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Search results for: DATA PALM LEAFLERS
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Application Of Generative Adversarial Network for Data Augmentation and Multiplication to Automated Cell Segmentation of the Corneal Endothelium
PublicationConsidering the automatic segmentation of the endothelial layer, the available data of the corneal endothelium is still limited to a few datasets, typically containing an average of only about 30 images. To fill this gap, this paper introduces the use of Generative Adversarial Networks (GANs) to augment and multiply data. By using the ``Alizarine'' dataset, we train a model to generate a new synthetic dataset with over 513k images....
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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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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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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 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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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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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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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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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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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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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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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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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...
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Performance and Emission Modelling and Simulation of Marine Diesel Engines using Publicly Available Engine Data
PublicationTo analyse the behaviour of marine diesel engines in unsteady states for different purposes, for example to determine the fuel consumption or emissions level, to adjust the control strategy, to manage the maintenance, etc., a goal-based mathematical model that can be easily implemented for simulation is necessary. Such a model usually requires a wide range of operating data, measured on a test stand. This is a time-consuming process...
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Impact of information systems (IS) infusion on Open Government Data (OGD) adoption
PublicationPurpose – This study aims to underline the possible influence of the moderator, information systems (IS) infusion, on Open Government Data (OGD) adoption and usage. Design/methodology/approach – Using the partial least squares-structural equation modeling methodological approach, the adapted unified theory of acceptance and use of technology (UTAUT) model has been used for understanding the role of themoderating variable, namely,...
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Data fusion of GPS sensors using Particle Kalman Filter for ship dynamic positioning system
PublicationDepending on standards and class, dynamically positioned ships make use of different numbers of redundant sensors to determine current ship position. The paper presents a multi-sensor data fusion algorithm for the dynamic positioning system which allows it to record the proper signal from a number of sensors (GPS receivers). In the research, the Particle Kalman Filter with data fusion was used to estimate the position of the vessel....
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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)
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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
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OCENA DOBROSTANU W KRAJACH OECD Z WYKORZYSTANIEM DATA ENVELOPMENT ANALYSIS
PublicationDobrostan (well-being) jest pojęciem wieloaspektowym obejmującym czynniki wpływające na satysfakcję z życia. Celem artykułu jest ocena dobrostanu społeczeństw krajów OECD w 2013 roku, na podstawie danych z bazy OECD Regional Well-Being. Uwzględniono 9 obszarów: dochody gospodarstw domowych, miejsce pracy, warunki zamieszkania, poziom wykształcenia, zdrowie, środowisko, bezpieczeństwo, zaangażowanie obywatelskie i dostęp do usług....
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Research and analysis of high-speed data transmission radio link designed for maritime environment
PublicationIn these article the realization of digital radio link for high-speed data transmission was presented. Its concept and practical realization, using USRP devices from National Instruments, were described. Developed software for generation and reception of digital signals in baseband, including description of modulation types, and time and frequency synchronization mechanisms, was presented. Moreover, an operation of designed radio...
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Research and Analysis of High-Speed Data Transmission Radio Link Designed for Maritime Environment
PublicationIn these article, the realization of digital radio link for high-speed data transmission was presented. Its concept and practical realization, using USRP devices from National Instruments, were described. Developed software for generation and reception of digital signals in baseband, including description of modulation types, and time and frequency synchronization mechanisms, was presented. Moreover, an operation of designed radio...
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Prediction of flow boiling heat transfer data for R134a, R600a and R290 in minichannels
PublicationIn the paper presented is the analysis of the results of calculations using a model to predict flow boiling of refrigerants such as R134a, R600a and R290. The latter two fluids were not used in development of model semiempirical correction. For that reason the model was verified with present experimental data. The experimental research was conducted for a full range of quality variation and a relatively wide range of mass velocity....
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Optymalizacja parametrów aplikacji w procesie wytwarzania oprogramowania dla Big Data
PublicationWytwarzanie oprogramowania wiąże się z szeregiem decyzji projektowych obejmujących architekturę aplikacji, wykorzystywane technologie implementacji, jak i zewnętrzne biblioteki. W pracy przedstawiono metodę wyboru technologii i bibliotek związanych z big data, której celem jest optymalizacja atrybutów aplikacji takich jak wydajność działajacej aplikacji jak również optymalizacja procesu wytwarzania oprogramowania. Metoda wyboru...
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Learning sperm cells part segmentation with class-specific data augmentation
PublicationInfertility affects around 15% of couples worldwide. Male fertility problems include poor sperm quality and low sperm count. The advanced fertility treatment methods like ICSI are nowadays supported by vision systems to assist embryologists in selecting good quality sperm. Computer-Assisted Semen Analysis (CASA) provides quantitative and qualitative sperm analysis concerning concentration, motility, morphology, vitality, and fragmentation....
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublicationThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Investigation for Genetic Signature of Radiosensitivity – Data Analysis
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Sediment-quality assessment by intelligent data analysis
PublicationCoraz powszechniej do oceny jakości próbek środowiskowych osadów wykorzystuje się analizy chemometryczne. Ich głównym zadaniem jest znalezienie zależności pomiędzy wynikami analiz chemicznych oraz oszacowanymi parametrami toksyczności.Zastosowanie chemometrii w ocenie jakości próbek środowiskowych umożliwiłoby zredukowanie kosztów biomonitoringu prowadzonego na badanym obszarze poprzez optymalizację procedury badawczej.
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Sensor data fusion techniques for environment modelling
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Carbon-Coated Tellurium for Optical Data Storage
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Multilevel pharmacokinetics-driven modeling of metabolomics data
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Frequent Sequence Mining in Web Log Data
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Analysis of Rainfall Data of Gdansk Meteorological Station
PublicationW pracy przedstawiono wyniki analizy danych opadowych z okresu 51 lat (1951-2008) ze stacji meteorologicznej w Gdańsku. Analizę przeprowadzono zarówno dla sum rocznych opadów jak i sezonowych i miesięcznych. Dokonano również analizy maksymalnych sum dobowych opadów dla każdego miesiąca, badając ich zmienność w wieloleciu.
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Clustering Bathymetric Data for Electronic Navigational Charts
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New distributional data on Bryophytes of Poland, 1
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