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Improved Thermal Comfort Model Leveraging Conditional Tabular GAN Focusing on Feature Selection
(2024)
The indoor thermal comfort in both homes and workplaces significantly influences the health and productivity of inhabitants. The heating system, controlled by Artificial Intelligence (AI), can automatically calibrate the indoor thermal condition by analyzing various physiological and environmental variables. To ensure a comfortable indoor environment, smart home systems can adjust parameters related to thermal comfort based on accurate predictions of inhabitants’ preferences. Modeling personal thermal comfort preferences poses two significant challenges: the inadequacy of data and its high dimensionality. An adequate amount of data is a prerequisite for training efficient machine learning (ML) models. Additionally, high-dimensional data tends to contain multiple irrelevant and noisy features, which might hinder ML models’ performance. To address these challenges, we propose a framework for predicting personal thermal comfort preferences, combining the conditional tabular generative adversarial network (CTGAN) with multiple feature selection techniques. We first address the data inadequacy challenge by applying CTGAN to generate synthetic data samples, incorporating challenges associated with multimodal distributions and categorical features. Then, multiple feature selection techniques are employed to identify the best possible sets of features. Experimental results based on a wide range of settings on a standard dataset demonstrated state-of-the-art performance in predicting personal thermal comfort preferences. The results also indicated that ML models trained on synthetic data achieved significantly better performance than models trained on real data. Overall, our method, combining CTGAN and feature selection techniques, outperformed existing known related work in thermal comfort prediction in terms of multiple evaluation metrics, including area under the curve (AUC), Cohen’s Kappa, and accuracy. Additionally, we presented a global, model-agnostic explanation of the thermal preference prediction system, providing an avenue for thermal comfort experiment designers to consciously select the data to be collected.
Green infrastructure has been widely recognized for the benefits to human health and biodiversity conservation. However, knowledge of the qualities and requirements of such spaces and structures for the effective delivery of the range of ecosystem services expected is still limited, as well as the identification of trade-offs between services. In this study, we apply the One Health approach in the context of green spaces to investigate how urban park characteristics affect human mental health and wildlife support outcomes and identify synergies and trade-offs between these dimensions. Here we show that perceived restorativeness of park users varies significantly across sites and is mainly affected by safety and naturalness perceptions. In turn, these perceptions are driven by objective indicators of quality, such as maintenance of facilities and vegetation structure, and subjective estimations of biodiversity levels. The presence of water bodies benefited both mental health and wildlife. However, high tree canopy coverage provided greater restoration potential whereas a certain level of habitat heterogeneity was important to support a wider range of bird species requirements. To reconcile human and wildlife needs in green spaces, cities should strategically implement a heterogeneous green infrastructure network that considers trade-offs and maximizes synergies between these dimensions.
Die moderne Arbeitswelt erfordert digitale Kompetenz, doch Hochschulen mangelt es an Angeboten zum digitalen Kompetenzaufbau Studierender. Peer-Angebote können ein sinnvoller Ansatz zur Förderung digitaler Kompetenz sein, allerdings fehlen empirische Belege für deren Wirksamkeit. Die Studie setzt hier an und evaluiert den digitalen Kompetenzerwerb von Teilnehmenden fachübergreifender Peer-Trainings auf Grundlage des DigComp Rahmenmodells. Die Ergebnisse zeigen, dass Trainings-Teilnehmende ihre digitale Kompetenz im Vergleich zur Kontrollgruppe signifikant stärker steigern konnten. Die Ausbildung zur bzw. zum Peer-Trainer:in sowie die Peer-Trainings wurden von allen Beteiligten sehr positiv bewertet.
The digitization of financial activities in consumers' lives is increasing, and the digitalization of invoicing processes is expected to play a significant role, although this area is not well understood regarding the private sector. Human-Computer Interaction (HCI) and Computer Supported Cooperative Work (CSCW) research have a long history of analyzing the socio-material and temporal aspects of work practices that are relevant for the domestic domain. The socio-material structuring of invoicing work and the working styles of consumers must be considered when designing effective consumer support systems. In this ethnomethodologically-informed, design-oriented interview study, we followed 17 consumers in their daily practices of dealing with invoices to make the invisible administrative work involved in this process visible. We identified and described the meaningful artifacts that were used in a spatial-temporal process within various storage locations such as input, reminding, intermediate (for postponing cases) buffers, and archive systems. Furthermore, we identified three different working styles that consumers exhibited: direct completion, at the next opportunity, and postpone as far as possible. This study contributes to our understanding of household economics and domestic workplace studies in the tradition of CSCW and has implications for the design of electronic invoicing systems.
Dried serum spots that are well prepared can be attractive alternatives to frozen serum samples for shelving specimens in a medical or research center's biobank and mailing freshly prepared serum to specialized laboratories. During the pre-analytical phase, complications can arise which are often challenging to identify or are entirely overlooked. These complications can lead to reproducibility issues, which can be avoided in serum protein analysis by implementing optimized storage and transfer procedures. With a method that ensures accurate loading of filter paper discs with donor or patient serum, a gap in dried serum spot preparation and subsequent serum analysis shall be filled. Pre-punched filter paper discs with a 3 mm diameter are loaded within seconds in a highly reproducible fashion (approximately 10% standard deviation) when fully submerged in 10 μl of serum, named the "Submerge and Dry" protocol. Such prepared dried serum spots can store several hundred micrograms of proteins and other serum components. Serum-borne antigens and antibodies are reproducibly released in 20 μl elution buffer in high yields (approximately 90%). Dried serum spot-stored and eluted antigens kept their epitopes and antibodies their antigen binding abilities as was assessed by SDS-PAGE, 2D gel electrophoresis-based proteomics, and Western blot analysis, suggesting pre-punched filter paper discs as handy solution for serological tests.
Trust-Building in Peer-to-Peer Carsharing: Design Case Study for Algorithm-Based Reputation Systems
(2023)
Peer-to-peer sharing platforms become increasingly important in the platform economy. From an HCI-perspective, this development is of high interest, as those platforms mediate between different users. Such mediation entails dealing with various social issues, e.g., building trust between peers online without any physical presence. Peer ratings have proven to be an important mechanism in this regard. At the same time, scoring via car telematics become more common for risk assessment by car insurances. Since user ratings face crucial problems such as fake or biased ratings, we conducted a design case study to determine whether algorithm-based scoring has the potential to improve trust-building in P2P-carsharing. We started with 16 problem-centered interviews to examine how people understand algorithm-based scoring, we co-designed an app with scored profiles, and finally evaluated it with 12 participants. Our findings show that scoring systems can support trust-building in P2P-carsharing and give insights how they should be designed.
Citizen participation is deemed to be crucial for sustainability and resilience planning. However, generational equity has been missing from recent academic discussions regarding sustainability and resilience. Therefore, the purpose of this paper is to reintroduce the topic of the existence or absence of an intergenerational consensus on the example of a rural community and its perceived brand image attributes and development priorities. The research is based on primary data collected through an online survey, with a sample size of N = 808 respondents in Neunkirchen-Seelscheid, Germany. The data were analyzed using the Kruskal–Wallis test for the presence and/or absence of consensus among the five generations regarding brand image attributes and development priorities. The findings point to divergence between what the median values indicate as the most relevant brand image attributes and development priorities among the citizens and the areas where the Kruskal–Wallis test shows that an intergenerational consensus either does or does not exist. The results imply the need for new concepts and applied approaches to citizen participation for sustainability and resilience, where intergenerational dialogue and equity-building take center stage. In addition to the importance of the theory of citizen participation for sustainability and resilience, our results provide ample evidence for how sustainability and resilience planning documents could potentially benefit from deploying the concept of intergenerational equity. The present research provides sustainability and political science with new conceptual and methodological approaches for taking intergenerational equity into account in regional planning processes in rural and other areas.
Trust your guts: fostering embodied knowledge and sustainable practices through voice interaction
(2023)
Despite various attempts to prevent food waste and motivate conscious food handling, household members find it difficult to correctly assess the edibility of food. With the rise of ambient voice assistants, we did a design case study to support households’ in situ decision-making process in collaboration with our voice agent prototype, Fischer Fritz. Therefore, we conducted 15 contextual inquiries to understand food practices at home. Furthermore, we interviewed six fish experts to inform the design of our voice agent on how to guide consumers and teach food literacy. Finally, we created a prototype and discussed with 15 consumers its impact and capability to convey embodied knowledge to the human that is engaged as sensor. Our design research goes beyond current Human-Food Interaction automation approaches by emphasizing the human-food relationship in technology design and demonstrating future complementary human-agent collaboration with the aim to increase humans’ competence to sense, think, and act.
Background
Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion. Much prior research focuses on the automated detection of these fake reviews, which are far from perfect. Therefore, consumers must be able to detect fake reviews on their own. In this study we survey the research examining how consumers detect fake reviews online.
Methods
We conducted a systematic literature review over the research on fake review detection from the consumer-perspective. We included academic literature giving new empirical data. We provide a narrative synthesis comparing the theories, methods and outcomes used across studies to identify how consumers detect fake reviews online.
Results
We found only 15 articles that met our inclusion criteria. We classify the most often used cues identified into five categories which were (1) review characteristics (2) textual characteristics (3) reviewer characteristics (4) seller characteristics and (5) characteristics of the platform where the review is displayed.
Discussion
We find that theory is applied inconsistently across studies and that cues to deception are often identified in isolation without any unifying theoretical framework. Consequently, we discuss how such a theoretical framework could be developed.
Universities, Entrepreneurship and Enterprise Development in Africa – Conference Proceedings 2022
(2023)
These proceedings are the outcome of the 10th annual joint conference on "Universities Entrepreneurship and Enterprise Development in Africa".
These proceedings document the culmination of the 10th annual joint conference on "Universities, Entrepreneurship and Enterprise Development in Africa," which was held on the 8th and 9th of September 2022 at the Campus Sankt Augustin, Hochschule Bonn-Rhein-Sieg University of Applied Sciences. The conference was a collaboration between the University of Cape Coast, Ghana, and Hochschule Bonn-Rhein-Sieg University of Applied Sciences, Germany.