Refine
Year of publication
- 2023 (53) (remove)
Document Type
- Conference Proceeding (27)
- Article (peer reviewed) (16)
- Working Paper (4)
- Part of a Book (2)
- Book (1)
- Contribution to a Periodical (1)
- Other (1)
- Preprint (1)
Language
- English (53) (remove)
Is part of the Bibliography
- no (53)
Keywords
- Neural networks (7)
- Fluorescence (5)
- Fluorescence lifetime imaging (4)
- Phase shift (4)
- AI-mediated communication (3)
- FD-FLIM (3)
- Laser sources (3)
- MLP (3)
- Microscopy (3)
- fluorescence (3)
Institute
- Fakultät für Ingenieurwissenschaften (13)
- Zentrum für Forschung, Entwicklung und Transfer (8)
- Fakultät für Angewandte Gesundheits- und Sozialwissenschaften (5)
- Fakultät für Betriebswirtschaft (5)
- Fakultät für Holztechnik und Bau (3)
- Fakultät für Sozialwissenschaften (2)
- Fakultät für Wirtschaftsingenieurwesen (2)
- Fakultät für Chemische Technologie und Wirtschaft (1)
- Fakultät für Informatik (1)
We present inductive power transfer (IPT) with a half-bridge converter based on differential relaxation self-oscillation. The oscillation dynamics of the converter automatically adapts to variation in the inductive coupling link and changes in the load, respectively. Design equations based on theoretical circuit analysis reveals a high power transfer efficiency (>90%) for alteration of coupling distance in the strong coupling regime. A prototype system employing GaN-HEMTs confirms the theoretically predicted characteristics of the proposed circuit.
A Planar Magneto-Inductive Device with Modulated Mutual Inductance for Wireless Power Transmission
(2023)
A Magneto-Inductive Wave (MIW) structure for wireless power transfer (WPT) is proposed with switchable mutual inductance between neighbored coupling coils. Orthogonally placed switchable short circuit loops are added in order to modulate the wave propagation properties of the MIW structure without changing the resonance frequency. We derive an analytical model based on lumped circuit analysis for the MIW waveguide and successfully evaluate the theoretical findings by circuit modeling and field simulation. We demonstrate switchable, i.e. addressable, guided wireless power transfer along an experimental MIW structure at a resonance frequency of 20.5 MHz.
This study investigates the impact of generative AI systems like ChatGPT on semi-structured decision-making, specifically in evaluating undergraduate dissertations. We propose using Davis’ technology acceptance model (TAM) and Schulz von Thun’s four-sides communication model to understand human–AI interaction and necessary adaptations for acceptance in dissertation grading. Utilizing an inductive research design, we conducted ten interviews with respondents having varying levels of AI and management expertise, employing four escalating-consequence scenarios mirroring higher education dissertation grading. In all scenarios, the AI functioned as a sender, based on the four-sides model. Findings reveal that technology acceptance for human–AI interaction is adaptive but requires modifications, particularly regarding AI’s transparency. Testing the four-sides model showed support for three sides, with the appeal side receiving negative feedback for AI acceptance as a sender. Respondents struggled to accept the idea of AI, suggesting a grading decision through an appeal. Consequently, transparency about AI’s role emerged as vital. When AI supports instructors transparently, acceptance levels are higher. These results encourage further research on AI as a receiver and the impartiality of AI decision-making without instructor influence. This study emphasizes communication modes in learning-ecosystems, especially in semi-structured decision-making situations with AI as a sender, while highlighting the potential to enhance AI-based decision-making acceptance.
For sustainable handling of wood and high material utilization, post-consumer wood has to be sorted by post-consumer wood categories in Germany. The non-destructive FD-FLIM method could improve the wood recycling process by automatic classification of waste wood into post-consumer wood classes. Thus, the phase-dependent fluorescence decay time of treated wood is analysed in this study to obtain the impact of the treatment on the fluorescence decay time. It is shown that treated and untreated wood can be differentiated using the fluorescence decay time, although the state-of-the-art theoretical fluorescence decay time differs from the experimentally determined fluorescence decay time.
BACKGROUND
Vertigo, dizziness or balance disorders (VDB) affect the mobility and participation of many older people and are also one of the most frequent reasons for visiting the general practitioner's (GP) practice due to multifactorial causes. Physiotherapy (PT) can be crucial for the complex care of people with VDB but is rarely prescribed by GPs. So we developed an evidence-based, multidisciplinary care pathway as a complex intervention following the UK Medical Research Council guideline, which was piloted and is now being evaluated for effectiveness, accompanied by a process evaluation.
METHOD
The care pathway of the multicentre cluster-RCT (MobilE-PHY2) included decision aids and training for PTs and GPs in the intervention group and optimised standard care in the control group. A mixed-methods process evaluation following Grant’s framework for designing process evaluations examined barriers, facilitating factors and mechanisms of impact in recruiting and reaching participants, implementing the intervention and the response of all participants. Therefore, a logic model was developed illustrating the relationship between the planned work to implement the intervention, the expected mechanism of impact (based on the behaviour change wheel as a change theory), the intended results (output, outcome and impact), and categories of possible influencing factors. The underlying assumption is that a behavioural change in PT and GP is a prerequisite for a change in patient behaviour, which can lead to improved mobility and participation (outcome of MobilE-PHY2). Guided interviews were conducted with patients before the intervention and after six months and with PTs and GPs after six months. Additionally, the training evaluations, completed decision aids and structural questionnaires will be analysed from June 2023.
RESULTS AND CONCLUSION
At one study site, a total of 37 patients, 17 PTs and nine GPs were included. Interviews were conducted with 16 patients, six PTs and GPs. In the intervention group, 12 PTs and 18 GPs completed decision aids, 13 PTs and two GPs completed evaluation forms, and eight PTs and four GPs completed structural data. The preliminary results of the process evaluation will be reported at the Congress. The results are intended to give indications for a broad implementation of the care pathway, including and promoting physiotherapy and therefore contributing to improved evidence-based healthcare for older people with VDB.
Background
The admission to a nursing home is a critical life-event for affected persons as well as their families. Admission related processes are lacking adequate participation of older people and their families. To improve transitions to nursing homes, context- and country-specific knowledge about the current practice is needed. Hence, our aim was to summarize available evidence on challenges and care strategies associated with the admission to nursing homes in Germany.
Methods
We conducted a scoping review and searched eight major international and German-specific electronic databases for journal articles and grey literature published in German or English language since 1995. Further inclusion criteria were focus on challenges or care strategies in the context of nursing home admissions of older persons and comprehensive and replicable information on methods and results. Posters, only-abstract publications and articles dealing with mixed populations including younger adults were excluded. Challenges and care strategies were identified and analysed by structured content analysis using the TRANSCIT model.
Results
Twelve studies of 1,384 records were finally included. Among those, seven were qualitative studies, three quantitative observational studies and two mixed methods studies. As major challenges neglected participation of older people, psychosocial burden among family caregivers, inadequate professional cooperation and a lack of shared decision-making and evidence-based practice were identified. Identified care strategies included strengthening shared decision-making and evidence-based practice, improvement in professional cooperation, introduction of specialized transitional care staff and enabling participation for older people.
Conclusion
Although the process of nursing home admission is considered challenging and tends to neglect the needs of older people, little research is available for the German health care system. The perspective of the older people seems to be underrepresented, as most of the studies focused on caregivers and health professionals. Reported care strategies addressed important challenges, however, these were not developed and evaluated in a comprehensive and systematic way. Future research is needed to examine perspectives of all the involved groups to gain a comprehensive picture of the needs and challenges. Interventions based on existing care strategies should be systematically developed and evaluated to provide the basis of adequate support for older persons and their informal caregivers.
Corrosion of steel reinforcements in concrete constructions is a big topic for the building industry. Polymeric materials are a possible alternative due to their ability to withstand corrosion. To replace steel reinforcements, fibers with high mechanical properties and a good bonding ability between fiber and concrete are needed. Today different approaches for concrete reinforcement by polymer fibers have been investigated. The bonding ability of the fibers can be increased by mechanical anchoring, e.g. crimped or embossed fibers, as well as by a chemical bonding between concrete and fiber surface. To realize the requirements of high mechanical properties and a good bonding behavior, a fiber that is drawn from a co-extruded filament shall be produced and tested. The filament owns an innovative core-shell-structure. The core maintains the fiber-stiffness and the tensile strength while the shell allows using another material to affect the bonding behavior of the fiber. This study shows the usage of fibers with differing shell materials to examine their influence on the mechanical properties of the fiber in total and the adhesion abilities to concrete. As core material, an unfilled polypropylene (PP) is used. The shell materials are varied using different polymers e.g. polypropylene or ethylene acrylic acid copolymer, as well as two PP based compounds filled with wood particles and calcium carbonate blended with a maleic anhydride based coupling agent. The mechanical properties of the fibers are tested by fiber tensile tests to compare the younǵs modulus and the tensile strength. The influence of the shell phase on the bonding ability to concrete is evaluated by the interfacial shear strength calculated from single fiber pull-out tests. Microscopy is used to interpret changes before and after pull-out. The results depict incredible positive effects and allow new insights in possible materials for fiber reinforced concrete constructions.
Environmental pollution by plastics is an increasing problem. However, state-of-the-art methods have significant disadvantages in detecting and identifying plastics directly in an environmental matrix. In this study, we propose a blob detection algorithm in combination with a neural network for fast and automated identification of plastics and non-plastics in a single fluorescence lifetime image. Therefore an artificial environmental matrix is prepared that contains soil, grass, spruce and HDPE (high density polyethylene) particles. Several FD-FLIM (frequency domain fluorescence lifetime imaging microscopy) images are taken, and the detection algorithm and the neural network are applied. We successfully demonstrated the suitability of the thresholding algorithm and the binary classification of the HDPE particles directly in the environmental matrix.
The FD-FLIM technique has a high potential for automated post-consumer wood sorting. A problem of analysing post-consumer wood fluorescence properties is the uncertainty of the post-consumer wood category as the origin of the samples are unknown. In this study, the fluorescence properties of actual post-consumer wood is compared with prepared wood samples. The post-consumer wood samples display slightly different fluorescence intensities and lifetimes due to environmental influences and a higher sample diversity. For improved training of evaluation algorithms for post-consumer wood sorting, the prepared sample set should be extended or the post-consumer wood should be additionally analysed in the laboratory.
Previous research on identifying plastic types and differentiating plastics from environmental material is promising by utilizing the specific fluorescence lifetime, but the evaluation still has to be automated. Therefore, an automated Gaussian analysis is developed for evaluating frequency-domain fluorescence lifetime images of plastics and environmental materials. Furthermore, we applied a “Multilayer Perceptron” and “Random Forest Classifier” to the data resulting from the Gaussian analysis of the frequency domain fluorescence lifetime imaging microscopy data. The classification results show high F1-scores, whereby the best “Multilayer Perceptron” and “Random Forest Classifier” achieved an F1-score of 90%. Thus, identifying and differentiating plastics and environmental materials is possible by applying a “Multilayer Perceptron” or “Random Forest Classifier” to the Gaussian-analyzed imaged fluorescence lifetime data.
Many experts project generative AI will impact the types of competencies that are valued among working professionals. This is the first known academic study to explore the views of business practitioners about the impacts of generative AI on skill sets. This survey of 692 business practitioners showed that business practitioners widely use generative AI, with the most common uses involving research and ideation, drafting of business messages and reports, and summarizing and revising text. Business practitioners report that character-based traits such as integrity and soft skills will become more important. Implications for teaching business communication are discussed.
SMEs are increasingly forced to shift to more sustainable manufacturing. Industry 4.0 can support the transformation and foster innovation. But, SMEs need solutions with a low barrier to entry in terms of investment, IT knowledge and capacities. A framework based on value and material flow analysis, low investments and user-oriented IT skills is proposed. As an example, it is implemented in the furniture industry and shows a digital twin in terms of monitoring the energy and material flows. In addition, a product-specific allocation of energy consumption, energy peak shaving and other applications are possible.
Development of a Neural Network for Automatic Classification of Post-Consumer Wood Using Rapid-FLIM
(2023)
The economic use of wood is a growing sector, not only because of the significant advantage of wood to retain CO 2 . It is crucial to increase the material recycling of wood in several lifecycles, but currently, there is no reliable post-consumer wood sorting technique in line. This research measures 365 post-consumer wood samples of classes A1-4 four times with the frequency domain fluorescence lifetime imaging microscopy (FD-FLIM) subset method rapid fluorescence lifetime imaging microscopy (Rapid-FLIM). The data is analyzed on their statistical features. Four neural networks based on Multilayer perceptron are then trained and tested with twelve statistical features extracted from the Rapid-FLIM images. The best model for this application contains the optimizer RMSprop, the activation function SELU and the loss function binary crossentropy. The best model of this structure could achieve a false positive ratio of 4.79 % over the ten folds.
One major problem of a continuous process like plastic extrusion is their incapability to deal with non-local gas pressure. This is an inherent problem because a continuous process has an open end in the feeding port where pressure can escape. In this study a novel feeding system was developed to enable granulate feeding into gas pressurized processes inside a single- or twin-screw extruder. With this apparatus gas pressure can be applied inside the extrusion process. The apparatus separates the pressurized extruder from the dosing equipment that feeds the extruder. It keeps the pressure inside the system while continuously feeding new material into the process. A small-scale prototype was designed for proof-of concept. The small size of the prototype was able to handle small amounts of granulates of around 100 - 200 g/h. An applied gas pressure of 8 bar was achieved. In future optimizations, throughput can be increased and maximum applied gas pressure towards 15-20 bar.
Background
Vertigo, dizziness or balance disorders (VDB) are common leading symptoms in older people, which can have a negative impact on their mobility and participation in daily live, yet, diagnosis is challenging and specific treatment is often insufficient. An evidence-based, multidisciplinary care pathway (CPW) in primary care was developed and pilot tested in a previous study. The aim of the present study is to evaluate the effectiveness and safety of the CPW in terms of improving mobility and participation in community-dwelling older people with VDB in primary care.
Methods
For this multicentre cluster randomised controlled clinic trial, general practitioners (GP) will be recruited in two regions of Germany. A total of 120 patients over 60 years old with VDB will be included. The intervention is an algorithmized CPW. GPs receive a checklist for standardise clinical decision making regarding diagnostic screening and treatment of VDB. Physiotherapists (PT) receive a decision tree for evidence-based physiotherapeutic clinical reasoning and treatment of VDB. Implementation strategies comprises educational trainings as well as a workshop to give a platform for exchange for the GPs and PTs, an information meeting and a pocket card for home care nurses and informal caregivers and telephone peer counselling to give all participants the capability, opportunity and the motivation to apply the intervention. In order to ensure an optimised usual care in the control group, GPs get an information meeting addressing the national guideline. The primary outcome is the impact of VDB on participation and mobility of patients after 6 month follow-up, assessed using the Dizziness Handicap Inventory (DHI) questionnaire. Secondary outcomes are physical activity, static and dynamic balance, falls and fear of falling as well as quality of life. We will also evaluate safety and health economic aspects of the intervention. Behavioural changes of the participants as well as barriers, facilitating factors and mechanisms of impact of the implementation will be investigated with a comprehensive process evaluation in a mixed-methods design.
Discussion
With our results, we aim to improve evidence-based health care of community-dwelling older people with VDB in primary care.
Virtual meeting recordings have become a common part of virtual and hybrid workplace environments. Meeting recordings offer potential benefits (speedy transcript production, expedited information sharing, searchable information, inclusion of visual and tonal expressions) and drawbacks (difficulty discussing sensitive issues, employee privacy, limited off-the-record capabilities, and employee concerns over sharing recordings). Given this variance, policies for virtual meetings are a necessity. Managers can successfully implement a policy by co-creating policy preferences with employees in open-ended and nonjudgmental conversations that openly discuss potential benefits, drawbacks, and employee concerns. Topics such as when to record, when not to record, how to gain consent, and who will have administrative and sharing rights should be covered. Accessibility concerns, use or rejection of software features, for how long and where meeting recordings should be stored, and emerging issues such as use of virtual reality meetings and AI tools are areas of less urgency that may be part of the conversations. Managers should deliver policy preferences to a group of representatives from Human Resources, Information Technology, and the executive team to compose the policy, request a legal review, then introduce and implement it in the organization.
Exploring stakeholder perspectives: Enhancing robot acceptance for sustainable healthcare solutions
(2023)
The pandemic has highlighted the fact that healthcare systems around the world are under pressure. Demographic change is leading to an increasing shortage of care workers in most countries, and the demographic challenge is only just beginning in most societies. While robots are widely used in industry, robotic support in healthcare is still limited to very specialized robots in the operating theatre. The question of what type of deployment is likely to be successful in a healthcare scenario is not only a technological or economical question but also one of technology acceptance. The answer to this question supports entrepreneurial opportunities to develop sustainable healthcare solutions.
In this paper, we analyze the acceptance of robots in elderly care from the perspective of patients, patient families, and geriatric care professionals. To understand the various positions and to identify the suitability of existing acceptance models, we applied stakeholder mapping to conduct qualitative interviews with 14 people with different knowledge backgrounds and levels of involvement in care situations, based on 9 videos showing different robots and application scenarios.
The results confirmed that existing technology acceptance models need to be extended by factors such as robot appearance. We found that the background knowledge of the respondents influences the results of the questions about e.g. safety concerns. In addition, we found that the contribution to patients' self-determination and independence is an important factor that is not included in existing technology acceptance models. Finally, the discovery of a significant discrepancy between the self-perception and the external perception of the different stakeholders regarding the acceptance of a service robot can be explained by the stakeholder positions involved in caring for the benefit of a specific patient.
These findings encourage further research, especially with the underlying assumption that technology acceptance in healthcare is not just a patient issue, but a stakeholder issue. Stakeholder mapping is a valid tool to analyze the interdependencies for the acceptance of robots. Therefore, we suggest using a tool such as stakeholder mapping to further analyze these issues.
Fault and anomaly detection in district heating substations: A survey on methodology and data sets
(2023)
District heating systems are essential building blocks for affordable, low-carbon heat supply. Early detection and elimination of faults is crucial for the efficiency of these systems and necessary to achieve the low temperatures targeted for 4th generation district heating systems. Especially methods for fault and anomaly detection in district heating substations are currently of high interest, as faults in substations can be repaired quickly and inexpensively, and smart meter data are becoming widely available. In this paper, we review recent scientific publications presenting data-driven approaches for fault and anomaly detection in district heating substations with a focus on methods and data sets. Our review indicates that researchers use a wide variety of methods, mostly focusing on unsupervised anomaly detection rather than fault detection. This is due to a lack of labeled data sets, preventing the use of supervised learning methods and quantitative analysis. Together with the lack of publicly available data sets, this impedes the accurate comparison of individual methods. To overcome this impediment, increase the comparability of different methods and foster competition, future research should focus on establishing publicly available data sets, and industry-relevant metrics as benchmarks.
Psychological safety, the feeling of being comfortable to express one’s ideas or opinions in teams, is a key determinant of successful global virtual teams. Even though there exists considerable knowledge about its antecedents, it is unknown how team-based (e.g., clarification of deliverables and deadlines) and technology-based (e.g., digital reminder nudges/ DRN) interventions foster psychological safety given cultural variations of team members. Based on a survey involving 148 participants, our data shows that both team-based interventions (TBI) and digital nudges foster psychological safety in global virtual teams. TBI are even more effective for high-context, indirect communicators than for low-context, direct communicators. However, digital nudges were equally effective across cultures for building psychological safety. These findings contribute to the literature on psychological safety as we show that not all antecedents hold equally across cultures and to the literature of digital nudges as we show the effectiveness of technology-based interventions in a team context.
The fast classification and identification of plastics presents a significant challenge. The study assesses the suitability of a Multilayer Perceptron to classify and identify commonly found plastic types using Rapid-FLIM, achieving an accuracy of 88.33%. @inproceedingsSchwarz:23, Increasing demand for wood products requires methods to determine its harvest origin and ensure sustainable and legal sourcing. In 15 out of 21 cases, the origin of Quercus robur was differentiable in FD-FLIM studies.
Research Questions
• What attitudes do professionals hold towards the impact of AI on society and their jobs? How do early adopters of ChatGPT differ in their attitudes towards the impact of AI on society and their jobs?
• In what ways are professionals using ChatGPT? How do these uses differ by managerial status? • What do professional perceive as benefits of generative AI? How do they differ in these views based on level of ChatGPT adoption and managerial status?
• What do professionals perceive as the benefits of organizational policy for the use of generative AI? How do these views differ based on level of ChatGPT adoption and managerial status?
Samples
• Study 1 involved 148 working adults in the United States who had heard of ChatGPT
• Study 2 involved 395 working adults in the United States who had heard of ChatGPT
Research Questions
• What attitudes do professionals hold towards the impact of AI on society and their jobs? How do early adopters of ChatGPT differ from non-adopters in their attitudes towards the impact of AI on society and their jobs?
• In what ways are professionals using ChatGPT? How do these uses differ by managerial status?
• What do professionals perceive as benefits of generative AI? How do they differ in these views based on level of ChatGPT adoption and managerial status?
• What do professionals perceive as the benefits of organizational policy for the use of generative AI? How do these views differ based on level of ChatGPT adoption and managerial status?
Key Findings and Conclusions
• Many US workers in this sample are using ChatGPT for professional purposes. Roughly the following percentages have already used ChatGPT in the following ways: o 42% for researching a topic or generating ideas o 32% for drafting messages o 26% for drafting longer documents, such as reports o 22% for editing text
• Many US workers in this sample believe ChatGPT can help them become better communicators. This is particularly the case for executives and managers. Roughly two thirds of executives (67%) and managers (64%) believe generative AI can help them communicate more effectively.
• Early adopters of ChatGPT in this sample hold much different views of generative AI than do non-users of ChatGPT. Early adopters hold the following distinctive views:
o They are much more likely to think AI is good for society than non-users (64% to 22%) and believe it will make them more productive (82% for early adopters; 26% for non-users); however, they are also more likely to worry about the ethical implications of AI (68% to 55%) in the workplace and worry that their own job will be replaced by AI (41% to 20%).
o They are much more likely to think generative AI will support them in their work. About 85% of early adopters say that ChatGPT can help them generate ideas for work compared to about 50% of non-users. About 73% of early adopters say it can improve the quality of their work compared to 42% of non-users. About 74% of early adopters say it can help them communicate more effectively compared to 41% of non-users. Executives and managers are slightly more likely to be enthusiastic about the benefits.
• Employees in organizations with generative AI policies view these policies positively. Those who are aware of an organizational policy about generative AI generally believe it has supported more comfort in using ChatGPT for work, has improved trust, has improved efficiency, and has provided legal protections. Those who are early adopters are generally more positive about each of these benefits of organizational policy than those who are non-users of ChatGPT.
• Most early adopters of generative AI in organizations without generative AI policies want more guidance about ChatGPT use. Most early adopters believe an organizational policy would make them more comfortable using ChatGPT (61%), that it would increase trust (56%), and that it would improve efficiency (66%).
Key Recommendations
• Develop generative AI policies that support innovation and efficiency while putting into place legal safeguards for organizations and their employees.
• Use a social contracts approach to develop generative AI policies.
In the whole field of woodworking, from carpentry to industry, new products are created and designed every day and manufacturers wonder if similar workpieces have already been produced in the company and if corresponding drawings, information, tools, jigs, etc. can be reused. Under certain circumstances, considerable duplication of work can be avoided and a more efficient production is possible. In order to find similar workpieces, it must be clarified what exactly is meant by similarity. The different fields of knowledge do not provide a clear definition. However, similarities are always used to compare objects. In woodworking, objects can be a wide variety of components and products, such as carcase sides, furniture fronts, fittings, tools or profile strips. The search for similar profiled elements – related to the potential, data structure and algorithms – is the focus of this paper. There is a wide range of different profiled elements, which are used constructively as well as decoratively, e.g. for baseboards, door frames, window frames or decorative moulding profiles. These profiles are manufactured in a multi-stage production process in which the workpieces are first machined with profiled tools before surface finishing takes place. Along this production chain, tools, machine settings and, in some cases, fixtures are used that are adapted to the respective profile and can be reused for the same or similar jobs. Inheritance of information offers the greatest potential of similarity search. Inheritance means that existing knowledge in the form of drawings, CNC programs, process parameters and setup specifications, etc., is transferred from existing profiles to a new profile. By inheriting existing information, for example, the effort required for process setting can be reduced by adopting spindle positions, positions of guides and stops, or feed and cutting speeds. However, this can only be done if the process knowledge and other technological information concerning a profile are sufficiently documented. This is the only way how all information is made available for the similarity search and inheritance, and also for setting the processes when the profile is manufactured once again. The profile data must therefore be stored in a meaningful structure without loss of information. Therefore, a holistic product data model was developed that combines the geometrical with the technological profile data. The developed model allows a combined search for geometrically and e.g. materially similar products – also with a weighted evaluation of the individual criteria. The research has shown that data modelling is the essential foundation for the implementation of modern AI algorithms to enable similarity search. In conclusion, the use of a search system for geometrically and technologically similar profiles represents a real innovation for wood processing companies. This paper presents a holistic approach for geometrical and technological similarity search presenting different algorithms
Investigation of tool wear of the trimming unit and resulting quality in the edgebanding process
(2023)
The edgebanding process, i.e. the covering of the raw edge of the laminated particleboard by means of decorative plastic or real wood veneer bands, is an important process step in the manufacture of furniture components. The quality of the final product is significantly influenced by this production step. The manufacturing process step within the edgebanding machine begins with the milling of the raw edge. The quality of the edgebanding process is determined by a large number of process input variables, such as the tool used and the cutting geometry, the type of laminate used for the wood-based material, adhesives, etc. The quality of the edgebanding process is also determined by the type of material processed. Particularly with regard to the materials, the increased use of recycled wood in the particleboard sector and different types of adhesives (with reduced formaldehyde emissions) results in increased demands on the milling process. Due to this developments, most of the earlier investigations (in the years 1990 - 2000) are not comparable with today’s general conditions. The mechanical and optical properties of the edge applied to the end product are decisively influenced by the quality of this joint. The milling technology used, as well as the tool used for this purpose and its condition, is a decisive influencing factor in the formation of quality. Tests on the indication of various influencing variables in the edgebanding process at the Rosenheim Technical University of Applied Sciences showed that in the case of chipboard milling, a decrease in the electrical power required for the cutting process can take place with increasing tool wear. It was also demonstrated that previous process steps in furniture production, such as panel dividing by means of sawing or milling/nesting, generally have a significantly different influence on the subsequent joining process during edge banding process. Furthermore, a direct correlation was determined between the mechanical properties of the end product and the condition of the tool used, which can be used as a measurable indicator. In addition to the effect of the tool condition on the mechanical properties of the edge banding, this also has an impact on the optical quality characteristics. Accordingly, it could be demonstrated here that an increase in the size and number of chippings takes place in the laminate of the board material to be processed.
Stable isotope data from hypogene (i.e., below the line of weathering) iron oxides and gangue minerals from BIF-hosted iron ore deposits in Australia, South Africa, and Brazil have significantly assisted in constraining different hydrothermal fluid sources and fluid flow models during the upgrade of BIF to iron ore. The δ18O values on iron oxides from BIF and different paragenetic stages of enrichment display a consistent decrease from unenriched BIF (4–9‰) to as low as −10‰ for high-grade iron ore. This large shift in oxygen isotope values is interpreted as evidence for enormous incursion of ‘ancient’ meteoric water into fault and fracture zones at the time of iron enrichment during the Archean and Paleoproterozoic time. The δ18Ofluid values of paragenetically early iron oxides of > 4‰ suggest the involvement of magmatic fluids in greenstone belt-hosted Carajás-type iron ore deposits, and basinal brines in basin-hosted Hamersley-type deposits. In contrast, the paragenetically late stage iron oxides in the metamorphosed, basin hosted iron ore deposits of the Quadrilátero Ferrífero display δ18Ofluid values > 6‰. This reflects the renewed deep crustal, hypogene (metamorphic or magmatic) fluid influx. Carbon and oxygen isotope data on carbonates in BIF and hydrothermally altered iron ore indicate that carbon in the latter is not derived from BIF units, but represents either magmatic carbon in the case of the Carajás-type deposits or carbon within the underlying basin stratigraphy as in the case of the Hamersley-type iron deposits. The systematic decrease of δ18O values in iron oxides from the early to late paragenetic stages and from the distal to proximal alteration zone, including the ore zone, may be used as a geochemical vector. In this case, oxygen isotope analyses on iron oxides provide a potential exploration tool, particularly for targeting the extension of iron ore bodies or entirely concealed high-grade iron ore deposits, in which hematite/magnetite are frequently the only mineral that can be readily analysed.
Due to the increasing customer demands, companies face the challenge of adapting their manufacturing facilities to produce batch size one parts. In this context, each component comes with specific customer requirements, significantly increasing the complexity of its manufacturing process. Traditional process planning done by employees is no longer feasible in the face of the growing complexity and diversity of batch size one parts. Therefore, there is a need for novel computer-aided process planning methods capable of autonomously learning and identifying the necessary machining features of these parts. We propose a configurable automated feature recognition framework tailored to batch size one parts to address this need. This framework comprises two main components. First, a customizable data generator is developed to create a dataset of computer-aided design models incorporating user-specific machining features. Second, a graph neural network is employed to learn these user-specific machining features by leveraging the graph structure represented by the vertices and edges in each computer-aided design model. We evaluate the effectiveness of our framework using a real-world example from the furniture industry. Specifically, we construct a dataset comprising over 7000 computer-aided design models of wooden boards using our framework's data generator. Each wooden board contains up to 30 randomly placed machining features for the application of connectors and fittings, randomly selected from 14 standard machining features commonly used in the furniture industry. An optimization algorithm adapts a graph neural network for classifying these specific machining features. The results demonstrate that our framework addresses the automated feature recognition problem without requiring data conversions, such as pixels or voxels, as other approaches often do. By introducing this configurable automated feature recognition framework, we solve the challenges posed by batch size one manufacturing. The framework's effectiveness and accuracy are demonstrated through extensive testing on the example of the furniture industry, showcasing its potential for enhancing manufacturing processes in various domains
Existing plastic analysis techniques such as Fourier transform infrared spectroscopy and Raman spectroscopy are problematic because samples must be anhydrous and identification can be hindered by additives. This article describes a new approach that has been successfully demonstrated in which plastics can be classified by neural networks that are trained, validated, and tested by frequency domain fluorescence lifetime imaging microscopy measurements.
Non-Rest to non-Rest Reference Slews for Agile Imaging Satellites With LQ-minimized Angular Momentum
(2023)
This paper shows a full parametrization non-rest to non-rest slew maneuvers using polynomials. A new modelling formulation is developed which on one hand satisfies exactly the given boundary conditions as well as the kinematic differential equation of the rotating body exactly. The idea is to determine one part of the unknown coefficients by the kinematical boundary conditions and to use the other part as free design parameters to shape the dynamic in between the boundary conditions. In addition, a least squares problem is formulated in order to minimize the angular momentum of the slew. This approach allows optimal slew maneuvers as well as low computational need such that an onboard usage is possible.
In this research, we discuss the past and current trends in defining poverty to look at the topic from different perspectives and to provide an outline of future work that we aim to complete the picture on the qualitative and quantitative side. For this purpose, our focus here is to evaluate the diversity of definitions and to emphasize how important it is to combine subjective and objective approaches for practical policy analysis. As a first step of our future work, we also present the pilot study results to assess the results comparatively in the EU states and Türkiye.
This article examines interweaving collective histories in different formerly colonized regions of the world: 1. Migratory movements from the territory of the former Ottoman Empire to the Americas, specifically to Brazil, and 2. transregional migration between different regions within China. On the basis of empirical data, we discuss sociological biographical research as an approach to analyzing migration and social mobility as transgenerational processes. In the case of Syrians in Brazil who have fled from the civil war, these processes are reflected in transnational family structures, transgenerational mandates, and knowledge transmission. In the case of domestic migration within China, the “mission” that families give their children is social advancement through education (e.g., Crabb 2010; Fong 2004). In the context of anti-Western discourses in China, it can be demonstrated that postcolonial discourses are functional in the effort to regain former international strength and national prosperity, and that discourses on “becoming a modern citizen” pervade family aspirations. The article is intended as a plea for i) taking a closer look at historical and contemporary South-South relations, and ii) situating current migration movements historically. It ties into global historical and sociological debates on “shared/common histories” and “intertwined histories."
We introduce a quick and accurate quasi-static magnetic field scanning technique by employing a progressive sampling method in an unconfined input space. The proposed
machine learning algorithm is tested against uniform sampling on a printed circuit board test structure. We prove allocation of multiple, separated regions with predefined tangential field strengths at MHz frequencies. The feasibility of equivalent magnetic dipole source modeling based on a small number of samples is demonstrated. Compared to uniform testing, progressive expansion sampling detects contours of given field limits in less than 3% of the reference measurement time.
We present a fast and accurate measurement technique for quasi-static magnetic fields by employing a progressive sampling method in an unconfined input space. The proposed machine learning algorithm is tested against uniform sampling on printed circuit board test structures and a buck converter. We prove allocation of multiple, separated regions with predefined lateral field limits at MHz frequencies. The feasibility of equivalent magnetic dipole source modeling based on a small number of samples is demonstrated. Compared to uniform testing, progressive expansion sampling identifies contours of given field limits in less than 3% of the reference measurement time.
The bond between polymer fibers and the surrounding cementitious matrix is essential for the development of concrete reinforcement. The single fiber pull-out test (SFPT) is the standard characterization technique for testing the bond strength. However, the different phases of debonding cannot be distinguished by the SFPT. This study investigates the debonding of different polymer fibers from the surrounding cementitious matrix with a modified SFPT and proposes methods to change the SFPT setup to generate more valuable information on the debonding mechanism. The SFPT was equipped with linear variable differential transformers (LVDT), digital image correlation (DIC) and acoustic emission (AE) analysis. The results demonstrate that the modified SFPT allows a better understanding of the different phases of debonding during fiber pull-out. Furthermore, bond strength values calculated by different methods reveal that the chemical bond of the investigated polymers is not different as reported by previous studies. Deformation measurements performed using LVDTs and DIC are suitable measuring techniques to characterize the debonding mechanism in SFPT. A correlation between recorded AE and debonding phases was not found.
Background:
3D gait analysis (3DGA) is a common assessment in Cerebral Palsy (CP) to quantify the extent of movement abnormalities. Yet, 3DGA is performed in laboratories and may thus be of debatable significance to everyday life.
Aim
The aim was to assess the relationship between kinematic gait abnormality and everyday mobility in ambulatory children and youth with spastic CP.
Methods:
73 paediatric and juvenile patients with uni- or bilateral spastic CP (N = 21 USCP, N = 52, BSCP, age: 4–20 y, GMFCS I-III) underwent a 3DGA, while the MobQues47 Questionnaire quantified caregiver-reported mobility. We calculated the Gait Profile Score (GPS), a metric that summarizes how far the lower limb joint angles during walking deviate from those of matched controls.
Results:
The GPS correlated well with indoor and outdoor mobility (rho = −0.69 and −0.70, both p < 0.001) and the relationships were not significantly different for USCP and BSCP. Still, mobility was lower in BSCP (p < 0.001) and more compromised outdoors (p = 0.002). Indoor mobility could be predicted by walking speed, GPS and age (adj. R2 = 0.62). Outdoor mobility was best predicted by walking speed and GPS (adj. R2 = 0.60). The additive explained variance by the GPS was even higher outdoors than indoors (17.1% vs. 11.4%).
Conclusions:
Measuring movement deviations with 3DGA seems equally meaningful in uni- and bilaterally affected children and has considerable relevance for real-life ambulation, particurlarly outdoors, where children with spastic CP typically face greater difficulties. Therapeutic strategies that achieve faster walking and reduction of kinematic deviations may increase outdoor mobility.
Background Personalized mRNA vaccines are promising new therapeutic options for patients with cancer. Because mRNA vaccines are not yet approved for first-line therapy, the vaccines are presently applied to individuals that received prior therapies that can have immunocompromising effects. There is a need to address how prior treatments impact mRNA vaccine outcomes.
Method Therefore, we analyzed the response to BioNTech/Pfizer’s anti-SARS-CoV-2 mRNA vaccine in 237 oncology outpatients, which cover a broad spectrum of hematologic malignancies and solid tumors and a variety of treatments. Patients were stratified by the time interval between the last treatment and first vaccination and by the presence or absence of florid tumors and IgG titers and T cell responses were analyzed 14 days after the second vaccination.
Results Regardless of the last treatment time point, our data indicate that vaccination responses in patients with checkpoint inhibition were comparable to healthy controls. In contrast, patients after chemotherapy or cortisone therapy did not develop an immune response until 6 months after the last systemic therapy and patients after Cht-immune checkpoint inhibitor and tyrosine kinase inhibitor therapy only after 12 months.
Conclusion Accordingly, our data support that timing of mRNA-based therapy is critical and we suggest that at least a 6-months or 12-months waiting interval should be observed before mRNA vaccination in systemically treated patients.
The pandemic has highlighted the fact that healthcare systems around the world are under pressure. Demographic change is leading to an increasing shortage of care workers in most countries, and the demographic challenge is only just beginning in most societies. While robots are widely used in industry, robotic support in healthcare is still limited to very specialised robots in the operating theatre. The question of what type of deployment is likely to be successful in a healthcare scenario is not only a technological or economical question, but also one of technology acceptance.
In this paper we analyse the acceptance of robots in elderly care from the perspective of patients, patient families, and geriatric care professionals. To understand the various positions and to identify the suitability of existing acceptance models, we applied stakeholder mapping to conduct qualitative interviews with 14 people with different knowledge backgrounds and levels of involvement in care situations, based on 9 videos showing different robots and application scenarios.
The results confirmed that existing technology acceptance models need to be extended by factors such as robot appear-ance. We found that the background knowledge of the respondents influences the results of the questions about e.g. safety concerns. In addition, we found that the contribution to patients' self-determination and independence is an im-portant factor that is not included in existing technology acceptance models. Finally, the discovery of a significant dis-crepancy between the self-perception and the external perception of the different stakeholders regarding the acceptance of a service robot can be explained by the stakeholder positions involved caring for the benefit of a specific patient.
These findings encourage further research, especially with the underlying assumption that technology acceptance in healthcare is not just a patient issue, but a stakeholder issue. Stake holder mapping is a valid tool to analyze the inter-dependences for acceptance of robots. Therefore, we suggest using a tool such as stakeholder mapping to further ana-lyze these issues.
Virtual team meetings are increasingly supported with advanced technology. This study investigates the extent to which Al-enabled speech technology can be useful for global virtual teams (GVT). A survey was conducted in GVTs in 2020 and 2021, when people's lives were primarily dominated by the pandemic. A transcription software was used to support the collaboration. A total of 530 survey responses were analyzed using a structured approach- qualitative content analysis. The data was structured using the SWOT framework that aimed at comprehensively answering the research question "To what extent is the use of Al-supported speech technology in GVTs useful?". Al-generated transcripts are helping to overcome language and time zone barriers in GVT. Yet, they also cause misunderstandings and impact openness of communication. Further results and implications for GVT are discussed.
This article introduces the Database for Estimation of Road Network Performance (DERNP) to enable wide-scale estimation of relevant Road Network Performance (RNP) factors for major German cities. The methodology behind DERNP is based on a randomized route sampling procedure that utilizes the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) in combination with the tile-based HERE Maps Traffic API v7 and a digital elevation model provided by the European Union’s Earth Observation Programme Copernicus to generate a large set of independent and realistic routes throughout OpenStreetMap road networks. By evaluating these routes using the PHEMLight5 framework, a comprehensive list of RNP parameters is estimated and translated into polynomial regression models for general usage. The applicability of these estimations is demonstrated based on a case study of four major German cities. This case study considers network characteristics in terms of detours, infrastructure, traffic congestion, fuel consumption, and CO2 emissions. Our results show that DERNP and its underlying randomized route sampling methodology overcomes major limitations of previous wide-scale RNP approaches, enabling efficient, easy-to-use, and region-specific RNP comparisons.
The Challenges and Opportunities of AI-Assisted Writing: Developing AI Literacy for the AI Age
(2023)
Generative AI may significantly disrupt the teaching and practice of business communication. This study of 343 communication instructors revealed a collective view that AI-assisted writing will be widely adopted in the workplace and will require significant changes to instruction. Key perceived challenges include less critical thinking and authenticity in writing. Key perceived benefits include more efficiency and better idea generation in writing. Students will need to develop AI literacy—composed of application, authenticity, accountability, and agency—to succeed in the workplace. Recommendations are provided for instructors and administrators to ensure the benefits of AI-assisted writing can outweigh the challenges.
This article investigates multimodal elements—images, links, gifs, videos, and galleries—of crowdfunding campaigns on the platform Kickstarter to develop an understanding of characteristics of successful campaigns. The authors scraped 327,586 campaign pages, analyzing the multimodal elements of successful and unsuccessful campaigns. They found that successful campaigns featured more images, links, and gifs and more frequently included a project video than did unsuccessful campaigns. Images, links, and the presence of a project video had a positive impact on success while gifs and project galleries did not. These findings give business communicators practical guidance, develop theoretical aspects of Kickstarter research, and validate previous findings with a larger data set.
The impulse to think about process-induced social networks (in short: process networks) comes from the discipline of “Process Mining” (e.g. van der Aalst et al. 2005). The relevant literature refers to an "organizational view" or "organizational mining" in process mining.
In essence, process mining is about creating a time-logical chain of related tasks from automatically logged user activities on a computer. In this way, real processes can be mapped and analyzed as models. As a "by-product", task-related social networks are created between the process participants through the predecessor/successor relationships in the workflow.
However, it should be noted and criticized that process mining research neglects the potential of social network analysis. The extensive findings of classical network research are not taken up further. An organizational and social scientific deepening of the data-driven preliminary work is missing in this discipline. Process mining, which tends to be mathematical and technical, has not yet developed the ambition to ally itself with empirical organizational and social research.
This working paper tries to counteract this. It presents a first, social science-based approach to theoretically grounding process networks.