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The maximum entropy method is used to predict flows on water distribution networks. This analysis extends the water distribution network formulation of Waldrip et al. (2016) Journal of Hydraulic Engineering (ASCE), by the use of a continuous relative entropy defined on a reduced parameter set. This reduction in the parameters that the entropy is defined over ensures consistency between different representations of the same network. The performance of the proposed reduced parameter method is demonstrated with a one-loop network case study.
The maximum entropy method is used to derive an alternative gravity model for a transport network. The proposed method builds on previous methods which assign the discrete value of a maximum entropy distribution to equal the traffic flow rate. The proposed method however, uses a distribution to represent each flow rate. The proposed method is shown to be able to handle uncertainty in a more elegant way and give similar results to traditional methods. It is able to incorporate more of the observed data through the entropy function, prior distribution and integration limits potentially allowing better inferences to be made.
Lately, first implementation approaches of Internet of Things (IoT) technologies penetrate industrial value-adding processes. Within this, the competence requirements for employees are changing. Employees’ organization, process, and interaction competences are of crucial importance in this new IoT environment, however, in students and vocational training not sufficiently considered yet. On the other hand, conventional learning factories evolve and transform to digital learning factories. Nevertheless, the integration of IoT technology and its usage for training in digital learning factories has been largely neglected thus far. Existing learning factories do not explicitly and properly consider IoT technology, which leads to deficiencies regarding an appropriate development of employees’ Industrial IoT competences. The goal of this contribution is to point out a didactic concept that enables development and training of these new demanded competences by using an IoT laboratory. For this purpose, a design science approach is applied. The result of this contribution is a didactic concept for the development of Industrial IoT competences in an IoT laboratory.
In this extended abstract, we will analyze the current challenges for the envisioned Self-Adaptive CPS. In addition, we will outline our results to approach these challenges with SMARTSOS [10] a generic approach based on extensions of graph transformation systems employing open and adaptive collaborations and models at runtime for trustworthy self-adaptation, self-organization, and evolution of the individual systems and the system-of-systems level taking the independent development, operation, management, and evolution of these systems into account.
E-commerce marketplaces are highly dynamic with constant competition. While this competition is challenging for many merchants, it also provides plenty of opportunities, e.g., by allowing them to automatically adjust prices in order to react to changing market situations. For practitioners however, testing automated pricing strategies is time-consuming and potentially hazardously when done in production. Researchers, on the other side, struggle to study how pricing strategies interact under heavy competition. As a consequence, we built an open continuous time framework to simulate dynamic pricing competition called Price Wars. The microservice-based architecture provides a scalable platform for large competitions with dozens of merchants and a large random stream of consumers. Our platform stores each event in a distributed log. This allows to provide different performance measures enabling users to compare profit and revenue of various repricing strategies in real-time. For researchers, price trajectories are shown which ease evaluating mutual price reactions of competing strategies. Furthermore, merchants can access historical marketplace data and apply machine learning. By providing a set of customizable, artificial merchants, users can easily simulate both simple rule-based strategies as well as sophisticated data-driven strategies using demand learning to optimize their pricing strategies.
We compare Visual Berrypicking, an interactive approach allowing users to explore large and highly faceted information spaces using similarity-based two-dimensional maps, with traditional browsing techniques. For large datasets, current projection methods used to generate maplike overviews suffer from increased computational costs and a loss of accuracy resulting in inconsistent visualizations. We propose to interactively align inexpensive small maps, showing local neighborhoods only, which ideally creates the impression of panning a large map. For evaluation, we designed a web-based prototype for movie exploration and compared it to the web interface of The Movie Database (TMDb) in an online user study. Results suggest that users are able to effectively explore large movie collections by hopping from one neighborhood to the next. Additionally, due to the projection of movie similarities, interesting links between movies can be found more easily, and thus, compared to browsing serendipitous discoveries are more likely.
We develop a simple two-zone interpretation of the broadband baseline Crab nebula spectrum between 10(-5) eV and similar to 100 TeV by using two distinct log-parabola energetic electrons distributions. We determine analytically the very-high energy photon spectrum as originated by inverse-Compton scattering of the far-infrared soft ambient photons within the nebula off a first population of electrons energized at the nebula termination shock. The broad and flat 200 GeV peak jointly observed by Fermi/LAT and MAGIC is naturally reproduced. The synchrotron radiation from a second energetic electron population explains the spectrum from the radio range up to similar to 10 keV. We infer from observations the energy dependence of the microscopic probability of remaining in proximity of the shock of the accelerating electrons.
Web-based E-Learning uses Internet technologies and digital media to deliver education content to learners. Many universities in recent years apply their capacity in producing Massive Open Online Courses (MOOCs). They have been offering MOOCs with an expectation of rendering a comprehensive online apprenticeship. Typically, an online content delivery process requires an Internet connection. However, access to the broadband has never been a readily available resource in many regions. In Africa, poor and no networks are yet predominantly experienced by Internet users, frequently causing offline each moment a digital device disconnect from a network. As a result, a learning process is always disrupted, delayed and terminated in such regions. This paper raises the concern of E-Learning in poor and low bandwidths, in fact, it highlights the needs for an Offline-Enabled mode. The paper also explores technical approaches beamed to enhance the user experience inWeb-based E-Learning, particular in Africa.
Recently, Kocyan & Wiland-Szymańska (2016) have published a thorough research article on one of the outstanding members of the family Hypoxidaceae on the Seychelles, which resulted in the raise of a new genus (Friedmannia Kocyan & Wiland-Szymańska 2016: 60) to accommodate the former Curculigo seychellensis Bojer ex Baker (1877: 368). However, it has turned out that the name Friedmannia Chantanachat & Bold (1962: 45) already exists in literature for a green alga, which renders the new hypoxid genus illegitimate (Melbourne Code; McNeill et al. 2012). Therefore, we assign a new generic epithet to Curculigo seychellensis.
Editorial
(2017)
Background: Infliximab (IFX), an anti-TNF monoclonal antibody approved for the treatment of inflammatory bowel disease, is dosed per kg body weight (BW). However, the rationale for body size adjustment has not been unequivocally demonstrated [1], and first attempts to improve IFX therapy have been undertaken [2]. The aim of our study was to assess the impact of different dosing strategies (i.e. body size-adjusted and fixed dosing) on drug exposure and pharmacokinetic (PK) target attainment. For this purpose, a comprehensive simulation study was performed, using patient characteristics (n=116) from an in-house clinical database.
Methods: IFX concentration-time profiles of 1000 virtual, clinically representative patients were generated using a previously published PK model for IFX in patients with Crohn's disease [3]. For each patient 1000 profiles accounting for PK variability were considered. The IFX exposure during maintenance treatment after the following dosing strategies was compared: i) fixed dose, and per ii) BW, iii) lean BW (LBW), iv) body surface area (BSA), v) height (HT), vi) body mass index (BMI) and vii) fat-free mass (FFM)). For each dosing strategy the variability in maximum concentration Cmax, minimum concentration Cmin (= C8weeks) and area under the concentration-time curve (AUC), as well as percent of patients achieving the PK target, Cmin=3 μg/mL [4] were assessed.
Results: For all dosing strategies the variability of Cmin (CV ≈110%) was highest, compared to Cmax and AUC, and was of similar extent regardless of dosing strategy. The proportion of patients reaching the PK target (≈⅓ was approximately equal for all dosing strategies.
Gaussianity Fair
(2017)
Eighteen scientists met at Jurata, Poland, to discuss various aspects of the transition from adolescence to adulthood. This transition is a delicate period facing complex interactions between the adolescents and the social group they belong to. Social identity, group identification and identity signalling, but also stress affecting basal salivary cortisol rhythms, hypertension, inappropriate nutrition causing latent and manifest obesity, moreover, in developing and under-developed countries, parasitosis causing anaemia thereby impairing growth and development, are issues to be dealt with during this period of the human development. In addition, some new aspects of the association between weight, height and head circumference in the newborns were discussed, as well as intrauterine head growth and head circumference as health risk indicators.
Root infinitives on Twitter
(2017)
Background: Evidence that home telemonitoring (HTM) for patients with chronic heart failure (CHF) offers clinical benefit over usual care is controversial as is evidence of a health economic advantage. Therefore the CardioBBEAT trial was designed to prospectively assess the health economic impact of a dedicated home monitoring system for patients with CHF based on actual costs directly obtained from patients’ health care providers.
Methods: Between January 2010 and June 2013, 621 patients (mean age 63,0 ± 11,5 years, 88 % male) with a confirmed diagnosis of CHF (LVEF ≤ 40 %) were enrolled and randomly assigned to two study groups comprising usual care with and without an interactive bi-directional HTM (Motiva®). The primary endpoint was the Incremental Cost-Effectiveness Ratio (ICER) established by the groups’ difference in total cost and in the combined clinical endpoint “days alive and not in hospital nor inpatient care per potential days in study” within the follow up of 12 months. Secondary outcome measures were total mortality and health related quality of life (SF-36, WHO-5 and KCCQ).
Results: In the intention-to-treat analysis, total mortality (HR 0.81; 95% CI 0.45 – 1.45) and days alive and not in hospital (343.3 ± 55.4 vs. 347.2 ± 43.9; p = 0.909) were not significantly different between HTM and usual care. While the resulting primary endpoint ICER was not positive (-181.9; 95% CI −1626.2 ± 1628.9), quality of life assessed by SF-36, WHO-5 and KCCQ as a secondary endpoint was significantly higher in the HTW group at 6 and 12 months of follow-up.
Conclusions: The first simultaneous assessment of clinical and economic outcome of HTM in patients with CHF did not demonstrate superior incremental cost effectiveness compared to usual care. On the other hand, quality of life was improved. It remains open whether the tested HTM solution represents a useful innovative approach in the recent health care setting.
Preclinical assessment of penetration not only in intact, but also in barrier‐disrupted skin is important to explore the surplus value of novel drug delivery systems, which can be specifically designed for diseased skin. Here, we characterized physical and chemical barrier disruption protocols for short‐term ex vivo skin cultures with regard to structural integrity, physiological and biological parameters. Further, we compared the penetration of dexamethasone (Dex) in different nanoparticle‐based formulations in stratum corneum, epidermis and dermis extracts of intact vs. barrier‐disrupted skin as well as by dermal microdialysis at 6, 12 and 24 hours after topical application. Dex was quantified by liquid‐chromatography ‐ tandem‐mass spectrometry (LC‐MS/MS). Simultaneously, we investigated the Dex efficacy by interleukin (IL) analysis. Tape‐stripping (TS) and 4 hours sodium lauryl sulfate 5 % (SLS) exposure were identified as highly effective barrier disruption methods assessed by reproducible transepidermal water loss (TEWL) changes and IL‐6/8 increase which was more pronounced in SLS‐treated skin. The barrier state has also a significant impact on the Dex penetration kinetics: for all formulations, TS highly increased dermal Dex concentration despite the fact that nanocrystals quickly and effectively penetrated both, intact and barrier‐disrupted skin reaching significantly higher dermal Dex concentration after 6 hours compared to Dex cream. The surplus value of encapsulation in ethyl cellulose nanocarriers could mostly be observed when applied on intact skin, in general showing a delayed Dex penetration. Estimation of cytokines was limited due to the trauma caused by probe insertion. In summary, ex vivo human skin is a highly interesting short‐term preclinical model for the analysis of penetration and efficacy of novel drug delivery systems.
Emergency Care in Germany being re-assessed Hybrid Medical Care Model Seen As Potential Answer
(2017)
Nanocarriers
(2017)
Der Leserbrief fokussiert in weiten Teilen auf das Gutachterwesen, weshalb wir ausschließlich auf die inhaltlichen Punkte im Zusammenhang mit unserer Arbeit eingehen. Untersucht wurden schmerzpsychologische Interventionen, wie beschrieben definiert als psychologische Interventionen, deren primäres Ziel die Schmerzreduktion war.
Die extrahierten Zielgrößen, wie Lebensqualität oder Depressivität, ergaben sich aus den in den Primärstudien untersuchten Hauptoutcomes und nicht aus der Suchstrategie.
Zur Einschätzung der methodischen Qualität der Primärstudien konnte ein Kriterium des von Johannsen und Kollegen [2] gebildeten Scores nicht berücksichtigt werden, da die eingeschlossenen Primärstudien keine metaanalytische Zusammenfassung erlaubten. Stellt man dies in Rechnung, bleibt die Vergleichbarkeit beider Werte erhalten.
Die Evidenzsynthese erfolgte narrativ in Text- und Tabellenform, d. h. in Form einer strukturierten Zusammenfassung und Diskussion von Studien [1].
Um unsere Arbeit zu fokussieren, hätten wir eine weitergehende Gegenüberstellung wie auch eine Überprüfung von Zitaten und Übersetzungen selbstverständlich vorgenommen, wenn wir den Hinweis dazu vor Publikation erhalten hätten.
As a potentially toxic agent on nervous system and bone, the safety of aluminium exposure from adjuvants in vaccines and subcutaneous immune therapy (SCIT) products has to be continuously reevaluated, especially regarding concomitant administrations. For this purpose, knowledge on absorption and disposition of aluminium in plasma and tissues is essential. Pharmacokinetic data after vaccination in humans, however, are not available, and for methodological and ethical reasons difficult to obtain. To overcome these limitations, we discuss the possibility of an in vitro-in silico approach combining a toxicokinetic model for aluminium disposition with biorelevant kinetic absorption parameters from adjuvants. We critically review available kinetic aluminium-26 data for model building and, on the basis of a reparameterized toxicokinetic model (Nolte et al., 2001), we identify main modelling gaps. The potential of in vitro dissolution experiments for the prediction of intramuscular absorption kinetics of aluminium after vaccination is explored. It becomes apparent that there is need for detailed in vitro dissolution and in vivo absorption data to establish an in vitro-in vivo correlation (IVIVC) for aluminium adjuvants. We conclude that a combination of new experimental data and further refinement of the Nolte model has the potential to fill a gap in aluminium risk assessment. (C) 2017 Elsevier Inc. All rights reserved.
Recently a multitude of empirically derived damage models have been applied to project future tropical cyclone (TC) losses for the United States. In their study (Geiger et al 2016 Environ. Res. Lett. 11 084012) compared two approaches that differ in the scaling of losses with socio-economic drivers: the commonly-used approach resulting in a sub-linear scaling of historical TC losses with a nation's affected gross domestic product (GDP), and the disentangled approach that shows a sub-linear increase with affected population and a super-linear scaling of relative losses with per capita income. Statistics cannot determine which approach is preferable but since process understanding demands that there is a dependence of the loss on both GDP per capita and population, an approach that accounts for both separately is preferable to one which assumes a specific relation between the two dependencies. In the accompanying comment, Rybski et al argued that there is no rigorous evidence to reach the conclusion that high-income does not protect against hurricane losses. Here we affirm that our conclusion is drawn correctly and reply to further remarks raised in the comment, highlighting the adequateness of our approach but also the potential for future extension of our research.
Over the past few years, studying abroad and other educational international experiences have become increasingly highly regarded. Nevertheless, research shows that only a minority of students actually take part in
academic mobility programs. But what is it that distinguishes those students who take up these international opportunities from those who do not? In this
study we reviewed recent quantitative studies on why (primarily German) students choose to travel abroad or not. This revealed a pattern of predictive factors. These indicate the key role played by students’ personal and social background, as well as previous international travel and the course of studies they are enrolled in. The study then focuses on teaching students. Both facilitating and debilitating factors are discussed and included in a model illustrating the decision-making process these students use. Finally, we discuss the practical implications for ways in which international, studyrelated travel might be increased in the future. We suggest that higher education institutions analyze individual student characteristics, offering differentiated programs to better meet the needs of different groups, thus raising the likelihood of disadvantaged students participating in academic international travel.
In the course of patient treatments, psychotherapists aim to meet the challenges of being both a trusted, knowledgeable conversation partner and a diligent documentalist. We are developing the digital whiteboard system Tele-Board MED (TBM), which allows the therapist to take digital notes during the session together with the patient. This study investigates what therapists are experiencing when they document with TBM in patient sessions for the first time and whether this documentation saves them time when writing official clinical documents. As the core of this study, we conducted four anamnesis session dialogues with behavior psychotherapists and volunteers acting in the role of patients. Following a mixed-method approach, the data collection and analysis involved self-reported emotion samples, user experience curves and questionnaires. We found that even in the very first patient session with TBM, therapists come to feel comfortable, develop a positive feeling and can concentrate on the patient. Regarding administrative documentation tasks, we found with the TBM report generation feature the therapists save 60% of the time they normally spend on writing case reports to the health insurance.
The globally distributed sperm whale (Physeter macrocephalus) has a partly matrilineal social structure with predominant male dispersal. At the beginning of 2016, a total of 30 male sperm whales stranded in five different countries bordering the southern North Sea. It has been postulated that these individuals were on a migration route from the north to warmer temperate and tropical waters where females live in social groups. By including samples from four countries (n = 27), this event provided a unique chance to genetically investigate the maternal relatedness and the putative origin of these temporally and spatially co-occuring male sperm whales. To utilize existing genetic resources, we sequenced 422 bp of the mitochondrial control region, a molecular marker for which sperm whale data are readily available from the entire distribution range. Based on four single nucleotide polymorphisms (SNPs) within the mitochondrial control region, five matrilines could be distinguished within the stranded specimens, four of which matched published haplotypes previously described in the Atlantic. Among these male sperm whales, multiple matrilineal lineages co-occur. We analyzed the population differentiation and could show that the genetic diversity of these male sperm whales is comparable to the genetic diversity in sperm whales from the entire Atlantic Ocean. We confirm that within this stranding event, males do not comprise maternally related individuals and apparently include assemblages of individuals from different geographic regions. (c) 2017 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.
Utilizing quad-trees for efficient design space exploration with partial assignment evaluation
(2018)
Recently, it has been shown that constraint-based symbolic solving techniques offer an efficient way for deciding binding and routing options in order to obtain a feasible system level implementation. In combination with various background theories, a feasibility analysis of the resulting system may already be performed on partial solutions. That is, infeasible subsets of mapping and routing options can be pruned early in the decision process, which fastens the solving accordingly. However, allowing a proper design space exploration including multi-objective optimization also requires an efficient structure for storing and managing non-dominated solutions. In this work, we propose and study the usage of the Quad-Tree data structure in the context of partial assignment evaluation during system synthesis. Out experiments show that unnecessary dominance checks can be avoided, which indicates a preference of Quad-Trees over a commonly used list-based implementation for large combinatorial optimization problems.
Imaginar la nación
(2018)
The classification of vulnerabilities is a fundamental step to derive formal attributes that allow a deeper analysis. Therefore, it is required that this classification has to be performed timely and accurate. Since the current situation demands a manual interaction in the classification process, the timely processing becomes a serious issue. Thus, we propose an automated alternative to the manual classification, because the amount of identified vulnerabilities per day cannot be processed manually anymore. We implemented two different approaches that are able to automatically classify vulnerabilities based on the vulnerability description. We evaluated our approaches, which use Neural Networks and the Naive Bayes methods respectively, on the base of publicly known vulnerabilities.
Preface
(2018)
This book aims at understanding the diversity of planetary and lunar magnetic fields and their interaction with the solar wind. A synergistic interdisciplinary approach combines newly developed tools for data acquisition and analysis, computer simulations of planetary interiors and dynamos, models of solar wind interaction, measurement of terrestrial rocks and meteorites, and laboratory investigations. The following chapters represent a selection of some of the scientific findings derived by the 22 projects within the DFG Priority Program Planetary Magnetism" (PlanetMag). This introductory chapter gives an overview of the individual following chapters, highlighting their role in the overall goals of the PlanetMag framework. The diversity of the different contributions reflects the wide range of magnetic phenomena in our solar system. From the program we have excluded magnetism of the sun, which is an independent broad research discipline, but include the interaction of the solar wind with planets and moons. Within the subsequent 13 chapters of this book, the authors review the field centered on their research topic within PlanetMag. Here we shortly introduce the content of all the subsequent chapters and outline the context in which they should be seen.
Foreword
(2018)
In Europe, different countries developed a rich variety of sub-municipal institutions. Out of the plethora of intra- and sub-municipal decentralization forms (reaching from local outposts of city administration to “quasi-federal” structures), this book focuses on territorial sub-municipal units (SMUs) which combine multipurpose territorial responsibility with democratic legitimacy and can be seen as institutions promoting the articulation and realization of collective choices at a sub-municipal level.
Country chapters follow a common pattern that is facilitating systematic comparisons, while at the same time leaving enough space for national peculiarities and priorities chosen and highlighted by the authors, who also take advantage of the eventually existing empirical surveys and case studies.
Business process simulation is an important means for quantitative analysis of a business process and to compare different process alternatives. With the Business Process Model and Notation (BPMN) being the state-of-the-art language for the graphical representation of business processes, many existing process simulators support already the simulation of BPMN diagrams. However, they do not provide well-defined interfaces to integrate new concepts in the simulation environment. In this work, we present the design and architecture of a proof-of-concept implementation of an open and extensible BPMN process simulator. It also supports the simulation of multiple BPMN processes at a time and relies on the building blocks of the well-founded discrete event simulation. The extensibility is assured by a plug-in concept. Its feasibility is demonstrated by extensions supporting new BPMN concepts, such as the simulation of business rule activities referencing decision models and batch activities.
In university teaching today, it is common practice to record regular lectures and special events such as conferences and speeches. With these recordings, a large fundus of video teaching material can be created quickly and easily. Typically, lectures have a length of about one and a half hours and usually take place once or twice a week based on the credit hours. Depending on the number of lectures and other events recorded, the number of recordings available is increasing rapidly, which means that an appropriate form of provisioning is essential for the students. This is usually done in the form of lecture video platforms. In this work, we have investigated how lecture video platforms and the contained knowledge can be improved and accessed more easily by an increasing number of students. We came up with a multistep process we have applied to our own lecture video web portal that can be applied to other solutions as well.
Embedded smart home — remote lab MOOC with optional real hardware experience for over 4000 students
(2018)
MOOCs (Massive Open Online Courses) become more and more popular for learners of all ages to study further or to learn new subjects of interest. The purpose of this paper is to introduce a different MOOC course style. Typically, video content is shown teaching the student new information. After watching a video, self-test questions can be answered. Finally, the student answers weekly exams and final exams like the self test questions. Out of the points that have been scored for weekly and final exams a certificate can be issued. Our approach extends the possibility to receive points for the final score with practical programming exercises on real hardware. It allows the student to do embedded programming by communicating over GPIO pins to control LEDs and measure sensor values. Additionally, they can visualize values on an embedded display using web technologies, which are an essential part of embedded and smart home devices to communicate with common APIs. Students have the opportunity to solve all tasks within the online remote lab and at home on the same kind of hardware. The evaluation of this MOOCs indicates the interesting design for students to learn an engineering technique with new technology approaches in an appropriate, modern, supporting and motivating way of teaching.
When students watch learning videos online, they usually need to watch several hours of video content. In the end, not every minute of a video is relevant for the exam. Additionally, students need to add notes to clarify issues of a lecture. There are several possibilities to enhance the metadata of a video, e.g. a typical way to add user-specific information to an online video is a comment functionality, which allows users to share their thoughts and questions with the public. In contrast to common video material which can be found online, lecture videos are used for exam preparation. Due to this difference, the idea comes up to annotate lecture videos with markers and personal notes for a better understanding of the taught content. Especially, students learning for an exam use their notes to refresh their memories. To ease this learning method with lecture videos, we introduce the annotation feature in our video lecture archive. This functionality supports the students with keeping track of their thoughts by providing an intuitive interface to easily add, modify or remove their ideas. This annotation function is integrated in the video player. Hence, scrolling to a separate annotation area on the website is not necessary. Furthermore, the annotated notes can be exported together with the slide content to a PDF file, which can then be printed easily. Lecture video annotations support and motivate students to learn and watch videos from an E-Learning video archive.
An efficient Design Space Exploration (DSE) is imperative for the design of modern, highly complex embedded systems in order to steer the development towards optimal design points. The early evaluation of design decisions at system-level abstraction layer helps to find promising regions for subsequent development steps in lower abstraction levels by diminishing the complexity of the search problem. In recent works, symbolic techniques, especially Answer Set Programming (ASP) modulo Theories (ASPmT), have been shown to find feasible solutions of highly complex system-level synthesis problems with non-linear constraints very efficiently. In this paper, we present a novel approach to a holistic system-level DSE based on ASPmT. To this end, we include additional background theories that concurrently guarantee compliance with hard constraints and perform the simultaneous optimization of several design objectives. We implement and compare our approach with a state-of-the-art preference handling framework for ASP. Experimental results indicate that our proposed method produces better solutions with respect to both diversity and convergence to the true Pareto front.
Operational decisions in business processes can be modeled by using the Decision Model and Notation (DMN). The complementary use of DMN for decision modeling and of the Business Process Model and Notation (BPMN) for process design realizes the separation of concerns principle. For supporting separation of concerns during the design phase, it is crucial to understand which aspects of decision-making enclosed in a process model should be captured by a dedicated decision model. Whereas existing work focuses on the extraction of decision models from process control flow, the connection of process-related data and decision models is still unexplored. In this paper, we investigate how process-related data used for making decisions can be represented in process models and we distinguish a set of BPMN patterns capturing such information. Then, we provide a formal mapping of the identified BPMN patterns to corresponding DMN models and apply our approach to a real-world healthcare process.
Modern server systems with large NUMA architectures necessitate (i) data being distributed over the available computing nodes and (ii) NUMA-aware query processing to enable effective parallel processing in database systems. As these architectures incur significant latency and throughout penalties for accessing non-local data, queries should be executed as close as possible to the data. To further increase both performance and efficiency, data that is not relevant for the query result should be skipped as early as possible. One way to achieve this goal is horizontal partitioning to improve static partition pruning. As part of our ongoing work on workload-driven partitioning, we have implemented a recent approach called aggressive data skipping and extended it to handle both analytical as well as transactional access patterns. In this paper, we evaluate this approach with the workload and data of a production enterprise system of a Global 2000 company. The results show that over 80% of all tuples can be skipped in average while the resulting partitioning schemata are surprisingly stable over time.
Preface
(2018)
Previous work has shown that surface modification with orthophosphoric acid can significantly enhance the charge stability on polypropylene (PP) surface by generating deeper traps. In the present study, thermally stimulated potential-decay measurements revealed that the chemical treatment may also significantly increase the number of available trapping sites on the surface. Thus, as a consequence, the so-called "cross-over" phenomenon, which is observed on as-received and thermally treated PP electrets, may be overcome in a certain range of initial charge densities. Furthermore, the discharge behavior of chemically modified samples indicates that charges can be injected from the treated surface into the bulk, and/or charges of opposite polarity can be pulled from the rear electrode into the bulk at elevated temperatures and at the high electric fields that are caused by the deposited charges. In the bulk, a lack of deep traps causes rapid charge decay already in the temperature range around 95 degrees C.
The influence of chemical composition and crystallisation conditions on the ferroelectric and paraelectric phases and the resulting morphology in Poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) (P(VDF-TrFE-CFE)) terpolymer films with 55.4/37.2/7.3 mol% or with 62.2/29.4/8.4 mol% of VDF/TrFE/CFE was studied. Poly(vinylidene fluoride trifluoroethylene) (P(VDF-TrFE)) with 75/25 mol% VDF/TrFE was employed as reference material. Fourier-Transform Infrared Spectroscopy (FTIR) was used to determine the fractions of the relevant terpolymer phases, and X-Ray Diffraction (XRD) was employed to assess the crystalline morphology. The FTIR results show an increase of the fraction of paraelectric phases after annealing. On the other hand, XRD results indicate a more stable paraelectric phase in the terpolymer with higher CFE content.
The electret state stability in nonpolar semicrystalline polymers is largely determined by the traps located at crystalline/ amorphous phase interfaces. Thus, the thermal history of such polymers should considerably influence their electret properties. In the present work, we investigate how recrystallization influences charge stability in low-density polyethylene corona electrets. It has been found that electret charge stability in quenched samples is higher than in slowly-crystallized ones. Phenomenologicaly, this can be explained by the increased number of deeper traps in samples with smaller crystallite size.
Published results on LDPE/MgO nanocomposites (3wt%) show that they promise to be good electrical-insulation materials. In this work, the nanocomposites are examined as a potential (ferro-)electret material as well. Isothermal surface-potential decay measurements show that charged LDPE/MgO films still exhibit significant surface potentials after heating for 4 hours at 80 degrees C, which suggests good capabilities of LDPE/MgO nanocomposites to hold electric charges of both polarities. Open-tubular-channel ferroelectrets prepared from LDPE/MgO nanocomposite films show significant piezoelectricity with d(33) coefficients of about 20 pC/N after charging and are stable up to temperatures of at least 80 degrees C. Thus LDPE/MgO nanocomposites may become available as a new ferroelectret material. To increase their d(33) coefficients, it is desirable to optimize the charging conditions and the ferroelectret structure.
No other means of communication determines through its seemingly unrestricted possibilities our everyday life more than the internet. From the mid-90s onwards, more and more technical advancements in the field of communication appear on the market, which in turn call for new terminology. In the first place, it is the internet (essentially based on the interaction between users and experts), which requires effective nomenclature in order to mediate between lay users and their restricted knowledge on the one, and experts and their sophisticated terminology on the other hand. At the interface between the new and complex realities and the need for simple linguistic access, a huge quantity of metaphoric denominations is used, making abstract innovations more comprehensible. Metaphor in the internet discourse serves to "reduce verticality" (Stenschke 2006) between specialized terminology and common language. The paper deals with metaphors based on spatial concepts. Space and spatiality play a key role in cognitive theories of metaphor as these theories themselves (according to Lakoff/Johnson 1980) are often based on the application of spatial concepts to non-spatial relations. After describing spatial concepts in general (referring to the internet), the paper explores which kind of metaphor takes advantage of the complexity present in the internet and how the medial space is linguistically recaptured in terms of spatial perception.
This introductory essay to the HSR Special Issue “Economists, Politics, and Society” argues for a strong field-theoretical programme inspired by Pierre Bourdieu to research economic life as an integral part of different social forms. Its main aim is threefold. First, we spell out the very distinct Durkheimian legacy in Bourdieu’s thinking and the way he applies it in researching economic phenomena. Without this background, much of what is actually part of how Bourdieu analysed economic aspects of social life would be overlooked or reduced to mere economic sociology. Second, we sketch the main theoretical concepts and heuristics used to analyse economic life from a field perspective. Third, we focus on practical methodological issues of field-analytical research into economic phenomena. We conclude with a short summary of the basic characteristics of this approach and discuss the main insights provided by the contributions to this special issue.
This paper presents the concept of a community-accessible stratospheric balloon-based observatory that is currently under preparation by a consortium of European research institutes and industry. We present the technical motivation, science case, instrumentation, and a two-stage image stabilization approach of the 0.5-m UV/visible platform. In addition, we briefly describe the novel mid-sized stabilized balloon gondola under design to carry telescopes in the 0.5 to 0.6 m range as well as the currently considered flight option for this platform. Secondly, we outline the scientific and technical motivation for a large balloon-based FIR telescope and the ESBO DS approach towards such an infrastructure.
The nature restoration project ‘Lenzener Elbtalaue’, realised from 2002 to 2011 at the river Elbe, included the first large scale dike relocation in Germany (420 ha). Its aim was to initiate the development of endangered natural wetland habitats and processes, accompanied by greater biodiversity in the former grassland dominated area. The monitoring of spatial and temporal variations of soil moisture in this dike relocation area is therefore particularly important for estimating the restoration success. The topsoil moisture monitoring from 1990 to 2017 is based on the Soil Moisture Index (SMI)1 derived with the triangle method2 by use of optical remotely sensed data: land surface temperature and Normalized Differnce Vegetation Index are calculated from Landsat 4/5/7/8 data and atmospheric corrected by use of MODIS data. Spatial and temporal soil moisture variations in the restored area of the dike relocation are compared to the agricultural and pasture area behind the new dike. Ground truth data in the dike relocation area was obtained from field measurements in October 2017 with a FDR device. Additionally, data from a TERENO soil moisture sensor network (SoilNet) and mobile cosmic ray neutron sensing (CRNS) rover measurements are compared to the results of the triangle method for a region in the Harz Mountains (Germany). The SMI time series illustrates, that the dike relocation area has become significantly wetter between 1990 and 2017, due to restructuring measurements. Whereas the SMI of the dike hinterland reflects constant and drier conditions. An influence of climate is unlikely. However, validation of the dimensionless index with ground truth measurements is very difficult, mostly due to large differences in scale.
Point clouds provide high-resolution topographic data which is often classified into bare-earth, vegetation, and building points and then filtered and aggregated to gridded Digital Elevation Models (DEMs) or Digital Terrain Models (DTMs). Based on these equally-spaced grids flow-accumulation algorithms are applied to describe the hydrologic and geomorphologic mass transport on the surface. In this contribution, we propose a stochastic point-cloud filtering that, together with a spatial bootstrap sampling, allows for a flow accumulation directly on point clouds using Facet-Flow Networks (FFN). Additionally, this provides a framework for the quantification of uncertainties in point-cloud derived metrics such as Specific Catchment Area (SCA) even though the flow accumulation itself is deterministic.
Why choice matters
(2018)
Measures of democracy are in high demand. Scientific and public audiences use them to describe political realities and to substantiate causal claims about those realities. This introduction to the thematic issue reviews the history of democracy measurement since the 1950s. It identifies four development phases of the field, which are characterized by three recurrent topics of debate: (1) what is democracy, (2) what is a good measure of democracy, and (3) do our measurements of democracy register real-world developments? As the answers to those questions have been changing over time, the field of democracy measurement has adapted and reached higher levels of theoretical and methodological sophistication. In effect, the challenges facing contemporary social scientists are not only limited to the challenge of constructing a sound index of democracy. Today, they also need a profound understanding of the differences between various measures of democracy and their implications for empirical applications. The introduction outlines how the contributions to this thematic issue help scholars cope with the recurrent issues of conceptualization, measurement, and application, and concludes by identifying avenues for future research.
Konrad Repgen (1923-2017)
(2018)
The problem of atmospheric emission from OH molecules is a long standing problem for near-infrared astronomy. PRAXIS is a unique spectrograph which is fed by fibres that remove the OH background and is optimised specifically to benefit from OH-Suppression. The OH suppression is achieved with fibre Bragg gratings, which were tested successfully on the GNOSIS instrument. PRAXIS uses the same fibre Bragg gratings as GNOSIS in its first implementation, and will exploit new, cheaper and more efficient, multicore fibre Bragg gratings in the second implementation. The OH lines are suppressed by a factor of similar to 1000, and the expected increase in the signal-to-noise in the interline regions compared to GNOSIS is a factor of similar to 9 with the GNOSIS gratings and a factor of similar to 17 with the new gratings. PRAXIS will enable the full exploitation of OH suppression for the first time, which was not achieved by GNOSIS (a retrofit to an existing instrument that was not OH-Suppression optimised) due to high thermal emission, low spectrograph transmission and detector noise. PRAXIS has extremely low thermal emission, through the cooling of all significantly emitting parts, including the fore-optics, the fibre Bragg gratings, a long length of fibre, and the fibre slit, and an optical design that minimises leaks of thermal emission from outside the spectrograph. PRAXIS has low detector noise through the use of a Hawaii-2RG detector, and a high throughput through a efficient VPH based spectrograph. PRAXIS will determine the absolute level of the interline continuum and enable observations of individual objects via an IFU. In this paper we give a status update and report on acceptance tests.
We present a project combining lidar, photometer and particle counter data with a regularization software tool for a closure study of aerosol microphysical property retrieval. In a first step only lidar data are used to retrieve the particle size distribution (PSD). Secondly, photometer data are added, which results in a good consistency of the retrieved PSDs. Finally, those retrieved PSDs may be compared with the measured PSD from a particle counter. The data here were taken in Ny Alesund, Svalbard, as an example.
Logical modeling has been widely used to understand and expand the knowledge about protein interactions among different pathways. Realizing this, the caspo-ts system has been proposed recently to learn logical models from time series data. It uses Answer Set Programming to enumerate Boolean Networks (BNs) given prior knowledge networks and phosphoproteomic time series data. In the resulting sequence of solutions, similar BNs are typically clustered together. This can be problematic for large scale problems where we cannot explore the whole solution space in reasonable time. Our approach extends the caspo-ts system to cope with the important use case of finding diverse solutions of a problem with a large number of solutions. We first present the algorithm for finding diverse solutions and then we demonstrate the results of the proposed approach on two different benchmark scenarios in systems biology: (1) an artificial dataset to model TCR signaling and (2) the HPN-DREAM challenge dataset to model breast cancer cell lines.
High Mountain Asia provides water for more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow - the vast majority of which is not monitored by sparse weather networks. We leverage passive microwave data from the SSMI series of satellites (SSMI, SSMI/S, 1987-2016), reprocessed to 3.125 km resolution, to examine trends in the volume and spatial distribution of snow-water equivalent (SWE) in the Indus Basin. We find that the majority of the Indus has seen an increase in snow-water storage. There exists a strong elevation-trend relationship, where high-elevation zones have more positive SWE trends. Negative trends are confined to the Himalayan foreland and deeply-incised valleys which run into the Upper Indus. This implies a temperature-dependent cutoff below which precipitation increases are not translated into increased SWE. Earlier snowmelt or a higher percentage of liquid precipitation could both explain this cutoff.(1) Earlier work 2 found a negative snow-water storage trend for the entire Indus catchment over the time period 1987-2009 (-4 x 10(-3) mm/yr). In this study based on an additional seven years of data, the average trend reverses to 1.4 x 10(-3). This implies that the decade since the mid-2000s was likely wetter, and positively impacted long-term SWE trends. This conclusion is supported by an analysis of snowmelt onset and end dates which found that while long-term trends are negative, more recent (since 2005) trends are positive (moving later in the year).(3)
Metamaterial Devices
(2018)
In our hands-on demonstration, we show several objects, the functionality of which is defined by the objects' internal micro-structure. Such metamaterial machines can (1) be mechanisms based on their microstructures, (2) employ simple mechanical computation, or (3) change their outside to interact with their environment. They are 3D printed from one piece and we support their creating by providing interactive software tools.
Cloud storage brokerage is an abstraction aimed at providing value-added services. However, Cloud Service Brokers are challenged by several security issues including enlarged attack surfaces due to integration of disparate components and API interoperability issues. Therefore, appropriate security risk assessment methods are required to identify and evaluate these security issues, and examine the efficiency of countermeasures. A possible approach for satisfying these requirements is employment of threat modeling concepts, which have been successfully applied in traditional paradigms. In this work, we employ threat models including attack trees, attack graphs and Data Flow Diagrams against a Cloud Service Broker (CloudRAID) and analyze these security threats and risks. Furthermore, we propose an innovative technique for combining Common Vulnerability Scoring System (CVSS) and Common Configuration Scoring System (CCSS) base scores in probabilistic attack graphs to cater for configuration-based vulnerabilities which are typically leveraged for attacking cloud storage systems. This approach is necessary since existing schemes do not provide sufficient security metrics, which are imperatives for comprehensive risk assessments. We demonstrate the efficiency of our proposal by devising CCSS base scores for two common attacks against cloud storage: Cloud Storage Enumeration Attack and Cloud Storage Exploitation Attack. These metrics are then used in Attack Graph Metric-based risk assessment. Our experimental evaluation shows that our approach caters for the aforementioned gaps and provides efficient security hardening options. Therefore, our proposals can be employed to improve cloud security.
High storage density magnetic devices rely on the precise, reliable and ultrafast switching times of the magnetic states. Optical control of magnetization using femtosecond laser without applying any external magnetic field offers the advantage of switching magnetic states at ultrashort time scales, which has attracted a significant attention. Recently, it has been reported and demonstrated the,so-called, all-optical helicity-dependent switching (AO-HDS) in which a circularly polarized femtosecond laser pulse switches the magnetization of a ferromagnetic thin film as function of laser helicity [1]. Afterward, in more recent studies, it has been reported that AO-HDS is a general phenomenon existing in magnetic materials ranging from rare earth - transition metals ferrimagnetic (e.g. alloys, multilayers and hetero-structures system) to even ferromagnetic thin films. Among numerous studies in the literature which are discussing the microscopic origin of AO-HDS in ferromagnets or ferrimagnetic alloys, the most renowned concepts are momentum transfer via Inverse Faraday Effect (IFE) [1-3]and the concept of preferential thermal demagnetization for one magnetization direction by heating close to Tc (Curie temperature) in the presence of magnetic circular dichroism (MCD) [4-6]. In this study, we investigate all-optical magnetic switching using a stationary femtosecond laser spot (3-5 μm) in TbFe alloys via photoemission electron microscopy (PEEM) and x-ray magnetic circular dichroism (XMCD) with a spatial resolution of approximately 30 nm. We spatially characterize the effect of laser heating and local temperature profile created across the laser spot on AO-HDS in TbFe thin films. We find that AO-HDS occurs only in a `ring' shaped region surrounding the thermally demagnetized region formed by the laser spot and the formation of switched domains relies further on thermally induced domain wall motion. Our temperature dependent measurements highlight the importance of attainin...
Development of a tool to identify intensive care patients at risk of meropenem therapy failure
(2018)
The problem of constructing and maintaining a tree topology in a distributed manner is a challenging task in WSNs. This is because the nodes have limited computational and memory resources and the network changes over time. We propose the Dynamic Gallager-Humblet-Spira (D-GHS) algorithm that builds and maintains a minimum spanning tree. To do so, we divide D-GHS into four phases, namely neighbor discovery, tree construction, data collection, and tree maintenance. In the neighbor discovery phase, the nodes collect information about their neighbors and the link quality. In the tree construction, D-GHS finds the minimum spanning tree by executing the Gallager-Humblet-Spira algorithm. In the data collection phase, the sink roots the minimum spanning tree at itself, and each node sends data packets. In the tree maintenance phase, the nodes repair the tree when communication failures occur. The emulation results show that D-GHS reduces the number of control messages and the energy consumption, at the cost of a slight increase in memory size and convergence time.
An energy consumption model for multiModal wireless sensor networks based on wake-up radio receivers
(2018)
Energy consumption is a major concern in Wireless Sensor Networks. A significant waste of energy occurs due to the idle listening and overhearing problems, which are typically avoided by turning off the radio, while no transmission is ongoing. The classical approach for allowing the reception of messages in such situations is to use a low-duty-cycle protocol, and to turn on the radio periodically, which reduces the idle listening problem, but requires timers and usually unnecessary wakeups. A better solution is to turn on the radio only on demand by using a Wake-up Radio Receiver (WuRx). In this paper, an energy model is presented to estimate the energy saving in various multi-hop network topologies under several use cases, when a WuRx is used instead of a classical low-duty-cycling protocol. The presented model also allows for estimating the benefit of various WuRx properties like using addressing or not.
Scrum2kanban
(2018)
Using university capstone courses to teach agile software development methodologies has become commonplace, as agile methods have gained support in professional software development. This usually means students are introduced to and work with the currently most popular agile methodology: Scrum. However, as the agile methods employed in the industry change and are adapted to different contexts, university courses must follow suit. A prime example of this is the Kanban method, which has recently gathered attention in the industry. In this paper, we describe a capstone course design, which adds the hands-on learning of the lean principles advocated by Kanban into a capstone project run with Scrum. This both ensures that students are aware of recent process frameworks and ideas as well as gain a more thorough overview of how agile methods can be employed in practice. We describe the details of the course and analyze the participating students' perceptions as well as our observations. We analyze the development artifacts, created by students during the course in respect to the two different development methodologies. We further present a summary of the lessons learned as well as recommendations for future similar courses. The survey conducted at the end of the course revealed an overwhelmingly positive attitude of students towards the integration of Kanban into the course.
802.15.4 security protects against the replay, injection, and eavesdropping of 802.15.4 frames. A core concept of 802.15.4 security is the use of frame counters for both nonce generation and anti-replay protection. While being functional, frame counters (i) cause an increased energy consumption as they incur a per-frame overhead of 4 bytes and (ii) only provide sequential freshness. The Last Bits (LB) optimization does reduce the per-frame overhead of frame counters, yet at the cost of an increased RAM consumption and occasional energy-and time-consuming resynchronization actions. Alternatively, the timeslotted channel hopping (TSCH) media access control (MAC) protocol of 802.15.4 avoids the drawbacks of frame counters by replacing them with timeslot indices, but findings of Yang et al. question the security of TSCH in general. In this paper, we assume the use of ContikiMAC, which is a popular asynchronous MAC protocol for 802.15.4 networks. Under this assumption, we propose an Intra-Layer Optimization for 802.15.4 Security (ILOS), which intertwines 802.15.4 security and ContikiMAC. In effect, ILOS reduces the security-related per-frame overhead even more than the LB optimization, as well as achieves strong freshness. Furthermore, unlike the LB optimization, ILOS neither incurs an increased RAM consumption nor requires resynchronization actions. Beyond that, ILOS integrates with and advances other security supplements to ContikiMAC. We implemented ILOS using OpenMotes and the Contiki operating system.
The present work is part of a collaborative H2020 European funded research project called SENSKIN, that aims to improve Structural Health Monitoring (SHM) for transport infrastructure through the development of an innovative monitoring and management system for bridges based on a novel, inexpensive, skin-like sensor. The integrated SENSKIN technology will be implemented in the case of steel and concrete bridges, and tested, field-evaluated and benchmarked on actual bridge environment against a conventional health monitoring solution developed by Mistras Group Hellas. The main objective of the present work is to implement the autonomous, fully functional strain monitoring system based on commercially available off-the-shelf components, that will be used to accomplish direct comparison between the performance of the innovative SENSKIN sensors and the conventional strain sensors commonly used for structural monitoring of bridges. For this purpose, the mini Structural Monitoring System (mini SMS) of Physical Acoustics Corporation, a comprehensive data acquisition unit designed specifically for long-term unattended operation in outdoor environments, was selected. For the completion of the conventional system, appropriate foil-type strain sensors were selected, driven by special conditioners manufactured by Mistras Group. A comprehensive description of the strain monitoring system and its peripheral components is provided in this paper. For the evaluation of the integrated system’s performance and the effect of various parameters on the long-term behavior of sensors, several test steel pieces instrumented with different strain sensors configurations were prepared and tested in both laboratory and field ambient conditions. Furthermore, loading tests were performed aiming to validate the response of the system in monitoring the strains developed in steel beam elements subject to bending regimes. Representative results obtained from the above experimental tests have been included in this paper as well.
CurEx
(2018)
The integration of diverse structured and unstructured information sources into a unified, domain-specific knowledge base is an important task in many areas. A well-maintained knowledge base enables data analysis in complex scenarios, such as risk analysis in the financial sector or investigating large data leaks, such as the Paradise or Panama papers. Both the creation of such knowledge bases, as well as their continuous maintenance and curation involves many complex tasks and considerable manual effort. With CurEx, we present a modular system that allows structured and unstructured data sources to be integrated into a domain-specific knowledge base. In particular, we (i) enable the incremental improvement of each individual integration component; (ii) enable the selective generation of multiple knowledge graphs from the information contained in the knowledge base; and (iii) provide two distinct user interfaces tailored to the needs of data engineers and end-users respectively. The former has curation capabilities and controls the integration process, whereas the latter focuses on the exploration of the generated knowledge graph.
Beacon in the Dark
(2018)
The large amount of heterogeneous data in these email corpora renders experts' investigations by hand infeasible. Auditors or journalists, e.g., who are looking for irregular or inappropriate content or suspicious patterns, are in desperate need for computer-aided exploration tools to support their investigations.
We present our Beacon system for the exploration of such corpora at different levels of detail. A distributed processing pipeline combines text mining methods and social network analysis to augment the already semi-structured nature of emails. The user interface ties into the resulting cleaned and enriched dataset. For the interface design we identify three objectives expert users have: gain an initial overview of the data to identify leads to investigate, understand the context of the information at hand, and have meaningful filters to iteratively focus onto a subset of emails. To this end we make use of interactive visualisations based on rearranged and aggregated extracted information to reveal salient patterns.
The detection of all inclusion dependencies (INDs) in an unknown dataset is at the core of any data profiling effort. Apart from the discovery of foreign key relationships, INDs can help perform data integration, integrity checking, schema (re-)design, and query optimization. With the advent of Big Data, the demand increases for efficient INDs discovery algorithms that can scale with the input data size. To this end, we propose S-INDD++ as a scalable system for detecting unary INDs in large datasets. S-INDD++ applies a new stepwise partitioning technique that helps discard a large number of attributes in early phases of the detection by processing the first partitions of smaller sizes. S-INDD++ also extends the concept of the attribute clustering to decide which attributes to be discarded based on the clustering result of each partition. Moreover, in contrast to the state-of-the-art, S-INDD++ does not require the partition to fit into the main memory-which is a highly appreciable property in the face of the ever growing datasets. We conducted an exhaustive evaluation of S-INDD++ by applying it to large datasets with thousands attributes and more than 266 million tuples. The results show the high superiority of S-INDD++ over the state-of-the-art. S-INDD++ reduced up to 50 % of the runtime in comparison with BINDER, and up to 98 % in comparison with S-INDD.
One particular challenge in the Internet of Things is the management of many heterogeneous things. The things are typically constrained devices with limited memory, power, network and processing capacity. Configuring every device manually is a tedious task. We propose an interoperable way to configure an IoT network automatically using existing standards. The proposed NETCONF-MQTT bridge intermediates between the constrained devices (speaking MQTT) and the network management standard NETCONF. The NETCONF-MQTT bridge generates dynamically YANG data models from the semantic description of the device capabilities based on the oneM2M ontology. We evaluate the approach for two use cases, i.e. describing an actuator and a sensor scenario.
Live migration is an important feature in modern software-defined datacenters and cloud computing environments. Dynamic resource management, load balance, power saving and fault tolerance are all dependent on the live migration feature. Despite the importance of live migration, the cost of live migration cannot be ignored and may result in service availability degradation. Live migration cost includes the migration time, downtime, CPU overhead, network and power consumption. There are many research articles that discuss the problem of live migration cost with different scopes like analyzing the cost and relate it to the parameters that control it, proposing new migration algorithms that minimize the cost and also predicting the migration cost. For the best of our knowledge, most of the papers that discuss the migration cost problem focus on open source hypervisors. For the research articles focus on VMware environments, none of the published articles proposed migration time, network overhead and power consumption modeling for single and multiple VMs live migration. In this paper, we propose empirical models for the live migration time, network overhead and power consumption for single and multiple VMs migration. The proposed models are obtained using a VMware based testbed.
The electromagnetic coupling of molecular excitations to plasmonic nanoparticles offers a promising method to manipulate the light-matter interaction at the nanoscale. Plasmonic nanoparticles foster exceptionally high coupling strengths, due to their capacity to strongly concentrate the light-field to sub-wavelength mode volumes. A particularly interesting coupling regime occurs, if the coupling increases to a level such that the coupling strength surpasses all damping rates in the system. In this so-called strong-coupling regime hybrid light-matter states emerge, which can no more be divided into separate light and matter components. These hybrids unite the features of the original components and possess new resonances whose positions are separated by the Rabi splitting energy h Omega. Detuning the resonance of one of the components leads to an anticrossing of the two arising branches of the new resonances omega(+) and omega(-) with a minimal separation of Omega = omega(+) - omega(-).
The coupling between molecular excitations and nanoparticles leads to promising applications. It is for example used to enhance the optical cross-section of molecules in surface enhanced Raman scattering, Purcell enhancement or plasmon enhanced dye lasers. In a coupled system new resonances emerge resulting from the original plasmon (ωpl) and exciton (ωex) resonances as
ω±=12(ωpl+ωex)±14(ωpl−ωex)2+g2−−−−−−−−−−−−−−−√,
(1)
where g is the coupling parameter. Hence, the new resonances show a separation of Δ = ω+ − ω− from which the coupling strength can be deduced from the minimum distance between the two resonances, Ω = Δ(ω+ = ω−).
An IoT network may consist of hundreds heterogeneous devices. Some of them may be constrained in terms of memory, power, processing and network capacity. Manual network and service management of IoT devices are challenging. We propose a usage of an ontology for the IoT device descriptions enabling automatic network management as well as service discovery and aggregation. Our IoT architecture approach ensures interoperability using existing standards, i.e. MQTT protocol and SemanticWeb technologies. We herein introduce virtual IoT devices and their semantic framework deployed at the edge of network. As a result, virtual devices are enabled to aggregate capabilities of IoT devices, derive new services by inference, delegate requests/responses and generate events. Furthermore, they can collect and pre-process sensor data. These tasks on the edge computing overcome the shortcomings of the cloud usage regarding siloization, network bandwidth, latency and speed. We validate our proposition by implementing a virtual device on a Raspberry Pi.
For the last ten years, almost every theoretical result concerning the expected run time of a randomized search heuristic used drift theory, making it the arguably most important tool in this domain. Its success is due to its ease of use and its powerful result: drift theory allows the user to derive bounds on the expected first-hitting time of a random process by bounding expected local changes of the process - the drift. This is usually far easier than bounding the expected first-hitting time directly. Due to the widespread use of drift theory, it is of utmost importance to have the best drift theorems possible. We improve the fundamental additive, multiplicative, and variable drift theorems by stating them in a form as general as possible and providing examples of why the restrictions we keep are still necessary. Our additive drift theorem for upper bounds only requires the process to be nonnegative, that is, we remove unnecessary restrictions like a finite, discrete, or bounded search space. As corollaries, the same is true for our upper bounds in the case of variable and multiplicative drift.
One of the most important aspects of a randomized algorithm is bounding its expected run time on various problems. Formally speaking, this means bounding the expected first-hitting time of a random process. The two arguably most popular tools to do so are the fitness level method and drift theory. The fitness level method considers arbitrary transition probabilities but only allows the process to move toward the goal. On the other hand, drift theory allows the process to move into any direction as long as it move closer to the goal in expectation; however, this tendency has to be monotone and, thus, the transition probabilities cannot be arbitrary. We provide a result that combines the benefit of these two approaches: our result gives a lower and an upper bound for the expected first-hitting time of a random process over {0,..., n} that is allowed to move forward and backward by 1 and can use arbitrary transition probabilities. In case that the transition probabilities are known, our bounds coincide and yield the exact value of the expected first-hitting time. Further, we also state the stationary distribution as well as the mixing time of a special case of our scenario.
For theoretical analyses there are two specifics distinguishing GP from many other areas of evolutionary computation. First, the variable size representations, in particular yielding a possible bloat (i.e. the growth of individuals with redundant parts). Second, the role and realization of crossover, which is particularly central in GP due to the tree-based representation. Whereas some theoretical work on GP has studied the effects of bloat, crossover had a surprisingly little share in this work. We analyze a simple crossover operator in combination with local search, where a preference for small solutions minimizes bloat (lexicographic parsimony pressure); the resulting algorithm is denoted Concatenation Crossover GP. For this purpose three variants of the wellstudied Majority test function with large plateaus are considered. We show that the Concatenation Crossover GP can efficiently optimize these test functions, while local search cannot be efficient for all three variants independent of employing bloat control.