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Wyniki wyszukiwania dla: multi-task learning
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Determination of COD Fractionation as a Key Factor for Appropriate Modelling and Monitoring of Activated Sludge Processes
PublikacjaAn 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...
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The potential of LC–MS technique in direct analysis of perfume content
PublikacjaPerfumes 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...
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Chromatographic separation, determination and identification of ecdysteroids: Focus on Maral root (Rhaponticum carthamoides, Leuzea carthamoides )
PublikacjaThe 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...
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Detection of the First Component of the Received LTE Signal in the OTDoA Method
PublikacjaIn 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,...
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Bridging challenges of clinical decision support systems with a semantic approach. A case study on breast cancer
PublikacjaThe integration of Clinical Decision Support Systems (CDSS) in nowadays clinical environments has not been fully achieved yet. Although numerous approaches and technologies have been proposed since 1960, there are still open gaps that need to be bridged. In this work we present advances from the established state of the art, overcoming some of the most notorious reported difficulties in: (i) automating CDSS, (ii) clinical workflow...
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Usage of parametric echosounder with emphasis on buried object searching.
PublikacjaThe purpose of this article is to present the results of investigation to search for buried objects. The paper will contain echograms and other means of visualization from buried pipe placed between area of W?adys?awowo and gas platform and interesting in terms of the number of small and medium-sized unidentified objects found in the muddy bottom at different depths localized in the Gulf of Puck - results will be presented also...
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Bearing estimation using double frequency reassignment for a linear passive array
PublikacjaThe 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...
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Neural Oscillation During Mental Imagery in Sport: An Olympic Sailor Case Study
PublikacjaThe 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)...
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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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Investigation of optical properties of Infitec and Active Stereo stereoscopic techniques for CAVE-type virtual reality systems
PublikacjaIn 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...
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Metals and metal-binding ligands in wine: Analytical challenges in identification.
PublikacjaBackground 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...
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Creating new voices using normalizing flows
PublikacjaCreating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities. Firstly, we create an approach for TTS...
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Numerically Efficient Miniaturization-Oriented Optimization of an Ultra-Wideband Spline-Parameterized Antenna
PublikacjaDesign 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,...
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The Digital Tissue and Cell Atlas and the Virtual Microscope
PublikacjaWith 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...
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Optical fiber aptasensor for label-free bacteria detection in small volumes
PublikacjaHighly 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...
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Biological processes modelling for MBR systems: A review of the state-of-the-art focusing on SMP and EPS
PublikacjaA mathematical correlation between biomass kinetic and membrane fouling can improve the understanding and spread of Membrane Bioreactor (MBR) technology, especially in solving the membrane fouling issues. On this behalf, this paper, produced by the International Water Association (IWA) Task Group on Membrane modelling and control, reviews the current state-of-the-art regarding the modelling of kinetic processes of biomass, focusing on...
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Autistic Employees’ Technology-Based Workplace Accommodation Preferences Survey—Preliminary Findings
PublikacjaBackground: There has been an increase in the number of research studies focused on the design of accommodations aimed at improving the well-being and work performance of autistic employees. These accommodations took various forms; some of them were based on modification of management practices, for example, support in the area of effective communication, or involved modifications to the physical working environment aimed at limiting...
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Multi-DBD plasma actuator for flow separation control around NACA 0012 and NACA 0015 airfoil models
PublikacjaIn this paper application of innovative multi-DBD plasma actuator for flow separation control is presented. The influence of the airflowgenerated by this actuator on the flow around NACA 0012 and NACA 0015 airfoil models was investigated. The results obtained from 2D PIVmeasurements showed that the multi-DBD actuator with floating interelectrode can be attractive for leading and trailing edge separation control.
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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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Application of multi-criteria methods to compare different solutions of supplying buildings in electricity from photovoltaic systems
PublikacjaNowadays, 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...
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Framework of an Evolutionary Multi-Objective Optimisation Method for Planning a Safe Trajectory for a Marine Autonomous Surface Ship
PublikacjaThis 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...
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Designing learning spaces through international and interdisciplinary collaborative design studio: The case of engineer architects and pedagogic students
PublikacjaThe study explores the dynamics and outcomes of an international interdisciplinary design studio focusing on innovative learning spaces. Conducted over two years between students of Faculty of Architecture at Gdansk Tech and pedagogic students from Kibbutzim College in Tel Aviv, this design-based study examines the contributions of unique educational program to student learning, the evolution of the design process, collaboration,...
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Investigation of Performance and Energy Consumption of Tokenization Algorithms on Multi-core CPUs Under Power Capping
PublikacjaIn this paper we investigate performance-energy optimization of tokenizer algorithm training using power capping. We focus on parallel, multi-threaded implementations of Byte Pair Encoding (BPE), Unigram, WordPiece, and WordLevel run on two systems with different multi-core CPUs: Intel Xeon 6130 and desktop Intel i7-13700K. We analyze execution times and energy consumption for various numbers of threads and various power caps and...
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Application of multi-criteria method to assess the usefulness of a hydrotechnical object for floating housing
PublikacjaThis 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....
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Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublikacjaThe 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...
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Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates
PublikacjaIn 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...
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Multi-Objective Water Distribution Systems Control of Pumping Cost, Water Quality, and Storage-Reliability Constraints
PublikacjaThis 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...
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Repeated Projectile Impact Tests on Multi-Layered FibrousCementitious Composites
PublikacjaThis 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...
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Strategies for computationally feasible multi-objective simulation-driven design of compact RF/microwave components
PublikacjaMulti-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...
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On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublikacjaPurpose 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...
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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 approach to packaging compatibility testing in the new product development process
PublikacjaThe 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...
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Sounding Mechanism of a Flue Organ Pipe—A Multi-Sensor Measurement Approach
PublikacjaThis 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...
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An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
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Parallelization of Selected Algorithms on Multi-core CPUs, a Cluster and in a Hybrid CPU+Xeon Phi Environment
PublikacjaIn 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...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublikacjaThe 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...
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Determination of probabilities defining safety of a sea-going ship during performance of a transportation task in stormy weather conditions
PublikacjaThe 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...
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Genetic solver of optimization task of mpc for optimizing control of integrated quantity and quality in drinking water distribution systems
PublikacjaPredykcyjne 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...
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Nested Kriging Surrogates for Rapid Multi-Objective Optimization of Compact Microwave Components
PublikacjaA 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,...
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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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Multi-objective optimization of microwave couplers using corrected domain patching
PublikacjaPractical 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...
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Availability of UAV Fleet Evaluation Based on Multi-State System
PublikacjaUnmanned 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...
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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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Collision‐Aware Routing Using Multi‐Objective Seagull Optimization Algorithm for WSN‐Based IoT
PublikacjaIn 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...
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Reliable Multi-Stage Optimization of Antennas for Multiple Performance Figures in Highly-Dimensional Parameter Spaces
PublikacjaDesign 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...
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublikacjaBackground. 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...
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Planning optimised multi-tasking operations under the capability for parallel machining
PublikacjaThe 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...
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Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
PublikacjaInstalling 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...
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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...