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Wyniki wyszukiwania dla: multi-task learning
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublikacjaWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Approximate Criteria for the Evaluation of Truly Multi-Dimensional Optimization Problems
PublikacjaIn this paper we propose new improved approximate quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO). In the performed comparative study we take into account the various EMO algorithms of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces. It is well known that useful executive criteria, such as those based on the true Pareto...
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublikacjaThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Investigation of Narrow Electrostatic Precipitator with Wire Multi-Electrode
PublikacjaDiesel engines emit fine particles, which are harmful to human and animal health. There are several methods for decrease particulate emission from a diesel engines, but up to now, these methods are notenough effective or very expensive. An electrostatic precipitation was proposed as an alternative method for control of a diesel particulate emission. Therefore, narrow electrostatic precipitators (ESPs) have become a subject of interest...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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RESIDENTIAL FUNCTION IN MULTI-CRITERIA MULTIFUNCTIONAL BUILDING SYSTEM DESIGN PROCESS
PublikacjaThe paper presents the multi-criteria approach in the design process of residential structure as a part of a multifunctional building system. The purpose of work was to broaden the field of multifunctional building system design process. Background for the presented work is to define the direction of architectural growth of the modern city center area where actually are built complex and large capacity structures with a great impact...
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A Generalized SDP Multi-Objective Optimization Method for EM-Based Microwave Device Design
PublikacjaIn this article, a generalized sequential domain patching (GSDP) method for efficient multi-objective optimization based on electromagnetics (EM) simulation is proposed. The GSDP method allowing fast searching for Pareto fronts for two and three objectives is elaborated in detail in this paper. The GSDP method is compared with the NSGA-II method using multi-objective problems in the DTLZ series, and the results show the GSDP method...
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Collaborative development model and strategies of multi-energy industry clusters: Multi-indicators analysis affecting the development of coastal energy clusters
PublikacjaThe paper explores Coastal Energy-Based Industrial Clusters (EBICs) and their role in advancing energy efficiency and sustainability through collaborative innovation. Economic growth theory and energy sustainability have been introduced into industrial clusters to illustrate indicators that have a greater impact on the development of EBICs. This paper proposes an EBICs development model based on the Cobb-Douglas function, in which...
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Multi-factor fuzzy sets decision system forecasting consumer insolvency risk
PublikacjaThe objective of this study is to develop a multi-factor decision system predicting insolvency risk for natural persons with the use of fuzzy sets. Considering that the financial situation of households is affected by various endogenous and exogenous factors, the main assumption of this study is that the system for predicting financial difficulties should not be limited to the use of only a few financial variables concerning consumers,...
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Optimizing Control by Robustly Feasible Model Predictive Control and Application to Drinking Water Distribution Systems
PublikacjaThe paper considers optimizing Model Predictive Control (MPC) for nonlinear plants with output constraints under uncertainties. Although the MPC technology can handle the constraints in the model by solving constraint model based optimization task, satisfying the plant output constraints still remains a challenge. The paper proposes Robustly Feasible MPC (RFMPC), which achieves feasibility of the outputs in the controlled plant....
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Hybrid Finite Element Method Development for Offshore Structures’ Calculation with the Implementation of Industry Standards
PublikacjaIn the design process of offshore steel structures, it is typical to employ commercial calculation codes in which simulationand evaluation of results are performed on the basis of the available standards (e.g. API, DNV, Lloyds). The modelingand solution rely on finite element methods and cover the simulation of the structure’s properties along with the influenceof the marine environment – sea currents, wave...
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On the Modern and Postmodern Paradigms of Ideology and Social Criticism
PublikacjaThe article takes on the problem of ideology, critical consciousness and social criticism and distinguishes two ways of thematizing it. The first approach is developed within the post-Hegelian framework. According to this paradigm, critique of ideology is a means of transgressing the antagonistic forms of socialization and emancipating humanity from the false forms of consciousness and corresponding irrational and oppressive social...
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Nonlinear Fuzzy Control System for Dissolved Oxygen with Aeration System in Sequencing Batch Reactor
PublikacjaBiological processes at a wastewater treatment plant are complex, multivariable, time varying and nonlinear. Moreover, interactions between the components are very strong. Control of dissolved oxygen is one of most important task at the plant. The level of dissolved oxygen in aerobic tanks has significant influence on behaviour and activity of microorganisms at the plant. Air for aerated tanks is supplied by the aeration system...
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A design framework and a digital toolset supporting the early-stage explorations of responsive kinetic building skin concepts
PublikacjaIn this paper we present the first phase of our research on the development of a framework for early-stage responsive kinetic building skin design. The aims of this study were: to formulate a methodological and instrumental basis for the construction of the framework, to conduct an initial pre-assessment of its features, and finally to provide the first example of how the framework could be applied in practice. Importantly, at...
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Attitudes towards Collaboration in Multicultural Teams in the opinion of Polish and Chinese Students
PublikacjaThe main goal of this paper is to present results of research that addresses the issue of attitudes towards working in both multicultural and single culture teams among Polish and Chinese students. The relationship between those attitudes and factors that includes individual experiences of research participants as well as characteristics of team tasks was analyzed. The research was conducted with students of one Polish and one...
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Constructing a map of an anonymous graph: applications of universal sequences
PublikacjaWe study the problem of mapping an unknown environmentrepresented as an unlabelled undirected graph. A robot (or automaton)starting at a single vertex of the graph G has to traverse the graph and return to its starting point building a map of the graph in the process. We are interested in the cost of achieving this task (whenever possible) in terms of the number of edge traversal made by the robot. Another optimization criteria...
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Building a Nest by an Automaton
PublikacjaA robot modeled as a deterministic finite automaton has to build a structure from material available to it. The robot navigates in the infinite oriented grid $Z x Z$. Some cells of the grid are full (contain a brick) and others are empty. The subgraph of the grid induced by full cells, called the {\em field}, is initially connected. The (Manhattan) distance between the farthest cells of the field is called its {\em span}. The robot...
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MnxCo3-xO4 spinel oxides as efficient oxygen evolution reaction catalysts in alkaline media
PublikacjaThe design of efficient electrocatalysts for oxygen evolution reaction (OER) is an essential task in developing sustainable water splitting technology for the production of hydrogen. In this work, manganese cobalt spinel oxides with a general formula of MnxCo3-xO4 (x=0, 0.5, 1, 1.5, 2) were synthesised via a soft chemistry method. Non-equilibrium mixed powder compositions were produced, resulting in high electrocatalytic activity....
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Just look at to open it up: A biometric verification facility for password autofill to protect electronic documents
PublikacjaElectronic documents constitute specific units of information, and protecting them against unauthorized access is a challenging task. This is because a password protected document may be stolen from its host computer or intercepted while on transfer and exposed to unlimited offline attacks. The key issue is, therefore, making document passwords hard to crack. We propose to augment a common text password authentication interface...
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Theoretical and Actual Feed Per Tooth During Wood Sawing on an Optimizing Cross-Cut Saw
PublikacjaThe work presents the geometries of circular saw teeth, whose task is to divide the cross-cut of the cutting layer. For efficient machining on a cross-cut saw with high feed speed values (about 1 ms−1) maximal theoretical feeds per tooth are determined. These values were compared with the actual values determined during transverse cutting of pine wood on a special test stands in industrial conditions. In the experiment the rotational...
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On topology optimization of large deformation contact-aided shape morphing compliant mechanisms
PublikacjaA topology optimization approach for designing large deformation contact-aided shape morphing compliant mechanisms is presented. Such mechanisms can be used in varying operating conditions. Design domains are described by regular hexagonal elements. Negative circular masks are employed to perform dual task, i.e., to decide material states of each element and also, to generate rigid contact surfaces. Each mask is characterized by...
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On EM-driven size reduction of antenna structures with explicit constraint handling
PublikacjaSimulation-driven miniaturization of antenna components is a challenging task mainly due to the presence of expensive constraints, evaluation of which involves full-wave electromagnetic (EM) analysis. The recommended approach is implicit constraint handling using penalty functions, which, however, requires a meticulous selection of penalty coefficients, instrumental in ensuring optimization process reliability. This paper proposes...
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Compact global association based adaptive routing framework for personnel behavior understanding
PublikacjaPersonnel behavior understanding under complex scenarios is a challenging task for computer vision. This paper proposes a novel Compact model, which we refer to as CGARPN that incorporates with Global Association relevance and Adaptive Routing Pose estimation Network. Our framework firstly introduces CGAN backbone to facilitate the feature representation by compressing the kernel parameter space compared with typical algorithms,...
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Experimental validation of pressure drop models during flow boiling of R134a – effect of flow acceleration and entrainment
PublikacjaA crucial step to assure proficient work of power and process apparatus is their proper design. A wide array of those devices operates within boiling or condensation of the working fluid to benefit from high heat transfer rates. Two-phase flows are associated with high heat transfer coefficients because of the latent heat of evaporation and high turbulence level between the liquid and the solid surface. Predicting heat transfer...
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Using River Formation Dynamics Algorithm in Mobile Robot Navigation
PublikacjaRiver Formation Dynamics is a heuristic optimization algorithm based on the manner, in which drops of water form the river bed. The idea is to imitate the movement of drops on the edges between given nodes thus performing a search based on their height, which is modified through the mechanism of soil erosion and sediment deposition. In this way decreasing gradients are constructed, and these are followed by subsequent drops to...
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Determination of Mechanical Energy Loss in Steady Flow by Means of Dissipation Power
PublikacjaWhen systems of simple geometry like pipes or regular channels are considered, the mechan- ical energy loss of the fluid flow can be expressed by local and longitudinal empirical energy loss coefficients. However, in the case of large spatially distributed objects, there are no simple approaches to this task. In practice, general recommendations addressing different types of objects are used, but they usually provide very coarse...
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Can Evaluation Patterns Enable End Users to Evaluate the Quality of an e-learning System? An Exploratory Study.
PublikacjaThis paper presents the results of an exploratory study whose main aim is to verify if the Pattern-Based (PB) inspection technique enables end users to perform reliable evaluation of e-learning systems in real work-related settings. The study involved 13 Polish and Italian participants, who did not have an HCI background, but used e-learning platforms for didactic and/or administrative purposes. The study revealed that the participants...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublikacjaLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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Computationally Efficient Multi-Objective Optimization of and Experimental Validation of Yagi-Uda Antenna
PublikacjaIn this paper, computationally efficient multi-objective optimization of antenna structures is discussed. As a design case, we consider a multi-parameter planar Yagi-Uda antenna structure, featuring a driven element, three directors, and a feeding structure. Direct optimization of the high-fidelity electromagnetic (EM) antenna model is prohibitive in computational terms. Instead, our design methodology exploits response surface...
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Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation
PublikacjaMulti-objective optimization yields indispensable information about the best possible design trade-offs of an antenna structure, yet it is challenging if full-wave electromagnetic (EM) analysis is utilized for performance evaluation. The latter is a necessity for majority of contemporary antennas as it is the only way of achieving acceptable modeling accuracy. In this paper, a procedure for accelerated multi-objective design of...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Deep Learning Approaches in Histopathology
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e-Learning in Tourism Education
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Online Learning Based on Prototypes
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Distributed Learning with Data Reduction
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Remote learning among students with and without reading difficulties during the initial stages of the COVID-19 pandemic
PublikacjaThis article presents the results of a survey on yet under-researched aspects of remote learning and learning difficulties in higher education during the initial stage (March – June 2020) of the COVID-19 pandemic. A total of 2182 students from University of Warsaw in Poland completed a two-part questionnaire regarding academic achievements in the academic year 2019/2020, living conditions and stress related to learning and pandemic,...
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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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Learning & Memory
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Adult Learning
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Open Learning
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For the Learning of Mathematics
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Teaching & Learning
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Vocations and Learning
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