@misc{13339, abstract = {{Additive manufacturing (AM) paves the way for low-cost production of optical and terahertz (THz) components such as waveguides, fibers, and lenses [1]–[3]. This work addresses the fabrication and THz characterization of a 3D-printed waveguide composed of cyclic olefin copolymer (TOPAS). Such a waveguide is a convenient and inexpensive tool in the development of THz interconnects, and in applications such as biomedical sensing.}}, author = {{Joshi, Suraj and Starsaja, Annamarija and Shrotri, Abhijeet Narendra and Stübbe, Oliver and Preu, Sascha}}, booktitle = {{2025 50th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)}}, keywords = {{Optical fibers, Optical fiber sensors, Optical interconnections, Biomedical optical imaging, Optical device fabrication, Production, Optical waveguide components, Three-dimensional printing, Optical waveguides, Lenses}}, location = {{Helsinki, Finland }}, publisher = {{IEEE}}, title = {{{Additively-Manufactured Terahertz Waveguides}}}, doi = {{10.1109/irmmw-thz61557.2025.11320095}}, year = {{2026}}, } @misc{11495, abstract = {{To evaluate the suitability of an analytical instrument, essential figures of merit such as the limit of detection (LOD) and the limit of quantification (LOQ) can be employed. However, as the definitions k nown in the literature are mostly applicable to one signal per sample, estimating the LOD for substances with instruments yielding multidimensional results like electronic noses (eNoses) is still challenging. In this paper, we will compare and present different approaches to estimate the LOD for eNoses by employing commonly used multivariate data analysis and regression techniques, including principal component analysis (PCA), principal component regression (PCR), as well as partial least squares regression (PLSR). These methods could subsequently be used to assess the suitability of eNoses to help control and steer processes where volatiles are key process parameters. As a use case, we determined the LODs for key compounds involved in beer maturation, namely acetaldehyde, diacetyl, dimethyl sulfide, ethyl acetate, isobutanol, and 2-phenylethanol, and discussed the suitability of our eNose for that dertermination process. The results of the methods performed demonstrated differences of up to a factor of eight. For diacetyl, the LOD and the LOQ were sufficiently low to suggest potential for monitoring via eNose. }}, author = {{Kruse, Julia and Wörner, Julius and Schneider, Jan and Dörksen, Helene and Pein-Hackelbusch, Miriam}}, booktitle = {{Sensors}}, issn = {{1424-8220 }}, keywords = {{multidimensional sensor arrays, MOS sensors, beer fermentation, process control, gas analysis, metal oxide semiconductors, intentional data analysis, chemometrics, PLSR, PCA, first-order calibration}}, number = {{11}}, publisher = {{MDPI}}, title = {{{Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses }}}, doi = {{10.3390/s24113520}}, volume = {{24}}, year = {{2024}}, } @misc{11977, abstract = {{Additive manufacturing of lenses offers quick prototyping and characterization. This paper explains the additive manufacturing and characterization of axicon lenses using TOPAS material for Terahertz sensing applications. The beam patterns of additively manufactured axicon lens prototypes are characterized around 0.3 THz with silicon-based THz-camera to evaluate the depth of focus.}}, author = {{Shrotri, Abhijeet Narendra and Krause, Benedikt and Stübbe, Oliver and Pfeiffer, Ullrich and Preu, Sascha}}, booktitle = {{2024 49th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)}}, issn = {{2162-2035}}, keywords = {{Additives, Prototypes, Three-dimensional printing, Sensors, Lenses}}, location = {{Perth, Australia }}, publisher = {{IEEE}}, title = {{{Evaluation of Additively Manufactured Axicon Lenses Using a THz-Camera}}}, doi = {{10.1109/irmmw-thz60956.2024.10697740}}, volume = {{2024}}, year = {{2024}}, } @misc{12993, abstract = {{In computer science and related technical fields, researchers, educators, and practitioners are continuously automating recurring tasks for high efficiency in a wide variety of fields. In higher education, such tasks that educators face are the recurring review and assessment process of students' programming coursework. Thus, various attempts exist to automate the assessment and feedback generation for course homework and practicals in higher education. Those approaches for automated programming task assessment often comprise running automated tests to check for limited functional correctness and potentially style checking for various violations (LINTing). Educators familiar with large-scale automated task assessment are likely used to seeing hard-coded solutions specifically or accidentally designed to just pass the required tests, ignoring or misinterpreting the actual task requirements. Detecting such issues in arbitrary code is non-trivial and an ongoing research topic in software engineering. Software engineering research has yielded various semantic analysis frameworks, such as GitHub's CodeQL, which can be adapted for programming task assessment. We present a work-in-progress programming task analysis framework which employs CodeQL's analysis technology to identify the actual use of task-description-mandated syntactic and semantic elements such as loop structures or the use of mandated data blocks in branching conditions. This allows extending existing course work analysis frameworks to include a semantic check of an uploaded program which exceeds the relatively simple set of input-output test cases provided by unit tests. We use a running example of entry level programming tasks and several solution attempts to introduce and explain our proposed control flow and data flow -based analysis method. We discuss the benefits of including semantic analysis as an additional method in the automated programming task assessment toolbox. Our main contribution is the adaptation of an semantic analysis code framework to analyse syntactic and semantic components in students' programming coursework.}}, author = {{Wehmeier, Leon and Eilermann, Sebastian and Niggemann, Oliver and Deuter, Andreas}}, booktitle = {{FIE 2023 : College Station, TX, USA, October 18-21, 2023 : conference proceedings / 2023 IEEE Frontiers in Education Conference (FIE)}}, isbn = {{979-8-3503-3643-6}}, keywords = {{Codes, Electronic learning, Soft sensors, Semantics, Education, Syntactics, Task analysis}}, location = {{Texas}}, publisher = {{IEEE}}, title = {{{Task-fidelity Assessment for Programming Tasks Using Semantic Code Analysis}}}, doi = {{10.1109/fie58773.2023.10342916}}, year = {{2024}}, } @misc{10326, abstract = {{In the food industry, and especially in wines as products thereof, ethanol and sulfur dioxide play an equally important role. Both substances are important wine quality characteristics as they influence the taste and odor. As both substances comprise volatile matter, electronic noses should be applicable to discriminate the different qualities of wines. Our study investigates the influence of alcohol and sulfur dioxide on the discrimination ability of wines (especially those of the same grape variety) using two different electronic nose systems. One system is equipped with metal oxide sensors and the other with quartz crystal microbalance sensors. Contrary to indications in literature, where the alcohol content is discussed to have a large influence on e-nose results, it was shown that a difference of 1 % ethanol was not sufficient to allow accurate discrimination using Linear Discriminant Analysis by any system. On the positive side, the analyzed concentrations of ethanol (about 12 %) did not superimpose other volatile information. So difference in sulfur dioxide content gave an accuracy for sample discrimination of up to 90.6 % with MOS nose. Thus, we are so far partially able to discriminate wines with electronic noses based on their volatile imprint.}}, author = {{Wörner, Julius and Dörksen, Helene and Pein-Hackelbusch, Miriam}}, booktitle = {{2023 IEEE 21st International Conference on Industrial Informatics (INDIN)}}, keywords = {{Ethanol, Pipelines, Metals, Nose, Electronic noses, Sensor systems, Sensors, Quartz crystals, Linear discriminant analysis, Sulfur}}, location = {{Lemgo}}, title = {{{Key Indicators for the Discrimination of Wines by Electronic Noses}}}, doi = {{https://doi.org/10.1109/INDIN51400.2023.10217912}}, year = {{2023}}, } @inproceedings{554, abstract = {{Light guiding structures, like optical waveguides or fibers, take an important role in several industries, e.g. communication, sensing, illumination or medical applications. For the latter, it could be very interesting to have the possibility to manufacture problem-adapted structureswith a mechanicalfunctionality andwith additional embedded optical or electrical sensor functionalities.Modern additive manufacturing (AM) technologies like Stereolithography (SLA) or Fused Layer Modeling (FLM) may provide these opportunities.This paper is aimedto figure out the light guiding opportunities of both technologies. For this different kind of structures are built by FLM and SLA. To compare both manufacturing technologies, the layout of each structure is identical for both technologies. After manufacturing, the transmission and the attenuation of the guided light of these structures areanalyzed by measurement.Then the measurement results of the different technologies are compared with each other.}}, author = {{Beyer, Micha and Stübbe, Oliver and Villmer, Franz-Josef}}, booktitle = {{Production engineering and management : proceedings 8th international conference, October 04 and 05, 2018, Lemgo, Germany}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-03-0}}, keywords = {{Additive manufacturing, Embedded optical waveguides, Optical sensors, SLA technology, FLM technology}}, location = {{Lemgo}}, number = {{1}}, pages = {{70--82}}, title = {{{Comparsion of FLM and SLA Processing Technologies Towards Manufacturing of Optical Waveguides for Communicationi and Sensing Applications}}}, year = {{2018}}, } @inproceedings{573, abstract = {{Additive manufacturing (AM) technologies have not only revolutionized product development and design by enabling rapid prototyping. They also gained influence on production in general, mainly because of their direct manufacturing capabilities. In the context of Industry 4.0 and the related process automation, innovative and advanced production technologies with completely new approaches are required [1]. AM technologies contribute to this with their advantages like freedom of design, cost efficient product individualization, and functional integration. On the other hand, AM still shows shortcomings in exploiting its full potential. Most current AM technologies are only applicable for manufacturing with singular materials. In particular, opportunities for processing of optically or electrically conductive materials are still missing. This paper contributes to the advancement of additive manufacturing of two different material variants or even two completely different materials. A special focus is laid on producing a part that combines mechanical with optical or electrical functionalities in one process step. The ultimate goal is to integrate sensor functionalities into an AM object, e.g. strain gauges. Extrusion processes, predominantly Fused Layer Modeling (FLM), are preferred in this research due to their mechanically simple machine setup in which additional functional materials can be adapted easily to the build process. In a first step, the general manufacturability has been evaluated. Thereafter, the resulting optical transmission properties have been analyzed. Especially the attenuation has to remain below a threshold value to accomplish a minimum signal-to-noise ratio.}}, author = {{Ehlert, Patrick and Stübbe, Oliver and Villmer, Franz-Josef}}, booktitle = {{Production Engineering and Management}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-946856-01-6}}, keywords = {{Additive manufacturing, Embedded optical waveguides, Electrical conductors, Embedded systems, FLM technology, Sensors}}, location = {{Pordenone, Italy}}, number = {{1}}, pages = {{127--136}}, title = {{{Investigation on the Direct Manufacturing of Waveguides and Sensors Using FLM Technology}}}, year = {{2017}}, } @book{4336, abstract = {{Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with “big data” are turning the medical sciences into a data-intensive science. To keep pace with the growing amounts of complex data, smart hospital approaches are a commandment of the future, necessitating context aware computing along with advanced interaction paradigms in new physical-digital ecosystems. The very successful synergistic combination of methodologies and approaches from Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions for the vision to support human intelligence with machine learning. The papers selected for this volume focus on hot topics in smart health; they discuss open problems and future challenges in order to provide a research agenda to stimulate further research and progress.}}, editor = {{Holzinger, Andreas and Röcker, Carsten and Ziefle, Martina}}, isbn = {{978-3-319-16225-6}}, issn = {{1611-3349}}, keywords = {{HCI, ambient assisted living, big data, computational intelligence, context awareness, data centric medicine, decision support, interactive data mining, keyword detection, knoweldge bases, knoweldge discovery, machine learning, medical decision support, medical informatics, natural language processing, pervasive health, smart home, ubiquitous computing, visualization, wearable sensors}}, pages = {{275}}, publisher = {{Springer}}, title = {{{Smart Health: Open Problems and Future Challenges}}}, doi = {{10.1007/978-3-319-16226-3}}, volume = {{8700}}, year = {{2015}}, } @inproceedings{2133, abstract = {{Due to the material changes of components from metal to plastic or composite materials, the structural health monitoring finds more and more interest in the industrial fields. The reason is that these materials are more vulnerable to damage or impacts which cannot be optically detected. In this contribution we present a method to analyze the structure of plastic components with piezo-electrical sensors and actuators. The components are stimulated by actuators, and sensors capture the injected vibrations. These signals are decomposed into Intrinsic Mode Functions to compute statistical features. A Fuzzy-Pattern-Classifier is applied to detect structural modifications at the components under test.}}, author = {{Dicks, Alexander and Lohweg, Volker and Wittke, Henrik and Linke, Stefan}}, booktitle = {{20th IEEE International Conference on Emerging Technologies and Factory Automation}}, keywords = {{Sensors, Actuators, Finite element analysis, Plastics, Modal analysis, Monitoring, Empirical mode decomposition}}, title = {{{Structural Health Monitoring of Plastic Components with Piezoelectric Sensors}}}, doi = {{ 10.1109/ETFA.2015.7301595}}, year = {{2015}}, } @inproceedings{2136, abstract = {{In modern industrial applications driven by Cyber-physical systems (CPS) it is a challenging task to model and optimize processes such as machine analysis and diagnosis. Since the CPS have to act autonomously, a procedure for automated decision making has to be designed. In our work we concentrate on the design of a decision procedure by a fuzzy classifier approach. For our application on decision making in an industrial environment, a fuzzy approach was picked as convenient classification technique regarding balance between accuracy and computational time. We present a supervised learning method called FUZZY-ComRef which combines fuzzy classification and our combinatorial refinement method, called ComRef [1]. Due to the fact that fuzzy classification might behave inaccurately for some datasets, the aim of our approach is to improve the results provided by the (stand-alone) fuzzy classification. We show the performance of FUZZY-ComRef evaluated on the samples from the UCI Repository and on our real-world dataset Motor Drive Diagnosis. In addition, we discuss the quadratic computational time problem arising from the combinatorial nature of ComRef. Furthermore, we show based on real-time evaluations that within parallelisation the proposed FUZZY-ComRef is suitable to many applications in CPS.}}, author = {{Dörksen, Helene and Lohweg, Volker}}, booktitle = {{20th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Luxembourg, Sep 2015. }}, keywords = {{Support vector machines, Accuracy, Time complexity, Decision making, Motor drives, Shape, Sensors}}, publisher = {{IEEE}}, title = {{{Automated Fuzzy Classification with Combinatorial Refinement}}}, doi = {{ 10.1109/ETFA.2015.7301514}}, year = {{2015}}, } @article{2140, abstract = {{Recent industrial applications are implemented in a modular way, resulting in flexibility during the whole life cycle, i.e., setup, operation, and maintenance. This applies especially to larger applications like logistic, production, and printing processes. Their modular character is resulting from the constantly increasing complexity of such installations, which makes their supervision for securing reliable operation a difficult task: the data of hundreds (if not thousands) of signal sources must be acquired, communicated, and evaluated for system diagnosis. In this contribution we summarize the challenges arising in such applications and show that distributed sensor and information fusion for modular self-diagnosis tackles these challenges. Here, we propose an innovative distributed architecture encompassing intelligent sensor nodes, self-configuring real-time communication networks, and a suitable sensor and information fusion system for condition monitoring. New challenges arise in the context of distributed information fusion systems, which are identified and to which an outlook on future solutions is provided. A number of these solutions have already been discovered, implemented, and are evaluated in the context of a demonstrator, which resembles a real-world printing application.}}, author = {{Mönks, Uwe and Trsek, Henning and Dürkop, Lars and Geneiß, Volker and Lohweg, Volker}}, issn = {{0957-4158}}, journal = {{Mechatronics}}, keywords = {{Cyber-physical systems, Information fusion, Fusion system design, Intelligent sensors, Self-configuration, Intelligent networking}}, number = {{34}}, pages = {{63--71}}, publisher = {{Elsevier}}, title = {{{Towards distributed intelligent sensor and information fusion}}}, doi = {{10.1016/j.mechatronics.2015.05.005}}, year = {{2015}}, } @inproceedings{2155, abstract = {{Today, mobile devices (smartphones, tablets, etc.) are widespread and of high importance for their users. Their performance as well as versatility increases over time. This leads to the opportunity to use such devices for more specific tasks like image processing in an industrial context. For the analysis of images requirements like image quality (blur, illumination, etc.) as well as a defined relative position of the object to be inspected are crucial. Since mobile devices are handheld and used in constantly changing environments the challenge is to fulfill these requirements. We present an approach to overcome the obstacles and stabilize the image capturing process such that image analysis becomes significantly improved on mobile devices. Therefore, image processing methods are combined with sensor fusion concepts. The approach consists of three main parts. First, pose estimation methods are used to guide a user moving the device to a defined position. Second, the sensors data and the pose information are combined for relative motion estimation. Finally, the image capturing process is automated. It is triggered depending on the alignment of the device and the object as well as the image quality that can be achieved under consideration of motion and environmental effects.}}, author = {{Henning, Kai-Fabian and Fritze, Alexander and Gillich, Eugen and Mönks, Uwe and Lohweg, Volker}}, booktitle = {{IST/SPIE Electronic Imaging 2015, Digital Photography and Mobile Imaging XI}}, keywords = {{Image processing, Image acquisition, Mobile devices Sensors, Image fusion, Motion estimation, Cameras}}, pages = {{1--12}}, publisher = {{SPIE}}, title = {{{Stable Image Acquisition for Mobile Image Processing Applications}}}, doi = {{10.1117/12.2076146}}, year = {{2015}}, } @inproceedings{2068, abstract = {{The production of printing goods is laborious. Furthermore, the print quality, especially in banknotes, must be assured. It is accepted, that print defects are generated because printing parameters, also machine parameters can change unnoticed. Therefore, a combined concept for a multi-sensory learning and classification model based on new adaptive fuzzy-pattern-classifiers for data inspection is proposed. This inspection concept, which combines optical, acoustical and other machine information, comes up with a large amount of data, which leads to multivariate methods for data analysis. Multivariate methods are useful for analysis of large and complex data sets that consist of many variables measured on large numbers of physical data.}}, author = {{Dyck, Walter and Türke, Thomas and Schaede, Johannes and Lohweg, Volker}}, isbn = {{978-1-4244-1565-6}}, issn = {{1551-2541 }}, keywords = {{Sensor fusion, Inspection, Optical sensors, Printing machinery, Data security, Data analysis, Production, Degradation, Principal component analysis, Karhunen-Loeve transforms}}, pages = {{accepted for publication}}, publisher = {{MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING}}, title = {{{A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion}}}, doi = {{10.1109/MLSP.2007.4414320}}, year = {{2007}}, } @inproceedings{2062, abstract = {{Bank note inspection is a complex task. As more and more print techniques and new security features are established, total quality security and bank note printing must be assured. Therefore, this factor necessitates change of a sensorial concept in general. We propose an optical-acoustical inspection method based upon the concepts of information fusion and fuzzy interpretation of data measures. Furthermore, we present a simplified scheme for information fusion for pattern recognition and data classification based on parametrical unimodal potential functions and a Sugeno-type score value analysis. Digital Object Identifier: 10.1109/ICIF.2006.301779
}}, author = {{Dyck, Walter and Schaede, Johannes and Türke, Thomas and Lohweg, Volker}}, booktitle = {{ 2006 9th International Conference on Information Fusion}}, isbn = {{ 1-4244-0953-5}}, keywords = {{Information security, Inspection, Printing machinery, Optical sensors, Data security, Personnel, Fuzzy systems, Sensor systems, Expert systems, Ink}}, pages = {{1--8}}, publisher = {{9th International Conference on Information Fusion, 2006. ICIF '06}}, title = {{{Information Fusion Application On Security Printing With Parametrical Fuzzy Classification}}}, doi = {{10.1109/ICIF.2006.301779}}, year = {{2006}}, }