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Advances in the Internet of Things (IoT) enable a huge number of connected devices that produce large amounts of data. Such data is increasingly shared among various stakeholders to support advanced (predictive) analytics and precision decision making in different application domains like smart cities and industrial internet. Currently there are several platforms that facilitate sharing, buying and...
Decision guidance models are a means for design space exploration and documentation. In this paper, we present decision guidance models for microservice monitoring. The selection of a monitoring system is an essential part of each microservice architecture due to the high level of dynamic structure and behavior of such a system. We present decision guidance models for generation of monitoring data,...
Phasor Measurement Units (PMUs) provide high precision data at high sampling rates to support Smart Grid applications. Power Line Outage detection mechanisms can enhance the grid reliability by assisting power operators in taking proper control actions. Despite the potential provided by PMUs, there are very limited efforts on exploiting data available to more effectively detect outages. Conventional...
According to a recent study, 30% of VMs in private cloud data centers are "comatose", in part because there is generally no strong incentive for their human owners to delete them at an appropriate time. These inactive VMs are still scheduled and executed on physical cloud resources, taking valuable access away from productive VMs. In an extreme, cloud infrastructure may deny legitimate requests...
Miniaturization of electronics, reduction of time to market and new functionalities in the current context of autonomous driving, electrification and connectivity, are bringing new reliability challenges. Prognostics and Health Management (PHM) can be used effectively to address some of the key challenges, in particular new challenges associated with the transfer of consumer electronics to automotive...
This study deals with a simulation and data processing method for health monitoring of a power electronics device. A typical approach to power electronics lifetime assessment is to run accelerated ageing tests and statistical methods to determine a mean time to failure for a given mission profile. Using safety coefficients, an expected service life is then known for a given unit. Depending on the...
Based on the actual traffic detection data of the upstream and downstream video monitor blind area, Support Vector Machines (SVM) algorithm was used to realize the short-term traffic flow forecasting, and VISSIM simulation technology was used build the traffic blind area prediction model. The video blind spot detection algorithm with practical engineering application value and the traffic incident...
A wireless sensor network (WSN) is a conglomeration of scattered self organized sensor nodes to agreeably monitor the physical and surrounding conditions. These sensor nodes are equipped with limited resources such as memory, processing capability, battery power and transceiver for monitoring, processing and communicating the observed phenomena to make critical decisions with respect to collected...
In allusion to the communication security problem of measurement and control data on unmanned platform, a reverse analysis model of measurement and control protocol is proposed. The model adopts the data mining method to analyze the protocol format and semantic information in the message. Mainly adopts the improved BF algorithm and the AP algorithm to carry on the pattern string matching and the association...
Nutrition related health conditions can seriously decrease quality of life; a system able to monitor the kitchen activities and eating behaviour of patients could provide clinicians with important indicators for improving a patient's condition. To achieve this, the system has to reason about the person's actions and goals. To address this challenge, we present a behaviour recognition approach that...
Trends in industrial automation systems are placing more importance on using streams of digitized data to perform various automation functions in real-time, e.g., power, process, and factory automation. To ensure high reliability and availability, individual devices or (sub-)systems thereof need to be tested with respect to their expected real-time behavior in the system context at various stages...
Physical activity helps reduce the risk of cardiovascular disease, hypertension and obesity. The ability to monitor a person's daily activity level can inform self-management of physical activity and related interventions. For older adults with obesity, the importance of regular, physical activity is critical to reduce the risk of long-term disability. In this work, we present ActivityAware, an application...
Social interactions have been traditionally studied via questionnaires and participant observations, imposing high burden, low scalability and precision. The goal of my research is to explore novel techniques to detect and monitor social interactions in indoor settings. Through the development of a scalable research platform it would be possible to study social dynamics at a finer granularity. The...
Exascale computing represents the next leap in the HPC race. Reaching this level of performance is subject to several engineering challenges such as energy consumption, equipment-cooling, reliability and massive parallelism. Model-based optimization is an essential tool in the design process and control of energy efficient, reliable and thermally constrained systems. However, in the Exascale domain,...
Educational data mining (EDM) is an up-coming interdisciplinary research field, in which data mining (DM) techniques applying in educational data. Its objective is to better understand how students gain knowledge and recognize the settings in which they learn to improve educational outcomes. Educational systems can store a huge amount of data that coming from multiple sources in different formats...
Dementia is an age-related memory loss. It is a long-term and often the gradual decrease of thinking ability that affects the patient's daily living. Constant monitoring and support from caretaker is required to carry out routine activities. The overhead incurred in caretaking is high in terms of money, time and energy. Thus, assistive health care system for dementia is essential and feasible through...
In any power plants, it is crucial to perform a preventive maintenance to avoid unexpected breakdown of machinery, e.g., circulating water pump, using data collected from various sensors. There have been prior attempts using just traditional prediction techniques. In this paper, we propose a two-stage model that employs a technique from time series analysis to predict when the machine tends to be...
In this paper, we investigate how to improve the reliability of heart–rate monitoring of a large number of people playing sports over a limited area of sports field. Densely– located nodes attached to exercisers transmit heart–rate data to a data collection node simultaneously, which negatively affects the reliability of data collection due to severe congestions caused by excessive traffic load. In...
An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of develop- ing a user model as the basis for investigating user expe- rience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment...
Monitoring user interaction activities provides the basis for creating a user model that can be used to predict user behaviour and enable user assistant services. The BaranC framework provides components that perform UI monitoring (and collect all associated context data), builds a user model, and supports services that make use of the user model. In this case study, a Next-App prediction service...
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