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Wyniki wyszukiwania dla: FIELSD DATA
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Investigating impacts of asphalt mixture properties on pavement performance using LTPP data through random forests
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Spatial and Temporal Variability of Moisture Condition in Soil-Plant Environmet using Spectral Data and GIS Tools
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Ephemeral wetland communities of Isoëto-Nano-Juncetea class – new data from south-eastern Poland
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Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers
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Experiences of people with dementia and informal caregivers with post‐diagnostic support: Data from the international COGNISANCE study
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Angiotensin receptor blockers and cancer – Relationship dismissed by VALUE data while waiting for EMA and FDA reports
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CLEPSYDRA Data Aggregation and Enrichment Framework: Design, Implementation and Deployment in the PIONIER Network Digital Libraries Federation
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Selection of Methods of Surface Texture Characterisation for Reduction of the Frequency-Based Errors in the Measurement and Data Analysis Processes
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Early agricultural colonisation of peripheral areas of loess uplands: new data from Sandomierz Upland, Poland
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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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Methotrexate Decreases the Level of PCSK9—A Novel Indicator of the Risk of Proatherogenic Lipid Profile in Psoriasis. The Preliminary Data
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Application of COSMO-RS-DARE as a Tool for Testing Consistency of Solubility Data: Case of Coumarin in Neat Alcohols
PublikacjaCoumarin is a naturally occurring lactone-type benzopyrone with various applications in the pharmaceutical, food, perfume, and cosmetics industries. This hydrophobic compound is poorly soluble in water but dissolves well in protic organic solvents such as alcohols. Despite the extensive use of coumarin, there are only a few reports documenting its solubility in organic solvents, and some reported data are incongruent, which...
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High Resolution Sea Ice Floe Size and Shape Data from Knox Coast, East Antarctica
PublikacjaThis dataset contains floe size distribution data from a very high resolution (pixel size: 0.3 m) optical satellite image of sea ice, acquired on 16 Feb. 2019 off the Knox Coast (East Antarctica). The image shows relatively small ice floes produced by wave-induced breakup of landfast ice between Mill Island and Bowman Island. The ice floes are characterised by a narrow size distribution and angular, polygonal shapes, typical...
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Predicting the Number of Days With Visibility in a Specific Range in Warsaw (Poland) Based on Meteorological and Air Quality Data
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Potential Saving of Antibiotics for Respiratory Infections in Several European Countries: Insights from Market Research Data
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Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification Databases
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Analysis of spectral data by complementary methods. Inspection of the molecular complex in N,N-dimethylformamide - methanol mixtures
PublikacjaDane widmowe FTIR mieszanin N,N-dimetyloformamidu z metanolem poddano anlizie faktorowej oraz analizie metodą ważonych widm różnicowych. Przydatność obu metod analizy w odniesieniu do układów z wiązaniem wodorowym poddano krytycznej dyskusji. Stwierdzono obecność kompleksu molekularnego typu 1:1 w całym zakresie składów mieszanin. Forma tego kompleksu zależy jednak od składu roztworu. Postulowano występowanie słabych wiązań wodorowych...
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The analysis of resistante to noise and edge jitter of the chosen methodsof recovering the data transmitted over a radio link.
PublikacjaW artykule porównano odporność na szumy i zakłócenia wybranych metod synchronizacji danych przesyłanych drogą radiową. Wybrano następujące metody:próbkowanie nadmiarowe i decyzja większościowa w odniesieniu do ciągu danych NRZ oraz metoda korelacyjna przeznaczona dla ciągu danych zakodowanych sposobem Manchester. Efektywność wyrażono jako liczbę pakietów, które osiągnęły synchronizację ramki do całkowitej liczby nadanych...
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Fuzzy soft modeling of environmental data. A study of the impact of a Phosphatic Fertilizer Plant on the adjacent environment in Gdańsk
PublikacjaAnaliza podobieństwa obejmuje nie tylko zastosowanie logiki rozmytej, ale również wiele innych podejść matematycznych. Opracowano wiele algorytmów, których celem jest wyodrębnienie wyraźnych skupień (hard clusters) z danego zbioru danych. Prawdopodobnie najczęściej stosowanymi algorytmami są tzw. algorytmy c-średnie (c-means algorithms). Twarde c-średnie (hard c-means) służy do ostrej klasyfikacji, podczas której obiekt jest przypisany...
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Application of splines and wavelets along with TIN decimation to 3D imagingof seafloor from multibeam sonar data
PublikacjaW pracy przedstawiono dwie metody reprezentacji danych batymetrycznych otrzymanych z pomiarów z użyciem sonaru wielowiązkowego. Reprezentacja przy pomocy funkcji sklejanych jest odpowiednia dla baz danych, podczas gdy reprezentacja z wykorzystaniem funkcji falkowych posiada dobre właściwości kompresyjne.
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Data-Centric Dempster-Shafer Theory-Based Selfishness Thwarting via Trust Evaluation in MANETs and WSNs
PublikacjaPrzedstawiono ramy wymiany informacji reputacyjnej pomiędzy terminalami sieci mobilnej ad hoc lub sensorowej, prowadzące do efektywnej lokalizacji terminali egoistycznych i jednocześnie zapobiegające skutkom fałszywych rekomendacji. Integrację miar zaufania i rekomendacji reputacyjnych oparto na teorii Dempstera-Shafera.
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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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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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TRANSPORT POSSIBILITY FOR MPEG-4/AVC- AND MPEG-2-ENCODED VIDEO DATA IN IPTV: A COMPARISON STUDY
PublikacjaIPTV (Television over IP) is a modern service with a great potential to expand. It uses the IP transport platform, that is already in worldwide operation. At the time of writing, two techniques are used to transport the video and audio data of IPTV: MPEG-2 TS and Native RTP. The two techniques quite definitely have an influence on both quality of service (QoS) and quality of experience (QoE). This paper sets out to demonstrate...
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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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Seafloor characterisation using multibeam data: sonar image properties, seabed surface properties and echo properties
PublikacjaIn the paper, the approach to seafloor characterisation is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry and underwater object detection and imaging, are also the promising tool in seafloor characterization and classification, having several advantages over conventional single beam echosounders. The proposed approach relies on the combined, concurrent use...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublikacjaKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Analysis of effect of overloaded vehicles on fatigue life of flexible pavements based on weigh in motion (WIM) data
PublikacjaOverloaded vehicles have a significant impact on pavement fatigue life and distress. As the studies show, the phenomena intensify when the control of traffic is poor. The paper presents the results of the research including analysis of weigh in motion data from eight stations and analysis of asphalt pavement fatigue caused by mixed traffic. Distributions of vehicles axles load including the multiple axles effects are presented....
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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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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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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublikacjaIn 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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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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Data analysis of FTIR spectra for study of outlet gases of Solid Oxide Fuel Cells fuelled by biogas
PublikacjaW pracy przedstawiono system umożliwiający połączenie spektroskopii FTIR z specjalnie zaprojektowanym oprogramowaniem w celu uzyskania informacji o stężeniach gazów wylotowych z ogniw paliwowych SOFC. Przebadane zostały główne produkty reformingu biogazu: tlenek węgla, dwutlenek węgla, metan oraz wodór. Opisane oprogramowanie umożliwia w prosty i szybki sposób uzyskanie informacji o gazach wylotowych ogniwa paliwowego.
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A model, design, and implementation of an efficient multithreaded workflow execution engine with data streaming, caching, and storage constraints
PublikacjaThe paper proposes a model, design, and implementation of an efficient multithreaded engine for execution of distributed service-based workflows with data streaming defined on a per task basis. The implementation takes into account capacity constraints of the servers on which services are installed and the workflow data footprint if needed. Furthermore, it also considers storage space of the workflow execution engine and its cost....
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Instrumented end notched flexure - Crack propagation and process zonemonitoring Part II: Data reduction and experimental
PublikacjaA mode II instrumented end notched flexure three point bending (ENF) adhesion test is described. The adhesive joint consists of two aluminium alloy (AW7075-T6) plates bonded with a structural epoxy adhesive (Hysol EA 9395™). Strain gauges are attached to the outer surface (backface) of the substrates in the lengthwise direction to measure local surface strain during crack propagation. Simultaneously, load/displacement measurements...
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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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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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Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams
PublikacjaThe paper investigates parallel data processing in a hybrid CPU+GPU(s) system using multiple CUDA streams for overlapping communication and computations. This is crucial for efficient processing of data, in particular incoming data stream processing that would naturally be forwarded using multiple CUDA streams to GPUs. Performance is evaluated for various compute time to host-device communication time ratios, numbers of CUDA streams,...
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Application of Msplit method for filtering airborne laser scanning data sets to estimate digital terrain models
PublikacjaALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Reliable OFDM Data Transmission with Pilot Tones and Error-Correction Coding in Shallow Underwater Acoustic Channel
PublikacjaThe performance of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Horizontal, shallow-water channels are characterised by extremely disadvantageous transmission properties, due to strong multipath propagation and refraction phenomena. The paper presents the results of communication tests performed during a shallow, inland-water experiment with...
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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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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublikacjaProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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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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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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Reversible Data Hiding in Encrypted DICOM Images Using Cyclic Binary Golay (23, 12) Code
PublikacjaIn this paper, a novel reversible data hiding method for encrypted images (RDHEI) is proposed. An efficient coding scheme based on cyclic binary Golay (23, 12) code is designed to embed additional data into the least significant bits (LSBs) of the encrypted image. The most significant bits (MSBs) are used to ensure the reversibility of the embedding process. The proposed scheme is lossless, and based on the receiver’s privileges,...
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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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Experimental investigations of the hydroelasticity of a liquid-filled tank
PublikacjaW artykule przedstwiono wyniki badań eksperymentalnych dotyczących współoddziaływania konstrukcji odkształcalnej z cieczą. Badania przeprowadzono na dwóch zbiornikach prostopadłościennych ze sprężyście odkształcalnymi ścianami szczytowymi. Badanie tego zjawiska ma odniesienie do często spotykanych zdarzeń praktycznych jak zderzenie zbiornikowca z innym statkiem lub nabrzeżem portowym.