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In bimodal cochlear implant (CI) / hearing aid (HA) users a constant interaural time delay in the order of several milliseconds occurs due to differences in signal processing of the devices. For MED-EL CI systems in combination with different HA types, we have quantified the respective device delay mismatch (Zirn et al. 2015). In the current study, we investigate the effect of the device delay mismatch in simulated and actual bimodal listeners on sound localization accuracy.
To deal with the device delay mismatch in actual bimodal listeners we delayed the CI stimulation according to the measured HA processing delay and two other values. With all delay values highly significant improvements of the rms error in the localization task were observed compared to the test without the delay. The results help to narrow down the optimal patient-specific delay value.
Despite increasing budgets for social media activities and a wide variety of performance measurement possibilities, many companies do not measure the performance of their social media activities. Research shows that those companies that measure the performance of social media activities use incorrect, too few or inappropriate metrics. A central problem is that there is often an inadequate performance measurement process. This article presents a process that focuses on the objectives of social media activities. In phase one of this process, suitable metrics are selected and target values are defined based on these objectives. In phase two, data are collected and analysed. Finally, actions are defined. The developed process helps companies to measure the performance of their social media activities.
This article presents a comparative experimental study of the electrical, structural and chemical properties of large‐format, 180 Ah prismatic lithium iron phosphate (LFP)/graphite lithium‐ion battery cells from two different manufacturers. These cells are particularly used in the field of stationary energy storage such as home‐storage systems. The investigations include (1) cell‐to‐cell performance assessment, for which a total of 28 cells was tested from each manufacturer, (2) electrical charge/discharge characteristics at different currents and ambient temperatures, (3) internal cell geometries, components, and weight analysis after cell opening, (4) microstructural analysis of the electrodes via light microscopy and scanning electron microscopy, (5) chemical analysis of the electrode materials using energy‐dispersive X‐ray spectroscopy, and (6) mathematical analysis of the electrode balances. The combined results give a detailed and comparative insight into the cell characteristics, providing essential information needed for system integration. The study also provides complete and self‐consistent parameter sets for the use in cells models needed for performance prediction or state diagnosis.
Treadmills are essential to the study of human and animal locomotion as well as for applied diagnostics in both sports and medicine. The quantification of relevant biomechanical and physiological variables requires a precise regulation of treadmill belt velocity (TBV). Here, we present a novel method for time-efficient tracking of TBV using standard 3D motion capture technology. Further, we analyzed TBV fluctuations of four different treadmills as seven participants walked and ran at target speeds ranging from 1.0 to 4.5 m/s. Using the novel method, we show that TBV regulation differs between treadmill types, and that certain features of TBV regulation are affected by the subjects’ body mass and their locomotion speed. With higher body mass, the TBV reductions in the braking phase of stance became higher, even though this relationship differed between locomotion speeds and treadmill type (significant body mass × speed × treadmill type interaction). Average belt speeds varied between about 98 and 103% of the target speed. For three of the four treadmills, TBV reduction during the stance phase of running was more intense (> 5% target speed) and occurred earlier (before 50% of stance phase) unlike the typical overground center of mass velocity patterns reported in the literature. Overall, the results of this study emphasize the importance of monitoring TBV during locomotor research and applied diagnostics. We provide a novel method that is freely accessible on Matlab’s file exchange server (“getBeltVelocity.m”) allowing TBV tracking to become standard practice in locomotion research.
Objective: To identify and evaluate the evidence of the most relevant running-related risk factors (RRRFs) for running-related overuse injuries (ROIs) and to suggest future research directions.
Design: Systematic review considering prospective and retrospective studies. (PROSPERO_ID: 236832)
Data sources: Pubmed. Connected Papers. The search was performed in February 2021.
Eligibility criteria: English language. Studies on participants whose primary sport is running addressing the risk for the seven most common ROIs and at least one kinematic, kinetic (including pressure measurements), or electromyographic RRRF. An RRRF needed to be identified in at least one prospective or two retrospective studies.
Results: Sixty-two articles fulfilled our eligibility criteria. Levels of evidence for specific ROIs ranged from conflicting to moderate evidence. Running populations and methods applied varied considerably between studies. While some RRRFs appeared for several ROIs, most RRRFs were specific for a particular ROI. The biomechanical measurements performed in many studies would have allowed for consideration of many more RRRFs than have been reported, highlighting a potential for more effective data usage in the future.
Conclusion: This study offers a comprehensive overview of RRRFs for the most common ROIs, which might serve as a starting point to develop ROI-specific risk profiles of individual runners. Future work should use macroscopic (big data) approaches involving long-term data collections in the real world and microscopic approaches involving precise stress calculations using recent developments in biomechanical modelling. However, consensus on data collection standards (including the quantification of workload and stress tolerance variables and the reporting of injuries) is warranted.
Activities for rehabilitation and prevention are often lengthy and associated with pain and frustration. Their playful enrichment (hereafter: gamification) can counteract this, resulting in so-called “exergames”. However, in contrast to games designed solely for entertainment, the increased motivation and immersion in gamified training can lead to a reduced perception of pain and thus to health deterioration. Therefore, it is necessary to monitor activities continuously. However, only an AI-based system able to generate autonomous interventions could vacate the therapists’ costly time and allow better training at home. An automated adjustment of the movement training’s difficulty as well as individualized goal setting and control are essential to achieve such autonomy. This article’s contribution is two-fold: (1) We portray the potentials of gamification in the health area. (2) We present a framework for smart rehabilitation and prevention training allowing autonomous, dynamic, and gamified interactions.
Governments have restricted public life during the COVID-19 pandemic, inter alia closing sports facilities and gyms. As regular exercise is essential for health, this study examined the effect of pandemic-related confinements on physical activity (PA) levels. A multinational survey was performed in 14 countries. Times spent in moderate-to-vigorous physical activity (MVPA) as well as in vigorous physical activity only (VPA) were assessed using the Nordic Physical Activity Questionnaire (short form). Data were obtained for leisure and occupational PA pre- and during restrictions. Compliance with PA guidelines was calculated based on the recommendations of the World Health Organization (WHO). In total, n = 13,503 respondents (39 ± 15 years, 59% females) were surveyed. Compared to pre-restrictions, overall self-reported PA declined by 41% (MVPA) and 42.2% (VPA). Reductions were higher for occupational vs. leisure time, young and old vs. middle-aged persons, previously more active vs. less active individuals, but similar between men and women. Compared to pre-pandemic, compliance with WHO guidelines decreased from 80.9% (95% CI: 80.3–81.7) to 62.5% (95% CI: 61.6–63.3). Results suggest PA levels have substantially decreased globally during the COVID-19 pandemic. Key stakeholders should consider strategies to mitigate loss in PA in order to preserve health during the pandemic.
The compliant nature of distal limb muscle-tendon units is traditionally considered suboptimal in explosive movements when positive joint work is required. However, during accelerative running, ankle joint net mechanical work is positive. Therefore, this study aims to investigate how plantar flexor muscle-tendon behavior is modulated during fast accelerations. Eleven female sprinters performed maximum sprint accelerations from starting blocks, while gastrocnemius muscle fascicle lengths were estimated using ultrasonography. We combined motion analysis and ground reaction force measurements to assess lower limb joint kinematics and kinetics, and to estimate gastrocnemius muscle-tendon unit length during the first two acceleration steps. Outcome variables were resampled to the stance phase and averaged across three to five trials. Relevant scalars were extracted and analyzed using one-sample and two-sample t-tests, and vector trajectories were compared using statistical parametric mapping. We found that an uncoupling of muscle fascicle behavior from muscle-tendon unit behavior is effectively used to produce net positive mechanical work at the joint during maximum sprint acceleration. Muscle fascicles shortened throughout the first and second steps, while shortening occurred earlier during the first step, where negative joint work was lower compared with the second step. Elastic strain energy may be stored during dorsiflexion after touchdown since fascicles did not lengthen at the same time to dissipate energy. Thus, net positive work generation is accommodated by the reuse of elastic strain energy along with positive gastrocnemius fascicle work. Our results show a mechanism of how muscles with high in-series compliance can contribute to net positive joint work.
Disruptive innovations can solve major global challenges. However, the system in Germany does not sufficiently favor the development of such innovations. The disruptive output of leading nations like the United States puts increasing pressure on Germany’s innovation leadership. The German innovation agency SPRIND was founded in 2019 and is a suitable instrument to promote disruptive innovations. The SPRIND itself cites the American innovation agency DARPA, which has been promoting disruptive innovations since 1958, a role model. Therefore, the aim of this paper is to conduct a comparative analysis of DARPA and SPRIND. To answer the research question, secondary sources were used. In addition, two expert interviews were conducted with employees of SPRIND. The result of this paper is a systematic comparison that identifies the key differences and similarities between the two agencies. SPRIND is based on DARPA in key success factors, such as the person-centered approach, funding instruments or risk management. However, compared to DARPA, SPRIND has a major disadvantage; namely several administrative hurdles which inhibit agile action.
Emerging applications in soft robotics, wearables, smart consumer products or IoT-devices benefit from soft materials, flexible substrates in conjunction with electronic functionality. Due to high production costs and conformity restrictions, rigid silicon technologies do not meet application requirements in these new domains. However, whenever signal processing becomes too comprehensive, silicon technology must be used for the high-performance computing unit. At the same time, designing everything in flexible or printed electronics using conventional digital logic is not feasible yet due to the limitations of printed technologies in terms of performance, power and integration density. We propose to rather use the strengths of neuromorphic computing architectures consisting in their homogeneous topologies, few building blocks and analog signal processing to be mapped to an inkjet-printed hardware architecture. It has remained a challenge to demonstrate non-linear elements besides weighted aggregation. We demonstrate in this work printed hardware building blocks such as inverter-based comprehensive weight representation and resistive crossbars as well as printed transistor-based activation functions. In addition, we present a learning algorithm developed to train the proposed printed NCS architecture based on specific requirements and constraints of the technology.
Printed electronics (PE) offers flexible, extremely low-cost, and on-demand hardware due to its additive manufacturing process, enabling emerging ultra-low-cost applications, including machine learning applications. However, large feature sizes in PE limit the complexity of a machine learning classifier (e.g., a neural network (NN)) in PE. Stochastic computing Neural Networks (SC-NNs) can reduce area in silicon technologies, but still require complex designs due to unique implementation tradeoffs in PE. In this paper, we propose a printed mixed-signal system, which substitutes complex and power-hungry conventional stochastic computing (SC) components by printed analog designs. The printed mixed-signal SC consumes only 35% of power consumption and requires only 25% of area compared to a conventional 4-bit NN implementation. We also show that the proposed mixed-signal SC-NN provides good accuracy for popular neural network classification problems. We consider this work as an important step towards the realization of printed SC-NN hardware for near-sensor-processing.
Achieving Positive Hospitality Experiences through Technology: Findings from Singapore and Malaysia
(2021)
Customers’ experience is one of the most impactful factors in the tourism industry. Only by offering customers an excellent experience is it possible to build and ensure long-term customer loyalty. In today’s world, technology plays a key role in providing customers with an excellent customer experience. This study has the objective of analyzing how a positive customer experience can be achieved, and which technologies are necessary to ensure this. Results were collected through a literature review, and qualitative interviews with managers of selected hotels, as well as of attractions in Malaysia and Singapore. The analysis of these hotels and attractions is based on a set of criteria to determine the extent of the adoption of the new standards that contribute to positive online customer experiences. As a conclusion, different perspectives are compared, and positive and negative aspects of the use of modern technologies in the tourism industry are specified and discussed.
Introduction: The use of scaffolds in tissue engineering is becoming increasingly important as solutions need to be found to preserve human tissues such as bone or cartilage. Various factors, including cells, biomaterials, cell and tissue culture conditions, play a crucial role in tissue engineering. The in vivo environment of the cells exerts complex stimuli on the cells, thereby directly influencing cell behavior, including proliferation and differentiation. Therefore, to create suitable replacement or regeneration procedures for human tissues, the conditions of the cells’ natural environment should be well mimicked. Therefore, current research is trying to develop 3-dimensional scaffolds (scaffolds) that can elicit appropriate cellular responses and thus help the body regenerate or replace tissues. In this work, scaffolds were printed from the biomaterial polycaprolactone (PCL) on a 3D bioplotter. Biocompatibility testing was used to determine whether the printed scaffolds were suitable for use in tissue engineering.
Material and Methods: An Envisiontec 3D bioplotter was used to fabricate the scaffolds. For better cell-scaffold interaction, the printed polycaprolactone scaffolds were coated with type-I collagen. Three different cell types were then cultured on the scaffolds and various tests were used to investigate the biocompatibility of the scaffolds.
Results: Reproducible scaffolds could be printed from polycaprolactone. In addition, a coating process with collagen was developed, which significantly improved the cell-scaffold interaction. Biocompatibility tests showed that the PCL-collagen scaffolds are suitable for use with cells. The cells adhered to the surface of the scaffolds and as a result extensive cell growth was observed on the scaffolds. The inner part of the scaffolds, however, remained largely uninhabited. In the cytotoxicity studies, it was found that toxicity below 20% was present in some experimental runs. The determination of the compressive strength by means of the universal testing machine Z005 by ZWICK according to DIN EN ISO 604 of the scaffolds resulted in a value of 68.49 ± 0.47 MPa.
In an experience economy market competition in software branches is becoming more and more intense. Technical innovations, global retail practices and the multidimensional conception of experiences provide both opportunities and challenges for companies worldwide. Retailers strive for an optimized conversion rate, but poor UX still abound. Particularly Germany-based companies are less evolved in an international comparison of industrialized economies. The value of integrating users in the development process is recognized, but methodologies must carefully be incorporated into existing agile workflows. The goal of this study is to bridge the gaps between internal agency and external client and user interests. The contribution is four-fold: an overview of the current status of customer centricity in the E-Commerce branch of trade is provided (I). Based on this corpus, a methodical framework, aiming to incorporate the experience logic in UX practices within an agile project team, is presented (II). The framework is applied by a single case study - the shop relaunch of a motorbike accessory store (III). Finally, all interest groups (UX, development and project management) are incorporated in the qualitative content analysis (IV).
Social Haptic Communication (SHC) is one of the many tactile modes of communication used by persons with deafblindness to access information about their surroundings. SHC usually involves an interpreter executing finger and hand signs on the back of a person with multi-sensory disabilities. Learning SHC, however, can become challenging and time-consuming, particularly to those who experience deafblindness later in life. In this work, we present PatRec: a mobile game for learning SHC concepts. PatRec is a multiple-choice quiz game connected to a chair interface that contains a 3x3 array of vibration motors emulating different SHC signs. Players collect scores and badges whenever they guess the right SHC vibration pattern, leading to continuous engagement and a better position on a leaderboard. The game is also meant for family members to learn SHC. We report the technical implementation of PatRec and the findings from a user evaluation.
Dementia is a clinical diagnosis reflecting many possible underlying pathologies, for example, vascular dementia and neurodegenerative disorders such as frontotemporal dementia, Lewy body-type disorder or Alzheimer’s disease (AD). The breakthrough of 99mtechnetium-labelled perfusion tracers in the 1990s resulted in many SPECT studies of flow changes in AD. In the first decade of 2000, the role of perfusion SPECT was shifted from diagnosis towards differential diagnosis, parallel to the growing attention for diagnosing early stages of dementia. Previously a diagnosis based largely on a process of exclusion, new guidelines have emerged increasingly employing positive criteria to establish the diagnosis, including neuroimaging biomarkers. Nowadays, FDG PET has largely limited the role of perfusion SPECT, although it is still considered a valuable and cost-effective alternative when PET is not available.
The Go programming language is an increasingly popular language but some of its features lack a formal investigation. This article explains Go's resolution mechanism for overloaded methods and its support for structural subtyping by means of translation from Featherweight Go to a simple target language. The translation employs a form of dictionary passing known from type classes in Haskell and preserves the dynamic behavior of Featherweight Go programs.
In recent years, both the Internet of Things (IoT) and blockchain technologies have been highly influential and revolutionary. IoT enables companies to embrace Industry 4.0, the Fourth Industrial Revolution, which benefits from communication and connectivity to reduce cost and to increase productivity through sensor-based autonomy. These automated systems can be further refined with smart contracts that are executed within a blockchain, thereby increasing transparency through continuous and indisputable logging. Ideally, the level of security for these IoT devices shall be very high, as they are specifically designed for this autonomous and networked environment. This paper discusses a use case of a company with legacy devices that wants to benefit from the features and functionality of blockchain technology. In particular, the implications of retrofit solutions are analyzed. The use of the BISS:4.0 platform is proposed as the underlying infrastructure. BISS:4.0 is
intended to integrate the blockchain technologies into existing enterprise environments. Furthermore, a security analysis of IoT and blockchain present attacks and countermeasures are presented that are identified and applied to the mentioned use case.
This paper describes a thorough analysis of using PPO to learn kick behaviors with simulated NAO robots in the simspark environment. The analysis includes an investigation of the influence of PPO hyperparameters, network size, training setups and performance in real games. We believe to improve the state of the art mainly in four points: first, the kicks are learned with a toed version of the NAO robot, second, we improve the reliability with respect to kickable area and avoidance of falls, third, the kick can be parameterized with desired distance and direction as input to the deep network and fourth, the approach allows to integrate the learned behavior seamlessly into soccer games. The result is a significant improvement of the general level of play.