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Comparison of Language Models Trained on Written Texts and Speech Transcripts in the Context of Automatic Speech Recognition
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Justyna Signerska-Rynkowska dr inż.
PeopleI am currently an assistant professor (adjunct) at Gdansk University of Technology (Department of Differential Equations and Mathematics Applications). My scientific interests include dynamical systems theory, chaos theory and their applications to modeling of biological phenomena, especially to neurosciences. In June 2013 I completed PhD in Mathematics at the Institute of Mathematics of Polish Academy of Sciences (IMPAN) (thesis...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublicationIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Klasyfikator SVM w zastosowaniu do synchronizacji sygnału OFDM zniekształconego przez kanał wielodrogowy
PublicationW pracy przedstawiono analizę przydatności klasyfikatora SVM bazującego na uczeniu maszynowym do estymacji przesunięcia czasowego odebranego symbolu OFDM. Przedstawione wyniki wykazują, że ten klasyfikator potrafi zapewnić synchronizację dla różnych kanałów wielodrogowych o wysokim poziomie szumu. Eksperymenty przeprowadzone w Matlabie z użyciem modeli modulatora i demodulatora wykazały, że w większości przypadków klasyfikator...
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LSA Is not Dead: Improving Results of Domain-Specific Information Retrieval System Using Stack Overflow Questions Tags
PublicationThe paper presents the approach to using tags from Stack Overflow questions as a data source in the process of building domain-specific unsupervised term embeddings. Using a huge dataset of Stack Overflow posts, our solution employs the LSA algorithm to learn latent representations of information technology terms. The paper also presents the Teamy.ai system, currently developed by Scalac company, which serves as a platform that...
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Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublicationThis article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...
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Wymiary klimatu pracy zespołowej
PublicationArtykuł prezentuje koncepcje klimatu pracy zespołowej jako determinanty zespołowej efektywności i innowacyjności. Zaprezentowano sześć modeli klimatu pracy zespołowej i przeanalizowano główne wymiary klimatu, opracowując na tej podstawie nowy, 5-wymiarowy model, który obejmuje: wsparcie oparte na zaufaniu, popieranie innowacji,odpowiedzialność, wizja i motywacja. Pokazano również kilka narzędzi do pomiaru klimatu pracy zespołowej.
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublicationNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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Obtaining a Well-Trained Artificial Intelligence Algorithm from Cross-Validation in Endoscopy
PublicationThe article shortly discusses endoscopic video analysis problems and artificial intelligence algorithms supporting it. The most common method of efficiency testing of these algorithms is to perform intensive cross-validation. This allows for accurately evaluate their performance of generalization. One of the main problems of this procedure is that there is no simple and universal way of obtaining a specific instance of a well-trained...
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TNFA expression level changes observed in response to the Wingate Anaerobic Test in non-trained and trained individuals
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Models in spatial development
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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GRAPHICAL MODELS
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STOCHASTIC MODELS
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Pre-swirl energy saving device in marine application
PublicationThis paper covers topics of energy saving device (ESD) with application to marine propulsors. The form of ESD, considered in this paper, consists of fixed lifting foils mounted in front of the screw propeller (the pre-swirl stator/guide vanes). An algorithm for designing propulsion systems, consisting of guide vanes and screw propeller, is presented. The proposed method relies on hybrid lifting line (guide vanes)-lifting surface...
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Accelerometer signal pre-processing influence on human activity recognition
PublicationA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy.
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Hydrogen degradation of pre-oxidized zirconium alloys
PublicationThe presence of the oxide layers on Zr alloys may retard or enhance the hydrogen entry and material degradation, depending on the layer features. This research has been aimed to determine the effects of pre-oxidation of the Zircaloy-2 alloy at a different temperature on hydrogen degradation. The specimens were oxidised in laboratory air at 350°C, 700°C, and 900°C. After, some samples were tensed at 10-5 strain rate and simultaneously...
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Malignant neoplasm arising from pre-existing spiradenoma - Male, 64 - Tissue image [912072957516291]
Open Research DataThis 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.
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Optimization of Saccharification Conditions of Lignocellulosic Biomass under Alkaline Pre-Treatment and Enzymatic Hydrolysis
PublicationPre-treatment is a significant step in the production of second-generation biofuels from waste lignocellulosic materials. Obtaining biofuels as a result of fermentation processes requires appropriate pre-treatment conditions ensuring the highest possible degree of saccharification of the feed material. An influence of the following process parameters were investigated for alkaline pre-treatment of Salix viminalis L.: catalyst concentration...
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Comparison of image pre-processing methods in liver segmentation task
PublicationAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Hydrogen Production from Energy Poplar Preceded by MEA Pre-Treatment and Enzymatic Hydrolysis
PublicationThe need to pre-treat lignocellulosic biomass prior to dark fermentation results primarily from the composition of lignocellulose because lignin hinders the processing of hard wood towards useful products. Hence, in this work a two-step approach for the pre-treatment of energy poplar, including alkaline pre-treatment and enzymatic saccharification followed by fermentation has been studied. Monoethanolamine (MEA) was used as the...
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Malignant neoplasm arising from pre-existing spiradenoma - Male, 63 - Tissue image [9220729551204161]
Open Research DataThis is the histopathological image of BRONCHUS AND LUNG 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.
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Effect of modified soybeen oil amount on rheological characteriza-tion of polyurethane pre-polymers
PublicationPolyurethanes (Pu’s) are the polymeric materials which have got urethane groups in the structure. The properties of Pu’s depend both on the method of preparation and monomers used. Polyurethanes are produced by two methods known as one step or two step method called as “pre-polymers method”, especially for the case of segmented polyurethanes (SPU’s). These materials are thermoplastic block copolymers of the (AB)n type consisting...
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Pre-analytical aspects in metabolomics of human biofluids – sample collection, handling, transport, and storage
PublicationMetabolomics is the field of omics research that offers valuable insights into the complex composition of biological samples. It has found wide application in clinical diagnostics, disease investigation, therapy prediction, monitoring of treatment efficiency, drug discovery, or in-depth analysis of sample composition. A suitable study design constitutes the fundamental requirements to ensure robust and reliable results from the...
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Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering
PublicationContext-aware Recommender Systems aim to provide users with better recommendations for their current situation. Although evaluations of recommender systems often focus on accuracy, it is not the only important aspect. Often recommendations are overspecialized, i.e. all of the same kind. To deal with this problem, other properties can be considered, such as serendipity. In this paper, we study how an ontology-based and context-aware...
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Fermentative Conversion of Two-Step Pre-Treated Lignocellulosic Biomass to Hydrogen
PublicationFermentative hydrogen production via dark fermentation with the application of lignocellulosic biomass requires a multistep pre-treatment procedure, due to the complexed structure of the raw material. Hence, the comparison of the hydrogen productivity potential of different lignocellulosic materials (LCMs) in relation to the lignocellulosic biomass composition is often considered as an interesting field of research. In this study,...
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Journal of Pre-Raphaelite Studies
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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
PublicationContext-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort...
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Influence of accelerometer signal pre-processing and classification method on human activity recognition
PublicationA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.
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Journal of Pre-Clinical and Clinical Research
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Pre-treatment of bio fraction waste prior to fermentation processes
PublicationCurrent efforts are taken to increase resource efficiency, close material loops, and improve sustainable waste and by-products management. Thus, networking agro-food by-products and converting them into valuable products completely exhausting the potential of the raw material becomes significant. Model lignocellulosic and starch based biomass were subjected to pre-treatment with the application of acidic compounds, i.e. sulphuric...
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[AEiE] Selected topics of electrical engineering - models of electrical machines
e-Learning Courses{mlang pl} Dyscyplina: automatyka, elektronika i elektrotechnika Zajęcia fakultatywne dla doktorantów II roku Prowadzący: dr hab. inż. Andrzej Wilk, prof. PG, prof. dr hab. inż. Zbigniew Krzemiński Liczba godzin: 15 Forma zajęć: wykład {mlang} {mlang en} Discipline: control, electronic and electrical engineering Facultative course for 2nd-year PhD students Academic teachers: dr hab. inż. Andrzej Wilk, prof. PG, prof....
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LCF behavior of 2024AA under uni- and biaxial loading taking into account creep pre-deformation
PublicationThis study presents the results of experimental low-cycle fatigue (LCF) tests of aluminum 2024 alloy T3511 temper in uni- and biaxial loading states. Tests were carried out on both the as-received material (hardened extruded rods) and material with different pre-deformation histories. These deformations were carried out in the creep process at 200 °C and 300 °C for two different levels of at each temperature. The pre-deformed material’s...
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Generation of inhibitory compounds during pre-treatment of lignocellulosic biomass
Open Research DataDataset contains calibration curves and typical resultsa obtained during biomass pre-treatment. Data are converted from digital raw files to xlsx files
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Disease Models & Mechanisms
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Kinetic and Related Models
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Language Models in Speech Recognition
PublicationThis chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.
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Information Extraction from Polish Radiology Reports using Language Models
PublicationRadiology reports are vital elements of directing patient care. They are usually delivered in free text form, which makes them prone to errors, such as omission in reporting radiological findings and using difficult-to-comprehend mental shortcuts. Although structured reporting is the recommended method, its adoption continues to be limited. Radiologists find structured reports too limiting and burdensome. In this paper, we propose...
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Models of Structures in Didactics
PublicationThe final aim of teaching students subjects, such as structural mechanics, reinforced concrete, and steel structures is to teach them how structures work in a given building as well as to provide them with skills enabling them to calculate and design structures. The behavioral model of the structure, contrary to the architectural model, which focuses mainly on the external form of the building, shows workings from both the static...
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Bridging the gap between business process models and use-case models
PublicationToday's software development methodologies are equipped with a plethora of methods and techniques for business process engineering and Requirements Engineering. However, heavy investments in IT have not brought forth expected results. What seems to be lacking is a systematic approach that consolidates both disciplines to gain a synergistic effect. To address this challenge we extend Use-Case Driven Approach (UCDA) by binding use...
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Comparison of technology adoption models
PublicationThere are several technology adoption models, that try to explain, how and why the technologies are adopted and used. Among those, that are widely used to explain, how the older adults accept technologies, there are some general models and models specific to the group of older users. Among the general ones I would recommend paying attention to the following models: Technology Acceptance Model (TAM) proposed by Davis...
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Comparison and Optimization of Saccharification Conditions of Alkaline Pre-Treated Triticale Straw for Acid and Enzymatic Hydrolysis Followed by Ethanol Fermentation
PublicationThis paper concerns the comparison of the efficiency of two-stage hydrolysis processes, i.e., alkaline pre-treatment and acid hydrolysis, as well as alkaline pre-treatment followed by enzymatic hydrolysis, carried out in order to obtain reducing sugars from triticale straw. For each of the analyzed systems, the optimization of the processing conditions was carried out with respect to the glucose yield. For the alkaline pre-treatment,...
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Kriging Models for Microwave Filters
PublicationSurrogate modeling of microwave filters’ response is discussed. In particular, kriging is used to model either the scattering parameters of the filter or the rational representation of the filter’s characteristics. Surrogate models for these two variants of kriging are validated in solving a microwave filter optimization problem. A clear advantage of surrogate models based on the rational representation over the models based on scattering...
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Pre-feasibility study for treatment wetland application for wastewater treatment in dispersed development
PublicationThe aim of the paper is to present the conducted analyses of pre-feasibility study of different approaches for wastewater management in a settlement of 180 persons. In the assessment both technical and economic aspects were analyzed. The costs were calculated for three different and, at the same time, most popular as well as possible technical solutions like: (i) construction of local wastewater treatment plant with gravitational...
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Multibody models for gait analysis
PublicationThe aim of this study was to create multibody biomechanical models to analyze a normal gait of the human. Proposed models can be used to identify joint moments of the lower limbs during normal gait in the single and double support phases. Applying Newton-Euler formulation, following planar models were developed: 1) a mathematical 6DOF model describing a gait in the sagittal plane of the body for single support phase and double...