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Search results for: BUILDINGS, VIBRATIONS, MACHINE LEARNING, NUMERICAL ALGORITHM
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Advanced Mechanics of Marine Structures I, MSc, Summer 2022-2023, [L,T], PG_00051723
e-Learning Courses1. Literature overview, definition of marine and offshore structures, ocean engineering technologies and mechanical aspects, structural systems applied, jack-up drilling platforms and structural elements. 2. Tensor algebra fundamentals, stress and small strain states of a solid, constitutive relations. 3. SDOF and MDOF dynamic systems, damping and added masses in offshore vibrations, generalised eigenvalue problem, forced vibrations...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Application of the Monte Carlo algorithm for solving volume integral equation in light scattering simulations
PublicationVarious numerical methods were proposed for analysis of the light scattering phenomenon. Important group of these methods is based on solving the volume integral equation describing the light scattering process. The popular method from this group is the discrete dipole approximation (DDA). DDA uses various numerical algorithms to solve the discretized integral equation. In the recent years, the application of the Monte Carlo (MC)...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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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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Forced vibrations in a dynamic system that is damped by a mechanism that trans-pass through its singular position
PublicationIn the paper, vibrations of a hybrid multibody-continuous system are investigated. For all the mechanical devices, effective damping methods are crucial in the design process. To obtain it, installation of viscous dampers or elasto-viscous elements is dominant. In the paper, an alternative method is investigated. It is based on modal disparity. To describe the method briefly, when structural damping is present in continuous systems,...
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Better polynomial algorithms for scheduling unit-length jobs with bipartite incompatibility graphs on uniform machines
PublicationThe goal of this paper is to explore and to provide tools for the investigation of the problems of unit-length scheduling of incompatible jobs on uniform machines. We present two new algorithms that are a significant improvement over the known algorithms. The first one is Algorithm 2 which is 2-approximate for the problem Qm|p j = 1, G = bisubquartic|Cmax . The second one is Algorithm 3 which is 4-approximate for the problem Qm|p...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Soil-structure interaction effects on modal parameters of office buildings with different number of stories
PublicationThe paper summarizes the results of a numerical investigation designed to study the soil-structure interaction effects on modal parameters of three office buildings. The reinforced-concrete 4-storey, 8-storey, and 12-storey office buildings, each with additional two levels of embedded basements, represent low, medium, and high-rise structures, respectively. In order to conduct this research, detailed finite-element structure models...
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A review on analytical models of brushless permanent magnet machines
PublicationThis study provides an in-depth investigation of the use of analytical and numerical methods in analyzing electrical machines. Although numerical models such as the finite-element method (FEM) can handle complex geometries and saturation effects, they have significant computational burdens, are time-consuming, and are inflexible when it comes to changing machine geometries or input values. Analytical models based on magnetic equivalent...
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The Neural Knowledge DNA Based Smart Internet of Things
PublicationABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublicationThe 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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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Dynamic Response of the Suspended on a Single Cable Footbridge
PublicationThe article presents numerical simulations, dynamic in situ load tests and a structural health monitoring (SHM) system installed in a suspended on a single cable footbridge. Numerical simulations performed prior to construction indicated the possibility of structural dynamics problems, finally confirmed in the course of dynamic test loading. In the dynamic load course the bridge deck developed vibrations displaying accelerations...
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Adversarial attack algorithm for traffic sign recognition
PublicationDeep learning suffers from the threat of adversarial attacks, and its defense methods have become a research hotspot. In all applications of deep learning, intelligent driving is an important and promising one, facing serious threat of adversarial attack in the meanwhile. To address the adversarial attack, this paper takes the traffic sign recognition as a typical object, for it is the core function of intelligent driving. Considering...
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Approximation algorithms for job scheduling with block-type conflict graphs
PublicationThe problem of scheduling jobs on parallel machines (identical, uniform, or unrelated), under incompatibility relation modeled as a block graph, under the makespan optimality criterion, is considered in this paper. No two jobs that are in the relation (equivalently in the same block) may be scheduled on the same machine in this model. The presented model stems from a well-established line of research combining scheduling theory...
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Timber frame houses resistant to dynamic loads - seismic analysis
PublicationThe aim of the article is to present results of seismic analysis results of two real-sized timber frame buildings subjected to seismic excitations. The first model was insulated with mineral wool, the second one with polyurethane foam. Technology and specifications involved in both models construction is based on the previously conducted experimental research on timber frame houses, including wall panels tests, wall numerical models...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe 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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Basic Hand Gestures Classification Based on Surface Electromyography
PublicationThis paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...
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Numerical solution of threshold problems in epidemics and population dynamics
PublicationA new algorithm is proposed for the numerical solution of threshold problems in epidemics and population dynamics. These problems are modeled by the delay-differential equations, where the delay function is unknown and has to be determined from the threshold conditions. The new algorithm is based on embedded pair of continuous Runge–Kutta method of order p = 4 and discrete Runge–Kutta method of order q = 3 which is used for the...
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Application of Shape Memory Alloys in Retrofitting of Masonry and Heritage Structures Based on Their Vulnerability Revealed in the Bam 2003 Earthquake
PublicationFor decades, one of the most critical considerations of civil engineers has been the construction of structures that can sufficiently resist earthquakes. However, in many parts of the globe, ancient and contemporary buildings were constructed without regard for engineering; thus, there is a rising necessity to adapt existing structures to avoid accidents and preserve historical artefacts. There are various techniques for retrofitting...
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Application of polymer element in reduction of temporary steel grandstand vibrations
PublicationThe numerical analysis focused on reduction of vibrations of a temporary steel scaffolding grandstand has been conducted in this paper. These types of structures are regularly subjected to dynamic loads which, in conjunction with light and quite slender structural members, may induce dangerous vibrations. To increase their safety, temporary steel grandstands are usually strengthened with the diagonal stiffeners of tubular cross...
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Active Kriging-based conjugate first-order reliability method for highly efficient structural reliability analysis using resample strategy
PublicationEfficient structural reliability analysis method is crucial to solving reliability analysis of complex structural problems. High-computational cost and low-failure probability problems greatly limit the efficiency in structural reliability analysis problems, causing the safety and reliability of the structure to be questioned. In this work, a highly efficient structural reliability analysis method coupling active Kriging algorithm...
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Dynamic analysis of temporary steel grandstand equipped with different types of bracing system
PublicationIn the paper, behaviour of a temporary steel grandstand equipped with two different types of bracing system has been analysed through the numerical study. A typical solution concerning application of a diagonal tubular members has been compared with elements proposed by authors and called polymer dampers. A polymer element consists of two L-shape steel members bonded with polymer mass. The aim of the paper is to verify the effectiveness...
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Akustyczna analiza parametrów ruchu drogowego z wykorzystaniem informacji o hałasie oraz uczenia maszynowego
PublicationCelem rozprawy było opracowanie akustycznej metody analizy parametrów ruchu drogowego. Zasada działania akustycznej analizy ruchu drogowego zapewnia pasywną metodę monitorowania natężenia ruchu. W pracy przedstawiono wybrane metody uczenia maszynowego w kontekście analizy dźwięku (ang.Machine Hearing). Przedstawiono metodologię klasyfikacji zdarzeń w ruchu drogowym z wykorzystaniem uczenia maszynowego. Przybliżono podstawowe...
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Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublicationDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
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Diagnostics of historic columns using wave propagation
PublicationThis paper presents a numerical analysis of elastic wave propagation in columns of historical buildings for diagnostics purposes. Numerical calculations were performed using the finite element method in the Abaqus software package. The analysis was carried out for three types of brick columns: a full column, a column filled with debris, and a column empty inside. The excitation was in the form of a wave packet and signals of propagating...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Reduced-Cost Microwave Design Closure by Multi-Resolution EM Simulations and Knowledge-Based Model Management
PublicationParameter adjustment through numerical optimization has become a commonplace of contemporary microwave engineering. Although circuit theory methods are ubiquitous in the development of microwave components, the initial designs obtained with such tools have to be further tuned to improve the system performance. This is particularly pertinent to miniaturized structures, where the cross-coupling effects cannot be adequately accounted...
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Analysis of Modal Parameters Using a Statistical Approach for Condition Monitoring of the Wind Turbine Blade
PublicationThe primary objective of the presented paper is the numerical and experimental investigation related to developing a useful diagnostic method, which can be used for determining the site and size of damage in laminated shells of wind turbine blades. The described detection technique is based on the analysis of low frequencies bending vibrations mode shapes of rotor blades. The authors used the commonly applied statistics methods...
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Phong B. Dao D.Sc., Ph.D.
PeoplePhong B. Dao received the Engineer degree in Cybernetics in 2001, the M.Sc. degree in Instrumentation and Control in 2004, both from Hanoi University of Science and Technology in Vietnam, and the Ph.D. degree in Control Engineering in 2011 from the University of Twente, the Netherlands. In May 2020, Dr. Dao received the degree of D.Sc. (Habilitation) in Mechanical Engineering from the AGH University of Science and Technology, Poland....
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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STAN AWARYJNY TRYBUNY STADIONU W ZIELONEJ GÓRZE WYWOŁANY SYNCHRONICZNYM TAŃCEM KIBICÓW
PublicationW artykule przedstawiono badania i naprawy trybuny stadionu żużlowego w Zielonej Górze narażonej na nadmierne drgania podczas synchronicznego tańca kibiców zwanego „Labado”. W trakcie prac wykonano dwa etapy wzmocnień: za pomocą dodatkowych słupków (zalecenie zespołu z Uniwersytetu Zielonogórskiego) oraz wzmocnienie dodatkowymi stężeniami całej konstrukcji zadaszenia trybuny. W artykule przedstawiono wyniki badań pomiarowych in...
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STAN AWARYJNY TRYBUNY STADIONU W ZIELONEJ GÓRZE WYWOŁANY SYNCHRONICZNYM TAŃCEM KIBICÓW
PublicationW artykule przedstawiono badania i naprawy trybuny stadionu żużlowego w Zielonej Górze narażonej na nadmierne drgania podczas synchronicznego tańca kibiców zwanego „Labado”. W trakcie prac wykonano dwa etapy wzmocnień: za pomocą dodatkowych słupków (zalecenie zespołu z Uniwersytetu Zielonogórskiego) oraz wzmocnienie dodatkowymi stężeniami całej konstrukcji zadaszenia trybuny. W artykule przedstawiono wyniki badań pomiarowych in...
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Adrian Kastrau mgr inż.
People -
Tomasz Deręgowski dr inż.
PeopleTomasz Deręgowski is Assistant Professor at the Department of Informatics in Management, Faculty of Management and Economics, Gdańsk University of Technology, Poland, and Head of Data Platform Engineering Department, working on Big Data, Machine Learning and Data Science solutions at Nordea Bank AB - the largest Scandinavian financial institution. He has more than 15 years of industrial experience, working as a programmer, team...
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An Analysis of Uncertainty and Robustness of Waterjet Machine Positioning Vision System
PublicationThe paper presents a new Automatic Waterjet Positioning Vision System (AWPVS) and investigates components of workpiece positioning accuracy. The main purpose of AWPVS is to precisely identify the position and rotation of a workpiece placed on a waterjet machine table. Two webcams form a basis for the system, and constitute its characteristics. The proposed algorithm comprises various image processing techniques to assure a required...
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublicationPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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Adaptive Algorithm for Interactive Question-based Search
PublicationPopular web search engines tend to improve the relevanceof their result pages, but the search is still keyword-oriented and far from "understanding" the queries' meaning. In the article we propose an interactive question-based search algorithm that might come up helpful for identifying users' intents. We describe the algorithm implemented in a form of a questions game. The stress is put mainly on the most critical aspect of this...
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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008)
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Modal analysis of temporary steel grandstand equipped with different bracing systems
PublicationThe aim of this paper is to present the results of numerical analysis focused on temporary steel scaffolding grandstand. The investigation has been devoted to modal analysis where modes of free vibrations and corresponding natural frequencies have been estimated and compared. The structure was equipped with different types of stiffener members. One on them is a typical tubular stiffener, while the second one is spe-cially designed...
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Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms
PublicationImplementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...
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Effects of Column Base Flexibility on Seismic Response of Steel Moment-Frame Buildings
PublicationSteel Moment Resisting Frames (SMRFs) are very popular lateral load resisting systems in many seismically active regions. However, their seismic response is strongly dependent on the rotational fixity of column base connections. Despite many studies (both experimental and numerical) in this particular area, available approaches for estimating column base flexibility have been validated only against laboratory test data. In the...
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Experience-Oriented Knowledge Management for Internet of Things
PublicationIn this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional...
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Julita Wasilczuk dr hab.
PeopleBorn on 5th of April, 1965 in Gdansk. In 1987-1991 studied the economics of transport, at the University of Gdansk. At 1993 she started to work at the Faculty of Management and Economics. In 1997 received a PhD at the faculty, in 2006 habilitation at the Faculty of Management, University of Gdansk. Since 2009 Associate Professor at Gdansk University of Technology. In 2010-2012 Associate Professor of Humanistic High School at Gdansk. The...
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Predicting the peak structural displacement preventing pounding of buildings during earthquakes
PublicationThe aim of the present paper is to verify the effectiveness of the artificial neural network (ANN) in predicting the peak lateral displacement of multi-story building during earthquakes, based on the peak ground acceleration (PGA) and building parameters. For the purpose of the study, the lumped-mass multi-degree-of-freedom structural model and different earthquake records have been considered. Firstly, values of stories mass and...
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A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds
PublicationThe recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital...
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Mixed-use buildings as the basic unit that shapes the housing environment of smart cities of the future
PublicationThe contemporary approach to creating the residential function is confronted with the trend of increasing the volume of buildings and expectations regarding the future urban environment focused on sustainable development. This paper presents an overview of the residential structure in the context of defined thematic scopes. Namely, it is a systemic approach to the problem of designing mixed-use buildings which create a modern residential...