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The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. The digitization of software-intensive products and services is enabled basically by four megatrends: Cloud computing, big data mobile systems, and social technologies. This disruptive change interacts with all information processes and systems that are important business enablers for the current digital transformation. The internet of things, social collaboration systems for adaptive case management, mobility systems and services for big data in cloud services environments are emerging to support intelligent user-centered and social community systems. Modern enterprises see themselves confronted with an ever growing design space to engineer business models of the future as well as their IT support, respectively. The decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures (EA), is duly needed. With the advent of intelligent user-centered and social community systems, the challenging decision processes can be supported in more flexible and intuitive ways. Tapping into these systems and techniques, the engineers and managers of the enterprise architecture become part of a viable enterprise, i.e. a resilient and continuously evolving system that develops innovative business models.
Besides the optimisation of the car, energy-efficiency and safety can also be increased by optimising the driving behaviour. Based on this fact, a driving system is in development whose goal is to educate the driver in energy efficient and safe driving. It monitors the driver, the car and the environment and gives energy-efficiency and safety relevant recommendations. However, the driving system tries not to distract or bother the driver by giving recommendations for example during stressful driving situations or when the driver is not interested in that recommendation. Therefore, the driving system monitors the stress level of the driver as well as the reaction of the driver to a given recommendation and decideswhether to give a recommendation or not. This allows to suppress recommendations when needed and, thus, to increase the road safety and the user acceptance of
the driving system.
The evolution of Services Oriented Architectures (SOA) presents many challenges due to their complex, dynamic and heterogeneous nature. We describe how SOA design principles can facilitate SOA evolvability and examine several approaches to support SOA evolution. SOA evolution approaches can be classified based on the level of granularity they address, namely, service code level, service interaction level and model level. We also discuss emerging trends, such as microservices and knowledge-based support, which can enhance the evolution of future SOA systems.
This article covers the design of highly integrated gate drivers and level shifters for high-speed, high power efficiency and dv/dt robustness with focus on automotive applications. With the introduction of the 48 V board net in addition to the conventional 12 V battery, there is an increasing need for fast switching integrated gate drivers in the voltage range of 50 V and above. State-of-the-art drivers are able to switch 50 V in less than 5 ns. The high-voltage electrical drive train demands for galvanic isolated and highly integrated gate drivers. A gate driver with bidirectional signal transmission with a 1 MBit/s amplitude modulation, 10/20 MHz frequency modulation and power transfer over one single transformer will be discussed. The concept of high-voltage charge storing enables an area-efficient fully integrated bootstrapping supply with 70 % less area consumption. EMC is a major concern in automotive. Gate drivers with slope control optimize EMC while maintaining good switching efficiency. A current mode gate driver, which can change its drive current within 10 ns, results in 20 dBuV lower emissions between 7 and 60 MHz and 52 % lower switching loss compared to a conventional constant current gate driver.
Natural wood colors occur within a wide range from almost white (e.g., white poplar), various yellowish, reddish, and brownish hues to almost black (e.g., ebony). The intrinsic color of wood is basically defined by its chemical composition. However, other factors such as specific anatomical formations or physical properties further affect the optical impression. Starting with the chemical composition of wood and anatomical basics, wood color and its modifications are discussed in this chapter. The classic method of coloring or re-coloring wood-based material surfaces is the application of a coating containing appropriate dyes or pigments. Different concepts for wood coating and coloration are presented. Another method used dyes for coloration of the wood structure. As alternative techniques, physical methods, for example, drying, steaming, ammoniation, bleaching, enzyme treatment, as well as treatment with electromagnetic irradiation (e.g., UV), are explained in this chapter.
A lot of people need help in their daily life to wash, select and manage their clothing. The goal of this work is to design an assistant system (eKlarA) to support the user by giving recommendations to choose the clothing combinations, to find the clothing and to wash the clothing. The idea behind eKlarA is to generate a system that uses sensors to identify the clothing and their state in the clothing cycle. The clothing cycle consists of the stations: closets, laundry basket and washing machine in one or several places. The system uses the information about the clothing, weather and calendar to support the user in the different steps of the clothing cycle. The first prototype of this system has been developed and tested. The test results are presented in this work.
Software scripts for sensor data extraction in Rasberry Pi: user-space and kernel-space comparison
(2024)
This paper compares two popular scripting implementations for hardware prototyping: Python scripts execut from User-Space and C-based Linux-Driver processes executed from Kernel-Space, which can provide information to researchers when considering one or another in their implementations. Conclusions exhibit that deploying software scripts in the kernel space makes it possible to grant a certain quality of sensor information using a Raspberry Pi without the need for advanced real-time operational systems.
Entrepreneurship plays a role both for the development of African countries and for foreign companies with market entry plans. The infrastructural and institutional conditions for entrepreneurship are still difficult, but the advancing digitization leads to an increasingly active start-up scene in many African countries. There is still a mismatch between the areas where start-ups are created and the areas where foreign companies are looking for partners for market entry. Thus, despite positive developments in entrepreneurship, it remains difficult to find suitable partners in the foreseeable future.
Rapidly growing data volumes push today's analytical systems close to the feasible processing limit. Massive parallelism is one possible solution to reduce the computational time of analytical algorithms. However, data transfer becomes a significant bottleneck since it blocks system resources moving data-to-code. Technological advances allow to economically place compute units close to storage and perform data processing operations close to data, minimizing data transfers and increasing scalability. Hence the principle of Near Data Processing (NDP) and the shift towards code-to-data. In the present paper we claim that the development of NDP-system architectures becomes an inevitable task in the future. Analytical DBMS like HPE Vertica have multiple points of impact with major advantages which are presented within this paper.
Higher education institutions (HEIs) rely heavily on information technology (IT) to create innovations. Therefore, IT governance (ITG) is essential for education activities, particularly during the ongoing COVID-19 pandemic. However, the traditional concept of ITG is not fully equipped to deal with the current changes occurring in the digital age. Today's ITG requires an agile approach that can respond to disruptions in the HEI environment. Consequently, universities increasingly need to adopt agile strategies to ensure superior performance. This research proposes a conceptualization comprising three agile dimensions within the ITG construct: structures, processes, and relational mechanisms. An extensive qualitative evaluation of industry uncovered 46 agile governance mechanisms. Moreover, 16 professors rated these elements to assess agile ITG in their HEIs to determine those most effective for HEIs. This led to the identification of four structure elements, seven processes, and seven relational mechanisms.