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Wyniki wyszukiwania dla: multi-task learning
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Optimizing FSO networks resilient to adverse weather conditions by means of enhanced uncertainty sets
PublikacjaThis work deals with dimensioning of wireless mesh networks (WMN) composed of FSO (free space optics) links. Although FSO links realize broadband transmission at low cost, their drawback is sensitivity to adverse weather conditions causing transmission degradation on multiple links. Hence, designing such FSO networks requires an optimization model to find the cheapest configuration of link capacities that will be able to carry...
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Creating Polish space language dictionary - lessons learned
PublikacjaPolish space industry suffers from lack of space vocabulary. Since joining European Space Agency in 2012, the sector has expanded rapidly now employing over 1000 specialists focusing mainly on space sustainability, space debris detection and tracking, robotics and propulsion systems. The Polish Space Agency together with The Polish Committee for Standardization have committed to creating the first lexicon of space language, along...
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Wage response to global production links: evidence for workers from 28 European countries (2005–2014)
PublikacjaUsing rich individual-level data on workers from 28 European countries, this study provides the first so extensive cross-country assessment of wage response to global production links within GVC in the period 2005–2014. Unlike the other studies, the authors (i) address the importance of backward linkages in globally integrated production structures (capturing imports of goods and services needed in any stage of the production of...
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Exploratory analysis and ranking of analytical procedures for short-chain chlorinated paraffins determination in environmental solid samples
PublikacjaShort-chain chlorinated paraffins are ones of the most recent chemical compounds that have been classified as persistent organic pollutants. They have various applications and are emitted to the environment. Despite the fact, that the content levels of these compounds in the environmental compartments should be monitored, there is still a lack of well-defined and validated analytical procedures, proposed or suggested by the national...
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Manufacture and research of TPS/PE biocomposites properties
PublikacjaIn this paper the process of native starch preparing for modification by extrusion and manufacture of biocomposites is presented. The first aim of this study was to determine the mixing and granulating condition of native starch to obtain granulated native starch. For mixing and granulation of native starch Intensive Mixer manufactured by Maschinenfabrik Gustav Eirich was used. Mixing and granulation in a single process is a new...
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Body surface area formulae: an alarming ambiguity
PublikacjaBody surface area (BSA) plays a key role in several medical fields, including cancer chemotherapy, transplantology, burn treatment and toxicology. BSA is often a major factor in the determination of the course of treatment and drug dosage. A series of formulae to simplify the process have been developed. Because easy-to-identify, yet general, body coefficient results of those formulae vary considerably, the question arises as to...
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Using Statistical Methods to Estimate The Worst Case Response Time of Network Software Running on Indeterministic Hardware Platforms
PublikacjaIn this paper we investigate whether the statistical Worst Case Execution Time (WCET) estimation methods devised for embedded platforms can be successfully applied to find the Worst Case Response Time (WCRT) of a network application running on a complex hardware platform such as a contemporary commercial off-the-shelf (COTS) system. Establishing easy-to-use timing validation techniques is crucial for real-time applications and...
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CFD and FEM model of an underwater vehicle propeller
PublikacjaDuring the project execution of design and optimization the Remotely Operated Vehicle (ROV) research on its propulsion has been carried out. The entire project was supported by CFD and FEM calculations, which taking into account the characteristics of underwater vehicle. One of the tasks was to optimize the semi-open duct for horizontal propellers, which provided propulsion and controllability in horizontal plane. In order to...
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Dynamic model of nuclear power plant turbine
PublikacjaThe paper presents the dynamic multivariable model of Nuclear Power Plant steam turbine. Nature of the processes occurring in a steam turbine causes a task of modeling it very difficult, especially when this model is intended to be used for on-line optimal process control (model based) over wide range of operating conditions caused by changing power demand. Particular property of developed model is that it enables calculations...
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Improving depth maps of plants by using a set of five cameras
PublikacjaObtaining high-quality depth maps and disparity maps with the use of a stereo camera is a challenging task for some kinds of objects. The quality of these maps can be improved by taking advantage of a larger number of cameras. The research on the usage of a set of five cameras to obtain disparity maps is presented. The set consists of a central camera and four side cameras. An algorithm for making disparity maps called multiple...
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Numerical crash analysis of the cable barrier
PublikacjaSafety barriers are used to increase road safety. Their basic task is to prevent the errant vehicle from getting off the road in places which are potentially dangerous for vehicle passengers. Barriers, which are used on European roads, must fulfill the requirements of EN 1317 standards by passing appropriate crash tests. Because of their high cost, numerical simulations are increasingly used to evaluate the properties of safety...
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Exergy analysis of a negative CO2 emission gas power plant based on water oxy-combustion of syngas from sewage sludge gasification and CCS
PublikacjaA power cycle with water-injected oxy-combustion (water cycle) is investigated by exergy analysis. It is fueled with syngas (aka. producer gas) from gasification of sewage sludge. The cycle is equipped with a spray-ejector condenser (SEC). CO2 is separated and compressed for transportation and storage. The net delivered electric power is 31% of the fuel exergy. The task efficiency is 39% when the flue gas bleed to gasification...
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Recent advances in 3D bioprinted tumor models for personalized medicine
PublikacjaCancerous tumors are among the most fatal diseases worldwide, claiming nearly 10 million lives in 2020. Due to their complex and dynamic nature, modeling tumors accurately is a challenging task. Current models suffer from inadequate translation between in vitro and in vivo results, primarily due to the isotropic nature of tumors and their microenvironment's relationship. To address these limitations, hydrogel-based 3D bioprinting...
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Report for the Short Term Scientific Mission within COST Action FP1101: development of the in-field sensor for estimation of fracture toughness and shear strength by measuring cutting forces
PublikacjaKnowledge on the fracture properties of materials is essential to assure structural integrity and proper design of mechanical connections in timber constructions. Measurement of this property is, however, a very challenging task. The linear fracture mechanics is usually used for its assessment assisted with experimental data acquired by means of various techniques, usually of destructive nature. The cutting force is an energetic...
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Optimal control at energy performance index of the mobile robots following dynamically created trajectories
PublikacjaIn practice, the problem of motion control of the wheeled mobile robots is often neglected. Wheeled mobile robots are strongly nonlinear systems and restricted by non-holonomic constraints. Motion control of such systems is not trivial task and usage of non-optimal control signals can lead to deterioration of the overall robot system’s performance. In case of autonomous application of the mobile robots all parts of its control...
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Addressing the Weaknesses of Multi-Criteria Decision-Making Methods using Python
PublikacjaThe 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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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublikacjaBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Multi-Agent Signal Filtering for Electrical Energy Demand Management
PublikacjaConsumers participating in electrical energy Demand Response (DR) programs may be exposed to energy-use related decisions at instants of time which are generally hard to predict. This is especially cumbersome to residential consumers who are less capable of investing in special equipment, or devoting significant time to analyze information and take decisions. To ease residential consumer participation, a multi-agent system proposed...
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Gender approaches to evolutionary multi-objective optimization using pre-selection of criteria
PublikacjaA novel idea to perform evolutionary computations (ECs) for solving highly dimensional multi-objective optimization (MOO) problems is proposed. Following the general idea of evolution, it is proposed that information about gender is used to distinguish between various groups of objectives and identify the (aggregate) nature of optimality of individuals (solutions). This identification is drawn out of the fitness of individuals...
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Expedited Multi-Objective Design Optimization of Miniaturized Microwave Structures Using Physics-Based Surrogates
PublikacjaIn this paper, a methodology for fast multi-objective design optimization of compact microwave circuits is presented. Our approach exploits an equivalent circuit model of the structure under consideration, corrected through implicit and frequency space mapping, then optimized by a multi-objective evolutionary algorithm. The correction/optimization of the surrogate is iterated by design space confinement and segmentation based on...
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Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes
PublikacjaIn this paper, we present a concept of a multi-criteria knowledge-based Recommender System (RS) designed to provide decision support in complex business process (BP) scenarios. The developed approach is based on the knowledge aspects of Stylistic Patterns, Business Sentiment and Decision-Making Logic extracted from the BP unstructured texts. This knowledge serves as an input for a multi-criteria RS algorithm. The output is prediction...
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Rapid multi-objective simulation-driven design of compact microwave circuits
PublikacjaA methodology for rapid multi-objective design of compact microwave circuits is proposed. Our approach exploits point-by-point Pareto set identification using surrogate-based optimization techniques, auxiliary equivalent circuit models, and space mapping as the major model correction method. The proposed technique is illustrated and validated through the design of a compact rat-race coupler. A set of ten designs being trade-offs...
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Multi-layered mineral glass units used as viewport elements of underwater ship structures
PublikacjaIn the paper, Authors deals with viewport elements of underwater marine constructions. If a single-plate viewport constructions are considered, big thicknesses of the glass plate are required to resist the pressure. To build the viewports from the commercially accessible glass panes, multi-layered glass units are proposed in the paper. Numerical calculations are presented, summarized and compared with experimental tests. Focusing...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Multi-Objective Design Optimization of Compact Quasi-Isotropic Dielectric Resonator Antenna
PublikacjaMulti-objective optimization of a quasi-isotropic dielectric resonator antenna (DRA) is presented. Utilization of variable-fidelity electromagnetic (EM) DRA models, response surface approximations, and response correction techniques, allows us to obtain—at a low computational cost—a set of alternative antenna designs representing the best possible trade-offs between three conflicting objectives: antenna size, its reflection response,...
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Mariusz Jaczewski dr inż.
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The convergence of gender wage differences - myth or fact - multi country multi sector analysis
PublikacjaThe Becker’s theory of discrimination predicts that in the long run the gender wage differences should disappear. In our empirical analysis we verify the testable implications of this mode considering the hypothesis of gender wage gap convergence. The study takes into account 31 sectors in 13 European countries for the period between 1970 and 2005. We distinguish between wages paid to different groups of workers classified according...
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O-43 Data-driven selection of active iEEG channels during verbal memory task performance
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Enabling a Stable High-Power Lithium-Bromine Flow Battery Using Task-Specific Ionic Liquids
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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublikacjaAchieving compact size has emerged as a key consideration in modern microwave design. While structural miniaturization can be accomplished through judicious circuit architecture selection, precise parameter tuning is equally vital to minimize physical dimensions while meeting stringent performance requirements for electrical characteristics. Due to the intricate nature of compact structures, global optimization is recommended,...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublikacjaDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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Multi-objective optimization of water quality, pumps operation, and storage sizing of water distribution systems
PublikacjaA multi-objective methodology utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) linked to EPANET for trading-off pumping costs, water quality, and tanks sizing of water distribution systems is developed and demonstrated. The model integrates variable speed pumps for modeling the pumps operation, two water quality objectives (one based on chlorine disinfectant concentrations and one on water age), and tanks sizing cost...
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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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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Rapid multi-objective design optimization of miniaturized impedance transformer by Pareto front exploration
PublikacjaFast multi-objective optimization of compact impedance transformer is discussed. A set of alternative designs representing possible trade-offs between conflicting design criteria, i.e., electrical performance (here, wideband matching) and the structure size, is obtained through Pareto front exploration by means of surrogate-assisted methods.
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Cost-efficient multi-objective design optimization of antennas in highly-dimensional parameter spaces
PublikacjaMulti-objective optimization of antenna structures in highly-dimensional parameter spaces is investigated. For expedited design, variable-fidelity EM simulations and domain patching algorithm are utilized. The results obtained for a monopole antenna with 13 geometry parameters are compared with surrogate-assisted optimization involving response surface approximation modeling.
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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IEEE Transactions on Molecular, Biological, and Multi-Scale Communications
Czasopisma -
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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Connectivity in Multi-Interface Networks
PublikacjaRozważano zagadnienie minimalizacji energii w sieciach bezprzewodowych bez infrastruktury, w których niektóre węzły są wyposażone w więcej, niż jeden interfejs. W przyjętym modelu sieci podano nowe algorytmy przybliżone oraz wyniki dotyczące złożoności obliczeniowej dla problemu najtańszej spójnej podsieci spinającej.
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The Workshop on Multi-Phase Flows
PublikacjaPrzedstawiono ideę warsztatów ''Modelowanie przepływów wielofazowych w układach termochemicznych'' - organizowanych corocznie - od 2000 roku, przez Podsekcję Przepływów Wielofazowych Komitetu Mechaniki PAN. Omówiono tematykę VI Warsztatów, które były poświęcone głównie metodom eksperymentalnym.
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Note on universal algoritms for learning theory
PublikacjaW 2001 Cucker i Smale zaproponowali nowe podejście do teorii uczenia się w oparciu o problematykę teorii aproksymacji.W 2005 i 2007 Bivev, Cohen, Dahmen, DeVore i Temlyakov opublikowali dwie prace z teorii uczenia się. W omawianej publikacji uogólniliśmy ich rezultaty jednocześnie upraszczając dowody.
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A consensus-based approach to the distributed learning
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Prototype selection algorithms for distributed learning
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An agent-based framework for distributed learning
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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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Some aspects of blended-learning education
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