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Abstract: The onset of cerebral ischemia is difficult to predict in patients with altered consciousness using the methods available. We hypothesize that changes in Heart Rate Variability (HRV), Near‐Infrared Spectroscopy (NIRS), and Electroencephalography (EEG) correlated with clinical data and processed by artificial intelligence (AI) can indicate the development of imminent cerebral ischemia and reperfusi...
Abstract: Growth behavior of different species under different habitats can be studied by comparing the production of biomass, plasticity index and relative competitive interaction. However, these functional traits of invasive species received rare consideration for determining the invasion success of invasive species at wetlands. Here, we examined the effect of water depth at 5 cm and 15 cm (static and flu...
Abstract: Purpose This study aims to report on how programme directors address sustainability within engineering education at Swedish universities and engineering colleges. Design/methodology/approach The study was performed as a survey with follow-up interviews around the following core questions: to what extent do programme directors possess a deep understanding of the subject of sustainable developmen...
Abstract: Artificial Intelligence is becoming increasingly popular with organizations due to the success of Machine Learning and Deep Learning techniques. Using these techniques, data scientists learn from vast amounts of data to enhance behaviour in software-intensive systems. Despite the attractiveness of these techniques, however, there is a lack of systematic and structured design process for developing...
Abstract: Human, social, organizational, and technical aspects are intertwined with each other in software teams during the software development process. Practices that teams actually adopt often deviate from those of the used frameworks, such as Scrum. However, currently there is little empirical insight explaining typical deviations, including their reasons and consequences. In this paper we use observati...
Abstract: Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method ...
Abstract: Integrating machine learning components in software systems is a task more and more companies are confronted with. However, there is not much knowledge today on how the software development process needs to change, when such components are integrated into a software system. We performed an interview study with 16 participants, focusing on emerging and changing task. The results uncover a set of 25...
Abstract: The collection of high-quality data provides a key competitive advantage to companies in their decision-making process. It helps to understand customer behavior and enables the usage and deployment of new technologies based on machine learning. However, the process from collecting the data, to clean and process it to be used by data scientists and applications is often manual, non-optimized and er...
Abstract: Due to reliability and performance considerations, employing multiple software-defined networking (SDN) controllers is known as a promising technique in Wireless Sensor Networks (WSNs). Nevertheless, employing multiple controllers increases the inter-controller synchronization overhead. Therefore, optimal placement of SDN controllers to optimize the performance of a WSN, subject to the maximum num...
Abstract: Abstract The automotive domain is rapidly changing in the last years. Among the different challenges OEMs (i.e. the vehicle manufacturers) are facing, vehicles are evolving into systems of systems. In fact, over the last years vehicles have evolved from disconnected and “blind” systems to systems that are (i) able to sense the surrounding environment and (ii) connected with other vehicles, the cit...
Abstract: Continuous experimentation (CE) refers to a group of practices used by software companies to rapidly assess the usage, value and performance of deployed software using data collected from customers and the deployed system. Despite its increasing popularity in the development of web-facing applications, CE has not been discussed in the development process of business-to-business (B2B) mission-criti...
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