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- ItemLab::Measurement—A portable and extensible framework for controlling lab equipment and conducting measurements(Amsterdam : North Holland Publ. Co., 2019) Reinhardt, S.; Butschkow, C.; Geissler, S.; Dirnaichner, A.; Olbrich, F.; Lane, C.E.; Schröer, D.; Hüttel, A.K.Lab::Measurement is a framework for test and measurement automatization using Perl 5. While primarily developed with applications in mesoscopic physics in mind, it is widely adaptable. Internally, a layer model is implemented. Communication protocols such as IEEE 488 [1], USB Test & Measurement [2], or, e.g., VXI-11 [3] are addressed by the connection layer. The wide range of supported connection backends enables unique cross-platform portability. At the instrument layer, objects correspond to equipment connected to the measurement PC (e.g., voltage sources, magnet power supplies, multimeters, etc.). The high-level sweep layer automates the creation of measurement loops, with simultaneous plotting and data logging. An extensive unit testing framework is used to verify functionality even without connected equipment. Lab::Measurement is distributed as free and open source software. Program summary: Program Title: Lab::Measurement 3.660 Program Files doi: http://dx.doi.org/10.17632/d8rgrdc7tz.1 Program Homepage: https://www.labmeasurement.de Licensing provisions: GNU GPL v23 Programming language: Perl 5 Nature of problem: Flexible, lightweight, and operating system independent control of laboratory equipment connected by diverse means such as IEEE 488 [1], USB [2], or VXI-11 [3]. This includes running measurements with nested measurement loops where a data plot is continuously updated, as well as background processes for logging and control. Solution method: Object-oriented layer model based on Moose [4], abstracting the hardware access as well as the command sets of the addressed instruments. A high-level interface allows simple creation of measurement loops, live plotting via GnuPlot [5], and data logging into customizable folder structures. [1] F. M. Hess, D. Penkler, et al., LinuxGPIB. Support package for GPIB (IEEE 488) hardware, containing kernel driver modules and a C user-space library with language bindings. http://linux-gpib.sourceforge.net/ [2] USB Implementers Forum, Inc., Universal Serial Bus Test and Measurement Class Specification (USBTMC), revision 1.0 (2003). http://www.usb.org/developers/docs/devclass_docs/ [3] VXIbus Consortium, VMEbus Extensions for Instrumentation VXIbus TCP/IP Instrument Protocol Specification VXI-11 (1995). http://www.vxibus.org/files/VXI_Specs/VXI-11.zip [4] Moose—Apostmodern object system for Perl 5. http://moose.iinteractive.com [5] E. A. Merritt, et al., Gnuplot. An Interactive Plotting Program. http://www.gnuplot.info/ © 2018 The Author(s)
- ItemInteraction Network Analysis Using Semantic Similarity Based on Translation Embeddings(Berlin ; Heidelberg : Springer, 2019) Manzoor Bajwa, Awais; Collarana, Diego; Vidal, Maria-Esther; Acosta, Maribel; Cudré-Mauroux, Philippe; Maleshkova, Maria; Pellegrini, Tassilo; Sack, Harald; Sure-Vetter, YorkBiomedical knowledge graphs such as STITCH, SIDER, and Drugbank provide the basis for the discovery of associations between biomedical entities, e.g., interactions between drugs and targets. Link prediction is a paramount task and represents a building block for supporting knowledge discovery. Although several approaches have been proposed for effectively predicting links, the role of semantics has not been studied in depth. In this work, we tackle the problem of discovering interactions between drugs and targets, and propose SimTransE, a machine learning-based approach that solves this problem effectively. SimTransE relies on translating embeddings to model drug-target interactions and values of similarity across them. Grounded on the vectorial representation of drug-target interactions, SimTransE is able to discover novel drug-target interactions. We empirically study SimTransE using state-of-the-art benchmarks and approaches. Experimental results suggest that SimTransE is competitive with the state of the art, representing, thus, an effective alternative for knowledge discovery in the biomedical domain.
- ItemTemporal Role Annotation for Named Entities(Amsterdam [u.a.] : Elsevier, 2018) Koutraki, Maria; Bakhshandegan-Moghaddam, Farshad; Sack, Harald; Fensel, Anna; de Boer, Victor; Pellegrini, Tassilo; Kiesling, Elmar; Haslhofer, Bernhard; Hollink, Laura; Schindler, AlexanderNatural language understanding tasks are key to extracting structured and semantic information from text. One of the most challenging problems in natural language is ambiguity and resolving such ambiguity based on context including temporal information. This paper, focuses on the task of extracting temporal roles from text, e.g. CEO of an organization or head of a state. A temporal role has a domain, which may resolve to different entities depending on the context and especially on temporal information, e.g. CEO of Microsoft in 2000. We focus on the temporal role extraction, as a precursor for temporal role disambiguation. We propose a structured prediction approach based on Conditional Random Fields (CRF) to annotate temporal roles in text and rely on a rich feature set, which extracts syntactic and semantic information from text. We perform an extensive evaluation of our approach based on two datasets. In the first dataset, we extract nearly 400k instances from Wikipedia through distant supervision, whereas in the second dataset, a manually curated ground-truth consisting of 200 instances is extracted from a sample of The New York Times (NYT) articles. Last, the proposed approach is compared against baselines where significant improvements are shown for both datasets.
- ItemA Case for Integrated Data Processing in Large-Scale Cyber-Physical Systems(Maui, Hawaii : HICSS, 2019) Glebke, René; Henze, Martin; Wehrle, Klaus; Niemietz, Philipp; Trauth, Daniel; Mattfeld, Patrick; Bergs, Thomas; Bui, Tung X.Large-scale cyber-physical systems such as manufacturing lines generate vast amounts of data to guarantee precise control of their machinery. Visions such as the Industrial Internet of Things aim at making this data available also to computation systems outside the lines to increase productivity and product quality. However, rising amounts and complexities of data and control decisions push existing infrastructure for data transmission, storage, and processing to its limits. In this paper, we exemplarily study a fine blanking line which can produce up to 6.2 Gbit/s worth of data to showcase the extreme requirements found in modern manufacturing. We consequently propose integrated data processing which keeps inherently local and small-scale tasks close to the processes while at the same time centralizing tasks relying on more complex decision procedures and remote data sources. Our approach thus allows for both maintaining control of field-level processes and leveraging the benefits of “big data” applications.
- ItemFormalizing Gremlin pattern matching traversals in an integrated graph Algebra(Aachen, Germany : RWTH Aachen, 2019) Thakkar, Harsh; Auer, Sören; Vidal, Maria-Esther; Samavi, Reza; Consens, Mariano P.; Khatchadourian, Shahan; Nguyen, Vinh; Sheth, Amit; Giménez-García, José M.; Thakkar, HarshGraph data management (also called NoSQL) has revealed beneficial characteristics in terms of flexibility and scalability by differ-ently balancing between query expressivity and schema flexibility. This peculiar advantage has resulted into an unforeseen race of developing new task-specific graph systems, query languages and data models, such as property graphs, key-value, wide column, resource description framework (RDF), etc. Present-day graph query languages are focused towards flex-ible graph pattern matching (aka sub-graph matching), whereas graph computing frameworks aim towards providing fast parallel (distributed) execution of instructions. The consequence of this rapid growth in the variety of graph-based data management systems has resulted in a lack of standardization. Gremlin, a graph traversal language, and machine provide a common platform for supporting any graph computing sys-tem (such as an OLTP graph database or OLAP graph processors). In this extended report, we present a formalization of graph pattern match-ing for Gremlin queries. We also study, discuss and consolidate various existing graph algebra operators into an integrated graph algebra.
- ItemA survey on Bluetooth multi-hop networks(Amsterdam [u.a.] : Elsevier Science, 2019) Todtenberg, Nicole; Kraemer, RolfBluetooth was firstly announced in 1998. Originally designed as cable replacement connecting devices in a point-to-point fashion its high penetration arouses interest in its ad-hoc networking potential. This ad-hoc networking potential of Bluetooth is advertised for years - but until recently no actual products were available and less than a handful of real Bluetooth multi-hop network deployments were reported. The turnaround was triggered by the release of the Bluetooth Low Energy Mesh Profile which is unquestionable a great achievement but not well suited for all use cases of multi-hop networks. This paper surveys the tremendous work done on Bluetooth multi-hop networks during the last 20 years. All aspects are discussed with demands for a real world Bluetooth multi-hop operation in mind. Relationships and side effects of different topics for a real world implementation are explained. This unique focus distinguishes this survey from existing ones. Furthermore, to the best of the authors’ knowledge this is the first survey consolidating the work on Bluetooth multi-hop networks for classic Bluetooth technology as well as for Bluetooth Low Energy. Another individual characteristic of this survey is a synopsis of real world Bluetooth multi-hop network deployment efforts. In fact, there are only four reports of a successful establishment of a Bluetooth multi-hop network with more than 30 nodes and only one of them was integrated in a real world application - namely a photovoltaic power plant. © 2019 The Authors
- ItemBlood platelet enrichment in mass-producible surface acoustic wave (SAW) driven microfluidic chips(Cambridge : RSC, 2019) Richard, Cynthia; Fakhfouri, Armaghan; Colditz, Melanie; Striggow, Friedrich; Kronstein-Wiedemann, Romy; Tonn, Torsten; Medina-Sánchez, Mariana; Schmidt, Oliver G.; Gemming, Thomas; Winkler, AndreasThe ability to separate specific biological components from cell suspensions is indispensable for liquid biopsies, and for personalized diagnostics and therapy. This paper describes an advanced surface acoustic wave (SAW) based device designed for the enrichment of platelets (PLTs) from a dispersion of PLTs and red blood cells (RBCs) at whole blood concentrations, opening new possibilities for diverse applications involving cell manipulation with high throughput. The device is made of patterned SU-8 photoresist that is lithographically defined on the wafer scale with a new proposed methodology. The blood cells are initially focused and subsequently separated by an acoustic radiation force (ARF) applied through standing SAWs (SSAWs). By means of flow cytometric analysis, the PLT concentration factor was found to be 7.7, and it was proven that the PLTs maintain their initial state. A substantially higher cell throughput and considerably lower applied powers than comparable devices from literature were achieved. In addition, fully coupled 3D numerical simulations based on SAW wave field measurements were carried out to anticipate the coupling of the wave field into the fluid, and to obtain the resulting pressure field. A comparison to the acoustically simpler case of PDMS channel walls is given. The simulated results show an ideal match to the experimental observations and offer the first insights into the acoustic behavior of SU-8 as channel wall material. The proposed device is compatible with current (Lab-on-a-Chip) microfabrication techniques allowing for mass-scale, reproducible chip manufacturing which is crucial to push the technology from lab-based to real-world applications. © The Royal Society of Chemistry.
- ItemWhy reinvent the wheel: Let's build question answering systems together(New York City : Association for Computing Machinery, 2018) Singh, K.; Radhakrishna, A.S.; Both, A.; Shekarpour, S.; Lytra, I.; Usbeck, R.; Vyas, A.; Khikmatullaev, A.; Punjani, D.; Lange, C.; Vidal, Maria-Esther; Lehmann, J.; Auer, SörenModern question answering (QA) systems need to flexibly integrate a number of components specialised to fulfil specific tasks in a QA pipeline. Key QA tasks include Named Entity Recognition and Disambiguation, Relation Extraction, and Query Building. Since a number of different software components exist that implement different strategies for each of these tasks, it is a major challenge to select and combine the most suitable components into a QA system, given the characteristics of a question. We study this optimisation problem and train classifiers, which take features of a question as input and have the goal of optimising the selection of QA components based on those features. We then devise a greedy algorithm to identify the pipelines that include the suitable components and can effectively answer the given question. We implement this model within Frankenstein, a QA framework able to select QA components and compose QA pipelines. We evaluate the effectiveness of the pipelines generated by Frankenstein using the QALD and LC-QuAD benchmarks. These results not only suggest that Frankenstein precisely solves the QA optimisation problem but also enables the automatic composition of optimised QA pipelines, which outperform the static Baseline QA pipeline. Thanks to this flexible and fully automated pipeline generation process, new QA components can be easily included in Frankenstein, thus improving the performance of the generated pipelines.
- ItemHi Doppelgänger: Towards Detecting Manipulation in News Comments(New York City : Association for Computing Machinery, 2019) Pennekamp, Jan; Henze, Martin; Hohlfeld, Oliver; Panchenko, AndriyPublic opinion manipulation is a serious threat to society, potentially influencing elections and the political situation even in established democracies. The prevalence of online media and the opportunity for users to express opinions in comments magnifies the problem. Governments, organizations, and companies can exploit this situation for biasing opinions. Typically, they deploy a large number of pseudonyms to create an impression of a crowd that supports specific opinions. Side channel information (such as IP addresses or identities of browsers) often allows a reliable detection of pseudonyms managed by a single person. However, while spoofing and anonymizing data that links these accounts is simple, a linking without is very challenging. In this paper, we evaluate whether stylometric features allow a detection of such doppelgängers within comment sections on news articles. To this end, we adapt a state-of-the-art doppelgänger detector to work on small texts (such as comments) and apply it on three popular news sites in two languages. Our results reveal that detecting potential doppelgängers based on linguistics is a promising approach even when no reliable side channel information is available. Preliminary results following an application in the wild shows indications for doppelgängers in real world data sets.
- ItemDoMoRe – A recommender system for domain modeling(Setúbal : SciTePress, 2018) Agt-Rickauer, Henning; Kutsche, Ralf-Detlef; Sack, Harald; Hammoudi, Slimane; Ferreira Pires, Luis; Selic, BranDomain modeling is an important activity in early phases of software projects to achieve a shared understanding of the problem field among project participants. Domain models describe concepts and relations of respective application fields using a modeling language and domain-specific terms. Detailed knowledge of the domain as well as expertise in model-driven development is required for software engineers to create these models. This paper describes DoMoRe, a system for automated modeling recommendations to support the domain modeling process. We describe an approach in which modeling benefits from formalized knowledge sources and information extraction from text. The system incorporates a large network of semantically related terms built from natural language data sets integrated with mediator-based knowledge base querying in a single recommender system to provide context-sensitive suggestions of model elements.