Information und Kommunikation
Refine
Year of publication
- 2021 (22) (remove)
Document Type
- conference proceeding (article) (12)
- Article (7)
- Part of a Book (1)
- Preprint (1)
- Report (1)
Language
- English (22)
Is part of the Bibliography
- no (22)
Keywords
- Cloud Computing (2)
- Collaborative Learning (1)
- Continuous Deployment (1)
- Continuous Monitoring (1)
- Continuous delivery (1)
- Continuous integration (1)
- Critical Infrastructure (1)
- Crowdsourcing (1)
- Cybersecurity (1)
- DEGREE-N (1)
Institute
- Fakultät Informatik und Mathematik (15)
- Regensburg Strategic IT Management (ReSITM) (6)
- Fakultät Elektro- und Informationstechnik (5)
- Fakultät Angewandte Natur- und Kulturwissenschaften (2)
- Labor Bauphysik (1)
- Labor Industrielle Elektronik (1)
- Laboratory for Safe and Secure Systems (LAS3) (1)
- Mechatronics Research Unit (MRU) (1)
Begutachtungsstatus
- peer-reviewed (15)
The vernier or nonius (in other languages) goes back to a measuring tool used in navigation and astronomy named after its inventor Pedro Nunes (1502–1578; Latin: Petrus Nonius), a Portuguese mathematician and navigator. The nonius was created in 1542 to take finer measurements on circular instruments such as the astrolabe. In 1631 the French mathematician Pierre Vernier (1580–1637) adapted and simplified the system which was later denoted “vernier”.
We present a method to construct a vernier-like scale for logarithmic scales (as used for typical slide rules), which results in variable tick spacings. The idea is to put the non-linear scale on a spiral. The method can be applied to any non-linear scale, not only logarithmic scales.
Networked control systems as e.g., battery management systems, smart grids or vehicular systems, consist of sensors, actuators and controllers with a communication network in the control loop. The data rate and the reliability of the underlying communication network are key factors since delays or message losses directly affect the system control. In addition, the processor load caused by the communication is significant as it influences the calculation of system states and the setting of control parameters. The power consumption of the communication network has a further impact on the energy efficiency of the respective application. In this paper, the communication technologies Controller Area Network (CAN), Controller Area Network Flexible Data-rate (CAN FD) and Ethernet are compared in the context of networked control systems with focus on a decentralized battery management system. First, the message processing time and the processor load are measured. With regard to energy efficiency, the maximum power consumption is determined. The Bit Error Rates (BER) and the Residual Error Rates (RER) are calculated to evaluate the reliability. Finally, the receive FIFO load under high traffic conditions is examined. Index Terms—Networked control systems, decentralized battery management system, microcontrollers, communication systems, Ethernet, Controller Area Network (CAN), Controller Area Network Flexible Data-rate (CAN FD) energy efficiency, energy consumption, bit error rate, residual error rate, processor load.
This article compares the standard electrical method of partial discharge detection with a novel optical detection method based on silicon photomultipliers. A third, complementary, single-loop antenna method is added to represent the ultra-high frequency method commonly used in gas-insulated switchgear/lines. A trio of air-insulated electrode designs that simulate the fundamental fault/discharge types in gaseous insulation (protrusion – corona discharge, floating conductive particle, surface discharges) are employed. Phase-resolved partial discharge activity patterns are compiled for each electrode design. The patterns are analyzed using spatial statistics and the interpretation of the obtained data trends explained by means of an example. Ultimately, the consistency and reliability of discharge detection by the optical methods for each fault/discharge type are evaluated, and suggestions for improvement are made.
Dubbing, i.e., the lip-synchronous translation and revoicing of audio-visual media into a target language from a different source language, is essential for the full-fledged reception of foreign audio-visual media, be it movies, instructional videos or short social media clips. In this paper, we objectify influences on the ‘dubbability’ of translations, i.e., how well a translation would be synchronously revoiceable to the lips on screen. We explore the value of traditional heuristics used in evaluating the qualitative aspects, in particular matching bilabial consonants and the jaw opening while producing vowels, and control for quantity, i.e., that translations are similar to the source in length. We perform an ablation study using an adversarial neural classifier which is trained to differentiate “true” dubbing translations from machine translations. While we are able to confirm the value of matching lip closure in dubbing, we find that the opening angle of the jaw as determined by the realized vowel may be less relevant than frequently considered in audio-visual translation.
In this paper, we present a study in which a robot initiates interactions with people passing by in an in-the-wild scenario. The robot adapts the loudness of its voice dynamically to the distance of the respective person approached, thus indicating who it is talking to. It furthermore tracks people based on information on body orientation and eye gaze and adapts the text produced based on people's distance autonomously. Our study shows that the adaptation of the loudness of its voice is perceived as personalization by the participants and that the likelihood that they stop by and interact with the robot increases when the robot incrementally adjusts its behavior.
We present an open source plugin for live subtitling in the popular open source video conferencing software BigBlueBut-ton. Our plugin decodes each speaker’s audio stream separately and in parallel, thereby obliviating the need for speaker di-arization and seamlessly handling overlapped talk. Any Kaldi-compatible nnet3 model can be used with our plugin and we demonstrate it using freely available TDNN-HMM-based ASR models for English and German. Our subtitles can be used as they are (e.g., in loud environments) or can form the basis for further NLP processes. Our tool can also simplify the collection of remotely recorded multi-party dialogue corpora.
We present a fully automatic solution for German video subtitling, with a focus on lecture videos. We rely entirely on open source models and scripts for German ASR, automatic punctuation reconstruction and subtitle segmentation. All training scripts, 1000h of German speech training data, pre-trained models and the final subtitling program are publicly available. It can readily be integrated into lecture video platforms such as Lecture2Go. The automatically generated subtitles can also serve as a basis to make the video material more accessible (e.g. via search, keyword clouds, and the like) or for further manual revision, potentially helping in significantly speeding up manual work. A particular challenge that we observe in lectures are technical terms that are frequent in a particular lecture, but infrequent in a typical language model and that might be out of vocabulary for a general purpose ASR. We approach this challenge by extracting texts from accompanying lecture slides to adapt the language model of our TDNN-HMM based ASR system. We demonstrate the usability of the full system and its generated subtitles and evaluate on a dataset of manually transcribed lectures with an average of 26.3% WER.
Speech quality and likability is a multi-faceted phenomenon consisting of a combination of perceptory features that cannot easily be computed nor weighed automatically. Yet, it is often easy to decide which of two voices one likes better, even though it would be hard to describe why, or to name the underlying basic perceptory features. Although likability is inherently subjective and individual preferences differ, generalizations are useful and there is often a broad intersubjective consensus about whether one speaker is more likeable than another. We present a methodology to efficiently create a likability ranking for many speakers from crowdsourced pairwise likability ratings which focuses manual rating effort on pairs of similar quality using an active sampling technique. Using this methodology, we collected pairwise likability ratings for many speakers (>220) from many raters (>160). We analyze listener preferences by correlating the resulting ranking with various acoustic and prosodic features. We also present a neural network that is able to model the complexity of listener preferences and the underlying temporal evolution of features. The recurrent neural network achieves remarkably high performance in estimating the pairwise decisions and an ablation study points toward the criticality of modeling temporal aspects in speech quality assessment.
The SMOOTH-robot is a mobile robot that-due to its modularity-combines a relatively low price with the possibility to be used for a large variety of tasks in a wide range of domains. In this article, we demonstrate the potential of the SMOOTH-robot through three use cases, two of which were performed in elderly care homes. The robot is designed so that it can either make itself ready or be quickly changed by staff to perform different tasks. We carefully considered important design parameters such as the appearance, intended and unintended interactions with users, and the technical complexity, in order to achieve high acceptability and a sufficient degree of utilization of the robot. Three demonstrated use cases indicate that such a robot could contribute to an improved work environment, having the potential to free resources of care staff which could be allocated to actual care-giving tasks. Moreover, the SMOOTH-robot can be used in many other domains, as we will also exemplify in this article.
Car manufacturers define proprietary protocols to be used inside their vehicular networks, which are kept an industrial secret, therefore impeding independent researchers from extracting information from these networks. This article describes a statistical and a neural network approach that allows reverse engineering proprietary controller area network (CAN)-protocols assuming they were designed using the data base CAN (DBC) file format. The proposed algorithms are tested with CAN traces taken from a real car. We show that our approaches can correctly reverse engineer CAN messages in an automated manner.
Cybersecurity is a complex global phenomenon where the risk for individuals, organisation and the society at large are at risk. These risks need to be in focus and solutions for the prevention and developing countermeasures. In this paper, we describe the Joint Effort Workshop as an approach to raise awareness to these threads and the possibility to generate and exchange knowledge between students and experts. We conclude that mechanisms for systematic response to attacks need the developed technical requirements, but foremost human behaviour, knowledge and resilience to response to risks, which can be experienced through the collaborative environment of the Joint Effort Workshop
Due to technological advances, IT is increasingly introduced and managed outside of (or even hidden from) an organisation's IT department. As a result, researchers and practitioners have created multiple concepts describing different facets and trends of this development. While the individual concepts typically focus on different aspects, there are overlaps between these concepts. This effect hampers research progress as it creates redundancies and separate streams of knowledge development. We propose a taxonomy of the concepts Lightweight IT, IT Consumerisation, Bring Your Own Device, Shadow IT, and Business-Managed IT to solve this research problem based on a systematic literature review. For this purpose, we derive characterising dimensions of each concept from existing studies and analyse literature according to the usage of terms. As a result, we can describe and delineate the concepts. Thus, we contribute a taxonomy of IT outside the IT department to improve the transfer of research results between research streams.
We prove a functional equation for a vector valued real analytic Eisenstein series transforming with the Weil representation of Sp(n, Z) on C[(L'/L)(n)]. By relating such an Eisenstein series with a real analytic Jacobi Eisenstein series of degree n, a functional equation for such an Eisenstein series is proved. Employing a doubling method for Jacobi forms of higher degree established by Arakawa, we transfer the aforementioned functional equation to a zeta function defined by the eigenvalues of a Jacobi eigenform. Finally, we obtain the analytic continuation and a functional equation of the standard L-function attached to a Jacobi eigenform, which was already proved by Murase, however in a different way.
Linear models are a mainstay in statistical pattern recognition but do not play a role in time series classification, because they fail to account for temporal variations. To overcome this limitation, we combine linear models with dynamic time warping (dtw). We analyze the resulting warped-linear models theoretically and empirically. The three main theoretical results are (i) the Representation Theorem, (ii) the Matrix Complexity Lemma, and (iii) local Lipschitz continuity of the warped softmax function. The Representation Theorem roughly states that warped-linear models correspond to polytope classifiers in Euclidean spaces. This key result is useful because it simplifies analysis of warped-linear models. For example, it provides a geometric interpretation, points to the label dependency problem, and justifies application of warped-linear models not only on temporal but also on multivariate data. The Representation Theorem together with the Matrix Complexity Lemma reveals that warped-linear models implement a weight trick by weight selection and massive weight sharing. Local Lipschitz continuity of warped softmax functions admits a principled training of warped-linear models by stochastic subgradient methods. Empirical results show that replacing the inner product of linear models with a dtw-score substantially improves its predictive performance. The theoretical and empirical contributions of this article provide a simple and efficient first-trial alternative to nearest-neighbor methods and open up new perspectives for more sophisticated classifiers such as warped deep learning.
The smooth transition between stable, Talbot-effect-dominated and modulationally unstable nonlinear optical beam propagation is described as the superposition of oscillating, growing and decaying eigenmodes of the common linearized theory of modulation instability. The saturation of the instability in form of breather maxima is embedded between eigenmode growth and decay. This explains well the changes of beam characteristics when the input intensity increases in experiments on modulation instability and breather excitation in spatial-spatial experimental platforms. An increased accuracy of instability gain measurements, a variety of interesting nonlinear beam scenarios and a more selective and well-directed breather excitation are demonstrated experimentally.
DevOps paradigm
(2021)
DevOps, the widely used term in software industry, integrates the Development and IT Operations activities to frequently deliver, deploy, and release quality software features. DevOps approach emphasizes collaboration among Developments and IT operations teams throughout System Development Life Cycle (SDLC). The DevOps process is supported by wide variety of tool chains for various phases of SDLC. There exist many DevOps models. However, in this paper authors use a simple four phase pedagogical models to demonstrate principles of DevOps. In this paper authors attempt to show how DevOps principles can effectively be used to manage and implement business problems in classroom setting. Specifically, DevOps methodology is applied to manage develop and implement a small web application.
This pedagogical approach is specially aimed at students who do not have prior experiences and skillsets in applying DevOps methodology and associated toolsets to every stages of SDLC. At the conclusion of the project, students gained valuable insights on how to apply DevOps principles to business problems and to select and use commonly used state of the arts tools to plan, manage, build, test, monitor, deploy tasks at every stages of DevOps. The authors also discuss the limitations and practical issues related to implementing DevOps within classroom settings.
IS resilience addresses the challenge of securing organizational information systems against disruptions to ensure the continuation of daily business processes and to guarantee the resilience of the organization as a whole. In this paper, we adopt Agency Theory and Weill’s IT Governance framework to investigate the decision priorities of senior executives in the context of IS resilience planning, which falls under the broader umbrella of IT governance. The management of IS resilience involves different fields of action types and interests which decision-makers within organizations must confront. This is of special importance for small- to medium-sized companies (SMEs) where IS often is not a dedicated or small corporate function. This paper identifies distinctive character types of corporate decision-makers at SMEs in a European context and their priorities in IS resilience. The study was performed using Q-methodology. It was able to identify and describe three additional types of decision-makers in comparison to previous research thereby clearly showing that the field has progressed. These character types provide an informative insight into the priorities of IS resilience planning in SMEs and show differences and commonalities between decision-makers.
A basic task in the design of an industrial robot application
is the relative placement of robot and workpiece. Process points are defined in Cartesian coordinates relative to the workpiece coordinate system, and the workpiece has to be located such that the robot can reach all points. Finding such a location is still an iterative procedure based on the developers' intuition. One difficulty is the choice of one of the several solutions of the backward transform of a typical 6R robot.
We present a novel algorithm that simultaneously optimizes the workpiece location and the robot configuration at all process points using higher order optimization algorithms. A key ingredient is the extension of the robot with a virtual prismatic axis. The practical feasibility of the approach is shown with an example using a commercial industrial robot.
This paper connects research from business model innovation and information systems by exploring critical IT capabilities for servitized business models. The adoption of servitized business models is a major business model innovation strategy. At the same time, digitalization drives the evolution of IT capabilities at these business models. Scholars argue that it remains unclear how IT capabilities enable servitized business models to build a competitive advantage by achieving cost advantages or differentiation. This paper explores IT capabilities that enable building a competitive advantage for servitized business models based on a qualitative analysis of multiple published case studies. The authors identify configurations of IT capabilities among servitized business models. The findings contribute to servitization research by exploring IT capabilities
and how they are combined among servitized business models.
The insights help practitioners deploy digital technologies and IT
assets effectively as building blocks of IT capabilities to advance
their servitized business model.
Cloud Computing Adoption: A Literature Review on What Is New and What We Still Need to Address
(2021)
Research on cloud computing (CC) recently emerged congruently with the technology’s importance for organizations at a fast pace. This makes it difficult for practitioners to obtain a consolidated overview of what determines CC adoption based on the numerous papers in this regard. Moreover, for further research in the field to add value, it is necessary to identify what still needs to be addressed. In this vein, we conducted a descriptive review of 39 papers, integrating the results of a previous review on 23 papers from 2014, to compare findings across studies. We identify 44 determinant factors that exhibit consistent directional influence on the dependent meta-variable “CC adoption”, extending previous literature reviews with regard to asset, client, and environmental characteristics. We then critically reviewed the research landscape to identify what is there, and what is not yet covered: Future research should specifically regard the adoption of Infrastructure-, Platform-, and Everything-as-a-Service, private, hybrid, and multi-cloud deployment, investigate vendor, solution, and individual characteristics, analyzing information systems, or the decision-maker.
Most large-scale organizations adopted Cloud Computing (CC) on a company level in recent years. Managers now face the challenge to appropriately implement CC "operationally", i.e., for information systems (ISs). We refer to this as post-adoption, addressing the extent of technology usage after adoption. Specifically, managers need to choose among the CC delivery models Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-asa-Service (SaaS). We differentiate the determinants of this post-adoption decision for IaaS, PaaS, and SaaS. Based on this analysis, we derive criteria that guide managers' delivery model selection: Adopt 1) IaaS for ISs requiring flexibility and reduced time to market, 2) PaaS to access specialized resources, and 3) SaaS to focus on core competencies. Moreover, we analyze the impact on the CC strategy and postulate them as recommendations: I) acknowledge the interplay between governance and time-to-market, II) realize cost savings on company level, and III) consider strategically important ISs for CC.