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<title>Data quality management system (DQMS) for BAC detector in the ZEUS experiment at the HERA accelerator</title>
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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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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Angiotensin receptor blockers and cancer – Relationship dismissed by VALUE data while waiting for EMA and FDA reports
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Determinants of inward FDI into Visegrad countries: empirical evidence based on panel data for the years 2000–2012
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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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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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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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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The onset of growing season based on meteorological and remotely sensed data as well as phenological observations of the common hazel
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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.
PublicationW 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
PublicationAnaliza 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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Analysis of spectral data by complementary methods. Inspection of the molecular complex in N,N-dimethylformamide - methanol mixtures
PublicationDane 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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MATCHED FILTER APPROACH FOR MICROSEISMIC SIGNAL PROCESSING OF REAL DATA FROM EAST POMERANIA SHALE GAS
PublicationThe 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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Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing
PublicationThe 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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Wave Method for Structural Health Monitoring: Testing Using Full-Scale Shake Table Experiment Data
PublicationAn 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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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn 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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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublicationArticle 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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Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams
PublicationThe 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
PublicationALS 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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Reversible Data Hiding in Encrypted DICOM Images Using Cyclic Binary Golay (23, 12) Code
PublicationIn 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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Researching Digital Society: Using Data-Mining to Identify Relevant Themes from an Open Access Journal
PublicationOpen 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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Researching Digital Society: Using Data-Mining to Identify Relevant Themes from an Open Access Journal
PublicationOpen 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 OFDM Data Transmission with Pilot Tones and Error-Correction Coding in Shallow Underwater Acoustic Channel
PublicationThe 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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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublicationProject 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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Reliable data-driven modeling of high-frequency structures by means of nested kriging with enhanced design of experiments
PublicationData-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
PublicationOne 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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Application of splines and wavelets along with TIN decimation to 3D imagingof seafloor from multibeam sonar data
PublicationW 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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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData 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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Utilizing UAV and orthophoto data with bathymetric LiDAR in google earth engine for coastal cliff degradation assessment
PublicationThis study introduces a novel methodology for estimating and analysing coastal cliff degradation, using machine learning and remote sensing data. Degradation refers to both natural abrasive processes and damage to coastal reinforcement structures caused by natural events. We utilized orthophotos and LiDAR data in green and near-infrared wavelengths to identify zones impacted by storms and extreme weather events that initiated mass...
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Efficacy of modal curvature damage detection in various pre-damage data assumptions and modal identification techniques
PublicationThe efficacy of modal curvature approach for damage localization is discussed in the paper in the context of input data. Three modal identification methods, i.e., Eigensystem Realization Algorithm (ERA), Natural Excitation Technique with ERA (NExT-ERA) and Covariance Driven Stochastic Subspace Identification (SSI-Cov), and four methods of determining baseline data, i.e., real measurement of the undamaged state, analytical function,...
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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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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublicationOpen 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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Ontological Modeling for Contextual Data Describing Signals Obtained from Electrodermal Activity for Emotion Recognition and Analysis
PublicationMost 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
PublicationWhether 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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Influence of input data on airflow network accuracy in residential buildings with natural wind - and stack - driven ventilation.
PublicationW 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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Polska leksykografia terminologiczna z komponentem rosyjskim z dziedziny nauk prawnych. Bibliografia słowników za lata 1803–2014, [Polish terminological lexicography in the field of legal science including a Russian component. A bibliography of dictionaries published between 1803–2014]
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Phytotechnology applied to municipal wastewater treatment on irrigated fields of Gdansk (Poland) (1872-1992)
PublicationPola nawadniane ściekami w Gdańsku zbudowane zostały w roku 1872 i pracowały do roku 1992. Obejmowały one 320 ha piasków nadmorskich w miejscowości Gdansk Sianki, między Wisloujściem a Stogami. Obciążenie hydrauliczne pól wynosiło początkowqo 3000 mm rocznie, ale stopniowo wzrastało aż do poziomu 8000 mm rocznie. Pola pokryte były monokulturą trawiasta złożoną głównie z perzu, a zagłębieniach terenowych występowała głównie pokrzywa....
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Estimation of nitrogen leaching load from agricultural fields in the Puck Commune with an interactive calculator
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Ab initio and experimental studies of polarization and polarization related fields in nitrides and nitride structures
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Application of Rotating Magnetic Fields Increase the Activity of Antimicrobials Against Wound Biofilm Pathogens
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“Electromagnetic ULF/ELF Fields on Earth and in Space” Conference, Warsaw, Poland, 2019. Preface
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Zero phase shift digital filtering for assessment of exposure to non-sinusoidal magnetic fields
PublicationAccuracy of assessment of human body exposure to magnetic fields is affected by several uncertainty sources. One of them is estimation of the total exposure to non-sinusoidal fields. Standard methods can be implemented using analogue or digital filters that introduce a phase shift that affect the result of total exposure level estimation. The paper presents a new method that allows performing more precise assessment of exposure...
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Fungal L-Methionine Biosynthesis Pathway Enzymes and Their Applications in Various Scientific and Commercial Fields
PublicationL-methionine (L-Met) is one of the nine proteinogenic amino acids essential for humans since, in human cells, there are no complete pathways for its biosynthesis from simple precursors. L-Met plays a crucial role in cellular function as it is required for proper protein synthesis, acting as an initiator. Additionally, this amino acid participates in various metabolic processes and serves as a precursor for the synthesis of S-adenosylmethionine...
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The state of the art in the field of non-stationary instruments for the determination and monitoring of atmospheric pollutants
PublicationW artykule przedstawiono informacje oparte zarówno na danych literaturowych jak i własnych doświadczeniach dotyczące:-podstawowych tendencji rozwojowych w zakresie analityki i monitoringu zaneczyszczeń powietrza atmosferycznego-wymogów metrologicznych stawianych różnych typom urządzeń kontrolno-pomiarowych;-klasyfikacji analizatorów i monitorów wykorzystywanych w monitoringu powietrza.
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Modelling of temperature field of flat boiling section with active single nucleation site
PublicationZaprezentowano główne założenia wybranych modeli wrzenia dla pojedynczego centrum nukleacji. Przedstawiony model numeryczny dotyczy zagadnienia dwuwymiarowego, osiowo-symetrycznego, nieizotropowego przewodzenia ciepła dla warunków brzegowych pierwszego, drugiego i trzeciego rodzaju. Warunek brzegowy drugiego rodzaju reprezentuje gęstość strumienia ciepła połączoną z generacją pęcherzy z pojedynczego centrum nukleacji.