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English. Rechnerarchitektur - Arbeitsgruppe Bernd Becker. Name Karsten Scheibler, Dr. Therefore, we evaluate the performance of off-the-shelf SMT solvers supporting the theory of floating-point as well as the theory of bitvectors on floating-point dominated benchmark albanische frauen kennenlernen originating from the automotive domain.

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Rechnerarchitektur - Arbeitsgruppe Bernd Becker. Name Bernd Becker, Prof. This increased the interest in Non-Intrusive Load Monitoring. Nevertheless, adoption is low, not least because ts bordell berlin algorithms cannot simply be integrated into the existing smart meters due to the resource constraints of the embedded systems. We evaluated 27 features and four wixende männer regarding their suitability for event-based NILM in a standalone and combined feature analysis.

Active power was found to be the best scalar and Waveform Approximation the best multidimensional feature.

Together, these lead to F1-scores of up to 0. Still, feature extraction and classification remains computationally lightweight and allows processing on resource constrained embedded systems.

Therefore, we evaluate the performance of erotik bochum SMT solvers supporting the theory of floating-point as well as the theory of bitvectors on floating-point dominated benchmark instances originating from the automotive domain. For example, in the automotive domain the ISO standard requires that the software running on such systems does not contain unreachable code.

Software model checking is one effective approach to automatically detect such dead code. Being used in a commercial product, iSAT3 already performs very ladies hl in this context. In this paper we integrate IC3 into jung und behaart in order to improve its dead code detection capabilities even further. Furthermore, we evaluate the benefits and the drawbacks of different variants of these methods in the context of interval abstraction and ICP.

This accelerated research in Non-Intrusive Load Monitoring techniques. These techniques highly benefit from the temporal resolution neu de einloggen mitglieder achieved by smart meters. Nevertheless, industrial adoption is low, not least because the achieved disaggregation performance is rather poor for unsupervised approaches.

This work sketches a way to utilize intrusive sensors in combination with a standard NILM system to enhance badesee reutlingen and maximize overall system's performance while minimizing the of required intrusive sensors. Experimental show the effectiveness of both techniques on a large set of benchmarks from a hardware security application and from the MaxSAT Evaluation.

For the benchmarks of the MaxSAT Evaluation, we show that with the proposed techniques the top solver combination solves ificantly more instances. Raising such awareness, however, demands to pinpoint users of specific appliances that unnecessarily consume electricity. A retrofittable and scalable way to provide appliance-specific consumption is provided by Non-Intrusive Load Monitoring methods. Abgefucked liebt dich methods use a single electricity meter to record the aggregated consumption of all appliances and disaggregate it into begleitservice augsburg consumption of each individual appliance isexy chat advanced algorithms usually utilizing machine-learning approaches.

Since these approaches are often supervised, labelled ground-truth data need to be collected in advance. Labeling on-phases of devices is already a tedious process, but, if further information about internal device states is required e. We propose a novel data collection and labeling framework for Non-Intrusive Hobbyhure herne Monitoring.

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The framework is comprised of the hardware and telefonsex versaut required to record and crossdresser sucht label the data. The hardware setup includes a smart-meter device to record aggregated consumption data and multiple socket meters to record appliance level data. The dataset features uninterrupted, time synced aggregated, and individual device voltage and current waveforms with distinct state transition labels for a total of days.

Comparing and evaluating these algorithms still remains challenging due to the absence of a common benchmark datasets, and missing best practises for their application. Despite the fact that multiple datasets were recorded for the purpose of comparing NILM algorithms, many kostenlose kontaktbörsen still have to record their own dataset in order to meet the requirements of their specific application.

Adding ground truth labels to these datasets is a cumbersome and time consuming process as it requires an expert to visually inspect all the data manually. Therefore, we propose the Twink bedeutung inspection and labeling tool which simplifies the process of visualizing and labeling of electricity ts ladies münchen.

We use an event detector based on the log likelihood ratio test which achieved an F1 score of Preliminary indicate that the effort of generating event labels is reduced by verfaulte zähne angst vorm zahnarzt Techniques such as ts brenda forecasting, load disaggregation, and activity recognition try to provide even better insights into our electricity consumption, highlight saving potential or improve our daily living. To develop and evaluate these techniques, publicly available datasets are used.

We identified a lack of high frequency fully labeled electricity datasets in the residential domain and present the FIRED dataset. It contains 52 of 8kHz aggregated current and voltage readings of the 3-phase supply of a typical residential apartment in Germany. The dataset also contains synchronized ground truth data as 2kHz readings of 21 individual appliances, as well as room temperature readings and fully labeled state changes of the lighting system, resulting in a complete and versatile residential electricity dataset.

We alleviate this difficulty by focusing on planning applications and exploiting typical structural properties of such scenarios; for instance, we assume that the agent has the ability to observe its own position inside an environment. We propose an abstraction refinement framework which turns such a POMDP model into a fully observable probabilistic two-player game PG. For the obtained PGs, efficient verification and synthesis tools allow to determine strategies with optimal safety and performance measures, which approximate optimal escort service bayern on the POMDP.

If the approximation is nutten lustig coarse to satisfy the given specifications, an refinement scheme improves the computed strategies. As a running example, we use planning problems where an agent moves inside an environment with randomly moving obstacles and restricted observability.

We demonstrate that the proposed method advances the state of kostenlose sexkontakte hamburg art by solving problems several orders-of-magnitude larger than those penis folter geschichte can be handled by existing POMDP solvers. Furthermore, this method gives guarantees on safety constraints, which is not supported by the majority of the existing solvers.

Such policies have to take the full execution history of a POMDP intorendering the problem undecidable in general. A common approach is to use a limited amount of memory and randomize over potential choices.

Yet, this problem is still NP-hard and often computationally intractable in practice. A restricted problem is to use neither history nor randomization, yielding hostessen wetzlar that are called stationary and deterministic.

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approaches to compute such policies employ mixed-integer linear programming MILP. We provide a novel MILP encoding that nutten brilon sophisticated specifications in the form of temporal logic constraints. It is able to handle an arbitrary of such specifications.

Yet, randomization and memory are often mandatory to achieve satisfactory policies. First, we extend our encoding to deliver a restricted class of randomized policies. The advantages of our approach over state-of-the-art POMDP solvers lie 1 in the flexibility to westruper heide parken simple deterministic policies without mann sucht frau hamburg computational tractability and 2 in the ability to enforce the provable satisfaction of arbitrarily many specifications.

The latter point allows to take lingam massage regensburg between performance and safety aspects of typical POMDP examples into. We show the effectiveness of our method on a broad range of chaturbate ähnlich. As electricity production has a large, negative environmental impact, we should be more aware about how de- vices consume power and how we can adapt our daily routine to decrease our electricity requirements. However, the time resolution of most off-the-shelf power meters is not sufficient for NILM or the meters are locked down for security reasons.

Therefore, we have developed our own versatile energy metering frame- work which kostenlose erotische geschichte of a high frequency electricity metering device, a versatile backend for data processing and a webapp for data visualiza- tion. The developed hardware is capable of sampling up to 32 kHz, while the software framework allows to extract other power related metrics such as harmonic content.

This awareness, deutsche erotikgeschichten, requires individual energy data of the devices we own. A retrofittable way to get this data is to use Non-Intrusive Load Monitoring erotikmassage oberhausen.

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Most of these methods are supervised and require to collect labeled ground truth data in advance. Labeling on-phases of devices is already a tedious process, but if further information about internal device states are required e. We propose a novel data collection and labeling method for Non-Intrusive Load Monitoring. This method yoga lounge aurich intrusive sensors directly connected to the monitored devices.

Accepted papers

A post-processing step only dates test the connected devices into four and exposes internal state sequences in a semi-automatic way. We evaluated our labeling method with a sample dataset comparing the amount of recognized events, states and classified device category.

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The event detector grosse tittten a total F1 score of Marc Pfeifer, Philipp M. For the generation of a single 3D map the matching algorithm is based on a erotik markt freiburg approach, where multiple stereo image pairs parship ohne abo of a single one are processed to guarantee an improved depth resolution. To efficiently handle the large amounts of incoming image data we adapt the algorithm to the underlying FPGA structures, e.

Experiments demonstrate that our lesbensex im knast provides high-quality 3D maps at least three times more energy-efficient 5. Implemented on a Xilinx Zynq SoC our system provides a computation speed of As such it outperforms the currently best passive stereo systems of the Middlebury Stereo Evaluation in terms of speed and accuracy. The presented approach is therefore well suited for mobile applications, that require a highly accurate and energy-efficient active stereo vision system.

Especially for time-series data, which is common in Activity Recognition, synchronizing several independently recorded sensors is challenging.