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Frequently, port scans are early indicators of more serious attacks. Unfortunately, the detection of slow port scans in company networks is challenging due to the massive amount of network data. This paper proposes an innovative approach for preprocessing flow-based data which is specifically tailored to the detection of slow port scans. The preprocessing chain generates new objects based on flow-based data aggregated over time windows while taking domain knowledge as well as additional knowledge about the network structure into account. The computed objects are used as input for the further analysis. Based on these objects, we propose two different approaches for detection of slow port scans. One approach is unsupervised and uses sequential hypothesis testing whereas the other approach is supervised and uses classification algorithms. We compare both approaches with existing port scan detection algorithms on the flow-based CIDDS-001 data set. Experiments indicate that the proposed approaches achieve better detection rates and exhibit less false alarms than similar algorithms.
Combining Distributed Consensus with Robust H-infinity-Control for Satellite Formation Flying
(2019)
Control methods that guarantee stability in the presence of uncertainties are mandatory in space applications. Further, distributed control approaches are beneficial in terms of scalability and to achieve common goals, especially in multi-agent setups like formation control. This paper presents a combination of robust H-infinity control and distributed control using the consensus approach by deriving a distributed consensus-based generalized plant description that can be used in H-infinity synthesis. Special focus was set towards space applications, namely satellite formation flying. The presented results show the applicability of the developed distributed robust control method to a simple, though realistic space scenario, namely a spaceborne distributed telescope. By using this approach, an arbitrary number of satellites/agents can be controlled towards an arbitrary formation geometry. Because of the combination with robust H-infinity control, the presented method satisfies the high stability and robustness demands as found e.g., in space applications.
The capabilities of small satellites have improved significantly in recent years. Specifically multi-satellite systems become increasingly popular, since they allow the support of new applications. The development and testing of these multi-satellite systems is a new challenge for engineers and requires the implementation of appropriate development and testing environments. In this paper, a modular network simulation framework for space–terrestrial systems is presented. It enables discrete event simulations for the development and testing of communication protocols, as well as mission-based analysis of other satellite system aspects, such as power supply and attitude control. ESTNeT is based on the discrete event simulator OMNeT++ and will be released under an open source license.
Due to biased assumptions on the underlying ordinal rating scale in subjective Quality of Experience (QoE) studies, Mean Opinion Score (MOS)-based evaluations provide results, which are hard to interpret and can be misleading. This paper proposes to consider the full QoE distribution for evaluating, reporting, and modeling QoE results instead of relying on MOS-based metrics derived from results based on ordinal rating scales. The QoE distribution can be represented in a concise way by using the parameters of a multinomial distribution without losing any information about the underlying QoE ratings, and even keeps backward compatibility with previous, biased MOS-based results. Considering QoE results as a realization of a multinomial distribution allows to rely on a well-established theoretical background, which enables meaningful evaluations also for ordinal rating scales. Moreover, QoE models based on QoE distributions keep detailed information from the results of a QoE study of a technical system, and thus, give an unprecedented richness of insights into the end users’ experience with the technical system. In this work, existing and novel statistical methods for QoE distributions are summarized and exemplary evaluations are outlined. Furthermore, using the novel concept of quality steps, simulative and analytical QoE models based on QoE distributions are presented and showcased. The goal is to demonstrate the fundamental advantages of considering QoE distributions over MOS-based evaluations if the underlying rating data is ordinal in nature.
Deriving QoE in systems: from fundamental relationships to a QoE-based Service-level Quality Index
(2020)
With Quality of Experience (QoE) research having made significant advances over the years, service and network providers aim at user-centric evaluation of the services provided in their system. The question arises how to derive QoE in systems. In the context of subjective user studies conducted to derive relationships between influence factors and QoE, user diversity leads to varying distributions of user rating scores for different test conditions. Such models are commonly exploited by providers to derive various QoE metrics in their system, such as expected QoE, or the percentage of users rating above a certain threshold. The question then becomes how to combine (a) user rating distributions obtained from subjective studies, and (b) system parameter distributions, so as to obtain the actual observed QoE distribution in the system? Moreover, how can various QoE metrics of interest in the system be derived? We prove fundamental relationships for the derivation of QoE in systems, thus providing an important link between the QoE community and the systems community. In our numerical examples, we focus mainly on QoE metrics. We furthermore provide a more generalized view on quantifying the quality of systems by defining a QoE-based Service-level Quality Index. This index exploits the fact that quality can be seen as a proxy measure for utility. Following the assumption that not all user sessions should be weighted equally, we aim to provide a generic framework that can be utilized to quantify the overall utility of a service delivered by a system.
Evaluating the Quality of Experience (QoE) of video streaming and its influence factors has become paramount for streaming providers, as they want to maintain high satisfaction for their customers. In this context, crowdsourced user studies became a valuable tool to evaluate different factors which can affect the perceived user experience on a large scale. In general, most of these crowdsourcing studies either use, what we refer to, as an in vivo or an in vitro interface design. In vivo design means that the study participant has to rate the QoE of a video that is embedded in an application similar to a real streaming service, e.g., YouTube or Netflix. In vitro design refers to a setting, in which the video stream is separated from a specific service and thus, the video plays on a plain background. Although these interface designs vary widely, the results are often compared and generalized. In this work, we use a crowdsourcing study to investigate the influence of three interface design alternatives, an in vitro and two in vivo designs with different levels of interactiveness, on the perceived video QoE. Contrary to our expectations, the results indicate that there is no significant influence of the study’s interface design in general on the video experience. Furthermore, we found that the in vivo design does not reduce the test takers’ attentiveness. However, we observed that participants who interacted with the test interface reported a higher video QoE than other groups.
Purpose
Pronounced differences in individual physiological adaptation may occur following various training mesocycles in runners. Here we aimed to assess the individual changes in performance and physiological adaptation of recreational runners performing mesocycles with different intensity, duration and frequency.
Methods
Employing a randomized cross-over design, the intra-individual physiological responses [i.e., peak (\(\dot{VO}_{2peak}\)) and submaximal (\(\dot{VO}_{2submax}\)) oxygen uptake, velocity at lactate thresholds (V\(_2\), V\(_4\))] and performance (time-to-exhaustion (TTE)) of 13 recreational runners who performed three 3-week sessions of high-intensity interval training (HIIT), high-volume low-intensity training (HVLIT) or more but shorter sessions of HVLIT (high-frequency training; HFT) were assessed.
Results
\(\dot{VO}_{2submax}\), V\(_2\), V\(_4\) and TTE were not altered by HIIT, HVLIT or HFT (p > 0.05). \(\dot{VO}_{2peak}\) improved to the same extent following HVLIT (p = 0.045) and HFT (p = 0.02). The number of moderately negative responders was higher following HIIT (15.4%); and HFT (15.4%) than HVLIT (7.6%). The number of very positive responders was higher following HVLIT (38.5%) than HFT (23%) or HIIT (7.7%). 46% of the runners responded positively to two mesocycles, while 23% did not respond to any.
Conclusion
On a group level, none of the interventions altered \(\dot{VO}_{2submax}\), V\(_2\), V\(_4\) or TTE, while HVLIT and HFT improved \(\dot{VO}_{2peak}\). The mean adaptation index indicated similar numbers of positive, negative and non-responders to HIIT, HVLIT and HFT, but more very positive responders to HVLIT than HFT or HIIT. 46% responded positively to two mesocycles, while 23% did not respond to any. These findings indicate that the magnitude of responses to HIIT, HVLIT and HFT is highly individual and no pattern was apparent.
Latency is a key characteristic inherent to any computer system. Motion-to-Photon (MTP) latency describes the time between the movement of a tracked object and its corresponding movement rendered and depicted by computer-generated images on a graphical output screen. High MTP latency can cause a loss of performance in interactive graphics applications and, even worse, can provoke cybersickness in Virtual Reality (VR) applications. Here, cybersickness can degrade VR experiences or may render the experiences completely unusable. It can confound research findings of an otherwise sound experiment. Latency as a contributing factor to cybersickness needs to be properly understood. Its effects need to be analyzed, its sources need to be identified, good measurement methods need to be developed, and proper counter measures need to be developed in order to reduce potentially harmful impacts of latency on the usability and safety of VR systems. Research shows that latency can exhibit intricate timing patterns with various spiking and periodic behavior. These timing behaviors may vary, yet most are found to provoke cybersickness. Overall, latency can differ drastically between different systems interfering with generalization of measurement results. This review article describes the causes and effects of latency with regard to cybersickness. We report on different existing approaches to measure and report latency. Hence, the article provides readers with the knowledge to understand and report latency for their own applications, evaluations, and experiments. It should also help to measure, identify, and finally control and counteract latency and hence gain confidence into the soundness of empirical data collected by VR exposures. Low latency increases the usability and safety of VR systems.
The electric propulsion system NanoFEEP was integrated and tested in orbit on the UWE-4 satellite, which marks the first successful demonstration of an electric propulsion system on board a 1U CubeSat. In-orbit characterization measurements of the heating process of the propellant and the power consumption of the propulsion system at different thrust levels are presented. Furthermore, an analysis of the thrust vector direction based on its effect on the attitude of the spacecraft is described. The employed heater liquefies the propellant for a duration of 30 min per orbit and consumes 103 ± 4 mW. During this time, the respective thruster can be activated. The propulsion system including one thruster head, its corresponding heater, the neutralizer and the digital components of the power processing unit consume 8.5 ± 0.1 mW ⋅μ A\(^{−1}\) + 184 ± 8.5 mW and scales with the emitter current. The estimated thrust directions of two thruster heads are at angles of 15.7 ± 7.6∘ and 13.2 ± 5.5∘ relative to their mounting direction in the CubeSat structure. In light of the very limited power on a 1U CubeSat, the NanoFEEP propulsion system renders a very viable option. The heater of subsequent NanoFEEP thrusters was already improved, such that the system can be activated during the whole orbit period.
Aims Acute myocardial infarction (MI) is the major cause of chronic heart failure. The activity of blood coagulation factor XIII (FXIIIa) plays an important role in rodents as a healing factor after MI, whereas its role in healing and remodelling processes in humans remains unclear. We prospectively evaluated the relevance of FXIIIa after acute MI as a potential early prognostic marker for adequate healing.
Methods and results This monocentric prospective cohort study investigated cardiac remodelling in patients with ST-elevation MI and followed them up for 1 year. Serum FXIIIa was serially assessed during the first 9 days after MI and after 2, 6, and 12 months. Cardiac magnetic resonance imaging was performed within 4 days after MI (Scan 1), after 7 to 9 days (Scan 2), and after 12 months (Scan 3). The FXIII valine-to-leucine (V34L) single-nucleotide polymorphism rs5985 was genotyped. One hundred forty-six patients were investigated (mean age 58 ± 11 years, 13% women). Median FXIIIa was 118 % (quartiles, 102–132%) and dropped to a trough on the second day after MI: 109%(98–109%; P < 0.001). FXIIIa recovered slowly over time, reaching the baseline level after 2 to 6 months and surpassed baseline levels only after 12 months: 124 % (110–142%). The development of FXIIIa after MI was independent of the genotype. FXIIIa on Day 2 was strongly and inversely associated with the relative size of MI in Scan 1 (Spearman’s ρ = –0.31; P = 0.01) and Scan 3 (ρ = –0.39; P < 0.01) and positively associated with left ventricular ejection fraction: ρ = 0.32 (P < 0.01) and ρ = 0.24 (P = 0.04), respectively.
Conclusions FXIII activity after MI is highly dynamic, exhibiting a significant decline in the early healing period, with reconstitution 6 months later. Depressed FXIIIa early after MI predicted a greater size of MI and lower left ventricular ejection fraction after 1 year. The clinical relevance of these findings awaits to be tested in a randomized trial.