Formal methods (in a broad sense) have been around almost since the beginning of computerscience. Nonetheless, there is a perception in the formal methods community that take-up by industry is low considering the pot...
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Pollen allergies are considered as a global epidemic nowadays, as they influence more than a quarter of the worldwide population, with this percentage expected to rapidly increase because of ongoing climate change. To...
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Pollen allergies are considered as a global epidemic nowadays, as they influence more than a quarter of the worldwide population, with this percentage expected to rapidly increase because of ongoing climate change. To date, alerts on high-risk allergenic pollen exposure have been provided only via forecasting models and conventional monitoring methods that are laborious. The aim of this study is to develop and evaluate our own pollen classification model based on deep neural networks. Airborne allergenic pollen have been monitored in Augsburg, Bavaria, Germany, since 2015, using a novel automatic Bio-Aerosol Analyzer (BAA 500, Hund GmbH). The automatic classification system is compared and evaluated against our own, newly developed algorithm. Our model achieves an unweighted average precision of 83.0 % and an unweighted average recall of 77.1 % across 15 classes of pollen taxa. Automatic, real-time information on concentrations of airborne allergenic pollen will significantly contribute to the implementation of timely, personalized management of allergies in the future. It is already clear that new methods and sophisticated models have to be developed so as to successfully switch to novel operational pollen monitoring techniques serving the above need.
Existing wireless communication systems are not able to meet the stringent requirements for critical machine-to-machine communications regarding ultra-reliability and low-latency. Since increasing the communication re...
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Existing wireless communication systems are not able to meet the stringent requirements for critical machine-to-machine communications regarding ultra-reliability and low-latency. Since increasing the communication reliability often comes at the price of increasing the latency as well, new mechanisms must be proposed that consider both challenges together. A promising approach, according to analytical work, is to increase the reliability by using cooperative diversity, where all stations within range help each other in the transmission process. Theoretical analyses, however, only provide a limited insight regarding the actual performance due to the strong assumptions they make to model such complex systems. In this paper, we thus evaluate the practical feasibility of ultra-reliable low-latency communication through cooperation by designing a data link protocol that incorporates a best relay selection mechanism. We implement our protocol in a real-world testbed, consisting of software-defined radios, to gain a better understanding of how future ultra-reliable low-latency systems should be designed and implemented. Our measurement campaigns show that at a given low target latency of 1 ms, we achieve a packet error rate between 10 -5 and 10 -7 with a standard 802.11a physical layer.
Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientifi...
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In a cloud computing environment, datacenter consists of number of servers, cooling and power delivery equipment's that require enormous measure of computational energy to drive complex frameworks. Due to the risi...
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ISBN:
(纸本)9781538614433;9781538614426
In a cloud computing environment, datacenter consists of number of servers, cooling and power delivery equipment's that require enormous measure of computational energy to drive complex frameworks. Due to the rising demand of the computation power, datacenter has become the hub for significant increase in the power consumption, heat dissipation and rise in temperature of the servers. Cloud datacenter's energy consumption has increased tremendously due to increase in the computation requirements of the user workload. Thus, saving energy has become an important concern to address. Researchers proposed different techniques to optimize the energy consumption. In this paper, we focus on different aspects of cloud computing for holistic management of cloud resources in an energy-efficient, reliable and sustainable manner. We recognized different opportunities, identified research challenges and propose possible future research directions for cloud computing.
In an age where science is often interdisciplinary, it is frequently necessary to combine scientific data from different (sub-)disciplines and thus from different sources. Ontologies can play an important role in this...
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The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task f...
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Vehicles are the target of a rising number of hacking attacks. The integration of in-vehicle intrusion detection systems is a common approach to increase the overall system security. However' testing and evaluatin...
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ISBN:
(纸本)9783885796633
Vehicles are the target of a rising number of hacking attacks. The integration of in-vehicle intrusion detection systems is a common approach to increase the overall system security. However' testing and evaluating these systems is difficult due to the lack of tools to generate realistic benign and malicious workloads as well as sharing these workloads with other researchers. Currently' testing tools are predominantly intended for Network Intrusion Detection System (NIDS) in company or industrial networks where their usefulness became apparent. Yet' in the automotive domain' development of testing tools is still in the early stages. Existing non-commercial automotive tools only focuson one specific bus technology each. However' in-vehicle communication exceeds bus technologyboundaries and a testing tool must cover multiple technologies. We propose a framework architecture concept for in-vehicle NIDS testing and evaluation to enable the creation of realistic network traffic and attacks in consideration of automotive specific challenges. Our concept provides the opportunity to share data without additional anonymization effort therefore improving cooperation and reproducibility of testing results.
Plant diseases are important factors as they result in serious reduction in quality and quantity of agriculture products. Therefore, early detection and diagnosis of these diseases are important. To this end, we propo...
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