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Conception of a Vertical Farm for the Maun Science Park in Botswana
Get PDFGlobal agriculture will face major challenges in the future. In addition to the increasing demand for food due to constant population growth, the consequences of climate change will make it even more difficult to operate agriculture and supply people with food. In addition to further productivity increases in traditional agriculture, new concepts for sustainable and scalable food production are needed. Vertical farming offers a promising approach.
The aim of this project is to demonstrate how vertical farming can be used to ensure sustainable food production and how this concept can be applied in the pioneering Maun Science Park project in Botswana. In doing so, the Maun Science Park will address future challenges such as demographics, governance and climate change and become a best practice model for Botswana, the whole of Africa and the world. The country of Botswana grew to become one of the most prosperous countries in Africa in recent decades due to strong economic growth from mining. However, the population faces great challenges in the future; in addition to great social inequality, climate change threatens the country's overall supply.
With the help of a literature review and qualitative and quantitative interviews with stakeholders from Maun (Botswana), the potentials and challenges for vertical farming in Botswana could be identified and future measures for a possible realization could be derived. Basically, some challenges in Botswana are addressed by the technology, for example, Vertical Farming offers high food security through year-round production of food through the closed ecosystem and creates independence from current and future climatic conditions, poor conditions for traditional agriculture (e.g. infertile soils) and foreign imports. However, the main structural problems of agriculture in Botswana, such as the lack of infrastructure, know-how and policy support, are not addressed
Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates
No full textWith the high resolution of modern sensors such as multilayer LiDARs, estimating the 3D shape in an extended object tracking procedure is possible. In recent years, 3D shapes have been estimated in spherical coordinates using Gaussian processes, spherical double Fourier series or spherical harmonics. However, observations have shown that in many scenarios only a few measurements are obtained from top or bottom surfaces, leading to error-prone estimates in spherical coordinates. Therefore, in this paper we propose to estimate the shape in cylindrical coordinates instead, applying harmonic functions. Specifically, we derive an expansion for 3D shapes in cylindrical coordinates by solving a boundary value problem for the Laplace equation. This shape representation is then integrated in a plain greedy association model and compared to shape estimation procedures in spherical coordinates. Since the shape representation is only integrated in a basic estimator, the results are preliminary and a detailed discussion for future work is presented at the end of the paper
Improving the tribological properties of Stainless Steels by low-temperature surface hardening
No full textWirtschaftsethik und deren praktische Anwendung durch die ISO 26000
No full textWirtschaftsethik ist aktueller denn je. Woher kommt dieser Begriff und welche Auswirkungen hat die Wirtschaftsethik auf das wirtschaftliche Handeln
BiLeSA: Mathematik mit digitalen Bildern sichtbar machen
Get PDFDie Frage „Wozu braucht man das?“ vonseiten der Studierenden oder Aussagen wie „Das habe ich im Beruf später nie mehr benötigt.“ von ehemaligen Studierenden ist den meisten Mathematikdozierenden sehr vertraut. Im Projekt BiLeSA wird dem Wunsch nach Integration von Praxisnähe im Mathematikunterricht mithilfe einer Smartphone-App, welche ausgewählte Themen in der Mathematik anhand von digitalen Bildern sichtbar macht, umgesetzt. Bei den ausgewählten Themen handelt es sich um (affin) lineare Abbildungen, Ableitungen in höheren Raumdimensionen und Potenzen von Komplexen Zahlen. Die Konzeptionierung des Lernobjekts erfolgte mit dem Design Based Research (DBR) Ansatz, welches im Basisprojekt des IBH-Labs „Seamless Learning“ konzipiert und entwickelt wurde
Deep Learning-based EEG Detection of Mental Alertness States from Drivers under Ethical Aspects
No full textOne of the most critical factors for a successful road trip is a high degree of alertness while driving. Even a split second of inattention or sleepiness in a crucial moment, will make the difference between life and death. Several prestigious car manufacturers are currently pursuing the aim of automated drowsiness identification to resolve this problem. The path between neuro-scientific research in connection with artificial intelligence and the preservation of the dignity of human individual’s and its inviolability, is very narrow. The key contribution of this work is a system of data analysis for EEGs during a driving session, which draws on previous studies analyzing heart rate (ECG), brain waves (EEG), and eye function (EOG). The gathered data is hereby treated as sensitive as possible, taking ethical regulations into consideration. Obtaining evaluable signs of evolving exhaustion includes techniques that obtain sleeping stage frequencies, problematic are hereby the correlated interference’s in the signal. This research focuses on a processing chain for EEG band splitting that involves band-pass filtering, principal component analysis (PCA), independent component analysis (ICA) with automatic artefact severance, and fast fourier transformation (FFT). The classification is based on a step-by-step adaptive deep learning analysis that detects theta rhythms as a drowsiness predictor in the pre-processed data. It was possible to obtain an offline detection rate of 89% and an online detection rate of 73%. The method is linked to the simulated driving scenario for which it was developed. This leaves space for more optimization on laboratory methods and data collection during wakefulness-dependent operations
Citizen-centered health platform concept for EU cross-border regions
Get PDFThe citizen-centered health platform project is intended to provide a platform that can be used in EU cross-border regions, where social and economic exchange occurs across national borders. The overriding challenges are: (a) social: improving citizen-centered health and care provision; (b) technical: providing a digital platform for networking citizens, service providers, and municipal actors; (c) economic: developing long-term successful (sustainable) business models/value chains. The platform should strengthen and expand existing networks and establish new regional networks. Each network addresses particular challenges and apply them in a region-specific manner. Here, the national boundary conditions and the interregional needs play an essential role. These objectives require sufficient participation of civil society representatives. Furthermore, the platform will establish an overarching, sustainable, and knowledge-based network of health experts. The platform is to be jointly developed and implemented in the regions and follow an open-access approach. Therefore, synergies will be shared more quickly, strengthening competencies and competitiveness. In addition to practice partners, scientific and municipal institutions and SMEs are involved. The actors thus contribute to scientific performance, innovative strength, and resilience
Main requirements of end-to-end deep learning models for biomedical time series classification in healthcare environments
No full textThe use of deep learning models with medical data is becoming more widespread. However, although numerous models have shown high accuracy in medical-related tasks, such as medical image recognition (e.g. radiographs), there are still many problems with seeing these models operating in a real healthcare environment. This article presents a series of basic requirements that must be taken into account when developing deep learning models for biomedical time series classification tasks, with the aim of facilitating the subsequent production of the models in healthcare. These requirements range from the correct collection of data, to the existing techniques for a correct explanation of the results obtained by the models. This is due to the fact that one of the main reasons why the use of deep learning models is not more widespread in healthcare settings is their lack of clarity when it comes to explaining decision making
Advancing towards a Business Model Innovation process for start-ups
Get PDFBecause process and product innovations are usually no longer sufficient to establish a company in the market or to generate a competitive advantage, Business Model Innovation is considered a powerful tool, especially for start-ups for which innovation is at the core of their business. Due to the complexity of this process, frameworks should help entrepreneurs with executing Business Model Innovation. However, theory and practice diverge. The aim of this paper is to identify the needs of a start-up regarding Business Model Innovation frameworks, underlining the importance of Business Model Innovation for start-ups as well as the relevance of a supporting framework. The research results aim to contribute to an ideal process for Business Model Innovation when applied to start-ups
Generalisierung und Weiterentwicklung des digitalen Betonfertigteil-Trackings
Get PDFIn der vorliegenden Arbeit wird eine Vorlage für ein generalisiertes Betonfertigteil-Tracking für die Bauindustrie geschaffen. In dem ersten der vier Kapitel wird zuerst der Prozess des Fertigteil-Trackings dargestellt. Dieser wird anhand von Experteninterviews modifiziert und es wird ein Standardprozess als Vorlage präsentiert. Dieser Standardprozess soll für projektspezifische Wünsche modular erweiterbar sein. Hierfür werden Vorteile, Probleme und Verbesserungswünsche der Anwender eingearbeitet. Um den Prozess auf die gesamte Baubranche erweitern zu können, werden die softwaretechnischen Voraussetzungen für eine Standardschnittstelle der Fertigteil-Werke analysiert. Um Probleme bei der Implementierung und Durchführung des Trackings zu verhindern, werden die Partikularinteressen aller Beteiligten analysiert. Die Ergebnisse werden aus Experteninterviews generiert sowie durch Literaturrecherche und die eigenen Erfahrungen bei der Implementierung des Fertigteil-Trackings auf der Baustelle Telekom Areal der Ed. Züblin AG ergänzt.This Master thesis lays the foundations in the construction industry for the implementation of a generalized precast tracking. Chapter one describes the process of precast tracking. The process is modified based on expert interviews and a standardized process is specified as a process template. This process can be adjusted modularly according to project-specific requirements. For this pur-pose, advantages, issues, and improvement requests of the users are incorporated. To extend the process to the entire construction industry, it is necessary to analyze the software-technical re-quirements for a standardized interface of the precast plants. To prevent problems during the im-plementation, the interests of all parties involved are examined. These results are taken from ex-pert interviews as well as from a thorough literature research and individual experience through the implementation process of precast tracking on the construction site Telekom Areal by the Ed. Züblin AG