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Sanktionen stellen Zwangsmaßnahmen dar, die bei der Bewältigung politischer Spannungen zwischen Nationen eine lange und wiederkehrende Stellung einnehmen. Sie werden sowohl einseitig als auch in Staatenbündnissen verhängt und besonders nach dem 2. Weltkrieg mit zunehmender Häufigkeit eingesetzt. Während im letzten Jahrhundert, insbesondere vor dem 2. Weltkrieg, Handelsbeschränkungen und umfassende Wirtschaftsblockaden die vorherrschenden Sanktionsinstrumente darstellten, werden heute in einer stärker integrierten und globalisierten Welt Sanktionen in verschiedenen weiteren Formen verhängt, einschließlich internationaler Finanzbeschränkungen, Reiseverbote, Handelseinschränkungen für bestimmte Gütergruppen, Aufhebung militärischer Hilfen und spezifische Einschränkungen, wie beispielsweise Flugverbote und Hafensperrungen.
100 Jahre Türkische Republik
(2023)
Multi-faceted stresses of social, environmental, and economic nature are increasingly challenging the existence and sustainability of our societies. Cities in particular are disproportionately threatened by global issues such as climate change, urbanization, population growth, air pollution, etc. In addition, urban space is often too limited to effectively develop sustainable, nature-based solutions while accommodating growing populations. This research aims to provide new methodologies by proposing lightweight green bridges in inner-city areas as an effective land value capture mechanism. Geometry analysis was performed using geospatial and remote sensing data to provide geometrically feasible locations of green bridges. A multi-criteria decision analysis was applied to identify suitable locations for green bridges investigating Central European urban centers with a focus on German cities as representative examples. A cost-benefit analysis was performed to assess the economic feasibility using a case study. The results of the geometry analysis identified 3249 locations that were geometrically feasible to implement a green bridge in German cities. The sample locations from the geometry analysis were proved to be validated for their implementation potential. Multi-criteria decision analysis was used to select 287 sites that fall under the highest suitable class based on several criteria. The cost-benefit analysis of the case study showed that the market value of the property alone can easily outweigh the capital and maintenance costs of a green bridge, while the indirect (monetary) benefits of the green space continue to increase the overall value of the green bridge property including its neighborhood over time. Hence, we strongly recommend light green bridges as financially sustainable and nature-based solutions in cities worldwide.
Trotz des seit über zehn Jahren anhaltend negativen Trends im traditionellen Kameramarkt werden in Zukunft exponentiell mehr Bilder mit technischen Hilfsmitteln produziert und veröffentlicht werden, nur eben auf eine fundamental andere Weise, mit anderen, vermeintlich komfortableren Geräten, im Hintergrund unterstützt durch sogenannte »smarte« Technologien. Die blitzschnelle Verrechnung von kurzen Bildserien zu einem einzigen Bild, unter Zuhilfenahme von leistungsfähigen Algorithmen aus dem Bereich des maschinellen Sehens, simuliert eine handwerkliche Perfektion, die auf optisch, chemischem Weg so nicht möglich wäre. Auch wenn die analoge Fotografie, teils im Rückgriff auf Jahrhunderte alte Praktiken der Bildenden Kunst, einstmals die Vorbilder und Standards etabliert hat, auf die KI-Modelle derzeit trainiert werden, spielen analoge Bildgebungsverfahren heutzutage quantitativ kaum mehr eine Rolle. Qualitativ erfährt die analoge Fotografie, sowohl im Sinne einer entschleunigenden Gegenbewegung, als auch auf Grund ihrer vermeintlich höheren Authentizität und ihrer haptischen und materiellen Qualitäten, eine überraschend starke Aufmerksamkeit. Diese richtet sich auf die Auseinandersetzung mit fotografischen Wahrnehmungsweisen, die Erforschung unserer realen Umgebung und nicht zuletzt auf die Begegnung mit uns selbst. Analoge Kameras, die Arbeit in der Dunkelkammer und historische Verfahren, wie das Nasse-Kollodion-Verfahren oder die Cyanotypie haben seit einigen Jahren weltweit wieder Konjunktur unter Photoenthusiasten und Studierenden. Was die Protagonisten eines vermeintlich nostalgischen Retro-Trends indes nicht davon abhält, in ihrem Alltag ganz selbstverständlich in »Echtzeit« mit Handys und häufig unter strategisch diversifizierten, mehr oder weniger privaten User-Profilen und Identitäten in den sogenannten sozialen Netzwerken mit anderen (und auch sich selbst) in Form von digitalen bzw. digitalisierten Bildern in einen möglichst flüchtigen Kontakt zu treten.
Creative Coding - void draw
(2023)
Creative Coding ist eines der vielen trendigen Schlagwörter, die in letzter Zeit in der Designbranche auftauchen. Wie so oft ist Creative Coding aber prinzipiell gar nicht so neu, sondern eine Wortschöpfung, die etwas beschreibt, was DesignerInnen schon lange betreiben, was jedoch nun breiter diskutiert wird und als wichtiges Konzept für Designer anerkannt ist.
Analysing observability is an important step in the
process of designing state feedback controllers. While for linear
systems observability has been widely studied and easy-to-check
necessary and sufficient conditions are available, for nonlinear
systems, such a general recipe does not exist and different classes
of systems require different techniques. In this paper, we analyse
observability for an industrial heating process where a stripe-
shaped plastic workpiece is moving through a heating zone where
it is heated up to a specific temperature by applying hot air to its
surface through a nozzle. A modeling approach for this process
is briefly presented, yielding a nonlinear Ordinary Differential
Equation model. Sensitivity-based observability analysis is used
to identify unobservable states and make suggestions for addi-
tional sensor locations. In practice, however, it is not possible
to place additional sensors, so the available measurements are
used to implement a simple open-loop state estimator with
offset compensation and numerical and experimental results are
presented.
“Crowd contamination”?
(2023)
Misconduct allegations have been found to not only affect the alleged firm but also other, unalleged firms in form of reputational and financial spillover effects. It has remained unexplored, however, how the number of prior allegations against other firms matters for an individual firm currently facing an allegation. Building on behavioral decision theory, we argue that the relationship between allegation prevalence among other firms and investor reaction to a focal allegation is inverted U-shaped. The inverted U-shaped effect is theorized to emerge from the combination of two effects: In the absence of prior allegations against other firms, investors fail to anticipate the focal allegation, and hence react particularly negatively (“anticipation effect”). In the case of many prior allegations against other firms, investors also react particularly negatively because investors perceive the focal allegation as more warranted (“evaluation effect”). The multi-industry, empirical analysis of 8,802 misconduct allegations against US firms between 2007 and 2017 provides support for our predicted, inverted U-shaped effect. Our study complements recent misconduct research on spillover effects by highlighting that not only a current allegation against an individual firm can “contaminate” other, unalleged firms but that also prior allegations against other firms can “contaminate” investor reaction to a focal allegation against an individual firm.
Misbehave like Nobody’s Watching? Investor Attention to Corporate Misconduct and its Implications
(2023)
Cities around the world are facing the implications of a changing climate as an increasingly pressing issue. The negative effects of climate change are already being felt today. Therefore, adaptation to these changes is a mission that every city must master. Leading practices worldwide demonstrate various urban efforts on climate change adaptation (CCA) which are already underway. Above all, the integration of climate data, remote sensing, and in situ data is key to a successful and measurable adaptation strategy. Furthermore, these data can act as a timely decision support tool for municipalities to develop an adaptation strategy, decide which actions to prioritize, and gain the necessary buy-in from local policymakers. The implementation of agile data workflows can facilitate the integration of climate data into climate-resilient urban planning. Due to local specificities, (supra)national, regional, and municipal policies and (by) laws, as well as geographic and related climatic differences worldwide, there is no single path to climate-resilient urban planning. Agile data workflows can support interdepartmental collaboration and, therefore, need to be integrated into existing management processes and government structures. Agile management, which has its origins in software development, can be a way to break down traditional management practices, such as static waterfall models and sluggish stage-gate processes, and enable an increased level of flexibility and agility required when urgent. This paper presents the findings of an empirical case study conducted in cooperation with the City of Constance in southern Germany, which is pursuing a transdisciplinary and trans-sectoral co-development approach to make management processes more agile in the context of climate change adaptation. The aim is to present a possible way of integrating climate data into CCA planning by changing the management approach and implementing a toolbox for low-threshold access to climate data. The city administration, in collaboration with the University of Applied Sciences Constance, the Climate Service Center Germany (GERICS), and the University of Stuttgart, developed a co-creative and participatory project, CoKLIMAx, with the objective of integrating climate data into administrative processes in the form of a toolbox. One key element of CoKLIMAx is the involvement of the population, the city administration, and political decision-makers through targeted communication and regular feedback loops among all involved departments and stakeholder groups. Based on the results of a survey of 72 administrative staff members and a literature review on agile management in municipalities and city administrations, recommendations on a workflow and communication structure for cross-departmental strategies for resilient urban planning in the City of Constance were developed.
This chapter takes a detailed look at the developmental state model and its manifestations in regional development policies. Developmentalist ideas have been waxing and waning across periods of economic boom and bust. Recent years, however, have seen a renaissance of East Asian developmentalism – reminiscent of its heyday in the 1980s and 1990s and most notably driven by the region’s continued economic strength.
The endorsement of state-led modernization, preferential policies, and close state-business relations – which underpinned Japan/Korea/China’s transformations – has also left its mark on current ODA practices in the region and beyond. East Asia’s state agencies are pushing ahead with colossal infrastructure programs – in close cooperation with commercial actors – that advance broad development goals and, at the same time, promotes national interests. Compared to Western OECD peers, Asian development cooperation tends to focus less on neoliberal and democratic principles and, instead, places greater emphasis on state-corporatist and meritocratic ideas.
To what extent East Asia’s infrastructural megaprojects and connectivity corridors across Eurasia and Africa (BRI, EAI, and Partnership for Quality Infrastructure) will generate political momentum for an emergent developmental consensus remains uncertain. The jury is still out when it comes to whether and how Asian developmentalism will take center stage in global development debates. What is clear, however, is that the changing zeitgeist of a less Anglo/Euro-centric world bodes well for more heterodox and diverse ideas on development cooperation.
Southeast Asia
(2023)
Southeast Asia continues to inspire and intrigue observers from all walks
of life due to its diverse cultural traditions and its interwoven threads of
geographical, historical, and social transformation. This essay will explore some of these threads by highlighting Southeast Asia’s (1) deep-rooted diversity, (2) decolonial nation-building, (3) digital leapfrogging, and (4) under-rated prospects
Development of an expert system to overpass citizens technological barriers on smart home and living
(2023)
Adopting new technologies can be overwhelming, even for people with experience in the field. For the general public, learning about new implementations, releases, brands, and enhancements can cause them to lose interest. There is a clear need to create point sources and platforms that provide helpful information about the novel and smart technologies, assisting users, technicians, and providers with products and technologies. The purpose of these platforms is twofold, as they can gather and share information on interests common to manufacturers and vendors. This paper presents the ”Finde-Dein-SmartHome” tool. Developed in association with the Smart Home & Living competence center [5] to help users learn about, understand, and purchase available technologies that meet their home automation needs. This tool aims to lower the usability barrier and guide potential customers to clear their doubts about privacy and pricing. Communities can use the information provided by this tool to identify market trends that could eventually lower costs for providers and incentivize access to innovative home technologies and devices supporting long-term care.
This paper compares two popular scripting implementations for hardware prototyping: Python scripts exe- cut from User-Space and C-based Linux-Driver processes executed from Kernel-Space, which can provide information to researchers when considering one or another in their implementations. Conclusions exhibit that deploying software scripts in the kernel space makes it possible to grant a certain quality of sensor information using a Raspberry Pi without the need for advanced real-time operational systems.
Regional economies clearly benefit from thriving entrepreneurial ecosystems. However, ecosystems are not yet entirely gender-inclusive and therefore are not tapping their full potential. This is most critical with respect to technology-based entrepreneurship which features the largest gender imbalance. Despite the considerably growing amount of literature in the two research fields of female entrepreneurship and entrepreneurial ecosystems, the intersection of the two areas has not yet been outlined. We depict the state of knowledge with a structured review of the literature highlighting bibliometric information, methods used, and the main topics addressed in current articles. From there, recommendations for future research are derived.
This paper applies the concept of Soja’s Thirdspace to the phenomenon of Lazgi dance and tourism in Uzbekistan. In doing so it analyses the different levels of perception (including Firstspace and Secondspace) of Lazgi and tourism via an autoethnographic lens. Complemented by expert interviews, the interaction of Lazgi and tourism is examined and characteristics of the Lazgisphere (world of Lazgi) in Uzbekistan are distilled. The results show that Lazgi is often directly or indirectly connected with tourism in Uzbekistan, but even more so serves to reaffirm national identity.
A post-growth economy is a comparatively new paradigm in the tourism discourse. The aim of this article is to find out the commonalities between this concept and Māori tourism and in which way the latter can contribute to a post-growth economy. A qualitative mixed method approach, including in-depth-interviews, participant observation, and secondary analysis is applied. The results show that there is a lot of overlap between Māori tourism and a post-growth economy. Differences are visible, as well, regarding the value approach of Māori tourism and the indicator approach of a post-growth economy. Especially the social innovation created in Aotearoa New Zealand at the instigation of Māori groups of granting legal personhood to parts of nature may serve as a driver for a form of tourism that is in line with the idea of a post-growth economy.
The aim of this paper is to find out in how accommodation providers in the Seychelles perceive climate change and what mitigation and adaptation measures they can provide. In order to answer these questions, a qualitative mixed-method-approach, comprised of twenty semi-structured interviews, an online-survey and participant observation was used. Results show that accommodation providers especially perceive the effects of climate change that directly affect their business and that they have already partly implemented some mitigation and adaptation measures. However, strategies and regulations are needed at the Seychelles’ government level and on a global level to actually achieve CO2 neutral travel.
Large-scale quantum computers threaten the security of today's public-key cryptography. The McEliece cryptosystem is one of the most promising candidates for post-quantum cryptography. However, the McEliece system has the drawback of large key sizes for the public key. Similar to other public-key cryptosystems, the McEliece system has a comparably high computational complexity. Embedded devices often lack the required computational resources to compute those systems with sufficiently low latency. Hence, those systems require hardware acceleration. Lately, a generalized concatenated code construction was proposed together with a restrictive channel model, which allows for much smaller public keys for comparable security levels. In this work, we propose a hardware decoder suitable for a McEliece system based on these generalized concatenated codes. The results show that those systems are suitable for resource-constrained embedded devices.
Public-key cryptographic algorithms are an essential part of todays cyber security, since those are required for key exchange protocols, digital signatures, and authentication. But large scale quantum computers threaten the security of the most widely used public-key cryptosystems. Hence, the National Institute of Standards and Technology ( NIST ) is currently in a standardization process for post-quantum secure public-key cryptography. One type of such systems is based on the NP-complete problem of decoding random linear codes and therefore called code-based cryptography. The best-known code-based cryptographic system is the McEliece system proposed in 1978 by Robert McEliece. It uses a scrambled generator matrix as a public key and the original generator matrix as well as the scrambling as private key. When encrypting a message it is encoded in the public code and a random but correctable error vector is added. Only the legitimate receiver can correct the errors and decrypt the message using the knowledge of the private key generator matrix. The original proposal of the McEliece system was based on binary Goppa codes, which are also considered for standardization. While those codes seem to be a secure choice, the public keys are extremely large, limiting the practicality of those systems. Many different code families were proposed for the McEliece system, but many of them are considered insecure since attacks exist, which use the known code structure to recover the private key. The security of code-based cryptosystems mainly depends on the number of errors added by the sender, which is limited by the error correction capability of the code. Hence, in order to obtain a high security for relatively short codes one needs a high error correction capability. Therefore maximum distance separable ( MDS ) codes were proposed for those systems, since those are optimal for the Hamming distance. In order to increase the error correction capability we propose q -ary codes over different metrics. There are many code families that have a higher minimum distance in some other metric than in the Hamming metric, leading to increased error correction capability over this metric. To make use of this one needs to restrict not only the number of errors but also their value. In this work, we propose the weight-one error channel, which restricts the error values to weight one and can be applied for different metrics. In addition we propose some concatenated code constructions, which make use of this restriction of error values. For each of these constructions we discuss the usability in code-based cryptography and compare them to other state-of-the-art code-based cryptosystems. The proposed code constructions show that restricting the error values allows for significantly lower public key sizes for code-based cryptographic systems. Furthermore, the use of concatenated code constructions allows for low complexity decoding and therefore an efficient cryptosystem.
Infrastructure-making in interwar India was a dynamic, multilayered process involving roads and vehicles in urban and rural sites. One of their strongest playgrounds was Bombay Presidency and the Central Provinces in central and western India. Focusing on this region in the interwar period, this paper analyzes the varied relationship between peasant households and town-centred modernizing agents in the making of road transport infrastructures. The central argument of this paper is about the persistence of bullock carts over motor cars in the region. This persistence was grounded in the specific regional environment, the effects of the 1930s economic depression, and the priorities of social classes. Pinpointing these connections, the paper highlights that “modernization” of infrastructure was not a simple, linear process of progressivist change, nor did it mean the survival of apparently “old” technologies in the modern era. Instead, the paper pays attention to conflicting social complexities, implications, and meanings of the connection between infrastructure and modernity that modernization assumptions often overlook. Here, the paper shows how technological change occurred as a result of real, material class interests pulling infrastructural technology in different directions. This was where and why arguments of road-motor lobbyists and cart advocates eventually clashed, and Gandhian social workers resisted motor transport in defense of peasant interests.
Trotz des dringenden Erfordernisses einer nachhaltigen und unabhängigen Energieerzeugung und bereits steigender Anteile photovoltaisch erzeugten Stroms stockt die Verbreitung der bauwerkintegrierten Photovoltaik (BIPV). Zahlreiche „Leuchtturm“-Projekte zeigen das große ästhetische Potential solaraktiver Bauteile und dennoch werden insbesondere von Architekt/innen-Seite neben vermeintlichen Einschränkungen in der planerischen Freiheit immer wieder auch gestalterische Vorbehalte angeführt.
Bisher wurde im Zusammenhang mit PV-Bauteilen schwerpunktmäßig die technische und konstruktive Einfügung thematisiert. Um einen Beitrag zur Diskussion um die Entwicklung visuell überzeugender Ergebnisse zu leisten, die verhindern, dass photovoltaische Bauteile am Gebäude als Fremdkörper wahrgenommen werden, ermittelt die vorliegende Arbeit auf der Grundlage ästhetischer Architekturtheorien allgemeingültige Kriterien für architektonische Wirkungsqualität und transferiert diese auf den Bereich der BIPV-Gestaltung.
Dabei werden zum Verständnis erforderliche Grundlagen der BIPV-Systemtechnik vermittelt sowie verfügbare Bauteile und die unterschiedlichen Akteure und Ziele bei der Gestaltung von BIPV aufzeigt. Auch die speziellen funktionalen und technischen Anforderungen, die PV-Bauteile als „aktive“ Bauteile stellen, werden berücksichtigt und hinsichtlich ihrer hemmenden oder synergetischen Wechselwirkungen differenziert.
Im Rahmen einer Projektstudie finden die oben genannten Kriterien Anwendung auf 13 „best practice“-Beispiele aktueller Wettbewerbsgewinner des vom Solarenergieförderverein Bayern e. V. (SeV) ausgelobten „Architekturpreis Gebäudeintegrierte Solartechnik“, die in Form von Steckbriefen vergleichend dargestellt werden.
Das Ergebnis ist die Synthese eines Kriterienkatalogs als Orientierungs-, Planungs- und Kommunikationswerkzeug, in dem alle Ergebnisse systematisiert zusammengestellt werden.
Ergänzend wird in einem kurzen Exkurs auf von der Hauptuntersuchung ausgenommene, für die Praxis aber relevante Schnittstellen zu wirtschaftlichen Aspekten eingegangen.
MiniKueWeE-Abwärmenutzung
(2023)
Das Thema Energiewende ist derzeit so aktuell wie nie. Neben dem Umstieg von fossilen auf erneuerbare Energien gewinnt auch die Energieeffizienz auf allen Ebenen immer mehr an Bedeutung. Dies gilt besonders für viele Teile des Gebäudebereichs, wo heute eine beachtliche Energiemenge, nicht nur für die Wärmeerzeugung, sondern auch zur Raumkühlung benötigt wird (Umweltbundesamt 2020). In Anbetracht der Klimaveränderungen wird der Kühlbedarf in den nächsten Jahrzehnten zudem noch weiter ansteigen. Aus diesem Grund gibt es einen großen Bedarf an innovativen Lösungen, welche eine effiziente Raumkühlung unter möglichst geringem Energieeinsatz gewährleisten. Die vorliegende Projektarbeit untersucht einen Teilbereich einer solchen Lösung. Genaueres zum Hintergrund, den technischen Randbedingungen sowie den Zielen des Projekts, wird in den folgenden Abschnitten erläutert.
Purpose
In order to combat climate change and safeguard a liveable future we need fundamental and rapid social change. Climate communication can play an important role to nurture the public engagement needed for this change, and higher education for sustainability can learn from climate communication.
Approach
The scientific evidence base on climate communication for effective public engagement is summarised into ten key principles, including ‘basing communication on people’s values’, ‘conscious use of framing’, and ‘turning concern into action’. Based on the author’s perspective and experience in the university context, implications are explored for sustainability in higher education.
Findings
The article provides suggestions for teaching (e.g. complement information with consistent behaviour by the lecturer, integrate local stories, and provide students with basic skills to communicate climate effectively), for research (e.g. make teaching for effective engagement the subject of applied research), for universities’ third mission to contribute to sustainable development
in the society (e.g. provide climate communication trainings to empower local stakeholders), andgreening the campus (develop a proper engagement infrastructure, e.g. by a university storytelling exchange on climate action).
Originality
The article provides an up-to-date overview of climate communication research, which is in itself original. This evidence base holds interesting learnings for institutions of higher education, and the link between climate communication and universities has so far not been explored comprehensively.
Background: Polysomnography (PSG) is the gold standard for detecting obstructive sleep apnea (OSA). However, this technique has many disadvantages when using it outside the hospital or for daily use. Portable monitors (PMs) aim to streamline the OSA detection process through deep learning (DL).
Materials and methods: We studied how to detect OSA events and calculate the apnea-hypopnea index (AHI) by using deep learning models that aim to be implemented on PMs. Several deep learning models are presented after being trained on polysomnography data from the National Sleep Research Resource (NSRR) repository. The best hyperparameters for the DL architecture are presented. In addition, emphasis is focused on model explainability techniques, concretely on Gradient-weighted Class Activation Mapping (Grad-CAM).
Results: The results for the best DL model are presented and analyzed. The interpretability of the DL model is also analyzed by studying the regions of the signals that are most relevant for the model to make the decision. The model that yields the best result is a one-dimensional convolutional neural network (1D-CNN) with 84.3% accuracy.
Conclusion: The use of PMs using machine learning techniques for detecting OSA events still has a long way to go. However, our method for developing explainable DL models demonstrates that PMs appear to be a promising alternative to PSG in the future for the detection of obstructive apnea events and the automatic calculation of AHI.
The massive use of patient data for the training of artificial intelligence algorithms is common nowadays in medicine. In this scientific work, a statistical analysis of one of the most used datasets for the training of artificial intelligence models for the detection of sleep disorders is performed: sleep health heart study 2. This study focuses on determining whether the gender and age of the patients have a relevant influence to consider working with differentiated datasets based on these variables for the training of artificial intelligence models.
The development of automatic solutions for the detection of physiological events of interest is booming. Improvements in the collection and storage of large amounts of healthcare data allow access to these data faster and more efficiently. This fact means that the development of artificial intelligence models for the detection and monitoring of a large number of pathologies is becoming increasingly common in the medical field. In particular, developing deep learning models for detecting obstructive apnea (OSA) events is at the forefront. Numerous scientific studies focus on the architecture of the models and the results that these models can provide in terms of OSA classification and Apnea-Hypopnea-Index (AHI) calculation. However, little focus is put on other aspects of great relevance that are crucial for the training and performance of the models. Among these aspects can be found the set of physiological signals used and the preprocessing tasks prior to model training. This paper covers the essential requirements that must be considered before training the deep learning model for obstructive sleep apnea detection, in addition to covering solutions that currently exist in the scientific literature by analyzing the preprocessing tasks prior to training.
Sleep is a multi-dimensional influencing factor on physical health, cognitive function, emotional well-being, mental health, daily performance, and productivity. The barriers such as time-consuming, invasiveness, and expense have caused a gradual shift in sleep monitoring from traditional and standard in-lab approach, e. g., polysomnography (PSG) to unobtrusive and noninvasive in-home sleep monitoring, yet further improvement is required. Despite an increasing interest in fiberoptic-based methods for cardiorespiratory estimation, the traditional mechanical-based sensors consist of force-sensitive resistors (FSR), lead zirconate titanate piezoelectric (PZT), and accelerometers yet serve as the dominant approach. The part of popularity lies in reducing the system’s complexity, expense, easy maintenance, and user-friendliness. However, care must be taken regarding the performance of such sensors with respect to accuracy and calibration.
Measuring cardiorespiratory parameters in sleep, using non-contact sensors and the Ballistocardiography technique has received much attention due to the low-cost, unobtrusive, and non-invasive method. Designing a user-friendly, simple-to-use, and easy-to-deployment preserving less errorprone remains open and challenging due to the complex morphology of the signal. In this work, using four forcesensitive resistor sensors, we conducted a study by designing four distributions of sensors, in order to simplify the complexity of the system by identifying the region of interest for heartbeat and respiration measurement. The sensors are deployed under the mattress and attached to the bed frame without any interference with the subjects. The four distributions are combined in two linear horizontal, one linear vertical, and one square, covering the influencing region in cardiorespiratory activities. We recruited 4 subjects and acquired data in four regular sleeping positions, each for a duration of 80 seconds. The signal processing was performed using discrete wavelet transform bior 3.9 and smooth level of 4 as well as bandpass filtering. The results indicate that we have achieved the mean absolute error of 2.35 and 4.34 for respiration and heartbeat, respectively. The results recommend the efficiency of a triangleshaped structure of three sensors for measuring heartbeat and respiration parameters in all four regular sleeping positions.
Die durch kleine und mittelständische Unternehmen geprägte Investitionsgüterindustrie steht aufgrund der zunehmenden Internationalisierung im Servicegeschäft vor großen Herausforderungen. Mitarbeiterengpässe, hohe Prozesskosten und unzureichendes Wissensmanagement machen den Service zur potenziellen betriebs- und volkswirtschaftlichen Wachstumsbremse. Durch die Digitalisierung entstehen aber auch große Nutzenpotenziale im Servicegeschäft. Ziel des im Projekt SerWiss entwickelten integrierten Ansatzes ist es, kleine und mittelständische Anbieter von Investitionsgütern zu befähigen, Servicewissen auf der Basis eines digitalen Lösungsansatzes unter Gewährleistung einer humanen Arbeitsgestaltung effizient zu generieren, zu strukturieren und international bereitzustellen bzw. zu vermarkten.
Der Kundenservice von morgen
(2023)
Die digitale Selbstbedienung im Einzelhandel und anderen Dienstleistungsbereichen verändert die Konsumwelt. Self-Services werden zunehmend von Konsumenten aller Altersklassen genutzt. Der Handel muss seine Servicekanäle hinterfragen und vermehrt auf Self-Service als Kundenkontaktpunkt setzen. Andere Branchen haben diesbezüglich bereits Lösungen umgesetzt. Vor diesem Hintergrund analysiert der Beitrag die Nutzung von Self-Service-Lösungen in Abhängigkeit von der Generationen-Zugehörigkeit und gibt Handlungsempfehlungen für KMU aus dem Einzelhandel.
This paper aims to apply the basics of the Service-Dominant Logic, especially the concept of creating benefits through serving, to the stationary retail industry. In the industrial context, the shift from a product-driven point of view to a service-driven perspective has been discussed widely. However, there are only few connections to how this can be applied to the retail sector on a B2C-level and how retailers can use smart services in order to enable customer engagement, loyalty and retention. The expectations of customers towards future stationary retail develop significantly as consumers got used to the comfort of online shopping. Especially the younger generation—the Generation Z—seems to have changed their priorities from the bare purchase of products to an experience- and service-driven approach when shopping over-the-counter. To stay successful long-term, companies from this sector need to adapt to the expectations of their future main customer group. Therefore, this paper will analyse the specific needs of Generation Z, explain how smart services contribute to creating benefit for this customer group and how this affects the economic sustainability of these firms.
Die durch KMU geprägte Investitionsgüterindustrie steht aufgrund der zunehmenden Internationalisierung im Servicegeschäft, Mitarbeiterengpässen, hohen Prozesskosten sowie fehlendem Wissensmanagment vor großen Herausforderungen. Durch die Digitalisierung entstehen große Nutzenpotenziale im Servicegeschäft. Vor diesem Hintergrund wurde ein auf den Methoden Intelligent Swarming und Knowledge Centered Service basierender, integrierter Ansatz entwickelt, der KMU aus der Investitionsgüterindustrie befähigt, Servicewissen effizient zu generieren, zu strukturieren und international zu vermarkten.
Im Investitionsgüterservice ist Wissen längst zu einem zentralen Erfolgshebel geworden, sowohl zur Steigerung der Prozesseffektivität und -effizienz als auch als Fundament für werthaltige Geschäftsmodelle. Das Management Service-relevanten Wissens ist für kleine und mittelständische Unternehmen der Investitionsgüterindustrie jedoch oftmals eine nicht zu unterschätzende Herausforderung, welche weit über IT-technische Aspekte hinausreicht. In dem vom BMBF sowie vom ESF (ko)finanzierten Projekt „SerWiss“ wurde vor diesem Hintergrund ein umfassender Lösungsansatz entwickelt und bei zwei Projektpartnern aus der Investitionsgüterindustrie prototypisch umgesetzt.
Die Berücksichtigung ökologischer und sozialer Gesichtspunkte in der Konzeption, Planung und Errichtung von Gebäuden hat in den vergangenen Jahren großen Einfluss auf Marktfähigkeit der Immobilien gewonnen. Regulatorische Rahmenwerke wie die Taxonomie-Verordnung der Europäischen Union formulieren die klare Anforderung an die Bauwirtschaft dem Schutz von Mensch und Natur mehr Bedeutung einzuräumen. Nur mit einem wesentlichen Beitrag zu den Klimazielen der Europäischen Union wird es der Branche langfristig möglich sein sich einen uneingeschränkten Zugang zum Investorenmarkt zu sichern.
Die vorliegende wissenschaftliche Arbeit widmet sich dem Kriterienkatalog der Deutschen Gesellschaft für Nachhaltiges Bauen e.V. und legt Übereinstimmungen mit den technischen Bewertungskriterien der EU-Taxonomie Verordnung offen. Der im Frühjahr 2023 erschienen Kriterienkatalog umfasst eine Vielzahl von Kriterien, anhand derer Gebäude auf Nachhaltigkeit geprüft werden. Im Vergleich zu der Vorgängerversion aus dem Jahr 2018 wurden erhebliche Änderungen eingearbeitet. Besonders hervorzuheben sind neue technische Prüfkriterien im Bereich Klimaschutz, Ressourcengewinnung, Biodiversität und Kreislaufwirtschaft. Die Angleichung der Berechnungsmethode für die Ökobilanzen an das bundeseigene „Qualitätssiegel Nachhaltiges Gebäude“, die Mindestanforderung nach dem erhöhten Einsatz von nachhaltig gewachsenem Holz, die Prüfung spezifischer Zielquoten bei dem Einsatz von Recyclingbeton sowie Anforderungen an die Zirkularität sind nur ein Teil der Neuerungen. Für die zusätzlichen Anforderung müssen Projektentwickler mit Mehrkosten im hohen sechsstelligen Bereich im Vergleich zu der Vorgängerversion rechnen. Vorteile der Neuauflage des Kriterienkataloges sind eine erhöhte Übereinstimmung mit den Nachhaltigkeitsanforderungen der Europäischen Union. Es werden jedoch nicht alle Anforderungen erfüllt. Nachweise für den Primärenergiebedarf, die Schadstoffbelastung von Bauteilen bzw. -materialien und eine Umweltverträglichkeitsprüfung müssen zusätzlich zu dem Kriterienkatalog der Deutschen Gesellschaft für Nachhaltiges Bauen geleistet werden. Insgesamt ebnen die Kriterien der Deutschen Gesellschaft für Nachhaltiges Bauen aber den Weg hin zu einer EU-Konformität und helfen Projektentwicklern Immobilien erfolgreich auf dem Markt zu positionieren.
Insecurity Refactoring is a change to the internal structure of software to inject a vulnerability without changing the observable behavior in a normal use case scenario. An implementation of Insecurity Refactoring is formally explained to inject vulnerabilities in source code projects by using static code analysis. It creates learning examples with source code patterns from known vulnerabilities.
Insecurity Refactoring is achieved by creating an Adversary Controlled Input Dataflow tree based on a Code Property Graph. The tree is used to find possible injection paths. Transformation of the possible injection paths allows to inject vulnerabilities. Insertion of data flow patterns introduces different code patterns from related Common Vulnerabilities and Exposures (CVE) reports. The approach is evaluated on 307 open source projects. Additionally, insecurity-refactored projects are deployed in virtual machines to be used as learning examples. Different static code analysis tools, dynamic tools and manual inspections are used with modified projects to confirm the presence of vulnerabilities.
The results show that in 8.1% of the open source projects it is possible to inject vulnerabilities. Different inspected code patterns from CVE reports can be inserted using corresponding data flow patterns. Furthermore the results reveal that the injected vulnerabilities are useful for a small sample size of attendees (n=16). Insecurity Refactoring is useful to automatically generate learning examples to improve software security training. It uses real projects as base whereas the injected vulnerabilities stem from real CVE reports. This makes the injected vulnerabilities unique and realistic.
Das Management von Aktienfonds strebt effiziente Mischungen von Aktien an. Nachdem diese durch Optimierungsverfahren ermittelt wurden, müssen sie aus ökonomischen oder rechtlichen Gründen oft angepasst werden mit der Konsequenz, dass die Lösungen nicht mehr effizient sind. Ein rechtlicher Grund kann bei einem öffentlich angebotenen Aktienfond der Artikel 52(2) der EU-Richtlinie 2009/65/EC bzw. das KAGB § 206 sein. Ein Teil der Richtlinie besagt z.B., dass in eine Aktie nie mehr als 10% des Budgets investiert werden kann. Diese Regeln insgesamt sich auch als 5-10-40-Bedingung bekannt. Um derartige Risikobeschränkungen in der Portfoliooptimierung zu integrieren wurden zwei Optimierungsmodelle entwickelt – ein quadratisches und ein lineares. Die Modelle wurden anhand von historischen Renditedaten des HDAX getestet. Das lineare Modell zeigt, dass die Vorgaben der EU-Richtlinie die angestrebte Volatilitätsreduktion erreicht. Diese Risikobeschränkung hat aber einen Preis, der in den Währungen „Renditeverlust“ bzw. „Volatilitätszuwachs“ ausgedrückt werden kann. Bei gleicher Volatilität erzielte das nicht durch die 5-10-40-Bedingung eingeschränkte Portfolio eine ca. 10% höhere Jahresrendite. Der „Volatilitätszuwachs“ ist im Umfeld des minimalen Volatilitätspunktes (MVP) gering, kann aber bis zu 25% betragen, wenn Portfolios die unter der 5-10-40-Bedingung ermittelt wurden verglichen werden mit uneingeschränkt optimierten Portfolios bei jeweils gleicher Rendite. Das quadratische Modell baut auf dem Ansatz von H. Markowitz auf und zeigt einen flexibleren Weg der Risikobegrenzung der zu vergleichbaren Resultaten führt.
Das Projekt eFlow, an dem unter anderem die HTWG Konstanz seit 2012 forscht, simuliert mit Hilfe einer mathematischen Simulation wie sich Menschenmassen verhalten, wenn sie ein vorgegebenes Gelände verlassen sollen. Die Simulation baut auf einen Ansatz der Finite Elemente Methode auf, in der mehrere gekoppelte Differenzialgleichungen berechnet werden müssen. Diese Berechnungen erweisen sich gerade bei komplexen Szenarien mit großem Gelände und vielen Personen als sehr rechenintensiv. Ziel dieser Bachelorarbeit ist es ein Surrogate Modell zu erstellen, welches basierend auf machine-learning Ansätzen im spezifischen auf Regressionsmethoden Ergebnisse der Simulation vorhersagen soll. Somit müssen Datensätze generiert werden. Diese entstehen durch wiederholte Durchläufe der Simulation, in der jeweils die Eingabeparameter, die in das Regressionsmodell einfließen sollen variiert werden und mit dem entsprechenden Ergebnis der Simulation verknüpft werden. Die Regressionsansätze werden dabei pro Durchlauf komplexer, in dem jeweils zusätzliche Eingabeparameter mit in die Datengenerierung aufgenommen werden. Es soll überprüft werden, ob diese Simulation mittels machine-learning Ansätzen reproduzierbar ist. Basierend auf diesen Surrogate Modellen soll es möglich gemacht werden, Situationen in Echtzeit zu überprüfen, ohne dabei den Weg der rechenaufwendigen Simulation zu gehen. Die Ergebnisse bestätigen, dass die mathematische Simulation mittels Regression reproduzierbar ist. Es erweist sich jedoch als sehr rechenaufwendig, Daten zu sammeln, um genügend Eingabeparameter mit in die Regressionsmethode einfließen zu lassen. Diese Arbeit gestaltet somit eine Vorstudie zur Umsetzung eines ausgereiften Surrogate Modells, welches jegliche Eingabeparameter der Simulation berücksichtigen kann.