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Search results for: PREDICTIVE MACHINE LEARNING-BASED TOOLS
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Sathwik Prathapagiri
PeopleSathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Computational Analysis of Transformational Organisational Change with Focus on Organisational Culture and Organisational Learning: An Adaptive Dynamical Systems Modeling Approach
PublicationTransformative Organisational Change becomes more and more significant both practically and academically, especially in the context of organisational culture and learning. However computational modeling and formalization of organisational change and learning processes are still largely unexplored. This chapter aims to provide an adaptive network model of transformative organisational change and translate a selection of organisational...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublicationTransformative 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
PublicationTransformative 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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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Instantaneous power signal measurements for bearing diagnostics
Open Research DataBearing 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
Open Research DataThe 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
Open Research DataThe 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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Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit
PublicationThe general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...
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Metal–Organic Frameworks (MOFs) for Cancer Therapy
PublicationMOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...
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Analiza działania rozszerzonego obserwatora prędkości w szerokim zakresie zmian prędkości maszyny indukcyjnej
PublicationW artykule przedstawiono zagadnienia związane z odtwarzaniem zmiennych stanu maszyny indukcyjnej. Wykorzystano obserwator oparty na modelu matematycznym maszyny z dodatkowymi zmiennymi. Przedstawiono macierz stanu zlinearyzowanych równań błędu odtwarzania. Opisano sposób definiowania wyznacznika jakości na podstawie rozkładu biegunów obserwatora. Zaproponowano metodę korekcji wzmocnień wraz ze zmianą warunków pracy maszyny. Wykazano...
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Standards Conformity Framework in comparison with contemporary methods supporting standards application
PublicationAchieving and assessing conformity with standards and compliance with various sets of requirements generates significant costs for contemporary economies. Great deal of this is spent on fulfilment of safety and security requirements. However, standards application is not supported sufficiently by the tools available on the market. Therefore, Standards Conformity Framework (SCF) containing methods and tools which provide support...
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Toward Mechanosynthesis of Diamondoid Structures: X. Commercial Capped CNT SPM Tip as Nowadays Available C2 Dimer Placement Tool for Tip-Based Nanofabrication
PublicationAccording to Drexler, advanced mechanosynthesis will employ advanced nano-machines, but advanced nano-machines will themselves be products of advanced mechanosynthesis. This circular relationship must be broken via TBN technology development. In this article, the possibility of using easily available commercial CNT tips to assemble carbon-based intermediate generations of nano-devices is considered. Mechanosynthesis of a target...
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Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review
PublicationThe segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents...
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Adaptive Positioning Systems Based on Multiple Wireless Interfaces for Industrial IoT in Harsh Manufacturing Environments
PublicationAs the industrial sector is becoming ever more flexible in order to improve productivity, legacy interfaces for industrial applications must evolve to enhance efficiency and must adapt to achieve higher elasticity and reliability in harsh manufacturing environments. The localization of machines, sensors and workers inside the industrial premises is one of such interfaces used by many applications. Current localization-based systems...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublicationThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Double Bias of Mistakes: Essence, Consequences, and Measurement Method
PublicationThere is no learning without mistakes. However, there is a clash between‘positive attitudes and beliefs’regarding learning processes and the ‘negative attitudes and beliefs’towardthese being accompanied bymistakes. Thisclash exposesa cognitive bias towardmistakesthat might block personal and organizational learning. This study presents an advanced measurement method to assess thebias of mistakes. The essence of it is the...
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Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease
PublicationIn this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...
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Switching Regulation in the Control of 5-Phase Permanent Magnet Synchronous Motor Fed by 3×5 Direct Matrix Converter
PublicationMatrix converter is an AC-AC direct power converter comprising of an array of bi- directional switches. It does not require an intermediate DC-link and allows sinusoidal output waveforms with varying amplitudes and frequencies. The configuration of these bi- directional switches decides the number of inputs and outputs...
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublicationThe 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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The Bridge of Data Project Objectives
PublicationOpen Research Data (ORD) is one of the emerging trends for researchers across the globe. However, it has to be stressed that the level of implementation and awareness of ORD varies between countries. Many initiatives have been created in Polish scientific institutions to support the process of opening publications. These are mainly Open Access (OA) repositories, implementing the so-called green road of OA. However, only a few universities...
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Pedestrian safety management using the risk-based approach
PublicationThe paper presents a concept of a multi-level pedestrian safety management system. Three management levels are distinguished: strategic, tactical and operational. The basis for the proposed approach to pedestrian safety management is a risk-based method. In the approach the elements of behavioural and systemic theories were used, allowing for the development of a formalised and repeatable procedure integrating the phases of risk...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublicationW 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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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
PublicationMonitoring plays an important role in advanced control of complex dynamic systems. Precise information about system's behaviour, including faults detection, enables efficient control. Proposed method- Kernel Principal Component Analysis (KPCA), a representative of machine learning, skilfully takes full advantage of the well known PCA method and extends its application to nonlinear case. The paper explains the general idea of KPCA...
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Roller burnishing
PublicationThe paper shows the process of roller burnishing as a method of finishing machine components. Based on own research the author presents the effects of the roller burnishing process to increase the hardness and residual stress as well as the wear and fatigue strength of burnishing components.
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Brygida Mielewska dr
PeopleBorn on 1 December 1972 in Gdynia. Education and professional experience:June 1997 MSc in Physics, Gdańsk University, Faculty of Mathematics and Physics; October 1997 – August 2003 – Assistant at Gdańsk University of Technology (GUT), Faculty of Applied Physics nad Technical Mathematics, Department of Physics of Electronic Phenomena;June 2003 – PhD in Physics, thesis advisor prof. dr hab. Mariusz Zubek; September 2003- January...
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Category-Based Workload Modeling for Hardware Load Prediction in Heterogeneous IaaS Cloud
PublicationThe paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.
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A comparative analysis of methods and tools for low impact development (LID) site selection
PublicationThe site selection for Low Impact Development (LID) practices is a significant process. It affects the effectiveness of LID in controlling stormwater surface runoff, volume, flow rate, and infiltration. This research paper presents a comprehensive review of various methods used for LID site selection. It starts by introducing different methods and tools. Three main methods: index-based methods, GIS-based multi-criteria decision...
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublicationDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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How to teach architecture? – Remarks on the edge of Polish transformation processes after 1989
PublicationThe political changes in Poland after 1989 have resulted in a whole range of dynamic processes including the transformation of space. Until that time the established institutional framework for spatial, urban and architectural planning policy was based on uniform provisions of the so-called planned economy. The same applied to the training of architects, which was based on a unified profile of education provided at the state’s...
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublicationPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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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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A novel architecture for e-learning knowledge assessment systems
PublicationAbstract. In this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture,while well suited for didactic content distribution systems is ill-suited for knowledge assessment...
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Challenges for universities in the face of knowledge-based economy - directions for higher education institutions in the Baltic Sea Region
PublicationThe aim of this paper is to present new challenges that are faced by universities in the knowledge-based economy. There are several phenomena that can presently be observed like the need for life-long learning or interdisciplinary approach, and universities should prepare their graduates for those challenges. One of the crucial questions that universities need to ask is how to teach and what to teach. Knowledge becomes obsolete...
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Challenges for universities in the face of the knowledge-based economy - Directions for higher education institutions in the Baltic Sea Region
PublicationThe aim of this paper is to present new challenges that are faced by universities in the knowledge-based economy. There are several phenomena that can presently be observed like the need for life-long learning or interdisciplinary approach, and universities should prepare their graduates for those challenges. One of the crucial questions that universities need to ask is how to teach and what to teach. Knowledge becomes obsolete...
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JamesBot - an intelligent agent playing StarCraft II
PublicationThe most popular method for optimizing a certain strategy based on a reward is Reinforcement Learning (RL). Lately, a big challenge for this technique are computer games such as StarCraft II which is a real-time strategy game, created by Blizzard. The main idea of this game is to fight between agents and control objects on the battlefield in order to defeat the enemy. This work concerns creating an autonomous bot using reinforced...
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Internet photogrammetry as a tool for e-learning
PublicationAlong 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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Medical Image Dataset Annotation Service (MIDAS)
PublicationMIDAS (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
PublicationCurrently 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
PublicationThe 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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Analysis of Factors Influencing the Prices of Tourist Offers
PublicationTourism 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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Leveraging spatio-temporal features for joint deblurring and segmentation of instruments in dental video microscopy
PublicationIn dentistry, microscopes have become indispensable optical devices for high-quality treatment and micro-invasive surgery, especially in the field of endodontics. Recent machine vision advances enable more advanced, real-time applications including but not limited to dental video deblurring and workflow analysis through relevant metadata obtained by instrument motion trajectories. To this end, the proposed work addresses dental...
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Bayesian Optimization for solving high-frequency passive component design problems
PublicationIn 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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The Impact of Information and Communication Technology on the Rise of Urban Social Movements in Poland
PublicationThe chapter examines the relationship between the use of Information and Communications Technology (ITC) and the emergence of social movements focused on urban agenda in Poland. The aim is to investigate how and to what extent a growing body of smaller activist groups use opportunities provided by the ITC to achieve their political objectives. The research results indicate that Web-based media have helped to raise the profile...
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The Impact of Information and Communications Technology on the Rise of Urban Social Movements in Poland
PublicationThe chapter examines the relationship between the use of Information and Communications Technology (ITC) and the emergence of social movements focused on urban agenda in Poland. The aim is to investigate how and to what extent a growing body of smaller activist groups use opportunities provided by the ITC to achieve their political objectives. The research results indicate that Web-based media have helped to raise the profile of...
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Genetic Hybrid Predictive Controller for Optimized Dissolved-Oxygen Tracking at Lower Control Level
PublicationA hierarchical two-level controller for dissolvedoxygenreference trajectory tracking in activated sludge processeshas been recently developed and successfully validated on a realwastewater treatment plant. The upper level control unit generatestrajectories of the desired airflows to be delivered by theaeration system to the aerobic zones of the biological reactor. Anonlinear model predictive control algorithm is applied to designthis...
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Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer
PublicationThe subject of this paper is gains selection of an extended induction machine speed observer. A high number of gains makes manual gains selection difficult and due to nonlinear equations of the observer, well-known methods of gains selection for linear systems cannot be applied. A method based on genetic algorithms has been proposed instead. Such an approach requires multiple fitness function calls; therefore, using a quality index...
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Wear of Electroplated Tools Used for Flat Grinding of Ceramics
PublicationTwo methods for the abrasive properties evaluation, based on the image processing, are presented in the paper. Image processing analysis was developed to evaluate quickly the abrasive properties as the tool wears down. The coefficient based on the image brightness was calculated and additional analysis was based on the number of grains located on the active surface of the tool before and after machining. The active surfaces of...
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Arsalan Muhammad Soomar Doctoral Student
PeopleHi, I'm Arsalan Muhammad Soomar, an Electrical Engineer. I received my Master's and Bachelor's Degree in the field of Electrical Engineering from Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan. Currently enrolled as a Doctoral student at the Gdansk University of Technology, Gdansk, Poland. Also worked in Yellowlite. INC, Ohio as a Solar Design Engineer. HEADLINE Currently Enrolled as a Doctoral...