Federated machine learning (FL) allows to collectively train models on sensitive data as only the clients’ models and not their training data need to be shared. However, despite the attention that research on FL has ...
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Decision-making is a complex and important task in softwareengineering. The current state-of-the-practice is rather non-systematic as it typically relies upon personal experience without using explicit models. Empiri...
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ISBN:
(纸本)1581135564
Decision-making is a complex and important task in softwareengineering. The current state-of-the-practice is rather non-systematic as it typically relies upon personal experience without using explicit models. Empirical studies can help but are to some extent context dependent and costly to conduct. Typically it is not efficient or even possible to conduct empirical studies for a large number of context parameter variations. We propose to build on a set of systematic empirical studies to fill gaps in context variable space with simulation: (a) Simulation can use the empirical results from different contexts and apply them to a planning situation as appropriate. (b) The analysis of simulation results can point out situations and factors for which conducting empirical studies would be most worthwhile. This paper presents a general decision model, a simulation framework, and examples for different decisions to use V&V activities in software development (e.g., under which conditions is a V&V activity, such as a re-inspection, worthwhile) to demonstrate practical applications of the general model. Copyright 2000 ACM.
The functionality realized by software in modern cars is increasing and as a result the development artifacts of automotive systems are getting more complex. The existence of traceability along these artifacts is esse...
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The functionality realized by software in modern cars is increasing and as a result the development artifacts of automotive systems are getting more complex. The existence of traceability along these artifacts is essential, since it allows to monitor the product development from the initial requirements to the final code. However, traceability is established and maintained mostly manually, which is time-consuming and error-prone. A further crucial problem is the assurance of the validity of the trace links, that is, the linked elements are indeed related to each other. In this paper we present a semiautomatic approach to create, check, and update trace links between artifacts along an automotive development process.
With the goal of reducing energy costs, carbon emissions, and achieving cleaner production, manufacturing companies aim to reduce their energy consumption. In manufacturing companies, a considerable amount of energy i...
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With the goal of reducing energy costs, carbon emissions, and achieving cleaner production, manufacturing companies aim to reduce their energy consumption. In manufacturing companies, a considerable amount of energy is wasted due to plant-, process- and human-related faults. Tools and methods for detecting anomalies are widely used for fraud detection in finance or intrusion detection in cybersecurity. When it comes to anomaly detection of malicious energy consumption, the residential building sector is leading. Industrial applications are not being addressed by now. In this paper, an end-to-end solution of an anomaly detection system is presented that uses the concept of a Long Short-term Memory based Autoencoder (LSTM-AE) as an unsupervised learning model that detects anomalies without labeling the data beforehand.
Professional knowledge management is imperative for the success of enterprises. One decisive factor for the success of knowledge management projects is the coordination of elements such as corporate culture, enterpris...
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ISBN:
(数字)9783540316206
ISBN:
(纸本)9783540304654
Professional knowledge management is imperative for the success of enterprises. One decisive factor for the success of knowledge management projects is the coordination of elements such as corporate culture, enterprise organization, - man resource management, as well as information and communication techn- ogy. The proper alignment and balancing of these factors are currently little understood—especially the role of information technology, which is often - garded only as an implementation tool, though it can be a catalyst by making new knowledge management solutions possible. This conference brought together representativesfrom practical and research ?elds for discussing experiences, professional applications, and visions through presentations, workshops, tutorials, and an accompanying industry exhibition. The main focus of the conference was the realization of knowledge mana- ment strategies with the aid of innovative information technology solutions, such as intelligent access to organizational memories, or integration of business processes and knowledge management. Also of interest were holistic/integrative approaches to knowledge management that deal with issues raised by the in- gration of people, organizations, and information technology.
Patients with epilepsy suffer from recurrently occurring seizures. To improve diagnosis and treatment as well as to increase patients’ safety and quality of life, it is of great interest to develop reliable methods f...
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Unternehmen erkennen zunehmend die Bedeutung evidenzbasierter Entscheidungen. Insbesondere die zunehmende Nutzung unternehmensexterner und offener Datensätze (Open Data) fördert die Möglichkeiten eviden...
Unternehmen erkennen zunehmend die Bedeutung evidenzbasierter Entscheidungen. Insbesondere die zunehmende Nutzung unternehmensexterner und offener Datensätze (Open Data) fördert die Möglichkeiten evidenzbasierter Entscheidungen. Dabei basieren evidenzbasierte Entscheidungen mit diesen Datensätzen immer häufiger auf Analysen, welche mittels maschineller Lernverfahren bzw. Machine Learning (ML) vorbereitet oder durchgeführt werden. Weil der Inhalt und die Qualität und damit der Nutzen eines Datensatzes für solche Analyseverfahren im Vorfeld ungewiss ist, stellt die Auswahl und die Beschaffung von geeigneten Daten unabhängig vom ML-Verfahren eine Kernherausforderung dar. Dieser Beitrag stellt deshalb zum Zwecke der Effizienz ein hierarchisches Vorgehen vor. Mit diesem können schemabasierte Datensätze strukturiert und effektiv dahingehend überprüft werden, ob deren Qualität und inhaltliche Fit für einen bestimmten Anwendungsfall (z. B. eine wiederkehrende Entscheidungssituation) ausreichend ist. Im Beitrag beschreiben wir einen Anwendungsfall aus dem Bereich der datengestützten Energieverbrauchsprognose für Wohngebäude, bei dem der Aufwand für die Datensatzauswahl reduziert werden konnte.
Companies across industries aim to disseminate blockchain through respective projects that evaluate, design, or implement use cases. However, due to its novelty and complexity, blockchain poses novel challenges in car...
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Know your customer (KYC) processes place a great burden on banks, because they are costly, inefficient, and inconvenient for customers. While blockchain technology is often mentioned as a potential solution, it is not...
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