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Search results for: Data Collection Techniques
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Classification and fingerprinting of kiwi and pomelo fruits by multivariate analysis of chromatographic and spectroscopic data
PublicationThe fingerprinting capacity of two analytical techniques, HPLC and UV-Vis spectroscopy in the case of fruits samples (kiwi and pomelo) has been investigated. The multivariate exploratory techniques were used for sample discrimination according to the fruit species and subspecies. The combination of principal component analysis with linear discriminant analysis is opening new directions in the fingerprinting analysis. The classifications...
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Artysta i analityk. Big data w przestrzeni kultury
PublicationTekst rozważa rolę Big Data - ogromnych zbiorów danych - w badaniu kultury oraz w jej tworzeniu. Przedmiotem analiz jest również wpływ tej technologii na twórczość artystyczną, w tym na współczesną architekturę i urbanistykę. Przedstawione zostały scenariusze potencjalnej przyszłej roli Big Data w społeczeństwie.
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Recent Developments in Data-Assisted Modeling of Flexible Proteins
PublicationMany proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this...
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Music Data Processing and Mining in Large Databases for Active Media
PublicationThe aim of this paper was to investigate the problem of music data processing and mining in large databases. Tests were performed on a large data-base that included approximately 30000 audio files divided into 11 classes cor-responding to music genres with different cardinalities. Every audio file was de-scribed by a 173-element feature vector. To reduce the dimensionality of data the Principal Component Analysis (PCA) with variable...
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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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JOURNAL OF TRACE AND MICROPROBE TECHNIQUES
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JBJS Essential Surgical Techniques
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Techniques in Foot and Ankle Surgery
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He Jishu/Nuclear Techniques
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IET Computers and Digital Techniques
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Techniques in Vascular and Interventional Radiology
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Techniques in Shoulder and Elbow Surgery
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Food Processing: Techniques and Technology
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JOURNAL OF SPINAL DISORDERS & TECHNIQUES
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Journal of Environmental Treatment Techniques
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OPERATIVE TECHNIQUES IN SPORTS MEDICINE
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Techniques and Innovations in Gastrointestinal Endoscopy
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Visualization of events using various kinds of synchronized data for the Border Guard
PublicationSTRADAR project is dedicated to streaming real-time data in a distributed dispatcher and teleinfor-mation system of the Border Guard. The Events Visualization Post is a software designed for simultaneous visualization of data of different types in BG headquarters. The software allows the operator to visualize files, images, SMS, SDS, video, audio, and current or archival data on naval situation on digital maps. All the visualized...
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Evolutionary Sets of Safe Ship Trajectories: improving the method by adjusting evolutionary techniques and parameters
PublicationThe paper presents some of the evolutionary techniques used by the evolutionary sets of safe ship trajectories method. In general, this method utilizes a customized evolutionary algorithm to solve a constrained optimization problem. This problem is defined as finding a set of cooperating trajectories (here the set is an evolutionary individual) of all the ships involved in the encounter situation. The resulting trajectories are...
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Evaluation of position estimation based on accelerometer data
PublicationThe paper concerns the problem of integrating data from accelerometers. A suitable model of a MEMS accelerometer is presented which is a part of inertial measurement units (IMU). Such units allow to measure orientation as well as to localize systems. They also appear to be applicable for systems positioning. The main purpose of the paper is to discuss conditions that must be satisfied to calculate the location of the sensor by...
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Big Data and the Internet of Things in Edge Computing for Smart City
PublicationRequests expressing collective human expectations and outcomes from city service tasks can be partially satisfied by processing Big Data provided to a city cloud via the Internet of Things. To improve the efficiency of the city clouds an edge computing has been introduced regarding Big Data mining. This intelligent and efficient distributed system can be developed for citizens that are supposed to be informed and educated by the...
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Analysis of data fusion algorithms for the vessel with the dynamic positioning system
PublicationThe dynamic positioning (DP) system on the vessel is operated to control the position and heading of the vessel with the use of propellers and thrusters installed on the board. On DP vessels redundant measurement systems of position, heading and the magnitude and direction of environmental forces are required for safety at sea. In this case, a fusion of data is needed from individual measurement devices. The article proposes a...
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublicationIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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ARIMA vs LSTM on NASDAQ stock exchange data
PublicationThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
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Methods of data extraction from sub-bottom profiler's signal
PublicationData obtain during sounding Gdansk Bay with SES-2000 Standard parametric sub-bottom profiler has two types of information: envelope and pure signal. First is used to plot echograms in real time and contain envelope of echo. The second one is stored during sounding and can be processed after recording data. Comparison of results will be shown and discussed. First step in investigation was proper configuration of small measurement...
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Cache service for maps presentation in distributed information data exchange system
PublicationThe paper presents the proposition of caches implementation for map presentation in distributed information data exchange system. The concept of cache service is described in the context of distributed information data exchange system elements which control and present on maps positions and other identification data of vessels and other suspicious objects on the territorial sea, sea-coast and the internal sea-waters. The proposed...
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Determination of volatile organic compounds using solventless sample preparation techniques and gas chromatography
PublicationIn this paper the latest advances in the determination of volatile organic compounds using solvent-free extraction techniques in the sample preparation step are presented. A paper is focus mainly on one of the most popular sample preparation technique: solid-phase microextraction technique (SPME) combined with different detection systems and its applications to sampling of VOCs from the samples with different matrices. This paper...
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Automatic Clustering of EEG-Based Data Associated with Brain Activity
PublicationThe aim of this paper is to present a system for automatic assigning electroencephalographic (EEG) signals to appropriate classes associated with brain activity. The EEG signals are acquired from a headset consisting of 14 electrodes placed on skull. Data gathered are first processed by the Independent Component Analysis algorithm to obtain estimates of signals generated by primary sources reflecting the activity of the brain....
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Assessing the failure of Open Government Data initiatives in Brazil
PublicationWhile assessing the potential of a particular digital innovation initiative, especially when it has implications for a range of societal stakeholders, it becomes pertinent to understand the possible bottlenecks in its acceptability as well. In this regard, the present study seeks to understand how the Open Government Data (OGD) initiatives in Brazil are being confronted with bottlenecks in terms of their execution and acceptability....
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Multibeam Sonar Characterisation of Seafloor in the Context of Visualisation and Dissemination of Marine Data
PublicationThe paper presents the seafloor characterisation method based on multibeam sonar data. it relies on using three types of multibeam seafloor sensing data: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of high resolution bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification is performed by utilisation...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Early Oceanographical Data Collected by the Institute of Oceanography, University of Gdańsk
PublicationThree data sets entitled Water currents in Głębinka Passage in late spring of 1975, Hydrometeorological and hydrochemical conditions in the Gulf of Gdańsk in the vicinity of Vistula river mouth in July of 1977, and Gulf of Gdańsk monitoring conducted by the Institute of Oceanography, University of Gdańsk, in 1981–1994 contain archival field measurement results from the Gulf of Gdańsk (the southern Baltic). The data can be used...
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Model of an Integration Bus of Data and Ontologies of Smart Cities Processes
PublicationThis paper presents a model of an integration bus used in the design of Smart Cities system architectures. The model of such a bus becomes necessary when designing high-level architectures, within which the silo processes of the organization should be seen from the perspective of its ontology. For such a bus to be used by any city, a generic solution was proposed which can be implemented as a whole or in part depending on the requirements...
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Miniaturized solid phase extraction techniques for different kind of pollutants analysis: State of the art and future perspectives – PART 2
PublicationDetermination of pollutants present in environmental samples at a low concentration level very often requires the analytical protocol that includes analytes isolation and/or enrichment prior to the final quantification. Miniaturized SPE offers an interesting alternative to LLE. Nowadays, many types of sorbents are available and can be used as selective materials for extraction of varied analytes in different kinds of samples. The...
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Comparison of different extraction techniques of polychlorinated biphenyls from sediments samples.
PublicationIn this work, problems that may occur during determination of trace levels of polychlorinated biphenyls in sediment samples are described. Main error sources are connected with extraction of analytes prior to final determination. During model studies, polychlorinated biphenyls have been extracted from sedimentreference material (METRANAL 2) with the use of different solvents (dichloromethane, hexsane, and toluene); the process...
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EvOLAP Graph – Evolution and OLAP-Aware Graph Data Model
PublicationThe objective of this paper is to propose a graph model that would be suitable for providing OLAP features on graph databases. The included features allow for a multidimensional and multilevel view on data and support analytical queries on operational and historical graph data. In contrast to many existing approaches tailored for static graphs, the paper addresses the issue for the changing graph schema. The model, named Evolution...
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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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Ireneusz Czarnowski Prof.
PeopleIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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Critical Review on Robust Speed Control Techniques for Permanent Magnet Synchronous Motor (PMSM) Speed Regulation
PublicationThe permanent magnet synchronous motor (PMSM) is a highly efficient energy saving machine. Due to its simple structural characteristics, good heat radiation capability, and high efficiency, PMSMs are gradually replacing AC induction motors in many industrial applications. The PMSM has a nonlinear system and lies on parameters that differ over time with complex high-class dynamics. To achieve the excessive performance operation...
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Big Data Processing by Volunteer Computing Supported by Intelligent Agents
PublicationIn this paper, volunteer computing systems have been proposed for big data processing. Moreover, intelligent agents have been developed to efficiency improvement of a grid middleware layer. In consequence, an intelligent volunteer grid has been equipped with agents that belong to five sets. The first one consists of some user tasks. Furthermore, two kinds of semi-intelligent tasks have been introduced to implement a middleware...
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Emulator and simulator of Terma SCANTER and ARPA radar data server
PublicationThe software solutions presented in this paper generate real-time data compatible with ARPA radar standard as well as Terma SCANTER 2001 radar cooperating with Video Distribution and Tracking (VDT) server. Two different approaches to this problem are considered: emulation based on the data captured from real devices and simulation of objects on the sea. For both of them architecture, implementation details and functional test results...
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Seafloor characterisation using multibeam data: sonar image properties, seabed surface properties and echo properties
PublicationIn 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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NEW AND FAST ANALYTICAL TECHNIQUES IN FOOD QUALITY ANALYSIS 2024
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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First deep eutectic solvent-based (DES) stationary phase for gas chromatography and future perspectives for DES application in separation techniques
PublicationThe paper presents the first application of deep eutectic solvents (DES) as stationary phases for gas chromatography. DES obtained by mixing tetrabutylammonium chloride (TBAC) as a hydrogen bond acceptor (HBA) with heptadecanoic acid being a hydrogen bond donor (HBD) in a mole ratio of HBA:HBD equal to 1:2 was characterized by its ability to separate volatile organic compounds (VOCs). The Rohrschneider – McReynolds constants determined...
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Synteza algorytmu detekcji pęknięcia szyby metodą ''data fission - data fusion''
PublicationPrzedstawiono założenia projektowe oraz proces syntezy algorytmu detekcyjnego akustycznego detektora pęknięcia szyby. W konstrukcji algorytmu użyto techniki rozszczepiania i syntezy danych. Przedstawiono użyte narzędzia badawcze, opracowany model pęknięcia szyby oraz wynki testowania finalnego algorytmu detekcyjnego. Metoda znalazła zastosowanie w konstrukcji akustycznego detektora pęknięcia szyby stosowanego w systemach alarmowych.
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Analysis of radiation and scattering problems with the use of hybrid techniques based on the discrete Green's function formulation of the FDTD method
PublicationIn this contribution, simulation scenarios are presented which take advantage of the hybrid techniques based on the discrete Green's function formulation of the finite-difference time-domain (DGF-FDTD) method. DGF-FDTD solutions are compatible with the finite-difference grid and can be applied for perfect hybridization of the FDTD method. The following techniques are considered: (i) DGF-FDTD for antenna simulations, (ii) DGF-based...
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Assessing Highway Travel Time Reliability using Probe Vehicle Data
PublicationProbe vehicle data (also known as “floating car data”) can be used to analyze travel time reliability of an existing road corridor in order to determine where, when, and how often traffic congestion occurs at particular road segments. The aim of the study is to find the best reliability performance measures for assessing congestion frequency and severity based on probe data. Pilot surveys conducted on A2 motorway in Poland confirm...
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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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Structure of partially reduced xPbO (1-x)SiO2 glasses: combined EXAFS and MD study
PublicationWykorzystując połączenie metody EXAFS (extended X-ray absorption finestructure) i symulacji MD (molecular dynamics) zbadano strukturęczęściowo zredukowanych szkieł ołowiowo-krzemianowych o różnejstechiometrii wyjściowej. W wyniku analizy uzyskano szczegółowyopis struktury lokalnej wokół atomów ołowiu i jej zmiany w funkcjiskładu szkła i poziomu redukcji. Określono również jaką tendencjędo aglomeracji w metaliczne klastry wykazują...