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Search results for: PROBE VEHICLE DATA
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Data gathering methods : review - questionnaire
PublicationArtykuł przedstawia koncepcję, pochodzenie oraz zastosowania dla jednej z metod oceny użyteczności - wywiadu, wraz z jego głównym narzędziem - ankietami. Stanowi część przeglądu dostępnych metod poprawy użyteczności.
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Data gathering methods : card sorting
PublicationArtykuł przedstawia koncepcję, pochodzenie oraz zastosowania dla jednej z metod oceny użyteczności i budowania menu w aplikacjach informatycznych - sortowania kart. Stanowi część przeglądu dostępnych metod poprawy użyteczności.
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Multimedia data mining for e-Commerce.
PublicationPrzedstawiono studium porównawcze metod eksploracji danych dla e-Commerce.Skupiono się na studium przypadku aplikacji medycznych - wyszukiwania przypadków podobnych.
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Ensemble Classifier for Mining Data Streams
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"Big data" i Wielki Brat
PublicationFelieton popularnonaukowy dotyczący ochrony prywatności danych.
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Deduplication of Position Data and Global Identification of Objects Tracked in Distributed Vessel Monitoring System
PublicationVessel monitoring systems (VMS) play a very important role in safety navigation. In most cases, their structure is distributed and they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Such approach results in several objects identification and position data duplication problems, which need to be solved in order to ensure the correct performance of a given VMS....
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Comparison of Traffic Flow Models with Real Traffic Data Based on a Quantitative Assessment
PublicationThe fundamental relationship of traffic flow and bivariate relations between speed and flow, speed and density, and flow and density are of great importance in transportation engineering. Fundamental relationship models may be applied to assess and forecast traffic conditions at uninterrupted traffic flow facilities. The objective of the article was to analyze and compare existing models of the fundamental relationship. To that...
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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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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Computational complexity and length of recorded data for fluctuation enhanced sensing method in resistive gas sensors
PublicationThis paper considers complexity and accuracy of data processing for gas detection using resistance fluctuation data observed in resistance gas sensors. A few selected methods were considered (Principal Component Analysis – PCA, Support Vector Machine – SVM). Functions like power spectral density or histogram were used to create input data vector for these algorithms from the observed resistance fluctuations. The presented considerations...
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Dynamic Data Management Among Multiple Databases for Optimization of Parallel Computations in Heterogeneous HPC Systems
PublicationRapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting of multiple collections of nodes with different types of computing devices. The execution engine of the system is open for...
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Processing of LiDAR and Multibeam Sonar Point Cloud Data for 3D Surface and Object Shape Reconstruction
PublicationUnorganised point cloud dataset, as a transitional data model in several applications, usually contains a considerable amount of undesirable irregularities, such as strong variability of local point density, missing data, overlapping points and noise caused by scattering characteristics of the environment. For these reasons, further processing of such data, e.g. for construction of higher order geometric models of the topography...
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European Multicenter Evaluation of High-Density DNA Probe Arrays for Detection of Hepatitis B Virus Resistance Mutations and Identification of Genotypes
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A Comprehensive Framework for Measuring Governments’ Digital Initiatives Including Open Data
PublicationDigital innovation and digital initiatives are generally recognized and considered to be the driving forces behind firm survival and success in the market. This is not the case in the public sector, where digital initiatives have suffered not only from a lack of research trying to explain them but also from a major lack of recognition of their importance. The government’s eagerness to introduce more digital initiatives for better...
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IV Pomorska Konferencja Open Science - udostępnianie danych badawczych (sharing research data)
EventsTematyka Otwartej Nauki jest coraz bardziej rozpowszechniona. Zarówno udostępnianie wyników badań w postaci publikacji jak i danych badawczych jest coraz częściej wymogiem instytucji i agencji finansujących badania naukowe. Tworzone są liczne rekomendacje, dobre praktyki i polityki w zakresie wprowadzania otwartego dostępu. Celem konferencji jest zebranie...
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Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
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Radio system for monitoring and acquisition of data from traffic enforcement cameras - features and assumptions of the system
PublicationThe study presents the architecture and selected functional assumptions of Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (RSMAD). Ultimately, the system will be used for transmission and archiving image data of traffic offenses, but can also perform other duties related to traffic safety. Implementation of the RSMAD system will facilitate, inter alia, issuing the fine process and supervision...
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[ITiT] Technologies of Spatial Data Analysis and Processing
e-Learning Courses{mlang pl} Dyscyplina: Informatyka Techniczna i Telekomunikacja Zajęcia obowiązkowe dla doktorantów II roku Prowadzący: dr hab. inż. Marcin Kulawiak Liczba godzin: 30 h Forma zajęć: wykład/seminarium {mlang} {mlang en} Discipline: Technical Informatics and Telecommunications Obligatory course for 2nd year PhD students Academic teacher: dr hab. inż. Marcin Kulawiak Total hours of training: 30 teaching hours Course...
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Scientific methods of computer data analysis and presentation
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New data acquisition system for birch sap concentrate production using the reverse osmosis technology
PublicationThe work presents a simple electronic device that helps to monitor the basic parameters of the reverse osmosis (RO) system during the concentration of birch tree sap. The construction costs are low (around 150 Euro) but the functionality of the device is high. It has an in-build two channel conductometer and can measure the volumetric flow rate of two streams of liquids. The collected data are transmitted wirelessly via Bluetooth...
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Price bubbles in commodity market – A single time series and panel data analysis
PublicationThis paper examines thirty-five commodities, grouped into three market sectors (energy, metals, agriculture & livestock) in terms of the occurrence of price bubbles. The study was based on monthly data for each commodity separately and, in a panel approach, for selected sectors and for all commodities combined. The GSADF test and its version for panel data – panel GSADF – were used to identify bubbles. The beginning and end of...
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A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors
PublicationIn recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones,...
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LIDAR data from a topographic survey conducted in the area where the Gdańsk Głowa Fortress was located
Open Research DataThe measurement data was obtained during research aimed at utilizing LiDAR observations to detect remnants of the historical complex of the Gdańsk Głowa Fortress. The collected information comes from a spatial survey conducted using a scanner mounted on an unmanned aerial vehicle. This advanced measurement system allows for precise registration of the...
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A New Coupler Concept for Contactless High-Speed Data Transmission Monitoring
PublicationThis paper presents a new concept of a couplerthat can be applied to high-speed data transmission contactlessmeasurements. The proposed approach is dedicated for differentialsignal transmission monitoring in microstrip coupled lineson printed circuit boards (PCBs). The coupler, produced on aseparate PCB, is overlayed on the transmission line with thedifferential signal and delivers decoupled differential signal tothe main measurement...
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Reconstruction Methods for 3D Underwater Objects Using Point Cloud Data
PublicationExisting methods for visualizing underwater objects in three dimensions are usually based on displaying the imaged objects either as unorganised point sets or in the form of edges connecting the points in a trivial way. To allow the researcher to recognise more details and characteristic features of an investigated object, the visualization quality may be improved by transforming the unordered point clouds into higher order structures....
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3D Object Shape Reconstruction from Underwater Multibeam Data and Over Ground Lidar Scanning
PublicationThe technologies of sonar and laser scanning are an efficient and widely used source of spatial information with regards to underwater and over ground environment respectively. The measurement data are usually available in the form of groups of separate points located irregularly in three-dimensional space, known as point clouds. This data model has known disadvantages, therefore in many applications a different form of representation,...
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Which Curve Fits Best: Fitting ROC Curve Models to Empirical Credit-Scoring Data
PublicationIn the practice of credit-risk management, the models for receiver operating characteristic (ROC) curves are helpful in describing the shape of an ROC curve, estimating the discriminatory power of a scorecard, and generating ROC curves without underlying data. The primary purpose of this study is to review the ROC curve models proposed in the literature, primarily in biostatistics, and to fit them to actual credit-scoring ROC data...
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Is data management a new “digitisation”? A change of the role of librarians in the context of changing academic libraries’ tasks
PublicationAcademic libraries’ tasks have been evolving over the years. The changes have been stimulated by appearing of electronic resources, automated library systems, digital libraries and Open Access (OA) repositories. Librarians’ tasks and responsibilities in the academic environment have been evolving in accordance with new tasks they were expected to assume. A few years ago there was a discussion during which an attempt was made to...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Big Data Paradigm Developed in Volunteer Grid System with Genetic Programming Scheduler
PublicationArtificial intelligence techniques are capable to handle a large amount of information collected over the web. In this paper, big data paradigm has been studied in volunteer and grid system called Comcute that is optimized by a genetic programming scheduler. This scheduler can optimize load balancing and resource cost. Genetic programming optimizer has been applied for finding the Pareto solu-tions. Finally, some results from numerical...
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Performance of data transmission in UMTS with turbo code about decreased number of states
PublicationIn the paper a structure of turbo encoder and decoder about decreased number of states has been described. The simulation results of transmission performance based on turbo coding without the reduction of the number of iterations for the uplink and downlink of WCDMA/FDD interface have been presented. The SOVA algorithm for turbo decoding has been used. The investigations have been carried out for Outdoor to Indoor & Pedestrian...
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Floodplain inundation Mapping using SAR Scattering Coefficient Thresholding and Observed Discharge Data
PublicationInundation area time series are important for wetlands monitoring and hydrological model validation. This study is conducted in Biebrza floodplain, which is a natural wetland with complex inundation generation processes. In order to map 2014-2018 series of inundation in the floodplain we test our automatic thresholding method on Sentinel 1 data. The threshold value is optimized using correlation of the inundation area with observed...
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Three-dimensional mapping for data collected using variable stereo baseline
PublicationThe paper describes a system of 3D mapping of data collected with due regard for variable baseline. This solution constitute an extension to a VisRobot sub-system developed as a subsystem, necessary for implementing the generic idea of using mobile robots to explore an indoor static environment. This subsystem is to acquire stereo images, calculate the depth in the images and construct the sought 3D map. Stereo images are obtained...
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Choosing Exploration Process Path in Data Mining Processes for Complex Internet Objects
PublicationWe present an experimental case study of a novel and original framework for classifying aggregate objects, i.e. objects that consist of other objects. The features of the aggregated objects are converted into the features of aggregate ones, by use of aggregate functions. The choice of the functions, along with the specific method of classification can be automated by choosing of one of several process paths, and different paths...
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Choosing Exploration Process Path in Data Mining Processes for Complex Internet Objects
PublicationWe present an experimental case study of a novel and original framework for classifying aggregate objects, i.e. objects that consist of other objects. The features of the aggregated objects are converted into the features of aggregate ones, by use of aggregate functions. The choice of the functions, along with the specific method of classification can be automated by choosing of one of several process paths, and different paths...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Testing HIADAC high impedance analyzer in Trento University laboratory on protective foil using 2-wire probe 24h exposition
Open Research DataThe dataset presents impedance spectrum of anticorrosion foil (coating) protecting aluminium frame . This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole...
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Testing HIADAC high impedance analyzer in Trento University laboratory on protective foil using 2-wire probe 48h exposition
Open Research DataThe dataset presents impedance spectrum of anticorrosion foil (coating) protecting aluminium frame . This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole...
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A model, design, and implementation of an efficient multithreaded workflow execution engine with data streaming, caching, and storage constraints
PublicationThe 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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Assessing business process complexity based on textual data: Evidence from ITIL IT ticket processing
PublicationPurpose This study aims to draw the attention of business process management (BPM) research and practice to the textual data generated in the processes and the potential of meaningful insights extraction. The authors apply standard natural language processing (NLP) approaches to gain valuable knowledge in the form of business process (BP) complexity concept suggested in the study. It is built on the objective, subjective and meta-knowledge...
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Simulation of Direct-Sequence Spread Spectrum Data Transmission System for Reliable Underwater Acoustic Communications
PublicationUnderwater acoustic communication (UAC) system designers tend to transmit as much information as possible, per unit of time, at as low as possible error rate. It is a particularly difficult task in a shallow underwater channel in which the signal suffers from strong time dispersion due to multipath propagation and refraction phenomena. The direct-sequence spread spectrum technique (DSSS) applied successfully in the latest standards...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Data set generation at novel test-rig for validation of numerical models for modeling granular flows
PublicationSignificant effort has been exerted on developing fast and reliable numerical models for modeling particulate flow; this is challenging owing to the complexity of such flows. To achieve this, reliable and high-quality experimental data are required for model development and validation. This study presents the design of a novel test-rig that allows the visualization and measurement of particle flow patterns during the collision...
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Evidence for solid state electrochemical degradation within a small molecule OLED
PublicationAcridone derivative have been synthesised and used as OLED (Organic Light Emitting Diode) emitters which were found to be electroactive. Electrochemical investigations showed a side reaction takes place inside an active layer which diminished the overall device efficiency. By using a dopant and host active layer architecture, the formation of the by product was removed. The by-product was identified as a σ-dimer formed inside an...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Evaluation and application of data from road weather stations for winter maintenance management
PublicationThe paper presents the analysis of road weather data from meteorological stations located at the Polish national roads of Pomerania District during the impact of winter conditions. Presented issue is particularly important from the point of view the problem of winter maintenance and especially for prediction and assurance of quality of asphalt pavement surface ie. resistance to low temperature cracking or risk of glazed frost....
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Optimization of Data Assignment for Parallel Processing in a Hybrid Heterogeneous Environment Using Integer Linear Programming
PublicationIn the paper we investigate a practical approach to application of integer linear programming for optimization of data assignment to compute units in a multi-level heterogeneous environment with various compute devices, including CPUs, GPUs and Intel Xeon Phis. The model considers an application that processes a large number of data chunks in parallel on various compute units and takes into account computations, communication including...
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The Positioning Accuracy of BAUV Using Fusion of Data from USBL System and Movement Parameters Measurements
PublicationThe article presents a study of the accuracy of estimating the position coordinates of BAUV (Biomimetic Autonomous Underwater Vehicle) by the extended Kalman filter (EKF) method. The fusion of movement parameters measurements and position coordinates fixes was applied. The movement parameters measurements are carried out by on-board navigation devices, while the position coordinates fixes are done by the USBL (Ultra Short Base...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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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...