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In this paper, we evaluate the application of Bayesian Optimization (BO) to discrete event simulation (DES) models. In a first step, we create a simple model, for which we know the optimal set of parameter values in advance. We implement the model in SimPy, a framework for DES written in Python. We then interpret the simulation model as a black box function subject to optimization. We show that it is possible to find the optimal set of parameter values using the open source library GPyOpt. To enhance our evaluation, we create a second and more complex model. To better handle the complexity of the model, and to add a visual component, we build the second model in Simio, a commercial off-the-shelf simulation modeling tool. To apply BO to a model in Simio, we use the Simio API to write an extension for optimization plug-ins. This extension encapsulates the logic of the BO algorithm, which we deployed as a web service in the cloud.
The fact that simulation models are black box functions with regard to their behavior and the influence of their input parameters makes them an apparent candidate for Bayesian Optimization (BO). Simulation models are multivariable and stochastic, and their behavior is to a large extent unpredictable. In particular, we do not know for sure which input parameters to adjust to maximize (or minimize) the model’s outcome. In addition, the complex models can take a substantial amount of time to run.
Bayesian Optimization is a sequential and self-learning algorithm to optimize black box functions similar to as we find them in simulation models: they contain a set of parameters for which we want to identify the optimal set, they are expensive to evaluate, and they exhibit stochastic noise. BO has proven to efficiently optimize black box functions from varius disciplines. Among those, and most notably, it is successfully applied in machine learning algorithms to optimize hyperparameters.
Background:
The evaluation of somatosensory dysfunction is important for diagnostics and may also have implications for prognosis and management. The current standard to evaluate somatosensory dysfunction is quantitative sensory testing (QST), which is expensive and time consuming. This study describes a low-cost and time-efficient clinical sensory test battery (CST), and evaluates its concurrent validity compared to QST.
Method: Three patient cohorts with carpal tunnel syndrome (CTS, n=86), non-specific neck and arm pain (NSNAP, n=40) and lumbar radicular pain/radiculopathy (LR n=26) were included. The CST consisted of 13 tests, each corresponding to a QST parameter and evaluating a broad spectrum of sensory functions using mechanical and thermal detection and pain thresholds and testing both loss and gain of function. Agreement rate, significance and strength of correlation between CST and QST were calculated.
Results: Several CST parameters (cold and warm detection, cold pain, mechanical detection, mechanical pain for loss of function, pressure pain) were significantly correlated with QST, with a majority demonstrating >60% agreement rates and weak to relatively strong correlations. However, agreement varied among cohorts. Gain of function parameters showed stronger correlation in the CTS and NSNAP cohort, whereas loss of function parameters performed better in the LR cohort. Other CST parameters (vibration detection, heat pain, mechanical pain for gain of function, windup ratio) did not significantly correlate with QST.
Conclusion: Some, but not all tests in the CST battery can detect somatosensory dysfunction as determined with QST. The CST battery may perform better when the somatosensory phenotype is more pronounced.
Purpose
Attracting skilled students is an important aim of many cities in a knowledge-based society. This paper focuses on urban factors of attractiveness from a student's perspective and analyses their influence on locational choices of students. The criteria found were also used to evaluate how the City of Osnabrück, Germany, is rated in terms of these criteria and to reveal the greatest discrepancies.
Design / Methodology / Approach
The paper is based on a multi-level empirical research concept, including qualitative and quantitative approaches. A survey of 2,300 students was conducted in Osnabrück on the basis of focus group discussions with students and interviews with various experts such as a neighbourhood manager, an urban planner, a district mayor, a college president, a real estate manager.
Originality/value
To date, little research has been undertaken to empirically examine the specific requirements that German students look for in a place to live and study. According to the author’s present state of knowledge (January 2018), a comparable study has not been done.
The main contribution of this paper is the empirical analysis of what makes cities attractive to students. In contrast to the findings of Richard Florida about the Creative Class, the cleanliness of a city, beautiful city scenery, and attractive apartments are more important to students than cultural offers, interesting job opportunities, or a multicultural population.
Practical Implications
Insights from the empirical survey can both help to analyse important factors in students' decision-making process and provide possible measures that the city stakeholders can take.
Keywords
1. Knowledge-based urban development
2. Mobility decisions by students and skilled professionals
3. Location factors
4. Place branding
Proposed paper: Academic Research Paper
Background:
Contact tracing apps are potentially useful tools for supporting national COVID-19 containment strategies. Various national apps with different technical design features have been commissioned and issued by governments worldwide.
Objective:
Our goal was to develop and propose an item set that was suitable for describing and monitoring nationally issued COVID-19 contact tracing apps. This item set could provide a framework for describing the key technical features of such apps and monitoring their use based on widely available information.
Methods:
We used an open-source intelligence approach (OSINT) to access a multitude of publicly available sources and collect data and information regarding the development and use of contact tracing apps in different countries over several months (from June 2020 to January 2021). The collected documents were then iteratively analyzed via content analysis methods. During this process, an initial set of subject areas were refined into categories for evaluation (ie, coherent topics), which were then examined for individual features. These features were paraphrased as items in the form of questions and applied to information materials from a sample of countries (ie, Brazil, China, Finland, France, Germany, Italy, Singapore, South Korea, Spain, and the United Kingdom [England and Wales]). This sample was purposefully selected; our intention was to include the apps of different countries from around the world and to propose a valid item set that can be relatively easily applied by using an OSINT approach.
Results:
Our OSINT approach and subsequent analysis of the collected documents resulted in the definition of the following five main categories and associated subcategories: (1) background information (open-source code, public information, and collaborators); (2) purpose and workflow (secondary data use and warning process design); (3) technical information (protocol, tracing technology, exposure notification system, and interoperability); (4) privacy protection (the entity of trust and anonymity); and (5) availability and use (release date and the number of downloads). Based on this structure, a set of items that constituted the evaluation framework were specified. The application of these items to the 10 selected countries revealed differences, especially with regard to the centralization of the entity of trust and the overall transparency of the apps’ technical makeup.
Conclusions:
We provide a set of criteria for monitoring and evaluating COVID-19 tracing apps that can be easily applied to publicly issued information. The application of these criteria might help governments to identify design features that promote the successful, widespread adoption of COVID-19 tracing apps among target populations and across national boundaries.
This paper presents an optimized algorithm for estimating static and dynamic gait parameters. We use a marker- and contact-less motion capture system that identifies 20 joints of a person walking along a corridor.
Based on the proposed gait cycle detection basic metrics as walking frequency, step/stride length, and support phases are estimated automatically. Applying a rigid body model, we are capable to calculate static and dynamic gait stability metrics. We conclude with initial results of a clinical study evaluating orthopaedic technical support.
This qualitative study focuses on assessing the “future readiness” capacity of three Peruvian Higher Education Institutions under the HEInnovate framework. The main question guiding this research is: To what extent can Peruvian universities be considered entrepreneurial and ready
for tackling the Challenges of the Future? The Challenges of the Future are understood as the challenges generated by concepts such as The Future of Work, The Global Skills Gap, Employability and unexpected and destabilizing risks of the environment, such as COVID-19.
Universities were studied based on 4 research sub-questions: 1) How do Peruvian HEIs rate in Entrepreneurial Capacity according to the HEInnovate framework? 2) What are the factors supporting or preventing Peruvian HEIs to accomplish their entrepreneurial potential? 3) What efforts are Peruvian HEIs making for developing 21st century skills, accomplishing Digital Transformation, and enhancing their students Employability? and 4) What measures could Peruvian HEIs take in order to maximize their entrepreneurial and future-proof potential? The research methodology used was mixed, applying first a quantitative assessment, and then
complementing the results with in-depth interviews. After presenting the conclusions, recommendations for policy action and for university management are given.
Relationship of QST measures between low back and leg sites in people with radicular leg pain
(2019)
Background and Aims
Clinicians and researchers often rely on altered neurological integrity tests in the leg to identify radicular pain, however neurological integrity is often not tested in the low back region even in the presence of pain in this region. There have been suggestions that the low back pain itself could be neuropathic in nature in some patients (Baron et al., 2016). This study aims to explore the relationship between quantitative sensory testing (QST) measures in the leg and low back in participants with radicular leg pain to consider if sensory testing should be performed in both areas in clinical practice.
Methods
13 participants (mean age 48.2 SD 13.8, gender (female) 8) with radicular leg pain were recruited from National Health Service spinal clinics in the UK. After assessment with the clinician, a full QST profile was taken from each participant’s affected leg and low back. Z scores were calculated using data from age matched healthy controls. Correlations using Pearson’s if the data was normally distributed or Kendall’s Tau-b if not, were undertaken between QST scores of the low back and leg. Paired t tests or Mann Whitney tests were performed to assess differences in QST scores between the leg and low back regions.
Results
There were no significant correlations (P>0.05) in any of the QST measures between the leg and the low back regions. However, only vibration detection threshold measures showed statistically significant differences between the leg and low back (p<0.001), with the low back region showing greater loss of function (mean -2.84) than the leg (mean -0.61).
Conclusions
Significantly lower vibration thresholds were found in the back compared to the leg. This may suggest some alteration in posterior primary ramus large diameter afferent nerve function, and indicate that the low back pain itself may indeed have a neuropathic component. Our findings suggest that sensory testing of the lumbar spine may be advisable in this group of individuals. The small sample size means that these results must be taken with some caution, however these results warrant further investigation in people with radicular leg pain.
Background:
Midwifery care in Germany is a legal right for every woman (SGB V). Midwives work employed or freelance in hospitals or in community services, providing maternal care from pregnancy until the end of breastfeeding (Sayn-Wittgenstein 2007). Increasingly, a shortage of midwifery care has been observed, forcing hospitals to understaff or to close their birth units, leaving women and their families without care (Sander et al. 2018). At the same time, birth rates are rising, thus leading to an increasing demand of midwifery care (Destatis 2019). As off today there is no central register for midwives across Germany’s 16 states. Therefor the exact number of registered midwives as well as the scope of services provided by midwives are not known (Niedersächsisches Landesgesundheitsamt 2019). Given the present situation, it seems to be imperative to establish effective midwifery workforce planning.
The aim of this poster is to identify already existing health workforce planning approaches and to determine the extent to which those can be transferred to the German system of midwifery care.
Methods:
Health workforce planning approaches, already being used on a national and international level, have been analysed, focusing their applicability to midwifery services in Germany.
Results:
Particular elements of the workforce planning approaches already being used in Germany for registered physicians seem to be adoptable. However, they need to be adjusted and enhanced to ensure the characteristics of midwifery in the German public health services. Internationally used approaches are not readily transferable due to systemic differences in health care systems.
Conclusions:
The development of new specific workforce and service planning approaches for midwifery care in Germany is crucial to meet present and future needs of women and their families during the childbirth period.
Management of agricultural processes is often troubled by disconnections and data transfer failures. Limited cellular network coverage may prevent information exchange between mobile process participants.
The research projects KOMOBAR and ISOCom designed, implemented und field-tested a delay tolerant platform for robust communication in rural areas and challenging environments. An adaptable combination of infrastructure-based cellular networks and infrastructure-free multihop ad hoc communication (WLAN) leads to a variety of new communication opportunities. Temporal storage and forwarding of data on mobile farm machinery as well as dynamic platform configurations during process runtime strongly enhance reliability and robustness of data transfers.