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Search results for: NAMED DATA NETWORKING
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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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Estimating the Average Speed of Public Transport Vehicles Based on Traffic Control System Data
PublicationIntelligent Transport Systems are a valuable source of traffic information, covering both private and public vehicles. The main problem, however, is that very few studies are conducted to determine the speed of buses, trams and trolleys in urban networks in relation to traffic conditions. The paper investigates how ITS systems data could be used to model the speed of Public Transport vehicles. This is now possible thanks to the...
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Anna Baj-Rogowska dr
PeopleAnna Baj-Rogowska is employed as an assistant professor at the Department of Informatics in Management at the Faculty of Management and Economics, Gdańsk University of Technology. Her higher education is connected with the University of Gdańsk, where she graduated from a master's degree in business informatics, doctoral studies and then obtained a PhD degree in economics in management science (Department of Business Informatics...
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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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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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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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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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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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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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Changes in the addiction prevalence in Polish population between 1990-2019: Review of available data
PublicationThe 1989 collapse of the socialist political system in Poland initiated an avalanche of modifications regarding healthcare policy resulting with new institutions and programs dedicated to monitoring and preventing addiction. In the current article, we look at the available data allowing to track changes in (1) the prevalence of exposure to addictive substances and behaviors, and (2) changes of addictions prevalence in Poland...
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Qualitative Data Analysis Methods -Summer 22/23
e-Learning Courses -
Data Warehouses - Part-time studies - 2022/2023
e-Learning CoursesThe curse is led for part-time studies, on the first semester of postgraduate studies.
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WETI (Data Engineering) - Mathematics 2021/22 (M.Musielak)
e-Learning Courses -
WETI (Data Engineering) - Mathematics 2022/23 (M.Musielak)
e-Learning Courses -
WETI (Data Engineering) - Mathematics 2019/20 (M.Musielak)
e-Learning Courses -
Data Warehouses - Part-time studies - 2023/2024
e-Learning CoursesThe curse is led for part-time studies, on the first semester of postgraduate studies.
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Analiza danych typu Big Data 2023/24
e-Learning Courses -
Integration Data Model of the Bathymetric Monitoring System for Shallow Waterbodies Using UAV and USV Platforms
PublicationChanges in the seafloor relief are particularly noticeable in shallow waterbodies (at depths up to several metres), where they are of significance for human safety and environmental protection, as well as for which the highest measurement accuracy is required. The aim of this publication is to present the integration data model of the bathymetric monitoring system for shallow waterbodies using Unmanned Aerial Vehicles (UAV) and...
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Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation
PublicationModern data acquisition technologies provide large datasets that are not always necessary in its entirety to properly accomplish the goal of the study. In addition, such datasets are often cumbersome for rational processing, and their processing is time and labour consuming. Therefore, methods that enable to reduce the size of the measurement dataset, such as the generalization of the Digital Terrain Model (DTM) or the reduction...
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Geographic information system for remote integration of diverse under-water acoustic sensor data
PublicationMaritime and port areas throughout the world are exposed to many different hazards, like pollution, terrorism and natural disasters. Early detection, identification and preparation of appropriateesponse strategies is especially important in the case of semi-enclosed basins like the Baltic Sea, mainly due to the marine ecosystems' continuous absorption of pollutants including oil, heavy metals and chemicals. Many of those agents...
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Qualitative evaluation of distributed clinical systems supporting research teams working on large-scale data
PublicationInthispaper,fivecontemporaryscalablesystemstosupportmedicalresearchteams are presented. Their functionalities extend from heterogeneous unstructured data acquisition through large-scale data storing, to on-the-fly analyzing by using robust methods. Such kinds of systems can be useful in the development of new medical procedures and recommendation rules for decision support systems. A short description of each of them is provided....
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublicationWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublicationIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Static Load Test on Instrumented Pile – Field Data and Numerical Simulations
PublicationFor some time (since 8-10 years in Poland) a special static load tests on instrumented piles are carried out. Such studies are usually of a scientific nature and provide detailed quantitative data on the load transfer into the ground and characteristics of particular soil layers interaction with a pile shaft and pile base. Deep knowledge about the pile-subsoil interaction can be applied for a various design purposes, e.g. numerical...
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The influence of climate change on the life insurance in the EU: A panel data approach
PublicationThe financial sector, as one of the most sensitive economic sectors, is alert to all trends and changes in the environment. The aim of the article is to study the impact of climate change on the life insurance market using panel data from 28 countries of the European Union (EU) for the last 9 years. This study is based on a panel model, where the amount of premiums under life insurance contracts is defined as a function of the...
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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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Enhanced Eye-Tracking Data: a Dual Sensor System for Smart Glasses Applications
PublicationA technique for the acquisition of an increased number of pupil positions, using a combined sensor consisting of a low-rate camera and a high-rate optical sensor, is presented in this paper. The additional data are provided by the optical movement-detection sensor mounted in close proximity to the eyeball. This proposed solution enables a significant increase in the number of registered fixation points and saccades and can be used...