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Search results for: TREE-BASED CLASSIFIERS
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An implementation of deterministic tree automata minimization
PublicationWstępujący, deterministyczny, skończony automat drzewiasty (DTA) może być używany jako struktura danych do przechowywania zbiorów nieuporządkowanych drzew bez narzuconej liczby poddrzew. Takie automaty są zwykle rzadsze niż automaty działające na napisach i dlatego należy zwrócić szczególną uwagę na ich wydajną minimalizację. W dostępnej literaturze jest jednak ciężko znaleźć proste i szczegółowe opisy procedury minimalizacji....
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Lower bound on the domination number of a tree.
PublicationW pracy przedstawiono dolne ograniczenie na liczbę dominowania w drzewach oraz przedstawiono pełną charakterystykę grafów ekstremalnych.
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Family Tree for Aqueous Organic Redox Couples for Redox Flow Battery Electrolytes: A Conceptual Review
PublicationRedox flow batteries (RFBs) are an increasingly attractive option for renewable energy storage, thus providing flexibility for the supply of electrical energy. In recent years, research in this type of battery storage has been shifted from metal-ion based electrolytes to soluble organic redox-active compounds. Aqueous-based organic electrolytes are considered as more promising electrolytes to achieve “green”, safe, and low-cost...
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Usage of Two-Center Basis Function Neural Classifiers in Compact Smart Resistive Sensors
PublicationA new solution of the smart resistance sensorwith the Two-Center Basis Function (TCBF) neuralclassifier, for which the resistance sensor is a component ofan anti-aliasing filter of an ADC is proposed. Thetemperature measurement procedure is based on excitationof the filter by square impulses, sampling time response ofthe filter and processing measured voltage values by theTCBF classifier. All steps of the measurement procedure...
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Accessibility to urban green spaces: A critical review of WHO recommendations in the light of tree-covered areas assessment
PublicationEasy accessibility of Urban Green Spaces (UGSs) is essential to the quality of life in urban areas. The World Health Organization (WHO) recommendations focus on spatial access to UGSs, define as accessible those larger than 0.5 ha situated up to 300 m of residential areas, and disregard the social significance of smaller green spaces. This paper assesses the extent to which the WHO recommendations permit the identification of locations...
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublicationThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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A Comparison Study of Strategies for Combining Classifiers from Distributed Data Sources
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A city is not a tree: a multi-city study on street network and urban life
PublicationChristopher Alexander, a British-American scholar, differentiated an old (natural) city from a new (planned) one by structure. The former resembles a “semilattice”, or a complex system encompassing many interconnected sub-systems. The latter is shaped in a graph-theoretical “tree”, which lacks the structural complexity as its sub-systems are compartmentalized into a single hierarchy. This structural distinction explains why, or...
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Lower bound on the paired domination number of a tree
PublicationW pracy przedstawione jest ograniczenie dolne dla liczby dominowania parami oraz scharakteryzowane są wszystkie drzewa ekstremalne.
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Tool support for ECSDM fault tree methodology
PublicationExtended Common Safety Description Model (ECSDM) jest językiem do formalnej specyfikacji systemów związanych z bezpieczeństwem oraz ich komponentów. Język ten zawiera konstrukcje umożliwiające specyfikację zależności czasowych. Może on zostać użyty w analizie drzew błędów, aby uzyskać jednoznaczną specyfikację hazardów w sytuacji, gdy są one uzależnione od związków czasowych pomiędzy przyczynami. Artykuł opisuje narzędzie wytworzone...
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Complexity of weak acceptonic conditions in tree automata
PublicationRozważano złożoność problemu pustości dla automatów na drzewach ze słabymi warunkami akceptowalności. Rozważano także translacje pomiędzy słabymi i silnymi warunkami akceptowalności.
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Lower bound on the weakly connected domination number of a tree
PublicationPraca dotyczy dolnego ograniczenia liczby dominowania słabo spójnego w drzewach (ograniczenie ze względu na ilość wierzchołków i ilość wierzchołków końcowych w drzewie).
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Lower bound on the distance k-domination number of a tree
PublicationW artykule przedstawiono dolne ograniczenie na liczbę k-dominowania w drzewach oraz scharakteryzowano wszystkie grafy ekstremalne.
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Application of artificial neural networks (ANN) as multiple degradation classifiers in thermal and flow diagnostics
PublicationPrzedyskutowano problem zwiększenia dokładności rozpoznawania wielokrotnych degradacji eksploatacyjnych urządzeń składowych dużych obiektów energetycznych. Zastosowani sieć neuronową (SSN) o skokowych funkcjach przejścia. Sprawdzono możliwości przyspieszenia treningu sieci neuronowych. Zastosowano modułową metodę budowy SSN, polegającą na dedykowaniu pojedynczej sieci do rozpoznawania tylko jednego typu degradacji.
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Increasing efficiency of technological process by limiting impact of corrosive environment on operation of spiral classifiers
PublicationMost of the technological operations related to the preparation of the output to be enriched and to the production of the final copper concentrate take place with the use of water environment. Water management, besides using innovative technical and technological solutions, is a significant factor in the whole copper ore enrichment process. Mine water resources and surface water of the tailing pond named "Żelazny Most" are the...
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A self-stabilizing algorithm for finding a spanning tree in a polynomial number of moves
PublicationW pracy rozważa się rozproszony model obliczeń, w którym struktura systemu jest reprezentowana przez graf bezpośrednich połączeń komunikacyjnych. W tym modelu podajemy nowy samostabilizujący algorytm znajdowania drzewa spinającego. Zgodnie z naszą wiedzą jest to pierwszy algorytm dla tego problemu z gwarantowaną wielomianową liczbą ruchów.
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Critical Case Stochastic Phylogenetic Tree Model via the Laplace Transform
PublicationBirth–and–death models are now a common mathematical tool to describe branching patterns observed in real–world phylogenetic trees. Liggett and Schinazi (2009) is one such example. The authors propose a simple birth–and–death model that is compatible with phylogenetic trees of both influenza and HIV, depending on the birth rate parameter. An interesting special case of this model is the critical case where the birth rate equals the...
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Construction of a picewise-linear classifier by applaing discriminant analysis to decision tree induction
PublicationArtykuł 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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INDIVIDUAL TREE DETECTION FROM UAV LIDAR DATA IN A MIXED SPECIES WOODLAND
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Fault Tree Analysis and Failure Diagnosis of Marine Diesel Engine Turbocharger System
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The partial-order tree: a new structure for indexing on complex attributes in object-oriented databases
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Music Genre Recognition in the Rough Set-Based Environment
PublicationThe aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...
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A Fuzzy Event Tree Model for Accident Scenario Analysis of Ship Stuck in Ice in Arctic Waters
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Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data
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Viewpoint independent shape-based object classification for video surveillance
PublicationA method for shape based object classification is presented.Unlike object dimension based methods it does not require any system calibration techniques. A number of 3D object models are utilized as a source of training dataset for a specified camera orientation. Usage of the 3D models allows to perform the dataset creation process semiautomatically. The background subtraction method is used for the purpose of detecting moving objects...
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublicationBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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Knowledge-based performance-driven modeling of antenna structures
PublicationThe 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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Identification of Emotions Based on Human Facial Expressions Using a Color-Space Approach
PublicationHCI technology improves human-computer interaction. Such communication can be carried out with the use of emotions that are visible on the human face since birth. In this paper the Emotion system for detecting and recognizing facial expressions, developed in the MSc work, is presented. The system recognizes emotion from webcam video in real time. It is based on color segmentation and morphological operations. The system uses a...
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A review of emotion recognition methods based on keystroke dynamics and mouse movements
PublicationThe paper describes the approach based on using standard input devices, such as keyboard and mouse, as sources of data for the recognition of users’ emotional states. A number of systems applying this idea have been presented focusing on three categories of research problems, i.e. collecting and labeling training data, extracting features and training classifiers of emotions. Moreover the advantages and examples of combining standard...
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An agent-based approach to ANN training
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Long-term changes in the Leucobryo-Pinetum community: interactions between the tree-stand, understorey and moss layer
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Buzz-based honeybee colony fingerprint
PublicationNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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Monitoring Parkinson's disease patients employing biometric sensors and rule-based data processing
PublicationArtykuł prezentuje automatyczny system wykrywania pogorszenia zdrowia pacjentów z chorobą Parkinsona opracowany w ramach projektu PERFORM.The paper presents how rule-based processing can be applied to automatically evaluate the motor state of Parkinson's Disease patients. Automatic monitoring of patients by using biometric sensors can provide assessment of the Parkinson's Disease symptoms. All data on PD patients' state are compared...
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Basic Hand Gestures Classification Based on Surface Electromyography
PublicationThis 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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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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The effects of forest patch size and ownership structure on tree stand characteristics in a highly deforested landscape of central Poland
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublicationAccounting 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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DBpedia and YAGO Based System for Answering Questions in Natural Language
PublicationIn this paper we propose a method for answering class 1 and class 2 questions (out of 5 classes defined by Moldovan for TREC conference) based on DBpedia and YAGO. Our method is based on generating dependency trees for the query. In the dependency tree we look for paths leading from the root to the named entity of interest. These paths (referenced further as fibers) are candidates for representation of actual user intention. The...
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublicationThe 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
PublicationDesign 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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Global EM-Driven Optimization of Multi-Band Antennas Using Knowledge-Based Inverse Response-Feature Surrogates
PublicationElectromagnetic 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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Accelerometer-based Human Activity Recognition and the Impact of the Sample Size
PublicationThe presented study focused on the recognition of eight user activities (e.g. walking, lying, climbing stairs) basing on the measurements from an accelerometer embedded in a mobile device. It is assumed that the device is carried in a specific location of the user’s clothing. Three types of classifiers were tested on different sizes of the samples. The influence of the time window (the duration of a single trial) on selected activities...
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Human-Computer Interface Based on Visual Lip Movement and Gesture Recognition
PublicationThe multimodal human-computer interface (HCI) called LipMouse is presented, allowing a user to work on a computer using movements and gestures made with his/her mouth only. Algorithms for lip movement tracking and lip gesture recognition are presented in details. User face images are captured with a standard webcam. Face detection is based on a cascade of boosted classifiers using Haar-like features. A mouth region is located in...
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Recent Advances in Accelerated Multi-Objective Design of High-Frequency Structures using Knowledge-Based Constrained Modeling Approach
PublicationDesign automation, including reliable optimization of engineering systems, is of paramount importance for both academia and industry. This includes the design of high-frequency structures (antennas, microwave circuits, integrated photonic components), where the appropriate adjustment of geometry and material parameters is crucial to meet stringent performance requirements dictated by practical applications. Realistic design has...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper 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
PublicationProper 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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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublicationThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations
PublicationThe fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where the canopy is sparse and there are well-defined tree crown boundaries. Here, the distinction...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...