Hochschule Konstanz University of Applied Sciences

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    2319 research outputs found

    Ignorantia doctorum

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    Since the turn of the millennium, many writing centers have been established at universities in the German-speaking world, in order to support students in academic writing. This essay argues for offering subject-anchored directive guidance and using scientific texts as a basis for model learning. It states that the rhetorical tradition is hardly taken into account in the writing centers. Five arguments for this ignorance are discussed and, if possible, dispelled: the antiquity argument, which considers rhetoric outdated; the orality argument, which understands rhetoric as irrelevant to writing; the moral argument, which condemns rhetoric as a tool for demagogues; the positivist argument, which criticizes rhetoric as unempirical; and the didactic argument, which rejects rhetoric as a rigid doctrine. The discussion shows, however, that the rhetorical tradition, with its normative power and centuries of teaching practice, is a treasure trove of writing didactics that holds many resources, such as well-founded assessment criteria for the quality, appropriateness, and usefulness of texts

    Thermal optimization of a laser scanner

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    Dissipation of heat can be a major challenge when applying sensor systems outdoors under varying environmental conditions. Typically, complex software and knowledge is needed to optimize thermal management. In this paper it is shown how the thermal optimization of a LiDAR (light detection and ranging) sensor can be performed efficiently. This approach uses standard CAD (computer aided design) software, which is readily available, and saves time and cost as the thermal design can be optimized before experimental realisation. A four-step process was developed and realized: (i) Measurement of the thermal energy distribution of the current sensor design; (ii) Simulation of the time-dependant thermal behaviour using standard CAD software; (iii) Simulation of a thermally optimized design. This was compared quantitatively with the original design and was also used for verification of sufficient increase in heat dissipation; (iv) Experimental realisation and verification of the optimized design. It could be shown that the optimized prototype shows significantly improved thermal behaviour in accordance with the predictions from the simulations. The new LiDAR sensor shows lower heat generation and optimized dissipation of thermal energy which proofs the applicability of the approach to complex sensors

    Serieller Ausbau des Bestands – Eine Analyse des Energiesprong-Prinzips und der Gebäudeaufstockung in Holzbauweise zur Identifikation gemeinsamer Potentiale

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    Um gegen den Klimawandel vorzugehen, ist im Gebäudebestand eine Reduktion der Treibhausemmissionen nötig. Dafür müssen politische Entscheidungsträger, Wohnungsunternehmen und Baufirmen gemeinsam arbeiten, um CO2 Neutralität zu erreichen. Die energetische Sanierung der bedürftigen Gebäude ist mit den konventionellen Methoden bis zum Jahr 2050 nicht zu erreichen. Das Energiesprong Prinzip bietet einen Lösungsansatz, welcher finanziell interessant ist und mit weniger Personalaufwand in großer Menge umgesetzt werden kann. Es wird die Erkenntnis gewonnen, dass die bisher verwendeten konstruktiven Systeme jedoch noch Optimierungsbedarf haben, um den finanziellen Rahmen des Prinzips einzuhalten und den Massenmarkt bedienen zu können. Die Untersuchungen dieser Arbeit ergeben, dass eine im Prozess eingebundene Gebäudeaufstockung in Holzbauweise eine lohnende Ergänzung sein kann. Aus nachhaltigem Baumaterial wird mit verhältnismäßigem Mehraufwand eine größere Rentabilität der Immobilie bewirkt und dem Problem der Wohnungsknappheit in Städten entgegengewirkt.In order to take action against climate change, a reduction in greenhouse emissions is necessary in existing buildings. Therefore, political decisionmakers, housing organisations and construction companies must work together to achieve carbon neutrality. The deep retrofit of the needy buildings till the year 2050 is not possible by conventional methods. The Energiesprong principle offers a solution that is financially interesting and can be implemented in large quantities with fewer personnel. The realization is gained that the previously used constructive systems still need to be optimized, in order to reach the financial goals of the principle and satisfy the mass market demand. The investigations of this work show that the concept could gain through the addition of a process integrated timber storey extension. With sustainable building materials, the property is made more profitable at considerable cost and workload, and the problem of housing shortages in cities is counteracted

    Evaluating Body Movement and Breathing Signals for Identification of Sleep/Wake States

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    Recognition of sleep and wake states is one of the relevant parts of sleep analysis. Performing this measurement in a contactless way increases comfort for the users. We present an approach evaluating only movement and respiratory signals to achieve recognition, which can be measured non-obtrusively. The algorithm is based on multinomial logistic regression and analyses features extracted out of mentioned above signals. These features were identified and developed after performing fundamental research on characteristics of vital signals during sleep. The achieved accuracy of 87% with the Cohen’s kappa of 0.40 demonstrates the appropriateness of a chosen method and encourages continuing research on this topic

    Deep and interpretable regression models for ordinal outcomes

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    Outcomes with a natural order commonly occur in prediction problems and often the available input data are a mixture of complex data like images and tabular predictors. Deep Learning (DL) models are state-of-the-art for image classification tasks but frequently treat ordinal outcomes as unordered and lack interpretability. In contrast, classical ordinal regression models consider the outcome’s order and yield interpretable predictor effects but are limited to tabular data. We present ordinal neural network transformation models (ontrams), which unite DL with classical ordinal regression approaches. ontrams are a special case of transformation models and trade off flexibility and interpretability by additively decomposing the transformation function into terms for image and tabular data using jointly trained neural networks. The performance of the most flexible ontram is by definition equivalent to a standard multi-class DL model trained with cross-entropy while being faster in training when facing ordinal outcomes. Lastly, we discuss how to interpret model components for both tabular and image data on two publicly available datasets

    Code-Based Cryptography With Generalized Concatenated Codes for Restricted Error Values

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    Code-based cryptosystems are promising candidates for post-quantum cryptography. Recently, generalized concatenated codes over Gaussian and Eisenstein integers were proposed for those systems. For a channel model with errors of restricted weight, those q-ary codes lead to high error correction capabilities. Hence, these codes achieve high work factors for information set decoding attacks. In this work, we adapt this concept to codes for the weight-one error channel, i.e., a binary channel model where at most one bit-error occurs in each block of m bits. We also propose a low complexity decoding algorithm for the proposed codes. Compared to codes over Gaussian and Eisenstein integers, these codes achieve higher minimum Hamming distances for the dual codes of the inner component codes. This property increases the work factor for a structural attack on concatenated codes leading to higher overall security. For comparable security, the key size for the proposed code construction is significantly smaller than for the classic McEliece scheme based on Goppa codes

    A Circular Detection Driven Adaptive Birth Density for Multi-Object Tracking with Sets of Trajectories

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    Multi-object tracking filters require a birth density to detect new objects from measurement data. If the initial positions of new objects are unknown, it may be useful to choose an adaptive birth density. In this paper, a circular birth density is proposed, which is placed like a band around the surveillance area. This allows for 360° coverage. The birth density is described in polar coordinates and considers all point-symmetric quantities such as radius, radial velocity and tangential velocity of objects entering the surveillance area. Since it is assumed that these quantities are unknown and may vary between different targets, detected trajectories, and in particular their initial states, are used to estimate the distribution of initial states. The adapted birth density is approximated as a Gaussian mixture, so that it can be used for filters operating on Cartesian coordinates

    Conception of smart farming solutions in the context of Botswana's digital development

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    Botswana serves as a role model for other African countries due to its rapid development in recent decades. Since the country is sparsely populated and a large part of the rural population depends on agriculture, especially livestock, this sector forms the backbone of the national economy. The digitization of this sector offers promising opportunities for economic growth and driving Botswana's evolution to a digital economy, while real value is being created for smallholder farmers. To support this process, an ITU research project made the key recommendation for the development of a digital crowdfarming tool and marketplace to create a digital ecosystem for smallholder agriculture. Within the research project, infrastructural challenges such as the creation of rural electricity supply and internet access, as well as the smallholders' need for remote monitoring, management, and better connectivity, were identified. Based on the findings of the ITU research report, this bachelor's thesis aims to identify potential innovations for the digital development of smallholder agriculture in Botswana and to conceptualize proposals to address the identified challenges and needs of smallholder farmers. To achieve this, solutions were developed through literature research, technology analysis and expert involvement. These included the design of a decentralized mini-grid for power supply, proposals to create internet access, and the graphic visualization of a conceptual app. The latter addresses smallholder farmers' needs for remote monitoring, market access, knowledge enhancement, and connection to colleagues, buyers, and investors. The proposed solutions and developed concepts provide impulses for further research and can serve as a basis for an extended evaluation through further involvement of experts and stakeholders

    CoKLIMAx

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    Extent Estimation of Sailing Boats Applying Elliptic Cones to 3D LiDAR Data

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    In this paper, approximating the shape of a sailing boat using elliptic cones is investigated. Measurements are assumed to be gathered from the target's surface recorded by 3D scanning devices such as multilayer LiDAR sensors. Therefore, different models for estimating the sailing boat's extent are presented and evaluated in simulated and real-world scenarios. In particular, the measurement source association problem is addressed in the models. Simulated investigations are conducted with a static and a moving elliptic cone. The real-world scenario was recorded with a Velodyne Alpha Prime (VLP-128) mounted on a ferry of Lake Constance. Final results of this paper constitute the extent estimation of a single sailing boat using LiDAR data applying various measurement models

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