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Wyniki wyszukiwania dla: big data deep learning remote medical diagnostic
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Monitoring Artificial Light Pollution Using a Multispectral Camera
PublikacjaStudying the adverse effects of artificial light pollution requires systematic monitoring using various methods. One commonly used technique involves assessing the intensity of light reflected from surfaces with different types of digital cameras at various measurement levels. However, this approach does not always fully capture the characteristics of the light source itself. In our study, we focused on the potential application...
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CNN-CLFFA: Support Mobile Edge Computing in Transportation Cyber Physical System
PublikacjaIn the present scenario, the transportation Cyber Physical System (CPS) improves the reliability and efficiency of the transportation systems by enhancing the interactions between the physical and cyber systems. With the provision of better storage ability and enhanced computing, cloud computing extends transportation CPS in Mobile Edge Computing (MEC). By inspecting the existing literatures, the cloud computing cannot fulfill...
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Hydration of aprotic donor solvents studied by means of FTIR spectroscopy
PublikacjaThe paper attempts to explain the mutual influence of nonpolar and electron-donor groups on solute hydration,the problem of big importance for biological aqueous systems. Aprotic organic solvents have been used asmodel solutes, differing in electron-donating power. Hydration of acetonitrile, acetone, 2-butanone, andtriethylamine has been studied by HDO and (partially) H2O spectra. The quantitative version of...
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Point cloud unification with optimization algorithm
PublikacjaTerrestrial laser scanning is a technology that enables to obtain three-dimensional data – an accurate representation of reality. During scanning not only desired objects are measured, but also a lot of additional elements. Therefore, unnecessary data is being removed, what has an impact on efficiency of point cloud processing. It can happen while single point clouds are displayed – user decides what he wants...
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Technical Engine for Democratization of Modeling, Simulations, and Predictions
PublikacjaComputational science and engineering play a critical role in advancing both research and daily-life challenges across almost every discipline. As a society, we apply search engines, social media, and se- lected aspects of engineering to improve personal and professional growth. Recently, leveraging such aspects as behavioral model analysis, simulation, big data extraction, and human computation is gain- ing momentum. The nexus...
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Supramolecular deep eutectic solvents and their applications
PublikacjaIn recent years, the growing awareness of the harmfulness of chemicals to the environment has resulted in the development of green and sustainable technologies. The compromise between economy and environmental requirements is based on the development of new efficient and green solutions. Supramolecular deep eutectic solvents (SUPRADESs), a new deep eutectic solvent (DES) subclass characterized by inclusion properties, are a fresh...
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Changes in conditions of acoustic wave propagation in the Gdansk deep as an effect of climate changes in the Baltic Sea region
PublikacjaThe article presents the results from a research project investigating acoustic climate changes in the Gdansk Deepbased on data extending from 1902 to 2019. This part of the southern Gotland Basin, is rarely discussed in thescientific literature.The speed of sound in the seawater is a function of temperature, salinity, and depth. In such shallow sea asBaltic Sea, the impact of depth is not substantial....
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Narzędzia i metody obliczeń z użyciem MATLABa
WydarzeniaDn. 19.03.2020 w godz. 10.00–13.15 na Politechnice Gdańskiej odbędzie się seminarium w języku angielskim poświęcone wykorzystaniu MATLABa w badaniach naukowych i dydaktyce.
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High resolution optical and acoustic remote sensing datasets of the Puck Lagoon
PublikacjaThe very shallow marine basin of Puck Lagoon in the southern Baltic Sea, on the Northern coast of Poland, hosts valuable benthic habitats and cultural heritage sites. These include, among others, protected Zostera marina meadows, one of the Baltic’s major medieval harbours, a ship graveyard, and likely other submerged features that are yet to be discovered. Prior to this project, no comprehensive high-resolution remote sensing...
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Comparison of PCBs and PAHs levels in European coastal waters using mussels from the Mytilus edulis complex as biomonitors
PublikacjaMussels from the Mytilus edulis complex were used as biomonitors for two groups of organic pollutants: polychlorinated biphenyls (PCBs, congeners: 28, 52, 101, 118, 138, 153 and 180) and polycyclic aromatic hydrocarbons (PAHs, naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benz(a)anthracene, chrysene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, indeno(1,2,3-cd)pyrene,...
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Preliminary safety assessment of Polish interchanges
PublikacjaInterchanges are a key and the most complex element of a road infrastructure. The safety and functionality of interchanges determine the traffic conditions and safety of the entire road network. This applies particularly to motorways and express-ways, for which they are the only way to access and exchange traffic. A big problem in Poland is the lack of comprehensive tools for designers at individual stages of the design process....
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Activity of isavuconazole and other triazole derivatives against clinical isolates of Aspergillus fumigatus
PublikacjaAspergillus fumigatus is the most frequent pathogen of the genus Asperillus, which is highly susceptible to triazole derivatives, especially to isavuconazole and voriconazole. Many countries face a growing problem of infections due to A. fumigatus showing acquired resistance to one or several triazoles. In medical centres, monitoring the susceptibility of isolated Aspergillus spp. is recommended. The aim of this study was to collect...
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Interspecific and intraspecific variation in organochlorine pesticides and polychlorinated biphenyls using non-destructive samples from Pygoscelis penguins
PublikacjaAs humans are present in Antarctica only for scientific and tourism-related purposes, it is often described as a pristine region. However, studies have identified measurable levels of Persistent Organic Pollutants (POPs), such as organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs), in the Antarctic region. These are highly toxic anthropogenic compounds with tendency to travel long distances and reach remote environments, where...
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Quantifying inconsistencies in the Hamburg Sign Language Notation System
PublikacjaThe advent of machine learning (ML) has significantly advanced the recognition and translation of sign languages, bridging communication gaps for hearing-impaired communities. At the heart of these technologies is data labeling, crucial for training ML algorithms on a huge amount of consistently labeled data to achieve models that generalize well. The adoption of language-agnostic annotations is essential to connect different sign...
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
PublikacjaBearing defect is statistically the most frequent cause of an induction motor fault. The research described in the paper utilized the phenomenon of the current change in the induction motor with bearing defect. Methods based on the analysis of the supplying current are particularly useful when it is impossible to install diagnostic devices directly on the motor. The presented method of rolling-element bearing diagnostics used indirect...
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A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors
PublikacjaIn 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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Dominika Wróblewska dr inż. arch.
OsobyDr inż. arch. Dominika Wróblewska, profesor uczelni uzyskała tytuł doktora nauk technicznych w 2000 roku. Od 2002 roku rozpoczęła pracę na wydziale Budownictwa Wodnego i Inżynierii Środowiska na Politechnice Gdańskiej (obecnie wydział Inżynierii Lądowej i Środowiska) na stanowisku adiunkta. Od 2019 roku pracuje na stanowisku profesora uczelni. Obszary zainteresowań to zmiany wprowadzanie edukacji opartej na interdyscyplinarnym...
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Aleksander Mroziński dr inż.
OsobyAleksander Mroziński jest doktorantem na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej. Od czerwca 2019r. został zatrudniony na stanowisku redaktora metadanych w projekcie MOST DANYCH. Ponadto jest uczestnikiem trzech innych projektów realizowanych na Politechnice Gdańskiej: InterPhD II, OPUS 13 oraz PROM. Chęć poznawania świata sprawia, że stara się zdobywać multidyscyplinarną wiedzę oraz umiejętności...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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A Fast and Accurate Prediction of Distortions in DCT-Based Lossy Image Compression
PublikacjaSince the number of acquired images and their size have the tendency to increase, their lossy compression is widely applied for their storage, transfer, and dissemination. Simultaneously with providing a relatively large compression ratio, lossy compression produces distortions that are inevitably introduced and have to be controlled. The properties of these distortions depend on several factors such as image properties, the...
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Exploring the Beam Squint Effects on Reflectarray Perfromance: A Comprehensive Analysis of the Specular and Scattered Reflection of the Unit Cell
PublikacjaIn this article, the phenomena of beam deviation in reflectarray is discussed. The radiation pattern of the unit cell, which plays a vital role in shaping the beam of the reflectarray, is analyzed by considering undesired specular and scattered reflections. These unwanted reflections adversely affect the pattern of the single unit cell, thereby reducing the overall performance of the reflectarray. To conduct our investigations,...
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Consequences of lysine auxotrophy for Candida albicans adherence and biofilm formation
PublikacjaA number of factors are known to be involved in Candida albicans virulence, although biofilm development on the surfaces of indwelling medical devices is considered to promote superficial or systemic disease. Based on previously reported up-regulation of saccharopine and acetyllysine in biofilm cells and activation of the lysine biosynthesis/degradation pathway, we investigated...
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Gold nanoparticles evaluation using functional optical coherence tomography
PublikacjaThe main object of this research was to assess the ability to characterize the gold nanoparticles using optical modalities like optical coherence tomography. Since the nanoparticles, especially gold one, have been very attractive for medical diagnosis and treatment the amount of research activities have been growing rapidly. The nanoparticles designed for different applications like contrast agents or drugs delivery change the...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Analysis of Factors Influencing the Prices of Tourist Offers
PublikacjaTourism is a significant branch of many world economies. Many factors influence the volume of tourist traffic and the prices of trips. There are factors that clearly affect tourism, such as COVID-19. The paper describes the methods of machine learning and process mining that allow for assessing the impact of various factors (micro, mezzo and macro) on the prices of tourist offers. The methods were used on large sets of real data...
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublikacjaIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublikacjaSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Analysis of air mass back trajectories with present and historical volcanic activity and anthropogenic compounds to infer pollution sources in the South Shetland Islands (Antarctica)
PublikacjaThis work analyses atmospheric transport of natural and anthropogenic pollution to the South Shetland Islands (SSI), with particular reference to the period September 2015 – August 2017. Based on data from the Global Volcanism Program database and air mass back trajectories calculated using the HySPLIT model, it was found that it is possible that in the analysed period volcanic pollution was supplied via long-range transport from...
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IoT for healthcare applications
PublikacjaThis chapter summarizes IRACON contributions related to the application of IoT in healthcare. It consists of the following three sections. Section 8.1 presents the measurement campaigns and the related statistical analysis to obtain various channel models for wearable and implantable devices. In addition, the importance of physical human-body phantoms used for channel, Specific Absorption Rate (SAR), and Electromagnetic (EM) exposure...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Koncepcja systemu wspomagania decyzji nawigatora statku opartego na ewolucyjnym planowaniu manewrów antykolizyjnych
PublikacjaArtykuł przedstawia koncepcję systemu wspomagania decyzji nawigatora statku opartego na wątkach badań prowadzonych wcześniej przez autora. System będzie rozszerzał funkcjonalność systemów dotychczasowych o możliwość szczegółowego planowania bezpiecznej trajektorii statku na wodach zamkniętych, z dużą liczbą statków obcych i ograniczeniami toru wodnego. Artykuł zawiera dyskusję możliwych podejść do planowania manewrów, optymalizacji...
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NADZOROWANIE WYPOSAŻENIA DO MONITOROWANIA I POMIARÓW WEDŁUG WYMAGAŃ WYBRANYCH NORM ORAZ PRZEPISÓW PRAWNYCH
Publikacja: Przyrządy pomiarowe stanowią zasadniczy element złożonego systemu oceny jakości wyrobów na wszystkich etapach produkcji. Odpowiednio zaprojektowane procedury opisujące procesy kontrolne i pomiarowe, sprawnie zorganizowane i przeprowadzane operacje monitorowania i pomiarów parametrów procesów i produktów oraz skutecznie funkcjonujący nadzór nad wyposażeniem do monitorowania i pomiarów w organizacji są podstawą do wykazania, że...
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Instantaneous power signal measurements for bearing diagnostics
Dane BadawczeBearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous current and voltage power supplied to the engines. Bearing damage causes the appearance of deformations, which are in the form of additional harmonic components...
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Analysis of the instantaneous power signal for bearing diagnostics -bearing damaged
Dane BadawczeThe attached dataset contains the measurement results of the instantaneous values of current and voltage, recorded during the diagnostics of a damaged bearing. Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous...
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Analysis of the instantaneous power signal for bearing diagnostics - bearing undamaged
Dane BadawczeThe attached dataset contains the measurement results of the instantaneous values of current and voltage, recorded during the diagnostics of an undamaged bearing. Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous...
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Vehicle detector training with minimal supervision
PublikacjaRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...
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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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A New Double Digestion Ligation Mediated Suppression PCR Method for Simultaneous Bacteria DNA-Typing and Confirmation of Species: An Acinetobacter sp. Model
PublikacjaWe have designed a new ddLMS PCR (double digestion Ligation Mediated Suppression PCR) method based on restriction site polymorphism upstream from the specific target sequence for the simultaneous identification and differentiation of bacterial strains. The ddLMS PCR combines a simple PCR used for species or genus identification and the LM PCR strategy for strain differentiation. The bacterial identification is confirmed in the...
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Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje
PublikacjaGeneratywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...
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Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover
PublikacjaThe process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus)...
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Identification of category associations using a multilabel classifier
PublikacjaDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
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Automatic recognition of males and females among web browser users based on behavioural patterns of peripherals usage
PublikacjaPurpose The purpose of this paper is to answer the question whether it is possible to recognise the gender of a web browser user on the basis of keystroke dynamics and mouse movements. Design/methodology/approach An experiment was organised in order to track mouse and keyboard usage using a special web browser plug-in. After collecting the data, a number of parameters describing the users’ keystrokes, mouse movements and clicks...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Malignant neoplasm of skin, unspecified - Male, 91 - Tissue image [12050630013028621]
Dane BadawczeThis is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.