000 Allgemeines, Informatik, Informationswissenschaft
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Das Praxisprojekt ist eine Fortführung des bereits umgesetzten Informatikprojektes.
Daher wird in den nachfolgenden Kapiteln ausschließlich auf die maßgeblichen Änderungen und Erweiterungen Bezug genommen.
Der Schwerpunkt ist die Konzeption und Umsetzung eines relationalen Datenbanksystems zur Erfassung, Verwaltung und Bearbeitung von leichtathletischen Mehrkampfwettbewerben.
Die Bedienung erfolgt über eine Weboberfläche, die Mithilfe des PHP-Frameworks Laravel an das Datenbanksystem MariaDB angekoppelt ist.
Die wichtigsten Themen im Projekt sind:
• Die Umsetzung und Koordinierung des Mehrbenutzerbetriebs
• Die Umsetzung und Kontrolle der Rechteverwaltung der Benutzer
• Die Möglichkeit zur Erfassung eigener Wettkämpfe bestehend aus beliebig vielen Disziplinen inklusive individueller Formeln zur Punkteberechnung
Die ersten beiden Punkte werden in dieser Ausarbeitung auf einer allgemeinen Ebene behandelt.
Machbarkeitsanalyse über den Aufbau eines Enterprise Data Warehouse auf Basis von Apache Hadoop
(2016)
Die vorliegende Masterthesis liefert eine Einführung in die Themen Data Warehouse, Big Data und Apache Hadoop. Sie präsentiert grundlegende Data-Warehouse-Kon-zepte und überprüft, inwieweit diese mit dem Apache Hadoop Software Framework zu realisieren sind. Hierbei wird sowohl eine technische Überprüfung vorgenommen als auch verschiedene Szenarien veranschaulicht, wie Hadoop inhaltlich sinnvoll in bestehende Systeme integriert werden kann. Inhaltlich wird über das Thema Big Data an die Notwendigkeit einer solchen Überprüfung herangeführt.
Intelligent use of energy is one of the keys to success for an energy revolution. To meet this challenge, smart meters are suitable tools because INTELLIGENT use of energy means not only to use efficiency technology, but also to determine load shifting potentials and use them accordingly. Especially farms with high power consumption are becoming increasingly concerned about reducing energy costs due to rising energy prices and need a systematic analysis of their operational energy flow. To find solutions for farms, the NaRoTec e.V., the TH Köln, and the Machinery Ring Höxter-Warburg have joined forces with partners and launched the project "Intelligent Energy in Agriculture", which is funded by the state of NRW. The aim of the project is to be able to give individual advice recommendations for energy optimization of agricultural holdings. This will be achieved inter alia through an operational energy audit and current measurements in different operating ranges. To achieve this, smart meters were installed in selected energy-intensive dairy and pig farms. As part of the project, the installed smart meter information about the consumption of various plants and their components were analyzed, regularities and adaptability in loading history identified, and the energy efficiency of the equipment and systems used verified (especially pumps, ventilators, feeding systems). Then recommendations were formulated to shift electricity-intensive processes to times with low electricity costs and high intrinsic power production. The resulting findings will be used as the basis for intelligent energy management in the further course of the project. Overall, efficiency streamlining measures in the field of ventilation and lighting systems, flexible dry feeding systems by decoupling power purchase and consumption, as well as energy savings and related CO2 savings were determined.
Intelligent use of energy is one of the keys to success for an energy revolution. To meet this challenge, smart meters are suitable tools because INTELLIGENT use of energy means not only to use efficiency technology, but also to determine load shifting potentials and use them accordingly. Especially farms with high power consumption are becoming increasingly concerned about reducing energy costs due to rising energy prices and need a systematic analysis of their operational energy flow. To find solutions for farms, the NaRoTec e.V., the TH Köln, and the Machinery Ring Höxter-Warburg have joined forces with partners and launched the project "Intelligent Energy in Agriculture", which is funded by the state of NRW in Germany. The aim of the project is to be able to give individual advice recommendations for energy optimization of agricultural holdings. This will be achieved inter alia through an operational energy audit and current measurements in different operating ranges. To achieve this, smart meters were installed in selected energy-intensive dairy and pig farms.
As part of the project, the installed smart meter information of one of the dairy Farms is used to optimize the energy consumption of the farm and increase the degree of self-sufficiency. A good way to achieve this is by taking a closer look at the cooling process of the produced milk since it is one of the most energy consuming processes on a dairy farm. In addition an installation of an ice cooling system instead of a direct cooling system enables the possibility to store self-produced energy in the form of ice and use it later on when it is needed to cool the milk. This flattens the usual energy peaks throughout the day and increases the degree of self-sufficiency. To ensure a sufficient amount of self-produced energy with solar power plants of various sizes were designed. The different sizes of the power plants are defined by the use of the gathered smart meter data is used to cover different electric loads in addition to the ice water cooling system. Afterwards the different simulated models are compared to find the best balance between energy production, investment cost and a high degree of self-sufficiency. First results show that using an ice cooling system in combination with a solar power plant improvement the degree of self-sufficiency by up to 7.8 %.
Das Ziel der vorliegenden Bachelorarbeit war es, das In-Memory-Konzept innerhalb einer Oracle Datenbank auf neue Mechanismen, Funktionen und Methoden zu untersuchen. Dazu wurde eine Datenbank erstellt und mit Beispieldaten bestückt. Diese Beispieldaten sind Aktienwerte der DAX-30 Unternehmen, welche durch eine Reihe von Indikatoren aus der technischen Analyse eine komplexe Möglichkeit der Analyse bieten. Die Ergebnisse bestätigen, dass das In-Memory-Konzept neben dem bekannten Spaltenformat eine Reihe von Techniken und Funktionen bietet, welche sich positiv bei der Verarbeitung von Daten durch Data Query Language-Befehle auswirken. Es kommen auch Nachteile, wie der flüchtige Speicher zum Vorschein, dennoch überwiegen die Vorteile stark. Nach einer Reihe von Tests wird deutlich, dass Objekte, die in den In-Memory-Column-Store geladen werden, nur 30 % der Zeit benötigen, um gelesen zu werden. Dies ist für die Verarbeitung von großen und komplexen Daten eine deutliche Verbesserung. Die Bachelorarbeit richtet sich an Studierende der Fachbereiche Informatik und BWL sowie an Interessierte im Bereich Datenbanken.
Der digitale Schwarzmarkt mit gestohlenen Daten floriert. Alleine im Jahr 2015 wurden über eine halbe Milliarde Datensätze aus Datenbanksystemen entwendet. Viele Unternehmen bemerken den Sicherheitsvorfall selbst nicht oder geben aus Angst vor einem Imageschaden den Vorfall nicht bekannt. Sind die Datenbestände nicht durch effektive Sicherheitsmechanismen vor Datendiebstahl geschützt, können Cyberkriminelle leicht aus den gestohlenen Daten Kapital schlagen. Die Softwarehersteller von Datenbanksystemen bieten für ihre Produkte unterschiedliche Schutzvorkehrungen an. Ziel dieser Ausarbeitung ist es, die Bedrohungen und die Sicherheitsrisiken von Datenbanksystemen aufzuzeigen und daraus die Aspekte der Datenbanksicherheit abzuleiten. Die ausgearbeiteten Sicherheitsaspekte bilden die Grundlage für den Vergleich der Datenbanksicherheit von relationalen Datenbanklösungen. Die anschließende Bewertung dient dem Nachweis und der Überprüfbarkeit der Datenbanksicherheit relationaler Datenbanksysteme.
Due to the present developments of the Internet and its technical components, the skills of the web experts have to be more and more complex and specific. The Internet experts in the creative field are located distributedly around the whole world. As a result, many companies have problems to find the needed experts on site and are dependent on creative cooperations and virtual teams with the help of technical tools. The virtual working place is an important issue, particularly in modern times and the market offers more and more cooperation systems for exactly this purpose: Creative cooperation in distributed working situations. This thesis examines the approaches of creative cooperation and cooperation technologies with an analysis about existing cooperation systems with a creative context. It spans a wide range of tools. On the one hand, there are approaches which offer only straightforward solutions for single design tasks. On the other hand, there are providers which recognised the great need of creative cooperation systems and working at full speed to extend their systems. The examined areas of this work lead to a design process oriented approach with flexible frames and enough space for the creative development of every single user. The cooperation in a creative context stays in the foreground and is the base for future approaches for the web design sector.
The topic for the thesis originated from the CAP4ACCESS project run by the European Commission and its partners, which deals towards the sensiti-zation of people and development of tools for awareness about people with movement disabilities. The explorative analysis is never ending and to explore and find interest-ing patterns and the results is a tedious task. Therefore, a scientific approach was very important. To start with, familiarizing the domain and the data sources were done. Thereafter, selection of methodology for data analysis was done which resulted in the use of CRISP-DM methodology. The data sources are the source of blood to the analysis methodology, and as there were two sources of data that is MICROM and OSM Wheelchair History(OWH), it was important to integrate them together to extract relevant datasets. Therefore a functional and technically impure data warehouse was created, from which the datasets are extracted and analysed.The next task was to select appropriate tools for analysis. This task was very important as the data set although was not big data but con-tained a large number of rows. After careful analysis, Apache spark and its machine learning library were utilized for building and testing supervised models. DataFrame API for Python, Pandas, the machine learning library Sci-kit learn provided unsupervised algorithms for analysis, the association rule analysis was performed using WEKA. Tableau[21] and Matplotlib[24] provide attractive visualizations for representation and analysis.
An empirical evaluation of using the Swift language as the underlying technology of RESTful APIs
(2016)
The purpose of the current thesis is to determine the appropriateness of using the Swift language as the underlying technology for the development of RESTful APIs in a Linux environment. The current paper describes the process of designing, implementing and testing individual RESTful API components based on Node.js, PHP, Python and Swift and seeks to determine whether Swift is a viable alternative.
The thesis begins by defining a methodology for implementing and testing individual RESTful API components based on Node.js, PHP, Python and Swift. It then proceeds to detail the implementation and testing processes, following with an analytic discussion regarding the advantages and drawbacks of using the Swift language as the underlying technology for RESTful APIs and server-side Linux-based applications in general.
Based on the implementation process and on the results of the previously mentioned evaluation phase, it can be stated that the Swift language is not yet ready to be used in a production environment. However, its rapid evolution and potential for surpassing its competitors in the foreseeable future make it an ideal candidate for implementing RESTful APIs to be used in development environments.