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Units of measure with prefixes and conversion rules are given a formal semantic model in terms of categorial group theory. Basic structures and both natural and contingent semantic operations are defined. Conversion rules are represented as a class of ternary relations with both group-like and category-like properties. A hierarchy of subclasses is explored, each satisfying stronger useful algebraic properties than the preceding, culminating in a direct efficient conversion-by-rewriting algorithm.
This demo explores an innovative artistic installation that creatively visualizes global temperature data using graphical visualization and motion capture technologies. By combining video-based posture capturing of nearby individuals with a dynamically rendered 3D model of the planet Earth, this installation offers an interactive and immersive experience. The goal is to transform climate change data into an engaging visual format, making it more accessible and impactful for a wide range of audiences.
Unleashing the power of remote sensing data in aquatic research: Guidelines for optimal utilization
(2024)
The growing utilization of remote sensing data in lake studies provides crucial spatial insights into biogeochemistry and biology. However, clarity regarding the development and intended use of remote sensing products is often lacking. This letter aims to elucidate the tradeoffs for the utilization of remote sensing data in limnological studies with an example of based on the estimation of chlorophyll a due to its importance as a water quality indicator. The analysis initiates with a meticulous product selection, requiring an evaluation of its capacity to address the optical complexity of freshwater systems. Assessing atmospheric correction and product limitations ensures alignment with the study's objectives. Subsequently, rigorous validation of remote sensing products is essential, accompanied by a cautious interpretation of the data. This letter advocates for the use of remote sensing data, offering key strategies for their optimal utilization in lake studies.
When small- and medium-sized Enterprises (SMEs) pursue digital transformation (DT) projects, awareness for available solutions and exploration of best practices and collaboration opportunities belong to key activities. This short paper presents background, design and preliminary evaluation of an open innovation (OI) platform for SME DT, which showcases projects completed by collaborating expert institutions and offers new project pitches. Initial findings from user tests with SME practitioners indicate that the solution supports SMEs in DT exploration phases. Moreover, insights on SME OI platform design criteria are derived.
The 300th birthday of the world-famous German philosopher Immanuel Kant (1724-1804) in 2024 offers an extraordinary opportunity to explore integrating advanced technologies into cultural mega-events. This paper examines the opportunities and challenges of using various technologies, such as Extended Reality (XR) and Visual Effects (VFX), to bring this essential European intellectual to a broader audience. These technologies, including technological advances based on real-time rendering in conjunction with LED volumes and high-quality 3D assets, offer immersive and interactive event experiences. However, the use of these technologies presents specific challenges, such as processing limitations and the need to create specialized content, including the development of 3D models relevant to the life and philosophy of Immanuel Kant. This article provides an overview of the current state of such opportunities and challenges and examines their application in the context of this cultural mega-event. The aim is to create a compelling event experience, e.g., as part of a museum visit, while simultaneously using technology in a meaningful educational way. It is essential not to overload historical and intellectual personalities such as Immanuel Kant with technological possibilities in the sense of an ethical responsibility. At the same time, the creation and communication of knowledge require explanation in a museum context or another explanatory framework.
SMath Studio is mathematical notebook software similar to Mathcad. Its outstanding and intuitive support for scientific units makes it an invaluable asset in higher engineering education. SMath Studio has been used for more than ten years in various courses at Brandenburg University of Applied Sciences, Germany (Technische Hochschule Brandenburg, THB). To enhance the usability of the software, substantial contributions have been made. One of them is the Maxima plugin for access to the free and open-source computer algebra system Maxima. This plugin combines the flexible notebook format of SMath Studio with powerful symbolic functions like integrals and solvers for algebraic and differential equations. Additionally, the plugin adds interactive 3D graphics to SMath. The paper discusses the basic design, features, and limitations, and showcases some applications.
IT Service Management (ITSM) education is nowadays an established subject of IT-related higher education programs worldwide. The recent years have witnessed significant developments in software and ITSM frameworks, which underscores the importance of adapting educational formats to meet the latest standards. Recent developments include the introduction of practice-oriented approaches and case-based learning. Building upon previous literature, this study describes and evaluates the first iteration of a teaching case integrating a simulation game for practicing ITIL® 4 foundations in an undergraduate ITSM curriculum. The game-based approach shows scalability and dynamism, fostering high student engagement and content comprehension. It represents a promising avenue for training IT workers and contributes to ongoing ITSM education development.
The attraction of insects to artificial light is a global environmental problem with far-reaching implications for ecosystems. Since light pollution is rarely integrated into conservation approaches, effective mitigation strategies towards environmentally friendly lighting that drastically reduce insect attraction are urgently needed. Here, we tested novel luminaires in two experiments (i) at a controlled experimental field site and (ii) on streets within three municipalities. The luminaires are individually tailored to only emit light onto the target area and to reduce spill light. In addition, a customized shielding renders the light source nearly invisible beyond the lit area. We show that these novel luminaires significantly reduce the attraction effect on flying insects compared to different conventional luminaires with the same illuminance on the ground. This underlines the huge potential of spatially optimized lighting to help to bend the curve of global insect decline without compromising human safety aspects. A customized light distribution should therefore be part of sustainable future lighting concepts, most relevant in the vicinity of protected areas.
Live music is often linked to elaborate light shows, particularly at large outdoor music festivals. However, artificial light at night is one form of environmental pollution, light pollution, and because outdoor festivals emit a substantial amount of artificial light into the environment, they are a potential source of light pollution. So far, no studies that quantified the impact of such festivals on urban light pollution and skyglow exist. Here, the light pollution produced by a major rock festival (Lollapalooza Berlin 2016 with 70,000 visitors per day in an urban park) was investigated with ground-based radiometry and night-time light data. A small night-sky radiometer installed near the main stages and a calibrated digital camera from a nearby observation spot inside of the park were used to quantify changes in night sky brightness and direct light emissions within the park. The impact of the music festival on the urban skyglow was indeed measurable. Zenith luminance increased locally by up to a factor of 8 and illuminance increased by about 50% at the observation spot within the park. The radiance detected by night-time satellite was also increased during the festival. This is the first time, that light pollution from such a major rock music event was quantified.
Light pollution has increased globally, with 80% of the total population now living under light-polluted skies. In this Review, we elucidate the scope and importance of light pollution and discuss techniques to monitor it. In urban areas, light emissions from sources such as street lights lead to a zenith radiance 40 times larger than that of an unpolluted night sky. Non-urban areas account for over 50% of the total night-time light observed by satellites, with contributions from sources such as transportation networks and resource extraction. Artificial light can disturb the migratory and reproductive behaviours of animals even at the low illuminances from diffuse skyglow. Additionally, lighting (indoor and outdoor) accounts for 20% of global electricity consumption and 6% of CO2 emissions, leading to indirect environmental impacts and a financial cost. However, existing monitoring techniques can only perform a limited number of measurements throughout the night and lack spectral and spatial resolution. Therefore, satellites with improved spectral and spatial resolution are needed to enable time series analysis of light pollution trends throughout the night.
Artificial light at night originating from bridge illumination can cause polarised light pollution when it is reflected at water body surfaces. This alters the optical conditions of a river at night and potentially interferes with natural polarisation signals from, for example, moonlight. Therefore, this type of light pollution could detrimentally change the behaviour of organisms sensitive to polarised light, a navigational cue and signal known to be used e.g. by flying water-seeking insects to detect suitable aquatic habitats to reproduce and lay eggs. So far, polarised light pollution from artificial light at night is understudied. Here, we quantify polarised light pollution at the water’s surface near seven illuminated bridges crossing the river Spree in Berlin. Our measurements show for the first time, that nocturnal bridge illumination induces polarised light pollution towards potential flying paths of polarotactic aquatic insects. On average, around 9% of the water surfaces at the investigated bridges were highly polluted by polarised light, with values ranging between 3 and 12 % for each bridge. Thus, polarised light pollution from artificial light at night is an emergent pollutant for aquatic systems. Future work on this topic should include more comprehensive measurements, further ecological studies on its impacts and the development of sustainable lighting solutions that can contribute to the protection of riverine nightscapes.
Coarsening of Quasi Two-Dimensional Emulsions Formed by Islands in Free-Standing Smectic Films
(2024)
We study the coarsening behavior of assemblies of islands on smectic A freely suspended films in ISS microgravity experiments. The islands can be regarded as liquid inclusions in a two-dimensional fluid in analogy to liquid droplets of the discontinuous phase of an emulsion. The coarsening is effectuated by two processes, predominantly by island coalescence, but to some extend also by Ostwald ripening, whereby large islands grow at the expense of surrounding smaller ones. A peculiarity of this system is that the continuous and the discontinuous phases consist of the same material. We determine the dynamics, analyze the self-similar aging of the island size distribution and discuss characteristic exponents of the mean island growth.
Smectic islands on a thin freely suspended smectic film form a quasi two-dimensional emulsion, without a liquid subphase. We describe the coarsening dynamics that involves island coalescence and Ostwald ripening.
Finding an optimal balance between risk and returns in investment portfolios is a central challenge in quantitative finance, often addressed through Markowitz portfolio theory (MPT). While traditional portfolio optimization is carried out in a continuous fashion, as if stocks could be bought in fractional increments, practical implementations often resort to approximations, as fractional stocks are typically not tradeable. While these approximations are effective for large investment budgets, they deteriorate as budgets decrease. To alleviate this issue, a discrete Markowitz portfolio theory (DMPT) with finite budgets and integer stock weights can be formulated, but results in a non-polynomial (NP)-hard problem. Recent progress in quantum processing units (QPUs), including quantum annealers, makes solving DMPT problems feasible. Our study explores portfolio optimization on quantum annealers, establishing a mapping between continuous and discrete Markowitz portfolio theories. We find that correctly normalized discrete portfolios converge to continuous solutions as budgets increase. Our DMPT implementation provides efficient frontier solutions, outperforming traditional rounding methods, even for moderate budgets. Responding to the demand for environmentally and socially responsible investments, we enhance our discrete portfolio optimization with ESG (environmental, social, governance) ratings for EURO STOXX 50 index stocks. We introduce a utility function incorporating ESG ratings to balance risk, return and ESG friendliness, and discuss implications for ESG-aware investors.
Deutsche Telekom, one of the world's leading integrated telecommunications companies, has recently shifted its focus in event marketing to prioritize more personal co-creational communication on regional occasions, rather than largescale events. This paper outlines the three-part LAW-principle that Deutsche Telekom follows in its brand communication in Germany, providing examples for each of the three pillars. The co-creation resulting from brand communication is changing the role of marketing and brand practitioners. They are now required to negotiate with various stakeholders.
The energy transfer between bouncing particles and rigid boundaries during impacts is crucially influenced not only by restitution coefficients of the material but also by particle shapes. This is particularly important when such particles are mechanically agitated with vibrating plates. Inertial measurement units are able to measure all acceleration and rotational velocity components of an object and store these data for subsequent analysis. We employ them to measure the dynamics of cubes and icosahedra on vibrating plates to study the efficiency of energy transfer into the individual degrees of freedom (DOFs) of the excited object. The rotational DOFs turn out to be much less excited than the vertical translational motion. Most remarkably, there is only little difference between the two Platonic solids in both the absolute energies and the energy partition ratios.
The German government's initiative to cover 80% of the gross electricity supply with renewable energies by 2050 brings considerable ecological benefits, but also poses several challenges. One of these challenges is the growing number of photovoltaic systems (PV systems), which, due to their high feed-in power, already pose a risk to the security of the electricity distribution grid during long periods of sunny weather. To counteract this, active research is being carried out in the field of PV power forecasting. This research is primarily aimed at providing the grid operator with a predicted power output, which enables a longer planning horizon and thus increases the operational grid security. However, the considerable annual electricity consumption of private households and the increasing spread of PV systems for self-consumption show that the energy behavior of households, especially self-consumption, also influences grid security. Additionally, households have an incentive to boost their self-consumption because the cost of drawing each kilowatt-hour from the grid is substantially higher than the compensation received for injecting an equivalent amount of energy back into the grid. However, as of now, there is no software available that easily enables households to tailor the usage patterns of their electrical appliances according to a photovoltaic (PV) forecast. The project described here aims to close this gap by creating such software. Various PV forecasting models are used and tested for their suitability for this purpose. A self-generated optimization process is implemented in this project to optimize the consumer configuration based on the PV forecasts. The here-developed tool enables the user to enter parameters for his PV system and the specific load profiles of his electrical appliances. Based on this data, the optimization algorithm determines a consumption plan with a forecast horizon until the end of the next day that maximizes the user's self-consumption. To validate the tool, the optimization process is carried out over a period of 60 days using a predefined scenario and the results are compared with a scenario in which the electrical appliances are intuitively operated at midday. The analysis of these results ultimately shows the potential impact of such a tool on the economic efficiency of private households and the supply stability.
1. Introduction
(2023)
Illuminated bridges have become important assets to navigable aquatic systems. However, if artificial light at night (ALAN) from illuminated bridges reaches aquatic habitats, such as rivers, it can threaten the river's natural heterogeneity and alter the behavioural responses of migratory fish. Here, via a pilot study, we quantified levels of ALAN at illuminated bridges that cross a river and, propose a conceptual model to estimate its potential implications on two migrating fish species with contrasting life histories. Night-time light measurements on the river Spree in Berlin were performed continuously along a transect and in detail at seven illuminated bridges. Photometric data of the pilot study showed rapidly increased and decreased light levels at several illuminated bridges from which we derived several model illumination scenarios. These illumination scenarios and their potential effect on migrating Atlantic salmon smolts (Salmo salar) and European silver eel (Anguilla anguilla) are presented as a conceptual model, considering illuminated bridges as behavioural barriers to fish migration. ALAN's adverse effects on freshwater habitats must be better researched, understood, managed, and properly communicated to develop future sustainable lighting practices and policies that preserve riverscapes and their biodiversity.
Propagation of information technology in the increasingly diverse domains, raises question concerning moral implications. While the number of ethical principles in the IT design is growing, they do not necessarily apply to specific products, which means developers and e.g. purchasing agent need to contextualize them for each specific IT product. This paper describes an actionable artifact that allows assessment of ethical non-functional requirements of an information system through operationalization of ethical values, Ethical Software Assessment Tool (ESAT). It is based on a survey of values that are currently considered in research and practice as well as in legal initiatives in IT context. The ethical approach and principles operationalized in ESAT are presented and discussed.
Laws are the reflection of the ethical and moral principles of the society. While the use of technology influences users’ behavior in a pace that is affected by the technology introduction to the market, legal activities can be driven by the society as the results of such interactions. This scenario analysis- based research focuses on a classic but fictional food recommender system and the ethical issues that might occur from its usage. The recommender system is taken here as an example of machine learning-based systems (MLS) that can often be found in the individual, business and administrative applications. The research compares the existing legal solutions, with the focus on the GDPR legislation, and the discovered ethical issues. The ethical analysis is led along the ALTAI principles suggested by the European Commission, the common good approach as well as the general principles constituted in human rights. While the GDPR-based analysis showed that this data- and privacy-based legislation addressed most of the identified ethical issues, questions related to the common good approach in the context of environment and mobility that arise due to the wide spectrum of the MLS usage require further legal discussion. The application of the two approaches shows that conducting the ethical and legal analysis is beneficial for both the designers of such MLS as well as the legal actors. The findings can enhance the design and functions of a user-facing MLS as well as influence or validate legal activities.
Brand value co-creation: field emergence, applications, measurement and future research directions
(2023)
Small Businesses Participating in Digital Platform Ecosystems - A Descriptive Literature Review
(2023)
The emergence of digital multi-sided platforms has disrupted day-to-day business in many industries. Nowadays, many small businesses participate in digital platform (DP) ecosystems and act as value creators or complementors. Investigating the small business perspective does not have a rich tradition in platform research yet. In response, this paper presents a systematic literature review (SLR) analyzing the thematic points of focus and highlighting new avenues for information systems and small business research. We find that objectives related to digital transformation, digital strategy- and business model-development, and DP adoption are fundamental topics in the conjunction of small business and DP ecosystems. Based on the findings, an agenda for future research is developed, including propositions for practice-oriented and human-centered approaches fostering sustilience, innovation capabilities and digital leadership competencies in small businesses facing DP ecosystem participation.
Climate will be decided in the global south Mankind is on a dangerous journey in the Anthropocene. Arriving at a good life for all within planetary boundaries is still possible. But at present, the journey is more likely to lead to an overheating of the Earth. Health and life would then be massively endangered for many living beings - including humans. A positive development is still possible, but it requires a global transformation of the economy and society. The prosperous states and companies are well advised, to respect the interests of the global south and future generations, and to use wisely the considerable financial resources in a cooperation of equals. This book • highlights past carbon emissions and their consequences, • reflects on the main drivers of future emissions, • discusses strategies like green growth, de-growth, • presents market-based instruments like carbon trading and carbon border adjustment and • emphasises the key role played by the emerging countries of the global south. It is not only a matter of justice but furthermore in the interest of the rich countries in the global north to contribute massively to financing a "green leapfrogging" of the global south into a carbon-free prosperity. Failing to achieve it will bring unspeakable losses and suffering to many people all over the planet.
This study examines the impact of Artificial Light at Night (ALAN) on two coral species, Acropora eurystoma and Pocillopora damicornis, in the Gulf of Aqaba/Eilat Red Sea, assessing their natural isotopic responses to highlight changes in energy and nutrient sourcing due to sensory light pollution. Our findings indicate significant disturbances in photosynthetic processes in Acropora eurystoma, as evidenced by shifts in δ13C values under ALAN, pointing to alterations in carbon distribution or utilization. In Pocillopora damicornis, similar trends were observed, with changes in δ13C and δ15N values suggesting a disruption in its nitrogen cycle and feeding strategies.
The study also uncovers species-specific variations in heterotrophic feeding, a crucial factor in coral resilience under environmental stress, contributing to the corals' fixed carbon budget. Light measurements across the Gulf demonstrated a gradient of light pollution which possess the potential of affecting marine biology in the region. ALAN was found to disrupt natural diurnal tentacle behaviors in both coral species, crucial for prey capture and nutrient acquisition, thereby impacting their isotopic composition and health.
Echoing previous research, our study underscores the need to consider each species' ecological and physiological contexts when assessing the impacts of anthropogenic changes. The findings offer important insights into the complexities of marine ecosystems under environmental stress and highlight the urgency of developing effective mitigation strategies.
In this study, we have investigated the form of velocity and pressure functions of a fluid oscillating between two parallel glass sheets that form a circular Hele-Shaw cell. The flow has been considered to be radial, incompressible and laminar. The time-dependent Navier-Stokes equation has been solved in cylindrical coordinates using Fourier transform, and the oscillating flow velocity across the thickness of the cell has been obtained at different times. The flow velocity function in the unsteady state is related to the vertical component of the coordinates in the form of parabolic functions and also to the inverse of the radial component. The time dependence appears as a simple harmonic with a frequency equal to the oscillation frequency. The velocity of the flow is maximum at the middle of the cell along its height and gradually decreases from the middle towards the top or bottom plane and reaches zero. Pressure does not depend on the height and changes logarithmically with the radius. The dependence of pressure on time is also a simple harmonic with the external frequency, but it has a phase shift with respect to the velocity.
With the release of the Apple iPhone 12 Pro Max in 2020, various features were integrated that make it attractive as a recording device for scene-related computer graphics pipelines. The captured Apple RAW images have a much higher dynamic range than the standard 8-bit images. Since a scene-based workflow naturally has an extended dynamic range (HDR), the Apple RAW recordings can be well integrated. To correctly integrate the iPhone 12 pro Apple RAW data into a scene-related workflow, two command-line software solutions, among others, are dcraw and rawtoaces. In this paper, we concentrate on dcraw. dcraw offers the possibility to export RAW images directly to ACES2065-1. Different images recorded under different lighting conditions are examined to determine which options for the dcraw development produce the best results. Images from five different lighting situations like D65, D60, D55, D50, and 2980K, are examined. The DNG files are developed using different methods within dcraw. The values of the recorded ColorChecker24 patches are compared to reference values derived from BabelColor [1] and ACES [2].
In this work, the most relevant 3D LiDAR technologies and their applications in 2022 were investigated. For this purpose, applications of LiDAR systems were classified into the typical application areas "3D modeling", "smart city", "robotics", "smart automotive" and "consumer goods". The investigation has shown that neither "mechanical" LiDAR technologies, nor so-called solid-state LiDAR technologies, nor "hybrid" LiDAR technologies can be evaluated as optimal for the typical application areas. In none of the application areas could all of the elaborated requirements be met. However, the "hybrid" LiDAR technologies such as sequential MEMS LiDAR technology and sequential flash LiDAR technology proved to be among the most suitable for most typical application areas. However, other technologies also tended to be suitable for individual typical application areas. Finally, it was found that several of the LiDAR technologies investigated are currently equally suitable for some typical application areas. To evaluate the suitability, concrete LiDAR systems - of different technologies and properties - were compared with the specific requirements of exemplary applications of an application area. The results of the investigation provide an orientation as to which LiDAR technology is promising for which application area.
DIN SPEC 92001-3 Artificial Intelligence – Life Cycle Processes and Quality Requirements. Artificial Intelligence has become a game-changer, but its impact must be approached responsibly. This is the third document in a series, and it aims to ensure that AI systems are developed, deployed, and used efficiently, responsibly, and in a trustworthy way. It focuses on “Explainability” – the ability to understand how AI makes decisions. This DIN SPEC 92001-3 provides a domain-independent guide on promoting explainability throughout the AI system’s life cycle. It tackles “opacity”, describing sources and effects of opacity in AI and how explanations can mitigate them. The goal is to foster a better understanding and effective use of Explainable AI across various applications, fostering principles of trust and transparency in AI-based systems. This DIN SPEC is the result of „Zertifizierung von Standard-KI-Anwendungen (Zertifizierte KI project)“ https://www.zertifizierte-ki.de/. The publication is available for free at Beuth Verlag GmbH www.beuth.de - plus the search for "DIN SPEC 92001-3"
This article presents a research outline on the use of microlearning applications to develop digital competencies in Small and Medium-sized Enter-prises (SMEs). The digital transformation of businesses has become essential for their survival, and SMEs need to develop digital competencies (DC) to remain competitive in the market. Microlearning (ML), a form of learning that involves small, bite-sized learning modules, has been gaining popularity in recent years as a way to efficiently and effectively develop skills. Through a semi-systematic literature review approach, our study examines prevalent knowledge in the area of ML and DC and discusses interrelations. As a result, we propose a research roadmap consisting of six research questions targeting four dimensions of ML for DC development in SMEs: 1) context, 2) formats, 3) reward system, and 4) complexity level.
Digital transformation initiatives in small and medium-sized enterprises (SME) are often hampered by individual practitioners' perceptions of information and communication technology (ICT). This research employs an educational escape room (ER) game for an intervention towards informed decision-making on ICT adoption in SMEs. ER design and implementation are elaborated and consequently tested with SME practitioners, all embedded in an action-design study based on a qualitative research methodology. The result highlights a trade-off between creating immersive game experiences and achieving learning objectives. Still, the outcome implies an impact on players' perception of ICT integrated in the ER. The findings contribute to the emerging field of serious games for learning and shed light on the potential of game-based interventions for SMEs.
This paper presents a study on the feasibility of using large language models (LLM) for coding with low-resource and domain-specific programming languages that typically lack the amount of data required for effective LLM processing techniques. This study focuses on the econometric scripting language named hansl of the open-source software gretl and employs a proprietary LLM based on GPT-3.5. Our findings suggest that LLMs can be a useful tool for writing, understanding, improving, and documenting gretl code, which includes generating descriptive docstrings for functions and providing precise explanations for abstract and poorly documented econometric code. While the LLM showcased promoting docstring-to-code translation capability, we also identify some limitations, such as its inability to improve certain sections of code and to write accurate unit tests. This study is a step towards leveraging the power of LLMs to facilitate software development in low-resource programming languages and ultimately to lower barriers to entry for their adoption.
Ubiquitous Music is an interdisciplinary research area that combines methodologies from music, computer science, education, creativity studies, human sciences and engineering.
The Ubiumus 2023 symposium, held at Ulster University and North West Regional College in Derry~Londonderry, Northern Ireland, included contributions on the following topics:
Rapid Prototyping and Live Environments
Ecological Approaches to Ubiquitous Music
Ubiquitous Music Creative Practices, Tools and Influences
The symposium also included a number of artistic contributions and workshops, which are also discussed in the proceedings volume. A number of events (including all paper presentations, an invited lecture, a panel discussion, and a keynote and associated performance) were also documented via video, with a link available in this Proceedings volume.
This Paper proposes a novel method for the blind detection of image pre-processing techniques by means of statistical pattern recognition in image forensics. The technique is intended to detect sensor intrinsic pre-processing steps as well as manually applied filters. We have exemplary chosen 6 pre-processing filters with different parameter settings. The concept utilizes 29 image features which are supposed to allow for a reliable model creation during supervised learning. The evaluation of the trained models indicates average accuracies between 82.50 and 94.53%. The investigation of image data from 8 sensors leads to the detection of credible pre-processing filters. Those results adumbrate that our method might be suitable to prove the authenticity of the data origin and the integrity of image data based on the detected preprocessing techniques. The preliminary evaluation for manually applied filters yields recognition accuracies between 39.09% (14 classes) and 53.33% (7 classes).
We investigate micrometer-sized flat droplets consisting of an isotropic core surrounded by a nematic rim in freely suspended smectic A liquid-crystal films. In contrast to purely isotropic droplets which are characterized by a sharp edge and no long-range interactions, the nematic fringe introduces a continuous film thickness change resulting in long-range mutual attraction of droplets. The coalescence scenario is divided in two phases. The first one consists in the fusion of the nematic regions. The second phase involves the dissolution of a thin nematic film between the two isotropic cores. The latter has many similarities with the rupture of thin liquid films between droplets coalescing in an immiscible viscous liquid.
Coalescence of biphasic droplets in free-standing smectic films is controlled in part by the rupture of a thin nematic membrane separating the isotropic droplet cores.
Sensing is nowadays an accepted application of phononic crystals with chemical and biosensors for liquid analytes being the perhaps most promising ones. A liquid-filled defect is introduced that turns into a resonant cavity. Similar to the well-known resonant sensors sensitivity can be increased with higher operating frequencies. We introduce a Sandwiched Phononic Crystal (SPC), which applies a resonant cavity located between two stacked layers on top of a SAW device. Key challenges are coupling of surface acoustic wave into the liquid cavities and avoiding scattering of the guided waves into the bulk of the sensor chip.
Phononic crystals (PnC) with a specifically designed liquid-filled defect have been recently introduced as a novel sensor platform (Lucklum et al. in Sens Actuators B Chem 171–172:271–277, 2012). Sensors based on this principle feature a band gap covering the typical input span of the measurand as well as a narrow transmission peak within the band gap where the frequency of maximum transmission is governed by the measurand. This approach has been applied for determination of volumetric properties of liquids (Lucklum et al. in Sens Actuators B Chem 171–172:271–277, 2012; Oseev et al. in Sens Actuators B Chem 189:208–212, 2013; Lucklum and Li in Meas Sci Technol 20(12):124014, 2009) and has demonstrated attractive sensitivity. One way to improve sensitivity requires higher probing frequencies in the range of 100 MHz and above. In this range surface acoustic wave (SAW) devices are an established basis for sensors. We have performed first tests towards a PnC microsensors (Lucklum et al. in Towards a SAW based phononic crystal sensor platform. In: 2013 Joint European frequency and time forum and international frequency control symposium (EFTF/IFC), pp 69–72, 2013). The respective feature size of the PnC SAW sensor has dimensions in the range of 10 µm and below. Whereas those dimensions are state of the art for common MEMS materials, etching of holes and cavities in piezoelectric materials that have an aspect ratio diameter/depth is still challenging. In this contribution we describe an improved technological process able to realize considerably deep and uniform holes in a SAW substrate.
The study focuses on high-performance combined electro-spark alloying of titanium and titanium alloy (VT1-0, VT16) surface and porous matrix structure oxidation. The metal-oxide coatings morphology is the result of melt drop transfer, heat treatment, and oxidation. The study establishes the influence of technological regimes of alloying and oxidation on morphological heterogeneity of biocompatible layered metal-oxide system Ti-Ta-(Ti,Ta)xOy. It was found that during electro-spark alloying the concentration of tantalum on the titanium surface ranges from 0.1 to 3.2 at.%. Morphology of the deposited splats is represented by uniformly grown crystals of titanium and tantalum oxides, which increase from nano- to submicron size.
The importance and the attractivity of the sensorimotor training is still growing. Up to now the impact of the training on the body is not yet fully investigated. Hence, nowadays the planning of the therapy is mainly based on the experiences of the physiotherapist and on the conditions of the practice. For the development of the therapy the physiotherapist is supported by manufacturer's information about the exercisers as well as by general assumptions regarding the sensorimotor training. For the validation of this information two setups were investigated. In the first part, the behavior of two students was studied on three exercisers. Here the EMG data and the motion data were analyzed. In the second part, the behavior of the left and the right body side was analyzed for 16 subjects. The study revealed that the major work for the maintenance of the equilibrium is done by the distal musculature. Furthermore, it was shown that there is a different behavior of the musculature at both body sides. Additionally, it has been proven that each test person had an individual behavior on the exercisers. Consequently, it would be hard to make general assumptions regarding the impact of the training on the body.
Surface classification and detection of latent fingerprints based on 3D surface texture parameters
(2012)
Water can exhibit many different colors due to a variety of physical properties. Here, we focus on some observable colors within very pure freshwater. We only treat the absorption of light due to electronic and ro-vibrational excitations and scattering due to refractive index fluctuations of the water and the respective consequences for the appearance of colors.
Freezing of lakes is described using a simplified one-dimensional model, which gives ice thickness, ice growth rates, and ice surface temperature as a function of time. Model data for a specific lake with known meteorological conditions are compared to estimated ice thickness using a simple optical method. Finally, more advanced potential students projects are briefly discussed and results of a numerical solution are compared to the simplified model.
Since the face morphing attack was introduced by Ferrara et al. in 2014, the detection of face morphings has become a wide spread topic in image forensics. By now, the community is very active and has reported diverse detection approaches. So far, the evaluations are mostly performed on images without post-processing. Face images stored within electronic machine readable documents (eMRTD) are ICAO-passport-scaled to a resolution of 413x531 and a JPG or JP2 lesize of 15 kilobytes. This paper introduces a face morphing detection concept with 3 modules (ICAO-aligned pre- processing module, feature extraction module and classi cation module), tailored for such images on eMRTD. In this work we exemplary design and evaluate two feature spaces for the feature extraction module, a frequency domain and a spatial domain feature space. Our evaluation will compare both feature spaces and is carried out with 66,229 passport-scaled images (64,363 morphed face images and 1,866 authentic face images) which are completly independent from training and include all images provided for the IHMMSEC'19 special session: "Media Forensics - Fake or Real?". Furthermore, we investigate the in uence of di erent morph gen- eration pipelines to the detection accuracies of the concept and we analyse the impact of neutral and smiling genuine faces to the morph detector performance. The evaluation determines a detection rate of 86.0% for passport-scaled morphed images with a false alarm rate of 4.4% for genuine images for the spatial domain feature space.
Reducing the False Alarm Rate for Face Morph Detection by a Morph Pipeline Footprint Detector
(2018)
This paper introduces an approach to automatic generation of visually faultless facial morphs along with a proposal on how such morphs can be automatically detected. It is endeavored that the created morphs cannot be recognized as such with the naked eye and a reference automatic face recognition (AFR) system produces high similarity scores while matching a morph against faces of persons who participated in morphing. Automatic generation of morphs allows for creating abundant experimental data, which is essential (i) for evaluating the performance of AFR systems to reject morphs and (ii) for training forensic systems to detect morphs. Our first experiment shows that human performance to distinguish between morphed and genuine face images is close to random guessing. In our second experiment, the reference AFR system has verified 11.78% of morphs against any of genuine images at the decision threshold of 1% false acceptance rate. These results indicate that facial morphing is a serious threat to access control systems aided by AFR and establish the need for morph detection approaches. Our third experiment shows that the distribution of Benford features extracted from quantized DCT coefficients of JPEG-compressed morphs is substantially different from that of genuine images enabling the automatic detection of morphs.
We analyze StirTrace towards benchmarking face morphing forgeries and extending it by additional scaling functions for the face biometrics scenario. We benchmark a Benford's law based multi-compression-anomaly detection approach and acceptance rates of morphs for a face matcher to determine the impact of the processing on the quality of the forgeries. We use 2 different approaches for automatically creating 3940 images of morphed faces. Based on this data set, 86614 images are created using StirTrace. A manual selection of 183 high quality morphs is used to derive tendencies based on the subjective forgery quality. Our results show that the anomaly detection seems to be able to detect anomalies in the morphing regions, the multi-compression-anomaly detection performance after the processing can be differentiated into good (e.g. cropping), partially critical (e.g. rotation) and critical results (e.g. additive noise). The influence of the processing on the biometric matcher is marginal.
In 2014 a novel identity theft scheme targeting specific application scenarios in face biometrics was introduced. In this scheme, a so called face morph melts two or more face images of different persons into one image, which is visually similar to multiple real world persons. Based on this non authentic image, it is possible to apply for an image based identity document to be issued by a corresponding authority. Thus, multiple persons can use such a document to pass image based person verification scenarios with a single document containing an artificially weakened template. Currently there is no reliable existing security mechanism to detect this attack.
The paper presents an observation and evaluation of the recovery process. Seven weeks after the fracture of the fibula and six weeks after surgery the measurement of the gait of the subject has been started. Inertial measurement units applied above both ankles are used to acquire kinematical data and three surface EMG at each leg to get information about the activity of three muscles. The intensity of the weekly tests has been increased in dependence on the healing progress. Both scenarios-walking on the floor and on the treadmill-were included in the experiments to obtain comparable data sets. Beside of the investigation of the healing process the paper is focused on symmetry/asymmetry properties of the gait. The results indicate that asymmetry is not only an essential property of pathologic gait but it is present in normal gait too, especially if short distances are evaluated. They may be caused by the influence of a dominant/injured leg, of the first/last steps, the natural variance of the gait or the daily fitness of the subject. Asymmetry is obviously in the contribution of both legs to a stride (step length, strike and lift angle, stand and swing phase).
The public sector faces several challenges, such as a number of external and internal demands for change, citizens' dissatisfaction and frustration with public sector organizations, that need to be addressed. An alternative to the traditional top-down development of public services is co-creation of public services. Co-creation promotes collaboration between stakeholders with the aim to create better public services and achieve public values. At the same time, data analytics has been fuelled by the availability of immense amounts of textual data. Whilst both co-creation and TA have been used in the private sector, we study existing works on the application of Text Analytics (TA) techniques on text data to support public service co-creation. We systematically review 75 of the 979 papers that focus directly or indirectly on the application of TA in the context of public service development. In our review, we analyze the TA techniques, the public service they support, public value outcomes, and the co-creation phase they are used in. Our findings indicate that the TA implementation for co-creation is still in its early stages and thus still limited. Our research framework promotes the concept and stimulates the strengthening of the role of Text Analytics techniques to support public sector organisations and their use of co-creation process. From policy-makers' and public administration managers' standpoints, our findings and the proposed research framework can be used as a guideline in developing a strategy for the designing co-created and user-centred public services.
Disclinations or disclination clusters in smectic C freely suspended films with topological charges larger than one are unstable. They disintegrate, preferably in a spatially symmetric fashion, into single defects with individual charges of +1, which is the smallest positive topological charge allowed in polar vector fields. While the opposite process of defect annihilation is well-defined by the initial defect positions, disintegration starts from a singular state and the following scenario including the emerging regular defect patterns must be selected by specific mechanisms. We analyze experimental data and compare them with a simple model where the defect clusters adiabatically pass quasi-equilibrium solutions in one-constant approximation. It is found that the defects arrange in geometrical patterns that correspond very closely to superimposed singular defect solutions, without additional director distortions. The patterns expand by affine transformations where all distances between individual defects scale with the same time-dependent scaling factor proportional to the square-root of time.
We present a method for the arbitrage-free interpolation of plain-vanilla option prices and implied volatilities, which is based on a system of integral equations that relates terminal density and option prices. Using a discretization of the terminal density, we write these integral equations as a system of linear equations. We show that the kernel matrix of this system is, in general, ill-conditioned, so that it cannot be solved for the discretized density using a naive approach. Instead, we construct a sparse model for the kernel matrix using singular value decomposition (SVD), which allows us not only to systematically improve the condition number of the kernel matrix, but also determines the computational effort and accuracy of our method. In order to allow for the treatment of realistic inputs that may contain arbitrage, we reformulate the system of linear equations as an optimization problem, in which the SVD-transformed density minimizes the error between the input prices and the arbitrage-free prices generated by our method. To further stabilize the method in the presence of noisy input prices or arbitrage, we apply an 𝐿1-regularization to the SVD-transformed density. Our approach, which is inspired by recent progress in theoretical physics, offers a flexible and efficient framework for the arbitrage-free interpolation of plain-vanilla option prices and implied volatilities, without the need to explicitly specify a stochastic process, expansion basis functions or any other kind of model. We demonstrate the capabilities of our method in a number of artificial and realistic test cases.
The Patellostabilometer: A New Device for Quantification of Mediolateral Patella Displacement
(2023)
Mediolateral patella displacement is of interest for diagnostics and clinically relevant
research questions. Apart from manual testing, no standardized method is currently available. Proper
quantification of patella mobility is necessary to better understand pathologies at the patellofemoral
joint. Patella mobility was assessed in 25 healthy individuals using a Patellostabilometer, a new
prototype instrument for quantification of the mediolateral patella displacement. The participants
underwent measurements of the mediolateral displacement three times using the Patellostabilome-
ter. A maximal force of 10 N was applied for patella movement. Additionally, leg length and
circumference of the knee, upper- and lower-leg were measured. Lateral patella displacement of
18.27 ± 3.76 mm (range 15.85–20.64 mm, interquartile range (IQR) of 4.79) was measured. The medial
patella displacement showed 24.47 ± 6.59 mm (range 19.29–29.76 mm, IQR of 10.47). The test–retest
measurement error was 2.32 ± 1.76 mm (IQR of 2.38 mm), with five outliers. There was greater
test–retest variability between the measurements of the medial displacement compared to the lateral
one. The test–retest variability reached 7% of the patella displacement. Other parameters provided no
significant correlations. Based on the natural patellofemoral mobility, a precise and clinically relevant
quantification of patella mobility is allowed.
Context awareness is critical for the successful execution of processes. In the abundance of business process management (BPM) research, frameworks exclusively devoted to extracting context from textual process data are scarce. With the deluge of textual data and its increasing value for organizations, it becomes essential to employ relevant text analytics techniques to increase the awareness of process workers, which is important for process execution. The present paper addresses this demand by developing a framework for context awareness based on process executions-related textual data using a well-established layered BPM context model. This framework combines and maps various text analytics techniques to the layers of the context model, aiming to increase the context awareness of process workers and facilitate informed decision-making. The framework is applied in an IT ticket processing case study. The findings show that contextual information obtained using our framework enriches the awareness of process workers regarding the process instance urgency, complexity, and upcoming tasks and assists in making decisions in terms of these aspects.
An approach for analyzing business process execution complexity based on textual data and event log
(2023)
With the advent of digital transformation, organizations increasingly rely on various information systems to support their business processes (BPs). Recorded data, including textual data and event log, expand exponentially, complicating decision-making and posing new challenges for BP complexity analysis in Business Process Management (BPM). Herein, Process Mining (PM) serves to derive insights based on historic BP execution data, called event log. However, in PM, textual data is often neglected or limited to BP descriptions. Therefore, in this study, we propose a novel approach for analyzing BP execution complexity by combining textual data serving as an input at the BP start and event log. The approach is aimed at studying the connection between complexities obtained from these two data types. For textual data-based complexity, the approach employs a set of linguistic features. In our previous work, we have explored the design of linguistic features favorable for BP execution complexity prediction. Accordingly, we adapt and incorporate them into the proposed approach. Using these features, various machine learning techniques are applied to predict textual data-based complexity. Moreover, in this prediction, we show the adequacy of our linguistic features, which outperformed the linguistic features of a widely-used text analysis technique. To calculate event log-based complexity, the event log and relevant complexity metrics are used. Afterward, a correlation analysis of two complexities and an analysis of the significant differences in correlations are performed. The results serve to derive recommendations and insights for BP improvement. We apply the approach in the IT ticket handling process of the IT department of an academic institution. Our findings show that the suggested approach enables a comprehensive identification of BP redesign and improvement opportunities.
Layered van der Waals ferromagnets, which preserve their magnetic properties down to exfoliated monolayers, are fueling an abundance of fundamental research and nanoscale device demonstration. CrGeTe3 is a prime example of this class of materials. Its temperature-pressure phase diagram features an insulator-to-metal transition and a significant increase in ferromagnetic Curie-Weiss temperatures upon entering the metallic state. We use density functional theory to understand the magnetic exchange interactions in CrGeTe3 at ambient and elevated pressures. We calculate Heisenberg exchange couplings, which provide the correct ferromagnetic ground state and explain the experimentally observed pressure dependence of magnetism in CrGeTe3. Furthermore, we combine density functional theory with dynamical mean-field theory to investigate the effects of electronic correlations and the nature of the high-pressure metallic state in CrGeTe3.
Large three-dimensional metallic parts can be printed layer-by-layer using gas metal arc directed energy deposition (GMA-DED) process at a high deposition rate and with little or no material wastage. Fast responsive real-time monitoring of GMA-DED process signatures and their transient variations is required for printing of dimensionally accurate and structurally sound parts. A systematic experimental investigation is presented here on multi-layer GMA-DED with two different scanning strategies using a high strength low alloy (HSLA) filler wire. The dynamic metal transfer, melt pool temperature field and its longitudinal cross-section, and arc voltage and current are monitored synchronously. The transient arc heat input and the melt pool solidification cooling rate are estimated from the monitored signals. The layer-wise variations of the melt pool dimension, surface temperature profile, thermal cycles, and solidification cooling rate are examined for different scanning strategies. It is comprehended that the part defects can be minimized, and the mass production of zero-defect parts can be achieved in GMA-DED process with synchronized monitoring and assessment of the real-time process signatures.
When a droplet is brought in contact with an undercooled surface, it wets the substrate and solidifies at the same time. The interplay between the phase transition effects and the contact-line motion, leading to its arrest, remains poorly understood. Here we reveal the early solidification patterns and dynamics of spreading hexadecane droplets. Total internal reflection imaging is employed to temporally and spatially resolve the early solidification behavior. With this, we determine the conditions leading to the contact-line arrest. We quantify the overall nucleation behavior, i.e., the nucleation rate and the crystal growth speed and show its sensitivity to the applied undercooling of the substrate. We also show that for strong enough undercooling it is the rapid growth of the crystals which determines the eventual arrest of the spreading contact line. By combining the Johnson-Mehl-Avrami-Kolmogorov nucleation theory and scaling relations for the spreading, we calculate the temporal evolution of the solid area fraction, which is in good agreement with our observations.
A unified understanding of terms and their applicability is essential for every scientific discipline: steganography is no exception. Being divided into several domains (for instance, text steganography, digital media steganography, and network steganography), it is crucial to provide a unified terminology as well as a taxonomy that is not limited to some specific applications or areas. A prime attempt towards a unified understanding of terms was conducted in 2015 with the introduction of a pattern-based taxonomy for network steganography. Six years later, in 2021, the first work towards a pattern-based taxonomy for steganography was proposed. However, this initial attempt still faced several shortcomings, e.g., the lack of patterns for several steganography domains (the work mainly focused on network steganography and covert channels), various terminology issues, and the need of providing a tutorial on how the taxonomy can be used during engineering and scientific tasks, including the paper-writing process.</p>
<p>As the consortium who published this initial 2021-study on steganography patterns, in this paper we present the first comprehensive pattern-based taxonomy tailored to fit all known domains of steganography, including smaller and emerging areas, such as filesystem steganography and cyber-physical systems steganography. Besides, to make our contribution more effective and promote the use of the taxonomy to advance research on steganography, we also provide a thorough tutorial on its utilization. </p>
<p>Our pattern collection is available at <a href="https://patterns.ztt.hs-worms.de/" target="_blank">https://patterns.ztt.hs-worms.de</a>.</p>
Fast protein and metabolite liquid chromatography (FPLMC) was introduced years ago to enable the easy separation of high-molecular compounds such as proteins from small molecules and the identification of the low-molecular substances. In this paper, the method is applied for the rapid evaluation of freshness and monitoring the aging of animal meat and fish. A novel chromatographic sensor was developed with a deep UV LED-based photometric detection unit (255–265 nm), an original flow cuvette and registration scheme; the processing of a chromatogram with the sensor takes approximately 15 min. Strict isochronism between the elution of ATP metabolites, mainly hypoxanthine (Hx) and inosine monophosphate (IMP), and the time of maturation of meat or fish, was discovered. A new freshness index H* = [Hx]/[IMP] was introduced, which is proportional to the instrumental delay time in the FPMLC chromatograms: the H* index < 0.5 indicates the presence of inosine monophosphate (IMP) and the high quality of the meat or fish. Reasonably strong correlations were revealed between data obtained by FPMLC and total volatile basic nitrogen TVB-N (for fish) or volatile fatty acids VFA (for meat) content. Moreover, putative nucleotide salvage and an increase in the concentration of IMP were observed in fish after heat treatment using the FPMLC sensor and NMR technique.
A sample set of calculations is presented in this supplemental document to analytically estimate joint distortion for gas metal arc lap joining of aluminum and steel thin sheets following the published article "Analytical Estimation of Thermomechanical Distortion and Interface Layer Thickness for Gas Metal Arc Lap Joining of Dissimilar Sheets"
Single dielectric microspheres can manipulate light focusing and collection to enhance optical interaction with surfaces. To demonstrate this principle, we experimentally investigate the enhancement of the Raman signal collected by a single dielectric microsphere, with a radius much larger than the exciting laser spot size, residing on the sample surface. The absolute microsphere-assisted Raman signal from a single graphene layer measured in air is more than a factor of two higher than that obtained with a high numerical aperture objective. Results from Mie’s theory are used to benchmark numerical simulations and an analytical model to describe the isolated microsphere focusing properties. The analytical model and the numerical simulations justify the Raman signal enhancement measured in the microsphere-assisted Raman spectroscopy experiments.
Biomass gasification is recognized as a viable avenue to accelerate the sustainable production of hydrogen. In this work, a numerical simulation model of air gasification of rice husks is developed using the Aspen Plus to investigate the feasibility of producing hydrogen-rich syngas. The model is experimentally validated with rice husk gasification results and other published studies. The influence of temperature and equivalence ratio on the syngas composition, H2 yield, LHVSyngas, H2/CO ratio, CGE, and PCG was studied. Furthermore, the synchronized effects of temperature and ER are studied using RSM to determine the operational point of maximizing H2 yield and PCG. The RSM analysis results show optimum performance at temperatures between 820 °C and 1090 °C and ER in the range of 0.06–0.10. The findings show that optimal operating conditions of the gasification system can be achieved at a more refined precision through simulations coupled with advanced optimization techniques.
Glass-ceramic composites consisting of potassium-iron-silicate glass and barium titanate mixed in various proportions were successfully synthesized by low-temperature sintering. The crystal structure of the obtained composite samples, the porosity and the microhardness were studied by the X-ray diffraction, the electron microscopy, the weight method, and the Vickers method. Electrical characteristics (dielectric permittivity, tunability and losses) of as-prepared and annealed in oxygen medium samples were investigated at microwaves. According to structural analysis, the synthesized samples are a mixture of KFeSi glass, ferroelectric BaTiO3, and dielectric barium polytitanates; the ratio of the latter determines the electrical properties of the composites. Depending on the content of barium titanate, the studied composite samples show a permittivity from 50 to 270 with a dielectric loss level of 0,1–0,02 in frequency range from 3 to 10 GHz. Annealing of composite samples in an oxygen-containing environment leads to an increase in their dielectric permittivity and tunability by 10–25% and a twofold decrease in dielectric loss.
Companies are increasingly facing the challenges of a persistent cyber threat landscape. By means of AI, cyber attacks can be efficiently conducted more successful through offensive AI. As for cyber defense, AI can be also utilized against cyber threats (defensive AI). Due to limited resources, especially in small and medium-sized companies (SMEs), there is a need to deploy more effective defensive cyber security solutions. Precisely, the adaptation of AI-based resilient defenses must be driven forward. Therefore, the aim of this paper is to identify and evaluate AI-related use cases with a high impact potential on the cyber security level, while being applicable to SMEs at the same time. In order to reach the research goal, an extensive literature review of several online catalogs, surveys and online platforms was conducted. In conclusion, seven crucial AI-based security features were outlined that are providing a high impact potential to the security level for SMEs. Afterwards, the results are discussed and set into a broader context. Even though AI-based security solutions are providing a large range of advantages, certain challenges and barriers using AI-related security applications are addressed in the paper as well. A high need for usable state of the art AI based cyber security solution for SMEs was identified.