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Wyniki wyszukiwania dla: deep learning, genetic algorithm, artificial neural networks, predictive maintenance, cost efficient maintenance
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Reduced-Cost Microwave Modeling Using Constrained Domains and Dimensionality Reduction
PublikacjaDevelopment of modern microwave devices largely exploits full-wave electromagnetic (EM) simulations. Yet, simulation-driven design may be problematic due to the incurred CPU expenses. Addressing the high-cost issues stimulated the development of surrogate modeling methods. Among them, data-driven techniques seem to be the most widespread owing to their flexibility and accessibility. Nonetheless, applicability of approximation-based...
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The distributed model predictive controller for the nuclear power plant turbo-generator set
PublikacjaTypically there are two main control loops with PI controllers operating at each turbo-generator set. In this paper a distributed model predictive controller DMPC, with local QDMC controllers for the turbine generator, is proposed instead of a typical PI controllers. The local QDMC controllers utilize step-response models for the controlled system components. These models parameters are determined based on the proposed black-box...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Chromatic cost coloring of weighted bipartite graphs
PublikacjaGiven a graph G and a sequence of color costs C, the Cost Coloring optimization problem consists in finding a coloring of G with the smallest total cost with respect to C. We present an analysis of this problem with respect to weighted bipartite graphs. We specify for which finite sequences of color costs the problem is NP-hard and we present an exact polynomial algorithm for the other finite sequences. These results are then extended...
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Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
PublikacjaThis study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company’s financial security using only economic indicators—as suggested in the existing literature—would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting...
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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublikacjaPredictive current control algorithms for permanent magnet synchronous (PMSM) drives rely on an assumption that within short intervals motor currents can be approximated with linear functions. This approximation may result either from discretizing the motor model or from simplifications applied to the continuous-time model. As the linear current approximation has been recognized as inaccurate in case when the drive operates with...
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Evolutionary algorithm and decisional DNA for multiple travelling salesman problem
PublikacjaIn the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization...
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Lifelong Learning Idea in Architectural Education
PublikacjaThe recent advances in IT and technology are forcing changes in the approach to educating society. In the 20th century, life-long learning was understood as educating adults in order to improve their occupational qualifications. Life-long learning allows the needs of the present-day world to be addressed through providing the individual with education at every stage of his/her life various forms. The search for a new model...
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublikacjaOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Topology recognition and leader election in colored networks
PublikacjaTopology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with...
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Adaptive Algorithm for Interactive Question-based Search
PublikacjaPopular web search engines tend to improve the relevanceof their result pages, but the search is still keyword-oriented and far from "understanding" the queries' meaning. In the article we propose an interactive question-based search algorithm that might come up helpful for identifying users' intents. We describe the algorithm implemented in a form of a questions game. The stress is put mainly on the most critical aspect of this...
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Modelling changes in the energy efficiency of buildings using neural networks on the example of Zielona Góra
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Clonal selection algorithm for vehicle routing
PublikacjaOver the years several successful computing techniques have been inspired by biological mechanisms. Studies of the mechanisms that allow the immune systems of vertebratesto adapt and learn have resulted in a class of algorithms called artificial immune systems. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents...
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublikacjaResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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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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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Capacity efficient shared protection and fast restoration scheme in self-configured optical networks
PublikacjaW artykule zaproponowano nową koncepcję optymalizacji rozdziału zasobów dla przeżywalnych sieci rozległych, która gwarantuje szybkie odtwarzanie usług po wystąpieniu awarii. Wykazano, iż proponowany algorytm, wykorzystujący ideę wierzchołkowego kolorowania grafów, nie powoduje wydłużania ścieżek zabezpieczających - zjawiska charakterystycznego dla powszechnie stosowanych algorytmów optymalizacji. Udowodniono, iż powyższa cecha...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublikacjaPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublikacjaMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublikacjaIn this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublikacjaSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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MANAGING LEARNING PROCESS WITH E-LEARNING TOOL
PublikacjaThis article presents one possibility to employ Moodle, the free e-Leaning platform, to organize learning understood as a process. Behavioral approach and application to massive courses are assumed. A case study is presented, where the introduction of Moodle resulted in better student performance in homework
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Controlling computer by lip gestures employing neural network
PublikacjaResults of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Photosensitization of TiO2 and SnO2 by Artificial Self-Assembling Mimics of the Natural Chlorosomal Bacteriochlorophylls
PublikacjaOf all known photosynthetic organisms, the green sulfur bacteria are able to survive under the lowest illumination conditions due to highly efficient photon management and exciton transport enabled by their special organelles, the chlorosomes, which consist mainly of self-assembled bacteriochlorophyll c, d, or e molecules. A challenging task is to mimic the principle of self-assembling chromophores in artificial light-harvesting...
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Application of deep eutectic solvents in bioanalysis
PublikacjaThe application of deep eutectic solvents (DESs) is sharply surging as a green alternative to conventional solvents due to their unique properties in terms of simplicity of preparation, designability and low cost. A great deal of attention has been paid to the application of these green solvents in analytical chemistry in recent years, and a lot of interesting work has been reported. This review summarizes the most relevant applications...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublikacjaIn this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...
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A predictive estimation based control strategy for a quasi-resonant dc-link inverter
PublikacjaIn this paper the predictive estimation based control strategy for a quasi-resonant dc link inverter (PQRDCLI) is developed. Instead of direct measurement of dc link input inverter current – its estimation with one step prediction is applied. The PQRDCLI fed induction motor, controlled with a predictive current estimation stabilized inverter output voltage slopes independently of load. Moreover, reduction of overvoltage spikes...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublikacjaA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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How Much Does an e-Vote Cost? Cost Comparison per Vote in Multichannel Elections in Estonia
PublikacjaWe are presenting the results of the CoDE project in this paper, where we investigate the costs per vote of different voting channels in Estonian Local Elections (2017). The elections analyzed involve different processes for casting a vote: Early Voting at County Centers, Advance Voting at County Centers, Advance Voting at Ordinary Voting District Committees, Electronic Voting, Election Day Voting, and Home Voting. Our analysis...
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Genetic and biochemical determinants of serum concentrations of monocyte chemoattractant protein-1, a potential neural tube defect risk factor
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Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic
PublikacjaThe national curricula of the EU member states are structured around learning outcomes, selected according to Bloom’s Taxonomy. The authors of this paper claim that using Bloom’s Taxonomy to phrase learning outcomes in medical education in terms of students’ achievements is difficult and unclear. This paper presents an efficient method of assessing course learning outcomes using Fuzzy Logic.
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Genetic predisposition to inflammatory bowel disease
PublikacjaInflammatory bowel disease (IBD) is a chronic, incurable inflammatory disease of the digestive system. The two main disease entities included in the IBD are ulcerative colitis and Crohn's disease. According to epidemiological studies there are more and more new cases every year. In especially among the youngest patients with symptoms of malnutrition and growth inhibition to land up in hospitalwith cancer suspected. The purpose...
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Patch size setup and performance/cost trade-offs in multi-objective EM-driven antenna optimization using sequential domain patching
PublikacjaPurpose This paper aims to assess control parameter setup and its effect on computational cost and performance of deterministic procedures for multi-objective design optimization of expensive simulation models of antenna structures. Design/methodology/approach A deterministic algorithm for cost-efficient multi-objective optimization of antenna structures has been assessed. The algorithm constructs a patch connecting extreme Pareto-optimal...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Blended Learning Model for Computer Techniques for Students of Architecture
PublikacjaAbstract: The article summarizes two-year experience of implementing hybrid formula for teaching Computer Techniques at the Faculty of Architecture at the Gdansk University of Technology. Original educational e-materials, consisting of video clips, text and graphics instructions, as well as links to online resources are embedded in the university e-learning educational platform. The author discusses technical constraints associated...
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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublikacjaModern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublikacjaThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Edge-Computing based Secure E-learning Platforms
PublikacjaImplementation of Information and Communication Technologies (ICT) in E-Learning environments have brought up dramatic changes in the current educational sector. Distance learning, online learning, and networked learning are few examples that promote educational interaction between students, lecturers and learning communities. Although being an efficient form of real learning resource, online electronic resources are subject to...
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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