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Optimal selection of the sawdust separation device for a narrow-kerf sawing machine PRW15-M
PublikacjaW pracy przedstawiono granulometryczną analizę rozkładu wiórów i pyłu drzewnego otrzymanego w procesie przecinania suchych pryzm sosnowych na pilarce ramowej wielopiłowej PRW15-M. Wielkości wiórów mieściły się w granicach od 84,7 μm do nawet 14 mm. Te ostatnie są elementami będącymi efektem rozszczepiania dolnej powierzchni pryzmy przez wychodzące z niej ostrza piły. Większośc wiórów z najmniejszych frakcji ma postać sześciennych...
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Quality evaluation of computer aided information retrieval from machine typed paper documents
PublikacjaCelem międzynarodowego projektu memorial jest wspomagane komputerowo rozpoznawanie maszynopisów. Referat prezentuje zagadnienie pomiaru jakości takiego procesu. Wskazano w nim potencjalne miejsca pojawiania się błędów oraz przedstawiono i sklasyfikowano odpowiednie miary.
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Pareto Optimal Decisions in Multi-Criteria Decision Making Explained with Construction Cost Cases
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Martini 3 Model of Cellulose Microfibrils: On the Route to Capture Large Conformational Changes of Polysaccharides
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Local advisory councils in deliberative decision-making. Findings from research in Polish cities
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Analyzing the relationship between sound, color, and emotion based on subjective and machine-learning approaches
PublikacjaThe aim of the research is to analyze the relationship between sound, color, and emotion. For this purpose, a survey application was prepared, enabling the assignment of a color to a given speaker’s/singer’s voice recordings. Subjective tests were then conducted, enabling the respondents to assign colors to voice/singing samples. In addition, a database of voice/singing recordings of people speaking in a natural way and with expressed...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublikacjaAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublikacjaFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
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Comparative studies of manufacturing strategies within multi-machine production systems using simulation
PublikacjaZaprezentowano metodykę budowy struktur przestrzennych systemów produkcji typu gniazdowego wg zasad technologii grupowej, wykorzystując zaproponowane modele i algorytmy analizy zbiorów/relacji rozmytych. Generowane, z wykorzystaniem tych algorytmów, przebiegi procesów porównywano z przebiegami procesów w strukturach przestrzennych typu hybrydowego, tj. o wspólnych zasobach. Odnosząc się do zdefiniowanego studium przypadku, wykazano...
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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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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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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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Mechanical Behavior of Plastic Strips-Reinforced Expansive Soils Stabilized with Waste Marble Dust
PublikacjaExpansive soil needs to undergo treatment to be used as safe foundation soil for roads and buildings. From an environmental conservation and economical point of view, the usage of agricultural and industrial wastes is the best option. In this study, the effects of utilizing plastic waste and marble waste dust on the engineering properties of expansive soils were examined. Various laboratory tests were carried out on sampled expansive...
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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...
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A FPTAS for minimizing total completion time in a single machine time-dependent scheduling problem
PublikacjaIn this paper a single machine time-dependent scheduling problem with total completion time criterion is considered. There are given n jobs J1,…,Jn and the processing time pi of the ith job is given by pi=a+bisi, where si is the starting time of the ith job (i=1,…,n),bi is its deterioration rate and a is the common base processing time. If all jobs have deterioration rates different and not smaller than a certain constant u>0,...
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublikacjaIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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A decision-making module for aiding ship system automation design; A knowledge-based approach
PublikacjaZastosowanie elementów sztucznej inteligencji, w tym systemów z bazą wiedzy staje się coraz bardziej powszechne przy komputerowo wspomaganym projektowaniu. Proces projektowy związany jest z wieloma problemami decyzyjnymi, jak: wybór struktury podsystemu, podzespołów czy też elementów składowych. Z tego względu zdecydowano się opracować system z bazą wiedzy z modułem wspirającym proces podejmowania decyzji.W artykule przedstawiono...
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Risk-averse decision-making to maintain supply chain viability under propagated disruptions
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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A framework estimating the minimum sample size and margin of error for maritime quantitative risk analysis
PublikacjaThe average accident frequency is essential for quantitative risk analysis and is conventionally estimated from accident statistics. This paper has systematically synthesised the knowledge on statistical errors and offered the missing instructions, a framework, for determining the minimum sample size and the margin of error (MOE) when calculating the average accident frequency from an accident database at hand. We have applied...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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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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Problems associated with the up of actuating system of a single-disc lapping machine for flat surfaces
PublikacjaPrzedstawiono wyniki badań nagrzewania się podstawowych elementów układu wykonawczego docierarki jednotarczowej o standardowej kinematyce do obróbki powierzchni płaskich. Analizowano przyrost temperatury zespołu napędowego, rolek i pierścieni prowadzących separatory oraz tarczy docierającej i obrabianych elementów. Badano nagrzewanie się układu obróbkowego podczas wyrównywania żeliwnego narzędzia i docierania powierzchni płaskich....
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Design specification management with automated decision-making for reliable optimization of miniaturized microwave components
PublikacjaThe employment of numerical optimization techniques for parameter tuning of microwave components has nowadays become a commonplace. In pursuit of reliability, it is most often carried out at the level of full-wave electromagnetic (EM) simulation models, incurring considerable computational expenses. In the case of miniaturized microstrip circuits, densely arranged layouts with strong cross-coupling effects make EM-driven tuning...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Techniki szybkiego prototypowania w budowie maszyn = Rapid prototyping techniques in machine building
PublikacjaW artykule omówiono przygotowanie oraz wykonanie poszczególnych elementów maszyn za pomocą techniki szybkiego prototypowania. W pierwszej części przedstawiono technologię wydruku przestrzennego oraz właściwości materiału budulcowego. Druga część artykułu została poświęcona przykładowym wydrukom i ich zastosowaniom w maszynach.
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Sensorless control system of induction machine supplied by voltage source inverter with output filter
PublikacjaThe paper focuses on sensorless control of the induction machines supplied by inverter with the output filters. “The novel” idea of the speed observer which is based on the backstepping approach is shown. The standard structure of the exponential observer is extended by the integrators and additional Z vector. The simulation and experimental results validate the proposed solution.
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Implication of the disulfide bridge in trypsin inhibitor SFTI-1 in its interaction with serine proteinases
PublikacjaFourteen monocyclic analogues of trypsin inhibitor SFTI-1 isolated from sunflower seeds were synthesized by the solid-phase method. The purpose of this work was to establish the role of a disulfide bridge present in inhibitor's side chains of Cys3 and Cys11 in association with serine proteinases. This cyclic fragment was replaced by the disulfide bridges formed by L-pencillamine (Pen), homo-L-cysteine (Hcy), N-sulfanylethylglycine...
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3D Machine Vision System for Inspection of Contact Strips in Railway Vehicle Current Collectors
PublikacjaConstruction and technical condition of current collectors is crucial to reliability and safety of railway transportation. According to the Technical Specifications for Interoperability railway vehicles in the European Union should be equipped with carbon contact strips. Excessive wear or defects of contact strips degrade the capability of undisturbed power transmission, cause faster wear of contact wire, and can even result in...
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SSFR Test of Synchronous Machine for Different Saturation Levels using Finite-Element Method
PublikacjaIn this paper the StandStill Frequency Response characteristics (SSFR) of saturated synchronous generator (SG) have been calculated using Finite Element Method (FEM) analysis. In order to validate proposed approach for unsaturated conditions FEM simulation from Flux2D software has been compared with the measurements performed on the 10 kVA, 4- poles synchronous machine ELMOR GCe64a of salient rotor construction, equipped with a...
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Designing Aggregate KPIs as a Method of Implementing Decision-Making Processes in the Management of Smart Cities
PublikacjaThe aim of the paper is to present a concept of measuring the performance of city management processes by use of a concept of aggregate KPIs. In the management of organizations and, as a consequence of the use of a common design framework also in the management of cities, silo KPIs are commonly used to show the statuses of the processes of organizations/cities. Thus the question arises as to what extent aggregate KPIs, as proposed...
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The forecasts-based instrument rule and decision making. How closely interlinked? The case of Sweden
PublikacjaResearch background: The Central Bank of Sweden declared in years 1999–2006 the implementation of the Svensson’s concept of inflation forecast targeting (IFT). It means that the repo rate decision-making process depends on the inflation forecasts. The concept evolved from the strict IFT with the decision-making algorithm called ‘the rule of thumb’ to the flexible IFT. Purpose of the article: The aim of...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Julien Guthmuller prof. dr hab.
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Oleksii Nosko dr hab. inż.
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Journal of Marine Science and Application
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MARINE TECHNOLOGY AND SNAME NEWS
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Michał Czubenko dr inż.
OsobyMichał Czubenko jest wyróżniającym się absolwentem z 2009 roku Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej, specjalizującym się w dyscyplinie automatyka i robotyka. Obecnie pełni funkcję adiunkta w Katedrze Systemów Decyzyjnych i Robotyki tej samej uczelni. W 2012 roku odbył trzymiesięczny staż na Kingston University London, poszerzając swoje horyzonty w tej dziedzinie. Od obrony pracy magisterskiej...
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BMC Medical Informatics and Decision Making
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IEEE Transactions on Human-Machine Systems
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International Journal of Machine Learning and Cybernetics
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Journal of Cognitive Engineering and Decision Making
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International Journal of Management and Decision Making
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International Journal of Machine Learning and Computing
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Margin-Journal of Applied Economic Research
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International Journal of Multicriteria Decision Making
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Decision Making: Applications in Management and Engineering
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