AQuA-CEP: adaptive quality-aware complex event processing in the Internet of Things. - In: DEBS 2023, (2023), S. 13-24
Sensory data profoundly influences the quality of detected events in a distributed complex event processing system (DCEP). Since each sensor's status is unstable at runtime, a single sensing assignment is often insufficient to fulfill the consumer's quality requirements. In this paper, we study in the context of AQuA-CEP the problem of dynamic quality monitoring and adaptation of complex event processing by active integration of suitable data sources. To support this, in AQuA-CEP, queries to detect complex events are supplemented with consumer-definable quality policies that are evaluated and used to autonomously select (or even configure) suitable data sources of the sensing infrastructure. In addition, we studied different forms of expressing quality policies and analyzed how it affects the quality monitoring process. Various modes of evaluating and applying quality-related adaptations and their impacts on correlation efficiency are addressed, too. We assessed the performance of AQuA-CEP in IoT scenarios by utilizing the notion of the quality policy alongside the query processing adaptation using knowledge derived from quality monitoring. The results show that AQuA-CEP can improve the performance of DCEP systems in terms of the quality of results while fulfilling the consumer's quality requirements. Quality-based adaptation can also increase the network's lifetime by optimizing the sensor's energy consumption due to efficient data source selection.
https://doi.org/10.1145/3583678.3596884
Demo: Interactive performance exploration of stream processing applications using colored Petri nets. - In: DEBS 2023, (2023), S. 191-194
Stream processing is becoming increasingly important as the amount of data being produced, transmitted, processed, and stored continues to grow. One of the greatest difficulties in designing stream processing applications is estimating the final runtime performance in production. This is often complicated by differences between the development and final execution environments, unexpected outliers in the incoming data, or subtle long-term problems such as congestion due to bottlenecks in the pipeline. In this demonstration, we present an automated tool workflow for interactively simulating and exploring the performance characteristics of a stream processing pipeline in real-time. Changes to input data, pipeline structure, or operator configurations during the simulation are immediately reflected in the simulation results, allowing to interactively explore the robustness of the pipeline to outliers, changes in input data, or long-term effects.
https://doi.org/10.1145/3583678.3603280
Energy market transition and climate change: a review of TSOs-DSOs C+++ framework from 1800 to present. - In: Energies, ISSN 1996-1073, Bd. 16 (2023), 17, 6139, S. 1-24
In response to the pressing global challenges around climate change and the imperative of transitioning the energy market towards sustainability, this paper presents a comprehensive review starting from the late 18th century. The study examines the pivotal role of Transmission System Operators (TSOs) and Distribution System Operators (DSOs) in shaping the evolving energy landscape, with a specific emphasis on the C+++ Framework. This framework emphasizes coordination, cooperation, and collaboration between TSOs and DSOs to achieve sustainable energy systems through the integration of renewable energy technologies, storage systems, and efficient energy demand management. In addition, the review provides a historical overview of global warming from 1800 to the present, highlighting key events and developments related to greenhouse gas emissions. Furthermore, the paper delves into the significance of international agreements such as the Paris Agreement and the importance of reducing greenhouse gas emissions for a sustainable future. Recognizing the vital role of the C+++ Framework, the paper concludes with a discussion of future hybrid sustainable technologies incorporating various storage and efficient lighting technologies that can optimize energy management and reduce carbon emissions. This research aims to contribute valuable insights to inform energy policy and decision-making processes for a reliable, efficient, and sustainable energy delivery system.
https://doi.org/10.3390/en16176139
Evaluating statistical disclosure attacks and countermeasures for anonymous voice calls. - In: ARES 23, (2023), 22, insges. 10 S.
Assuming a threat model of a global observer, statistical disclosure attacks have been proposed to efficiently de-anonymize communication relationships in text-based mix networks over time. It is commonly assumed that such attacks are also able to disclose call relationships in anonymous communication networks (ACNs) that support voice calls. One straightforward countermeasure is to expect users to permanently send and receive packets that mimic a Voice over IP (VoIP) call. However, this is not practical in real world scenarios, like on mobile devices. In this article, we adapt one specific statistical disclosure attack (Z-SDA-MD) to voice calls and quantitatively study less resource-intensive countermeasures. As base countermeasure, we evaluate a round-based communication model, corresponding to a timed mix. A simulation study of this scenario shows that the Z-SDA-MD is not well suited for a general disclosure of call relationships because of too many false positives. Nevertheless, the attack is able to correctly identify the most frequent relationships. Still, the accuracy in that regard may significantly be decreased by increasing the duration of one round, by decoupling actions (call setup and teardown) of caller and callee by a random number of rounds, and by occasional fake calls to a fixed set of “fake friends”. Overall, our study shows that anonymous voice calls may be implemented with an acceptable trade-off between anonymity, call setup time, and bandwidth overhead.
https://doi.org/10.1145/3600160.3600186
Targeting the insula with transcranial direct current stimulation: a simulation study. - In: Psychiatry research, ISSN 1872-7506, Bd. 335 (2023), 111718
Insula is considered an important region of the brain in the generation and maintenance of a wide range of psychiatric symptoms, possibly due to being key in fundamental functions such as interoception and cognition in general. Investigating the possibility of targeting this area using non-invasive brain stimulation techniques can open new possibilities to probe the normal and abnormal functioning of the brain and potentially new treatment protocols to alleviate symptoms of different psychiatric disorders. In the current study, COMETS2, a MATLAB based toolbox was used to simulate the magnitude of the current density and electric field in the brain caused by different transcranial direct current stimulation (tDCS) protocols to find an optimum montage to target the insula and its 6 subregions for three different current intensities, namely 2, 3, and 4 mA. Frontal and occipital regions were found to be optimal candidate regions. The results of the current study showed that it is viable to reach the insula and its individual subregions using tDCS.
https://doi.org/10.1016/j.pscychresns.2023.111718
OHO: a multi-modal, multi-purpose dataset for human-robot object hand-over. - In: Sensors, ISSN 1424-8220, Bd. 23 (2023), 18, 7807, S. 1-13
In the context of collaborative robotics, handing over hand-held objects to a robot is a safety-critical task. Therefore, a robust distinction between human hands and presented objects in image data is essential to avoid contact with robotic grippers. To be able to develop machine learning methods for solving this problem, we created the OHO (Object Hand-Over) dataset of tools and other everyday objects being held by human hands. Our dataset consists of color, depth, and thermal images with the addition of pose and shape information about the objects in a real-world scenario. Although the focus of this paper is on instance segmentation, our dataset also enables training for different tasks such as 3D pose estimation or shape estimation of objects. For the instance segmentation task, we present a pipeline for automated label generation in point clouds, as well as image data. Through baseline experiments, we show that these labels are suitable for training an instance segmentation to distinguish hands from objects on a per-pixel basis. Moreover, we present qualitative results for applying our trained model in a real-world application.
https://doi.org/10.3390/s23187807
2023 IEEE Vehicular Networking Conference (VNC) : 26-28 April 2023, Istanbul, Turkey. - [Piscataway, NJ] : IEEE, 2023. - 1 Online-Ressource ISBN 979-8-3503-3549-1
Literaturangaben
https://ieeexplore.ieee.org/servlet/opac?punumber=10136303
Spacecraft attitude estimation based on temperature measurements in cuboid configuration. - In: Control engineering practice, ISSN 1873-6939, Bd. 140 (2023), 105659
In any spacecraft mission it is vital to have knowledge about the attitude. In this context, multiple ways can be employed to estimate the current attitude of the spacecraft. As temperature sensors are cheap and lightweight they appear to be a viable alternative. A method is investigated to estimate the attitude of a spacecraft based on twelve temperature sensors in a cuboid configuration. The method relies on a proposed mathematical model governing the temperature and attitude dynamics and employs non-linear observer design. Further, it is investigated if the attitude estimation is still possible if some of the sensors are malfunctioning. The proposed algorithms are validated using real mission data.
https://doi.org/10.1016/j.conengprac.2023.105659
Microwave angiography by ultra-wideband sounding: a preliminary investigation. - In: Diagnostics, ISSN 2075-4418, Bd. 13 (2023), 18, 2950, S. 1-17
Angiography is a very informative method for physicians such as cardiologists, neurologists and neuroscientists. The current modalities experience some shortages, e.g., ultrasound is very operator dependent. The computerized tomography (CT) and magnetic resonance (MR) angiography are very expensive and near infrared spectroscopy cannot capture the deep arteries. Microwave technology has the potential to address some of these issues while compromising between operator dependency, cost, speed, penetration depth and resolution. This paper studies the feasibility of microwave signals for monitoring of arteries. To this aim, a homogenous phantom mimicking body tissue is built. Four elastic tubes simulate arteries and a mechanical system creates pulsations in these arteries. A multiple input multiple output (MIMO) array of ultra-wideband (UWB) transmitters and receivers illuminates the phantom and captures the reflected signals over the desired observation time period. Since we are only interested in the imaging of dynamic parts, i.e., arteries, the static clutters can be suppressed easily by background subtraction method. To obtain a fast image of arteries, which are pulsating with the heartbeat rate, we calculate the Fourier transform of each channel of the MIMO system over the observation time and apply delay and sum (DAS) beamforming method on the heartbeat rate aligned spectral component. The results show that the lateral and longitudinal images and motion mode (M-mode) time series of different points of phantom have the potential to be used for diagnosis.
https://doi.org/10.3390/diagnostics13182950
Cooperative memory management for table and temporary data. - In: 1st Workshop on Simplicity in Management of Data, (2023), 2, insges. 5 S.
The traditional paradigm for managing memory in database management systems (DBMS) treats memory used for caching table data and memory for temporary data as separate entities. This leads to inefficient utilization of the available memory capacity for mixed workloads. With memory being a significant factor in the costs of operating a DBMS, utilizing memory as efficiently as possible is highly desirable. As an alternative to the traditional paradigm, we propose managing the entire available memory in a cooperative manner to achieve better memory utilization and consequently higher cost-effectiveness for DBMSs. Initial experimental evaluation of cooperative memory management using a prototype implementation shows promising results and leads to several interesting further research directions.
https://doi.org/10.1145/3596225.3596230