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The end-to-end connectivity patterns between two points on Earth are highly volatile if mediated via a Low-Earth orbit (LEO) satellite constellation. This is rooted in the enormous speeds at which satellites in LEO must travel relative to the Earth's surface. While changes in end-to-end routes are rare events in stationary and terrestrial applications, they are a dominating factor for connection-oriented services running over LEO constellations and mega-constellations. This paper discusses how TCP-over-constellations is affected by the need for rerouting and how orbital route selection algorithms impact the end-to-end performance of communication. In contrast to the state of the art that primarily optimizes for instantaneous shortest routes (i.e. lowest delay), we propose several algorithms that have route stability and longevity in their focus. We show that this shift in focus comes with vastly improved end-to-end communication performance, and we discuss peculiar effects of the typical TCP-like implementations, taking inspiration from the Starlink constellation in our empirical investigations. The spectrum of algorithms proposed provides a basis for co-designing suitable orbital route selection algorithms and tailored transport control algorithms., Comment: 2024 IEEE International Conference on Communications Workshops (ICC Workshops), Denver, CO, USA, 2024, pp. 1708-1713

We present a case study on the strategic planning of a security operations center in a typical, modern, mid-size organization. Against the backdrop of the company's multi-cloud strategy a distributed approach envisioning the involvement of external providers is taken. From a security-centric abstraction of the organizational IT-landscape, a novel strategic planning method for security operation centers is developed with an adaptable relationship matrix as core tool. The method is put to a practical test in modeling different levels of engagement of external providers in the center's operation. It is shown that concrete output, such as a core statement of work for an external provider, can easily be derived.

Machine Learning~(ML) has provided promising results in recent years across different applications and domains. However, in many cases, qualities such as reliability or even safety need to be ensured. To this end, one important aspect is to determine whether or not ML components are deployed in situations that are appropriate for their application scope. For components whose environments are open and variable, for instance those found in autonomous vehicles, it is therefore important to monitor their operational situation to determine its distance from the ML components' trained scope. If that distance is deemed too great, the application may choose to consider the ML component outcome unreliable and switch to alternatives, e.g. using human operator input instead. SafeML is a model-agnostic approach for performing such monitoring, using distance measures based on statistical testing of the training and operational datasets. Limitations in setting SafeML up properly include the lack of a systematic approach for determining, for a given application, how many operational samples are needed to yield reliable distance information as well as to determine an appropriate distance threshold. In this work, we address these limitations by providing a practical approach and demonstrate its use in a well known traffic sign recognition problem, and on an example using the CARLA open-source automotive simulator.

Since data is often stored in different sources, it needs to be integrated to gather a global view that is required in order to create value and derive knowledge from it. A critical step in data integration is schema matching which aims to find semantic correspondences between elements of two schemata. In order to reduce the manual effort involved in schema matching, many solutions for the automatic determination of schema correspondences have already been developed. In this paper, we propose a novel end-to-end approach for schema matching based on neural embeddings. The main idea is to use a two-step approach consisting of a table matching step followed by an attribute matching step. In both steps we use embeddings on different levels either representing the whole table or single attributes. Our results show that our approach is able to determine correspondences in a robust and reliable way and compared to traditional schema matching approaches can find non-trivial correspondences., Comment: Accepted to the 2nd International Workshop on Applied AI for Database Systems and Applications (AIDB'20), August 31, 2020, Tokyo, Japan

We describe a new method for pulsed spin order transfer (SOT) of parahydrogen induced polarization (PHIP) that enables close to 100 % polarization in incompletely 2H-labeled molecules by exciting only the desired protons in a frequency-selective manner. While a selective pulse (SP) on 1H at the beginning of pulsed SOT had been considered before, using SPs during the SOT suppresses undesired indirect spin-spin interactions. As a result, we achieved a more robust SOT for the SP variants of the phINEPT+ sequence that we refer to as phSPINEPT+. Thereby, for the first time, we report a sequence that is effective for all weakly coupled spin systems. Our simulations show that the method converts close to 100 % of the parahydrogen-derived spin order into 13C hyperpolarization in weakly coupled three-spin systems and partially or fully 2H-labeled molecules if relaxation is neglected. Experimentally we demonstrate high hyperpolarization of 13C with 15.8 % for 1-13C-hydroxyethyl propionate-d3 and 12.6 % for 1-13C-ethyl acetate-d6, which corresponds to ~47 % and ~38 % if the enrichment of parahydrogen had been 100 %. Even in non-2H-labeled molecules, a remarkable 13C polarization is achieved, e.g. up to 20 % were simulated for 100 % pH2, and 1.25 % were obtained experimentally for 1-13C-ethyl pyruvate and 50 % pH2, which can be further improved by faster hydrogenation. As a result, full deuterium labeling may no longer be required e.g., when new PHIP agents are investigated, the synthesis of fully deuterated molecules is too complex, or when a kinetic isotope effect regarding the metabolic conversion rate of an agent is to be avoided. Using SPs during SOT seems very promising and may be extended to other sequences in the context of PHIP and be-yond to make them less prone to experimental imperfections or real molecular environments., Comment: 7 pages, 3 figures and supporting materials

In order to create cooperating swarms of Unmanned Autonomous Vehicles (UAVs) that also interact with various other systems and devices, open and free communication systems are mandatory. This paper presents an implementation of such a communication system to incorporate the Crazyflie nano-drone as a UAV platform. The protocol stack leverages the open Predictably Reliable Real-time Transport (PRRT) protocol that adds latency-awareness and -predictability to stacks composed of standard Internet protocols. To enable the drone to receive and reply to control commands via Wi-Fi, it has been extended with a Raspberry Pi that runs two variants of the Crazybridge---a software to connect the control board to the network. To evaluate how practical this solution is for the use in control applications, the communication has been analysed with a focus on the latency properties. Our investigations show that despite using the open protocol stack---and hence opting out of specialised implementations---the resulting latencies are in the same order of magnitude (4 to 9 ms) as the latency of the proprietary link.

We present anisotropic "separate universe" simulations which modify the N-body code Gadget-4 in order to represent a large-scale tidal field through an anisotropic expansion factor. These simulations are used to measure the linear, quasi-linear and nonlinear response of the matter power spectrum to a spatially uniform trace-free tidal field up to wavenumber $k = 7 h \text{Mpc}^{-1}$. Together with the response to a large-scale overdensity measured in previous work, this completely describes the nonlinear matter bispectrum in the squeezed limit. We find that the response amplitude does not approach zero on small scales in physical coordinates, but rather a constant value at $z=0$, $R_K\approx 0.5$ for $k \geq 3 h\text{Mpc}^{-1}$ up to the scale where we consider our simulations reliable, $k \leq 7 h\text{Mpc}^{-1}$ at $z=0$. This shows that even the inner regions of haloes are affected by the large-scale tidal field. We also measure directly the alignment of halo shapes with the tidal field, finding a clear signal which increases with halo mass., Comment: 19 pages, 9 figures

The typical approach for learned DBMS components is to capture the behavior by running a representative set of queries and use the observations to train a machine learning model. This workload-driven approach, however, has two major downsides. First, collecting the training data can be very expensive, since all queries need to be executed on potentially large databases. Second, training data has to be recollected when the workload and the data changes. To overcome these limitations, we take a different route: we propose to learn a pure data-driven model that can be used for different tasks such as query answering or cardinality estimation. This data-driven model also supports ad-hoc queries and updates of the data without the need of full retraining when the workload or data changes. Indeed, one may now expect that this comes at a price of lower accuracy since workload-driven models can make use of more information. However, this is not the case. The results of our empirical evaluation demonstrate that our data-driven approach not only provides better accuracy than state-of-the-art learned components but also generalizes better to unseen queries.

The continuously increasing degree of automation in many areas (e.g. manufacturing engineering, public infrastructure) lead to the construction of cyber-physical systems and cyber-physical networks. To both, time and energy are the most critical operating resources. Considering for instance the Tactile Internet specification, end-to-end latencies in these systems must be below 1ms, which means that both communication and system latencies are in the same order of magnitude and must be predictably low. As control loops are commonly handled over different variants of network infrastructure (e.g. mobile and fibre links) particular attention must be payed to the design of reliable, yet fast and energy-efficient data-transmission channels that are robust towards unexpected transmission failures. As design goals are often conflicting (e.g. high performance vs. low energy), it is necessary to analyze and investigate trade-offs with regards to design decisions during the construction of cyber-physical networks. In this paper, we present $\Delta$elta, an approach towards a tool-supported construction process for cyber-physical networks. $\Delta$elta extends the previously presented X-Lap tool by new analysis features, but keeps the original measurements facilities unchanged. $\Delta$elta jointly analyzes and correlates the runtime behavior (i.e. performance, latency) and energy demand of individual system components. It provides an automated analysis with precise thread-local time interpolation, control-flow extraction, and examination of latency criticality. We further demonstrate the applicability of $\Delta$elta with an evaluation of a prototypical implementation.