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Search results for: data%20mining
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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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A framework of open government data (OGD) e-service quality dimensions with future research agenda
PublicationPurpose This research paper aims to present a framework of open government data (OGD) relating to e-service quality dimensions. In addition, it provides a research agenda for the e-service delivery of OGD. Design/methodology/approach A literature review pertaining to e-service quality with special reference to e-government was delivered to deduce the key dimensions of e-service quality for OGD. Findings Five e-service quality dimensions...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Brownian Motion in Optical Tweezers, a Comparison between MD Simulations and Experimental Data in the Ballistic Regime
PublicationThe four most popular water models in molecular dynamics were studied in large-scale simulations of Brownian motion of colloidal particles in optical tweezers and then compared with experimental measurements in the same time scale. We present the most direct comparison of colloidal polystyrene particle diffusion in molecular dynamics simulations and experimental data on the same time scales in the ballistic regime. The four most...
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Count Data Modeling About Relationship Between Dubai Housing Sales Transactions and Financial Indicators
PublicationIn this study, illustrating and comparing the performances of count data models such as Poisson, negative binomial (NB), Hurdle and zero-inflated models for the determination of factors affected housing sales in Dubai. Model comparisons are made via Akaike’s information criterion (AIC), the Vuong test and examining the residuals. Main purpose of this study is building reliable statistical model for relationship between Dubai housing...
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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublicationDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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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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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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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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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublicationWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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Remote command and control capabilities for data acquisition systems provided by delay-tolerant network mechanisms
PublicationThe paper presents an assessment of a remote device reconfiguration service employing a Delay Tolerant Network (DTN) mechanisms. This service has been implemented as a part of a communication appliance dedicated to marine data transfer in off-shore and open sea areas. The service has been successfully deployed and validation test have been completed. The practical use-case has been defined as remote access to the equipment operating...
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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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Determinants of COVID-19 Impact on the Private Sector: A Multi-Country Analysis Based on Survey Data
PublicationOur paper aims to investigate the impact of COVID‐19 on private sector companies in terms of sales, production, finance and employment. We check whether the country and industry in which companies operate, government financial support and loan access matter to the behaviour and performances of companies during the pandemic. We use a microdata set from a worldwide survey of more than 15,729 companies conducted between April and...
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Global Value Chains and Wages: Multi-Country Evidence from Linked Worker-Industry Data
PublicationThis paper uses a multi-country microeconomic setting to contribute to the literature on the nexus between production fragmentation and wages. Exploiting a rich dataset on over 110,000 workers from nine Eastern and Western European countries and the United States, we study the relationship between individual workers’ wages and industry ties into global value chains (GVCs). We find an inverse (but weak) relationship between the...
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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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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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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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Open extensive IoT research and measurement infrastructure for remote collection and automatic analysis of environmental data.
PublicationInternet of Things devices that send small amounts of data do not need high bit rates as it is the range that is more crucial for them. The use of popular, unlicensed 2.4 GHz and 5 GHz bands is fairly legally enforced (transmission power above power limits cannot be increased). In addition, waves of this length are very diffiult to propagate under field conditions (e.g. in urban areas). The market response to these needs are the...
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Driving Performance Indicators of Electric Bus Driving Technique: Naturalistic Driving Data Multicriterial Analysis
PublicationThe issue of electric energy saving in public transport is becoming the key area of interest. By improving of driving techniques and the implementation of eco-driving, it is possible to save electric energy. Systems that help to decrease energy consumption and to reduce fuel emissions are becoming popular in vehicles powered by diesel engines. However, these methods have not yet gained popularity in electric vehicles. Therefore,...
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Data from the Survey on Entrepreneurs’ Opinions on Factors Determining the Employment of the Gdańsk University of Technology Graduates
PublicationThe dataset includes data from a survey on factors determining the employment of the Gdańsk University of Technology (Gdańsk Tech) graduates’ in the opinion of entrepreneurs. The survey was conducted in 2017. The research sample included 102 respondents representing various firms from the Pomeranian Voivodeship, Poland. The study concerned i.a. factors determining the decision to hire a candidate, methods of recruiting employees,...
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Using Synchronously Registered Biosignals Dataset for Teaching Basics of Medical Data Analysis – Case Study
PublicationMedical data analysis and processing strongly relies on the data quality itself. The correct data registration allows many unnecessary steps in data processing to be avoided. Moreover, it takes a certain amount of experience to acquire data that can produce replicable results. Because consistency is crucial in the teaching process, students have access to pre-recorded real data without the necessity of using additional equipment...
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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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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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Are creative users more apt in reusing and adopting Open Government Data (OGD)? Gender differences
PublicationOpen Government Data (OGD) has been considered as a potent instrument for value creation and innovation by a range of stakeholders. Given that individual ingenuity is a function of individual and environmental factors, it is important to understand how the OGD adoption and usage is a factor of creative performance behaviors (CPB), viz., Problem Identification (PI), Information Search (IS), Idea Generation (IG) and Idea Promotion...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublicationTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Different philosophical approaches to estimating missing data in AHP frameworks for uncertainty representation in risk assessments
PublicationAHP (ang. Analytic Hierarchy Process) jest jedną z metod szeroko stosowaną w wieloatrybutowym podejmowaniu decyzji. Zwykle ekspert lub grupa ekspertów jest proszona o wyrażenie swojej subiektywnej opinii o każdej z par wariantów decyzyjnych. Na tej podstawie tworzone są tzw. macierze ocen. Zdarza się często, że macierze takie są niekompletne i wtedy występuje problem brakujących danych. Referat dotyczy wybranych metod ich uzupełnienia.
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Evaluation of water turbine hydrodynamic thrust bearing performance on the basis of thermoelastohydrodynamic calculations and operational data.
PublicationW pracy przedstawiono analizę konstrukcji łożyska wzdłużnego turbiny wodnej. Łożysko zostało skonstruowane około 50 lat temu, a jego konstrukcja przewiduje kompensację termicznych odkształceń klocków. W analizie uwzględniono odkształcenia łożyska i wymianę ciepła w filmie smarowym i klockach łożyskowych. Poza obecną konstrukcją łożyska przeprowadzono również studium wpływu podstawowych parametrów konstrukcyjnych: grubości klocka...
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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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ACM Journal of Data and Information Quality
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Advances in Modelling and Analysis B: Signals, Information, Data, Patterns
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Nicole Nawrot dr inż.
PeopleDr. Eng. Nicole Nawrot has been employed at the Department of Sanitary Engineering since 2016. In 2021, she obtained a PhD in the field of engineering and technical sciences in the discipline of environmental engineering, mining and energy. Doctoral thesis entitled "Heavy metals in urban retention tanks bottom sediments: distribution, source tracking, and evaluation of phytostabilization adaptability and performance of P. australis...
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Planning Recreation around Water Bodies in Two Hard Coal Post-Mining Areas in Southern Poland
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Risk of cadmium, lead and zinc exposure from consumption of vegetables produced in areas with mining and smelting past
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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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Instrumented end notched flexure - Crack propagation and process zonemonitoring Part II: Data reduction and experimental
PublicationA mode II instrumented end notched flexure three point bending (ENF) adhesion test is described. The adhesive joint consists of two aluminium alloy (AW7075-T6) plates bonded with a structural epoxy adhesive (Hysol EA 9395™). Strain gauges are attached to the outer surface (backface) of the substrates in the lengthwise direction to measure local surface strain during crack propagation. Simultaneously, load/displacement measurements...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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A Fail-Safe NVRAM Based Mechanism for Efficient Creation and Recovery of Data Copies in Parallel MPI Applications
PublicationThe paper presents a fail-safe NVRAM based mechanism for creation and recovery of data copies during parallel MPI application runtime. Specifically, we target a cluster environment in which each node has an NVRAM installed in it. Our previously developed extension to the MPI I/O API can take advantage of NVRAM regions in order to provide an NVRAM based cache like mechanism to significantly speed up I/O operations and allow to preload...
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Early agricultural colonisation of peripheral areas of loess uplands: new data from Sandomierz Upland, Poland
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Wave Method for Structural Health Monitoring: Testing Using Full-Scale Shake Table Experiment Data
PublicationAn algorithm of the wave method for structural health monitoring (SHM) is tested and calibrated using shake table experiment data of a full-scale, seven-story, reinforced-concrete building slice. The method is based on monitoring changes in the velocity of waves propagating vertically through the structure, identified by least-squares (LSQ) fit of beam models. The experiment was conducted by a team from the University of California,...
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Analysis of effect of overloaded vehicles on fatigue life of flexible pavements based on weigh in motion (WIM) data
PublicationOverloaded vehicles have a significant impact on pavement fatigue life and distress. As the studies show, the phenomena intensify when the control of traffic is poor. The paper presents the results of the research including analysis of weigh in motion data from eight stations and analysis of asphalt pavement fatigue caused by mixed traffic. Distributions of vehicles axles load including the multiple axles effects are presented....
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Investigating impacts of asphalt mixture properties on pavement performance using LTPP data through random forests
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Spatial and Temporal Variability of Moisture Condition in Soil-Plant Environmet using Spectral Data and GIS Tools
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Ephemeral wetland communities of Isoëto-Nano-Juncetea class – new data from south-eastern Poland
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Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers
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Seafloor characterisation using multibeam data: sonar image properties, seabed surface properties and echo properties
PublicationIn the paper, the approach to seafloor characterisation is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry and underwater object detection and imaging, are also the promising tool in seafloor characterization and classification, having several advantages over conventional single beam echosounders. The proposed approach relies on the combined, concurrent use...
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Data analysis of FTIR spectra for study of outlet gases of Solid Oxide Fuel Cells fuelled by biogas
PublicationW pracy przedstawiono system umożliwiający połączenie spektroskopii FTIR z specjalnie zaprojektowanym oprogramowaniem w celu uzyskania informacji o stężeniach gazów wylotowych z ogniw paliwowych SOFC. Przebadane zostały główne produkty reformingu biogazu: tlenek węgla, dwutlenek węgla, metan oraz wodór. Opisane oprogramowanie umożliwia w prosty i szybki sposób uzyskanie informacji o gazach wylotowych ogniwa paliwowego.
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MATCHED FILTER APPROACH FOR MICROSEISMIC SIGNAL PROCESSING OF REAL DATA FROM EAST POMERANIA SHALE GAS
PublicationThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing (HF)process. An array of several hundred geophones is placed on the surface to record little ground tremors induced by fracturing process. Filtration and summation of signals from geophones is essential to identify and locate fracturing events from underground. Authors propose a method of matched filtering, that is usually...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublicationArticle presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.