Towards Inertial Sensor-Based Position Estimation in Bouldering

For some years, inertial sensors have become increasingly popular in various sports applications due to their small size and weight. However – due to the problem of sensor drift – additional sensors are usually required to obtain reliable position estimates. In this paper, we present an approach for position estimation in bouldering that relies solely on inertial sensors and domain knowledge that is modeled as a virtual sensor.Seit einigen Jahren erfreuen sich Inertialsensoren aufgrund ihrer geringen Größe und ihres geringen Gewichts zunehmender Beliebtheit in verschiedenen Sportanwendungen. Aufgrund des Problems des Sensordrifts sind jedoch in der Regel zusätzliche Sensoren erforderlich, um zuverlässige Positionsschätzungen zu erhalten. In diesem Beitrag stellen wir einen Ansatz zur Positionsschätzung beim Bouldern vor, der sich ausschließlich auf Inertialsensoren und Domänenwissen stützt, welches als virtueller Sensor modelliert wird

(A) Vision for 2050 - Context-Based Image Understanding for a Human-Robot Soccer Match

We believe it is possible to create the visual subsystem needed for the RoboCup 2050 challenge - a soccer match between humans and robots - within the next decade.  In this position paper, we argue, that the basic techniques are available, but the main challenge will be to achieve the necessary robustness. We propose to address this challenge through the use of probabilistically modeled context, so for instance a visually indistinct circle is  accepted as the ball, if it fits well with the ball's motion model and vice versa.Our vision is accompanied by a sequence of (partially already conducted) experiments for its verification.  In these experiments, a human soccer player carries a helmet with a camera and an inertial sensor and the vision system has to extract all information from that data, a humanoid robot would need to take the human's place

Calculation of 3D genome structures for comparison of chromosome conformation capture experiments with microscopy: An evaluation of single-cell Hi-C protocols.

Single-cell chromosome conformation capture approaches are revealing the extent of cell-to-cell variability in the organization and packaging of genomes. These single-cell methods, unlike their multi-cell counterparts, allow straightforward computation of realistic chromosome conformations that may be compared and combined with other, independent, techniques to study 3D structure. Here we discuss how single-cell Hi-C and subsequent 3D genome structure determination allows comparison with data from microscopy. We then carry out a systematic evaluation of recently published single-cell Hi-C datasets to establish a computational approach for the evaluation of single-cell Hi-C protocols. We show that the calculation of genome structures provides a useful tool for assessing the quality of single-cell Hi-C data because it requires a self-consistent network of interactions, relating to the underlying 3D conformation, with few errors, as well as sufficient longer-range cis- and trans-chromosomal contacts

Benchmarking robot cooperation without pre-coordination in the RoboCup Standard Platform League drop-in player competition

Abstract — The Standard Platform League is one of the main competitions of the annual RoboCup world championships. In this competition, teams of five humanoid robots play soccer against each other. In 2014, the league added a new sub-competition which serves as a testbed for cooperation without pre-coordination: the Drop-in Player Competition. Instead of homogeneous robot teams that are each programmed by the same people and hence implicitly pre-coordinated, this competition features ad hoc teams, i. e. teams that consist of robots originating from different RoboCup teams and that are each running different software. In this paper, we provide an overview of this competition, including its motivation and rules. We then present and analyze the results of the 2014 competition, which gathered robots from 23 teams, involved at least 50 human participants, and consisted of fifteen 20-minute games for a total playing time of 300 minutes. We also suggest improvements for future iterations, many of which will be evaluated at RoboCup 2015. I

A SIEM Architecture for Advanced Anomaly Detection

Dramatic increases in the number of cyber security attacks and breaches toward businesses and organizations have been experienced in recent years. The negative impacts of these breaches not only cause the stealing and compromising of sensitive information, malfunctioning of network devices, disruption of everyday operations, financial damage to the attacked business or organization itself, but also may navigate to peer businesses/organizations in the same industry. Therefore, prevention and early detection of these attacks play a significant role in the continuity of operations in IT-dependent organizations. At the same time detection of various types of attacks has become extremely difficult as attacks get more sophisticated, distributed and enabled by Artificial Intelligence (AI). Detection and handling of these attacks require sophisticated intrusion detection systems which run on powerful hardware and are administered by highly experienced security staff. Yet, these resources are costly to employ, especially for small and medium-sized enterprises (SMEs). To address these issues, we developed an architecture -within the GLACIER project- that can be realized as an in-house operated Security Information Event Management (SIEM) system for SMEs. It is affordable for SMEs as it is solely based on free and open-source components and thus does not require any licensing fees. Moreover, it is a Self-Contained System (SCS) and does not require too much management effort. It requires short configuration and learning phases after which it can be self-contained as long as the monitored infrastructure is stable (apart from a reaction to the generated alerts which may be outsourced to a service provider in SMEs, if necessary). Another main benefit of this system is to supply data to advanced detection algorithms, such as multidimensional analysis algorithms, in addition to traditional SIEMspecific tasks like data collection, normalization, enrichment, and storage. It supports the application of novel methods to detect security-related anomalies. The most distinct feature of this system that differentiates it from similar solutions in the market is its user feedback capability. Detected anomalies are displayed in a Graphical User Interface (GUI) to the security staff who are allowed to give feedback for anomalies. Subsequently, this feedback is utilized to fine-tune the anomaly detection algorithm. In addition, this GUI also provides access to network actors for quick incident responses. The system in general is suitable for both Information Technology (IT) and Operational Technology (OT) environments, while the detection algorithm must be specifically trained for each of these environments individually

A software framework for analysing solid-state MAS NMR data

Solid-state magic-angle-spinning (MAS) NMR of proteins has undergone many rapid methodological developments in recent years, enabling detailed studies of protein structure, function and dynamics. Software development, however, has not kept pace with these advances and data analysis is mostly performed using tools developed for solution NMR which do not directly address solid-state specific issues. Here we present additions to the CcpNmr Analysis software package which enable easier identification of spinning side bands, straightforward analysis of double quantum spectra, automatic consideration of non-uniform labelling schemes, as well as extension of other existing features to the needs of solid-state MAS data. To underpin this, we have updated and extended the CCPN data model and experiment descriptions to include transfer types and nomenclature appropriate for solid-state NMR experiments, as well as a set of experiment prototypes covering the experiments commonly employed by solid-sate MAS protein NMR spectroscopists. This work not only improves solid-state MAS NMR data analysis but provides a platform for anyone who uses the CCPN data model for programming, data transfer, or data archival involving solid-state MAS NMR data

Structure calculation, refinement and validation using CcpNmr Analysis

CcpNmr Analysis provides a streamlined pipeline for both NMR chemical shift assignment and structure determination of biological macromolecules. In addition, it encompasses tools to analyse the many additional experiments that make NMR such a pivotal technique for research into complex biological questions. This report describes how CcpNmr Analysis can seamlessly link together all of the tasks in the NMR structure-determination process. It details each of the stages from generating NMR restraints [distance, dihedral,hydrogen bonds and residual dipolar couplings (RDCs)],exporting these to and subsequently re-importing them from structure-calculation software (such as the programs CYANA or ARIA) and analysing and validating the results obtained from the structure calculation to, ultimately, the streamlined deposition of the completed assignments and the refined ensemble of structures into the PDBe repository. Until recently, such solution-structure determination by NMR has been quite a laborious task, requiring multiple stages and programs. However, with the new enhancements to CcpNmr Analysis described here, this process is now much more intuitive and efficient and less error-prone

Bacterial Genome Partitioning: N-Terminal Domain of IncC Protein Encoded by Broad-Host-Range Plasmid RK2 Modulates Oligomerisation and DNA Binding

ParAWalker ATPases form part of the machinery that promotes better-thanrandom segregation of bacterial genomes. ParA proteins normally occur in one of two forms, differing by their N-terminal domain (NTD) of approximately 100 aa, which is generally associated with site-specific DNA binding. Unusually, and for as yet unknown reasons, parA (incC) of IncP-1 plasmids is translated from alternative start codons producing two forms, IncC1 (364 aa) and IncC2 (259 aa), whose ratio varies between hosts.IncC2 could be detected as an oligomeric form containing dimers, tetramers and octamers, but the N-terminal extension present in IncC1 favours nucleotide-stimulated dimerisation as well as high-affinity and ATPdependent non-specific DNA binding. The IncC1 NTD does not dimerise or bind DNA alone, but it does bind IncC2 in the presence of nucleotides. Mixing IncC1 and IncC2 improved polymerisation and DNA binding. Thus,the NTD may modulate the polymerisation interface, facilitating polymerisation/ depolymerisation and DNA binding, to promote the cycle that drives partitioning