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In this paper we consider a simple syntactic extension of Answer Set Programming (ASP) for dealing with (nested) existential quantifiers and double negation in the rule bodies, in a close way to the recent proposal RASPL-1. The semantics for this extension just resorts to Equilibrium Logic (or, equivalently, to the General Theory of Stable Models), which provides a logic-programming interpretation for any arbitrary theory in the syntax of Predicate Calculus. We present a translation of this syntactic class into standard logic programs with variables (either disjunctive or normal, depending on the input rule heads), as those allowed by current ASP solvers. The translation relies on the introduction of auxiliary predicates and the main result shows that it preserves strong equivalence modulo the original signature.
The paper aims to bring the experience of playing videogames closer to objective knowledge, where the experience can be assessed and falsified via an operational concept. The theory focuses on explaining the basic elements that form the core of the process of the experience. The name of puppetry is introduced after discussing the similarities in the importance of experience for both videogames and theatrical puppetry. Puppetry, then, operationalizes the gaming experience into a concept that can be assessed.
We summarize Chandra observations of the emission line profiles from 17 OB stars. The lines tend to be broad and unshifted. The forbidden/intercombination line ratios arising from Helium-like ions provide radial distance information for the X-ray emission sources, while the H-like to He-like line ratios provide X-ray temperatures, and thus also source temperature versus radius distributions. OB stars usually show power law differential emission measure distributions versus temperature. In models of bow shocks, we find a power law differential emission measure, a wide range of ion stages, and the bow shock flow around the clumps provides transverse velocities comparable to HWHM values. We find that the bow shock results for the line profile properties, consistent with the observations of X-ray line emission for a broad range of OB star properties.
We study the time variability of emission lines in three WNE stars : WR 2 (WN2), WR 3 (WN3ha) and WR152 (WN3). While WR 2 shows no variability above the noise level, the other stars do show variation, which are like other WR stars in WR 152 but very fast in WR 3. From these motions, we deduce a value of β ∼1 for WR 3 that is like that seen in O stars and β ∼2–3 for WR 152, that is intermediate between other WR stars and WR 3.
Artificial intelligence (AI)-based technologies can increasingly perform knowledge work tasks, such as medical diagnosis. Thereby, it is expected that humans will not be replaced by AI but work closely with AI-based technology (“augmentation”). Augmentation has ethical implications for humans (e.g., impact on autonomy, opportunities to flourish through work), thus, developers and managers of AI-based technology have a responsibility to anticipate and mitigate risks to human workers. However, doing so can be difficult as AI encompasses a wide range of technologies, some of which enable fundamentally new forms of interaction. In this research-in-progress paper, we propose the development of a taxonomy to categorize unique characteristics of AI-based technology that influence the interaction and have ethical implications for human workers. The completed taxonomy will support researchers in forming cumulative knowledge on the ethical implications of augmentation and assist practitioners in the ethical design and management of AI-based technology in knowledge work.
By quantitatively fitting simple emission line profile models that include both atomic opacity and porosity to the Chandra X-ray spectrum of ζ Pup, we are able to explore the trade-offs between reduced mass-loss rates and wind porosity. We find that reducing the mass-loss rate of ζ Pup by roughly a factor of four, to 1.5 × 10−6 M⊙ yr−1, enables simple non-porous wind models to provide good fits to the data. If, on the other hand, we take the literature mass-loss rate of 6×10−6 M⊙ yr−1, then to produce X-ray line profiles that fit the data, extreme porosity lengths – of h∞ ≈ 3 R∗ – are required. Moreover, these porous models do not provide better fits to the data than the non-porous, low optical depth models. Additionally, such huge porosity lengths do not seem realistic in light of 2-D numerical simulations of the wind instability.
KEYCIT 2014
(2015)
In our rapidly changing world it is increasingly important not only to be an expert in a chosen field of study but also to be able to respond to developments, master new approaches to solving problems, and fulfil changing requirements in the modern world and in the job market. In response to these needs key competencies in understanding, developing and using new digital technologies are being brought into focus in school and university programmes. The IFIP TC3 conference "KEYCIT – Key Competences in Informatics and ICT (KEYCIT 2014)" was held at the University of Potsdam in Germany from July 1st to 4th, 2014 and addressed the combination of key competencies, Informatics and ICT in detail. The conference was organized into strands focusing on secondary education, university education and teacher education (organized by IFIP WGs 3.1 and 3.3) and provided a forum to present and to discuss research, case studies, positions, and national perspectives in this field.
We present an algorithm that computes a function that assigns consecutive integers to trees recognized by a deterministic, acyclic, finite-state, bottom-up tree automaton. Such function is called minimal perfect hashing. It can be used to identify trees recognized by the automaton. Its value may be seen as an index in some other data structures. We also present an algorithm for inverted hashing.
Many hot stars exhibit stochastic polarimetric variability, thought to arise from clumping low in the wind. Here we investigate the wind properties required to reproduce this variability using analytic models, with particular emphasis on Luminous Blue Variables. We find that the winds must be highly structured, consisting of a large number of optically-thin clumps; while we find that the overall level of polarization should scale with mass-loss rate – consistent with observations of LBVs. The models also predict variability on very short timescales, which is supported by the results of a recent polarimetric monitoring campaign.
We present the latest results on the observational dependence of the mass-loss rate in stellar winds of O and early-B stars on the metal content of their atmospheres, and compare these with predictions. Absolute empirical rates for the mass loss of stars brighter than 10$^{5.2} L_{\odot}$, based on H$\alpha$ and ultraviolet (UV) wind lines, are found to be about a factor of two higher than predictions. If this difference is attributed to inhomogeneities in the wind this would imply that luminous O and early-B stars have clumping factors in their H$\alpha$ and UV line forming regime of about a factor of 3--5. The investigated stars cover a metallicity range $Z$ from 0.2 to 1 $Z_{\odot}$. We find a hint towards smaller clumping factors for lower $Z$. The derived clumping factors, however, presuppose that clumping does not impact the predictions of the mass-loss rate. We discuss this assumption and explain how we intend to investigate its validity in more detail.
A key problem in automatic annotation of historical corpora is inconsistent spelling. Because the spelling of some word forms can differ between texts, a language model trained on already annotated treebanks may fail to recognize known word forms due to differences in spelling. In the present work, we explore the feasibility of an unsupervised method for spelling-adjustment for the purpose of improved part of speech (POS) tagging. To this end, we present a method for spelling normalization based on weighted edit distances, which exploits within-text spelling variation. We then evaluate the improvement in taging accuracy resulting from between-texts spelling normalization in two tagging experiments on several Early New High German (ENHG) texts.
Physiological and genomic variation among cryptic species of a marsh snail (Melampus bidentatus)
(2021)
Received views of utterance context in pragmatic theory characterize the occurrent subjective states of interlocutors using notions like common knowledge or mutual belief. We argue that these views are not compatible with the uncertainty and robustness of context-dependence in humanhuman dialogue. We present an alternative characterization of utterance context as objective and normative. This view reconciles the need for uncertainty with received intuitions about coordination and meaning in context, and can directly inform computational approaches to dialogue.
During the outbreak of the COVID-19 pandemic, many people shared their symptoms across Online Social Networks (OSNs) like Twitter, hoping for others’ advice or moral support. Prior studies have shown that those who disclose health-related information across OSNs often tend to regret it and delete their publications afterwards. Hence, deleted posts containing sensitive data can be seen as manifestations of online regrets. In this work, we present an analysis of deleted content on Twitter during the outbreak of the COVID-19 pandemic. For this, we collected more than 3.67 million tweets describing COVID-19 symptoms (e.g., fever, cough, and fatigue) posted between January and April 2020. We observed that around 24% of the tweets containing personal pronouns were deleted either by their authors or by the platform after one year.
As a practical application of the resulting dataset, we explored its suitability for the automatic classification of regrettable content on Twitter.
This paper describes the key aspects of the system SynCoP (Syntactic Constraint Parser) developed at the Berlin-Brandenburgische Akademie der Wissenschaften. The parser allows to combine syntactic tagging and chunking by means of constraint grammar using weighted finite state transducers (WFST). Chunks are interpreted as local dependency structures within syntactic tagging. The linguistic theories are formulated by criteria which are formalized by a semiring; these criteria allow structural preferences and gradual grammaticality. The parser is essentially a cascade of WFSTs. To find the most likely syntactic readings a best-path search is used.
A new method is used in an eye-tracking pilot experiment which shows that it is possible to detect differences in common ground associated with the use of minimally different types of indefinite anaphora. Following Richardson and Dale (2005), cross recurrence quantification analysis (CRQA) was used to show that the tandem eye movements of two Swedish-speaking interlocutors are slightly more coupled when they are using fully anaphoric indefinite expressions than when they are using less anaphoric indefinites. This shows the potential of CRQA to detect even subtle processing differences in ongoing discourse.
Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
Spectral detection enables multi-color fluorescence fluctuation spectroscopy studies in living cells
(2021)
We present an analysis of student language input in a corpus of tutoring dialogue in the domain of symbolic differentiation. Our focus on procedural tutoring makes the dialogue comparable to collaborative problem-solving (CPS). Existing CPS models describe the process of negotiating plans and goals, which also fits procedural tutoring. However, we provide a classification of student utterances and corpus annotation which shows that approximately 28% of non-trivial student language in this corpus is not accounted for by existing models, and addresses other functions, such as evaluating past actions or correcting mistakes. Our analysis can be used as a foundation for improving models of tutoring dialogue.
Background:
Anti-TNFα monoclonal antibodies (mAbs) are a well-established treatment for patients with Crohn’s disease (CD). However, subtherapeutic concentrations of mAbs have been related to a loss of response during the first year of therapy1. Therefore, an appropriate dosing strategy is crucial to prevent the underexposure of mAbs for those patients. The aim of our study was to assess the impact of different dosing strategies (fixed dose or body size descriptor adapted) on drug exposure and the target concentration attainment for two different anti-TNFα mAbs: infliximab (IFX, body weight (BW)-based dosing) and certolizumab pegol (CZP, fixed dosing). For this purpose, a comprehensive pharmacokinetic (PK) simulation study was performed.
Methods:
A virtual population of 1000 clinically representative CD patients was generated based on the distribution of CD patient characteristics from an in-house clinical database (n = 116). Seven dosing regimens were investigated: fixed dose and per BW, lean BW (LBW), body surface area, height, body mass index and fat-free mass. The individual body size-adjusted doses were calculated from patient generated body size descriptor values. Then, using published PK models for IFX and CZP in CD patients2,3, for each patient, 1000 concentration–time profiles were simulated to consider the typical profile of a specific patient as well as the range of possible individual profiles due to unexplained PK variability across patients. For each dosing strategy, the variability in maximum and minimum mAb concentrations (Cmax and Cmin, respectively), area under the concentration-time curve (AUC) and the per cent of patients reaching target concentration were assessed during maintenance therapy.
Results:
For IFX and CZP, Cmin showed the highest variability between patients (CV ≈110% and CV ≈80%, respectively) with a similar extent across all dosing strategies. For IFX, the per cent of patients reaching the target (Cmin = 5 µg/ml) was similar across all dosing strategies (~15%). For CZP, the per cent of patients reaching the target average concentration of 17 µg/ml ranged substantially (52–71%), being the highest for LBW-adjusted dosing.
Conclusion:
By using a PK simulation approach, different dosing regimen of IFX and CZP revealed the highest variability for Cmin, the most commonly used PK parameter guiding treatment decisions, independent upon dosing regimen. Our results demonstrate similar target attainment with fixed dosing of IFX compared with currently recommended BW-based dosing. For CZP, the current fixed dosing strategy leads to comparable percentage of patients reaching target as the best performing body size-adjusted dosing (66% vs. 71%, respectively).
Public blockchain
(2020)
Blockchain has the potential to change business transactions to a major extent. Thereby, underlying consensus algorithms are the core mechanism to achieve consistency in distributed infrastructures. Their application aims for transparency and accountability in societal transactions. As a result of missing reviews holistically covering consensus algorithms, we aim to (1) identify prevalent consensus algorithms for public blockchains, and (2) address the resource perspective with a sustainability consideration (whereby we address the three spheres of sustainability). Our systematic literature review identified 33 different consensus algorithms for public blockchains. Our contribution is twofold: first, we provide a systematic summary of consensus algorithms for public blockchains derived from the scientific literature as well as real-world applications and systemize them according to their research focus; second, we assess the sustainability of consensus algorithms using a representative sample and thereby highlight the gaps in literature to address the holistic sustainability of consensus algorithms.
Web Tracking
(2018)
Web tracking seems to become ubiquitous in online business and leads to increased privacy concerns of users. This paper provides an overview over the current state of the art of web-tracking research, aiming to reveal the relevance and methodologies of this research area and creates a foundation for future work. In particular, this study addresses the following research questions: What methods are followed? What results have been achieved so far? What are potential future research areas? For these goals, a structured literature review based upon an established methodological framework is conducted. The identified articles are investigated with respect to the applied research methodologies and the aspects of web tracking they emphasize.
EMOOCs 2023
(2023)
From June 14 to June 16, 2023, Hasso Plattner Institute, Potsdam, hosted the eighth European MOOC Stakeholder Summit (EMOOCs 2023).
The pandemic is fortunately over. It has once again shown how important digital education is. How well-prepared a country was could be seen in our schools, universities, and companies. In different countries, the problems manifested themselves differently. The measures and approaches to solving the problems varied accordingly. Digital education, whether micro-credentials, MOOCs, blended learning formats, or other e-learning tools, received a major boost.
EMOOCs 2023 focusses on the effects of this emergency situation. How has it affected the development and delivery of MOOCs and other e-learning offerings all over Europe? Which projects can serve as models for successful digital learning and teaching? Which roles can MOOCs and micro-credentials bear in the current business transformation? Is there a backlash to the routine we knew from pre-Corona times? Or have many things become firmly established in the meantime, e.g. remote work, hybrid conferences, etc.?
Furthermore, EMOOCs 2023 has a closer look at the development and formalization of digital learning. Micro-credentials are just the starting point. Further steps in this direction would be complete online study programs or full online universities.
Another main topic is the networking of learning offers and the standardization of formats and metadata. Examples of fruitful cooperations are the MOOChub, the European MOOC Consortium, and the Common Micro-Credential Framework.
The learnings, derived from practical experience and research, are explored in EMOOCs 2023 in four tracks and additional workshops, covering various aspects of this field. In this publication, we present papers from the conference’s Research & Experience Track, the Business Track and the International Track.
E-Mail tracking uses personalized links and pictures for gathering information on user behavior, for example, where, when, on what kind of device, and how often an e-mail has been read. This information can be very useful for marketing purposes. On the other hand, privacy and security requirements of customers could be violated by tracking. This paper examines how e-mail tracking works, how it can be detected automatically, and to what extent it is used in German e-commerce. We develop a detection model and software tool in order to collect and analyze more than 600 newsletter e-mails from companies of several different industries. The results show that the usage of e-mail tracking in Germany is prevalent but also varies depending on the industry.
Enforcing security policies to distributed systems is difficult, in particular, when a system contains untrusted components. We designed AspectKE*, a distributed AOP language based on a tuple space, to tackle this issue. In AspectKE*, aspects can enforce access control policies that depend on future behavior of running processes. One of the key language features is the predicates and functions that extract results of static program analysis, which are useful for defining security aspects that have to know about future behavior of a program. AspectKE* also provides a novel variable binding mechanism for pointcuts, so that pointcuts can uniformly specify join points based on both static and dynamic information about the program. Our implementation strategy performs fundamental static analysis at load-time, so as to retain runtime overheads minimal. We implemented a compiler for AspectKE*, and demonstrate usefulness of AspectKE* through a security aspect for a distributed chat system.
Clumps in hot star winds can originate from shock compression due to the line driven instability. One-dimensional hydrodynamic simulations reveal a radial wind structure consisting of highly compressed shells separated by voids, and colliding with fast clouds. Two-dimensional simulations are still largely missing, despite first attempts. Clumpiness dramatically affects the radiative transfer and thus all wind diagnostics in the UV, optical, and in X-rays. The microturbulence approximation applied hitherto is currently superseded by a more sophisticated radiative transfer in stochastic media. Besides clumps, i.e. jumps in the density stratification, so-called kinks in the velocity law, i.e. jumps in dv/dr, play an eminent role in hot star winds. Kinks are a new type of radiative-acoustic shock, and propagate at super-Abbottic speed.
Temporal propositions are mapped to sets of strings that witness (in a precise sense) the propositions over discrete linear Kripke frames. The strings are collected into regular languages to ensure the decidability of entailments given by inclusions between languages. (Various notions of bounded entailment are shown to be expressible as language inclusions.) The languages unwind computations implicit in the logical (and temporal) connectives via a system of finite-state constraints adapted from finite-state morphology. Applications to Hybrid Logic and non-monotonic inertial reasoning are briefly considered.
The P v λλ1118, 1128 resonance doublet is an extraordinarily useful diagnostic of O-star winds, because it bypasses the traditional problems associated with determining mass-loss rates from UV resonance lines. We discuss critically the assumptions and uncertainties involved with using P v to diagnose mass-loss rates, and conclude that the large discrepancies between massloss rates determined from P v and the rates determined from “density squared” emission processes pose a significant challenge to the “standard model” of hot-star winds. The disparate measurements can be reconciled if the winds of O-type stars are strongly clumped on small spatial scales, which in turn implies that mass-loss rates based on Hα or radio emission are too large by up to an order of magnitude.
Plant invasions, resilience, economics, and restoration - can fynbos pay for alien management?
(2012)
We introduce a simple approach extending the input language of Answer Set Programming (ASP) systems by multi-valued propositions. Our approach is implemented as a (prototypical) preprocessor translating logic programs with multi-valued propositions into logic programs with Boolean propositions only. Our translation is modular and heavily benefits from the expressive input language of ASP. The resulting approach, along with its implementation, allows for solving interesting constraint satisfaction problems in ASP, showing a good performance.
The difference-list technique is described in literature as effective method for extending lists to the right without using calls of append/3. There exist some proposals for automatic transformation of list programs into differencelist programs. However, we are interested in construction of difference-list programs by the programmer, avoiding the need of a transformation step. In [GG09] it was demonstrated, how left-recursive procedures with a dangling call of append/3 can be transformed into right-recursion using the unfolding technique. For simplification of writing difference-list programs using a new cons/2 procedure was introduced. In the present paper, we investigate how efficieny is influenced using cons/2. We measure the efficiency of procedures using accumulator technique, cons/2, DCG’s, and difference lists and compute the resulting speedup in respect to the simple procedure definition using append/3. Four Prolog systems were investigated and we found different behaviour concerning the speedup by difference lists. A result of our investigations is, that an often advice given in the literature for avoiding calls append/3 could not be confirmed in this strong formulation.
Preface
(2010)
The workshops on (constraint) logic programming (WLP) are the annual meeting of the Society of Logic Programming (GLP e.V.) and bring together researchers interested in logic programming, constraint programming, and related areas like databases, artificial intelligence and operations research. In this decade, previous workshops took place in Dresden (2008), Würzburg (2007), Vienna (2006), Ulm (2005), Potsdam (2004), Dresden (2002), Kiel (2001), and Würzburg (2000). Contributions to workshops deal with all theoretical, experimental, and application aspects of constraint programming (CP) and logic programming (LP), including foundations of constraint/ logic programming. Some of the special topics are constraint solving and optimization, extensions of functional logic programming, deductive databases, data mining, nonmonotonic reasoning, , interaction of CP/LP with other formalisms like agents, XML, JAVA, program analysis, program transformation, program verification, meta programming, parallelism and concurrency, answer set programming, implementation and software techniques (e.g., types, modularity, design patterns), applications (e.g., in production, environment, education, internet), constraint/logic programming for semantic web systems and applications, reasoning on the semantic web, data modelling for the web, semistructured data, and web query languages.
In times of digitalization, the collection and modeling of business processes is still a challenge for companies. The demand for trustworthy process models that reflect the actual execution steps therefore increases. The respective kinds of processes significantly determine both, business process analysis and the conception of future target processes and they are the starting point for any kind of change initiatives. Existing approaches to model as-is processes, like process mining, are exclusively focused on reconstruction. Therefore, transactional protocols and limited data from a single application system are used. Heterogeneous application landscapes and business processes that are executed across multiple application systems, on the contrary, are one of the main challenges in process mining research. Using RFID technology is hence one approach to close the existing gap between different application systems. This paper focuses on methods for data collection from real world objects via RFID technology and possible combinations with application data (process mining) in order to realize a cross system mining approach.
This paper highlights the different ways of perceiving video games and video game content, incorporating interactive and non-interactive methods. It examines varying cognitive and emotive reactions by persons who are used to play video games as well as persons who are unfamiliar with the aesthetics and the most basic game play rules incorporated within video games. Additionally, the principle of “Flow” serves as a theoretical and philosophical foundation. A small case-study featuring two games has been made to emphasize the numerous possible ways of perception of video games.
The variability of bone strength and skeletal robustness of young men - how it can be influenced
(2011)
A deterministic cycle scheduling of partitions at the operating system level is supposed for a multiprocessor system. In this paper, we propose a tool for generating such schedules. We use constraint based programming and develop methods and concepts for a combined interactive and automatic partition scheduling system. This paper is also devoted to basic methods and techniques for modeling and solving this partition scheduling problem. Initial application of our partition scheduling tool has proved successful and demonstrated the suitability of the methods used.
Virtual reality can have advantages for education and learning. However, it must be adequately designed so that the learner benefits from the technological possibilities. Understanding the underlying effects of the virtual learning environment and the learner’s prior experience with virtual reality or prior knowledge of the content is necessary to design a proper virtual learning environment. This article presents a pre-study testing the design of a virtual learning environment for engineering vocational training courses. In the pre-study, 12 employees of two companies joined the training course in one of the two degrees of immersion (desktop VR and VR HMD). Quantitative results on learning success, cognitive load, usability, and motivation and qualitative learning process data were presented. The qualitative data assessment shows that overall, the employees were satisfied with the learning environment regardless of the level of immersion and that the participants asked for more guidance and structure accompanying the learning process. Further research is needed to test for solid group differences.
In the last years, statistical machine translation has already demonstrated its usefulness within a wide variety of translation applications. In this line, phrase-based alignment models have become the reference to follow in order to build competitive systems. Finite state models are always an interesting framework because there are well-known efficient algorithms for their representation and manipulation. This document is a contribution to the evolution of finite state models towards a phrase-based approach. The inference of stochastic transducers that are based on bilingual phrases is carefully analysed from a finite state point of view. Indeed, the algorithmic phenomena that have to be taken into account in order to deal with such phrase-based finite state models when in decoding time are also in-depth detailed.
Turning shy on winter's day effects of season on personality and stress response in Microtus arvalis
(2013)
This paper outlines a newly-developed method to include the effects of time variability in the radiative transfer code CMFGEN. It is shown that the flow timescale is often large compared to the variability timescale of LBVs. Thus, time-dependent effects significantly change the velocity law and density structure of the wind, affecting the derivation of the mass-loss rate, volume filling factor, wind terminal velocity, and luminosity. The results of this work are directly applicable to all active LBVs in the Galaxy and in the LMC, such as AG Car, HR Car, S Dor and R 127, and could result in a revision of stellar and wind parameters. The massloss rate evolution of AG Car during the last 20 years is presented, highlighting the need for time-dependent models to correctly interpret the evolution of LBVs.
Traditional production systems are enhanced by cyber-physical systems (CPS) and Internet of Things. A kind of next generation systems, those cyber-physical production systems (CPPS) are able to raise the level of autonomy of its production components. To find the optimal degree of autonomy in a given context, a research approach is formulated using a simulation concept. Based on requirements and assumptions, a cyber-physical market is modeled and qualitative hypotheses are formulated, which will be verified with the help of the CPPS of a hybrid simulation environment.
Process analysis usually focuses only on single and selected processes. It is either existent processes that are recorded and analysed or reference processes that are implemented. So far no evident effort has been put into generalising specific process aspects into patterns and comparing those patterns with regard to their efficiency and effectiveness. This article focuses on the combination of dynamic and holistic analytical elements in enterprise architectures. Our goal is to outline an approach to analyse the development of business processes in a cyclical matter and demonstrate this approach based on an existent modelling language. We want to show that organisational learning can derive from the systematic analysis of past and existent processes from which patterns of successful problem solving can be deducted.
Context-aware, intelligent musical instruments for improving knowledge-intensive business processes
(2022)
With shorter song publication cycles in music industries and a reduced number of physical contact opportunities because of disruptions that may be an obstacle for musicians to cooperate, collaborative time consumption is a highly relevant target factor providing a chance for feedback in contemporary music production processes. This work aims to extend prior research on knowledge transfer velocity by augmenting traditional designs of musical instruments with (I) Digital Twins, (II) Internet of Things and (III) Cyber-Physical System capabilities and consider a new type of musical instrument as a tool to improve knowledge transfers at knowledge-intensive forms of business processes. In a design-science-oriented way, a prototype of a sensitive guitar is constructed as information and cyber-physical system. Findings show that this intelligent SensGuitar increases feedback opportunities. This study establishes the importance of conversion-specific music production processes and novel forms of interactions at guitar playing as drivers of high knowledge transfer velocities in teams and among individuals.
With larger artificial neural networks (ANN) and deeper neural architectures, common methods for training ANN, such as backpropagation, are key to learning success. Their role becomes particularly important when interpreting and controlling structures that evolve through machine learning. This work aims to extend previous research on backpropagation-based methods by presenting a modified, full-gradient version of the backpropagation learning algorithm that preserves (or rather crystallizes) selected neural weights while leaving other weights adaptable (or rather fluid). In a design-science-oriented manner, a prototype of a feedforward ANN is demonstrated and refined using the new learning method. The results show that the so-called crystallizing backpropagation increases the control possibilities of neural structures and interpretation chances, while learning can be carried out as usual. Since neural hierarchies are established because of the algorithm, ANN compartments start to function in terms of cognitive levels. This study shows the importance of dealing with ANN in hierarchies through backpropagation and brings in learning methods as novel ways of interacting with ANN. Practitioners will benefit from this interactive process because they can restrict neural learning to specific architectural components of ANN and can focus further development on specific areas of higher cognitive levels without the risk of destroying valuable ANN structures.
The paper deals with the increasing growth of embedded systems and their role within structures similar to the Internet (Internet of Things) as those that provide calculating power and are more or less appropriate for analytical tasks. Faced with the example of a cyber-physical manufacturing system, a common objective function is developed with the intention to measure efficient task processing within analytical infrastructures. A first validation is realized on base of an expert panel.
As Industry 4.0 infrastructures are seen as highly evolutionary environment with volatile, and time-dependent workloads for analytical tasks, particularly the optimal dimensioning of IT hardware is a challenge for decision makers because the digital processing of these tasks can be decoupled from their physical place of origin. Flexible architecture models to allocate tasks efficiently with regard to multi-facet aspects and a predefined set of local systems and external cloud services have been proven in small example scenarios. This paper provides a benchmark of existing task realization strategies, composed of (1) task distribution and (2) task prioritization in a real-world scenario simulation. It identifies heuristics as superior strategies.
Already successfully used products or designs, past projects or our own experiences can be the basis for the development of new products. As reference products or existing knowledge, it is reused in the development process and across generations of products. Since further, products are developed in cooperation, the development of new product generations is characterized by knowledge-intensive processes in which information and knowledge are exchanged between different kinds of knowledge carriers. The particular knowledge transfer here describes the identification of knowledge, its transmission from the knowledge carrier to the knowledge receiver, and its application by the knowledge receiver, which includes embodied knowledge of physical products. Initial empirical findings of the quantitative effects regarding the speed of knowledge transfers already have been examined. However, the factors influencing the quality of knowledge transfer to increase the efficiency and effectiveness of knowledge transfer in product development have not yet been examined empirically. Therefore, this paper prepares an experimental setting for the empirical investigation of the quality of knowledge transfers.
Accelerating knowledge
(2019)
As knowledge-intensive processes are often carried out in teams and demand for knowledge transfers among various knowledge carriers, any optimization in regard to the acceleration of knowledge transfers obtains a great economic potential. Exemplified with product development projects, knowledge transfers focus on knowledge acquired in former situations and product generations. An adjustment in the manifestation of knowledge transfers in its concrete situation, here called intervention, therefore can directly be connected to the adequate speed optimization of knowledge-intensive process steps. This contribution presents the specification of seven concrete interventions following an intervention template. Further, it describes the design and results of a workshop with experts as a descriptive study. The workshop was used to assess the practical relevance of interventions designed as well as the identification of practical success factors and barriers of their implementation.
Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level.
We investigate the effect of wind clumping on the dynamics of Wolf-Rayet winds, by means of the Potsdam Wolf-Rayet (PoWR) hydrodynamic atmosphere models. In the limit of microclumping the radiative acceleration is generally enhanced. We examine the reasons for this effect and show that the resulting wind structure depends critically on the assumed radial dependence of the clumping factor D(r). The observed terminal wind velocities for WR stars imply that D(r) increases to very large values in the outer part of the wind, in agreement with the assumption of detached expanding shells.
The spatially-resolved winds of the massive binary, Eta Carinae, extend an arcsecond on the sky, well beyond the 10 to 20 milliarcsecond binary orbital dimension. Stellar wind line profiles, observed at very different angular resolutions of VLTI/AMBER, HST/STIS and VLT/UVES, provide spatial information on the extended wind interaction structure as it changes with orbital phase. These same wind lines, observable in the starlight scattered off the foreground lobe of the dusty Homunculus, provide time-variant line profiles viewed from significantly different angles. Comparisons of direct and scattered wind profiles observed in the same epoch and at different orbital phases provide insight on the extended wind structure and promise the potential for three-dimensional imaging of the outer wind structures. Massive, long-lasting clumps, including the nebularWeigelt blobs, originated during the two historical ejection events. Wind interactions with these clumps are quite noticeable in spatially-resolved spectroscopy. As the 2009.0 minimum approaches, analysis of existing spectra and 3-D modeling are providing bases for key observations to gain further understanding of this complex massive binary.
How messy is your news feed
(2020)
Social Networking Sites (SNSs) are pervasive in our daily lives. However, emerging reports suggest that people are increasingly dissatisfied with their experience of SNSs News Feeds. Motivated by the cognitive load theory, the paper postulates that arrangement and presentation of information are important constituents of one’s Facebook News Feed experience. Integrating these factors into the novel concept of ‘perceived disorder’, this paper hypothesizes that the perception of disorder elicited by the Facebook News Feed plays an important role in causing discontinuance intentions. Drawing on the Stressor-Strain-Outcome Model, we suggest that perceived disorder leads to SNS discontinuance intention and is partially mediated by SNS fatigue. The paper uses the responses of 268 Facebook users to investigate these relationships and introduces perceived disorder as a novel stressor. Besides adding to the existing body of literature, these insights are of relevance to internet service providers, policy makers and SNS users.
Defining the allocation of decision rights for enterprise applications is a crucial issue in IT governance and organization design. Today, emerging delivery models such as Software as a Service (SaaS) defy the notion of the internal IT department as the focal point of centralized governance. Recognizing the importance of this issue, we find that the phenomenon of 'SaaS governance' itself is not yet well understood. Based on two cases of SaaS adoption, we take a process-theoretic approach to investigate the complex interaction between factors that influence in the allocation of SaaS authority. The results suggest that some factors, such as the locus of initiative and the decision for SaaS, interact with absorptive capacities and determine the later mode of application governance at a very early stage. Thus, the initiative for introducing SaaS emerges as an important intermediate variable between the overall IT governance mode and the resulting SaaS governance outcome.
The space-image
(2008)
In recent computer game research a paradigmatic shift is observable: Games today are first and foremost conceived as a new medium characterized by their status as an interactive image. The shift in attention towards this aspect becomes apparent in a new approach that is, first and foremost, aware of the spatiality of games or their spatial structures. This rejects traditional approaches on the basis that the medial specificity of games can no longer be reduced to textual or ludic properties, but has to be seen in medial constituted spatiality. For this purpose, seminal studies on the spatiality of computer games are resumed and their advantages and disadvantages are discussed. In connection with this, and against the background of the philosophical method of phenomenology, we propose three steps in describing computer games as space images: With this method it is possible to describe games with respect to the possible appearance of spatiality in a pictorial medium.
How games spoil creativity
(2020)
The demand for a creative workforce is every growing and effective measures to improve individual creativity are searched for. This study analyzes the possibility to use games as a prime for a creative mindset. Two short entertainment games, plus a no-game-comparison condition were set up in three versions of an online-study, along with two creativity tasks and scales to assess the individual creative mindset (fixed-vs-growth, creative self-efficacy and affect). Results indicate priming effects of the games, but in the opposite intended direction: gaming diminished the creative test performances. Those playing the games reported more ideas in the open-ended creative problem task, but those answers were of less quality and they solved less closed-problem items compared to those not playing. An impact of further mindset differences could be ruled out.
In the time of digitalization the demand for organizational change is rising and demands ways to cope with fundamental changes on the organizational as well as individual level. As a basis, learning and forgetting mechanisms need to be understood in order to guide a change process efficiently and successfully. Our research aims to get a better understanding of individual differences and mechanisms in the change context by performing an experiment where individuals learn and later re-learn a complex production process using a simulation setting. The individual’s performance, as well as retentivity and prior knowledge is assessed. Our results show that higher retentivity goes along with better learning and forgetting performances. Prior knowledge did not reveal such relation to the learning and forgetting performances. The influence of age and gender is discussed in detail.
Expanding modeling notations
(2021)
Creativity is a common aspect of business processes and thus needs a proper representation through process modeling notations. However, creative processes constitute highly flexible process elements, as new and unforeseeable outcome is developed. This presents a challenge for modeling languages. Current methods representing creative-intensive work are rather less able to capture creative specifics which are relevant to successfully run and manage these processes. We outline the concept of creative-intensive processes and present an example from a game design process in order to derive critical process aspects relevant for its modeling. Six aspects are detected, with first and foremost: process flexibility, as well as temporal uncertainty, experience, types of creative problems, phases of the creative process and individual criteria. By first analyzing what aspects of creative work modeling notations already cover, we further discuss which modeling extensions need to be developed to better represent creativity within business processes. We argue that a proper representation of creative work would not just improve the management of those processes, but can further enable process actors to more efficiently run these creative processes and adjust them to better fit to the creative needs.
Reward expectation and affective responses across psychiatric disorders - A dimensional approach
(2014)
We welcome you to the 54th Hawaii International Conference on System Sciences (HICSS-54) conference. This is the fifth year for the Organizational Learning Minitrack which has had the usual growing pains: two years ago, we added the topic of Unlearning and joined with the Intentional Forgetting Minitrack - as these topics are all organizationally-based knowledge management issues. We proudly bring you the latest research focused on the methods to develop and maintain organizational learning within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves “learning” or “knowledge-based” organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational
learning in this Minitrack.
We welcome you to the 53rd Hawaii International Conference on System Sciences (HICSS) conference. After joining with Intentional Forgetting Minitrack last year, this is the fourth year of the Organizational Learning Minitrack. We add Unlearning, and Intentional Forgetting to proudly bring you the latest research focused on organizational learning issues within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves “learning” or “knowledge-based” organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational learning in this Minitrack.
Observing inconsistent results in prior studies, this paper applies the elaboration likelihood model to investigate the impact of affective and cognitive cues embedded in social media messages on audience engagement during a political event. Leveraging a rich dataset in the context of the 2020 U.S. presidential elections containing more than 3 million tweets, we found the prominence of both cue types. For the overall sample, positivity and sentiment are negatively related to engagement. In contrast, the post-hoc sub-sample analysis of tweets from famous users shows that emotionally charged content is more engaging. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with a vast number of followers. Prosocial orientation (“we-talk”) is consistently associated with more likes, comments, and retweets in the overall sample and sub-samples.
Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
Modeling expanding atmospheres is a difficult task because of the extreme non-LTE situation, the need to account for complex model atoms, especially for the iron-group elements with their millions of lines, and because of the supersonic expansion. Adequate codes have been developed e.g. by Hillier (CMFGEN), the Munich group (Puls, Pauldrach), and in Potsdam (PoWR code, Hamann et al.). While early work was based on the assumption of a smooth and homogeneous spherical stellar wind, the need to account for clumping became obvious about ten years ago. A relatively simple first-order clumping correction was readily implemented into the model codes. However, its simplifying assumptions are severe. Most importantly, the clumps are taken to be optically thin at all frequencies (”microclumping”). We discuss the consequences of this approximation and describe an approach to account for optically thick clumps (“macroclumping”). First results demonstrate that macroclumping can generally reduce the strength of spectral features, depending on their optical thickness. The recently reported discrepancy between the Hα diagnostic and the Pv resonance lines in O star spectra can be resolved without decreasing the mass-loss rates, when macroclumping is taken into account.