This thesis is focused on development of framework for spatial data management. As proof of the concept, an Objective-C application based on the framework was developed. Further, Core Data framework including theoretical and practical functions for development is introduced. Research part of thesis deals with open source library SpatiaLite and their useful functions.

Cvrček, D. Web and mobile application for effective using working hours. Diploma thesis. Brno, 2018. This diploma thesis is focused on improvement of the work efficiency. The goal is to study existing technique called Pomodoro, design and implement a mobile and web application, which can provide the user an overview of performed work and its efficiency. Further, a mobile application for smartwatches which will be implemented for tracking of the user behavior and related personal notifications. All described applications are tested on a group of selected users.

The main campus of Virginia Polytechnic Institute and State University (Virginia Tech) has more than 120 buildings. The campus visitors face problems recognizing a building, finding a building, obtaining directions from one building to another, and getting information about a building. The exploratory development research described herein resulted in an iPhone / iPad software application (app) named VTQuestAR that provides assistance to the campus visitors by using the Augmented Reality (AR) technology. The Machine Learning (ML) technology is used to recognize a sample of 31 campus buildings in real-time. The VTQuestAR app enables the user to have a visual interactive experience with those 31 campus buildings by superimposing building information on top of the building picture shown through the camera. The app also enables the user to get directions from the current location or a building to another building displayed on a 2D map as well as an AR map. The user can perform complex searches on 122 campus buildings by building name, description, abbreviation, category, address, and year built. The app enables the user to take multimedia notes during a campus visit. Our exploratory development research illustrates the feasibility of using AR and ML in providing much more effective assistance to visitors of any organization. / Master of Science / The main campus of Virginia Polytechnic Institute and State University (Virginia Tech) has more than 120 buildings. The campus visitors face problems recognizing a building, finding a building, obtaining directions from one building to another, and getting information about a building. The exploratory development research described herein resulted in an iPhone / iPad software application named VTQuestAR that provides assistance to the campus visitors by using the Augmented Reality (AR) and Machine Learning (ML) technologies. Our research illustrates the feasibility of using AR and ML in providing much more effective assistance to visitors of any organization.

Även om de flesta av oss i dagsläget vet att våra mobila enheter kan tappa sina nätverksanslutningar lite då och då har det mer eller mindre blivit en självklarhet att i alla lägen ändå kunna använda våra favoritapplikationer som vanligt. Denna rapport syftade till att hitta en lösning på problemet med nätverksberoende applikationer genom att implementera ett offline-läge som kringgick detta beroende i GreatRate, en iOS-applikation för kundundersökningar i butik. Med hjälp av en databas för att mellanlagra data under tillfällen då en duglig nätverksanslutning inte fanns tillgänglig samt synkronisering av nämnda data när anslutningen åter blivit funktionell förväntades problemet kringgås. Resultatet blev som väntat en applikation som gav användaren en förhöjd användarupplevelse helt oberoende av nätverksanslutningens status. Några av slutsatserna som drogs var dock att flera olika lösningar finns för detta problem och att problemet högst troligt har olika utseenden för olika applikationer.

There exists an increasing demand for computing power and performance in real-time embedded systems, as new, more complex customer requirements and function-alities are appearing every day. In order to support these requirements and func-tionalities without breaking the power consumption wall, many embedded systems areswitching from traditional single-core hardware architectures to multi-core architec-tures. Multi-core architectures allow for parallel execution of tasks on the multiplecores. This introduces many benets from the perspective of achievable performance,but in turn introduces major issues when it comes to the timing predictability ofthe real-time embedded system applications deployed on them. The problem arisesfrom unpredictable and potentially unbounded inter-core interferences, which occuras a result of contention for the shared resources, such as the shared system busor shared system memory. This thesis studies the possible application of constraintprogramming as a resource optimization technique for the purpose of creating oineschedules for tasks in real-time embedded system applications executing on a dual-core architecture. The main focus is placed on tightening inter-core data-propagationinterferences, which can result in lower over-all data-propagation delays. A proto-type of an optimization engine, employing constraint programming techniques on ap-plications comprised of tasks structured according to the Phased Execution Model isdeveloped. The prototype is evaluated through several experiments on a large numberof industry inspired intellectual-property free benchmarks. Alongside the experimentsa case study is conducted on an example engine-control application and the resultingschedule is compared to a schedule generated by the Rubus-ICE industrial tool suite.The obtained results show that the proposed method is applicable to a potentially widerange of abstract systems with dierent requirements. The limitations of the methodare also discussed and potential future work is debated based on these results. / <p>Presentation was held over Zoom, due to the COVID-19 situation.</p>

A Bacia de São Paulo abriga a maior parte da principal região metropolitana do Brasil. Esta região concentra uma grande quantidade de obras subterrâneas, principalmente para fins de transporte público, executada nas rochas sedimentares que constituem a bacia. A Bacia de São Paulo é caracterizada pela heterogeneidade litológica, herança da tectônica do tipo rift que condicionou a sedimentação de depósitos de leques aluviais associados à planície aluvial e sedimentos lacustres. Essa heterogeneidade traz importantes implicações no planejamento e execução de obras subterrâneas, mas sua caracterização vem sendo progressivamente dificultada com o avanço da ocupação urbana, o que limita o acesso às exposições de rochas. Por outro lado, em consequência do grande número de obras, encontra-se disponível um volume considerável de dados geotécnicos, cuja interpretação à luz dos conhecimentos geológicos é hoje a principal forma de se avançar no conhecimento geológico-geotécnico da bacia. Neste trabalho buscou-se correlacionar dados geológicos e geotécnicos na Bacia de São Paulo. Para tanto foram empregados dados de sondagens e ensaios provenientes da Linha 17 - Ouro do Metrô de São Paulo, situada ao longo das avenidas Jornalista Roberto Marinho, Washington Luís e das Nações Unidas. Estes dados encontram-se disponíveis no acervo da Companhia do Metropolitano de São Paulo - Metrô. Foram realizadas análises tátil-visual das amostras para determinação das características e composição do material. Essas análises permitiram a definição de unidades geológico-geotécnicas, determinar a sua distribuição a partir de seções geológico-geotécnicas e as consequentes implicações para obras subterrâneas e de fundações. As seções geológico-geotécnicas confeccionadas mostraram que a Formação São Paulo predomina acima da cota 740m ao longo da Av. Washington Luís, a Formação Resende ocorre nas Avenidas Jornalista Roberto Marinho e Washington Luís e as rochas do embasamento predominam na região próxima à Marginal Pinheiros. Foram também identificadas falhas normais configurando um horst na Av. Jornalista Roberto Marinho. / The São Paulo Basin nestles most of the main metropolitan region of Brazil. Most of the underground works for public transport in the São Paulo city were performed in rocks of this basin. The basin presents a lithologic and structural heterogeneity, an inheritance of the rifting processes responsible for its development that conditioned the deposition of sediments in alluvial fans, floodplains and lakes. Understanding these heterogeneities is essential for better planning and execution of undergound works, but the study of the basin is becoming increasingly difficult as a consequence of urban occupation. The large number of undergound works, however, make available a considerable amount of geotechnical data, whose interpretation is the main way to advance in the knowledge of the geological and geotechnical characteristics of the São Paulo Basin. This study aimed to correlate geological and geotechnical data in the São Paulo Basin. We employed data from cores obtained along the Line 17 - Ouro, of the São Paulo Metro, located along the avenues Jornalista Roberto Marinho, Washington Luís and Nações Unidas. These data are available in the collection of the Metropolitan Company of São Paulo - Metro. Samples from cores were submitted to visual-tactile analysis in order to determine their characteristics and composition. The analysis allowed the definition of gelogical and geotechnical units, their distributions and implications for underground works and foundations. The geological and geotechnical sections showed that the São Paulo Formation predominates above 740m along the Washington Luís Avenue, the Resende Formation occurs in the avenues Jornalista Roberto Marinho and Washington Luís and the basement rocks predominate in the region near the Marginal Pinheiros. We also identified normal faults configuring a horst in the Jornalista Roberto Marinho Avenue.

Die automatische Informationsextraktion (IE) aus unstrukturierten Texten ermöglicht völlig neue Wege, auf relevante Informationen zuzugreifen und deren Inhalte zu analysieren, die weit über bisherige Verfahren zur Stichwort-basierten Dokumentsuche hinausgehen. Die Entwicklung von Programmen zur Extraktion von maschinenlesbaren Daten aus Texten erfordert jedoch nach wie vor die Entwicklung von domänenspezifischen Extraktionsprogrammen. Insbesondere im Bereich der Enterprise Search (der Informationssuche im Unternehmensumfeld), in dem eine große Menge von heterogenen Dokumenttypen existiert, ist es oft notwendig ad-hoc Programm-module zur Extraktion von geschäftsrelevanten Entitäten zu entwickeln, die mit generischen Modulen in monolithischen IE-Systemen kombiniert werden. Dieser Umstand ist insbesondere kritisch, da potentiell für jeden einzelnen Anwendungsfall ein von Grund auf neues IE-System entwickelt werden muss. Die vorliegende Dissertation untersucht die effiziente Entwicklung und Ausführung von IE-Systemen im Kontext der Enterprise Search und effektive Methoden zur Ausnutzung bekannter strukturierter Daten im Unternehmenskontext für die Extraktion und Identifikation von geschäftsrelevanten Entitäten in Doku-menten. Grundlage der Arbeit ist eine neuartige Plattform zur Komposition von IE-Systemen auf Basis der Beschreibung des Datenflusses zwischen generischen und anwendungsspezifischen IE-Modulen. Die Plattform unterstützt insbesondere die Entwicklung und Wiederverwendung von generischen IE-Modulen und zeichnet sich durch eine höhere Flexibilität und Ausdrucksmächtigkeit im Vergleich zu vorherigen Methoden aus. Ein in der Dissertation entwickeltes Verfahren zur Dokumentverarbeitung interpretiert den Daten-austausch zwischen IE-Modulen als Datenströme und ermöglicht damit eine weitgehende Parallelisierung von einzelnen Modulen. Die autonome Ausführung der Module führt zu einer wesentlichen Beschleu-nigung der Verarbeitung von Einzeldokumenten und verbesserten Antwortzeiten, z. B. für Extraktions-dienste. Bisherige Ansätze untersuchen lediglich die Steigerung des durchschnittlichen Dokumenten-durchsatzes durch verteilte Ausführung von Instanzen eines IE-Systems. Die Informationsextraktion im Kontext der Enterprise Search unterscheidet sich z. B. von der Extraktion aus dem World Wide Web dadurch, dass in der Regel strukturierte Referenzdaten z. B. in Form von Unternehmensdatenbanken oder Terminologien zur Verfügung stehen, die oft auch die Beziehungen von Entitäten beschreiben. Entitäten im Unternehmensumfeld haben weiterhin bestimmte Charakteristiken: Eine Klasse von relevanten Entitäten folgt bestimmten Bildungsvorschriften, die nicht immer bekannt sind, auf die aber mit Hilfe von bekannten Beispielentitäten geschlossen werden kann, so dass unbekannte Entitäten extrahiert werden können. Die Bezeichner der anderen Klasse von Entitäten haben eher umschreibenden Charakter. Die korrespondierenden Umschreibungen in Texten können variieren, wodurch eine Identifikation derartiger Entitäten oft erschwert wird. Zur effizienteren Entwicklung von IE-Systemen wird in der Dissertation ein Verfahren untersucht, das alleine anhand von Beispielentitäten effektive Reguläre Ausdrücke zur Extraktion von unbekannten Entitäten erlernt und damit den manuellen Aufwand in derartigen Anwendungsfällen minimiert. Verschiedene Generalisierungs- und Spezialisierungsheuristiken erkennen Muster auf verschiedenen Abstraktionsebenen und schaffen dadurch einen Ausgleich zwischen Genauigkeit und Vollständigkeit bei der Extraktion. Bekannte Regellernverfahren im Bereich der Informationsextraktion unterstützen die beschriebenen Problemstellungen nicht, sondern benötigen einen (annotierten) Dokumentenkorpus. Eine Methode zur Identifikation von Entitäten, die durch Graph-strukturierte Referenzdaten vordefiniert sind, wird als dritter Schwerpunkt untersucht. Es werden Verfahren konzipiert, welche über einen exakten Zeichenkettenvergleich zwischen Text und Referenzdatensatz hinausgehen und Teilübereinstimmungen und Beziehungen zwischen Entitäten zur Identifikation und Disambiguierung heranziehen. Das in der Arbeit vorgestellte Verfahren ist bisherigen Ansätzen hinsichtlich der Genauigkeit und Vollständigkeit bei der Identifikation überlegen. / The automatic information extraction (IE) from unstructured texts enables new ways to access relevant information and analyze text contents, which goes beyond existing technologies for keyword-based search in document collections. However, the development of systems for extracting machine-readable data from text still requires the implementation of domain-specific extraction programs. In particular in the field of enterprise search (the retrieval of information in the enterprise settings), in which a large amount of heterogeneous document types exists, it is often necessary to develop ad-hoc program-modules and to combine them with generic program components to extract by business relevant entities. This is particularly critical, as potentially for each individual application a new IE system must be developed from scratch. In this work we examine efficient methods to develop and execute IE systems in the context of enterprise search and effective algorithms to exploit pre-existing structured data in the business context for the extraction and identification of business entities in documents. The basis of this work is a novel platform for composition of IE systems through the description of the data flow between generic and application-specific IE modules. The platform supports in particular the development and reuse of generic IE modules and is characterized by a higher flexibility as compared to previous methods. A technique developed in this work interprets the document processing as data stream between IE modules and thus enables an extensive parallelization of individual modules. The autonomous execution of each module allows for a significant runtime improvement for individual documents and thus improves response times, e.g. for extraction services. Previous parallelization approaches focused only on an improved throughput for large document collections, e.g., by leveraging distributed instances of an IE system. Information extraction in the context of enterprise search differs for instance from the extraction from the World Wide Web by the fact that usually a variety of structured reference data (corporate databases or terminologies) is available, which often describes the relationships among entities. Furthermore, entity names in a business environment usually follow special characteristics: On the one hand relevant entities such as product identifiers follow certain patterns that are not always known beforehand, but can be inferred using known sample entities, so that unknown entities can be extracted. On the other hand many designators have a more descriptive character (concatenation of descriptive words). The respective references in texts might differ due to the diversity of potential descriptions, often making the identification of such entities difficult. To address IE applications in the presence of available structured data, we study in this work the inference of effective regular expressions from given sample entities. Various generalization and specialization heuristics are used to identify patterns at different syntactic abstraction levels and thus generate regular expressions which promise both high recall and precision. Compared to previous rule learning techniques in the field of information extraction, our technique does not require any annotated document corpus. A method for the identification of entities that are predefined by graph structured reference data is examined as a third contribution. An algorithm is presented which goes beyond an exact string comparison between text and reference data set. It allows for an effective identification and disambiguation of potentially discovered entities by exploitation of approximate matching strategies. The method leverages further relationships among entities for identification and disambiguation. The method presented in this work is superior to previous approaches with regard to precision and recall.

A Bacia de São Paulo abriga a maior parte da principal região metropolitana do Brasil. Esta região concentra uma grande quantidade de obras subterrâneas, principalmente para fins de transporte público, executada nas rochas sedimentares que constituem a bacia. A Bacia de São Paulo é caracterizada pela heterogeneidade litológica, herança da tectônica do tipo rift que condicionou a sedimentação de depósitos de leques aluviais associados à planície aluvial e sedimentos lacustres. Essa heterogeneidade traz importantes implicações no planejamento e execução de obras subterrâneas, mas sua caracterização vem sendo progressivamente dificultada com o avanço da ocupação urbana, o que limita o acesso às exposições de rochas. Por outro lado, em consequência do grande número de obras, encontra-se disponível um volume considerável de dados geotécnicos, cuja interpretação à luz dos conhecimentos geológicos é hoje a principal forma de se avançar no conhecimento geológico-geotécnico da bacia. Neste trabalho buscou-se correlacionar dados geológicos e geotécnicos na Bacia de São Paulo. Para tanto foram empregados dados de sondagens e ensaios provenientes da Linha 17 - Ouro do Metrô de São Paulo, situada ao longo das avenidas Jornalista Roberto Marinho, Washington Luís e das Nações Unidas. Estes dados encontram-se disponíveis no acervo da Companhia do Metropolitano de São Paulo - Metrô. Foram realizadas análises tátil-visual das amostras para determinação das características e composição do material. Essas análises permitiram a definição de unidades geológico-geotécnicas, determinar a sua distribuição a partir de seções geológico-geotécnicas e as consequentes implicações para obras subterrâneas e de fundações. As seções geológico-geotécnicas confeccionadas mostraram que a Formação São Paulo predomina acima da cota 740m ao longo da Av. Washington Luís, a Formação Resende ocorre nas Avenidas Jornalista Roberto Marinho e Washington Luís e as rochas do embasamento predominam na região próxima à Marginal Pinheiros. Foram também identificadas falhas normais configurando um horst na Av. Jornalista Roberto Marinho. / The São Paulo Basin nestles most of the main metropolitan region of Brazil. Most of the underground works for public transport in the São Paulo city were performed in rocks of this basin. The basin presents a lithologic and structural heterogeneity, an inheritance of the rifting processes responsible for its development that conditioned the deposition of sediments in alluvial fans, floodplains and lakes. Understanding these heterogeneities is essential for better planning and execution of undergound works, but the study of the basin is becoming increasingly difficult as a consequence of urban occupation. The large number of undergound works, however, make available a considerable amount of geotechnical data, whose interpretation is the main way to advance in the knowledge of the geological and geotechnical characteristics of the São Paulo Basin. This study aimed to correlate geological and geotechnical data in the São Paulo Basin. We employed data from cores obtained along the Line 17 - Ouro, of the São Paulo Metro, located along the avenues Jornalista Roberto Marinho, Washington Luís and Nações Unidas. These data are available in the collection of the Metropolitan Company of São Paulo - Metro. Samples from cores were submitted to visual-tactile analysis in order to determine their characteristics and composition. The analysis allowed the definition of gelogical and geotechnical units, their distributions and implications for underground works and foundations. The geological and geotechnical sections showed that the São Paulo Formation predominates above 740m along the Washington Luís Avenue, the Resende Formation occurs in the avenues Jornalista Roberto Marinho and Washington Luís and the basement rocks predominate in the region near the Marginal Pinheiros. We also identified normal faults configuring a horst in the Jornalista Roberto Marinho Avenue.