Filters
total: 3194
filtered: 2656
-
Catalog
Chosen catalog filters
displaying 1000 best results Help
Search results for: multi-task learning
-
Quantum entanglement
PublicationAll our former experience with application of quantum theory seems to say that what is predicted by quantum formalism must occur in the laboratory. But the essence of quantum formalism-entanglement, recognized by Einstein, Podolsky, Rosen, and Schrödinger-waited over 70 years to enter laboratories as a new resource as real as energy. This holistic property of compound quantum systems, which involves nonclassical correlations between...
-
Bearing estimation using double frequency reassignment for a linear passive array
PublicationThe paper demonstrates the use of frequency reassignment for bearing estimation. For this task, signals derived from a linear equispaced passive array are used. The presented method makes use of Fourier transformation based spatial spectrum estimation. It is further developed through the application of two-dimensional reassignment, which leads to obtaining highly concentrated energy distributions in the joint frequency-angle domain...
-
Determination of COD Fractionation as a Key Factor for Appropriate Modelling and Monitoring of Activated Sludge Processes
PublicationAn operation of wastewater treatment plant is usually controlled by global parameters such as flow, solids retention time, sludge age, concentration of ammonia and dissolved oxygen, etc. It is considered that, together with the chemical and biological oxygen demand (COD and BOD), those parameters indirectly exhibit the effectiveness of activated sludge processes. Especially the BOD indicate the amount of organic pollution that...
-
Detection of the First Component of the Received LTE Signal in the OTDoA Method
PublicationIn a modern world there is a growing demand for localization services of various kinds. Position estimation can be realized via cellular networks, especially in the currently widely deployed LTE (Long Term Evolution) networks. However, it is not an easy task in harsh propagation conditions which often occur in dense urban environments. Recently, time-methods of terminal localization within the network have been the focus of attention,...
-
Chromatographic separation, determination and identification of ecdysteroids: Focus on Maral root (Rhaponticum carthamoides, Leuzea carthamoides )
PublicationThe review presents general principles for choosing optimal conditions for ecdysteroid separation, identification, and isolation using HPLC/TLC techniques in RP, NP- HILIC or NP modes. Analytics of ecdyteroids pose a still insufficiently resolved problem. Plant-derived ecdysteroids are a point of interest of pharmaceutical industry and sport medicine due to their postulated adaptogenic and anabolic properties. In insects, ecdysteroids...
-
Optical fiber aptasensor for label-free bacteria detection in small volumes
PublicationHighly sensitive devices for fast bacteria detection are sought to be developed with the task of quantifying the worldwide problem of pathogenic bacteria and thus helping to take control over spreading bacterial infections. This work concerns a sensing solution based on microcavity in-line Mach-Zehnder interferometer (μIMZI) induced in an optical fiber. Such a device exhibits ultrahigh sensitivity to refractive index changes...
-
Metals and metal-binding ligands in wine: Analytical challenges in identification.
PublicationBackground Due to important role of metals in the vinification process as well as their impact on the human health, their content in this alcoholic beverage has been extensively studied by many researchers. It is already known that speciation of metals determines their toxicity and bioavailability as well as influences their activity. Understanding the chemistry and knowing the structures of metal complexes could have relevant...
-
The Digital Tissue and Cell Atlas and the Virtual Microscope
PublicationWith the cooperation of the CI TASK (Center of lnformatics Tri-Citry Academic Supercomputer and network) and the Gdańsk University of Technology, the Medical University of Gdańsk undertook the creation of the Digital Tissue and Cell Atlas and the Virtual Microscope for the needs of the Bridge of Data project. In the beginning, an extensive collection of histological and cytological slides was carefully selected and prepared by...
-
Neural Oscillation During Mental Imagery in Sport: An Olympic Sailor Case Study
PublicationThe purpose of the current study was to examine the cortical correlates of imagery depending on instructional modality (guided vs. self-produced) using various sports-related scripts. According to the expert-performance approach, we took an idiosyncratic perspective analyzing the mental imagery of an experienced two-time Olympic athlete to verify whether different instructional modalities of imagery (i.e., guided vs. self-produced)...
-
Numerically Efficient Miniaturization-Oriented Optimization of an Ultra-Wideband Spline-Parameterized Antenna
PublicationDesign of ultra-wideband radiators for modern handheld applications is a challenging task that involves not only selection of an appropriate topology, but also its tuning oriented towards balancing the electrical performance and size. In this work, a low-cost design of a compact, broadband, spline-parameterized monopole antenna has been considered. The framework used for the structure design implements trust-region-based methods,...
-
The potential of LC–MS technique in direct analysis of perfume content
PublicationPerfumes are products that consist of a wide range of natural and synthetic compounds. Due to complex composition, the determination of their ingredients is a difficult task. Most of the perfume components are either volatile or semi-volatile; however, most of the attention has been paid to volatile ones, and thus, gas chromatography or electronic noses are generally used. Nevertheless, in this study, liquid chromatography coupled...
-
Investigation of optical properties of Infitec and Active Stereo stereoscopic techniques for CAVE-type virtual reality systems
PublicationIn recent years, many scientific and industrial centres in the world developed virtual reality systems or laboratories. At present, among the most advanced virtual reality systems are CAVE-type (Cave Automatic Virtual Environment) installations. Such systems usually consist of four, five, or six projection screens arranged in the form of a closed or hemi-closed space. The basic task of such systems is to ensure the effect of user...
-
Application of multi-criteria methods to compare different solutions of supplying buildings in electricity from photovoltaic systems
PublicationNowadays, the technologies of electricity generation in distributed systems are usually associated with Renewable Energy Sources (RES). The choice of the construction site depends mainly on the availability of the power system. However, energy planning, especially in case of RES, is a complex process involving multiple and often conflicting objectives. The complexity of the selection of the electricity system is typically addressed...
-
Framework of an Evolutionary Multi-Objective Optimisation Method for Planning a Safe Trajectory for a Marine Autonomous Surface Ship
PublicationThis paper represents the first stage of research into a multi-objective method of planning safe trajectories for marine autonomous surface ships (MASSs) involved in encounter situations. Our method applies an evolutionary multi-objective optimisation (EMO) approach to pursue three objectives: minimisation of the risk of collision, minimisation of fuel consumption due to collision avoidance manoeuvres, and minimisation of the extra...
-
Application of multi-criteria method to assess the usefulness of a hydrotechnical object for floating housing
PublicationThis publication presents the analysis of three hydrotechnical objects located in the Municipality of Gdańsk with a view of mooring Floating Houses. The assessment of the adaptation of a hydrotechnical object has been carried out by a multi- criteria method AHP and using the main criteria such as: mooring system, communication with the mainland, availability of the utility networks, waste disposal and location of the parking spaces....
-
Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublicationThe paper describes the voltage control technique of squire-cage induction machines supplied by a current source inverter. The control system is based on new transformation of the electric drive system (machine and inverter) state variables to the multi-scalar variables form. The backstepping approach is used to obtain the feedback control law. The control system contains the structure of the observer...
-
Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates
PublicationIn the paper, computationally efficient constrained multi-objective design optimization of transonic airfoil profiles is considered. Our methodology focuses on fixed-lift design aimed at finding the best possible trade-offs between the two objectives: minimization of the drag coefficient and maximization of the pitching moment. The algorithm presented here exploits the surrogate-based optimization principle, variable-fidelity computational...
-
Multi-Objective Water Distribution Systems Control of Pumping Cost, Water Quality, and Storage-Reliability Constraints
PublicationThis work describes a multi-objective model for trading-off pumping cost and water quality for water distribution systems operation. Constraints are imposed on flows and pressures, on periodical tanks operation, and on tanks storage. The methodology links the multi-objective SPEA2 algorithm with EPANET, and is applied on two example applications of increasing complexity, under extended period simulation conditions and variable...
-
Repeated Projectile Impact Tests on Multi-Layered FibrousCementitious Composites
PublicationThis research aims to experimentally evaluate the behaviour of multi-layered fibrous cementitious composites withintermediate Glass Fibre Meshes (GFM) under repeated projectile load. The impact load was subjected through a convexedge projectile needle at a low velocity on cylindrical specimens of three-layered fibrous cementitious composites, whichhave two different steel fibre distributions. In series A mixtures, a constant steel...
-
Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
-
Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic 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....
-
Strategies for computationally feasible multi-objective simulation-driven design of compact RF/microwave components
PublicationMulti-objective optimization is indispensable when possible trade-offs between various (and usually conflicting) design objectives are to be found. Identification of such design alternatives becomes very challenging when performance evaluation of the structure/system at hand is computationally expensive. Compact RF and microwave components are representative examples of such a situation: due to highly compressed layouts and considerable...
-
An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
Publication -
On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublicationPurpose This paper aims to investigate deterministic strategies for low-cost multi-objective design optimization of compact microwave structures, specifically, impedance matching transformers. The considered methods involve surrogate modeling techniques and variable-fidelity electromagnetic (EM) simulations. In contrary to majority of conventional approaches, they do not rely on population-based metaheuristics, which permit lowering...
-
Sounding Mechanism of a Flue Organ Pipe—A Multi-Sensor Measurement Approach
PublicationThis work presents an approach that integrates the results of measuring, analyzing, and modeling air flow phenomena driven by pressurized air in a flue organ pipe. The investigation concerns a Bourdon organ pipe. Measurements are performed in an anechoic chamber using the Cartesian robot equipped with a 3D acoustic vector sensor (AVS) that acquires both acoustic pressure and air particle velocity. Also, a high-speed camera is employed...
-
Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublicationThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
-
Parallelization of Selected Algorithms on Multi-core CPUs, a Cluster and in a Hybrid CPU+Xeon Phi Environment
PublicationIn the paper we present parallel implementations as well as execution times and speed-ups of three different algorithms run in various environments such as on a workstation with multi-core CPUs and a cluster. The parallel codes, implementing the master-slave model in C+MPI, differ in computation to communication ratios. The considered problems include: a genetic algorithm with various ratios of master processing time to communication...
-
Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe 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...
-
Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery 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...
-
Nested Kriging Surrogates for Rapid Multi-Objective Optimization of Compact Microwave Components
PublicationA procedure for rapid EM-based multi-objective optimization of compact microwave components is presented. Our methodology employs a recently developed nested kriging modelling to identify the search space region containing the Pareto-optimal designs, and to construct a fast surrogate model. The latter permits determination of the initial Pareto set, further refined using a separate surrogate-assisted process. As an illustration,...
-
Multi-objective optimization of microwave couplers using corrected domain patching
PublicationPractical design of microwave components and circuits is a compromise between various, often conflicting objectives. In case of compact structures, the trade-offs are typically concerned with the circuit size and its electrical performance. Comprehensive information about the best possible trade-offs can be obtained by means of multi-objective optimization. In this paper, we propose a computationally efficient technique for identifying...
-
Availability of UAV Fleet Evaluation Based on Multi-State System
PublicationUnmanned Aerial Vehicle (UAV) applications are extended extremely. Some applications need to use several UAVs for a general mission which can be considered a UAV fleet. One of the important characteristics for the evaluation of a UAV or UAV fleet is reliability. There are studies in which methods for analysis of their reliability are considered. Reliability analysis of UAV fleets is less frequently studied, although a single UAV...
-
Collision‐Aware Routing Using Multi‐Objective Seagull Optimization Algorithm for WSN‐Based IoT
PublicationIn recent trends, wireless sensor networks (WSNs) have become popular because of their cost, simple structure, reliability, and developments in the communication field. The Internet of Things (IoT) refers to the interconnection of everyday objects and sharing of information through the Internet. Congestion in networks leads to transmission delays and packet loss and causes wastage of time and energy on recovery. The routing protocols...
-
Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
-
Genetic solver of optimization task of mpc for optimizing control of integrated quantity and quality in drinking water distribution systems
PublicationPredykcyjne sterowanie zintegrowana jakością i ilością wody pitnej umożliwia uzyskanie lepszej jakości sterowania niż w przypadku innych metod. Niestety wymaga rozwiązania nieliniowego, niewypukłego problemu optymalizacji. Z tego względu potrzebne jest wykorzystanie specjalizowanego solwera w celu rozwiązania problemu optymalizacji predykcyjnej w wymaganych czasie. W tym artykule przedstawiony jest dedykowany algorytm genetyczny...
-
Determination of probabilities defining safety of a sea-going ship during performance of a transportation task in stormy weather conditions
PublicationThe paper presents the possibility of applying the theory of semi-Markov processes to determine the limiting distribution for the process of changes of technical states being reliability states of the systems of sea-going ships significantly affecting safety of such ships, which include main engine, propeller and steering gear. The distribution concerns the probabilities of occurrence of the said states defined for a long time...
-
Reliable Multi-Stage Optimization of Antennas for Multiple Performance Figures in Highly-Dimensional Parameter Spaces
PublicationDesign of modern antenna structures needs to account for multiple performance figures and geometrical constraints. Fulfillment of these calls for the development of complex topologies described by a large number of parameters. EM-driven tuning of such designs is mandatory yet immensely challenging. In this letter, a new framework for multi-stage design optimization of multi-dimensional antennas with respect to several performance...
-
Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
PublicationInstalling photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based...
-
Transformational Leadership and Acceptance of Mistakes as a Source of Learning: Poland-USA Cross-Country Study
PublicationThis study explores the influence of transformational leadership on internal innovativeness mediated by mistakes acceptance, including country and industry as factors to be considered and gender and risk-taking attitude as moderators. General findings, primarily based on the US samples (healthcare, construction, and IT industry), confirmed that transformational leadership and internal innovativeness are mediated by mistakes acceptance...
-
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...
-
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...
-
Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
-
Planning optimised multi-tasking operations under the capability for parallel machining
PublicationThe advent of advanced multi-tasking machines (MTMs) in the metalworking industry has provided the opportunity for more efficient parallel machining as compared to traditional sequential processing. It entailed the need for developing appropriate reasoning schemes for efficient process planning to take advantage of machining capabilities inherent in these machines. This paper addresses an adequate methodical approach for a non-linear...
-
Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods 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...
-
Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
-
Fuzzy Multi-Regional Fractional PID controller for Pressurized Water nuclear Reactor
PublicationThe paper presents the methodology for the synthesis of a Fuzzy Multi-Regional Fractional Order PID controller (FMR-FOPID) used to control the average thermal power of a PWR nuclear reactor in the load following mode. The controller utilizes a set of FOPID controllers and the fuzzy logic Takagi-Sugeno reasoning system. The proposed methodology is based on two optimization parts. The first part is devoted to finding the optimal...
-
Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning
PublicationIn 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...
-
EM-Driven Multi-Objective Design of Impedance Transformers By Pareto Ranking Bisection Algorithm
PublicationIn the paper, the problem of fast multi-objective optimization of compact impedance matching transformers is addressed by utilizing a novel Pareto ranking bisection algorithm. It approximates the Pareto front by dividing line segments connecting the designs found in the previous iterations, and refining the obtained candidate solutions by means of poll-type search involving Pareto ranking. The final Pareto set is obtained using...
-
Fast Multi-Objective Aerodynamic Optimization Using Sequential Domain Patching and Multifidelity Models
PublicationExploration of design tradeoffs for aerodynamic surfaces requires solving of multi-objective optimization (MOO) problems. The major bottleneck here is the time-consuming evaluations of the computational fluid dynamics (CFD) model used to capture the nonlinear physics involved in designing aerodynamic surfaces. This, in conjunction with a large number of simulations necessary to yield a set of designs representing the best possible...
-
Issues relating to the efficient Application of passive solar protection in multi-family residential buildings
PublicationThe following article is intended to discuss the issues concerning the introduction of passive measures aimed at improving solar protection in multi-family buildings. A system of classifying these methods into two groups of solutions (architectural and material-building) was applied. The first group includes issues concerning facade design, the spatial features of which (such as loggias, balconies and other overhangs) can be treated...