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Against the background of growing data in everyday life, data processing tools become more powerful to deal with the increasing complexity in building design. The architectural planning process is offered a variety of new instruments to design, plan and communicate planning decisions. Ideally the access to information serves to secure and document the quality of the building and in the worst case, the increased data absorbs time by collection and processing without any benefit for the building and its user. Process models can illustrate the impact of information on the design- and planning process so that architect and planner can steer the process. This paper provides historic and contemporary models to visualize the architectural planning process and introduces means to describe today’s situation consisting of stakeholders, events and instruments. It explains conceptions during Renaissance in contrast to models used in the second half of the 20th century. Contemporary models are discussed regarding their value against the background of increasing computation in the building process.
In the research domain of energy informatics, the importance of open datais rising rapidly. This can be seen as various new public datasets are created andpublished. Unfortunately, in many cases, the data is not available under a permissivelicense corresponding to the FAIR principles, often lacking accessibility or reusability.Furthermore, the source format often differs from the desired data format or does notmeet the demands to be queried in an efficient way. To solve this on a small scale atoolbox for ETL-processes is provided to create a local energy data server with openaccess data from different valuable sources in a structured format. So while the sourcesitself do not fully comply with the FAIR principles, the provided unique toolbox allows foran efficient processing of the data as if the FAIR principles would be met. The energydata server currently includes information of power systems, weather data, networkfrequency data, European energy and gas data for demand and generation and more.However, a solution to the core problem - missing alignment to the FAIR principles - isstill needed for the National Research Data Infrastructure.
Due to the transition to renewable energies, electricity markets need to be made fit for purpose. To enable the comparison of different energy market designs, modeling tools covering market actors and their heterogeneous behavior are needed. Agent-based models are ideally suited for this task. Such models can be used to simulate and analyze changes to market design or market mechanisms and their impact on market dynamics. In this paper, we conduct an evaluation and comparison of two actively developed open-source energy market simulation models. The two models, namely AMIRIS and ASSUME, are both designed to simulate future energy markets using an agent-based approach. The assessment encompasses modelling features and techniques, model performance, as well as a comparison of model results, which can serve as a blueprint for future comparative studies of simulation models. The main comparison dataset includes data of Germany in 2019 and simulates the Day-Ahead market and participating actors as individual agents. Both models are comparable close to the benchmark dataset with a MAE between 5.6 and 6.4 €/MWh while also modeling the actual dispatch realistically.
The FAYMONVILLE case study describes how the family-owned company Faymonville from eastern Belgium has succeeded in becoming one of the leading manufacturers in its sector. The targeted identification of new markets, the focus on relevant customer needs, and a consistent product policy with a coordinated manufacturing concept lay the foundations for success. In this case study, students can learn about how a company can successfully resolve the fundamental contradiction between economic and customized production.
We conducted a scoping review for active learning in the domain of natural language processing (NLP), which we summarize in accordance with the PRISMA-ScR guidelines as follows:
Objective: Identify active learning strategies that were proposed for entity recognition and their evaluation environments (datasets, metrics, hardware, execution time).
Design: We used Scopus and ACM as our search engines. We compared the results with two literature surveys to assess the search quality. We included peer-reviewed English publications introducing or comparing active learning strategies for entity recognition.
Results: We analyzed 62 relevant papers and identified 106 active learning strategies. We grouped them into three categories: exploitation-based (60x), exploration-based (14x), and hybrid strategies (32x). We found that all studies used the F1-score as an evaluation metric. Information about hardware (6x) and execution time (13x) was only occasionally included. The 62 papers used 57 different datasets to evaluate their respective strategies. Most datasets contained newspaper articles or biomedical/medical data. Our analysis revealed that 26 out of 57 datasets are publicly accessible.
Conclusion: Numerous active learning strategies have been identified, along with significant open questions that still need to be addressed. Researchers and practitioners face difficulties when making data-driven decisions about which active learning strategy to adopt. Conducting comprehensive empirical comparisons using the evaluation environment proposed in this study could help establish best practices in the domain.
In recent years, more and more digital startups have been founded and many of them work remotely by applying enterprise collaboration systems (ECS). The study investigates the functional affordances of ECS, particularly Slack, and examines its potential as a virtual office environment for cultural development in digital startups. Through a case study and based on affordance theoretical considerations, the paper explores how ECS facilitates remote collaboration, communication, and socialization within digital startups. The findings comprise material properties of ECS (synchrony and asynchrony communication), functional affordances (virtual office and culture development affordances) as well as its realization (through communication practices, openness, and inter-company accessibility) and are conceptualized as a model for ECS affordances in digital startups.
Architecture is a university subject with educational roots in both the technical university and art/specialized architecture schools, yet it lacks a strong research orientation and is focused on professional expertise. This chapter explores the particular role of research within architectural education in general by discussing two different cases for the implementation of undergraduate research in architecture: during the late 1990s and early 2000s at the University of Sheffield, UK, and during the 2010s at RWTH Aachen University, Germany. These examples illustrate the asynchronous beginnings of similar developments, and also contextualize differences in disciplinary habitus and pedagogical approaches between Sheffield, where research impulses stemmed from within the Architectural Humanities, and Aachen with its strong tradition as a technical university.
Subglacial environments on Earth offer important analogs to Ocean World targets in our solar system. These unique microbial ecosystems remain understudied due to the challenges of access through thick glacial ice (tens to hundreds of meters). Additionally, sub-ice collections must be conducted in a clean manner to ensure sample integrity for downstream microbiological and geochemical analyses. We describe the field-based cleaning of a melt probe that was used to collect brine samples from within a glacier conduit at Blood Falls, Antarctica, for geomicrobiological studies. We used a thermoelectric melting probe called the IceMole that was designed to be minimally invasive in that the logistical requirements in support of drilling operations were small and the probe could be cleaned, even in a remote field setting, so as to minimize potential contamination. In our study, the exterior bioburden on the IceMole was reduced to levels measured in most clean rooms, and below that of the ice surrounding our sampling target. Potential microbial contaminants were identified during the cleaning process; however, very few were detected in the final englacial sample collected with the IceMole and were present in extremely low abundances (∼0.063% of 16S rRNA gene amplicon sequences). This cleaning protocol can help minimize contamination when working in remote field locations, support microbiological sampling of terrestrial subglacial environments using melting probes, and help inform planetary protection challenges for Ocean World analog mission concepts.