are also commonly used in measuring technical progress via the Malmquist index. These issues are addressed using two data sets recently collected in the warehousing industry. The first data set consists of 390 observations of various types of warehouses. The other data set has 25 observations from a specific industry. For both data sets, it is shown that significantly different results are realized if the methods suggested in this document are adopted.

Made available in DSpace on 2016-06-02T19:04:00Z (GMT). No. of bitstreams: 1 6824.pdf: 22060515 bytes, checksum: bde19feb7a6e296214aebe081f2d09de (MD5) Previous issue date: 2015-12-07 / Universidade Federal de Minas Gerais / O data warehouse espacial (DWE) é um banco de dados multidimensional integrado e volumoso que armazena dados espaciais e dados convencionais. Já o processamento analítico espacial online (SOLAP) permite consultar o DWE, tanto pela seleção de dados espaciais que satisfazem um relacionamento topológico, quanto pela agregação dos dados espaciais. Deste modo, DWE e SOLAP beneficiam o suporte a tomada de decisão. As aplicações de DWE e SOLAP abordam majoritarimente fenômenos representados por dados espaciais exatos, ou seja, que assumem localizações e fronteiras bem definidas. Contudo, tais aplicações negligenciam dados espaciais afetados por imperfeições, tais como a vagueza espacial, a qual interfere na identificação precisa de um objeto e de seus vizinhos. Um objeto espacial vago não tem sua fronteira ou seu interior precisamente definidos. Além disso, é composto por partes que certamente pertencem a ele e partes que possivelmente pertencem a ele. Apesar de inúmeros fenômenos do mundo real serem caracterizados pela vagueza espacial, na literatura consultada não se identificaram trabalhos que considerassem a vagueza espacial no projeto de DWE e nem para consultar o DWE. Tal limitação motivou a elaboração desta tese de doutorado, a qual introduz os conceitos de DWE vago e de SOLAP vago. Um DWE vago é um DWE que armazena dados espaciais vagos, enquanto que SOLAP vago provê os meios para consultar o DWE vago. Nesta tese, o projeto de DWE vago é abordado e as principais contribuições providas são: (i) o modelo conceitual VSCube que viabiliza a criação de um cubos de dados multidimensional para representar o esquema conceitual de um DWE vago; (ii) o modelo conceitual VSMultiDim que permite criar um diagrama para representar o esquema conceitual de um DWE vago; (iii) diretrizes para o projeto lógico do DWE vago e de suas restrições de integridade, e para estender a linguagem SQL visando processar as consultas de SOLAP vago no DWE vago; e (iv) o índice VSB-index que aprimora o desempenho do processamento de consultas no DWE vago. A aplicabilidade dessas contribuições é demonstrada em dois estudos de caso no domínio da agricultura, por meio da criação de esquemas conceituais de DWE vago, da transformação dos esquemas conceituais em esquemas lógicos de DWE vago, e do processamento de consultas envolvendo as regiões vagas do DWE vago. / Spatial data warehouses (SDW) and spatial online analytical processing (SOLAP) enhance decision making by enabling spatial analysis combined with multidimensional analytical queries. A SDW is an integrated and voluminous multidimensional database containing both conventional and spatial data. SOLAP allows querying SDWs with multidimensional queries that select spatial data that satisfy a given topological relationship and that aggregate spatial data. Existing SDW and SOLAP applications mostly consider phenomena represented by spatial data having exact locations and sharp boundaries. They neglect the fact that spatial data may be affected by imperfections, such as spatial vagueness, which prevents distinguishing an object from its neighborhood. A vague spatial object does not have a precisely defined boundary and/or interior. Thus, it may have a broad boundary and a blurred interior, and is composed of parts that certainly belong to it and parts that possibly belong to it. Although several real-world phenomena are characterized by spatial vagueness, no approach in the literature addresses both spatial vagueness and the design of SDWs nor provides multidimensional analysis over vague spatial data. These shortcomings motivated the elaboration of this doctoral thesis, which addresses both vague spatial data warehouses (vague SDWs) and vague spatial online analytical processing (vague SOLAP). A vague SDW is a SDW that comprises vague spatial data, while vague SOLAP allows querying vague SDWs. The major contributions of this doctoral thesis are: (i) the Vague Spatial Cube (VSCube) conceptual model, which enables the creation of conceptual schemata for vague SDWs using data cubes; (ii) the Vague Spatial MultiDim (VSMultiDim) conceptual model, which enables the creation of conceptual schemata for vague SDWs using diagrams; (iii) guidelines for designing relational schemata and integrity constraints for vague SDWs, and for extending the SQL language to enable vague SOLAP; (iv) the Vague Spatial Bitmap Index (VSB-index), which improves the performance to process queries against vague SDWs. The applicability of these contributions is demonstrated in two applications of the agricultural domain, by creating conceptual schemata for vague SDWs, transforming these conceptual schemata into logical schemata for vague SDWs, and efficiently processing queries over vague SDWs.

Depuis son apparition en 1998, le langage XML (eXtensible Markup Language) est devenu un standard pour la modélisation et l'échange de données. En effet, XML permet de modéliser des structures de données qui ne sont pas facilement représentées dans les systèmes relationnels. Dans ce contexte, les entrepôts de données XML représentent aujourd'hui la base de plusieurs applications décisionnelles qui exploitent des données hétérogènes (peu structurées et provenant des sources multiples) aux structures complexes comme par exemple des hiérarchies complexes.Dans ce mémoire, nous proposons une nouvelle solution XOLAP (XML-OLAP) en temps réel qui traite les problèmes d'additivité dus aux hiérarchies complexes. Tout d'abord, nous proposons un nouveau modèle de données : les arbres de données multidimensionnels, qui permet de modéliser les faits, les dimensions, les mesures et les hiérarchies complexes d'un entrepôt de données XML. Pour pouvoir interroger les arbres de données multidimensionnels, nous modélisons les requêtes utilisateur à l'aide de modèles d'arbre XML. Nous proposons ensuite un nouvel algorithme de regroupement et d'agrégation pour la résolution en temps réel des problèmes d'additivité dans les hiérarchies complexes. Nous généralisons enfin cet algorithme à un nouvel opérateur XOLAP de forage vers le haut (roll-up).Finalement, nous validons nos propositions de manière expérimentale. Pour cela, nous étendons le banc d'essais XWeB en introduisant des hiérarchies complexes dans son schéma. La comparaison de notre approche à une approche de référence montre que la surcharge due à l'exécution en temps réel de notre approche est tout à fait acceptable et que nos algorithmes sont susceptibles de passer à l'échelle. / Since its inception in 1998, the eXtensible Markup Language (XML) has emerged as a standard for data representation and exchange over the Internet. XML provides an opportunity for modeling data structures that are not easily represented in relational systems. In this context, XML data warehouses nowadays form the basis of several decision-support applications exploiting heterogeneous data (little structured and coming from various sources) bearing complex structures, such as complex hierarchies. In this thesis, we propose a novel XOLAP (XML-OLAP) approach that automatically detects and processes summarizability issues at query time, without requiring any particular expertise from the user. Thus, at the logical level, we choose XML data trees, so-called multidimensional data trees, to model the multidimensional structures (facts, dimensions, measures and complex hierarchies) of XML data warehouses. In order to query multidimensional data trees, we model user queries as XML pattern trees. Then, we introduce a new aggregation algorithm to address summarizability issues in complex hierarchies. On the basis of this algorithm, we propose a novel XOLAP roll-up operator. Finally, we experimentally validate our proposal and compare our approach with the reference approach for addressing summarizability issues in complex hierarchies. For this sake, we extend the XML warehouse benchmark XWeB with complex hierarchies to generate XML data warehouses with scalable complex hierarchies. The results of our experiments show that the overhead induced by managing hierarchy complexity at run-time is totally acceptable and that our approach is expected to scale up well.

M.Tech. (Architectural Technology) / The City of Johannesburg has no formal recycling strategy and waste is simply dumped as collected in designated landfill sites. Yet these landfill sites, reportedly, will be good for no more than another eight years. Throughout the city there is an informal network of waste collectors commonly known as trolley pushers who, together with the private buy-back and recycle centres, form the only real system of recycling in Johannesburg. There is no infrastructure for the trolley pushers, men and women who perform a vital function. There are no dedicated spaces and very little tolerance from the residents of Johannesburg. The trolley pushers sleep amongst their collection of waste, or travel far to start each day in the very early hours of the morning. They roll their improvised trolleys full of goods in the street among the traffic of commuters, hindering and being hindered. They store their messy waste, when they can in unsafe and public spaces, such as under bridges and on the side of some roads. Storage is such a problem for trolley pushers that often they’re forced to sell their goods as soon as they collect them, when the fluctuating prices may be too low. They are always essentially at the mercy of the privately-owned buyback centres. Their days are long and they have no ablution facilities, no designated space to catch their breath, eat, obtain drinking water, network or socialise. This project is about changing that by facilitating the informal recycling sector, providing the convenient infrastructure without formalising the process. The term ‘convenient’ in this context encompasses spaces close to the buy-back centre, with low tech, low maintenance, mixed-use facilities. These facilities include secure sorting and storage spaces, sleeping, ablution and social spaces. The essence of this project is to encourage, empower and improve work and income potential in the informal waste recycling sector through simple, appropriate architectural interventions that are essentially selfmaintaining.

The subject of this thesis is a pilot project of the implementation of the BI (Business Intelligence) solution in the company Haguess, a. s. The project is concerned with the analyses of data stored in a database -- DataBase Management System (DBMS) -- which is used as a data source by the web application Customer Support Center (CSC). Haguess primarily uses CSC as a helpdesk for its clients and partners, but also uses it for internal purposes. The main use of the CSC application is to support information systems delivered by Haguess. There were two motives for the choice of this subject: BI software tools had not previously been used by Haguess, and the company management was keen to get data analyses from the CSC application. That's why I decided to do these analyses. My goal was to create a practically useful solution which would be an incentive for Haguess to use BI software tools for other purposes. This thesis has two main goals. The first one is the realisation of the pilot BI solution, which would outline the possibilities for analysis of data from the CSC application using BI software tools. This involved the following activities: multidimensional analysis and BI solution design -- i.e. design of data pipelines, OLAP (On-Line Analytical Processing) cube/cubes, and user tools in MS Excel calculator. The second goal was to select the proper software tools for a future complex realisation and running of the BI solution. The first objective was achieved by doing the following: proper analysis of the CSC application data model, definition of user requests for output analysis and its comparison with the data model analysis. Based on this comparison, the basic subjects of output analyses were determined. These basic subjects were the starting point for the implementation of the BI solution. The second objective was achieved as follows: on the basis of the implementation results, basic demands (criteria) for BI software tools features were determined, bearing in mind the possible future complex realisation and running of a BI solution. Research determined which BI software tools were available on the market. The most suitable BI software tool was selected following a comparison of available options, and the criteria mentioned above. The primary outcome of this thesis is the creation of a practically usable BI solution.

This project attempts to break down categorization and systems of thought based on opposing qualities. Instead, disparate elements are considered to work together to increase their individual properties by creating a new property - a condition comprised of the individual elments yet also surpassing them. The word "hybrid" is appropriated to describe the nature of this investigation - the renovation of a turn-of-the-century warehouse building into a multi-use building. The project attempts to describe how a building that contains a range of disparate programmatic elements can go beyond each element's exclusivity to produce a condition in which the resultant is greater than the sum of the individual parts. The project looks at breaking down specific delimitors of adjacent programmatic elements and promotes cross-fertilization between them with the intended result of blurring the seams that separate one from the other. The intent is to investigate, through a series of minimal moves dictated by the conditions of the site and program, whether a condition of richer and more varied experience can be achieved and, as a result, provide a start for defining a condition of architectural hybridity. Due to the size of the building that is investigated, this project focuses on two areas of the building, the insertion of a courtyard and the insertion of a fissure, or crack. The point of these investigations is to provide a tactical solution for the specificities of this particular site while at the same time implying a larger, global strategy that not only infers the remainder of this building but includes similar building types in other locations. / Applied Science, Faculty of / Architecture and Landscape Architecture (SALA), School of / Graduate