This paper contributes to research on gamified learning by providing lessons learned from a gamified, self-paced, digital distant learning environment on business information systems. It expands previous research by reporting on a second iteration of an educational design experiment in S/4 HANA. Design elements were composed into a playful layout and associations with a non-learning-context were included, in order to create a more relaxed learning experience. Mistakes were allowed, to keep the students’ attention high and to make achievements more rewarding. A mixed media approach was applied to enrich students’ learning experience and to avoid monotony. This paper contributes to the body of knowledge by providing lessons learned from a radical conversion of a traditional face-to-face course into a digital distant learning environment using elements of gamification, self-paced learning, and learning from mistakes.
We describe our UAV imaging research and development from a business perspective. Our main goal is to increase business opportunities for our drone services. We build on experiences from an already deployed drone service provided by our IT company. The application is using a commercial tool for processing photogrammetry. Its advantage is accuracy, but the main disadvantage is the time needed for annotation by a trained human operator. Our methodology is based on user studies and knowledge gained in communicating with potential customers at IT trade fairs and exhibitions. We analyse the duration and automation of the service as key factors. We consider two types of higher automation of the solution. First is the automation of annotation less accurate, without human intervention. The second is automation in flight planning and implementation. The use of other drone peripherals or hybrid drones can also create new types of services. In particular, there is a demand for immediate execution of on-site flight imaging without any pre-calibration. Our considerations, expanding our services, also include various inspections or direct involvement in industrial processes. Some improvements were tested on an experimental prototype. The results indicate improvement making services cheaper and faster.
In times of Big Data and rapid changes, managers become increasingly reliant on dashboards to make fast and informed decisions. The advantages of dashboards are evident even at the beginning of Business Intelligence deployment in organizations. To address the inability of humans to deal with large amounts of data, dashboards are a typical instrument to represent business-critical information in a comprehensible manner. However, there are many difficulties in managing the needs of individuals, teams, and organizations together with the technology in the context of socio-technical systems. While a broad range of technologies for dashboards’ creation exists, the question remains in how far dashboard solutions consider the needs and preferences of their primary addressee – human worker. This paper addresses this question by offering a systematic review of recent literature on dashboards. The study focuses on the end-user perspective and includes domains, goals, design process and dashboard characteristics, technologies, and impacts of dashboards’ application in organizations. In conclusion, research gaps and potential directions are
Hashing to prime in zero-knowledge takes as input a committed secret $$a$$ -bit input x and outputs a committed secret $${(k+1)}$$ -bit prime number $$p_x$$ . In this work we are considering zero-knowledge arguments that establish that the corresponding computations are done correctly and that the resulting commitment is indeed on the prime number derived from x. Depending on the number of zero-knowledge argument rounds k and the number of primality bases t used to establish primality, we obtain a soundness error probability of at most $$2^{-k}+ 2^{-t}$$ . While the corresponding ZK arguments have already been established in earlier work [22], we explore the use of hash-to-prime ZK arguments to enable dynamic encodings for a selection of cryptographic schemes, namely prime-based accumulator [2, 10], attribute-based credential [7], and graph signature schemes [19, 21].
Smart city data has the potential to be used to support evidence -based decision making. Yet, to fulfil this potential, private data needs to be shared with governments in data collaborations, in which. trust between the participating actors is a major prerequisite. This paper aims to provide an answer on 1) what the business conditions and challenges for smart city data providers collaborating to share sensitive data to engender trust among each other are and 2) what the impact of open and closed business model configurations on the trustworthiness of smart city data collaborations is. A case study analysis of the Smart Retail Dashboard aims to set up a data collaboration between smart city data providers and cities to improve the evidence-based decision making of local retail policy makers. An analysis is made of the data sharing business model conditions of trustworthiness in an open, closed and hybrid model. The paper concludes with the advantages and disadvantages of each scenario to engender trust and how these scenarios solve the earlier determined
