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Firm-Level Internationalisation from the Theoretical Perspective: Knowledge-based Approach
PublikacjaThe objective of the paper is to present the role of knowledge in internationalisation process of the firm as well as the selected theoretical proposals which assume that the role of knowledge in international expansion of firms is crucial. The article first presents the selected but best known, the oldest internationalisation paradigms. Then it shows the direction of development of theoretical perspectives.
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Elastic protection coasting for ship tanks to increase environment protection level
PublikacjaW opracowaniu przedstawiono ideę nowego rozwiązania dla podniesienia bezpieczeństwa zbiorników paliwowych statków, polegającą na wprowadzeniu do zbiornika drugiej - elastycznej bariery ochronnej opartej na warstwie wypełniacza.
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Development level differences among European countries. Cross country study
PublikacjaRozdział w monografii zawiera analizę poziomu rozwoju gospodarczego dla 27 krajów Europy. W tekście autorzy traktują rozwój gospodarczy jako zjawisko wielowymiarowe. Poziom rozwoju gospodarczego jest szacowany na podstawie miary indeksowej.
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City scan as a tool to assess resilience challenges and vulnerabilities at the community level
PublikacjaThe majority of the world’s population lives in cities and cities are the key to achieving resilience. Local governments own only part of the land and can only partially decide about measures that should be taken ‘on the ground’. Local governments are therefore highly dependent on individuals, communities, and businesses to adapt and transform and take action in their own backyards or neighbourhoods. Since, for many people, climate...
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New data acquisition system for birch sap concentrate production using the reverse osmosis technology
PublikacjaThe 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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Gdańsk 2019 Jana z Kolna street - video data
Dane BadawczeGdańsk 2019 Jana z Kolna street - video data
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Automatic Cleaning of Time Series Data in Rural Internet of Things Ecosystems That Use Nomadic Gateways
PublikacjaA serious limitation to the deployment of IoT solutions in rural areas may be the lack of available telecommunications infrastructure enabling the continuous collection of measurement data. A nomadic computing system, using a UAV carrying an on-board gateway, can handle this; it leads, however, to a number of technical challenges. One is the intermittent collection of data from ground sensors governed by weather conditions for...
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A New Coupler Concept for Contactless High-Speed Data Transmission Monitoring
PublikacjaThis 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
PublikacjaExisting 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
PublikacjaThe 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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The pulse width modulation strategy for a five-phase three-level NPC voltage source inverter with DC-link voltage balancing ability
PublikacjaThe doctoral dissertation is all about the development of the space vector modulation algorithm for controlling the generation of output voltage vectors in a three-level, five-phase NPC inverter. The developed algorithm can be used to control five-phase motors, where it will be possible to increase the motor torque by 15%; by appropriate injection of 3rd harmonic current. The proposed control approach also opens up the possibility...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublikacjaAs 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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Performance of data transmission in UMTS with turbo code about decreased number of states
PublikacjaIn 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
PublikacjaArtificial 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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Is data management a new “digitisation”? A change of the role of librarians in the context of changing academic libraries’ tasks
PublikacjaAcademic 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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Which Curve Fits Best: Fitting ROC Curve Models to Empirical Credit-Scoring Data
PublikacjaIn 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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Floodplain inundation Mapping using SAR Scattering Coefficient Thresholding and Observed Discharge Data
PublikacjaInundation 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
PublikacjaThe 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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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether 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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Application Of Generative Adversarial Network for Data Augmentation and Multiplication to Automated Cell Segmentation of the Corneal Endothelium
PublikacjaConsidering 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
PublikacjaIn 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
PublikacjaWe 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
PublikacjaWe 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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Virtual Space Vector Pulse Width Modulation Algorithm for Three-Level NPC Converters Based on the Final Element Shape Functions
PublikacjaThe paper puts forth a novel idea for the computation of Nearest Three Virtual Space Vector Pulse Width Modulation for the three level NPC converters. The computations are based on the concept of final element shape function widely used in the domain of finite element analysis. The proposed approach significantly frees the computations from the use of trigonometric functions, which simplifies the computations and permits easier...
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A model, design, and implementation of an efficient multithreaded workflow execution engine with data streaming, caching, and storage constraints
PublikacjaThe 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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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn 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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Simulation of Direct-Sequence Spread Spectrum Data Transmission System for Reliable Underwater Acoustic Communications
PublikacjaUnderwater 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
PublikacjaIn 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
PublikacjaSignificant 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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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Method for determining of shallow water depths based on data recorded by UAV/USV vehicles and processed using the SVR algorithm
PublikacjaBathymetric measurements in waters shallower than 1 m are necessary to monitor seafloor relief changes in the coastal zone. This is especially important for ensuring the safety of navigation, navigation efficiency, as well as during the design and monitoring of hydrotechnical structures. Therefore, the aim of this article is to present a method for determining of shallow water depths based on data recorded by Unmanned Aerial Vehicle...
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[ITiT] Technologies of Spatial Data Analysis and Processing
Kursy Online{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
Kursy Online -
Changes in the addiction prevalence in Polish population between 1990-2019: Review of available data
PublikacjaThe 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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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublikacjaOpen 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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Geographic information system for remote integration of diverse under-water acoustic sensor data
PublikacjaMaritime 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
PublikacjaModern 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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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublikacjaIn 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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Qualitative evaluation of distributed clinical systems supporting research teams working on large-scale data
PublikacjaInthispaper,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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Static Load Test on Instrumented Pile – Field Data and Numerical Simulations
PublikacjaFor 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
PublikacjaThe 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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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe 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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Data and knowledge supporting decision-making for the urban Food-Water-Energy nexus
PublikacjaCities are hubs of innovation and wealth creation, and magnets for an increasing urban population. Cities also face unprecedented challenges in terms of food, water and energy scarcity, and governance and management. Urban environmental issues are no longer problems for experts to address but have become issues of public debate, in which knowledge from multiple sectors is needed to support inclusive governance approaches. Consequently,...
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Enhanced Eye-Tracking Data: a Dual Sensor System for Smart Glasses Applications
PublikacjaA 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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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublikacjaIn 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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Impact of information systems (IS) infusion on Open Government Data (OGD) adoption
PublikacjaPurpose – 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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High-Performance Machine-Learning-Based Calibration of Low-Cost Nitrogen Dioxide Sensor Using Environmental Parameter Differentials and Global Data Scaling
PublikacjaAccurate tracking of harmful gas concentrations is essential to swiftly and effectively execute measures that mitigate the risks linked to air pollution, specifically in reducing its impact on living conditions, the environment, and the economy. One such prevalent pollutant in urban settings is nitrogen dioxide (NO2), generated from the combustion of fossil fuels in car engines, commercial manufacturing, and food processing. Its...
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Data fusion of GPS sensors using Particle Kalman Filter for ship dynamic positioning system
PublikacjaDepending 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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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection
PublikacjaThis study presents an assessment of familial hypercholesterolemia (FH) probability using different algorithms (CatBoost, XGBoost, Random Forest, SVM) and its ensembles, leveraging electronic health record data. The primary objective is to explore an enhanced method for estimating FH probability, surpassing the currently recommended Dutch Lipid Clinic Network (DLCN) Score. The models were trained using the largest Polish cohort...
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Optymalizacja parametrów aplikacji w procesie wytwarzania oprogramowania dla Big Data
PublikacjaWytwarzanie 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...