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In industrial production facilities, technical Energy Management Systems are used to measure, monitor and display energy consumption related information. The measurements take place at the field device level of the automation pyramid. The measured values are recorded and processed at the control level. The functionalities to monitor and display energy data are located at the MES level of the automation pyramid. So the energy data from all PLCs has to be aggregated, structured and provided for higher level systems. This contribution introduces a concept for an Energy Data Aggregation Layer, which provides the functionality described above. For the implementation of this Energy Data Aggregation Layer, a combination of AutomationML and OPC UA is used.
The growing importance of renewable generation connected to distribution grids requires an increased coordination between transmission system operators (TSOs) and distribution system operators (DSOs) for reactive power management. This work proposes a practical and effective interaction method based on sequential optimizations to evaluate the reactive flexibility potential of distribution networks and to dispatch them along with traditional synchronous generators, keeping to a minimum the information exchange. A modular optimal power flow (OPF) tool featuring multi-objective optimization is developed for this purpose. The proposed method is evaluated for a model of a real German 110 kV grid with 1.6 GW of installed wind power capacity and a reduced order model of the surrounding transmission system. Simulations show the benefit of involving wind farms in reactive power support reducing losses both at distribution and transmission level. Different types of setpoints are investigated, showing the feasibility for the DSO to fulfill also individual voltage and reactive power targets over multiple connection points. Finally, some suggestions are presented to achieve a fair coordination, combining both TSO and DSO requirements.
The transfer of historically grown monolithic software architectures into modern service-oriented architectures creates a lot of loose coupling points. This can lead to an unforeseen system behavior and can significantly impede those continuous modernization processes, since it is not clear where bottlenecks in a system arise. It is therefore necessary to monitor such modernization processes with an adaptive monitoring concept to be able to correctly record and interpret unpredictable system dynamics. This contribution presents a generic QoS measurement framework for service-based systems. The framework consists of an XML-based specification for the measurement to be performed – the Information Model (IM) – and the QoS System, which provides an execution platform for the IM. The framework will be applied to a standard business process of the German insurance industry, and the concepts of the IM and their mapping to artifacts of the QoS System will be presented. Furtherm ore, design and implementation of the QoS System’s parser and generator module and the generated artifacts are explained in detail, e.g., event model, agents, measurement module and analyzer module.
Cloud computing has become well established in private and public sector projects over the past few years, opening ever new opportunities for research and development, but also for education. One of these opportunities presents itself in the form of dynamically deployable, virtual lab environments, granting educational institutions increased flexibility with the allocation of their computing resources. These fully sandboxed labs provide students with their own, internal network and full access to all machines within, granting them the flexibility necessary to gather hands-on experience with building heterogeneous microservice architectures. The eduDScloud provides a private cloud infrastructure to which labs like the microservice lab outlined in this paper can be flexibly deployed at a moment’s notice.
In the context of modern mobility, topics such as smart-cities, Car2Car-Communication, extensive vehicle sensor-data, e-mobility and charging point management systems have to be considered. These topics of modern mobility often have in common that they are characterized by complex and extensive data situations. Vehicle position data, sensor data or vehicle communication data must be preprocessed, aggregated and analyzed. In many cases, the data is interdependent. For example, the vehicle position data of electric vehicles and surrounding charging points have a dependence on one another and characterize a competition situation between the vehicles. In the case of Car2Car-Communication, the positions of the vehicles must also be viewed in relation to each other. The data are dependent on each other and will influence the ability to establish a communication. This dependency can provoke very complex and large data situations, which can no longer be treated efficiently. With this work, a model is presented in order to be able to map such typical data situations with a strong dependency of the data among each other. Microservices can help reduce complexity.
Portable-micro-Combined-Heat-and-Power-units are a gateway technology bridging conventional vehicles and Battery Electric Vehicles (BEV). Being a new technology, new software has to be created that can be easily adapted to changing requirements. We propose and evaluate three different architectures based on three architectural paradigms. Using a scenario-based evaluation, we conclude that a Service-Oriented Architecture (SOA) using microservices provides a higher quality solution than a layered or Event-Driven Complex-Event-Processing (ED-CEP) approach. Future work will include implementation and simulation-driven evaluation.
The transfer of historically grown monolithic software architectures into modern service-oriented architectures creates a lot of loose coupling points. This can lead to an unforeseen system behavior and can significantly impede those continuous modernization processes, since it is not clear where bottlenecks in a system arise. It is therefore necessary to monitor such modernization processes with an adaptive monitoring concept in order to be able to correctly record and interpret unpredictable system dynamics. For this purpose, a general measurement methodology and a specific implementation concept are presented in this work.
Background
Uncomplicated urinary tract infections (UTI) are common in general practice and usually treated with antibiotics. This contributes to increasing resistance rates of uropathogenic bacteria. A previous trial showed a reduction of antibiotic use in women with UTI by initial symptomatic treatment with ibuprofen. However, this treatment strategy is not suitable for all women equally. Arctostaphylos uva-ursi (UU, bearberry extract arbutin) is a potential alternative treatment. This study aims at investigating whether an initial treatment with UU in women with UTI can reduce antibiotic use without significantly increasing the symptom burden or rate of complications.
Methods
This is a double-blind, randomized, and controlled comparative effectiveness trial. Women between 18 and 75 years with suspected UTI and at least two of the symptoms dysuria, urgency, frequency or lower abdominal pain will be assessed for eligibility in general practice and enrolled into the trial. Participants will receive either a defined daily dose of 3 × 2 arbutin 105 mg for 5 days (intervention) or fosfomycin 3 g once (control). Antibiotic therapy will be provided in the intervention group only if needed, i.e. for women with worsening or persistent symptoms. Two co-primary outcomes are the number of all antibiotic courses regardless of the medical indication from day 0–28, and the symptom burden, defined as a weighted sum of the daily total symptom scores from day 0–7. The trial result is considered positive if superiority of initial treatment with UU is demonstrated with reference to the co-primary outcome number of antibiotic courses and non-inferiority of initial treatment with UU with reference to the co-primary outcome symptom burden.
Discussion
The trial’s aim is to investigate whether initial treatment with UU is a safe and effective alternative treatment strategy in women with UTI. In that case, the results might change the existing treatment strategy in general practice by promoting delayed prescription of antibiotics and a reduction of antibiotic use in primary care.
Research question: In order to reduce fan aggression surrounding rivalry games, team sport organizations often try to placate fans by downplaying the importance of the game (e.g. ‘the derby is not a war’). Drawing on the intergroup conflict literature, this research derives dual identity statements and examines their effectiveness in reducing fan aggressiveness compared to the managerial practice of downplaying rivalry.
Research methods: Three field experimental studies (one face-to-face survey and two online surveys) tested the hypotheses. Established rivalries in the German soccer league Bundesliga served as the empirical setting of the studies. The data were analyzed using ANCOVA and linear regression analyses.
Results and findings: Dual identity statements reduce fan aggressiveness compared to both downplay statements and a no-statement control condition, independent of team identification and trait aggression. Importantly, the managerial practice of downplaying rivalry appears to be counterproductive. It produces even higher levels of fan aggressiveness than making no statement, an effect caused by psychological reactance.
Implications: Sport organizations should not alienate their fan base by attempting to play down the importance of rivalry, which is an integral part of fan identity. Instead, they should strengthen the supporters’ unique identity (as fans of a particular team) while at the same time facilitating identification with the rival at a superordinate level (e.g. as joint fans of a region).
Marketing, get ready to rumble — How rivalry promotes distinctiveness for brands and consumers
(2018)
Scholars typically advise brands to stay away from public conflict with competitors as research has focused on negative consequences - e.g., price wars, escalating hostilities, and derogation. This research distinguishes between rivalry between firms (inter-firm brand rivalry) and rivalry between consumers (inter-consumer brand rivalry). Four studies and six samples show both types of rivalry can have positive consequences for both firms and consumers. Inter-firm brand rivalry boosts perceived distinctiveness of competing brands independent of consumption, attitude, familiarity, and involvement. Inter-consumer brand rivalry increases consumer group distinctiveness, an effect mediated by brand identification and rival brand disidentification. We extend social identity theory by demonstrating that: 1) outside actors like firms can promote inter-consumer rivalry through inter-firm rivalry and 2) promoting such conflict can actually provide benefits to consumers as well as firms. The paper challenges the axiom “never knock the competition,” deriving a counter-intuitive way to accomplish one of marketing's premier objectives.