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Wyniki wyszukiwania dla: SCORE-BASED CLASSIFIER
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Agent-Based RBF Network Classifier with Feature Selection in a Kernel Space
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A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublikacjaA new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...
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Ensemble Online Classifier Based on the One-Class Base Classifiers for Mining Data Streams
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Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublikacjaThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...
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A method of self-testing of analog circuits based on fully differential op-amps with theTCBF classifier
PublikacjaA new approach of self-testing of analog circuits based on fully differential op-amps of mixed-signal systems controlled by microcontrollers is presented. It consists of a measurement procedure and a fault diagnosis procedure. We measure voltage samples of a time response of a tested circuit on a stimulation of a unit step function given at the common-mode reference voltage input of the op-amp. The fault detection and fault localization...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublikacjaLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublikacjaThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast 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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Towards Increasing Density of Relations in Category Graphs
PublikacjaIn the chapter we propose methods for identifying new associations between Wikipedia categories. The first method is based on Bag-of-Words (BOW) representation of Wikipedia articles. Using similarity of the articles belonging to different categories allows to calculate the information about categories similarity. The second method is based on average scores given to categories while categorizing documents by our dedicated score-based...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublikacjaIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Wojciech Wojnowski dr inż.
OsobyUkończył V Liceum Ogólnokształcące w Gdańsku w klasie o profilu matematyczno-fizycznym z wykładowym językiem angielskim. W 2009 roku rozpoczął studia na Wydziale Chemicznym PG na kierunku technologia chemiczna, uzyskując w 2012 roku tytuł inżyniera, a w 2013 tytuł magistra. W latach 2013–2015 studiował sinologię na Uniwersytecie w Nankinie dzięki uzyskaniu Stypendium Rządu ChRL. Po powrocie do Polski w 2015 roku rozpoczął studia...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublikacjaIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Comparison of the effectiveness of automatic EEG signal class separation algorithms
PublikacjaIn this paper, an algorithm for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and...
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Klasyfikator SVM w zastosowaniu do synchronizacji sygnału OFDM zniekształconego przez kanał wielodrogowy
PublikacjaW 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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Diagnostyka analogowych filtrów wielosekcyjnych oparta na klasyfikato-rach neuronowych z dwucentrowymi funkcjami bazowymi
PublikacjaPrzedmiotem artykułu jest zastosowanie klasyfikatora z dwucentrowymi funkcjami bazowymi do lokalizacji uszkodzeń w wielosekcyjnych torach analogowych elektronicznych systemów wbudowanych sterowanych mikrokontrolerem. Przedstawiono szczegóły procedury pomiarowej oraz metody detekcji i lokalizacji uszkodzeń toru analogowego z wykorzysta-niem klasyfikatora DB zaimplementowanego w postaci algorytmicznej w kodzie programu mikrokontrolera....
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Strategie treningu neuronowego estymatora częstotliwości tonu krtaniowego z użyciem generatora syntetycznych samogłosek
PublikacjaW wielu zastosowaniach telekomunikacyjnych pojawia się problem przetwarzania lub analizy sygnału mowy, w ramach którego, często w obszarze podstawowych algorytmów, stosuje się estymator częstotliwości tonu krtaniowego. Estymator rozpatrywany w tej pracy bazuje na neuronowym klasyfikatorze podejmującym decyzje na podstawie częstotliwości oraz mocy chwilowej wyznaczanych w podpasmach analizowanego sygnału mowy. W pracy rozważamy...
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Two Stage SVM and kNN Text Documents Classifier
PublikacjaThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Thresholding Strategies for Large Scale Multi-Label Text Classifier
PublikacjaThis article presents an overview of thresholding methods for labeling objects given a list of candidate classes’ scores. These methods are essential to multi-label classification tasks, especially when there are a lot of classes which are organized in a hierarchy. Presented techniques are evaluated using the state-of-the-art dedicated classifier on medium scale text corpora extracted from Wikipedia. Obtained results show that the...
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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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How Specific Can We Be with k-NN Classifier?
PublikacjaThis paper discusses the possibility of designing a two stage classifier for large-scale hierarchical and multilabel text classification task, that will be a compromise between two common approaches to this task. First of it is called big-bang, where there is only one classifier that aims to do all the job at once. Top-down approach is the second popular option, in which at each node of categories’ hierarchy, there is a flat classifier...
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublikacjaThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublikacjaThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Anterior subcutaneous transposition and simple decompression of the ulnar nerve at the elbow – the postoperative improvement in DASH score, VAS score and sonographic findings
PublikacjaIntroduction. Although a lot of studies have described long- term outcomes after surgical treatment of cubital tunnel syndrome, and the usefulness of sonography in diagnosing of this disorder, few studies have evaluated patients self-reporting outcomes or sonographic findings after surgery. Aim. We assessed patients self-reporting instruments and sonographic findings in patients with the cubital tunnel syndrome before and after...
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Guido: a musical score recognition system
PublikacjaThis paper presents an optical music recognition system Guido that can automatically recognize the main musical symbols of music scores that were scanned or taken by a digital camera. The application is based on object model of musical notation and uses linguistic approach for symbol interpretation and error correction. The system offers musical editor with a partially automatic error correction.
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Weighted sequential classifier
PublikacjaZaproponowano wieloklasowe ważone kryterium Fishera i uzasadniono potrzebę jego wprowadzenia. Na bazie tego kryterium skonstruowano sekwencyjny algorytm uczenia klasyfikatora. Przedstawiono wyniki eksperymentów.
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SDF classifier revisited
PublikacjaArtykuł dotyczy problemów związanych z konstruowaniem klasyfikatorów wykorzystujących tzw. dyskryminacyjną funkcję samopodobieństwa (ang. Similarity Discriminant Function - SDF), w których tradycyjna, wektorowa reprezentacja obrazu została zastąpiona przez dane o strukturze macierzowej. Zaprezentowano możliwości modyfikowania macierzowych struktur danych i zaproponowano nowe warianty kryterium SDF. Przedstawione algorytmy zostały...
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Automated Classifier Development Process for Recognizing Book Pages from Video Frames
PublikacjaOne of the latest developments made by publishing companies is introducing mixed and augmented reality to their printed media (e.g. to produce augmented books). An important computer vision problem that they are facing is classification of book pages from video frames. The problem is non-trivial, especially considering that typical training data is limited to only one digital original per book page, while the trained classifier...
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KNOWLEDGE-BASED SYSTEMS
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Higher Responsiveness to Rosuvastatin in Polygenic versus Monogenic Hypercholesterolemia: A Propensity Score Analysis
PublikacjaBackground: The monogenic defect in familial hypercholesterolemia (FH) is detected in ∼40% of cases. The majority of mutation-negative patients have a polygenic cause of high LDL-cholesterol (LDL-C). We sought to investigate whether the underlying monogenic or polygenic defect is associated with the response to rosuvastatin. Methods: FH Individuals were tested for mutations in LDLR and APOB genes. A previously established LDL-C-specific...
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New variants of the SDF classifier
PublikacjaPraca dotyczy problemów związanych z konstruowaniem klasyfikatorów, w których typowa wektorowa reprezentacja obrazu została zastapiona danymi o strukturze macierzowej. W pracy zaproponowano nowe algorytmy oparte na funkcji SDF. Zostały one przetestowane na obrazach przedstawiających cyfry pisane ręcznie oraz na zdjęciach twarzy. Przeprowadzone eksperymenty pozwalają stwierdzić, że wprowadzone modyfikacje istotnie zwiększyły skuteczność...
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Higher responsiveness to rosuvastatin in polygenic versus monogenic hypercholesterolaemia: a propensity score analysis
PublikacjaBackground The underlying monogenic defect in familial hypercholesterolemia (FH) can be detected in ∼40% of cases. The majority of mutation-negative patients have a polygenic cause of high LDL-cholesterol (LDL-C) due to having inherited a greater than average number of common LDL-C raising single nucleotide polymorphisms (SNPs). Purpose We sought to investigate, whether the monogenic or polygenic defect in FH is associated with...
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An appropriate SCORE to assess cardiovascular risk in hypertension?
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Ochrona Przeciwkorozyjna Instalacji Przemysłowych i Risk Based Inspection (RBI)
Kursy OnlineRisk Based Inspection
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Ensemble Classifier for Mining Data Streams
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Grzegorz Boczkaj dr hab. inż.
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Reliability Based zoptimization 2023/24
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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The ORBIT bleeding score is associated with lysis and permeability of fibrin clots
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A multilocus genetic risk score is associated with arterial stiffness in hypertensive patients
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[ILiT, IŚGiE] Reliability-Based Optimization (RBO)
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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OCCUPATIONAL RISK ASSESSMENT USING THE RISK SCORE METHOD DURING GEODETIC MEASUREMENTS
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Validation of the Elderly Traumatic Brain Injury Score: Observational Case Control Study
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Analysis of the Possibility of Using New Types of Protective Coatings and Abrasion-Resistant Linings under the Operating Conditions of the Spiral Classifier at KGHM Polska Miedź S.A. Ore Concentration Plant
PublikacjaA study was carried out to select the appropriate coatings for corrosion protection of the spiral classifier working at KGHM Polska Miedź S.A. Ore Concentration Plant. The abrasion resistance of selected protective coatings and wear-resistant linings was investigated using a DT-523 rotary abrasion tester with Taber CS-10 rubber abrasive discs. The average weight loss of the coatings after a cycle of 2000 revolutions was determined....
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7-Score Function for Assessing the Strength of Association Rules Applied for Construction Risk Quantifying
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SCORE model underestimates cardiovascular risk in hypertensive patients: Results of the Polish Hypertension Registry
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Metoda i algorytmy sterowania procesami miksowania dźwięku za pomocą gestów w oparciu o analizę obrazu wizyjnego
PublikacjaGłównym celem rozprawy było opracowanie systemu miksowania dźwięku za pomocą gestów rąk wykonywanych w powietrzu oraz zbadanie możliwości oferowanych przez takie rozwiązanie w porównaniu ze współczesną metodą miksowania sygnałów fonicznych, wykorzystującą środowisko komputera. Opracowany system rozpoznaje zarówno dynamiczne jak i statyczne gesty rąk. Rozpoznawanie gestów dynamicznych zrealizowano w oparciu o metody logiki rozmytej...
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Construction of a picewise-linear classifier by applaing discriminant analysis to decision tree induction
PublikacjaArtykuł prezentuje metodę konstrukcji drzew decyzyjnych. W odróżnieniu od większości popularnych algorytmów, które wybierają pojedyncze cechy do budowy reguł decyzyjnych w węzłach drzewa, ta metoda łączy wszystkie cechy. Używa ona wieloklasowego kryterium Fishera do wydzielenia nowych cech, które są liniowa kombinacją cech pierwotnych. Takie drzewa mogą aproksymować złożone regiony decyzyjne używając mniejszej liczby węzłów w porównaniu...
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The Prognostic Value of PI-RADS Score in CyberKnife Ultra-Hypofractionated Radiotherapy for Localized Prostate Cancer
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[ILiT, IŚGiE] Reliability-Based Optimization (RBO) - 2022/23
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[ILiT, IŚGiE] Reliability-Based Optimization (RBO) - 2023/24
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Cathodic Protection System of the Spiral Classifier at the KGHM Polska Miedź S.A. Ore Concentration Plant—Case Study of Commissioning and Control of Operating Parameters
PublikacjaThe project involved designing, constructing and commissioning a cathodic protection system for a selected spiral classifier operating at the KGHM Polska Miedź S.A. Ore Concentration Plant (O/ZWR). The authors developed a concept and assumptions regarding the corrosion protection of a large industrial device using a cathodic protection system with an external power source. Pre-project studies included conducting a trial polarization...
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Evidence-Based Practice
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Evidence-based nursing
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Evidence Based Midwifery
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Evidence-based dentistry
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Evidence-Based Medicine
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Intelligence-Based Medicine
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Assessment of the mean time in the therapeutic INR range and the SAME-TT2R2 score in patients with atrial fibrillation and cognitive impairment
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Comparison of ANN Classifier to the Neuro-Fuzzy System for Collusion Detection in the Tender Procedures of Road Construction Sector
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublikacjaWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
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Rough Set-Based Classification of EEG Signals Related to Real and Imagery Motion
PublikacjaA rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion....
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Dynamic Signature Vertical Partitioning Using Selected Population-Based Algorithms
PublikacjaThe dynamic signature is a biometric attribute used for identity verification. It contains information on dynamics of the signing process. There are many approaches to the dynamic signature verification, including the one based on signature partitioning. Partitions are the regions created on the basis of signals describing the dynamics of the signature. They contain information on the shape of the signature characteristic of a...
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Justyna Płotka-Wasylka dr hab. inż.
OsobyUrodziła się w Słupsku (24.03.1986).W 2005 roku ukończyła I Liceum Ogólnokształcące im. Jana II Sobieskiego w Wejherowie i rozpoczęła studia na Wydziale Chemicznym Politechniki Gdańskiej. Po ich ukończeniu w 2010 rozpoczęła pracę naukową na tej uczelni, uzyskując w 2014 roku stopień doktora nauk chemicznych. Tematem jej rozprawy doktorskiej, wykonywanej pod kierunkiem prof. Marka Biziuka oraz dr Caluma Morrisona (Uniwersytet w...
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Knowledge-based performance-driven modeling of antenna structures
PublikacjaThe importance of surrogate modeling techniques in the design of modern antenna systems has been continuously growing over the recent years. This phenomenon is a matter of practical necessity rather than simply a fashion. On the one hand, antenna design procedures rely on full-wave electromagnetic (EM) simulation tools. On the other hand, the computational costs incurred by repetitive EM analyses involved in solving common tasks...
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Worldviews on Evidence-Based Nursing
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Journal of Evidence-Based Psychotherapies
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Bio-based and Applied Economics
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Evidence-Based Mental Health
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Journal of Location Based Services
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Evidence Based Care Journal
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Journal of Evidence-Based Medicine
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Journal of Gender-Based Violence
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BMJ Evidence-Based Medicine
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An agent-based approach to ANN training
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The dynamic signature verification using population-based vertical partitioning
PublikacjaThe dynamic signature is an attribute used in behavioral biometrics for verifying the identity of an individual. This attribute, apart from the shape of the signature, also contains information about the dynamics of the signing process described by the signals which tend to change over time. It is possible to process those signals in order to obtain descriptors of the signature characteristic of an individual user. One of the methods...
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Buzz-based recognition of the honeybee colony circadian rhythm
PublikacjaHoneybees are one of the highly valued pollinators. Their work as individuals is appreciated for crops pollination and honey production. It is believed that work of an entire bee colony is intense and almost continuous. The goal of the work presented in this paper is identification of bees circadian rhythm with a use of sound-based analysis. In our research as a source of information on bee colony we use their buzz that have been...
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Acoustic Detector of Road Vehicles Based on Sound Intensity
PublikacjaA method of detecting and counting road vehicles using an acoustic sensor placed by the road is presented. The sensor measures sound intensity in two directions: parallel and perpendicular to the road. The sound intensity analysis performs acoustic event detection. A normalized position of the sound source is tracked and used to determine if the detected event is related to a moving vehicle and to establish the direction of movement....
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Speech Analytics Based on Machine Learning
PublikacjaIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Marek Adamowicz dr hab. inż.
OsobyStopień naukowy doktora uzyskał w 2008 r. na Wydziale Elektrotechniki i Automatyki Politechniki Gdańskiej. W latach 2005 – 2011 pracował na Akademii Morskiej w Gdyni. W 2010 r. jako laureat programu NCBR LIDER wybrał Wydział Elektrotechniki i Automatyki Politechniki Gdańskiej jako jednostkę realizującą swój projekt z zakresu szerokopasmowych przyrządów półprzewodnikowych i ich zastosowań w elektrowniach wiatrowych. Od 2011 roku...
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Basic evaluation of limb exercises based on electromyography and classification methods
PublikacjaSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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Project and problem-based learning (PPBL): wprowadzenie
WydarzeniaZapraszamy na warsztaty, na których m.in. zrozumiesz założenia metody pracą projektu w oparciu o rozwiązywanie realnego problemu, poznasz etapy pracy zespołu metodą projektu oraz rolę nauczyciela i studentów w PPBL.
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublikacjaAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublikacjaThe ability to evaluate the effects of fabrication tolerances and other types of uncertainties is a critical part of microwave design process. Improving the immunity of the device to parameter deviations is equally important, especially when the performance specifications are stringent and can barely be met even assuming a perfect manufacturing process. In the case of modern miniaturized microwave components of complex topologies,...
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Low-Cost and Precise Automated Re-Design of Antenna Structures Using Interleaved Geometry Scaling and Gradient-Based Optimization
PublikacjaDesign of contemporary antennas is an intricate endeavor involving multiple stages, among others, tuning of geometry parameters. In particular, re-designing antennas to different operating frequencies, makes parametric optimization imperative to ensure the best achievable system performance. If the center frequency at the current design is distant from the target one, local tuning methods generally fail, whereas global algorithms...
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Basic Hand Gestures Classification Based on Surface Electromyography
PublikacjaThis paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...
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Global EM-Driven Optimization of Multi-Band Antennas Using Knowledge-Based Inverse Response-Feature Surrogates
PublikacjaElectromagnetic simulation tools have been playing an increasing role in the design of contemporary antenna structures. The employment of electromagnetic analysis ensures reliability of evaluating antenna characteristics but also incurs considerable computational expenses whenever massive simulations are involved (e.g., parametric optimization, uncertainty quantification). This high cost is the most serious bottleneck of simulation-driven...
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Favourable outcomes in patients with early-stage non-small-cell lung cancer operated on by video-assisted thoracoscopic surgery: a propensity score-matched analysis†
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Bass Enhancement Settings in Portable Devices Based on Music Genre Recognition
PublikacjaThe paper presents a novel approach to the Virtual Bass Synthesis (VBS) applied to mobile devices, called Smart VBS (SVBS). The proposed algorithm uses an intelligent, rule-based setting of bass synthesis parameters adjusted to the particular music genre. Harmonic generation is based on a nonlinear device (NLD) method with the intelligent controlling system adapting to the recognized music genre. To automatically classify music...
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Assessing the attractiveness of human face based on machine learning
PublikacjaThe 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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Marcin Kulawiak dr hab. inż.
Osoby -
A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublikacjaIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Assessment of Clinical Usefulness of Resting Electrocardiogram (PH-ECG Score) in Monitoring the Efficacy of Balloon Pulmonary Angioplasty (BPA) in Patients with Chronic Thromboembolic Pulmonary Hypertension (CTEPH)
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