Publikationsserver der Ostbayerischen Technischen Hochschule Regensburg
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Measurement of the cubic nonlinear susceptibility in lithium niobate
No full textWe measured the cubic nonlinear susceptibility tensor elements ( χ(3)) for polarization along the primary crystallographic axis in titanium-indiffused lithium niobate waveguides, assessed through self-phase modulation using picosecond-duration pulses at telecommunication wavelengths. A dominant, highly temperature- and wavelength-dependent contribution from a cascaded second-order nonlinearity is observed. Through careful extraction of the cascaded effect, we quantify the intrinsic third-order susceptibility tensor elements as χ(3) zzzz(ω; ω, ω, −ω) = (5.2 ± 1.3) × 10−21 m2 V2 and χ(3) xxxx(ω; ω, ω, −ω) = χ(3) yyyy(ω; ω, ω, −ω) = (3.6 ± 0.8) × 10−21 m2 V2 .
These measurements underscore the substantial impact of the cascaded nonlinearity in enhancing the effective cubic nonlinearity in lithium niobate and offer precise values essential for the design of nonlinear photonic devices
Topical collection: robotic solutions for digitally enabled production processes in construction
No full textAcross the global construction sector, a new generation of robotic systems is rapidly entering the market. Solutions for on-site drilling, spraying, masonry, logistics, and finishing are now being piloted at an unprecedented pace. Their deployment in emerging construction robotics hubs in Singapore, Hong Kong, Canada, Dubai, Abu Dhabi, Egypt, Denmark, Switzerland, and Germany demonstrates both the momentum of this technological shift and the considerable challenges that remain.
In real-world testing environments, the integration of these robots into digital construction pipelines—particularly BIM-to-robot workflows, semantic task modeling, and robust digital twins—continues to be a bottleneck. These challenges position digitally enabled fabrication and robotics as a priority topic within academia, motivating research on methods, techniques, algorithms, and workflows that can accelerate adoption in construction.
This Topical Collection brings together research spanning the emerging landscape of digitally enabled construction robotics. The contributions advance robotic fabrication, from flexible timber processes to innovative formwork, reinforcement, and earth-based additive methods, alongside computer vision, BIM integration, and sensing approaches that improve monitoring and quality assurance. The collection also includes mobile and aerial systems for inspection and mapping to support system autonomy in construction. Together, these works show how integrated perception, planning, and sociotechnical understanding of human–robot collaboration are becoming essential for reliable robotic performance in construction.
While current construction robots still focus on simple, structured tasks, the advances in this topical collection point toward a more capable generation. Contributions outline principles for robot-compatible buildings through new fabrication logics and BIM-linked task data, while work on perception, BIM integration, and data fusion reduces interoperability gaps. Research on sensing and adaptive processes supports more consistent workflows, and mobile and aerial robotics provide insights for deployment and site logistics. Collectively, these developments show how digitally enabled production processes can help to overcome key systemic barriers and enable future, scalable construction robotics
SAT Strikes Back: Parameter and Path Relations in Quantum Toolchains [Data set]
No full textIn the foreseeable future, toolchains for quantum computing should offer automatic means of transforming a high level problem formulation down to a hardware executable form.
Thereby, it is crucial to find (multiple) transformation paths that are optimised for (hardware specific) metrics. We zoom into this pictured tree of transformations by focussing on k-SAT instances as input and their transformation to QUBO, while considering structure and characteristic metrics of input, intermediate and output representations. Our results can be used to rate valid paths of transformation in advance—also in automated (quantum)
toolchains. We support the automation aspect by considering stability and therefore predictability of free parameters and transformation paths. Moreover, our findings can be used in the manifesting era of error correction (since considering structure
in a high abstraction layer can benefit error correcting codes in layers below). We also show that current research is closely linked to quadratisation techniques and their mathematical foundation
Machine Learning Dataset of U-Channel Sheet Metal Geometry Representations with Supervision Information for Drawability Assessment and Part Segmentation [Data set]
No full textThe dataset contains 2533 geometries from four different parametric CAD models sampled from the U-Channel python package. The representations include the original CAD geometries (.step), graph binaries (.bin), meshes (.off), and point clouds (.xyz). Additionally, we provide labels for supervised learning use cases of local and global drawability assessment and part segmentation (.json) for all representations. Custom label computation for drawability assessment is enabled by the provided strains.zip file, which contains minor and major true strains for the given meshes. For more details, refer to the associated publication
Ein Grundriss der Wissenschaftsdisziplin Wirtschaftsinformatik
No full textDieser Beitrag gibt einen Grundriss der Wissenschaftsdisziplin Wirtschaftsinformatik
(WI) und ihrer Entwicklung. Hierzu wird zunächst der Gegenstand der WI näher betrachtet, nämlich die Informationssysteme.
Dann wird erläutert, welche Ziele die WI verfolgt. Da WI ein interdisziplinäres Fach ist, werden anschließend die bestimmenden Basiswissenschaften der WI im Rahmen des Grundsystems der Wissenschaften dargestellt. Dabei wird deutlich, dass der Einfluss unterschiedlicher Disziplinen den Methodenpluralismus in der WI befördert. Im Beitrag werden die zwei grundlegenden Forschungsparadigmen in Form des verhaltensorientierten und des gestaltungsorientierten Ansatzes näher betrachtet. Nach einem kurzen Einblick in die zeitliche Entwicklung der deutschsprachigen WI werden die Themen-und Tätigkeitsfelder der WI näher erörtert. Abschließend wird ein Ausblick auf die Herausforderungen in der WI gegeben
Path Matters: Industrial Data Meet Quantum Optimization
No full textReal-world optimization problems must undergo a series of transformations before becoming solvable on current quantum hardware. Even for a fixed problem, the number of possible transformation paths-from industry-relevant formulations through binary constrained linear programs (BILPs), to quadratic unconstrained binary optimization (QUBO), and finally to a hardware-executable representation-is remarkably large. Each step introduces free parameters, such as Lagrange multipliers, encoding strategies, slack variables, rounding schemes or algorithmic choices-making brute-force exploration of all paths intractable. In this work, we benchmark a representative subset of these transformation paths using a realworld industrial production planning problem with industry data: the optimization of work allocation in a press shop producing vehicle parts. We focus on QUBO reformulations and algorithmic parameters for both quantum annealing (QA) and the Linear Ramp Quantum Approximate Optimization Algorithm (LR-QAOA). Our goal is to identify a reduced set of effective configurations applicable to similar industrial settings. Our results show that QA on D-Wave hardware consistently produces near-optimal solutions, whereas LR-QAOA on IBM quantum devices struggles to reach comparable performance. Hence, the choice of hardware and solver strategy significantly impacts performance. The problem formulation and especially the penalization strategy determine the solution quality. Most importantly, mathematically-defined penalization strategies are equally successful as hand-picked penalty factors, paving the way for automated QUBO formulation. Moreover, we observe a strong correlation between simulated and quantum annealing performance metrics, offering a scalable proxy for predicting QA behavior on larger problem instances
Make Some Noise! Measuring Noise Model Quality in Real-World Quantum Software
No full textNoise and imperfections are among the prevalent challenges in quantum software engineering for current NISQ systems. They will remain important in the post-NISQ area, as logical, error-corrected qubits will be based on software mechanisms. As real quantum hardware is still limited in size and accessibility, noise models for classical simulation-that in some cases can exceed dimensions of actual systems-play a critical role in obtaining insights into quantum algorithm performance, and the properties of mechanisms for error correction and mitigation. We present, implement and validate a tunable noise model building on the Kraus channel formalism on a large scale quantum simulator system (Qaptiva). We use empirical noise measurements from IBM quantum (IBMQ) systems to calibrate the model and create a realistic simulation environment. Experimental evaluation of our approach with Greenberger-Horne-Zeilinger (GHZ) state preparation and QAOA applied to an industrial usecase validate our approach, and demonstrate accurate simulation of hardware behaviour at reasonable computational cost. We devise and utilise a method that allows for determining the quality of noise models for larger problem instances than is possible with existing metrics in the literature. To identify potentials of future quantum software and algorithms, we extrapolate the noise model to future partially fault-tolerant systems, and give insights into the interplay between hardware-specific noise modelling and hardware-aware algorithm development
iRBSM: A Deep Implicit 3D Breast Shape Model
No full textWe present the first deep implicit 3D shape model of the female breast, building upon and improving the recently proposed Regensburg Breast Shape Model (RBSM). Compared to its PCA-based predecessor, our model employs implicit neural representations; hence, it can be trained on raw 3D breast scans and eliminates the need for computationally demanding non-rigid registration -- a task that is particularly difficult for feature-less breast shapes. The resulting model, dubbed iRBSM, captures detailed surface geometry including fine structures such as nipples and belly buttons, is highly expressive, and outperforms the RBSM on different surface reconstruction tasks. Finally, leveraging the iRBSM, we present a prototype application to 3D reconstruct breast shapes from just a single image. Model and code publicly available at this https URL
IS executives and sustainability
No full textThe pressing global sustainability challenges, encapsulated in the United Nations’ Sustainable Development Goals (SDGs), require profound transformations across multiple levels. It is imperative for the Information Systems (IS) discipline to engage in addressing these challenges. This paper aims to contribute to this imperative through a scoping literature review, examining factors that enable IS executives to drive sustainability outcomes within organizations, utilizing the Input-Mediator-Outcome (IMO) framework. By analyzing 31 articles from important IS journals and conferences between 2008 and 2024, this review identifies key input factors for sustainability outcomes, such as individual IS executive inputs, the role of the Top Management Team (TMT) setting and organizational contexts, as well as external influences. In addition, it explores how team-specific processes can augment sustainability efforts. The paper concludes by proposing future research questions to address underrepresented SDGs, investigate external impact factors more thoroughly, and emphasize the role of individual IS executive inputs. These insights aspire to advance the understanding of IS executives’ potential to influence sustainability in organizational settings
An Optimization Model for Production Scheduling with Energy Consumption and Energy-related Emissions
No full textDue to the scarcity of resources, rising costs as well as the further need for ecological improvement in industrial production, firms are increasingly motivated to take into account energy consumption in production planning. Associated with this, the consideration of energy-related emissions is becoming an additional point of interest for decisionmakers in both, economic and ecological terms. Based on an extensive systematic literature review, the study at hand presents a multicriterial scheduling problem that addresses tardiness, energy consumption and energy-related emissions in production scheduling. A
model is introduced that takes into account job release dates, multiple machine states, a power demand threshold as well as time-varying emission conversion factors. Multiple case studies are analysed and the effects of different technological implementations as energy onsite generation and energy storage systems are evaluated. Furthermore, several price mechanisms regarding energy procurement and emission trading are discussed. Moreover, by coupling the optimization model
to a discrete event simulation model, we are able to compare the model results to real case scenarios. First computational experiments have demonstrated that the model and its extensions can effectively reduce the environmental impact associated with production while simultaneously considering corresponding economic objectives. Based on the proposed approach, our research aims on answering the question with which economic trade-offs an ecological improvement in terms of energy consumption and emission output can be achieved in production