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Search results for: python
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Algorithmic synthesis using Python compiler
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Simulation Environment in Python for Ship Encounter Situations
PublicationTo assess the risk of collision in radar navigation distance-based safety measures such as Distance at the Closest Point of Approach and Time to the Closest Point of Approach are most commonly used. Also Bow Crossing Range and Bow Crossing Time measures are good complement to the picture of the meeting situation. When ship safety domain is considered then Degree of Domain Violation and Time to Domain Violation can be applied. This...
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Python based high-level synthesis compiler
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Addressing the Weaknesses of Multi-Criteria Decision-Making Methods using Python
PublicationThe book aims to draw attention to the weaknesses in Multi-Criteria Decision-Making (MCDM) methods and provide insights to improve the decision-making process. By addressing these weaknesses, it seeks to enhance the accuracy and effectiveness of MCDM methods in selecting the best alternatives in various fields. The book covers popular MCDM methods such as TOPSIS, ELECTRE, VIKOR, and PROMETHEE. It compares traditional methods with...
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System logiki rozmytej wspomagający tworzenie animacji komputerowych w oparciu o język Python
PublicationW celu tworzenia animacji komputerowych opartych o reguły wywodzące się z animacji tradycyjnej zaimplementowano system logiki rozmytej w języku Python, wykorzystujący słownikowy typ danych (tablice asocjacyjne). Zaprojektowane reguły łączą etykiety słowne, oznaczające zmienne lingwistyczne z etykietami nazw funkcji przynależności wykorzystującymi wartości lingwistyczne. W referacie przedstawiono fazy projektowania systemu, określania...
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Implementacja reguł animacji w logice rozmytej
PublicationZaprojektowano system komputerowy wspomagający tworzenie animacji. System wykorzystuje reguły animacji wywodzące się z animacji tradycyjnej. Reguły opisują sposób uzyskiwania animacji postaci nacechowanych emocjonalnie. Na potrzeby badań zostały one sformułowane w logice rozmytej i zaimplementowane w języku programowania Python. Wykorzystując system wygenerowano animacje testowe, które poddano ocenie subiektywnej, w celu określenia...
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Distance learning trends: introducing new solutions to data analysis courses
PublicationNowadays data analysis of any kind becomes a piece of art. The same happens with the teaching processes of statistics, econometrics and other related courses. This is not only because we are facing (and are forced to) teach online or in a hybrid mode. Students expect to see not only the theoretical part of the study and solve some practical examples together with the instructor. They are waiting to see a variety of tools, tutorials,...
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YADE - An extensible framework for the interactive simulation of multiscale, multiphase, and multiphysics particulate systems
PublicationThis contribution presents the key elements of YADE, an extensible open-source framework for dynamic simulations. During the past 19 years, YADE has evolved from "Yet Another Dynamic Engine"' to a versatile multiscale and multiphysics solver, counting a large, active, and growing community of users and developers. The computationally intense parts of the source code are written in C++, using flexible object models that allow for...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Driver fatigue detection method based on facial image analysis
PublicationNowadays, ensuring road safety is a crucial issue that demands continuous development and measures to minimize the risk of accidents. This paper presents the development of a driver fatigue detection method based on the analysis of facial images. To monitor the driver's condition in real-time, a video camera was used. The method of detection is based on analyzing facial features related to the mouth area and eyes, such as...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublicationThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
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Molywood: streamlining the design and rendering of molecular movies
PublicationMotivation High-quality dynamic visuals are needed at all levels of science communication, from the conference hall to the classroom. As scientific journals embrace new article formats, many key concepts – particularly in structural biology – are also more easily conveyed as videos than still frames. Notwithstanding, the design and rendering of a complex molecular movie remain an arduous task. Here, we introduce Molywood, a robust...
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Multimodal system for diagnosis and polysensory stimulation of subjects with communication disorders
PublicationAn experimental multimodal system, designed for polysensory diagnosis and stimulation of persons with impaired communication skills or even non-communicative subjects is presented. The user interface includes an eye tracking device and the EEG monitoring of the subject. Furthermore, the system consists of a device for objective hearing testing and an autostereoscopic projection system designed to stimulate subjects through their...
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Evaluati on of long-term start up costs impact on short-term price based operational optimization of a CCGT using MILP
PublicationAn increasing share of the weather-dependent RES generation in the power system leads to the growing importance of flexibility of conventional power plants. They were usually designed for base load operation and it is a challenge to determine the actual long-term cycling costs, which account for an increase in maintenance and overhaul expenditures, increased forced outage rates and shortened life expectancy of the plant and components....
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Zastosowanie wysokopoziomowych języków programowania do wyznaczania nośności przemieszczeniowych pali wkręcanych.
PublicationW artykule podjęta zostaje problematyka współczesnego, bardziej ekonomicznego projektowania pali. Rozwiązania normowe np. PN-83-B-2482, bazują zazwyczaj na wielkościach takich jak stopień zagęszczenia czy stopień plastyczności. Powoduje to, że dane uzyskane bezpośrednio z badań podłoża są korelowane podwójnie. W niniejszym opracowaniu proponuje się, aby korzystając z funkcji transformacyjnych wyznaczać nośność pala bezpośrednio...
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Finding the Right Solvent: A Novel Screening Protocol for Identifying Environmentally Friendly and Cost-Effective Options for Benzenesulfonamide
PublicationThis 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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Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublicationThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
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Decentralized Microgrid Energy Management System with Market-Based Energy Trade System
PublicationThis paper presents a decentralized energy management system for a power microgrid, which integrates individual users, who own renewable energy sources and energy storages. The purpose of the system is to make optimal use of available resources to cover the electricity needs of the whole microgrid. Thanks to the energy exchange system, in addition to exchanges with the distribution network, the system also allows trades within...
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Greenhouse control system design
PublicationCoraz większa populacja i zmniejszające się tereny uprawne wymusza efektywniejsze metody uprawy roślin. Zaradzić temu mogą układu hydroponiczne, które dzięki rozwojowi techniki są w stanie osiągać znacznie większe oraz bardziej jednorodne plony. Jest to możliwe dzięki zaawansowanym systemom opartym na dokładnych urządzeniach pomiarowych, sterowaniu w zamkniętej pętli oraz mikrokontrolerom umożliwiającym...
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Monte-Carlo Modeling of Optical Sensors for Postoperative Free Flap Monitoring
PublicationThis work aims to develop a numerical tissue model and implement software to simulate photon propagation using the Monte Carlo method to determine design guidelines for a physical measurement system. C++ was used for the simulation program, and Python as a programming environment to create an interface that allows the user to customize individual simulation elements, allowing for increased accuracy and flexibility when simulating...
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Cost-Effective and Sufficiently Precise Integration Method Adapted to the FEM Calculations of Bone Tissue
PublicationThe technique of Young’s modulus variation in the finite element is not spread in biomechanics. Our future goal is to adapt this technique to bone tissue strength calculations. The aim of this paper is to present the necessary studies of the element’s integration method that takes into account changes in material properties. For research purposes, a virtual sample with the size and distribution of mechanical properties similar...
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Monte-Carlo Modeling of Optical Sensors for Postoperative Free Flap Monitoring
PublicationThis work aims to develop a numerical tissue model and implement software to simulate photon propagation using the Monte Carlo method to determine design guidelines for a physical measurement system. C++ was used for the simulation program, and Python as a programming environment to create an interface that allows the user to customize individual simulation elements, allowing for increased accuracy and flexibility when simulating...
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Statistics with R A Handbook for Statistical Analysis with R and R-Studio
PublicationIf you are to perform any kind of data (statistical) analysis and use tools in the data science ecosystem, you may have seen a variety of tutorials, handbooks online (I’m not mentioning traditional bibles of statistics). Unfortunately most of them is written intentionally for specific purposes and/or target group of people and does not include many aspects, data types, difficult aspects, usually hiding them trying to solve theoretical...
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Proposition of the methodology for Data Acquisition, Analysis and Visualization in support of Industry 4.0
PublicationIndustry 4.0 offers a comprehensive, interlinked, and holistic approach to manufacturing. It connects physical with digital and allows for better collaboration and access across departments, partners, vendors, product, and people. Consequently, it involves complex designing of highly specialized state of the art technologies. Thus, companies face formidable challenges in the adoption of these new technologies....
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Behavior Based Complete Coverage Task of Unknown Area by an Autonomous Mobile Robot SCORPION with Static Obstacles in Environment
PublicationIn the paper the behavior based control system of an autonomous mobile robot SCORPION is presented to execute the one of the most difficult navigation task, which is the complete coverage task of unknown area with static obstacles in the environment. The main principle assumed to design control system was that the robot should cover all area only once, if it possible, to optimize the length of path and energy consumption. All commercial...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Automated measurement method for assessing thermal-dependent electronic characteristics of thin boron-doped diamond-graphene nanowall structures
PublicationThis paper investigates the electrical properties of boron-doped diamond-graphene (B:DG) nanostructures, focusing on their semiconductor characteristics. These nanostructures are synthesized on fused silica glass and Si wafer substrates to compare their behaviour on different surfaces. A specialized measurement system, incorporating Python-automated code, was developed for an in-depth analysis of electronic properties under various...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Long Distance Geographically Distributed InfiniBand Based Computing
PublicationCollaboration between multiple computing centres, referred as federated computing is becom- ing important pillar of High Performance Computing (HPC) and will be one of its key components in the future. To test technical possibilities of future collaboration using 100 Gb optic fiber link (Connection was 900 km in length with 9 ms RTT time) we prepared two scenarios of operation. In the first one, Interdisciplinary Centre for Mathematical...
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Electrical Simulations of the SIS100 Superconducting Dipole and Quadrupole Circuits: Transients, Earthing and Failure Modes
PublicationThe 100 Tm superconducting synchrotron SIS100 is the main accelerator of the international Facility for Antiproton and Ion Research (FAIR) currently under advanced construction in Darmstadt, Germany. The SIS100 dipole circuit which creates the magnetic field required to bend the beam, consists of 108 dipoles distributed over six arc sections of the ring. The magnetic field for the beam focusing is generated by three individual...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublicationIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublicationPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Techno-economic evaluation of combined cycle gas turbine and a diabatic compressed air energy storage integration concept
PublicationMore and more operational flexibility is required from conventional power plants due to the increasing share of weather-dependent renewable energy sources (RES) generation in the power system. One way to increase power plant’s flexibility is integrating it with energy storage. The energy storage facility can be used to minimize ramping or shutdowns and therefore should lower overall generating costs and CO2 emissions. In this article,...
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Metoda neuronowego wyznaczania przestrzennych pól przepływów w przydźwiękowych i naddźwiękowych kanałach łopatkowych turbin parowych
PublicationNiniejsza rozprawa doktorska została poświęcona opracowaniu metody neuronowego wyznaczania przestrzennych pól przepływów w okołodźwiękowych kanałach łopatkowych turbin parowych. Obiektem badań naukowych przedstawionych w kolejnych rozdziałach są dwa ostatnie stopnie części niskoprężnej turbozespołu 18K370 z wylotem ND-37. Pierwszym etapem badań była budowa numerycznego modelu przepływu pary mokrej przez analizowany układ łopatkowy....
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...