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We present a comprehensive analysis of the neural audio-visual synchrony evaluation tool SyncNet. We assess the agreement of SyncNet scores vis-a-vis human perception and whether we can use these as a reliable metric for evaluating audio-visual lip-synchrony in generation tasks with no ground truth reference audio-video pair. We further look into the underlying elements in audio and video which vitally affect synchrony using interpretable explanations from SyncNet predictions and analyse its susceptibility by introducing adversarial noise. SyncNet has been used in numerous papers on visually-grounded text-to-speech for scenarios such as dubbing. We focus on this scenario which features many local asynchronies (something that SyncNet isn’t made for).
Development trends for computing platforms moved from increasing the frequency of a single processor to increasing the parallelism with multiple cores on the same die. Multiple cores have strong potential to support cost-efficient fault tolerance due to their inherent spatial redundancy. This work makes a step towards software-only fault tolerance in the presence of permanent and transient hardware faults. Our approach utilizes software-based spatial triple modular redundancy and coded processing on a shared memory multi-core controller. We evaluate our approach on an Infineon AURIX TriBoard TC277 and provide experimental evidence for error resistance by fault injection campaigns with an iSystem iC5000 On-chip Analyzer.
A new approach to coat PA12 powders with laser-generated nanoparticles for selective laser sintering
(2018)
The modification of selective laser sintering (SLS) powder materials by nanoadditives offers the possibility to adapt the powder properties to the laser sintering process or the resulting part properties. To avoid agglomeration of the nanofiller, a new approach in which surfactant-free laser-generated colloidal nanoparticles are adsorbed onto the polymer surface directly in an aqueous solution is demonstrated. Based on this novel approach, polyamide 12 (PA12) powders are decorated with metal and oxide nanoparticles and processed via SLS. Electron microscopy and confocal laser scanning imaging are utilized to analyze the dispersion of the filler.
A Parametrization Scheme for High Performance Thermal Models of Electric Machines using Modelica
(2012)
Thermal models offer great advantages for enhancement of design, protection and control of electric machines. Detailed thermal models take a great number of time constants into account and provide accurate prediction of the temperatures. However, to parameterize such models detailed geometric data are needed. Whenever such detailed information is not available, or the performance of the detailed models is not satisfying, simplified thermal models as described in this paper are advantageous. The calculation of parameters is described in detail, in order to achieve best accordance with temperatures obtained from measurements or from simulations with detailed thermal models. Thermal resistances are calculated from end temperatures of a test run with constant load (and known losses). Thermal capacitances are obtained using optimization to minimize deviation of simulated and measured temperatures during the whole test run. The thermal model of an asynchronous induction machine with squirrel cage is coupled with an electrical model of the drive. For validation, simulation results of an optimally parameterized simplified model are compared with temperatures obtained by simulation of a detailed thermal model, which in turn has been validated against measurement results, both for continuous duty S1 and intermittent duty S6 (6 minutes no-load followed by 4 minutes of 140% nominal load). The deviations are not more than 4 K which is quite satisfying.
Adding experts’ perceptions to complement existing research on information systems backsourcing
(2018)
This paper extends the existing literature on information systems (IS) backsourcing by the perception of practitioners.
For this purpose, we conducted a series of qualitative, semistructured interviews with IS sourcing experts. The interview questions focused on the participants’ perceptions and experiences with the topic, on identifying reasons for and against IS backsourcing, and on revealing relevant trends pertinent to IS backsourcing. We then compared those
findings with two previously conducted comprehensive literature reviews on academic and practitioner literature on IS backsourcing. By following this approach, we contribute to the existing research by verifying previous findings, for example, the most important reasons why companies decide in favor of IS backsourcing. Additionally, we were able to enhance previous contributions as we highlight the significance of differentiating between the scope of IS backsourcing
by looking at the underlying services which are potentially backsourced. Further, we identified the importance of managers’ personal preferences as an additional reason for IS backsourcing, for example, based on personal experiences or a perceived need for change. Based on our findings, we created a comprehensive overview of all aspects connected to the IS backsourcing process and derived opportunities for further research to contribute to the IS backsourcing research agenda.
Abstract Social network analysis is extremely well supported by the R community and is routinely used for studying the relationships between people engaged in collaborative activities. While there has been rapid development of new approaches and metrics in this field, the challenging question of validity (how well insights derived from social networks agree with reality) is often difficult to address. We propose the use of several R packages to generate interactive surveys that are specifically well suited for validating social network analyses. Using our web-based survey application, we were able to validate the results of applying community-detection algorithms to infer the organizational structure of software developers contributing to open-source projects.
In modern manufacturing systems, milk run (MR) systems represent route-based, cyclic material-handling systems that are used widely and enable frequent deliveries of containerized parts in small lot sizes from a central storage area to multiple points of use on the factory floor. Usually, deliveries take place at predetermined, constant time intervals. As in real-world MR systems, the number of containers to deliver in each interval varies in the short term, peaks in the number of deliveries may lead to capacity bottlenecks and late deliveries. In this paper, we develop three alternative strategies to determine starting times of MR cycles in real-time based on the current number of delivery orders in the system aiming to better handle variations in the number of orders. We evaluate the three strategies for different system load scenarios with respect to delivery service levels, order lead times, systems utilization and necessary number of MR trains using a discrete-event simulation model.
Background
Older adults in care facilities face a high risk of experiencing depression. The impact that early interventions like biographical work have on the quality of life for older adults in such facilities is unknown.
Aim
To develop and evaluate a tablet-supported intervention for biographical work in long-term residential aged care to increase the quality of life for older adults.
Design
The study will be conducted in a randomized pretest–posttest control group design with follow-up testing in group and single settings. Participants will be randomized to the experimental intervention (tablet-supported biographic work) or the control intervention (planned tablet-supported game playing), each guided by senior volunteers. A total of 80 residents and 16 volunteers will be recruited. The primary outcome for the residents and volunteers will be quality of life as measured with the World Health Organization Quality of Life Assessment-for older adults. Secondary measures will be self-esteem and life satisfaction. In addition, we will examine residents’ ability to communicate and their functional independence.
Method
The first stage of the project involves developing an app. The app is developed in a user-centered, agile development process. It will use multimedia to prepare life history topics and links them to key questions. Next, a workshop is developed for the volunteers who accompany the use of the app in the institutions. During the second phase, biographic work stimulated by the app will be conducted in groups or individually with residents.
Discussion
This is the first known program tailored to older adults in care facilities and senior volunteers that aims to prevent depression by providing digitally supported biographic work.
Shadow IT and Business-managed IT describe the autonomous deployment/procurement or management of Information Technology (IT) instances, i.e., software, hardware, or IT services, by business entities. For Shadow IT, this happens covertly, i.e., without alignment with the IT organization; for Business-managed IT this happens overtly, i.e., in alignment with the IT organization or in a split responsibility model. We conduct a systematic literature review and structure the identified research themes in a framework of causing factors, outcomes, and governance. As causing factors, we identify enablers, motivators, and missing barriers. Outcomes can be benefits as well as risks/shortcomings of Shadow IT and Business-managed IT. Concerning governance, we distinguish two subcategories: general governance for Shadow IT and Business-managed IT and instance governance for overt Business-managed IT. Thus, a specific set of governance approaches exists for Business-managed IT that cannot be applied to Shadow IT due to its covert nature. Hence, we extend the existing conceptual understanding and allocate research themes to Shadow IT, Business-managed IT, or both concepts and particularly distinguish the governance of the two concepts. Besides, we find that governance themes have been the primary research focus since 2016, whereas older publications (until 2015) focused on causing factors.
The present paper provides an overview on current developments of cash usage and issue of central bank digital currency (CBDC) in the euro area and proposes a possible design of a digital euro that allows for instant offline payments. Cash usage at the point-of-sale decreased perceptibly in the past years mainly due to the ongoing trend towards digitalization. However, we show that there are also indications that consumers were somewhat pushed into cashless payments by government regulations and supply-side restrictions by commercial banks. Nonetheless, overall demand for euro cash remained strong and even increased relative to GDP since the financial crisis in 2008. In this process, however, we observe a supply-driven shift towards lower banknote denominations. Central banks all over the world are intensively thinking about the potential issue of CBDC as a substitute or complement to cash. Based on some of its preferred characteristics, we propose a double pre-paid scheme combining central elements of TARGET Instant Payment Settlement and electronic money features enabling offline and online instant payments. Since anonymity is categorically discarded by the ECB and as cash has some special advantages from a consumer perspective, the digital euro will rather co-circulate with cash than replace it in transactions.
Lean Management is a standard production mode that has been familiar to production organizations for several decades. To date, however, academic literature has presented surprisingly little information about the application of Lean Management in Information Technology (IT) organizations, or what is called Lean IT. Drawing upon an empirical qualitative case study of the IT departments of two multinational companies, in this paper we identify change management lessons learned for Lean IT implementations, as well as seven characteristics of a corresponding change management approach. As an extension of our work, researchers should validate and expand our initial findings, preferably in a quantitative setting.
Coupling energy sectors within the emerging residential PV prosumer systems is necessary for an optimised use of the houseowners’ own produced electricity. But the pure availability of different energy technologies in the system is not enough. By optimising the electricity usage as well as the capacities of PV generators, storage technologies, heat pumps and battery electric vehicles, not only the best solution in a technical point of view can be achieved, the need of finding the most financially beneficial system composition for single-family houses and tenements is possible. The study provides a detailed model for average German single-family houses and tenements and results for the energy transition period until 2050 for the optimised energy systems regarding optimised PV and stationary battery capacities and different heat storage capacities. Most noticeable outcomes can be observed by using a vehicle-to-home car, where a car can mostly take over the tasks of a stationary battery and by introducing a solidarity model using this type of car in tenement systems.
Decision-making in supply chain management is complex because of the relations between planning tasks from different stages and planning levels. Uncertainties such as unpredictable supplier lead times and supply chain disruptions further complicate decision-making. Considering the case study of a company in printed circuit board assembly, a three-level concept is proposed that includes a decision support system. The global single-source supply network is characterized by highly variable lead times. Hence, the company maintains high inventory levels to prevent running out of stock. The decision support system considers the purchasing and scheduling decision problems in an integrated way. The prototypical implementation of the purchasing algorithm uses a genetic algorithm that recommends reorder days and order quantities using a simulation model. In addition, it evaluates the risks of the recommended solution by calculating the probability of stockouts for each order cycle.
Digital Twin of a Photoacoustic Trace Gas Sensor for Monitoring Methane in Complex Gas Compositions
(2022)
The digitalization of industrial processes requires smart sensor systems. Photoacoustic spectroscopy is well suited for this purpose as it allows for small-sized and low-cost trace gas analysis. However, the method is susceptible to changes in measurement conditions and standard calibration routines often fail to correct for all changes. We therefore created a Digital Twin (DT) of a photoacoustic trace gas sensor for methane and evaluated it regarding variations in gas composition (CH4, N2, O2, CO2, H2O), temperature and pressure. With a mean absolute percentage error of 0.8 % the accuracy of the sensor after DT compensation significantly exceeds the 24 % achieved based on standard calibration in nitrogen. For the first time, we can fully analytically compute the photoacoustic signal under moderate ambient conditions with an error in the ppbV range by taking a holistic approach. Assuming knowledge of the underlying energy transfer processes, the model of this Digital Twin can be adapted to any microphone based photoacoustic sensor for monitoring any analyte species.
Exploring Opportunities
(2017)
Motivated by the increasing share of renewable energy in the markets for energy commodities, this study has evaluated the potential for optimizing production planning by taking into account disposable options for procuring energy, in this case electricity. For this purpose, a material flow simulation study extended by an electricity price simulation has been executed to examine possible cost scenarios. Our findings support the notion of a potential for further research in new optimization models involving energy procurement as well as energy trading options
A factory has to adapt to a future production program and increasing volumes. The planning of new factories must therefore already take expansion stages and reconfigurations into account. This leads to an increase in the complexity of planning, as different variants have to be planned and put into a chronologically reasonable and cost-optimized sequence. A factory data model that covers expansion stages manages the planning data amount and reduces complexity. Based on existing models from the literature, a factory data model was developed and modeled in the Unified Modeling Language standard. The factory data model shows which classes are interdependent and how planning results are stored reusable for other variants. An example is used to explain the developed factory data model and highlighting its advantages. The aim is to enable factory planners to document variant sequences and expansion stages in a comprehensible way, which supports the interdisciplinarity of factory planning projects.
The transition towards services has been imperative for manufacturing firms for years. The change from a productoriented to a more service-dominant business model affects the organizational structure of firms. However, literature provides limited insights into how manufacturing firms organize themselves in this transition. Even though digital technologies are critical for the transition, it is unclear how to orchestrate digital and traditional Information Technology (IT) resources in manufacturing firms accordingly. We analyze the case of a typical manufacturing firm that has adjusted its structure to reorganize for solution offerings based on product, service, and digital components. Our results describe a hybrid organizational structure that splits front- and back-end units. The back-end units are split along solution components. Digital IT resources are internalized and governed decentrally, with traditional IT resources being outsourced and steered centrally. Our findings contribute to digital servitization research by clarifying the overarching as well as the digital and traditional IT-related organization for manufacturing firms.
Serial 2D section images with high resolution, resulting from innovative imaging methods become even more valuable, if they are fused with in vivo volumes. Achieving this goal, the 3D context of the sections would be restored, the deformations would be corrected and the artefacts would be eliminated. However, the registration in this field faces big challenges and is not solved in general. On the other hand, several approaches have been introduced dealing at least with some of these difficulties. Here, a brief overview of the topic is given and some of the solutions are presented. It does not constitute the claim to be a complete review, but could be a starting point for those who are interested in this field.
The University of Shanghai for Science and Technology (USST), the Coburg University of Applied Sciences and Arts (CUASA) and the OTH Regensburg, University of Applied Sciences (OTHR) established an English taught international cooperative bachelor program in the area of Engineering Physics/Optoelectronics. Students from China study their first four semesters at USST. They continue their studies in Germany for the last three semesters, including an internship and a bachelor thesis, graduating with a Chinese and a German bachelor degree. Students from Germany study their third and fourth semester at USST to gain international experience. While the first cohort of Chinese students is currently in Germany, the second cohort of German students is in Shanghai. Up to now the feedback regarding this study program is completely positive, thus it is planned to develop it further.
The label-free nature of surface plasmon resonance techniques (SPR) enables a fast, specific, and sensitive analysis of molecular interactions. However, detection of highly diluted concentrations and small molecules is still challenging. It is shown here that in contrast to continuous gold films, gold nanohole arrays can significantly improve the performance of SPR devices in angle-dependent measurement mode, as a signal amplification arises from localized surface plasmons at the nanostructures. This leads consequently to an increased sensing capability of molecules bound to the nanohole array surface. Furthermore, a reduced graphene oxide (rGO) sensor surface was layered over the nanohole array. Reduced graphene oxide is a 2D nanomaterial consisting of sp<sup>2</sup>-hybridized carbon atoms and is an attractive receptor surface for SPR as it omits any bulk phase and therefore allows fast response times. In fact, it was found that nanohole arrays demonstrated a higher shift in the resonance angle of 250-380% compared to a continuous gold film. At the same time the nanohole array structure as characterized by its diameter-to-periodicity ratio had minimal influence on the binding capacity of the sensor surface. As a simple and environmentally highly relevant model, binding of the plasticizer diethyl phthalate (DEP) via π-stacking was monitored on the rGO gold nanohole array realizing a limit of detection of as low as 20 nM. The concentration-dependent signal change was studied with the best performing rGO-modified nanohole arrays. Compared to continuous gold films a diameter-to-periodicity ratio (<i>D</i>/<i>P</i>) of 0.43 lead to a 12-fold signal enhancement. Finally, the effect of environmental waters on the sensor was evaluated using samples from sea, lake and river waters spiked with analytically relevant amounts of DEP during which significant changes in the SPR signal are observed. It is expected that this concept can be successfully transferred to enhance the sensitivity in SPR sensors.