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Search results for: NATURAL LANGUAGE PROCESSING, LARGE LANGUAGE MODELS, DATA MINING, QUANTUM PHYSICS
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MODALITY corpus - SPEAKER 17 - SEQUENCE S6
Open Research DataThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 17 - SEQUENCE S1
Open Research DataThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland
Publication“The Image of the City” by Kevin Lynch is a landmark planning theory of lasting influence; its scientific rigor and relevance in the digital age were in dispute. The rise of social media and other digital technologies offers new opportunities to study the perception of urban environments. Questions remain as to whether social media analytics can provide a reliable measure of perceived city images? If yes, what implication does...
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Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
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Coarse-grained simulation - an efficient approach for studying motions of large proteins
PublicationOne of the most important challenges in performing Molecular Dynamics (MD) simulations of large protein complexes is to accommodate the model accuracy and the simulation timescale. Hitherto, for the most relevant dynamics of protein aggregates in an explicit aqueous environment, the timescale reachable for the all-atoms simulations is of hundreds of nanoseconds. This range is four to six orders of magnitude smaller than processes...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Uncertainty Quantification in Experimental Structural Dynamics Identification of Composite Material Structures
PublicationComposite materials are widely used in manufacture of aerospace and wind energy structural components. These load carrying structures are subjected to dynamic time-varying loading conditions. Robust structural dynamics identification procedure impose tight constraints on the quality of modal models estimates obtained from vibration experiments. Modal testing results are influenced by numerous factors introducing uncertainty to...
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Device-independent quantum key distribution based on measurement inputs
PublicationWe provide an analysis of a family of device-independent quantum key distribution (QKD) protocols that has the following features. (a) The bits used for the secret key do not come from the results of the measurements on an entangled state but from the choices of settings. (b) Instead of a single security parameter (a violation of some Bell inequality) a set of them is used to estimate the level of trust in the secrecy of the key....
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Generation of large finite-element matrices on multiple graphics processors
PublicationThis paper presents techniques for generating very large finite-element matrices on a multicore workstation equipped with several graphics processing units (GPUs). To overcome the low memory size limitation of the GPUs, and at the same time to accelerate the generation process, we propose to generate the large sparse linear systems arising in finite-element analysis in an iterative manner on several GPUs and to use the graphics...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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eFRADIR: An Enhanced FRAmework for DIsaster Resilience
PublicationThis paper focuses on how to increase the availability of a backbone network with minimal cost. In particular, the new framework focuses on resilience against natural disasters and is an evolution of the FRADIR/FRADIR-II framework. It targets three different directions, namely: network planning, failure modeling, and survivable routing. The steady state network planning is tackled by upgrading a sub-network (a set of links termed...
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An Experimentally Aided Operational Virtual Prototyping to Obtain the Best Spindle Speed during Face Milling of Large-Size Structures
PublicationAbstract: The paper presents an original method concerning the problem of vibration reduction in the general case while milling large-size and geometrically complex details with the use of an innovative approach to the selection of spindle speed. A computational model is obtained by applying the so-called operational approach to identify the parameters of the workpiece modal model. Thanks to the experimental modal analysis results,...
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IoT protocols, architectures, and applications
PublicationThe proliferation of embedded systems, wireless technologies, and Internet protocols have enabled the IoT to bridge the gap between the virtual and physical world enabling the monitoring and control of the environment by data processing systems. IoT refers to the inter-networking of everyday objects that are equipped with sensing, computation, and communication capabilities. These networks can collaboratively interact and perform...
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Numerical Study of the Impinging Jets Formed by an Injector with Different Nozzle Diameters
Open Research DataThe data set contains the simulation files related to the research paper “Numerical Study of the Impinging Jets Formed by an Injector with Different Nozzle Diameters”, https://doi.org/10.4271/2022-01-1080.
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Communication and Load Balancing Optimization for Finite Element Electromagnetic Simulations Using Multi-GPU Workstation
PublicationThis paper considers a method for accelerating finite-element simulations of electromagnetic problems on a workstation using graphics processing units (GPUs). The focus is on finite-element formulations using higher order elements and tetrahedral meshes that lead to sparse matrices too large to be dealt with on a typical workstation using direct methods. We discuss the problem of rapid matrix generation and assembly, as well as...
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In vivo imaging of the human eye using a two-photon excited fluorescence scanning laser ophthalmoscope
PublicationBACKGROUND. Noninvasive assessment of metabolic processes that sustain regeneration of human retinal visual pigments (visual cycle) is essential to improve ophthalmic diagnostics and to accelerate development of new treatments to counter retinal diseases. Fluorescent vitamin A derivatives, which are the chemical intermediates of these processes, are highly sensitive to UV light; thus, safe analyses of these processes in humans...
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Electronic conductivity in the SiO2-PbO-Fe2O3 glass containing magnetic nanostructures
PublicationThe linear impedance spectra of iron–silicate–lead glass samples were measured in the frequency range from 1 MHz to 1 MHz and in the temperature range from 153 K to 423 K. The structure was investigated by means of XRD and atomic force microscopy. Local electrical and magnetic properties of the samples were tested with the aid of electrostatic force microscopy (EFM) and magnetic force microscopy (MFM). The obtained results show...
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REVIEW OF WEATHER FORECAST SERVICES FOR SHIP ROUTING PURPOSES
PublicationWeather data is nowadays used in a variety of navigational and ocean engineering research problems: from the obvious ones like voyage planning and routing of sea-going vessels, through the analysis of stability-related phenomena, to detailed modelling of ships’ manoeuvrability for collision avoidance purposes. Apart from that, weather forecasts are essential for passenger cruises and fishing vessels that want to avoid the risk...
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Theory versus experiment for vacuum Rabi oscillations in lossy cavities. II. Direct test of uniqueness of vacuum
PublicationThe paper continues the analysis of vacuum Rabi oscillations we started in part I [Phys. Rev. A 79, 033836 (2009)]. Here we concentrate on experimental consequences for cavity QED of two different classes of representations of harmonic-oscillator Lie algebras. The zero-temperature master equation, derived in part I for irreducible representations of the algebra, is reformulated in a reducible representation that models electromagnetic...
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Electronically Excited States in Solution via a Smooth Dielectric Model Combined with Equation-of-Motion Coupled Cluster Theory
PublicationWe present a method for computing excitation energies for molecules in solvent, based on the combination of a minimal parameter implicit solvent model and the equation-of-motion coupled-cluster singles and doubles method (EOM-CCSD). In this method, the solvent medium is represented by a smoothly varying dielectric function, constructed directly from the quantum mechanical electronic density using only two tunable parameters. The...
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Performance-Driven Surrogate Modeling of High-Frequency Structures
PublicationThe development of modern high-frequency structures, including microwave and antenna components, heavily relies on full-wave electromagnetic (EM) simulation models. Notwithstanding, EM-driven design entails considerable computational expenses. This is especially troublesome when solving tasks that require massive EM analyzes, parametric optimization and uncertainty quantification be-ing representative examples. The employment of...
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Experimental and numerical identification of corrosion degradation of ageing structural components
PublicationThe study presents experimental and numerical identification of corrosion degradation of thin-walled structural components employing guided wave propagation. The steel structural components are subjected to through-thickness varying corrosion degradation levels. The developed approach using the non-destructive guided wave-propagation quantifies the equivalent average corrosion degradation level by exploring a limited number of...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Opracowanie i wprowadzenie nowoczesnego systemu utrzymania ruchu urządzeń opartego na strategii planowo – zapobiegawczej na obiekcie offshore
PublicationW pracy przedstawiono metodykę utrzymania ruchu maszyn i urządzeń na obiekcie offshore. Opracowany autorski system utrzymania ruchu, który został wdrożony na morskiej platformie wydobywczej „Petrobaltic” gdzie do przesyłu i przetwarzania danych wykorzystano dostępną infrastrukturę informatyczną. Założenia realizowano z wykorzystaniem metod naukowych takich jak analiza case study, metody eksperckie i inne. Pracę zrealizowano w ośmiu...
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Accurate simulation-driven modeling and design optimization of compact microwave structures
PublicationCost efficient design optimization of microwave structures requires availability of fast yet reliable replacement models so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations is often prohibitive. On the other hand, accurate data-driven modeling normally requires a very large number of training points and it is virtually infeasible...
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Measuring research on radio wave propagation
PublicationTelecommunication connections are increasingly based on the wireless links, both fixed and mobile, carried out under different radio systems. This kind of solution has many advantages. However, the propagation medium is a factor that causes many difficulties in designing wireless networks, because of large diversity of propagation environments. Transmission loss in each environment is determined by many variables phenomena and...
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Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
PublicationIn environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori...
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublicationEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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A Model-Based Improved Control of Dissolved Oxygen Concentration in Sequencing Wastewater Batch Reactor
PublicationBiochemical processes at wastewater treatment plant are complex, nonlinear, time varying and multivariable. Moreover, relationships between processes are very strong. One of the most important issues is exerting proper control over dissolved oxygen levels during nitrification phase. This parameter has a very large impact on activity of microorganisms in activated sludge and on quality of pollution removal processes. Oxygen is supplied...
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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublicationFast replacement models have been playing an increasing role in high-frequency electronics, including the design of antenna structures. Their role is to improve computational efficiency of the procedures that normally entail large numbers of expensive full-wave electromagnetic (EM) simulations, e.g., parametric optimization or uncertainty quantification. Recently introduced performance-driven modeling methods, such as the nested...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Smart Decisional DNA Technology to Enhance Industry 4.0 Environment in Conjunction with Conventional Manufacturing
PublicationKnowledge-based support has become an indispensable part not only to the traditional manufacturing set-ups but also to the new fast-emerging Industry 4.0 scenario. In this regard, successful research has been performed and extensively reported to develop Decisional DNA based knowledge representation models of engineering object and engineering process called Virtual engineering object (VEO), Virtual engineering process (VEP) and...
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Design advantages and analysis of a novel five-phase doubly-fed induction generator
PublicationPurpose – The purpose of this paper is to provide an analysis of the performance of a new five-phase doubly fed induction generator (DFIG). Design/methodology/approach – This paper presents the results of a research work related to fivephase DFIG framing, including the development of an analytical model, FEM analysis as well as the results of laboratory tests of the prototype. The proposed behavioral level analytical model is based...
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A New Method for Automatic Generation of Animated Motion
PublicationA new method for generation of animation with a quality comparable to a natural motion is presented. Proposed algorithm is based on fuzzy description of motion parameters and subjective features. It is assumed that such processing increases naturalness and quality of motion, which is verified by subjective evaluation tests. First, reference motion data are gathered utilizing a motion capture system, then these data are reduced...
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The Application of Satellite Image Analysis in Oil Spill Detection
PublicationIn recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to...
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A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds
PublicationThe recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital...
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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublicationReflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using...
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Monitoring strategy for industrially contaminated rivers - A study of all year round behaviour of Klodnica river catchment, upper Silesia, Poland
PublicationThe study was undertaken to thoroughly characterise the contamination of water in industrially influenced river Klodnica, in order to explore monitoring strategies in case of limited analytical capacity. Statistical analysis undertaken after a short study was found to be helpful in reducing monitoring efforts in the future.Klodnica river is located within area of dominating coal mining, metallurgy, and additionally being influenced...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublicationThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Numerical Modelling of Structures with Uncertainties
PublicationThe nature of environmental interactions, as well as large dimensions and complex structure of marine offshore objects, make designing, building and operation of these objects a great challenge. This is the reason why a vast majority of investment cases of this type include structural analysis, performed using scaled laboratory models and complemented by extended computer simulations. The present paper focuses on FEM modelling...
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METHODS OF TEACHING SPATIAL AND URBAN PLANNING AT GEODESY AND CARTOGRAPHY
PublicationSpatial and town planning is a complex process caused by the interaction between natural and social systems at different temporal and spatial scales. That is the reason, why it is difficult to introduce this subject to students studying disciplines other than spatial or urban planning. The main problem is to define goals, the scope and expected educational effects. The second step is to choose the appropriate teaching and assessment...
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Surrogate modeling of impedance matching transformers by means of variable‐fidelity electromagnetic simulations and nested cokriging
PublicationAccurate performance evaluation of microwave components can be carried out using full‐wave electromagnetic (EM) simulation tools, routinely employed for circuit verification but also in the design process itself. Unfortunately, the computational cost of EM‐driven design may be high. This is especially pertinent to tasks entailing considerable number of simulations (eg, parametric optimization, statistical analysis). A possible...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Integrated plant-wide modelling for evaluation of the energy balance and greenhouse gas footprint in large wastewater treatment plants
PublicationModern wastewater treatment plants (WWTPs) should maintain a balance between three combined sustainability criteria, including effluent quality, energy performance and greenhouse gas (GHG) emissions. All of these criteria were considered in the integrated plant-wide model developed in this study. The proposed model incorporates new features, including: (i) the addition of associated facilities to the overall energy balance and...
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Usage of parametric echosounder with emphasis on buried object searching.
PublicationThe purpose of this article is to present the results of investigation to search for buried objects. The paper will contain echograms and other means of visualization from buried pipe placed between area of W?adys?awowo and gas platform and interesting in terms of the number of small and medium-sized unidentified objects found in the muddy bottom at different depths localized in the Gulf of Puck - results will be presented also...
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Methodology of Selecting the Hadoop Ecosystem Configuration in Order to Improve the Performance of a Plagiarism Detection System
PublicationThe plagiarism detection problem involves finding patterns in unstructured text documents. Similarity of documents in this approach means that the documents contain some identical phrases with defined minimal length. The typical methods used to find similar documents in dig- ital libraries are not suitable for this task (plagiarism detection) because found documents may contain similar content and we have not any war- ranty that...
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Techno-economic evaluation of combined cycle gas turbine and a diabatic compressed air energy storage integration concept
PublicationMore and more operational flexibility is required from conventional power plants due to the increasing share of weather-dependent renewable energy sources (RES) generation in the power system. One way to increase power plant’s flexibility is integrating it with energy storage. The energy storage facility can be used to minimize ramping or shutdowns and therefore should lower overall generating costs and CO2 emissions. In this article,...
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ARTIFICIAL MODEL IN THE ASSESSMENT OF THE ALGORITHM OF OBJECTS RECORDED BY LASER SCANNING SHAPE DETECTION (ALS/TLS)
PublicationBrief description of the study and used methods. Brief description of the study and used As part of the preparatory work aimed to create the application solution allowing for the automation of searching objects in data, obtained in the scanning process using ALS (Airborne Laser Scanning) or TLS (Terrestrial Laser Scanning), the authors prepared a artificial (synthetic, theoretical) model of space, used for the verification of operation...
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Towards Scalable Simulation of Federated Learning
PublicationFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...