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wszystkich: 604
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Wyniki wyszukiwania dla: MACHINE LEARNING, MUSIC ANALYSIS, TONALITY
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublikacjaShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Comparison of Lithuanian and Polish Consonant Phonemes Based on Acoustic Analysis – Preliminary Results
PublikacjaThe goal of this research is to find a set of acoustic parameters that are related to differences between Polish and Lithuanian language consonants. In order to identify these differences, an acoustic analysis is performed, and the phoneme sounds are described as the vectors of acoustic parameters. Parameters known from the speech domain as well as those from the music information retrieval area are employed. These parameters are...
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Instantaneous power signal measurements for bearing diagnostics
Dane BadawczeBearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous current and voltage power supplied to the engines. Bearing damage causes the appearance of deformations, which are in the form of additional harmonic components...
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Analysis of the instantaneous power signal for bearing diagnostics -bearing damaged
Dane BadawczeThe attached dataset contains the measurement results of the instantaneous values of current and voltage, recorded during the diagnostics of a damaged bearing. Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous...
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Analysis of the instantaneous power signal for bearing diagnostics - bearing undamaged
Dane BadawczeThe attached dataset contains the measurement results of the instantaneous values of current and voltage, recorded during the diagnostics of an undamaged bearing. Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous...
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Separability Assessment of Selected Types of Vehicle-Associated Noise
PublikacjaMusic Information Retrieval (MIR) area as well as development of speech and environmental information recognition techniques brought various tools in-tended for recognizing low-level features of acoustic signals based on a set of calculated parameters. In this study, the MIRtoolbox MATLAB tool, designed for music parameter extraction, is used to obtain a vector of parameters to check whether they are suitable for separation of...
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Bartosz Szostak mgr inż.
OsobyBartosz Szostak w 2019 r. ukończył studia inżynierskie na Politechnice Gdańskiej na kierunku Geodezja i Kartografia. W 2021 r. ukończył studia magisterskie również w dziedzinie Geodezji i Kartografii na Politechnice Gdańskiej. Tematyka jego prac dyplomowych dotyczyła uczenia maszynowego i detekcji obiektów.
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A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine
PublikacjaThe article presents the method for the evaluation of selected manufacturing processes using the analysis of vibration and sound signals. This method is based on the use of sensors installed outside the machining zone, allowing to be used quickly and reliably in real production conditions. The article contains a developed measurement methodology based on the specific location of microphones and vibration transducers mounted on...
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PA32 aluminum alloy - tensile properties
Dane BadawczeIn addition to steel, aluminium alloys are the main building material used in the shipbuilding industry. Due to its undoubted advantages, such as low density (nearly three times lower than in the case of steel for shipbuilding) and high corrosion resistance, it is often used for hulls of yachts and small vessels as well as superstructures. For safety...
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Strucutral steel - tensile test results
Dane BadawczeModern floating structures such as ships, oil platforms and offshore wind towers are built mostly of structural steel. It is a material that is subject to requirements which, when met, allows the construction and safe operation of the structure throughout its entire work cycle. One of the basic criteria that a material must meet is its strength. The...
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Voice command recognition using hybrid genetic algorithm
PublikacjaAbstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...
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Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
PublikacjaThe entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance...
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Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies
PublikacjaThis guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...
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Classification of Polish wines by application of ultra-fast gas chromatography
PublikacjaThe potential of ultra-fast gas chromatography (GC) combined with chemometric analysis for classification of wine originating from Poland according to the variety of grape used for production was investigated. A total of 44 Polish wine samples differing in the type of grape (and grape growth region) used for the production as well as parameters of the fermentation process, alcohol content, sweetness, and others which characterize...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublikacjaBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Uncertainty analysis of measuring system for instantaneous power research
PublikacjaThe paper presents a metrological analysis of the measurement system used for diagnosis of induction motor bearings, based on the analysis of the instantaneous power. This system was implemented as a set of devices with dedicated software installed on a PC. A number of measurements for uncertainty estimation was carried out. The results of the measurements are presented in the paper. The results of the aforementioned analysis helped...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublikacjaNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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Selected Aspects of 3D Printing for Emergency Replacement of Structural Elements
PublikacjaThe paper presents a synthetic characterization of modern methods of manufacturing or regenerating machine elements. Considered methods are machining and additive methods, in particular 3D printing in the FDM/FFF technique. For the study, the authors made samples of the holder bracket using selected methods. Samples made by machining operations, 3D printing with various filling were tested. The paper contains a technical and economic...
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublikacjaThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
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Upper Limb Bionic Orthoses: General Overview and Forecasting Changes
PublikacjaUsing robotics in modern medicine is slowly becoming a common practice. However, there are still important life science fields which are currently devoid of such advanced technology. A noteworthy example of a life sciences field which would benefit from process automation and advanced robotic technology is rehabilitation of the upper limb with the use of an orthosis. Here, we present the state-of-the-art and prospects for development...
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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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Agata Kot-Wasik prof. dr hab. inż.
OsobyAgata Kot-Wasik, urodzona w 1964 r. w Siedlcach (woj. mazowieckie), ukończyła studia magisterskie w 1988 r. na Wydziale Chemicznym Politechniki Gdańskiej, w specjalności Analityka Techniczna i Przemysłowa. W latach 1988–1992 była zatrudniona w Katedrze Chemii Organicznej na macierzystym wydziale na stanowisku naukowo-technicznym. W 1990 r. ukończyła na PG studia podyplomowe „Techniki Instrumentalne w Analizie Śladów i Ochronie...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublikacjaW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wyko-rzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublikacjaThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Alhassan Ali Ahmed
OsobyAlhassan Ali Ahmed BSc of pharmacy, MSc in Bioinformatics and Biotechnology, and currently doing his PhD in Bioinformatics and Machine Learning. Alhassan has considerable experience in the pharmaceutical industry as he worked before in different positions such as; Community pharmacist, Medical advisor, Antibiotics production specialist, Quality assurance specialist, Key account manager for Immunotherapeutic medications, and currently,...
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Social learning and knowledge flows in cluster initiatives, In: Sanz S.C., Blanco F.P., Urzelai B. (Eds). Human and Relational Resources (pp. 44-45). the 4th International Conference on Clusters and Industrial Districts CLUSTERING, University of Valencia, Spain, May 23–24 (ISBN: 978-84-09-11926-4).
PublikacjaPurpose – The purpose of the paper is to explore how learning manifests and knowledge flows in cluster initiatives (CIs) due to interactions undertaken by their members. The paper addresses the research question of how social learning occurs and knowledge flows in CIs. Design/methodology/approach – The qualitative study of four cluster initiatives helped to identify various symptoms of social learning and knowledge flows in...
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How personality traits, sports anxiety, and general imagery could influence the physiological response measured by SCL to imagined situations in sports?
Dane BadawczeThe data were collected to understand how individual differences in personality (e.g. neuroticism), general imagery, and situational sports anxiety are linked to arousal measuring with skin conductance level (SCL) in situational imagery (as scripted for sport-related scenes). Thirty persons participated in the study, aged between 14 and 42 years, with...
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Basic evaluation of limb exercises based on electromyography and classification methods
PublikacjaSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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Expert systems in assessing the construction process safety taking account of the risk of disturbances
PublikacjaThe objective of the paper is to present the issue of safety manage-ment during the construction process. Threats in the form of disturb-ances may occur in the preparatory phase, during the execution of the construction project and also during its operational use. The arti-cle presents the concept of applying the methodology based, among others, on Learning Bayesian Networks, Artificial Neural Networks and Support Vector Machine,...
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Internet photogrammetry as a tool for e-learning
PublikacjaAlong with Internet development, there were interactive applications which allow for remote sensing and photogrammetric analysis. An example of an application that can provide Earth images and make it possible to measure distances in these images is Google Earth. The authors, who have experience from 2001-2015 argue that it is possible and it is important to create more advanced photogrammetric network applications. In this there...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublikacjaTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublikacjaThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
PublikacjaAn innovative tool for modeling the specific flood volume was presented that can be applied to assess the need for stormwater network modernization as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland, were used to apply the model and demonstrate its usefulness. This model extends the capability of recently developed statistical and machine learning hydrodynamic models developed...
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Self-Perceived Personal Brand Equity of Knowledge Workers by Gender in Light of Knowledge-Driven Organizational Culture: Evidence From Poland and the United States
PublikacjaThis study contributes to the limited literature on the personal branding of knowledge workers by revealing that a culture that incorporates knowledge, learning, and collaboration supports (explicit and tacit) knowledge sharing among employees and that sharing matters for knowledge workers’ self-perceived personal brand equity. Analysis of 2,168 cases from the United States and Poland using structural equation modeling (SEM) showed...
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublikacjaAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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Medical Image Dataset Annotation Service (MIDAS)
PublikacjaMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
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Computing methods for fast and precise body surface area estimation of selected body parts
PublikacjaCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
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Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublikacjaThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublikacjaIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Bayesian Optimization for solving high-frequency passive component design problems
PublikacjaIn this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all...
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Analysis of Factors Influencing the Prices of Tourist Offers
PublikacjaTourism is a significant branch of many world economies. Many factors influence the volume of tourist traffic and the prices of trips. There are factors that clearly affect tourism, such as COVID-19. The paper describes the methods of machine learning and process mining that allow for assessing the impact of various factors (micro, mezzo and macro) on the prices of tourist offers. The methods were used on large sets of real data...
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Broken rotor bar impact on sensorless control of induction machine
PublikacjaThe aim of the research is analysis of the sensorless control system of induction machine with broken rotor for diagnostic purposes. Increasing popularity of sensorless controlled variable speed drives requires research in area of reliability, range of stable operation, fault symptoms and application of diagnosis methods. T transformation (Cunha et al.,2003) used for conversion of instantaneous rotor currents electrical circuit...
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The KLC Cultures, Tacit Knowledge, and Trust Contribution to Organizational Intelligence Activation
PublikacjaIn this paper, the authors address a new approach to three organizational, functional cultures: knowledge culture, learning culture, and collaboration culture, named together the KLC cultures. Authors claim that the KLC approach in knowledge-driven organizations must be designed and nourished to leverage knowledge and intellectual capital. It is suggested that they are necessary for simultaneous implementation because no one of...
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Online sound restoration system for digital library applications
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublikacjaSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublikacjaThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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Feedback Control of Multiphase Induction Machines with Backstepping Technique
PublikacjaThe paper presents the control possibility of five phase induction machines. In the proposed solution the machine model vector form is not transformed to the (dq)-coordinate system, that is connected to rotor flux vector, but utilizes the stationary system ( αβ ). Moreover, the nonlinear model linearization is based on demonstrated nonlinear variables transformation for i-orthogonal ( αβ )(n) planes. By introducing the backstepping...
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Buzz-based honeybee colony fingerprint
PublikacjaNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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Deep neural networks for data analysis
Kursy OnlineThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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Herbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE)
Dane BadawczeHerbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE) is a research herbarium encompassing specimens of vascular plants and algae hosted by the Laboratory of Marine Plant Ecology at University of Gdańsk, Poland. The aim of Herbarium is to preserve marine plant and algae collections mostly from the Gulf of Gdańsk, but the herbarium...
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Karol Dziedziul dr hab.
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Method of selecting the LS-SVM algorithm parameters in gas detection process
PublikacjaIn this paper we showed the method of resistive gas sensors data processing. The UV irradiation and temperature modulation was applied to improve gas sensors’ selectivity and sensitivity. Noise voltage across the sensor’s terminals (proportional to its resistance fluctuations) was recorded to estimate power spectral density. This function was an input data vector for LS-SVM (least squares – support vector machine) algorithm, which...
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Technique for reducing erosion in large-scale circulating fluidized bed units
PublikacjaThis paper presents a methodology, implemented for a real industrial-scale circulating fluidized bed boiler, to mitigate the risk of heating surfaces exposed to an intensive particle erosion process. For this purpose, a machine learning algorithm was developed to support the boiler reliability management process. Having a tool that can help mitigate the risk of uncontrolled power unit failure without expensive and technically complex...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublikacjaPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublikacjaFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Remote measurement of building usable floor area - Algorithms fusion
PublikacjaRapid changes that are taking place in the urban environment have significant impact on urban growth. Most cities and urban regions all over the world compete to increase resident and visitor satisfaction. The growing requirements and rapidity of introducing new technologies to all aspects of residents' lives force cities and urban regions to implement "smart cities" concepts in their activities. Real estate is one of the principal...
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Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors
PublikacjaModern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Anna Czaja mgr inż.
OsobyPo ukończeniu studiów magisterskich na kierunku Informatyka (Politechnika Gdańska, Wydział Elektroniki, Telekomunikacji i Informatyki) przez szereg lat pracowała jako programista. Obecnie zatrudniona na stanowisku asystenta w Katedrze Zastosowań Informatyki w Zarządzaniu (Politechnika Gdańska, Wydział Zarządzania i Ekonomii). Uczestniczka studiów doktoranckich III stopnia na wydziale Zarządzania i Ekonomii na Politechnice Gdańskiej....
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Power Hardware-in-the-Loop Approach In Power System Development
PublikacjaThe main objective of the research is the verification of the Power Hardware-In-The-Loop (PHIL) approach in power system analysis and design. The premise of the article is that using PHIL approach the performance of the power system in steady and transient state conditions can be analysed in real power system conditions. Models of induction machine were developed and real time simulations were performed. Simulation variables were...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Pedestrian detection in low-resolution thermal images
PublikacjaOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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Analysis and evaluation of grouping methods for effective cutting tool operation
PublikacjaThis article presents the possibilities for using cluster analysis in the assignment of machine tools in automated manufacturing systems. Based on the similarity of manufacturing processes in the system, cutting tools have been grouped. The objective was to obtain groups of similar objects, which could potentially ensure the reduction of the frequency and time of setups, optimizing the maintenance of tool resources and improving...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublikacjaFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublikacjaSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
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Development and performance analysis of a novel multiphase doubly-fed induction generator
PublikacjaThis paper presents the research into the design and performance analysis of a novel five-phase doubly-fed induction generator (DFIG). The designed DFIG is developed based on standard induction motor components and equipped with a five-phase rotor winding supplied from the five-phase inverter. This approach allows the machine to be both efficient and reliable due to the ability of the five-phase rotor winding to operate during...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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Online sound restoration system for digital library applications.
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Comparative Study of Self-Organizing Maps vs. Subjective Evaluation of Quality of Allophone Pronunciation for Nonnative English Speakers
PublikacjaThe purpose of this study was to apply Self-Organizing Maps to differentiate between the correct and the incorrect allophone pronunciations and to compare the results with subjective evaluation. Recordings of a list of target words, containing selected allophones of English plosive consonants, the velar nasal and the lateral consonant, were made twice. First, the target words were read from the list by 9 non-native speakers and...
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Multimedia services applied to noise and hearing monitoring and measuring
PublikacjaThe goal of this chapter is to show a research study related to processing of data acquired by the multimedia services engineered at the multimedia systems department (MSD) of the Gdansk University of Technology. This concerns a survey on noise threat employing the multimedia noise monitoring system (MNMS) and hearing tests performed by the "I can hear. . . " system. The obtained results of the noise measurements revealed that...
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Wpływ automatycznej kalibracji wizyjnego systemu pozycjonowania na dokładność lokalizacji elementu roboczego
PublikacjaW artykule przedstawiono strukturę i działanie automatycznego wizyjnego systemu pozycjonowania (PVS), który został zainstalowany na maszynie waterjet (WJ). Ponadto przeprowadzono analizę wpływu kalibracji na działanie PVS. Podstawę systemu stanowią dwie kamery internetowe zamontowane na przemysłowej maszynie WJ. W połączeniu z algorytmem identyfikacji, system przeznaczony jest do pozycjonowania WJ z dużą dokładnością. W tym celu...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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An application of blended and collaborative learning in spatial planning course
PublikacjaSpatial Planning is a master course for graduate students of Environmental Engineering. The course is based on assumptions that students’ future work will be connected with spatial planning, and spatial issues will have an influence on their everyday lives. To familiarize students with environmental issues in planning, the teams of students get an assignment to design an urban space, waterfront along a stream. The whole project...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublikacjaOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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Tomasz Edward Berezowski dr inż.
OsobyUrodził się w 1986 r. w Warszawie. Ukończył w 2009r. z wyróżnieniem Międzywydziałowe Studium Ochrony Środowiska SGGW w Warszawie, specjalność Restoration and Management of Environment. Doktorat obronił z wyróżnieniem na Vrije UIniversiteit Brussels w 2015 roku. W latach 2015-2017 pracował jako asystent, a następnie adiunkt na Wydziale Budownictwa i Inżynierii Środowiska SGGW. W roku 2017 został zatrudniony jako adiunkt na Wydziale...
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Wybrane aspekty modelowania uderzenia pojazdem dźwigara wiaduktu
PublikacjaW pracy przedstawiono różne zagadnienia związane z uderzeniem pojazdu w dźwigar wiaduktu. Omówiono wybór modelu obliczeniowego, na podstawie porównania wyników dla modelu dźwigara zespolonego, modelu dźwigara stalowego oraz modelu wiaduktu. Następnie opisano model dźwigara zespolonego zastosowany w analizie MES oraz metodę wyznaczania współczynników tłumienia Rayleigha. Symulację numeryczną uderzenia dźwigara wiaduktu przez koparkę...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublikacjaIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
PublikacjaHypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. Instead, those systems concentrated on collecting features from many retinopathy-related...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublikacjaIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublikacjaThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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Polyarmonic model of synchronous generator for analysis of autonomous power generation systems
PublikacjaAbstract: This paper presents the polyharmonic modelling of synchronous generator (SG) in machine variables. The simple geometry and windings physical layout has been used for inductance calculations of a salient-pole SG. The main advantage of this model is the ease of describing an autonomous power generation system (APGS) in terms of its topology and thus providing effective analysis at the static and dynamic states, both for...
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Residue-Pole Methods for Variability Analysis of S-parameters of Microwave Devices with 3D FEM and Mesh Deformation
PublikacjaThis paper presents a new approach for variability analysis of microwave devices with a high dimension of uncertain parameters. The proposed technique is based on modeling an approximation of system by its poles and residues using several modeling methods, including ordinary kriging, Adaptive Polynomial Chaos (APCE), and Support Vector Machine Regression (SVM). The computational cost is compared with the traditional Monte-Carlo...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublikacjaLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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Hossein Nejatbakhsh Esfahani PhD
OsobySince 2012 when I graduated in master of mechatronics engineering I've been dealing with kinds of control theory problems in both theoretical and practical perspective. I have five years of work experience in industrial automation area in Iran where I was swamped with some industrial-based control algorithms such as PID and MPC algorithms which were adopted to control some processes including steam turbine, gas turbine, casting...
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Investigating Noise Interference on Speech Towards Applying the Lombard Effect Automatically
PublikacjaThe aim of this study is two-fold. First, we perform a series of experiments to examine the interference of different noises on speech processing. For that purpose, we concentrate on the Lombard effect, an involuntary tendency to raise speech level in the presence of background noise. Then, we apply this knowledge to detecting speech with the Lombard effect. This is for preparing a dataset for training a machine learning-based...
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Wave propagation signals in concrete beams under 3-point bending
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. The beams were made of concrete with the following ingredients: CEM I 42.5R (450 kg/m3), water (177 kg/m3), sand 0-2 (675 kg/m3) and gravel 2-8 (675 kg/m3). The bending test was performed using a Zwick/Roell Z10...
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Diploma Seminar (PG_00042079) D&PE 2023 Winter Semester
Kursy OnlinePresentation of the topic, the main issues of the diploma thesis and the tasks of the diploma thesis completed so far. The topic of the presentation is the same as the topic of the diploma thesis. Presentation of a literature analysis, including, among others: 10 papers from journals related to the topic of the work. Submitting to e-learning platform: - pdf version of the presentation - printed description (max 4 pages) a of the...
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Research on Tool Temperature Dependence on Lapping Grains Size
PublikacjaCommonly used as a finishing operation, lapping has been used for achieving ultra-high finishes and close tolerances between mating pieces. Its carried out by applying loose abrasive grains between work and lap surfaces, and causing a relative motion between them resulting in a finish of multi-directional lay. The grains activity (sliding and rolling) in the working gap causes not only the material removal but also the temperature...
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ANALYSIS OF BEARING CLEARANCE AND WIDTH OF OIL GROOVE ON CHARACTERISTIC OF FLUID FILM IN HYDRODYNAMIC MAIN CRANKSHAFT BEARINGS
PublikacjaAbstract Paper represents analysis of influence of oil groove width and bearing clearance on characteristics of oil film in hydrodynamic journal main crankshaft bearing. Analysis was performed in purpose to define influence of bearing clearance and dimensions of oil groove on static characteristics and manufacturability of half shelf bearings in industrial high-volume production. Computer simulations was made using ARTbear program...
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Przydział narzędzi obróbkowych a efektywność szeregowania zadań produkcyjnych
PublikacjaThe paper addresses issues concerning the analysis of tool flow within a multi-machine machining cell, designated to small batch manufacturing a definite spectrum of prismatic parts. The approach utilises a method for job and tool allocation to work centres with limited number of machines and capacity of tool resources, based on the analysis of formalised relations: job - tool sets required. Selected allocation strategies are considered...
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Application of sliding switching functions in backstepping based speed observer of induction machine
PublikacjaThe paper presents an analysis of the speed observer which is based on the backstepping and sliding mode approach. The speed observer structure is based on the extended mathematical model of an induction machine. The observer structure is based on the measured phase stator currents and transformed to ( αβ ) coordinate system. The stator voltage vector components are treated as known values. Additionally, such an observer structure...
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Modeling and simulation of tool cycle in manufacturing cell
PublikacjaThe paper addresses issues concerning modeling and analysis of tool flow within a three-machine manufacturing cell used for small batch manufacturing of a definite spectrum of prismatic parts. The approach utilizes a method for job and tool allocation to work centers with limited number of machines and capacity of tool resources, based on the analysis of formalized relations: job - tool sets required. Selected tool flow control...
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Karol Flisikowski dr inż.
OsobyKarol Flisikowski jest profesorem uczelni w Katedrze Statystyki i Ekonometrii, Wydziału Zarządzania i Ekonomii Politechniki Gdańskiej. Jest odpowiedzialny jest za prowadzenie zajęć ze statystyki opisowej i matematycznej (w języku polskim i angielskim), a także badań naukowych w zakresie statystyki społecznej. Był uczestnikiem wielu konferencji o zasięgu krajowym, jak i międzynarodowym, gdzie prezentował wyniki prowadzonych przez...