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Wyniki wyszukiwania dla: data-rasterization
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Researching Digital Society: Using Data-Mining to Identify Relevant Themes from an Open Access Journal
PublikacjaOpen Access scholarly literature is scientific output free from economic barriers and copyright restrictions. Using a case study approach, data mining methods and qualitative analysis, the scholarly output and the meta-data of the Open Access eJournal of e-Democracy and Open Government during the time interval 2009–2020 was analysed. Our study was able to identify the most prominent research topics (defined as thematic clusters)...
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Reliable data-driven modeling of high-frequency structures by means of nested kriging with enhanced design of experiments
PublikacjaData-driven (or approximation) surrogate models have been gaining popularity in many areas of engineering and science, including high-frequency electronics. They are attractive as a way of alleviating the difficulties pertinent to high computational cost of evaluating full-wave electromagnetic (EM) simulation models of microwave, antenna, and integrated photonic components and devices. Carrying out design tasks that involve massive...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublikacjaIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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Wave Method for Structural Health Monitoring: Testing Using Full-Scale Shake Table Experiment Data
PublikacjaAn algorithm of the wave method for structural health monitoring (SHM) is tested and calibrated using shake table experiment data of a full-scale, seven-story, reinforced-concrete building slice. The method is based on monitoring changes in the velocity of waves propagating vertically through the structure, identified by least-squares (LSQ) fit of beam models. The experiment was conducted by a team from the University of California,...
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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublikacjaArticle presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.
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A Regional ITRF Densification by Blending Permanent and Campaign Data — The CEGRN campaigns and the Central European Velocity Field
PublikacjaThe CERGOP Project of the Central European Countries initiated six GPS observation campaigns from 1994 to 2001. By the high standards set within this project for site selection, observation and analysis a consistent set of epoch solutions with a precision in the 3–5 mm range was created. The network contains about 19 permanent and 38 epoch stations. In this paper a first combination solution over the seven years with a velocity...
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Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing
PublikacjaThe GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network...
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MATCHED FILTER APPROACH FOR MICROSEISMIC SIGNAL PROCESSING OF REAL DATA FROM EAST POMERANIA SHALE GAS
PublikacjaThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing (HF)process. An array of several hundred geophones is placed on the surface to record little ground tremors induced by fracturing process. Filtration and summation of signals from geophones is essential to identify and locate fracturing events from underground. Authors propose a method of matched filtering, that is usually...
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A Fail-Safe NVRAM Based Mechanism for Efficient Creation and Recovery of Data Copies in Parallel MPI Applications
PublikacjaThe paper presents a fail-safe NVRAM based mechanism for creation and recovery of data copies during parallel MPI application runtime. Specifically, we target a cluster environment in which each node has an NVRAM installed in it. Our previously developed extension to the MPI I/O API can take advantage of NVRAM regions in order to provide an NVRAM based cache like mechanism to significantly speed up I/O operations and allow to preload...
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Ontological Modeling for Contextual Data Describing Signals Obtained from Electrodermal Activity for Emotion Recognition and Analysis
PublikacjaMost of the research in the field of emotion recognition is based on datasets that contain data obtained during affective computing experiments. However, each dataset is described by different metadata, stored in various structures and formats. This research can be counted among those whose aim is to provide a structural and semantic pattern for affective computing datasets, which is an important step to solve the problem of data...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublikacjaOpen Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...
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Influence of input data on airflow network accuracy in residential buildings with natural wind - and stack - driven ventilation.
PublikacjaW artykule omówiono wpływ danych wejściowych na dokładność modelu przepływu sieciowego powietrza w budynkach mieszkalnych z naturalną i kominową wentylacją. Zastosowano połączony model AFN-BES. Wyniki numeryczne omówiono dla 8 różnych przypadków z różnymi danymi ciśnienia wiatru. Wyniki pokazały, że ogromny wpływ danych wejściowych dotyczących ciśnienia wiatru na wyniki numeryczne.
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Permeation of mineral oils through protective glove materials in view of literature data and authors’ own studies
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Journal of Big Data
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Bibliografia publikacji pracowników Archiwum Państwowego w Lublinie za lata 2008–2016 z uzupełnieniami za lata 2000–2008.
PublikacjaBibliografia publikacji pracowników Archiwum Państwowego w Lublinie
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An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
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Estimating Water Retention in Post-mining Excavations Using LiDAR ALS Data for the Strzelin Quarry, in Lower Silesia
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Extraction of mass spectra free of background and neighboring component contributions from gas chromatography/mass spectrometry data
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Galectin-3 as a Novel Multifaceted and Not Only Cardiovascular Biomarker in Patients with Psoriasis with Regard to Systemic Treatment—Preliminary Data
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Air temperature and location of isobaric surfaces in relation to atmospheric circulation, based on radiosonde data from Legionowo, Poland
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Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps
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<title>Control and monitoring of data acquisition and trigger system (TRIDAQ) for backing calorimeter (BAC) of the ZEUS experiment</title>
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Performance of CMS hadron calorimeter timing and synchronization using test beam, cosmic ray, and LHC beam data
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<title>Data transmission optical link for LLRF TESLA project part II: application for BER measurements</title>
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<title>Distributed embedded-PC-based control and data acquisition system for TESLA cavity controller and simulator</title>
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Sustainable Development and Motivation Opportunities from the Perspective of Women in the Polish Science Sector in the Light of Statistical Data and Surveys
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Towards More Realistic Probabilistic Models for Data Structures: The External Path Length in Tries under the Markov Model
PublikacjaTries are among the most versatile and widely used data structures on words. They are pertinent to the (internal) structure of (stored) words and several splitting procedures used in diverse contexts ranging from document taxonomy to IP addresses lookup, from data compression (i.e., Lempel- Ziv'77 scheme) to dynamic hashing, from partial-match queries to speech recognition, from leader election algorithms to distributed hashing...
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Determination of EC50 toxicity data of selected heavy metals toward heterocypris incongruens and their comparison to "direct-contact" and microbiotests
PublikacjaW artykule omówiono czułość organizmu Heterocypris incongruens wobec metali ciężkich. Pomimo iż test Ostracodtoxkit F jest dostępny hadlowo na rynku od wielu lat to brak jest danych na temat czułości i selektywności tego organizmu, a dane na ten temat są niezbędne podczas interpretowania wyników oznaczeń toksyczności chronicznej próbek gleb i osadów. Wyniki LC50 oraz EC50 zostały też porównane z danymi innych handlowo dostępnych...
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Architecture of security and application layer structure of radio system for monitoring and acquisition of data from traffic enforcement cameras
PublikacjaThe study presents architecture of security and application layer structure of Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras. It also provides general assumptions concerning the range of the system as well as its modules and application components.
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Integration of Multi-Source Geospatial Data from GNSS Receivers, Terrestrial Laser Scanners, and Unmanned Aerial Vehicles
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Least square spline modelling along with tin decimation for 3D seafloor mapping from multibeam sonar data.
PublikacjaPrzedstawiono wyniki prac związane z zastosowaniem algorytmu aproksymacyjnego minimalnokwadratowego do wizualizacji danych wysokorozdzielczych pochodzących z sonaru wielowiązkowego. Metoda pozwala na redukcję danych oraz łatwą ich modyfikację.
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Temperature, velocity and mean turbulence structure in strongly heated internal gas flows. Comparison of numerical predictions with data
PublikacjaW pracy przedstawiono symulacje numeryczne przy użyciu szeregu modeli turbulencji celem analizy silnie ogrzewanego przepływu powietrza w pionowych rurach. Obliczenia porównano z danymi eksperymentalnymi. Analizowano modyfikacje pola prędkości, temperatury i turbulencji. W rozpatrywanych warunkach odnotowano silną wrażliwość obliczeń na silnie zmieniające się pole temperatury. Stwierdzono, że analizowane przypadki najlepiej odzwierciedla...
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Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics
PublikacjaEven in the era of automatization maritime safety constantly needs improvements. Regardless of the presence of crew members on board, both manned and autonomous ships should follow clear guidelines (no matter as bridge procedures or algorithms). To date, many safety indicators, especially in collision avoidance have been proposed. One of such parameters commonly used in day-to-day navigation but usually omitted by researchers is...
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Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps
PublikacjaThe study considers the need for an effective method of classification of patients with a temporomandibular joint disorder (TMD). The self-organising map method (SOM) was applied to group patients and used together with the cross-correlation approach to interpret the processed (rectified and smoothed by using root mean square (RMS) algorithm) surface electromyography signal (sEMG) obtained from testing the muscles (two temporal...
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Multi-Temporal Analysis of Changes of the Southern Part of the Baltic Sea Coast Using Aerial Remote Sensing Data
PublikacjaUnderstanding processes that affect changes in the coastal zone and the ability to predict these processes in the future depends on the period for which detailed monitoring is carried out and on the type of coast. This paper analyzes a southern fragment of the Baltic coast (30 km), where there has been no anthropogenic impact (Slowinski National Park). The study was carried out covering a time interval of 65 years. Historic and...
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublikacjaPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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Automated Valuation Model based on fuzzy and rough set theory for real estate market with insufficient source data
PublikacjaObjective monitoring of the real estate value is a requirement to maintain balance, increase security and minimize the risk of a crisis in the financial and economic sector of every country. The valuation of real estate is usually considered from two points of view, i.e. individual valuation and mass appraisal. It is commonly believed that Automated Valuation Models (AVM) should be devoted to mass appraisal, which requires a large...
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Mono- and bimetallic (Pt/Cu) titanium(IV) oxide photocatalysts. Physicochemical and photocatalytic data of magnetic nanocomposites’ shell
PublikacjaSurface modification of titania with noble and semi-noble metals resulted in significant enhancement of photocatalytic activity. Presented data, showing the photocatalytic properties of TiO2-M (where M is Pt and/or Cu) photocatalysts were further used as Fe3O4@SiO2/TiO2-M magnetic nanocomposites shells in "Mono- and bimetallic (Pt/Cu) titanium(IV) oxide core-shell photocatalysts with Vis light activity and magnetic separability"...
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ChatGPT Application vis-a-vis Open Government Data (OGD): Capabilities, Public Values, Issues and a Research Agenda
PublikacjaAs a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the academic, medicine, law, computing or other sectors, but also for the public sector-case in point being the Open Government Data (OGD) initiative. However, though there has been some limited (as this topic is quite new) research concerning the capabilities ChatGPT in these sectors, there has been no research about the capabilities it...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublikacjaWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Digital data and tools in transformative education to preserve architecture and cultural heritage: case studies from Italy and Poland
PublikacjaIn this article, the authors present the findings and results of a recent study focused on various collaborative activities mostly between Italy and Poland, and digital teaching platforms aimed at educating future architects. These architects are envisioned as curators of digital data and experts in using digital tools in the field of architecture and architectural heritage. The investigation had two main objectives. Firstly, it...
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Impact evaluation of a cycling promotion campaign using daily bicycle counters data: The case of Cycling May in Poland
PublikacjaThe promotion of active and sustainable transport modes as an alternative to motorised individual transport has become a key policy priority in Europe, to reduce air pollution, road congestion, noise, traffic injuries, and the adverse health outcomes of sedentary lifestyles. Policymakers are implementing a wide range of measures to encourage this shift in attitudes and behaviours. These interventions are most valuable when targeting...
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Integration of Multi-Source Geospatial Data from GNSS Receivers, Terrestrial Laser Scanners, and Unmanned Aerial Vehicles
PublikacjaThe analysis based on geospatial data from different measurement systems now constitutes a complex numerical and practical enterprise. The dynamic development of modern technologies enables rapid and precise acquisition of such data. Nonetheless, the diversity of reference systems is today one of the main challenges for their correct interpretation. The combined use of the processed measurement results and archival data in paper...
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Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
PublikacjaFast data-driven surrogate models can be employed as replacements of computationally demanding full-wave electromagnetic simulations to facilitate the microwave design procedures. Unfortunately, practical application of surrogate modelling is often hindered by the curse of dimensionality and/or considerable nonlinearity of the component characteristics. This paper proposes a simple yet reliable approach to cost-efficient modelling...
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Novel Adaptive Method for Data Streams Allocation Based on the Estimate of Radio Channel Parameters in Heterogeneous WBAN Network
PublikacjaThe new adaptive method for data streams allocation in heterogeneous Wireless Body Area Networks and meas-urement equipment is presented. The results obtained using the developed method compared with the selected algorithms likely to be used in those networks. The pro-posed adaptive data streams allocation method based on radio channel parameters makes it even twice as efficient to use in terms of resources usage in a WBAN heterogeneous...
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Processing of point cloud data retrieved from terrestrial laser scanning for structural modeling by Finite Element Method
PublikacjaFinite Element Method is one most popular contemporary method of strength analysis. The method is an advanced method for solving differential equations, based on discretization, which means that area is divided into finite elements. Each finite element has a solution of the equation approximated by specific functions and performing the actual calculations only for nodes of this division. Finite Element Method is widely used in...