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Enhancing the OGC WPS interface with GeoPipes support for real-time geoprocessing

International Journal of Digital Earth 2018年第1期11卷 48-63页

作者： Stefan Herle Jörg Blankenbach Geodetic Institute and Chair for Computing in Civil Engineering and Geo Information Systems RWTH Aachen UniversityAachenGermany

Real-time geospatial information is used in various applications such as risk management or alerting ***,the rise of new sensing technologies also increases the demand for processing the data in real ***’s spatial data infrastructures,however,do not meet the requirements for real-time *** OpenGIS®Web Processing Service(WPS)is not designed to process real-time *** has some major drawbacks in asynchronous processing and cannot handle(geo)data streams out of the *** previous papers,we introduced the GeoPipes approach to share spatiotemporal data in real *** implemented the concept extending the Message Queue and Telemetry Transport(MQTT)protocol by a spatial and temporal dimension,which we call *** this paper,we demonstrate the integration of the GeoPipes idea in the WPS interface to expose standardized real-time geoprocessing *** proof of the concept is illustrated in some exemplary real-time geo processes.

关键词： Real-time geoprocessing web processing service sensor web Internet-ofthings GeoPipes

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Machine Learning Based Cybersecurity Threat Detection for Secure IoT Assisted Cloud Environment

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Computer Systems Science & engineering 2023年第10期47卷 855-871页

作者： Z.Faizal Khan Saeed M.Alshahrani Abdulrahman Alghamdi Someah Alangari Nouf Ibrahim Altamami Khalid A.Alissa Sana Alazwari Mesfer Al Duhayyim Fahd N.Al-Wesabi Department of Computer Engineering College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Science College of Science and Humanities DawadmiShaqra UniversityShaqraSaudi Arabia Department of Mathematics College of EducationShaqra UniversityShaqraSaudi Arabia Saudi Aramco Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAlaflaj16828Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia

The Internet of Things(IoT)is determine enormous economic openings for industries and allow stimulating innovation which obtain between domains in childcare for eldercare,in health service to energy,and in developed to *** develops a difficult problem in IoT platform whereas the presence of cyber-attack requires that *** progress of automatic devices for cyber-attack classifier and detection employing Artificial Intelligence(AI)andMachine Learning(ML)devices are crucial fact to realize security in IoT *** can be required for minimizing the issues of security based on IoT devices ***,this research proposal establishes novel mayfly optimized with Regularized Extreme Learning Machine technique called as MFO-RELM model for Cybersecurity Threat classification and detection fromthe cloud and IoT *** proposed MFORELM model provides the effective detection of cybersecurity threat which occur in the cloud and IoT *** accomplish this,the MFO-RELM technique pre-processed the actual cloud and IoT data as to meaningful ***,the proposed models will receive the pre-processing data and carry out the classifier *** boosting the efficiency of the proposed models,theMFOtechnique was utilized to *** experiential outcome of the proposed technique was tested utilizing the standard CICIDS 2017 dataset,and the outcomes are examined under distinct aspects.

关键词： Mayfly optimization machine learning artificial intelligence cybersecurity threat detection

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Comparing ensemble methods combined with different aggregating models using micrograph cell segmentation as an initial application example

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Journal of Pathology Informatics 2023年 14卷 100304-100304页

作者： Göb, St. Sawant, S. Erick, F.X. Schmidkonz, C. Ramming, A. Lang, E.W. Wittenberg, T. Götz, Th.I. Fraunhofer Institute for Integrated Circuits IIS Erlangen Germany Chair of Visual Computing Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Department of Nuclear Medicine Friedrich-Alexander-Universität Erlangen-Nürnberg and University Hospital Erlangen Erlangen Germany Department of Internal Medicine University Hospital Erlangen Erlangen Germany CIML Group Biophysics University of Regensburg Regensburg Germany Department of Industrial Engineering and Health Technical University of Applied Sciences Amberg-Weiden Weiden Germany

Strategies such as ensemble learning and averaging techniques try to reduce the variance of single deep neural networks. The focus of this study is on ensemble averaging techniques, fusing the results of differently initialized and trained networks. Thereby, using micrograph cell segmentation as an application example, various ensembles have been initialized and formed during network training, whereby the following methods have been applied: (a) random seeds, (b) L₁-norm pruning, (c) variable numbers of training examples, and (d) a combination of the latter 2 items. Furthermore, different averaging methods are in common use and were evaluated in this study. As averaging methods, the mean, the median, and the location parameter of an alpha-stable distribution, fit to the histograms of class membership probabilities (CMPs), as well as a majority vote of the members of an ensemble were considered. The performance of these methods is demonstrated and evaluated on a micrograph cell segmentation use case, employing a common state-of-the art deep convolutional neural network (DCNN) architecture exploiting the principle of the common VGG-architecture. The study demonstrates that for this data set, the choice of the ensemble averaging method only has a marginal influence on the evaluation metrics (accuracy and Dice coefficient) used to measure the segmentation performance. Nevertheless, for practical applications, a simple and fast estimate of the mean of the distribution is highly competitive with respect to the most sophisticated representation of the CMP distributions by an alpha-stable distribution, and hence seems the most proper ensemble averaging method to be used for this application. © 2023 The Authors

关键词： Alpha-stable function Cell segmentation Combine ensembles Deep neural networks

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Automated wireless structural health monitoring and control using tuned liquid column dampers 7

Automated wireless structural health monitoring and control ...

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7th International Conference on Computational Methods in Structural Dynamics and Earthquake engineering, COMPDYN 2019

作者： Dragos, Kosmas Manolis, Georgios D. Smarsly, Kay Chair of Computing in Civil Engineering Bauhaus University Weimar Coudraystrasse 7 Weimar99423 Germany Laboratory of Experimental Mechanics Department of Civil Engineering Aristotle University of Thessaloniki University Campus Thessaloniki54124 Greece

ISBN: (纸本)9786188284463

Current trends in structural design and retrofit frequently dictate artificially modifying the structural behavior in an attempt to target unfavorable loading scenarios expected to compromise the fulfilment of stability and serviceability criteria. Particularly in structures where operational requirements result in adopting unconventional structural systems, usually falling outside the scope of codified regulations and guidelines, adapting the structural behavior by means of structural subsystems has been widespread. Referred to as "structural control", enhancing the ability of structures to adapt to unfavorable loading conditions encompasses attaching structural subsystems, such as dampers, to the main structure. Moreover, the increasing application of structural health monitoring (SHM) for structural assessment and maintenance has fueled research in coupling SHM with structural control, thus paving the way for developing structural systems capable of autonomously adapting structural properties. In this context, this paper describes a preliminary approach to automated structural health monitoring and control by coupling a wireless SHM system with a tuned liquid column damper (TLCD). The wireless SHM system is equipped with embedded algorithms managing SHM tasks, such as data sampling and data processing, and with actuators able to modify the properties of the TLCD based on any user-defined control algorithm. The proposed approach serves as a first step towards fully automated structural health monitoring and control and is validated through laboratory tests on a four-story shear frame structure equipped with a wireless SHM system and a TLCD on the top story. Copyright © 2019 COMPDYN Proceedings. All rights reserved.

关键词： Wireless sensor networks

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Robustness evaluation of cutting tool maintenance planning for soft ground tunneling projects

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Underground Space 2018年第1期3卷 72-85页

作者： Alena Conrads Markus Scheffer Markus Konig Markus Thewes Inastitute of Tunneling cand Construction Management Ruhr-Universitat BochunGermany Chair of Computing in Engineering Ruhr-Universitit BochunGermany

Tunnel boring machines require extensive maintenance and inspection effort to provide a high *** cutting tools of the cutting wheel must be changed timely upon reaching a critical *** one possible maintenance strategy is to change tools only when it is absolutely necessary,tools can also be changed preventively to avoid further *** different maintenance strategies inﬂuence the maintenance duration and the overall project ***,determine downtime related to a particular mainte-nance strategy is still a challenging *** paper shows an analysis of the robustness to achieve the planned project performance of a maintenance strategy considering uncertainties of wear behavior of the cutting tools.A simulation based analysis is presented,imple-menting an empirical wear prediction *** strategies of maintenance planning are compared by performing a parameter vari-ation study including Monte-Carlo *** maintenance costs are calculated and evaluated with respect to their ***,an improved and robust maintenance strategy has been determined.

关键词： Mechanized tunneling,Maintenance Wear of cutting tools Process simulation Robustness Uncertainty modeling

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MassSpecGym: a benchmark for the discovery and identification of molecules 24

MassSpecGym: a benchmark for the discovery and identificatio...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Roman Bushuiev Anton Bushuiev Niek F. de Jonge Adamo Young Fleming Kretschmer Raman Samusevich Janne Heirman Fei Wang Luke Zhang Kai Dührkop Marcus Ludwig Nils A. Haupt Apurva Kalia Corinna Brungs Robin Schmid Russell Greiner Bo Wang David S. Wishart Li-Ping Liu Juho Rousu Wout Bittremieux Hannes Rost Tytus D. Mak Soha Hassoun Florian Huber Justin J.J. van der Hooft Michael A. Stravs Sebastian Böcker Josef Sivic Tomáš Pluskal Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Bioinformatics Group Wageningen University & Research Department of Computer Science University of Toronto Chair for Bioinformatics Institute for Computer Science Friedrich Schiller University Jena Department of Computer Science University of Antwerp Department of computing science University of Alberta and Alberta Machine Intelligence Institute Department of Molecular Genetics University of Toronto Bright Giant GmbH Department of Computer Science Tufts University Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences Department of computing science and Department of Biological Sciences University of Alberta Department of Computer Science Aalto University Mass Spectrometry Data Center National Institute of Standards and Technology Department of Computer Science and Department of Chemical and Biological Engineering Tufts University Centre for Digitalisation and Digitality University of Applied Sciences Düsseldorf Bioinformatics Group Wageningen University & Research and Department of Biochemistry University of Johannesburg Eawag: Swiss Federal Institute of Aquatic Science and Technology

ISBN: (纸本)9798331314385

The discovery and identification of molecules in biological and environmental samples is crucial for advancing biomedical and chemical sciences. Tandem mass spectrometry (MS/MS) is the leading technique for high-throughput elucidation of molecular structures. However, decoding a molecular structure from its mass spectrum is exceptionally challenging, even when performed by human experts. As a result, the vast majority of acquired MS/MS spectra remain uninterpreted, thereby limiting our understanding of the underlying (bio)chemical processes. Despite decades of progress in machine learning applications for predicting molecular structures from MS/MS spectra, the development of new methods is severely hindered by the lack of standard datasets and evaluation protocols. To address this problem, we propose MassSpecGym - the first comprehensive benchmark for the discovery and identification of molecules from MS/MS data. Our benchmark comprises the largest publicly available collection of high-quality labeled MS/MS spectra and defines three MS/MS annotation challenges: de novo molecular structure generation, molecule retrieval, and spectrum simulation. It includes new evaluation metrics and a generalization-demanding data split, therefore standardizing the MS/MS annotation tasks and rendering the problem accessible to the broad machine learning community. MassSpecGym is publicly available at https://***/pluskal-lab/MassSpecGym.

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Deriving QoE in systems: from fundamental relationships to a QoE-based Service-level Quality Index

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Quality and User Experience 2020年第1期5卷 1-17页

作者： Hoßfeld, Tobias Heegaard, Poul E. Skorin-Kapov, Lea Varela, Martín University of Würzburg Chair of Communication Networks Würzburg Germany NTNU - Norwegian University of Science and Technology Department of Information Security and Communication Technology Trondheim Norway University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia Profilence Oulu Finland

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.

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An Ultra Broadband Multi-Tone Six-Port Radar for Distance Measurements in K-Band Waveguides

An Ultra Broadband Multi-Tone Six-Port Radar for Distance Me...

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IEEE Radio and Wireless Symposium (RWS formerly RAWCON)

作者： Simon Heining Fabian Michler Benedict Scheiner Emadeldeen Hassan Alexander Koelpin Robert Weigel Fabian Lurz Institute for Electronics Engineering Friedrich-Alexander University Erlangen-Nuremberg Erlangen Germany Department of Computing Science Umeå University Umeå Sweden Chair for Electronics and Sensor Systems Brandenburg University of Technology Cottbus Germany

ISBN: (数字)9781728111209

ISBN: (纸本)9781728111216

Continuous wave (CW) radars show an excellent performance in high precision distance measurements. However, when it comes to absolute distances, the ambiguity of these systems is a notable issue. To extend the unambigous range beyond λ/2, dual tone systems have been presented using two spaced CW measurements. In this paper, a broadband multi-tone radar operating in the K-band using six-port technology is presented. By using more than two frequencies, the unambigous range can be further enlarged. The radar system presented in this paper is able to perform 5-FSK measurements within a bandwidth of 5.5GHz delivering an update rate of 25Hz and a precision of 37.96μm.

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Preliminary study on the spread of air-borne pollutants in urban environment: a CFD simulation approach

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Scientific reports 2025年第1期15卷 18836页

作者： Fatma Ahmad Debjit Majumder Rabs Ranjit Aman Gupta Michael Manhart Chair of Computing in Civil Engineering and Geoinformation Systems and Geodetic Institute RWTH Aachen University Aachen Germany. fatma.ahmad@gia.rwth-aachen.de. School of Engineering and Design Technical University of Munich Munich Germany. Institute of Geography School of Geosciences University of Edinburgh Edinburgh UK. aman.gupta@ed.ac.uk. Department of Architecture and Planning Indian Institute of Engineering Science and Technology Shibpur India. aman.gupta@ed.ac.uk.

The spreading of pollutants within urban areas, particularly from traffic emissions, poses a significant health risk. Computational Fluid Dynamics (CFD) has emerged as a key tool in understanding how pollutants spread within a city. In particular, the large-eddy simulation (LES) approach allows us to capture the complex time-dependent behaviour of the 3D flow field due to buildings in a dense urban environment. This work utilizes the CFD tool MGLET (Multi Grid Large Eddy Turbulence) to model the transport of pollutants within a selected domain in Munich city. MGLET offers a feature of simulating transport of multiple passive scalar quantities simultaneously. This facilitates the individual analysis of emissions from each major street in the domain of interest, providing detailed insights into their respective impacts. Additionally, MGLET utilizes the Immersed Boundary Method to resolve 3D building geometries, removing the need to generate body-fitted grids, which tends to be highly time-consuming. The streets are defined by area sources, and the emission rates for each street are defined by the average traffic flow rate. This high-fidelity approach offers a detailed analysis, allowing us to identify local features such as recirculation zones in street canyons and pinpoint the streets that contribute most significantly to pollution at specific locations. The insights from CFD studies can empower policymakers to craft legislation tailored to local pollution control efforts, thus enhancing the quality of life in urban areas. Ultimately, the accurate prediction of pollutant concentration is critical, as it directly impacts the health and well-being of urban residents, highlighting the urgent need for effective pollution control measures.

关键词： Air quality Computational fluid dynamics Large eddy simulation Wind simulation

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An implementation and evaluation of large-scale multi-user human–robot collaboration with head-mounted augmented reality

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Advanced engineering Informatics 2025年 67卷

作者： Xiliu Yang Felix Amtsberg Benjamin Kaiser Lior Skoury Tim Stark Simon Treml Nils Opgenorth Aimée Sousa Calepso Michael Sedlmair Thomas Wortmann Alexander Verl Achim Menges Institute for Computational Design and Construction (ICD) University of Stuttgart Germany Cluster of Excellence Integrative Computational Design and Construction for Architecture (IntCDC) University of Stuttgart Germany Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Germany Institute for Computational Design and Construction Chair of Computing in Architecture (ICD-CA) University of Stuttgart Germany Visualization Research Center (VISUS) University of Stuttgart Germany

Human–robot collaboration (HRC) offers promising potential for more flexible and sustainable production practices in architecture and construction. This requires HRC setups to scale up from light-payload collaborative robots to conform with the scale of building construction while considering the safety and teamwork culture for workers. This research proposes a system for large-scale multi-user HRC using head-mounted augmented reality (AR) devices. To achieve this, we contribute three methods that work in conjunction: (1) an AR system that enables multiple users to share tasks and work together with robots; (2) a dynamic human task allocation engine that reacts to the changing production teams and task types; and (3) a safety zone generation and allocation method to configure human collaboration in shared space with large-scale robots. The system is evaluated using a case study of prefabricated timber cassettes combining discrete event simulations, a user study and a fabrication process demonstrator with an industry partner.

关键词： Human–robot collaboration Augmented reality Robotic fabrication Timber prefabrication Co-design

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