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Wyniki wyszukiwania dla: MACHINE LEARNING ALGORITHM SOIL-STRUCTURE INTERACTION SEISMIC RISK ASSESSMENT RESIDUAL INTERSTORY DRIFT SEISMIC DEMAND SEISMIC FAILURE PROBABILITY
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Application of the fluid–structure interaction technique for the analysis of hydrodynamic lubrication problems.
PublikacjaFluid–structure interaction technique seems to be one of the most promising possibilities for theoretical analysis of lubrication problems. It allows coupling of different physical fields in one computational task, taking into account the interaction between them. In this article, two sets of fluid–structure interaction analyses focusing on the bearing performance evaluation are presented. One analysis was applied to a water-lubricated...
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Discussion on “Dynamic soil-structure interaction: A three-dimensional numerical approach and its application to the Lotung case study”. Poor performance of the HSS model
PublikacjaThe Hardening Soil Small (HSS) is a constitutive model being extension to the well established Hardening Soil Model (HS) accounting for the nonlinearity of small strain stiffness. It is implemented in commercial finite element computer codes for geotechnical analyses and used widely in research and design. The article deals with a problem known as overshooting after very small load reversals. It induces much higher stiffness than...
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Corrigendum to “An investigation on residual stress and fatigue life assessment of T-shape welded joints” [Eng. Fail. Anal. 141 (2022) 106685]
PublikacjaThis paper aims to quantitatively evaluate the residual stress and fatigue life of T-type welded joints with a multi-pass weld in different direction. The main research objectives of the experimental test were to test the residual stress by changing direction along with multiple wielding passes and determine the fatigue life of the welded joints. The result shows that compressive residual stress increases in the sample gradually...
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Quantitative risk assessment of new ship designs in damage conditions
PublikacjaThe paper is devoted to safety of ships in damage conditions. The novel contribution of the paper is connected with a new Multi-Task ship (MT-ship) design at the preliminary stage of design. There are a few problems at the preliminary stage that should be considered. One problem is connected with if the quantitative risk-based method is a reliable and formal method for safety assessment of such the new design (MT-ship) in damage...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Assessment of cardiovascular risk in assisted living
PublikacjaWady i choroby układu krążenia są jedną z podstawowych przyczyn problemów zdrowotnych oraz przyczyn śmierci. Wczesne ich wykrycie jest szczególnie cenne jako, że może zapobiec przez poważnymi incydentami (np. zawał, udar, itp.). W artykule przedstawiono nasobny system pomiarowy integrujący wiele pomiarów przydatnych do oceny problemów kardiologicznych.Disorders of the heart and blood vessels are the leading cause of health problems...
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The risk assessment of adverse events of nursing activities as the element of quality management in healhcare
PublikacjaThe purpose of the paper is to present MedCARVER+Shock method and Pareto analysis and its usability for the risk assessment of adverse events of nursing activities. 888 activities carried out by all 190 nurses working at the District Hospital X located in Poland were taken into account. During the research the qualitative approach was used. As the result sixteen groups of nursing activities causing the highest risk of adverse events...
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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...
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Simulation of the response of base-isolated buildings under earthquake excitations considering soil flexibility
PublikacjaThe accurate analysis of the seismic response of isolated structures requires the incorporation of the flexibility of supporting soil. However, it is often customary to idealize the soil as rigid during the analysis of such structures. In the present paper, seismic response time history analyses of base-isolated buildings modelled as single degree-of-freedom (SDOF) and multi degree-of-freedom (MDOF) systems with linear and nonlinear...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Assessment of occupational risk in technical undertakings
PublikacjaSummary An undertaking - as a new and often single action - in its nature creates problems with predicting the realization of planned aims. Each undertaking bears some risk. Protection of a man who carries out an undertaking is even a more difficult task. The article offers a method of estimating potential risks connected with labour conditions on the basis of risk evaluation at the stage of undertaking planning.Streszczenie Realizacja...
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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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Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning
PublikacjaIn this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...
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Air flow phenomena in the model of the blind drift
PublikacjaIn the presented paper, Particle Image Velocimetry (PIV) has been used to investigate flow pattern and turbulent structure in the model of blind drift. The presented model exist in mining, and has been analyzed to resolve ventilation issues. Blind region is particularly susceptible to unsafe methane accumulation. The measurement system allows us to evaluate all components of the velocity vector in channel cross-section simultaneously....
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-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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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-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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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublikacjaIn this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
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Evaluation of Foundation Input Motions Based on Kinematic Interaction Models
PublikacjaThe present study was designed to demonstrate the importance of baseslab averaging and embedment effects on the foundation-level input motions due to earthquake excitations. Evaluation of foundation-level input motions based on the most commonly adopted kinematic interaction models are presented. In order to conduct this investigation, original records of horizontal accelerations for two casestudy buildings were utilized. Computed...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Variable-structure algorithm for identification of quasi-periodically varying systems
PublikacjaThe paper presents a variable-structure version of a generalized notchfiltering (GANF) algorithm. Generalized notch filters are used for identification of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The proposed algorithm is a cascade of two GANF filters: a multiple-frequency "precise" filter bank, used for precise system tracking, and a...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Numerical simulation of screw displacement pile interaction with non-cohesive soil
PublikacjaA trial numerical simulation of screw displacement pile interaction with non-cohesive subsoil during the transfer of compression load. The simulation was carried out in an axisymmetric system. The technological phases of pile installation in the ground were numerically modelled using equivalent processes which provided similar effects to real technical actions. The results of the numerical calculations were verified by comparing...
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Evaluation of foundation input motions based on kinematic interaction models
PublikacjaThe present study was designed to demonstrate the importance of base-slab averaging and embedment effects on the foundation-level input motions due to earthquake excitations. Evaluation of foundation-level input motions based on the most commonly adopted kinematic interaction models are presented. In order to conduct this investigation, original records of horizontal accelerations for two case-study buildings were utilized. Computed...
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Cargo ships heat demand - operational experiment
PublikacjaThe paper presents the results of an experiment conducted on two cargo ships – a 5300 TEU container with a steam heating system and a 7500 dwt general cargo ship with a thermal oil system. On both ships research has been carried out using specially designed measuring equipment. After gathering data about flow velocity and temperatures (steam/ cooling water/ thermal oil/ seawater/ outside air), calculations have been done, resulting...
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ANALYSIS OF THE PUNCHING FAILURE MECHANISM IN WORKING PLATFORMS
PublikacjaPaper presents an analysis of the shear failure mechanism which occurs from the punching of a working platform layer in relation to its thickness, grain size arrangement and mechanical properties, taking into consideration the interaction with soft subgrade. The study is based on the observations of performance of natural scale structures (Streefkerk) and the results of model investigations numerically represented with the use...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Failure Monitoring and Condition Assessment of Steel-Concrete Adhesive Connection Using Ultrasonic Waves
PublikacjaAdhesive bonding is increasingly being incorporated into civil engineering applications. Recently, the use of structural adhesives in steel-concrete composite systems is of particular interest. The aim of the study is an experimental investigation of the damage assessment of the connection between steel and concrete during mechanical degradation. Nine specimens consisted of a concrete cube and two adhesively bonded steel plates...
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Environmental Risk Assessment of WWII Shipwreck pollution
PublikacjaThe pollution of the sea is a global problem that has arisen as a consequence of the industrialization of the world and the intense transportation of crude oil and the products of its refinement. As sailing vessels were replaced by motor propelled ships towards the end of the 19th century, a new source of sea water pollution came into being. Every emergency involving a tanker carrying crude oil and its products is a potential source...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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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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An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
PublikacjaAn innovative tool for modeling the specific flood volume was presented that can be applied to assess the need for stormwater network modernization as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland, were used to apply the model and demonstrate its usefulness. This model extends the capability of recently developed statistical and machine learning hydrodynamic models developed...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublikacjaIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Behaviour of Asymmetric Structure with Base Isolation Made of Polymeric Bearings
PublikacjaEarthquake-induced ground motions are the most severe and unpredictable threats to the structures all around the world. Seismic excitations cause a lot of damage in a wide variety of ways, leaving thousands of casualties in their wake. Due to randomness of earthquake occurrence, lack of visible causes and their power of destructiveness, structural engineers need to develop new technical solutions and protection systems against...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublikacjaLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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A framework for risk matrix design: A case of MASS navigation risk
PublikacjaRisk matrix, a tool for visualizing risk assessment results, is essential to facilitate the risk communication and risk management in risk-based decision-making processes related to new and unexplored socio-technical systems. The use of an appropriate risk matrix is discussed in the literature, but it is overlooked for emerging technologies such as Maritime Autonomous Surface Ships (MASS). In this study, a comprehensive framework...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Structure and Randomness in Planning and Reinforcement Learning
PublikacjaPlanning in large state spaces inevitably needs to balance the depth and breadth of the search. It has a crucial impact on the performance of a planner and most manage this interplay implicitly. We present a novel method \textit{Shoot Tree Search (STS)}, which makes it possible to control this trade-off more explicitly. Our algorithm can be understood as an interpolation between two celebrated search mechanisms: MCTS and random...
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The influence of changes of soil parameters due to consolidation on the interaction of piles and soft soil layer
PublikacjaZaprezentowano problem wyznaczania bocznego parcia gruntu o małej wytrzymałości na pale. Opisano przypadki występowania bocznego obciążenia pali. Scharakteryzowano właściwości i zachowanie gruntów słabych stanowiących warstwę podłoża o małej wytrzymałości. Zaprezentowano propozycje obliczania bocznego parcia według różnych autorów. Przedstawiono wpływ konsolidacji na zmianę wytrzymałości gruntów słabych w czasie oraz na obliczanie...
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Failure analysis of a high-speed induction machine driven by a SiC-inverter and operating on a common shaft with a high-speed generator
PublikacjaDue to ongoing research work, a prototype test rig for testing high-speed motors/generators has been developed. Its design is quite unique as the two high- speed machines share a single shaft with no support bearings between them. A very high maximum operating speed, up to 80,000 rpm, was required. Because of the need to minimise vibration during operation at very high rotational speeds, rolling bearings were used. To eliminate...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublikacjaEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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The risk of corporate bankruptcy - the conceptual model
PublikacjaThis article concerns the assessment of different types of risks influencing the corporate bankruptcy risk. The author has developed conceptual model that explains the causes and the trajectories of the collapse of enterprises. In the analyses such factors as demographic, financial, market, political and operational factors influencing the risk of failure were taken into account.
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Interaction of Novel Ionic Liquids with Soils
PublikacjaWith the constant development of new ionic liquids, the understanding of the chemical fate of these compounds also needs to be updated. To this effect, in this contribution, the interaction of a number of novel ionic liquids with soils was determined. Therefore, three novel headgroups (ammonium, phosphonium or pyrrolidinium) with single or quaternary substitution were tested on a variety of soils with high to low organic matter...