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Wyniki wyszukiwania dla: VIBRATIONS, MACHINE LEARNING, BUILDINGS
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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CAD Integrated Architectural Design, MSc Arch (2023-24)
Kursy OnlineDetailed understanding of optimizing the design process using parametric BIM (Building Information Modeling) in the Autodesk Revit Architecture program. Practical design exercises included familiarize students with methods of integrating parametric design and exchanging data with other CAD/BIM programs, modifying parametric objects and generating automatic 2D/3D architectural documentation. The lesson plan introduces students to...
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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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Karol Dziedziul dr hab.
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Adam Władziński
OsobyAdam Władziński, doktorant na Politechnice Gdańskiej, specjalizuje się w inżynierii biomedycznej, skupiając się na uczeniu maszynowym do przetwarzania obrazów z druku 3D układów pomiarowych i tkanek biologicznych, a także na komercyjnym zastosowaniu technologii blockchain. Posiadając wykształcenie z dziedziny elektroniki na Wydziale Elektroniki, Telekomunikacji i Informatyki (ETI), praca magisterska Adama Władzińskiego koncentrowała...
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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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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublikacjaSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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A new multi-process collaborative architecture for time series classification
PublikacjaTime 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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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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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
PublikacjaMonitoring 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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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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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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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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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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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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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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Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublikacjaThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
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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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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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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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Leveraging spatio-temporal features for joint deblurring and segmentation of instruments in dental video microscopy
PublikacjaIn 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
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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Mobile wireless measurement system for potatoes storage management
PublikacjaThe paper discusses the idea and the design of a remote control system for a storage management of agricultural products which temperature may rise in a result of biological processes during the storage. Exemplary potatoes storehouse is discussed as an application of the automation system. Because of existing buildings and infrastructure in the farm, wireless data transfer system has been proposed for both sensors to data acquisition...
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Agricultural products' storage control system
PublikacjaThe paper discusses the idea and the design of a remote control system for storage management of agricultural products which temperature may rise as the result of biological processes during the storage. An actual potatoes storehouse is discussed as an application for the proposed automation system. Because of existing buildings and infrastructure at the farm, wireless data transfer system has been proposed for communication between...
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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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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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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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Listening to Live Music: Life beyond Music Recommendation Systems
PublikacjaThis paper presents first a short review on music recommendation systems based on social collaborative filtering. A dictionary of terms related to music recommendation systems, such as music information retrieval (MIR), Query-by-Example (QBE), Query-by-Category (QBC), music content, music annotating, music tagging, bridging the semantic gap in music domain, etc. is introduced. Bases of music recommender systems are shortly presented,...
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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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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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Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry
PublikacjaWe describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular...
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IFE: NN-aided Instantaneous Pitch Estimation
PublikacjaPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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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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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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Modeling of wood frame structures with different insulation materials under damaging dynamic loading
PublikacjaWood frame buildings are very popular in regions that are exposed to different dynamic excitations, such as damaging earthquakes. Their seismic resistance is really important in order to prevent structural damages and human losses. This paper presents the results of advanced numerical investigation carried out using the FEM. Based on the models of wall panels, the numerical model of real structure of the wood frame building has...
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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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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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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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Sound engineering as our commitment to its creators in Poland
PublikacjaSound engineering is an interdisciplinary and rapidly expanding domain. It covers many aspects, such as sound perception, studio and sound mastering technology, music information retrieval including content-based search systems and automatic music transcription frameworks, sound synthesis, sound restoration, electroacoustics, and other ones constituting multimedia technology. Moreover, machine learning methods applied to the topics...
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Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublikacjaPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
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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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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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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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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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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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Identification of category associations using a multilabel classifier
PublikacjaDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublikacjaThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Sounding Mechanism of a Flue Organ Pipe—A Multi-Sensor Measurement Approach
PublikacjaThis work presents an approach that integrates the results of measuring, analyzing, and modeling air flow phenomena driven by pressurized air in a flue organ pipe. The investigation concerns a Bourdon organ pipe. Measurements are performed in an anechoic chamber using the Cartesian robot equipped with a 3D acoustic vector sensor (AVS) that acquires both acoustic pressure and air particle velocity. Also, a high-speed camera is employed...