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Online Learning algorithms and Indoor Positioning Systems are complex applications in the environment of cyber-physical systems. These distributed systems are created by networking intelligent machines and autonomous robots on the Internet of Things using embedded systems that enable the exchange of information at any time. This information is processed by Machine Learning algorithms to make decisions about current developments in production or to influence logistics processes for optimization purposes. In this article, we present and categorize the further development of the prototype of a novel Indoor Positioning System, which constantly adapts its knowledge to the conditions of its environment with the help of Online Learning. Here, we apply Online Learning algorithms in the field of sound-based indoor localization with low-cost hardware and demonstrate the improvement of the system over its predecessor and its adaptability for different applications in an experimental case study.
The integration of genetic algorithms to optimize the networks of value chains could enormously improve the performance of supply chains. For this reason, this paper describes in more detail the application of genetic algorithms in the value chains of the automotive industry. For this purpose, a theoretical model is built up to evaluate whether the application of the model can optimize the value chain. This option is described, analyzed and its restrictions are shown. Instead of looking at the entire network, individual finished goods and their bill of material are used as a basis for optimization, which greatly reduces the complexity of the original problem. The original complexity of the supply chain networks can thus be reduced and considered based on the bill of material.
Organic semiconductor distributed feedback laser fabricated by direct laser interference ablation
(2007)
We use a pulsed, frequency tripled picosecond Nd:YAG laser for holographic ablation to pattern a surface relief grating into an organic semiconductor guest-host system. The resulting second order distributed feedback lasers exhibit laser action with laser thresholds being comparable to those obtained with resonators structured by standard lithographic techniques. The details of the interference ablation of tris-(8-hydroxyquinoline) aluminum (Alq(3)) doped with the laser dye 4- dicyanomethylene-2-methyl-6-(p-dimethylaminostyryl)-4H-pyran (DCM) are presented and discussed. Lasing action is demonstrated at a wavelength of 646.6 nm, exploiting second order Bragg reflection in a relief grating with a period of 399 nm.
Aim: The aim of the study was to identify common orthopedic sports injury profiles in adolescent elite athletes with respect to age, sex, and anthropometrics.
Methods: A retrospective data analysis of 718 orthopedic presentations among 381 adolescent elite athletes from 16 different sports to a sports medical department was performed. Recorded data of history and clinical examination included area, cause and structure of acute and overuse injuries. Injury-events were analyzed in the whole cohort and stratified by age (11–14/15–17 years) and sex. Group differences were tested by chi-squared-tests. Logistic regression analysis was applied examining the influence of factors age, sex, and body mass index (BMI) on the outcome variables area and structure (α = 0.05).
Results: Higher proportions of injury-events were reported for females (60%) and athletes of the older age group (66%) than males and younger athletes. The most frequently injured area was the lower extremity (47%) followed by the spine (30.5%) and the upper extremity (12.5%). Acute injuries were mainly located at the lower extremity (74.5%), while overuse injuries were predominantly observed at the lower extremity (41%) as well as the spine (36.5%). Joints (34%), muscles (22%), and tendons (21.5%) were found to be the most often affected structures. The injured structures were different between the age groups (p = 0.022), with the older age group presenting three times more frequent with ligament pathology events (5.5%/2%) and less frequent with bony problems (11%/20.5%) than athletes of the younger age group. The injured area differed between the sexes (p = 0.005), with males having fewer spine injury-events (25.5%/34%) but more upper extremity injuries (18%/9%) than females. Regression analysis showed statistically significant influence for BMI (p = 0.002) and age (p = 0.015) on structure, whereas the area was significantly influenced by sex (p = 0.005).
Conclusion: Events of soft-tissue overuse injuries are the most common reasons resulting in orthopedic presentations of adolescent elite athletes. Mostly, the lower extremity and the spine are affected, while sex and age characteristics on affected area and structure must be considered. Therefore, prevention strategies addressing the injury-event profiles should already be implemented in early adolescence taking age, sex as well as injury entity into account.
Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N = 44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 μm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care.
Background: Stratified care has the potential to be efficient in addressing the physical and psychosocial components of low back pain (LBP) and optimise treatment outcomes essential in low-income countries. This study aimed to investigate the perceptions of physiotherapists and patients in Nigeria towards stratified care for the treatment of LBP, exploring barriers and enablers to implementation.
Methods: A qualitative design with semistructured individual telephone interviews for physiotherapists and patients with LBP comprising research evidence and information on stratified care was adopted. Preceding the interviews, patients completed the Subgroups for Targeted Treatment tool. The interviews were recorded, transcribed and analysed following grounded theory methodology.
Results: Twelve physiotherapists and 13 patients with LBP participated in the study (11 female, mean age 42.8 (SD 11.47) years). Seven key categories emerged: recognising the need for change, acceptance of innovation, resistance to change, adapting practice, patient’s learning journey, trusting the therapist and needing conviction. Physiotherapists perceived stratified care to be a familiar approach based on their background training. The prevalent treatment tradition and the patient expectations were seen as major barriers to implementation of stratified care by the physiotherapists. Patients see themselves as more informed than therapists realise, yet they need conviction through communication and education to cooperate with their therapist using this approach. Viable facilitators were also identified as patients’ trust in the physiotherapist and adaptations in terms of training and modification of the approach to enhance its use.
Conclusion: Key barriers identified are the patients’ treatment expectations and physiotherapists’ adherence to the tradition of practice. Physiotherapists might facilitate implementation of the stratified care by communication, hierarchical implementation and utilisation of patients’ trust. Possibilities to develop a consensus on key strategies to overcome barriers and on utilisation of facilitators should be tested in future research.
Stratified care for low back pain (LBP) has been shown to be clinically- and cost-effective in the UK, but its transferability to the German healthcare system is unknown. This study explores LBP patients’ perspectives regarding future implementation of stratified care, through in-depth interviews (n = 12). The STarT-Back-Tool was completed by participants prior to interviews. Interview data were analysed using Grounded Theory. The overarching theme identified from the data was ‘treatment-success’, with subthemes of ‘assessment and treatment planning’, ‘acceptance of the questionnaire’ and ‘contextual factors’. Patients identified the underlying cause of pain as being of great importance (whereas STarT-Back allocates treatment based on prognosis). The integration of the STarT-Back-Tool in consultations was considered helpful as long as it does not disrupt the therapeutic relationship, and was acceptable if tool results are handled confidentially. Results indicate that for patients to find STarT-Back acceptable, the shift from a focus on identifying a cause of pain and subsequent diagnosis, to prediction-orientated treatment planning, must be made clear. Patient ‘buy in’ is important for successful uptake of clinical interventions, and findings can help to inform future strategies for implementing STarT-Back in the Germany, as well as having potential implications for transferability to other similar healthcare systems.
This paper describes the project “Visual Knowledge Communication”, a joint project that started recently. The partners are psychologists and computer scientists from four universities of the German state Rhineland-Palatinate. The starting point for the project was the fact that visualizations have attracted considerable interest in psychology as well as computer science within the last years. However, psychologists and computer scientists pursued their investigations independently from each other in the past. This project has as its main goal the support and fostering of cooperation between psychologists and computer scientists in several visualization research projects.
The paper sketches the overall project. It then discusses in more detail the authors' subproject which deals with a peer review process for animations developed by students. The basic ideas, the main goals, and the project plan are described.
This paper is a work-in-progress report. Therefore, it does not contain any results.
This scientific paper aims to collect and analyze various digital technologies connected to pharmacies and Health 4.0. Thus, the goal is to give basic recommendations for actions for pharmacies to remain successful businesses in the digital future of healthcare. While the total health sector is growing continuously, the total number of pharmacies is shrinking. To be able to face the competitive pressure on the pharmaceutical market, pharmacies have to integrate more efficient digital technologies to be able to increase customers’ experience. Hence, the acceptance and attitude of the German society towards digital health solutions are examined using a short survey and a precise questionnaire. After a detailed analysis of the survey results and the questionnaire answered by a pharmacist, specific digital methods and technologies which make sense for pharmacies can be elaborated. As the future of pharmacies is still quite unexplored, while the health market is shifting to more efficient digital solutions, pharmacies have to adapt to current developments fast. Therefore, this paper can serve as a guideline for pharmacies in the rapid changes toward more digital markets.
Background: The STarT-Back-Approach (STarT: Subgroups for Targeted Treatment) was developed in the UK and has demonstrated clinical and cost effectiveness. Based on the results of a brief questionnaire, patients with low back pain are stratified into three treatment groups. Since the organisation of physiotherapy differs between Germany and the UK, the aim of this study is to explore German physiotherapists’ views and perceptions about implementing the STarT-Back-Approach.
Methods: Three two-hour think-tank workshops with physiotherapists were conducted. Focus groups, using a semi-structured interview guideline, followed a presentation of the STarT-Back-Approach, with discussions audio recorded, transcribed and qualitatively analysed using content analysis.
Results: Nineteen physiotherapists participated (15 female, mean age 41.2 (SD 8.6) years). Three main themes emerged, each with multiple subthemes: 1) the intervention (15 subthemes), 2) the healthcare context (26 subthemes) and 3) individual characteristics (8 subthemes). Therapists’ perceptions of the extent to which the STarT-Back intervention would require changes to their normal clinical practice varied considerably. They felt that within their current healthcare context, there were significant financial disincentives that would discourage German physiotherapists from providing the STarT-Back treatment pathways, such as the early discharge of low-risk patients with supported self-management materials. They also discussed the need for appropriate standardised graduate and post-graduate skills training for German physiotherapists to treat high-risk patients with a combined physical and psychological approach (e.g., communication skills).
Conclusions: Whilst many German physiotherapists are positive about the STarT-Back-Approach, there are a number of substantial barriers to implementing the matched treatment pathways in Germany. These include financial disincentives within the healthcare system to early discharge of low-risk patients. Therapists also highlighted the need for solutions in respect of scalable physiotherapy training to gain skills in combined physical and psychological approaches.
Context: In the framework of studying cosmic microwave background polarization and characterizing its Galactic foregrounds, the angular power spectrum analysis of the thermal dust polarization map has led to intriguing evidence of an E/B asymmetry and a positive TE correlation. The interpretation of these observations is the subject of theoretical and simulation-driven studies in which the correlation between the density structure of the interstellar medium (ISM) and the magnetic field appears to be a key aspect. In this context, and when the magnetized ISM structures are modeled in three dimensions, dust clouds are generally considered to be filamentary structures only, but both filamentary and sheet-like shapes are supported by observational and theoretical evidence.
Aims: We aim to study the influence of the cloud shape and its connection to the local magnetic field, as well as the influence from the viewing angle, on the angular power spectra measured on thermal dust polarization maps; we specifically focus on the dependence of the E/B power asymmetry and TE correlation.
Methods: To this end, we simulated realistic interstellar clouds with both filament-like and sheet-like shapes using the software ASTERION, which also allowed us to generate synthetic maps of thermal dust polarized emission with an area of 400 square degrees. Then, we computed their polarization power spectra in the multipole range ℓ ϵ [100, 500] and focused on the E/B power asymmetry, quantified through the ℛEB ratio, and the correlation coefficient rTE between Τ and Ε modes. We quantified the dependence of ℛEB and rTE values on the offset angle (between the longest cloud axis and local magnetic field lines) and inclination angle (between the line of sight and the magnetic field) for both types of cloud shapes, either embedded in a regular magnetic field or coupled to a nonregular field to mimic turbulence.
Results: We find that both types of cloud shapes cover the same regions of the (ℛEB, rTE) parameter space. The dependence on the inclination and offset angles is similar for both shapes, although sheet-like structures generally show larger scatter than filamentary structures. In addition to the known dependence on the offset angle, we find a strong dependence of ℛEB and rTE on the inclination angle.
Conclusions: The very fact that filament-like and sheet-like structures may lead to polarization power spectra with similar (ℛEB,rTE) values complicates their interpretation. We argue that interpreting them solely in terms of filament characteristics is risky, and in future analyses, this degeneracy should be accounted for, as should the connection to the magnetic field geometry. Our results based on maps of 400 square degrees clarify that the overall geometrical arrangement of the magnetized ISM surrounding the observer leaves its marks on polarization power spectra.
The purpose of this article is to evaluate optimal expected utility risk measures (OEU) in a risk-constrained portfolio optimization context where the expected portfolio return is maximized. We compare the portfolio optimization with OEU constraint to a portfolio selection model using value at risk as constraint. The former is a coherent risk measure for utility functions with constant relative risk aversion and allows individual specifications to the investor’s risk attitude and time preference. In a case study with three indices, we investigate how these theoretical differences influence the performance of the portfolio selection strategies. A copula approach with univariate ARMA-GARCH models is used in a rolling forecast to simulate monthly future returns and calculate the derived measures for the optimization. The results of this study illustrate that both optimization strategies perform considerably better than an equally weighted portfolio and a buy and hold portfolio. Moreover, our results illustrate that portfolio optimization with OEU constraint experiences individualized effects, e.g., less risk-averse investors lose more portfolio value in the financial crises but outperform their more risk-averse counterparts in bull markets.
Water is crucial for socio-economic development and healthy ecosystems. With the actual population growth and in view of future water scarcity, development calls for improved sectorial allocation of groundwater and surface water for domestic, agricultural and industrial use. Instead of intensifying the pressure on water resources, leading to conflicts among users and excessive pressure on the environment, sewage effluents, after pre-treatment, provide an alternative nutrient-rich water source for agriculture in the vicinity of cities. Water scarcity often occurs in arid and semiarid regions affected by droughts and large climate variability and where the choice of crop to be grown is limited by the environmental factors. Jatropha has been introduced as a potential renewable energy resource since it is claimed to be drought resistant and can be grown on marginal sites. Sewage effluents provide a source for water and nutrients for cultivating jatropha, a combined plant production/effluent treatment system. Nevertheless, use of sewage effluents for irrigation in arid climates carries the risk of salinization. Thus, potential irrigation with sewage effluents needs to consider both the water requirement of the crop and those needed for controlling salinity build-up in the top soil. Using data from a case study in Southern Morocco, irrigation requirements were calculated using CROPWAT 8.0. We present here crop evapotranspiration during the growing period, required irrigation, the resulting nutrient input and the related risk of salinization from the irrigation of jatropha with sewage effluent.
Background: In recent years, the volume of medical knowledge and health data has increased rapidly. For example, the increased availability of electronic health records (EHRs) provides accurate, up-to-date, and complete information about patients at the point of care and enables medical staff to have quick access to patient records for more coordinated and efficient care. With this increase in knowledge, the complexity of accurate, evidence-based medicine tends to grow all the time. Health care workers must deal with an increasing amount of data and documentation. Meanwhile, relevant patient data are frequently overshadowed by a layer of less relevant data, causing medical staff to often miss important values or abnormal trends and their importance to the progression of the patient’s case.
Objective: The goal of this work is to analyze the current laboratory results for patients in the intensive care unit (ICU) and classify which of these lab values could be abnormal the next time the test is done. Detecting near-future abnormalities can be useful to support clinicians in their decision-making process in the ICU by drawing their attention to the important values and focus on future lab testing, saving them both time and money. Additionally, it will give doctors more time to spend with patients, rather than skimming through a long list of lab values.
Methods: We used Structured Query Language to extract 25 lab values for mechanically ventilated patients in the ICU from the MIMIC-III and eICU data sets. Additionally, we applied time-windowed sampling and holding, and a support vector machine to fill in the missing values in the sparse time series, as well as the Tukey range to detect and delete anomalies. Then, we used the data to train 4 deep learning models for time series classification, as well as a gradient boosting–based algorithm and compared their performance on both data sets.
Results: The models tested in this work (deep neural networks and gradient boosting), combined with the preprocessing pipeline, achieved an accuracy of at least 80% on the multilabel classification task. Moreover, the model based on the multiple convolutional neural network outperformed the other algorithms on both data sets, with the accuracy exceeding 89%.
Conclusions: In this work, we show that using machine learning and deep neural networks to predict near-future abnormalities in lab values can achieve satisfactory results. Our system was trained, validated, and tested on 2 well-known data sets to ensure that our system bridged the reality gap as much as possible. Finally, the model can be used in combination with our preprocessing pipeline on real-life EHRs to improve patients’ diagnosis and treatment.
For a detailed discussion of process mining, the objective of this paper is the analysis of the successful implementation of process mining in the practical fields of supply chain management. The research comprises the investigation of use cases in companies that are already actively using process mining.
Purpose: This research aims to highlight the applicability of process mining in the supply chain management business field.
Research Methodology: In order to examine the applicability of process mining in supply chain management a research study was conducted among experts in this business field. Further, theoretical findings were compared to the results and evaluated.
Results: Process Mining can be applied very well in the SCM area. The advantages that arise primarily reflect significant potential benefits and improved process throughput times. The information that can be gained from the operational areas supported by process mining is suitable for reliable decisions, both in the tactical and strategic areas.
Limitations: The results on the application of process mining show a certain generalization and have to be adapted and adjusted to the respective application case.
Contribution: This study is useful, especially for the purchasing and logistics business area.
Background: Stratified care is an up-to-date treatment approach suggested for patients with back pain in several guidelines. A comprehensively studied stratification instrument is the STarT Back Tool (SBT). It was developed to stratify patients with back pain into three subgroups, according to their risk of persistent disabling symptoms. The primary aim was to analyse the disability differences in patients with back pain 12 months after inclusion according to the subgroups determined at baseline using the German version of the SBT (STarT-G). Moreover, the potential to improve prognosis for disability by adding further predictor variables, an analysis for differences in pain intensity according to the STarT-Classification, and discriminative ability were investigated.
Methods: Data from the control group of a randomized controlled trial were analysed. Trial participants were members of a private medical insurance with a minimum age of 18 and indicated as having persistent back pain. Measurements were made for the risk of back pain chronification using the STarT-G, disability (as primary outcome) and back pain intensity with the Chronic Pain Grade Scale (CPGS), health-related quality of life with the SF-12, psychological distress with the Patient Health Questionnaire-4 (PHQ-4) and physical activity. Analysis of variance (ANOVA), multiple linear regression, and area under the curve (AUC) analysis were conducted.
Results: The mean age of the 294 participants was 53.5 (SD 8.7) years, and 38% were female. The ANOVA for disability and pain showed significant differences (p < 0.01) among the risk groups at 12 months. Post hoc Tukey tests revealed significant differences among all three risk groups for every comparison for both outcomes. AUC for STarT-G’s ability to discriminate reference standard ‘cases’ for chronic pain status at 12 months was 0.79. A prognostic model including the STarT-Classification, the variables global health, and disability at baseline explained 45% of the variance in disability at 12 months.
Conclusions: Disability differences in patients with back pain after a period of 12 months are in accordance with the subgroups determined using the STarT-G at baseline. Results should be confirmed in a study developed with the primary aim to investigate those differences.
For the assessment of human reaction time, a test environment was developed. This system consists of an embedded device with organic light-emitting diode (OLED) displays with push buttons for the combined presentation of visual stimulation and registration of the haptic human reaction. The test leader can define the test sequence with the aid of a graphical user interface (GUI) on a personal computer (PC). The validation of the system was proved by measuring the latency times of the whole system, which are conditioned by the specific hard- and software constellation. Through the investigation of the display’s light radiation by a photodiode and the recorded current consumption, latency times and their variance were specified. In the fastest mode the system can reach an error limit of 60 μs.
Radar systems for contactless vital sign monitoring are well known and an actual object of research. These radar-based sensors could be used for monitoring of elderly people in their homes but also for detecting the activity of prisoners and to control electrical devices (light, audio, etc.) in smart living environments. Mostly these sensors are foreseen to be mounted on the ceiling in the middle of a room. In retirement homes the rooms are mostly rectangular and of standardized size. Furniture like beds and seating are found at the borders or the corners of the room. As the propagation path from the center of the room ceiling to the borders and corners of a room is 1.4 and 1.7 time longer the power reflected by people located there is 6 or even 10 dB lower than if located in the center of the room. Furthermore classical antennas in microstrip technology are strengthening radiation in broadside direction. Radar systems with only one single planar antenna must be mounted horizontally aligned when measuring in all directions. Thus an antenna pattern which is increasing radiation in the room corners and borders for compensation of free space loss is needed. In this contribution a specification of classical room sizes in retirement homes are given. A method for shaping the antenna gain in the E-plane by an one-dimensional series-fed traveling wave patch array and in the H-plane by an antenna feeding network for improvement of people detection in the room borders and corners is presented for a 24 GHz digital beamforming (DBF) radar system. The feeding network is a parallel-fed power divider for microstrip patch antennas at 24 GHz. Both approaches are explained in theory. The design parameters and the layout of the antennas are given. The simulation of the antenna arrays are executed with CST MWS. Simulations and measurements of the proposed antennas are compared to each other. Both antennas are used for the transmit and the receive channel either. The sensor topology of the radar system is explained. Furthermore the measurement results of the protoype are presented and discussed.
Radar target simulator with complex-valued delay line modeling based on standard radar components
(2018)
With increasing radar activities in the automotive, industrial and private sector, there is a need to test radar sensors in their environment. A radar target simulator can help testing radar systems repeatably. In this paper, the authors present a concept of low-cost hardware for radar target simulation. The theoretical foundations are derived and analyzed. An implementation of a demonstrator operating in the 24 GHz ISM band is shown for which the dynamical range simulation was implemented in a FPGA with fast sampling ADCs and DACs. By using a FIR filtering approach a fine discretization of the range could be reached which will furthermore allow an inherent and automatic Doppler simulation by moving the target.
Reasons and potential solution approaches for the shortage of nursing staff in German hospitals
(2021)
The aim of this scientific paper was to find out the reasons for the shortage of nursing staff in German hospitals and to provide potential solution approaches for this shortage. Over the last years, the shortage of nursing staff has become a more and more important topic in the news: Not only due to the increasing amount of missing nurses, but also due to the ageing population in Germany, which leads to an increasing amount of patients in German hospitals. To reach this aim two surveys were done, of which one was for nursing staff only and the other one was for people from all occupational groups with the intention of creating comparative values. The surveys were done from March to April 2019 and were analysed afterwards. After a detailed analysis of the survey results, it can be summarized that the reasons for the shortage of nursing staff in German hospitals are very diverse: Starting with a weak salary, improvable working conditions – for example the shift work and the high amount of physical and psychological stress -, a difficult compatibility of family and job as well as the unattractive image of the job as a nurse in the society. It can be concluded that the solution for the shortage of nursing staff is very difficult. The future will show whether the governmental support will help to make the job as a nurse more attractive – not only for the current nurses, but also for potential future nurses.