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Wyniki wyszukiwania dla: ENSEMBLE
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Ensemble Classifier for Mining Data Streams
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Electrochemistry from first-principles in the grand canonical ensemble
PublikacjaProgress in electrochemical technologies, such as automotive batteries, supercapacitors, and fuel cells, depends greatly on developing improved charged interfaces between electrodes and electrolytes. The rational development of such interfaces can benefit from the atomistic understanding of the materials involved by first-principles quantum mechanical simulations with Density Functional Theory (DFT). However, such simulations are...
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Agent-Based Data Reduction Using Ensemble Technique
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EBE: elastic blob ensemble for coarse human tracking
PublikacjaProponujemy nowy probabilistyczny algorytm śledzenia oparty na elastycznym zespole kropelkowym (EBE), który ma zastosowanie przy śledzeniu obiektów elastycznych. Wynikiem jest wskazówka nt. zgrubnego ruchu w postaci lokalizacji i orientacji obiektu wraz z lokalizacją kropelki. Głównym założeniem jest to, że orientacja całego obiektu nie zmienia się znacznie między sąsiednimi klatkami. Dyskretna przestrzeń rozwiązań jest tworzona...
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Estimation of a Stochastic Burgers' Equation Using an Ensemble Kalman Filter
PublikacjaIn this work, we consider a difficult problem of state estimation of nonlinear stochastic partial differential equations (SPDE) based on uncertain measurements. The presented solution uses the method of lines (MoL), which allows us to discretize a stochastic partial differential equation in a spatial dimension and represent it as a system of coupled continuous-time ordinary stochastic differential equations (SDE). For such a system...
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SMOTE-Based Homogeneous Ensemble Methods for Software Defect Prediction
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Ensemble-Based Logistic Model Trees for Website Phishing Detection
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Heterogeneous Ensemble with Combined Dimensionality Reduction for Social Spam Detection
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Study of preference for surround microphone techniques, used in the recording of choir and instrumental ensemble
PublikacjaThe aim of this paper is to describe the process of choosing the best surround microphone technique for recording of choir with an instrumental ensemble. First, examples of multichannel microphone techniques including those used in the recording are described. Then, the assumptions and details of music recording in Radio Gdansk Studio are provided as well as the process of mixing of the multichannel recording. The extensive subjective...
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Multidimensional Feature Selection and Interaction Mining with Decision Tree Based Ensemble Methods
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Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction
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Ensemble Online Classifier Based on the One-Class Base Classifiers for Mining Data Streams
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Comparison of single best artificial neural network and neural network ensemble in modeling of palladium microextraction
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublikacjaThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublikacjaThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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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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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams
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Ensemble fits of restrained peptides’ conformational equilibria to NMR data. Dependence on force fields: AMBER/8 ff03 versus ECEPP/3
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublikacjaWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Recent Developments in Data-Assisted Modeling of Flexible Proteins
PublikacjaMany proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublikacjaMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Shape-Based Pose Estimation of Robotic Surgical Instruments
PublikacjaWe describe a detector of robotic instrument parts in image-guided surgery. The detector consists of a huge ensemble of scale-variant and pose-dedicated, rigid appearance templates. The templates, which are equipped with pose-related keypoints and segmentation masks, allow for explicit pose estimation and segmentation of multiple end-effectors as well as fine-grained non-maximum suppression. We train the templates by grouping examples...
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Polish Conference on Crystal Growth 2022
WydarzeniaWelcome to the webpage of the Polish Conference on Crystal Growth 2022! The conference will be held in Gdańsk, Poland on June 19-24, 2022. The event is organized by the Polish Society for Crystal Growth (PTWK) in collaboration with Gdańsk University of Technology and the ENSEMBLE 3 Centre...
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Transmitting Alarm Information in DAB+ Broadcasting System
PublikacjaThe main goal of digital broadcasting is to deliver high-quality content with the lowest possible bitrate. This paper is focused on transmitting alarm information, such as emergency warning and alerting, in the DAB+ (Digital Audio Broadcasting plus) broadcasting system. These additional services should be available at the lowest possible bitrate, in order to provide a clear and understandable voice message to people. Furthermore, additional...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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SUBIEKTYWNA OCENA MULTIPLEKSU RADIOFONII LOKALNEJ DAB+ DZIAŁAJĄCEJ W GDAŃSKU I WROCŁAWIU
PublikacjaStandard DAB+ (Digital Audio Broadcasting plus) jest wiodącym systemem naziemnej radiofonii cyfrowej. W porównaniu do analogowej radiofonii FM wszystkie usługi, obejmujące tradycyjne programy radiowe oraz usługi transmisji danych, grupowane są w zbiór (ensemble). Praca ta przedstawia proces rekonfiguracji polskiego multipleksu na przykładzie lokalnej radiofonii DAB+ w Gdańsku i Wrocławiu. Opisuje wyniki badań subiektywnych dotyczących...
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublikacjaOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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The influence of image masks definition onsegmentation results of histopathological imagesusing convolutional neural network
PublikacjaAbstract—In the era of collecting large amounts of tissue materials, assisting the work of histopathologists with various electronic and information IT tools is an undeniable fact. The traditional interaction between a human pathologist and the glass slide is changing to interaction between an AI pathologist with a whole slide images. One of the important tasks is the segmentation of objects (e.g. cells) in such images. In this...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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Convex set of quantum states with positive partial transpose analysed by hit and run algorithm
PublikacjaThe convex set of quantum states of a composite K×K system with positive partial transpose is analysed. A version of the hit and run algorithm is used to generate a sequence of random points covering this set uniformly and an estimation for the convergence speed of the algorithm is derived. For K >3 or K=3 this algorithm works faster than sampling over the entire set of states and verifying whether the partial transpose is positive....
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Generic appearance of objective results in quantum measurements
PublikacjaMeasurement is of central interest in quantum mechanics as it provides the link between the quantum world and the world of everyday experience. One of the features of everyday experience is its robust, objective character, contrasting the delicate nature of quantum systems. Here we analyze in a completely model-independent way the celebrated von Neumann measurement process, using recent techniques of information flow, studied in...
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Towards Improving Optimised Ship Weather Routing
PublikacjaThe aim of the paper is to outline a project focusing on the development of a new type of ship weather routing solution with improved uncertainty handling, through better estimation of ship performance and responses to sea conditions. Ensemble forecasting is considered to take into account the uncertainty levels that are typical of operations in a stochastic environment. Increased accuracy of weather prediction is achieved through...
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Empirical analysis of tree-based classification models for customer churn prediction
PublikacjaCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Subiektywny pomiar jakości sygnałów mowy i muzyki w lokalnych multipleksach radiofonii DAB+ w Gdańsku i Wrocławiu
PublikacjaRadiofonia cyfrowa DAB+ (Digital Audio Broadcasting plus) dostępna jest dla słuchaczy w Polsce od 2013 r. Standard ten oferuje szerokie możliwości konfiguracji multipleksów lokalnych nie tylko pod względem liczby, lecz także jakości nadawanych programów radiowych. Dzięki temu możliwe jest dostosowanie parametrów emitowanych sygnałów w celu sprostania oczekiwaniom odbiorców końcowych. W przeciwieństwie do radiofonii analogowej FM...
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Finding the Right Solvent: A Novel Screening Protocol for Identifying Environmentally Friendly and Cost-Effective Options for Benzenesulfonamide
PublikacjaThis study investigated the solubility of benzenesulfonamide (BSA) as a model compound using experimental and computational methods. New experimental solubility data were collected in the solvents DMSO, DMF, 4FM, and their binary mixtures with water. The predictive model was constructed based on the best-performing regression models trained on available experimental data, and their hyperparameters were optimized using a newly...
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Study Analysis of Transmission Efficiency in DAB+ Broadcasting System
PublikacjaDAB+ is a very innovative and universal multimedia broadcasting system. Thanks to its updated multimedia technologies and metadata options, digital radio keeps pace with changing consumer expectations and the impact of media convergence. Broadcasting analog and digital radio services does vary, concerning devices on both transmitting and receiving side, as well as content processing mechanisms. However, the biggest difference is...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Coherent-wave Monte Carlo method for simulating light propagation in tissue
PublikacjaSimulating propagation and scattering of coherent light in turbid media, such as biological tissues, is a complex problem. Numerical methods for solving Helmholtz or wave equation (e.g. finite-difference or finite-element methods) require large amount of computer memory and long computation time. This makes them impractical for simulating laser beam propagation into deep layers of tissue. Other group of methods, based on radiative...
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Influence of addition of carbon nanotubes on rheological properties of selected liquid lubricants - a computer simulation study
PublikacjaThis work is motivated by the improvement of anti-friction properties of lubricants by addition of CNTs proved experimentally in literature. In particular, a methodology is developed to compute the shear viscosity of liquid lubricants (Propylene Glycol) based on Molecular Dynamics simulation. Non-Equilibrium molecular dynamics (NEMD) approach is used with a reactive force field ReaxFF implemented in LAMMPS. The simulations are...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublikacjaThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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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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Vibrational Quenching of Optically Pumped Carbon Dimer Anions
PublikacjaCareful control of quantum states is a gateway to research in many areas of science such as quantum information, quantum-controlled chemistry, and astrophysical processes. Precise optical control of molecular ions remains a challenge due to the scarcity of suitable level schemes, and direct laser cooling has not yet been achieved for either positive or negative molecular ions. Using a cryogenic wire trap, we show how the internal...
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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...