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Quality evaluation of computer aided information retrieval from machine typed paper documents
PublicationCelem 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 for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-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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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs 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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Design specification management with automated decision-making for reliable optimization of miniaturized microwave components
PublicationThe 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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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublicationIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince 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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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording 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
PublicationCirculating 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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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper 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
PublicationProper 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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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany 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 Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Speed Observer Structure of Induction Machine Based on Sliding Super-Twisting and Backstepping Techniques
PublicationThis paper presents an analysis of the two speed observer structures which are based on the backstepping and sliding super twisting approach. The observer stabilizing functions result from the Lyapunov theorem. To obtain the observer tuning gains the observer structure is linearized near the equilibrium point. The rotor angular speed is obtained from non-adaptive dependence. In the sensorless control system structure the classical...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue 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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Problems associated with the up of actuating system of a single-disc lapping machine for flat surfaces
PublicationPrzedstawiono 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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Mechanical Behavior of Plastic Strips-Reinforced Expansive Soils Stabilized with Waste Marble Dust
PublicationExpansive 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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Non-Adaptive Rotor Speed Estimation of Induction Machine in an Adaptive Full-Order Observer
PublicationIn the sensorless control system of an induction machine, the rotor speed value is not measured but reconstructed by an observer structure. The rotor speed value can be reconstructed by the classical adaptive law with the integrator. The second approach, which is the main contribution of this paper, is the non-adaptive structure without an integrator. The proposed method of the rotor speed reconstruction is based on an algebraic...
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Speed observer of induction machine based on backstepping and sliding mode for low‐speed operation
PublicationThis paper presents a speed observer design based on backstepping and slidingmode approaches. The inputs to the observer are the stator current and thevoltage vector components. This observer structure is extended to the integra-tors. The observer stabilizing functions contain the appropriate sliding surfaceswhich result from the Lyapunov function. The rotor angular speed is obtainedfrom the non‐adaptive formula with a sliding...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Implication of the disulfide bridge in trypsin inhibitor SFTI-1 in its interaction with serine proteinases
PublicationFourteen 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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Techniki szybkiego prototypowania w budowie maszyn = Rapid prototyping techniques in machine building
PublicationW 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
PublicationThe 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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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublicationThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Polymeric Bearings as a new base isolation system suitable for mitigating machine-induced vibrations
PublicationThe present paper summarizes the preliminary results of the experimental shaking table investigation conducted in order to verify the effectiveness of a new base isolation system consisting of Polymeric Bearings in reducing strong horizontal machine-induced vibrations. Polymeric Bearing considered in the present study is a prototype base isolation system, which was constructed with the use of a specially prepared flexible polymer...
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The forecasts-based instrument rule and decision making. How closely interlinked? The case of Sweden
PublicationResearch 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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Designing Aggregate KPIs as a Method of Implementing Decision-Making Processes in the Management of Smart Cities
PublicationThe 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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A framework estimating the minimum sample size and margin of error for maritime quantitative risk analysis
PublicationThe 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
PublicationCatheter-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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How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends
PublicationIllegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....
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What Triggers Us to Be Involved in Martial Arts? Relationships between Motivations and Gender, Age and Training Experience
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Comparison of ANN Classifier to the Neuro-Fuzzy System for Collusion Detection in the Tender Procedures of Road Construction Sector
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HYDRAULIC CONDUCTIVITY OF COAL MINE TAILINGS
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Acoustic Processor of the Mine Countermeasure Sonar
PublicationThis paper presents the concept of an acoustic processor of the mine countermeasure sonar. Developed at the Department of Marine Electronics Systems, Gdansk University of Technology, the acoustic processor is an element of the MG-89, an underwater acoustic station. The focus of the article is on the modules of the processor. They are responsible for sampling analogue signals and implementing the algorithms controlling the measurement...
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Selection of the tunnel thuster main parameters.
PublicationPrzedstawiono przegląd podstawowych odmian konstrukcyjnych sterów strumieniowych urządzeń zalecanych przez producentów. Z uwagi na znaczne różnice wartości otrzymywane z wymienionych metod, zamieszczono także wyniki analizy statystycznej sterów strumieniowych zastosowanych na statkach zbudowanych w Stoczni Gdynia w latach1995-2002. Porównanie wyników poszczególnych metod z parametrami sterów zastosowanych na wymienionych...
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The main developments of the CSR initiatives in Poland
PublicationThis short paper outlines the most important documents and initiatives that have appeared in the subject throughout the years within the international institutions, such as United Nations or European Union. It also discusses the ways in which the international CSR initiatives are being incorporated into Polish legislative and organizational system, by providing an outline of the biggest and most active organizations and foundations...
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Monocyte Chemoattractant Protein-Induced Protein 1 (MCPIP1) Enhances Angiogenic and Cardiomyogenic Potential of Murine Bone Marrow-Derived Mesenchymal Stem Cells
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Enhancement of PUR/PIR foam thermal stability after addition of Zostera marina biomass component investigated via thermal analysis and isoconversional kinetics
PublicationIn the present work, a thorough thermogravimetric (TG) analysis of bio-based polyurethane–polyisocyanurate (PUR–PIR) foams in both nitrogen and oxygen atmosphere is performed. A sustainable element of the foam is a biopolyol obtained via acid-catalyzed liquefaction of Zostera marina and Enteromorpha Algae biomass. Based on isoconversional analysis and apparent activation energies, several conclusions are obtained. In contradiction...
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Amine–alkyl derivatives of hydantoin: New tool to combat resistant bacteria
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Studies of complexation of metal cations by tris(3,6-dioxaheptyl)amine in solution
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Amine-Based Ionic Liquid for CO2 Capture and Electrochemical or Thermal Regeneration
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Moisture damage mechanism and material selection of HMA with amine antistripping agent
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DNA repair is responsible for the presence of oxidatively damaged DNA lesions in urine
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Procedure of determination of volatile trihalomethanes in human urine with pervaporation and gas chromatography
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Calix[4]arene-Thioamides as Ionophores for Transition and Heavy Metal Cations.
PublicationPochodne kaliks[4]arenów odgrywają ważną rolę jako materiał aktywny w membranowych elektrodach jonoselektywnych. Obecnie duży nacisk kładzie się na kontrolę stężeń kationów metali ciężkich, takich jak Pb, Cd, Hg, Cu w wodach naturalnych. Naszym zadaniem było zaprojektować i zsyntezować ligandy, które wykazują zdolność do wiązania kationów metali ciężkich i przejściowych. Synteza, struktury krystaliczne, ekstrakcja i właściwości...
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Calix[4]arene-Thioamides as Ionophores for Transition and Heavy Metal cations
PublicationCalix[4]arene derivatives play an important role as sensing materials in Ion Selective Electrodes(ISEs). Nowadays a high impact is put to control in natural waters the level of toxic heavy metals, like Pb ,Cd, Hg or Cu which may cause the great risk to human health. Our goal was to design and to synthesize ligands possessing ability to bind transition and heavy metal cations. The synthesis, crystal structures,extractive and ionophoric...
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Effect of treating method on the physicochemical properties of amine-functionalized carbon nanotubes
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Effect of treated swimming pool water on the levels of trihalomethanes in swimmer's urine
PublicationBaseny są uważane za pierwotne źródło publicznego narażenia na trihalometany, między innymi chloroform (ma zastosowanie w dezynfekcji, a wysokie stężenia chloru są łatwo wyczuwalne zapachem). Celem badania był równoczesny przymiar poziomów THM w próbkach moczu i krwi pływaków jak również w wodzie basenowej (z miejskiego i uniwersyteckiego basenu), w celu zbadania związku między obecnością tych związków w różnych matrycach. Lotne...
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Procedure of determination of volatile trihalomethanes in human urine with perwaporation and gas chromatography
PublicationPraca przedstawia wyznaczanie podstawowych parametrów walidacyjnych nowej procedury oznaczania lotnych związków chlorowcoorganicznych z grupy trihalometanów w próbkach moczu ludzkiego, opartej na zastosowaniu:- techniki perwaporacji na etapie izolacji i wzbogacania analitów;- bezpośredniego dozowania próbek ekstraktów (permeatu) do kolumny chromatograficznej;- chromatograficznego rozdzielanie mieszaniny na poszczególne składniki;-wykorzystaniu...