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Data and Information Science: Book of Abstracts at BOBCATSSS 2022 Hybrid Conference, 23rd - 25th of May 2022, Debrecen.
This year marks the 30th anniversary of the BOBCATSSS. The BOBCATSSS is an international, annual symposium designed for librarians and information professionals in a rapidly changing environment. Over the past 30 years, the conference has included exciting topics, great venues, interested guests and engaging presenters.
This year we would like to introduce the topics of the many papers presented in the Book of Abstracts for the first time in presence at the University of Debrecen and hybrid. The Book of Abstracts provides an overview of all presentations given at BOBCATSSS. Presentations are listed in alphabetical order by title and include speeches, Pecha Kuchas, posters and workshops.
The theme of BOBCATSSS is Data and Information Science. Data and information are the basis for decisions and processes in business, politics and science. Particularly important in the current era of digital transformation. This is exactly where this year's subthemes come in. They deal with data science, openness as well as institutional roles.
[Geld]
(2002)
In the last years generative models have gained large public attention due to their high level of quality in generated images. In short, generative models learn a distribution from a finite number of samples and are able then to generate infinite other samples. This can be applied to image data. In the past generative models have not been able to generate realistic images, but nowadays the results are almost indistinguishable from real images.
This work provides a comparative study of three generative models: Variational Autoencoder (VAE), Generative Adversarial Network (GAN) and Diffusion Models (DM). The goal is not to provide a definitive ranking indicating which one of them is the best, but to qualitatively and where possible quantitively decide which model is good with respect to a given criterion. Such criteria include realism, generalization and diversity, sampling, training difficulty, parameter efficiency, interpolating and inpainting capabilities, semantic editing as well as implementation difficulty. After a brief introduction of how each model works on the inside, they are compared against each other. The provided images help to see the differences among the models with respect to each criterion.
To give a short outlook on the results of the comparison of the three models, DMs generate most realistic images. They seem to generalize best and have a high variation among the generated images. However, they are based on an iterative process, which makes them the slowest of the three models in terms of sample generation time. On the other hand, GANs and VAEs generate their samples using one single forward-pass. The images generated by GANs are comparable to the DM and the images from VAEs are blurry, which makes them less desirable in comparison to GANs or DMs. However, both the VAE and the GAN, stand out from the DMs with respect to the interpolations and semantic editing, as they have a latent space, which makes space-walks possible and the changes are not as chaotic as in the case of DMs. Furthermore, concept-vectors can be found, which transform a given image along a given feature while leaving other features and structures mostly unchanged, which is difficult to archive with DMs.
As noted by Roman poet Virgil already more than 2,000 years ago: “The greatest wealth is health.”. Without health, there is no happiness, no peace, and no success according to the Reflections Recovery Center from Arizona, United States (USA, U.S.). The goal of the Healthy People 2020-project (HP2020), which is led by the Office of Disease Prevention and Health Promotion (ODPHP), was to “promote quality life, healthy development, and health behaviors across all life stages” among the U.S. population. HP2020 measures progress by using so-called Leading Health Indicators (LHI), reliable data sources, baseline values as well as targets for LHI-individual improvements for every measurable objective to be achieved by 2020 and each following decade. In the further course, these values were compared to student populations from the U.S., Germany, and Poland. The goal of this master's thesis was to obtain more data on international health, particularly among student populations. For the statistical analysis, data were obtained from an online survey that was distributed to students in at least one university in each of the three countries. In total, data from 380 students were analyzed in terms of HP2020 goal attainment. To determine if statistically significant differences were present, the z-test was used. The biggest differences emerged on the following topics: access to healthcare, environmental quality, obesity as well as reproductive and sexual health.
The shift towards RES introduces challenges related to power system stability due to the characteristics of inverter-based resources (IBRs) and the intermittent nature of renewable resources. This paper addresses these challenges by conducting comprehensive time and frequency simulations on the IEEE two-area benchmark power system with detailed type 4 wind turbine generators (WTGs), including turbines, generators, converters, filters, and controllers. The simulations analyse small-signal and transient stability, considering variations in active and reactive power, short-circuit events, and wind variations. Metrics such as rate of change of frequency (RoCoF), frequency nadir, percentage of frequency variation, and probability density function (PDF) are used to evaluate the system performance. The findings emphasise the importance of including detailed models of RES in stability analyses and demonstrate the impact of RES penetration on power system dynamics. This study contributes to a deeper understanding of RES integration challenges and provides insights for ensuring the reliable and secure operation of power systems in the presence of high levels of RES penetration.
Objectives: To assess the relation between the number of clinical trials conducted and respective new drug approvals in India and South Africa.
Design: Construction and analysis of a comprehensive database of completed randomised controlled clinical trials based on clinicaltrials.gov from 1 January 2005 to 31 December 2010 and drug approval data from 2006 until 2013 for India and South Africa.
Setting: USA, the EU, India and South Africa.
Main outcome measures: Percentage of completed randomised clinical trials for an Investigational Medicinal Product (IMP) leading to new drug approval in India and South Africa.
Results: A total of 622 eligible randomised controlled trials were identified as per search criteria for India and South Africa. Clustering them for the same sponsor and the same Investigational New Drug (IND) resulted in 453 eligible trials, that is, 224 for India and 229 for South Africa. The distribution of the market application approvals between the EU/USA as well as India and South Africa revealed that out of clinical trials with the participation of test centres in India and/or South Africa, 39.6% (India) clinical trials and 60.1% (South Africa) clinical trials led to market authorisation in the EU/USA without a New Drug Application (NDA) approval in India or South Africa.
Conclusions: Despite an increase in clinical trial activities, there is a clear gap between the number of trials conducted and market availability of these new drugs in India and South Africa. Drug regulatory authorities, investigators, institutional review boards and patient groups should direct their efforts to ensuring availability of new drugs in the market that have been tested and researched on their population.
BACKGROUND: Even though physician rating websites (PRWs) have been gaining in importance in both practice and research, little evidence is available on the association of patients' online ratings with the quality of care of physicians. It thus remains unclear whether patients should rely on these ratings when selecting a physician. The objective of this study was to measure the association between online ratings and structural and quality of care measures for 65 physician practices from the German Integrated Health Care Network "Quality and Efficiency" (QuE). METHODS: Online reviews from two German PRWs were included which covered a three-year period (2011 to 2013) and included 1179 and 991 ratings, respectively. Information for 65 QuE practices was obtained for the year 2012 and included 21 measures related to structural information (N = 6), process quality (N = 10), intermediate outcomes (N = 2), patient satisfaction (N = 1), and costs (N = 2). The Spearman rank coefficient of correlation was applied to measure the association between ratings and practice-related information. RESULTS: Patient satisfaction results from offline surveys and the patients per doctor ratio in a practice were shown to be significantly associated with online ratings on both PRWs. For one PRW, additional significant associations could be shown between online ratings and cost-related measures for medication, preventative examinations, and one diabetes type 2-related intermediate outcome measure. There again, results from the second PRW showed significant associations with the age of the physicians and the number of patients per practice, four process-related quality measures for diabetes type 2 and asthma, and one cost-related measure for medication. CONCLUSIONS: Several significant associations were found which varied between the PRWs. Patients interested in the satisfaction of other patients with a physician might select a physician on the basis of online ratings. Even though our results indicate associations with some diabetes and asthma measures, but not with coronary heart disease measures, there is still insufficient evidence to draw strong conclusions. The limited number of practices in our study may have weakened our findings.
A descriptive cross-sectional study of cholera at Kakuma and Kalobeyei refugee camps, Kenya in 2018
(2020)
Introduction: cholera is a significant public health concern among displaced populations. Oral cholera vaccines are safe and can effectively be used as an adjunct to prevent cholera in settings with limited access to water and sanitation. Results from this study can inform future consideration for cholera vaccination at Kakuma and Kalobeyei.
Methods: a descriptive cross-sectional study of cholera cases at Kakuma refugee camp and Kalobeyei integrated settlement was carried out between May 2017 to May 2018 (one year). Data were extracted from the medical records and line lists at the cholera treatment centres.
Results: the results found 125 clinically suspected and confirmed cholera cases and one related death (CFR 0.8%). The cumulative incidence of all cases was 0.67 (95% CI=0.56-0.80) cases/1000 persons. Incidence of cholera was higher in children under the age of five 0.94(95% CI=0.63-1.36) cases/1000 persons. Children aged <5 years showed 51% increased risk of cholera compared to those aged ≥5 years (RR=1.51; 95% CI=1.00-2.31, p=0.051). Individuals from the Democratic Republic of Congo had nearly 9-fold risk of reporting cholera (RR=8.62; 95% CI=2.55-37.11, p<0.001) while individuals from South Sudan reported 7 times risk of cholera case compared to those from Somalia (RR=7.39; 95% CI=2.78-27.73, p<0.001).
Conclusion: in addition to the improvement of water, sanitation and hygiene (WaSH), vaccination could be implemented as a short-medium term measure of preventing cholera outbreaks. Age, country of origin and settlement independently predicted the risk of cholera.
In this paper, we consider the route coordination problem in emergency evacuation of large smart buildings. The building evacuation time is crucial in saving lives in emergency situations caused by imminent natural or man-made threats and disasters. Conventional approaches to evacuation route coordination are static and predefined. They rely on evacuation plans present only at a limited number of building locations and possibly a trained evacuation personnel to resolve unexpected contingencies. Smart buildings today are equipped with sensory infrastructure that can be used for an autonomous situation-aware evacuation guidance optimized in real time. A system providing such a guidance can help in avoiding additional evacuation casualties due to the flaws of the conventional evacuation approaches. Such a system should be robust and scalable to dynamically adapt to the number of evacuees and the size and safety conditions of a building. In this respect, we propose a distributed route recommender architecture for situation-aware evacuation guidance in smart buildings and describe its key modules in detail. We give an example of its functioning dynamics on a use case.