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Usable security puts the users into the center of cyber security developments. Software developers are a very specific user group in this respect, since their points of contact with security are application programming interfaces (APIs). In contrast to APIs providing functionalities of other domains than security, security APIs are not approachable by habitual means. Learning by doing exploration exercises is not well supported. Reasons for this range from missing documentation, tutorials and examples to lacking tools and impenetrable APIs, that makes this complex matter accessible. In this paper we study what abstraction level of security APIs is more suitable to meet common developers’ needs and expectations. For this purpose, we firstly define the term security API. Following this definition, we introduce a classification of security APIs according to their abstraction level. We then adopted this classification in two studies. In one we gathered the current coverage of the distinct classes by the standard set of security functionality provided by popular software development kits. The other study has been an online questionnaire in which we asked 55 software developers about their experiences and opinion in respect of integrating security mechanisms into their coding projects. Our findings emphasize that the right abstraction level of a security API is one important aspect to consider in usable security API design that has not been addressed much so far.
Solar energy is one option to serve the rising global energy demand with low environmental impact. Building an energy system with a considerable share of solar power requires long-term investment and a careful investigation of potential sites. Therefore, understanding the impacts from varying regionally and locally determined meteorological conditions on solar energy production will influence energy yield projections.
Reliable and regional differentiated power forecasts are required to guarantee an efficient and economic energy transition towards renewable energies. Amongst other renewable energy technologies, e.g. wind mills, photovoltaic (PV) systems are an essential component of this transition being cost-efficient and simply to install. Reliable power forecasts are however required for a grid integration of photovoltaic systems, which among other data requires high-resolution spatio-temporal global irradiance data.
This paper presents the b-it-bots RoboCup@Work team and its current hardware and functional architecture for the KUKA youBot robot. We describe the underlying software framework and the developed capabilities required for operating in industrial environments including features such as reliable and precise navigation, flexible manipulation and robust object recognition.
An Experimental Field-Study on Active and Passive Work Breaks in a Stressful Work Environment
(2017)
Work breaks are known to have positive effects on employees’ health, performance, and safety. However, prior research has focused mainly on their timing, duration, and frequency but less on break activities. Moreover, most studies examined work breaks in rather repetitive and physical demanding work. Thus, we conducted an experimental field study with a sample of employees’ working in a stressful and cognitive demanding working environment and examined how different types of work breaks (boxing, deep relaxation, and usual breaks) affect participants’ mood, cognitive performance, and neuro-physiological state.
This paper proposes a novel approach to the generation of state equations from a bond graph (BG) of a mode switching linear time invariant model. Fast state transitions are modelled by ideal or non-ideal switches. Fixed causalities are assigned following the Standard Causality Assignment Procedure such that the number of storage elements in integral causality is maximised. A system of differential and algebraic equations (DAEs) is derived from the BG that holds for all system modes. It is distinguished between storage elements with mode independent causality and those that change causality due to switch state changes.
Raman-microspectroscopy was used for the non-destructive characterization and differentiation of six different meat spoilage associated microorganisms, namely Brochothrix thermosphacta DSM 20171, Micrococcus luteus, Pseudomonas fluorescens DSM 4358, Escherichia coli Top10 and K12 and Pseudomonas fluorescens DSM 50090. To evaluate and classify the Raman-spectroscopic data at species and strain level an adequate preprocessing and subsequent principal component analysis was used. The same procedure was extended to an independent test data set, which could be successfully assigned to the correct bacterial species and even to the right strain. The evaluation was not only successful in differentiation of gram-positive and gram-negative bacteria but also the discrimination between the different bacterial species and strains was possible. This means that the training data set, the preprocessing method and the evaluation of the data lead to a robust principal component analysis. Even the correct assignment of unknown samples is possible. The results show that Raman-microspectroscopy in combination with an appropriate chemometric treatment can be a good tool for a rapid examination and classification of microbial cultures.
Traditionally automotive UI focusses on the ergonomic design of controls and the user experience in the car. Bringing networked sensors into the car, connected cars can provide additional information to car drivers and owners, for and beyond the driving task. While there already are technological solutions, such as mobile applications commercially available, research on users’ information demands in such applications is scarce. We conducted four focus groups to uncover what kind of information users might be interested in to see on a second dashboard. Our findings show that besides control screens of todays’ dashboards, people are also interested in connected car services providing context information for a current driving situation and allowing strategic planning of driving safety or supporting car management when not driving. Our use cases inform the design of content for secondary dashboards for and especially beyond the driving context with a user perspective.
Climate change is having drastic effects on various areas of the planet, including extreme impacts on weather and rainfall, in various Sub-Saharan East African countries (Hendrix, C. S., & Glaser, S. M. (2007). The willingness (and need) of a niche market to actively improve the damaged ecosystems in small ways is rising. Weaver and Lawton (2007, p 1170) maintain that ecotourism should satisfy three core criteria: "(1) attractions should be predominantly nature-based; (2) visitor interactions with those attractions should be focused on learning or education, and (3) experience and product management should follow principles and practices associated with ecological, socio-cultural and economic sustainability." In this study, the niche market of active German "tree-planters" is to be defined and the potential willingness to travel to, learn from and invest in the ecosystem through tree-planting, specifically in Kenya, is explored.
“Building Bridges Across Continents” (BBAC) is an intercultural and student-centered project that seeks to promote international communication and helps students develop competencies in entrepreneurship, international trade and global cultural awareness. The project, which is in its fourth phase of implementation, connects students from the United States, Germany, Ghana and Kenya with the help of Information Communication Technologies (ICT) in order to work on a common research assignment for a period of ten calendar weeks. The main ICTs used in the project are Skype, Facebook, wiki, email and WhatsApp. This paper describes and analyzes the background, structure, and results of the project.