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40 Jahre Neuland des Denkens
(2020)
Vor 40 Jahren erschien Frederic Vesters Hauptwerk „Neuland des Denkens“. Der Beitrag beleuchtet die wesentlichen Themen dieses programmatischen Buches im Hinblick auf Vesters Biokybernetik und deren Anwendung auf zahlreiche aktuelle Fragen in der Nachhaltigkeits-Debatte, z.B. Klimawandel-Problematik und Energiewende.
This work presents a new concept to implement the elliptic curve point multiplication (PM). This computation is based on a new modular arithmetic over Gaussian integer fields. Gaussian integers are a subset of the complex numbers such that the real and imaginary parts are integers. Since Gaussian integer fields are isomorphic to prime fields, this arithmetic is suitable for many elliptic curves. Representing the key by a Gaussian integer expansion is beneficial to reduce the computational complexity and the memory requirements of secure hardware implementations, which are robust against attacks. Furthermore, an area-efficient coprocessor design is proposed with an arithmetic unit that enables Montgomery modular arithmetic over Gaussian integers. The proposed architecture and the new arithmetic provide high flexibility, i.e., binary and non-binary key expansions as well as protected and unprotected PM calculations are supported. The proposed coprocessor is a competitive solution for a compact ECC processor suitable for applications in small embedded systems.
Digitalization is one of the most frequently discussed topics in industry. New technologies, platform concepts and integrated data models do enable disruptive business models and drive changes in organization, processes, and tools. The goal is to make a company more efficient, productive and ultimately profitable. However, many companies are facing the challenge of how to approach digital transformation in a structured way and to realize these potential benefits. What they realize is that Product Lifecycle Management plays a key role in digitalization intends, as object, structure and process management along the life cycle is a foundation for many digitalization use cases. The introduced maturity model for assessing a firm’s capabilities along the product lifecycle has been used almost two hundred times. It allows a company to compare its performance with an industry specific benchmark to reveal individual strengths and weaknesses. Furthermore, an empirical study produced multidimensional correlation coefficients, which identify dependencies between business model characteristics and the maturity level of capabilities.
A conceptual framework for indigenous ecotourism projects – a case study in Wayanad, Kerala, India
(2020)
This paper analyses indigenous ecotourism in the Indian district of Wayanad, Kerala, using a conceptual framework based on a PATA 2015 study on indigenous tourism that includes the criteria: human rights, participation, business and ecology. Detailed indicator sets for each criterion are applied to a case study of the Priyadarshini Tea Environs with a qualitative research approach addressing stakeholders from the public sector, non-governmental organisations, academia, tour operators and communities including Adivasi and non-Adivasi. In-depth interviews were supported by participant and non-participant observations. The authors adapted this framework to the needs of the case study and consider that this modified version is a useful tool for academics and practitioners wishing to evaluate and develop indigenous ecotourism projects. The results show that the Adivasi involved in the Priyadarshini Tea Environs project benefit from indigenous ecotourism. But they could profit more if they had more involvement in and control of the whole tourism value chain.
This paper presents the implementation of deep learning methods for sleep stage detection by using three signals that can be measured in a non-invasive way: heartbeat signal, respiratory signal, and movement signal. Since signals are measurements taken during the time, the problem is seen as time-series data classification. Deep learning methods are chosen to solve the problem are convolutional neural network and long-short term memory network. Input data is structured as a time-series sequence of mentioned signals that represent 30 seconds epoch, which is a standard interval for sleep analysis. The records used belong to the overall 23 subjects, which are divided into two subsets. Records from 18 subjects were used for training the data and from 5 subjects for testing the data. For detecting four sleep stages: REM (Rapid Eye Movement), Wake, Light sleep (Stage 1 and Stage 2), and Deep sleep (Stage 3 and Stage 4), the accuracy of the model is 55%, and F1 score is 44%. For five stages: REM, Stage 1, Stage 2, Deep sleep (Stage 3 and 4), and Wake, the model gives an accuracy of 40% and F1 score of 37%.
Modeling a suitable birth density is a challenge when using Bernoulli filters such as the Labeled Multi-Bernoulli (LMB) filter. The birth density of newborn targets is unknown in most applications, but must be given as a prior to the filter. Usually the birth density stays unchanged or is designed based on the measurements from previous time steps.
In this paper, we assume that the true initial state of new objects is normally distributed. The expected value and covariance of the underlying density are unknown parameters. Using the estimated multi-object state of the LMB and the Rauch-Tung-Striebel (RTS) recursion, these parameters are recursively estimated and adapted after a target is detected.
The main contribution of this paper is an algorithm to estimate the parameters of the birth density and its integration into the LMB framework. Monte Carlo simulations are used to evaluate the detection driven adaptive birth density in two scenarios. The approach can also be applied to filters that are able to estimate trajectories.
Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.
We propose and apply a requirements engineering approach that focuses on security and privacy properties and takes into account various stakeholder interests. The proposed methodology facilitates the integration of security and privacy by design into the requirements engineering process. Thus, specific, detailed security and privacy requirements can be implemented from the very beginning of a software project. The method is applied to an exemplary application scenario in the logistics industry. The approach includes the application of threat and risk rating methodologies, a technique to derive technical requirements from legal texts, as well as a matching process to avoid duplication and accumulate all essential requirements.
In this work, we investigate a hybrid decoding approach that combines algebraic hard-input decoding of binary block codes with soft-input decoding. In particular, an acceptance criterion is proposed which determines the reliability of a candidate codeword. For many received codewords the stopping criterion indicates that the hard-decoding result is sufficiently reliable, and the costly soft-input decoding can be omitted. The proposed acceptance criterion significantly reduces the decoding complexity. For simulations we combine the algebraic hard-input decoding with ordered statistics decoding, which enables near maximum likelihood soft-input decoding for codes of small to medium block lengths.
Many resource-constrained systems still rely on symmetric cryptography for verification and authentication. Asymmetric cryptographic systems provide higher security levels, but are very computational intensive. Hence, embedded systems can benefit from hardware assistance, i.e., coprocessors optimized for the required public key operations. In this work, we propose an elliptic curve cryptographic coprocessors design for resource-constrained systems. Many such coprocessor designs consider only special (Solinas) prime fields, which enable a low-complexity modulo arithmetic. Other implementations support arbitrary prime curves using the Montgomery reduction. These implementations typically require more time for the point multiplication. We present a coprocessor design that has low area requirements and enables a trade-off between performance and flexibility. The point multiplication can be performed either using a fast arithmetic based on Solinas primes or using a slower, but flexible Montgomery modular arithmetic.
For a long time, the use of intermediate products in production has been growing more rapidly in most countries than domestic production. This is a strong indication of more interdependency in production. The main purpose of input-output analysis is to study the interdependency of industries in an economy. Often the term interindustry analysis is also used. Therefore, the exchange of intermediate products is a key issue of input-output analysis. We will use input–output data for this study that the author prepared for the new ‘Handbook on Supply, Use and Input–Output Tables with Extensions and Applications’ of the United Nations. The supply use and input–output tables contain separate valuation matrices for trade margins, transport margins, value added tax, other taxes on products and subsidies on products. For the study, two input–output models were developed to evaluate the impact of fuel subsidy and taxation reform on output, gross domestic product, inflation and trade. Six scenarios are discussed covering different aspects of the reform.
This work is a study about a comparison of survey tools and it should help developers in selecting a suited tool for application in an AAL environment. The first step was to identify the basic required functionality of the survey tools used for AAL technologies and to compare these tools by their functionality and assignments. The comparative study was derived from the data obtained, previous literature studies and further technical data. A list of requirements was stated and ordered in terms of relevance to the target application domain. With the help of an integrated assessment method, the calculation of a generalized estimate value was performed and the result is explained. Finally, the planned application of this tool in a running project is explained.
Die Projektaufgabe bestand darin, den aktuellen Laborversuch zu modernisieren, indem die Kommunikation zwischen dem Versuchsaufbau und Laborrechner nicht wie bisher über Wandlerkarten stattfindet, sondern über EtherCAT und TwinCAT 3.
Die Installation von TwinCAT 3 mit den zugehörigen Erweiterungen und erforderlichen Programmen stellt sich als sehr umfangreich und schwierig dar, was die Installationsanleitungen zeigen. Außerdem gab es sehr viele Fehlerquellen, die nicht auf Anhieb ersichtlich waren, wie das Aktualisieren der aktuellen MATLAB Version. Ist die Installation abgeschlossen kann die Kommunikation zwischen MATLAB und TwinCAT relativ einfach umgesetzt werden.
In der Projektarbeit wurde anfangs dann die Kommunikation mit mehreren Tests überprüft und Optimierungen vorgenommen. So wurde zum Beispiel die Wegbegrenzung angepasst. Schwierigkeiten zeigten sich bei der Bedienung über MATLAB oder beim Abstürzen von MATLAB, da beim Stoppen oder Abstürzen von MATLAB, der zuletzt gesendete Wert immer noch an TwinCAT 3 anliegt und somit der Aktor weiter verfahren würde. Diese sehr gefährliche Situation wäre ein gravierender Nachteil, gegenüber der alten Kommunikation mit einer Wandlerkarte. Um einen sicheren Stopp zu garantieren, wird über ein neues TcCOM Objekt der Matlab-Status mit einem Togglebit überprüft, ändert sich der Wert des Bits nicht mehr, stoppt die Anlage sicher.
Um einen Vergleich mit dem bisherigen Masterversuch erhalten zu können, wurde die Strecke mit der neuen Kommunikation untersucht und ein passender Regler dafür auszulegt.
Die Auswertung der Impulsantwort sowie der „Spectrum-Analyse“ zeigten beim Vergleich mit den Schnittstellen gleiche Ergebnisse, somit sind die Versuche bei dem Laborversuch ohne Einschränkungen durchführbar. Die Auslegung des Reglers zeigte entgegen den Prognosen der Beckhoff-Experten sehr gute Ergebnisse und die Kommunikation über die Schnittstelle zeigte keine Probleme.
Einschränkungen zeigten sich jedoch bei der einzustellenden Abtastzeit, da eine Abtastzeit unter 2ms nicht möglich ist. Zwar kann man eine geringere Abtastzeit einstellen, jedoch zeigt sich bei der Auswertung, dass die Schnittstelle mit Abtastzeiten unter 2ms Probleme aufweist. Die Rechendauer wird deutlich größer und die größere Anzahl an Messpunkte kann nicht richtig verarbeitet werden. Ein Regler kann damit nicht implementiert werden.
Die Projektarbeit konnte somit erfolgreich angeschlossen werden und bis auf die aufwendige Installation sind die Erweiterungen von Beckhoff sehr zuverlässig und gut zu bedienen. Die ersten Voruntersuchen waren positiv, somit kann auch an weiteren Laborrechnern eine Umstellung der Schnittstelle in Betracht gezogen werden.
Digital technology and architecture have become inseparable, with new approaches and methodologies not just affecting the workflows and practice of architects but shaping the very character of architecture.
This compendious work offers a wide-ranging orientation to the new landscape with its opportunities, its challenges, and its vast potential.
In diesem Beitrag wird eine Methode des maschinellen Lernens entwickelt, die die Schlafstadienerkennung untersucht. Übliche Methoden der Schlafanalyse basieren auf der Polysomnographie (PSG). Der präsentierte Ansatz basiert auf Signalen, die ausschließlich nicht-invasiv in einer häuslichen Umgebung gemessen werden können. Bewegungs-, Herzschlags- und Atmungssignale können vergleichsweise leicht erfasst werden aber die Erkennung der Schlafstadien ist dadurch erschwert. Die Signale werden als Zeitreihenfolge strukturiert und in Epochen überführt. Die Leistungsfähigkeit von maschinellem Lernen wird der Polysomnographie gegenübergestellt und bewertet.
Im vorliegenden Beitrag wird der Einfluss der Modellierung des Kellergeschosses auf die Querkraft und die Verformungen von im Kellergeschoss eingespannten Stahlbeton‐Aussteifungswänden untersucht. Der Querkraftverlauf der Wand und die Verschiebung am Kopf der Wand werden mit den entsprechenden, am vereinfachten Kragwandmodell ermittelten Werten verglichen, bei dem die Wand auf Höhe der Kellerdecke voll eingespannt ist und die Weiterleitung der Schnittkräfte im Kellergeschoss nicht näher betrachtet wird. Für die Berücksichtigung des Kellergeschosses wird zunächst eine gelenkige Festhaltung durch die Kellerdecke und die Bodenplatte betrachtet, wodurch sich eine unrealistisch große Wandquerkraft im Kellergeschoss ergibt. Danach wird ein verfeinertes Modell mit Teileinspannung in der Bodenplatte und nachgiebiger Halterung durch die Kellerdecke untersucht. Es werden Empfehlungswerte für die Federkonstante der Drehfeder auf Höhe der Bodenplatte und der horizontalen Translationsfeder auf Höhe der Kellerdecke angegeben, die in der Praxis Anwendung finden können. Es wird besonders der Frage nachgegangen, welche Einflüsse die Berücksichtigung des Kellergeschosses bei der Erdbebenbemessung der Aussteifungswände hat. Dabei wird einerseits die Systemsteifigkeit, von der die Erdbebenersatzlasten abhängen, und andererseits die mögliche Verschiebungsduktilität, von der der mögliche Verhaltensbeiwert q abhängt, betrachtet.
What drives entrepreneurial action to create a lasting impact? The creation of new ventures that aim at having an impact beyond their financial performance face additional challenges: achieving economic sustainability and at the same time addressing social or environmental issues. Little is known on how these new hybrid organizations, aiming for multiple impact dimensions, manage to be congruent with their blended values. A dataset of 4,125 early-stage ventures is used to gain insights into how blended values are converted into financial, social and environmental impacts, giving shape to different types of hybrid organizations. Our findings suggest new hybrid organizations might opt to sacrifice financial impact to achieve social impact, yet this is not the case when they aim to generate environmental or sustainable impact. Therefore, the tensions and sacrifices related to holding blended values are not homogeneous across all types of new hybrid organizations.
Dieses besondere Lehrbuch führt in die Berechnung von Verbrennungsmotoren ein, geht dabei von aktuellen Fragestellungen z. B. zur Fahrzeugdynamik oder Motorthermodynamik aus und stellt bei der Lösung die notwendige Theorie mit bereit. Damit auch Quereinsteiger erfolgreich sind, ist in einem Verzeichnis aufgeführt, welche theoretischen Kenntnisse man für die Lösung der jeweiligen Aufgabe benötigt und in welchem Abschnitt des Buches diese hergeleitet werden. Alle Berechnungen werden in Excel durchgeführt.
In der vorliegenden Auflage wurden aktuelle Beispiele zur Motoreffizienz, zum Motorkennfeld, zur Lastpunktanhebung, zum Fahrzyklus WLTC und zu realen Fahrzyklen (RDE) ergänzt.
Der Inhalt:
- Fahrwiderstand und Motorleistung
- Kraftstoffe und Stöchiometrie
- Motorleistung und Mitteldruck
- Motorthermodynamik
- Motormechanik
- Fahrzeugdynamik
- Hybrid- und Elektrofahrzeuge
- Aufladung von Verbrennungsmotoren
Die Zielgruppen:
Studierende des Maschinenbaus und der Kfz-Technik an Hochschulen in Bachelor- und Masterstudiengängen; Motoreningenieure, die sich mit verbrennungsmotorischen Fragestellungen beschäftigen; Absolventen von Weiterbildungskursen auf Meisterniveau
Der Autor Dr.-Ing. Klaus Schreiner ist Professor an der HTWG Konstanz und Leiter des Labors für Verbrennungsmotoren in der Fakultät Maschinenbau. Er war viele Jahre lang Didaktikbeauftragter seiner Hochschule. Im Jahr 2008 erhielt er den Lehrpreis des Landes Baden-Württemberg.
The reliability of flash memories suffers from various error causes. Program/erase cycles, read disturb, and cell to cell interference impact the threshold voltages and cause bit errors during the read process. Hence, error correction is required to ensure reliable data storage. In this work, we investigate the bit-labeling of triple level cell (TLC) memories. This labeling determines the page capacities and the latency of the read process. The page capacity defines the redundancy that is required for error correction coding. Typically, Gray codes are used to encode the cell state such that the codes of adjacent states differ in a single digit. These Gray codes minimize the latency for random access reads but cannot balance the page capacities. Based on measured voltage distributions, we investigate the page capacities and propose a labeling that provides a better rate balancing than Gray labeling.
In previous studies, we used a method for detecting stress that was based exclusively on heart rate and ECG for differentiation between such situations as mental stress, physical activity, relaxation, and rest. As a response of the heart to these situations, we observed different behavior in the Root Mean Square of the Successive differences heartbeats (RMSSD). This study aims to analyze Virtual Reality via a virtual reality headset as an effective stressor for future works. The value of the Root Mean Square of the Successive Differences is an important marker for the parasympathetic effector on the heart and can provide information about stress. For these measurements, the RR interval was collected using a breast belt. In these studies, we can observe the Root Mean Square of the successive differences heartbeats. Additional sensors for the analysis were not used. We conducted experiments with ten subjects that had to drive a simulator for 25 minutes using monitors and 25 minutes using virtual reality headset. Before starting and after finishing each simulation, the subjects had to complete a survey in which they had to describe their mental state. The experiment results show that driving using virtual reality headset has some influence on the heart rate and RMSSD, but it does not significantly increase the stress of driving.
A residual neural network was adapted and applied to the Physionet/Computing data in Cardiology Challenge 2020 to detect 24 different classes of cardiac abnormalities from 12-lead. Additive Gaussian noise, signal shifting, and the classification of signal sections of different lengths were applied to prevent the network from overfitting and facilitating generalization. Due to the use of a global pooling layer after the feature extractor, the network is independent of the signal’s length. On the hidden test set of the challenge, the model achieved a validation score of 0.656 and a full test score of 0.27, placing us 15th out of 41 officially ranked teams (Team name: UC_Lab_Kn). These results show the potential of deep neural networks for ap- plication to raw data and a complex multi-class multi-label classification problem, even if the training data is from di- verse datasets and of differing lengths.
Despite the importance of Social Life Cycle Sustainability Assessment (S-LCSA), little research has addressed its integration into Product Lifecycle Management (PLM) systems. This paper presents a structured review of relevant research and practice. Also, to address practical aspects in more detail, it focuses on challenges and potential for adoption of such an integrated system at an electronics company.
We began by reviewing literature on implementations of Social-LCSA and identifying research needs. Then we investigated the status of Social-LCSA within the electronics industry, both by reviewing literature and interviewing decision makers, to identify challenges and the potential for adopting S-LCSA at an electronics company. We found low maturity of Social-LCSA, particularly difficulty in quantifying social sustainability. Adoption of Social-LCSA was less common among electronics industry suppliers, especially mining & smelting plants. Our results could provide a basis for conducting case studies that could further clarify issues involved in integrations of Social-LCSA into PLM systems.
NAND flash memory is widely used for data storage due to low power consumption, high throughput, short random access latency, and high density. The storage density of the NAND flash memory devices increases from one generation to the next, albeit at the expense of storage reliability.
Our objective in this dissertation is to improve the reliability of the NAND flash memory with a low hard implementation cost. We investigate the error characteristic, i.e. the various noises of the NAND flash memory. Based on the error behavior at different life-aging stages, we develop offset calibration techniques that minimize the bit error rate (BER).
Furthermore, we introduce data compression to reduce the write amplification effect and support the error correction codes (ECC) unit. In the first scenario, the numerical results show that the data compression can reduce the wear-out by minimizing the amount of data that is written to the flash. In the ECC scenario, the compression gain is used to improve the ECC capability. Based on the first scenario, the write amplification effect can be halved for the considered target flash and data model. By combining the ECC and data compression, the NAND flash memory lifetime improves three fold compared with uncompressed data for the same data model.
In order to improve the data reliability of the NAND flash memory, we investigate different ECC schemes based on concatenated codes like product codes, half-product codes, and generalized concatenated codes (GCC). We propose a construction for high-rate GCC for hard-input decoding. ECC based on soft-input decoding can significantly improve the reliability of NAND flash memories. Therefore, we propose a low-complexity soft-input decoding algorithm for high-rate GCC.
Climate protection in Seychelles through tourism: the advantages of a small-sized destination
(2020)
CO2 abatement costs are often low in developing countries. This is why most carbon offset projects are being implemented there. Nevertheless, this does not mean that the holiday resort and the project country are in any way related to each other. Linking compensation projects with the destination country could increase the willingness of air travellers to finance voluntary CO2 compensation measures.
This paper describes how a possible combination of CO2 compensation projects in the Seychelles could affect the voluntary carbon offset behaviour of Seychelles tourists. On the one hand, the issue of whether the voluntary willingness of Seychelles travellers to compensate can be increased is examined; on the other hand, whether tourists would be willing to visit a co-financed project in the Seychelles.
As a result, the willingness of tourists to offset air-travel carbon emissions can be increased. Important factors for this are e.g. that all persons have adequate information and that the carbon offset providers display a high degree of transparency. In addition, a broad interest in visiting the projects in the Seychelles during the holiday was expressed. An important condition for this is the spatial vicinity to the project. Due to its small size, the Seychelles are an ideal location for fulfilling this premise.
Three-dimensional ship localization with only one camera is a challenging task due to the loss of depth information caused by perspective projection. In this paper, we propose a method to measure distances based on the assumption that ships lie on a flat surface. This assumption allows to recover depth from a single image using the principle of inverse perspective. For the 3D ship detection task, we use a hybrid approach that combines image detection with a convolutional neural network, camera geometry and inverse perspective. Furthermore, a novel calculation of object height is introduced. Experiments show that the monocular distance computation works well in comparison to a Velodyne lidar. Due to its robustness, this could be an easy-to-use baseline method for detection tasks in navigation systems.
Spatial modulation is a low-complexity multipleinput/ multipleoutput transmission technique. The recently proposed spatial permutation modulation (SPM) extends the concept of spatial modulation. It is a coding approach, where the symbols are dispersed in space and time. In the original proposal of SPM, short repetition codes and permutation codes were used to construct a space-time code. In this paper, we propose a similar coding scheme that combines permutation codes with codes over Gaussian integers. Short codes over Gaussian integers have good distance properties. Furthermore, the code alphabet can directly be applied as signal constellation, hence no mapping is required. Simulation results demonstrate that the proposed coding approach outperforms SPM with repetition codes.
Good sleep is crucial for a healthy life of every person. Unfortunately, its quality often decreases with aging. A common approach to measuring the sleep characteristics is based on interviews with the subjects or letting them fill in a daily questionnaire and afterward evaluating the obtained data. However, this method has time and personal costs for the interviewer and evaluator of responses. Therefore, it would be important to execute the collection and evaluation of sleep characteristics automatically. To do that, it is necessary to investigate the level of agreement between measurements performed in a traditional way using questionnaires and measurements obtained using electronic monitoring devices. The study presented in this manuscript performs this investigation, comparing such sleep characteristics as "time going to bed", "total time in bed", "total sleep time" and "sleep efficiency". A total number of 106 night records of elderly persons (aged 65+) were analyzed. The results achieved so far reveal the fact that the degree of agreement between the two measurement methods varies substantially for different characteristics, from 31 minutes of mean difference for "time going to bed" to 77 minutes for "total sleep time". For this reason, a direct exchange of objective and subjective measuring methods is currently not possible.
Compliance Governance
(2020)
Für die Funktionsfähigkeit und Wirksamkeit eines Compliance-Management-Systems (CMS) – und damit verbunden, einer guten und verantwortungsvollen Corporate Governance – ist die Compliance Governance von fundamentaler Bedeutung. Damit sind passende Compliance-Strukturen und eine positive Compliance-Kultur gemeint, die in den Mittelpunkt der Aufmerksamkeit rücken. Im vorliegenden Beitrag wird dieser Themenkomplex aus unterschiedlichen Perspektiven beleuchtet. Zunächst nimmt Stephan Grüninger eine Begriffsbestimmung zur „Compliance Governance“ vor (1.3.1), um darauf aufbauend die wesentlichen Erfolgsprinzipien wirksamer Compliance-Struktur und -Kultur aus betriebswirtschaftlicher und organisationstheoretischer Perspektive herauszuarbeiten (1.3.2). Der Kontrolle und Aufsicht im Rahmen einer guten „Compliance Governance“ kommt eine wichtige Funktion zu, so dass Roland Steinmeyer darauf aufbauend (1.3.3) aus rechtlicher Perspektive die Verantwortlichkeiten des Aufsichtsrats im Rahmen des Compliance- Managements (CM) beschreibt. Abschließend (1.3.4) gibt Christian Strenger Einblicke in die Praxis der Compliance-Aufsicht und benennt Anforderungen, die Aufsichtsräte bei der Ausübung ihrer Überwachungsfunktion zu erfüllen haben und Herausforderungen, denen sie dabei gegenüberstehen.
Um die Antwort zu der Frage nach der Notwendigkeit von Compliance- Management für mittelständische Unternehmen gleich vorweg zu nehmen: ja, auch mittelständische Unternehmen tun gut daran, sich mit Compliance-Management auseinander zu setzen. Die Notwendigkeit für Compliance-Management verstanden als die Sicherstellung von Compliance, d. h. der Einhaltung gesetzlicher Regelungen, von Soft Law sowie interner Regeln und Verhaltensstandards, ergibt sich bereits allein aus der Verantwortung der Unternehmensleitung, das Unternehmen vor Bedrohungen zu schützen und den Fortbestand des Unternehmens sowie die Kooperationsbeziehungen mit den verschiedenen Stakeholdergruppen langfristig zu sichern. Anders formuliert: Compliance-Management ist Risikomanagement und somit von strategischer Bedeutung für eine verantwortungsvolle Unternehmensführung (good Corporate Governance) – in Großunternehmen wie in mittelständischen Unternehmen. Einzig die Frage nach dem „Wie“ von Compliance-Management in mittelständischen Unternehmen hat ihre Berechtigung.
The actual task of electrocardiographic examinations is to increase the reliability of diagnosing the condition of the heart. Within the framework of this task, an important direction is the solution of the inverse problem of electrocardiography, based on the processing of electrocardiographic signals of multichannel cardio leads at known electrode coordinates in these leads (Titomir et al. Noninvasiv electrocardiotopography, 2003), (Macfarlane et al. Comprehensive Electrocardiology, 2nd ed. (Chapter 9), 2011).
Creative industry and cultural tourism destination Lake Constance - a media discourse analysis
(2020)
The following media discourse analysis examines the news media coverage of four regional online newspapers, about the topics “creative industries” and “cultural tourism” at Lake Constance region in the period from 2006 until 2016. The results show that, besides event-relater reporting, there is currently no vibrant media discourse on the topics “creative industries” and “cultural tourism”. Even though the image of the Lake Constance region is heavily influenced by tourism, “cultural tourism” also plays a secondary role when it comes to regional news reporting. Moreover, discourses do not overlap and thus no synergies within the local media discourse are formed. This result is relevant for the regional tourism development, because the cooperation between “creative industries” and “cultural tourism” creates opportunities such as the expansion of the tourism offer and an extension of the tourist season. To activate unused opportunities at the different destinations of the region, a supra-regional visibility of the sector “creative industries” should be developed and the cooperation of the sector with local stakeholders of cultural tourism should be promoted.
Uncertainty about the future requires companies to create discontinuous innovations. Established companies, however, struggle to do so; whereas independent startups seem to better cope with this. Consequently, established companies set up entrepreneurial initiatives to make use of startups' benefits. Consequently, this led-amongst others-to great interest in socalled corporate entrepreneurship (CE) programs and to the development and characterization of several different forms. Their processes to achieve certain objectives, yet, are still rather ineffective. Thus, considerations of the actions performed in preparation for and during CE programs could be one approach to improve this but are still absent today. Furthermore, the increasing use of several CE programs in parallel seems to bear the potential for synergies and, thus, more efficient use of resources. Aiming to provide insights to both issues, this study analyzes actions of CE programs, by looking at interviews with managers of seven corporate incubators and accelerator programs of five established German tech-companies.
The ageing infrastructure in ports requires regular inspection. This inspection is currently carried out manually by divers who sense by hand the entire underwater infrastructure. This process is cost-intensive as it involves a lot of time and human resources. To overcome these difficulties, we propose to scan the above and underwater port structure with a Multi-SensorSystem, and -by a fully automated processto classify the obtained point cloud into damaged and undamaged zones. We make use of simulated training data to test our approach since not enough training data with corresponding class labels are available yet. To that aim, we build a rasterised heightfield of a point cloud of a sheet pile wall by cutting it into verticall slices. The distance from each slice to the corresponding line generates the heightfield. This latter is propagated through a convolutional neural network which detects anomalies. We use the VGG19 Deep Neural Network model pretrained on natural images. This neural network has 19 layers and it is often used for image recognition tasks. We showed that our approach can achieve a fully automated, reproducible, quality-controlled damage detection which is able to analyse the whole structure instead of the sample wise manual method with divers. The mean true positive rate is 0.98 which means that we detected 98 % of the damages in the simulated environment.
Location-aware mobile devices are becoming increasingly popular and GPS sensors are built into nearly every portable unit with computational capabilities. At the same time, the emergence of location-aware virtual services and ideas calls for new efficient spatial real-time queries. Communication latency in mobile environments interacting with high decentralization and the need of scalability in high-density systems with immense client counts leads to major challenges. In this paper we describe a decentralized architecture for continuous range queries in settings in which both, the requested and the requesting clients, are mobile. While prior works commonly use a request-response approach we provide a stream-based adaptive grid solution dealing with arbitrary high client counts and improving communication latency that meets given hard real-time constraints.
Der digitale Seilüberwacher
(2020)
Mapping of tree seedlings is useful for tasks ranging from monitoring natural succession and regeneration to effective silvicultural management. Development of methods that are both accurate and cost-effective is especially important considering the dramatic increase in tree planting that is required globally to mitigate the impacts of climate change. The combination of high-resolution imagery from unmanned aerial vehicles and object detection by convolutional neural networks (CNNs) is one promising approach. However, unbiased assessments of these models and methods to integrate them into geospatial workflows are lacking. In this study, we present a method for rapid, large-scale mapping of young conifer seedlings using CNNs applied to RGB orthomosaic imagery. Importantly, we provide an unbiased assessment of model performance by using two well-characterised trial sites together containing over 30,000 seedlings to assemble datasets with a high level of completeness. Our results showed CNN-based models trained on two sites detected seedlings with sensitivities of 99.5% and 98.8%. False positives due to tall weeds at one site and naturally regenerating seedlings of the same species led to slightly lower precision of 98.5% and 96.7%. A model trained on examples from both sites had 99.4% sensitivity and precision of 97%, showing applicability across sites. Additional testing showed that the CNN model was able to detect 68.7% of obscured seedlings missed during the initial annotation of the imagery but present in the field data. Finally, we demonstrate the potential to use a form of weakly supervised training and a tile-based processing chain to enhance the accuracy and efficiency of CNNs applied to large, high-resolution orthomosaics.
Cities around the world are facing an increasing number of global and local challenges, such as climate change and scarcity of raw materials. At the same time trends like digitalization, globalization and networking gain in importance. For this reason, cities have started imple-menting smart solutions within the urban structure in order to evolve towards a Smart City. In Botswana, the Maun Science Park is intended to provide a best practice approach for a Bot-swanan Smart City. Since Smart City concepts have to be specifically tailored to local condi-tions, the first main goal of this thesis is to develop a synthesis concept for the Maun Science Park. A key problem in cities is the utilization of space, which is further intensified by increasing urbanization and population growth. Therefore, the second main goal is to develop approaches of (digitally) re-programmable space to use available areas intelligently and optimized.
Within the thesis, human-centered design has been applied as structure-giving methodology. By clarifying relevant Smart City contents, considering reference examples as well as identify-ing local challenges and requirements, an appropriate concept has been developed with hu-man-focus. Furthermore, the methodologies of literature research and expert interviews have been used as input in the individual human-centered design phases. In combination with an innovation funnel, the methodology human-centered design forms the structure of the thesis.
In total, ten main solution areas and 37 sub-segments have been identified for the synthesis concept of Maun Science Park. Additionally, a concept for Smart Buildings has been devel-oped as a part of the synthesis concept and as an essential infrastructure component of the Maun Science Park (three main segments, 16 sub-segments). Based on expert input, a priori-tization has been determined by evaluating the impact and economic affordability of the indi-vidual sub-areas. Moreover, individual key areas have been highlighted by identifying direct interactions between sub-segments and on the basis of expert input – these are particularly related to the segments Smart Data and Smart People. Besides the synthesis concept, ap-proaches of (digitally) re-programmable space have been created. Thereby, ten approaches refer to the conversion, reuse or expansion abilities of space within daily, weekly or life cycle. In addition, the conventional (digitally) re-programmable space idea has been extended by two new considerations – “multi-purpose use of built-up space” and “concept programming in the planning phase”. Finally, within an overall consideration – synthesis concept combined with approaches of (digitally) re-programmable space – the added value of the developed contents has been outlined, positive and negative aspects have been identified within a SWOT analysis and the business model of the Maun Science Park approach has been verified in a Business Model Canvas.
Through explicit elaboration, classification and prioritization of solution areas, the developed concept can serve as a basis for further project steps. Based on the defined requirements of the sub-segments, solutions can be developed with regard to the entire Smart City context.
Für die Überwachung des Schlafs zu Hause sind nichtinvasive Methoden besonders gut anwendbar. Die Signale, die häufig überwacht werden, sind Herzfrequenz und Atemfrequenz. Die Ballistokardiographie (BCG)ist eine Technik, bei der die Herzfrequenz aus den mechanischen Schwingungen des Körpers bei jedem Herzzyklus gemessen wird. Kürzlich wurden Übersichtsarbeiten veröffentlicht. Die Untersuchung soll in einem ersten Ansatz bewerten, ob die Herzfrequenz anhand von BCG erkannt werden kann. Die wesentlichen Randbedingungen sind, ob dies gelingt, wenn der Sensor unter der Matratze positioniert wird und kostengünstige Sensoren zum Einsatz kommen.
Forschungsfrage: Welche Rollen lassen sich in Corporate Entrepreneurship identifizieren? Wie unterscheiden sich diese anhand verschiedener Merkmale und welche Fähigkeiten scheinen besonders relevant für ihre erfolgreiche Ausführung?
Methodik: Explorative Studie mit 56 semi-strukturierten Interviews mit Corporate-Entrepreneurship-Aktivitäten im DACH-Raum
Praktische Implikationen: Ein genaues Verständnis über die jeweiligen Rollen, ihre Unterschiedlichkeiten und Anforderungen ist notwendig, um die verschiedenen Corporate-Entrepreneurship-Aktivitäten mit passendem Personal zu besetzen.
Die Nibelungenbrücke Worms
(2020)
We present source code patterns that are difficult for modern static code analysis tools. Our study comprises 50 different open source projects in both a vulnerable and a fixed version for XSS vulnerabilities reported with CVE IDs over a period of seven years. We used three commercial and two open source static code analysis tools. Based on the reported vulnerabilities we discovered code patterns that appear to be difficult to classify by static analysis. The results show that code analysis tools are helpful, but still have problems with specific source code patterns. These patterns should be a focus in training for developers.
We provide an overview of the ongoing discussions on the objectives of the energy transition in the form of a conceptual framework, intending to facilitate the search for the most viable options for a successful transformation of the energy system. For this purpose, we examine the development of energy policy goals in Germany in the past and present, whereby we give an overview of objectives and assessment approaches from politics, economics, and science. Moreover, we then merge the different views into a common framework and analyze the central conflict between the wholeness of a hypothetical target circle and the simplification in favor of a hypothetical target point in more detail.
Multi-Dimensional Connectionist Classification is amethod for weakly supervised training of Deep Neural Networksfor segmentation-free multi-line offline handwriting recognition.MDCC applies Conditional Random Fields as an alignmentfunction for this task. We discuss the structure and patterns ofhandwritten text that can be used for building a CRF. Since CRFsare cyclic graphical models, we have to resort to approximateinference when calculating the alignment of multi-line text duringtraining, here in the form of Loopy Belief Propagation. This workconcludes with experimental results for transcribing small multi-line samples from the IAM Offline Handwriting DB which showthat MDCC is a competitive methodology.