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Wyniki wyszukiwania dla: BUILDINGS, VIBRATIONS, MACHINE LEARNING, NUMERICAL ALGORITHM
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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The effect of fishing basin construction on the behaviour of a footbrdge over the port channel
PublikacjaThe paper analyses possible causes of failure of the rotating footbridge over the Ustka port channel. In July, 2015, strange behaviour of this object was observed in the form of excessive vibrations of bridge platform suspension rods, with the accompanying acoustic effects. A preliminary geotechnical analysis has revealed that this destructive effect was caused by the nearby construction works, namely construction of a fishing...
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Szybka identyfikacja harmonicznych na podstawie oszczędnego próbkowania
PublikacjaW pracy przedstawiono implementację szybkiego algorytmu rekonstrukcji sygnału, opartego na teorii oszczędnego próbkowania, który może wykrywać harmoniczne w sygnale wejściowym. Zagadnienie rekonstrukcji sygnału jest problemem optymalizacyjnym rozwiązywanym za pomocą algorytmu programowania liniowego. Dodatkowo, aby przyspieszyć zbieżność rozwiązania zastosowano w rzadkiej dziedzinie sygnału filtr typu K-rank-order. Przeprowadzona...
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Numerical evaluation of dynamic response of an experimentally tested base-isolated and fixed-base steel structure model
PublikacjaSeismic isolation is recognized as one of the most popular and effective methods of protecting structures during earthquake. The present paper is focused on the comparison be-tween the dynamic responses of buildings with fixed and isolated bases exposed to seismic exci-tations. The aim of the study is to investigate the effectiveness of a simplified base isolation numerical modelling technique using the linear springs. One-storey...
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Multimodal Genetic Algorithm with Phase Analysis to Solve Complex Equations of Electromagnetic Analysis
PublikacjaIn this contribution, a new genetic-algorithm-based method of finding roots and poles of a complex function of a complex variable is presented. The algorithm employs the phase analysis of the function to explore the complex plane with the use of the genetic algorithm. Hence, the candidate regions of root and pole occurrences are selected and verified with the use of discrete Cauchy's argument principle. The algorithm is evaluated...
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Analyzing Wind Energy Potential Using Efficient Global Optimization: A Case Study for the City Gdańsk in Poland
PublikacjaWind energy (WE), which is one of the renewable energy (RE) sources for generating electricity, has been making a significant contribution to obtaining clean and green energy in recent years. Fitting an appropriate statistical distribution to the wind speed (WS) data is crucial in analyzing and estimating WE potential. Once the best suitable statistical distribution for WS data is determined, WE potential and potential yield could...
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Improved maximum power point tracking algorithms by using numerical analysis techniques for photovoltaic systems
PublikacjaSolar photovoltaic (PV) panels generate optimal electricity when operating at the maximum power point (MPP). This study introduces a novel MPP tracking algorithm that leverages the numerical prowess of the predictor-corrector method, tailored to accommodate voltage and current fluctuations in PV panels resulting from variable environmental factors like solar irradiation and temperature. This paper delves into the intricate dynamics...
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Central heating temperature control algorithm for systems with condensing boilers
PublikacjaThe problem of control of a central heating system in a small residence is considered. It is assumed that the system is based on a condensing boiler. Since the boiler efficiency depends on a returning water temperature, the proposed control goal is to provide proper air temperature in the residence as well as the lowest possible water temperature. The proposed algorithm is applied to two buildings. Both of them have the same heating...
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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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AffecTube — Chrome extension for YouTube video affective annotations
PublikacjaThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...
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Muhammad Jamshed Abbass Phd in Electrical Engineering
OsobyMuhammad Jamshed Abbass received the M.S. degree in electrical engineering from Riphah International University, Islamabad. He is currently pursuing the Ph.D. degree with the Wrocław University of Science and Technology, Wroclaw, Poland. His research interests include machine learning, voltage stability within power systems, control design, analysis, the modeling of electrical power systems, the integration of numerous decentralized...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublikacjaBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Asking Data in a Controlled Way with Ask Data Anything NQL
PublikacjaWhile to collect data, it is necessary to store it, to understand its structure it is necessary to do data-mining. Business Intelligence (BI) enables us to make intelligent, data-driven decisions by the mean of a set of tools that allows the creation of a potentially unlimited number of machine-generated, data-driven reports, which are calculated by a machine as a response to queries specified by humans. Natural Query Languages...
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Towards an efficient multi-stage Riemann solver for nuclear physics simulations
PublikacjaRelativistic numerical hydrodynamics is an important tool in high energy nuclear science. However, such simulations are extremely demanding in terms of computing power. This paper focuses on improving the speed of solving the Riemann problem with the MUSTA-FORCE algorithm by employing the CUDA parallel programming model. We also propose a new approach to 3D finite difference algorithms, which employ a GPU that uses surface memory....
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Optimised Robust Placement of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublikacjaA problem of optimised robust placement of the hard quality sensors in Drinking Water Distribution Systems under several water demand scenarios for robust quality monitoring is formulated. Numerical algorithms to solve the problem are derived. The optimality is meant as achieving at the same time a desired trade off between the sensor capital and maintenance costs and resulting robust estimation accuracy of the monitoring algorithm...
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublikacjaAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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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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Optimised Allocation of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublikacjaA problem of optimised placement of the hard quality sensors in Drinking Water Distribution Systems for robust quality monitoring is formulated. Two numerical algorithms to solve the problem are derived. The optimality is meant as achieving a desired trade off between the sensor capital and maintenance costs and resulting robust estimation accuracy of the monitoring algorithm. The robust estimation algorithm recently developed...
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Locating and Identifying Ferromagnetic Objects
PublikacjaThe new non-iterative method of determining the dipole moment and location is presented in this paper. The algorithm of an object's localization and identification was achieved by using numerical calculations and approximation method. The arbitrary shapes of an object were assumed in the identification algorithm - axially symmetric spheroid (a prolate and an oblate). Several examples of localization and identification of an object's...
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Locating and Identifying Ferromagnetic Objects
PublikacjaThe new non-iterative method of determining the dipole moment and location is presented in this paper. The algorithm of an object's localization and identification was achieved by using numerical calculations and approximation method. The arbitrary shapes of an object were assumed in the identification algorithm - axially symmetric spheroid (a prolate and an oblate). Several examples of localization and identification of an object's...
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Social media for e-learning of citizens in smart city
PublikacjaThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublikacjaThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Augmenting digital documents with negotiation capability
PublikacjaActive digital documents are not only capable of performing various operations using their internal functionality and external services, accessible in the environment in which they operate, but can also migrate on their own over a network of mobile devices that provide dynamically changing execution contexts. They may imply conflicts between preferences of the active document and the device the former wishes to execute on. In the...
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Improving all-reduce collective operations for imbalanced process arrival patterns
PublikacjaTwo new algorithms for the all-reduce operation optimized for imbalanced process arrival patterns (PAPs) are presented: (1) sorted linear tree, (2) pre-reduced ring as well as a new way of online PAP detection, including process arrival time estimations, and their distribution between cooperating processes was introduced. The idea, pseudo-code, implementation details, benchmark for performance evaluation and a real case example...
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Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublikacjaWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublikacjaIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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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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Resource productivity and environmental degradation in EU-27 countries: context of material footprint
PublikacjaThis study explores the relationship between the resource productivity and environmental degradation in European Union-27 countries. This study tests this relationship in context of high, moderate, and low material footprint sub-samples; these samples are formed utilizing the expectation–maximization machine learning algorithm. Using the panel data set of EU-27 countries from 2000 to 2020, linear and non-linear autoregressive distributed...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublikacjaAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Multi-objective Tabu-based Differential Evolution for Teleportation of Smart Virtual Machines in Private Computing Clouds
PublikacjaWe propose a multi-objective approach for using differential evolution algorithm with tabu search algorithm as an additional mutation for live migration (teleportation) of virtual machines. This issue is crucial in private computing clouds. Teleportation of virtual machines is supposed to be planned to determine Pareto-optimal solutions for several criteria such as workload of the bottleneck host, communication capacity of the...
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Impact of the Finite Element Mesh Structure on the Solution Accuracy of a Two-Dimensional Kinematic Wave Equation
PublikacjaThe paper presents the influence of the finite element mesh structure on the accuracy of the numerical solution of a two-dimensional linear kinematic wave equation. This equation was solved using a two-level scheme for time integration and a modified finite element method with triangular elements for space discretization. The accuracy analysis of the applied scheme was performed using a modified equation method for three different...
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Engineering education for smart grid systems in the quasi-industrial environment of the LINTE^2 laboratory
PublikacjaSmart grid systems are revolutionising the electric power sector, integrating advanced technologies to enhance efficiency, reliability and sustainability. It is important for higher education to equip the prospective smart grid professional with the competencies enabling them to navigate through the related complexities and drive innovation. To achieve this, interdisciplinary education programmes are necessary, addressing inter...
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From Knowledge based Vision Systems to Cognitive Vision Systems: A Review
PublikacjaComputer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...
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Expedited Trust-Region-Based Design Closure of Antennas by Variable-Resolution EM Simulations
PublikacjaThe observed growth in the complexity of modern antenna topologies fostered a widespread employment of numerical optimization methods as the primary tools for final adjustment of the system parameters. This is mainly caused by insufficiency of traditional design closure approaches, largely based on parameter sweeping. Reliable evaluation of complex antenna structures requires full-wave electromagnetic (EM) analysis. Yet, EM-driven...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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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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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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Insights in microbiotechnology: 2022.Editorial
PublikacjaThis Research Topic serves as an invaluable resource for readers interested in staying updated with the latest progress and developments in the field of microbiotechnology. It spotlights the innovative research conducted by up-and-coming experts in the field, specifically emphasizing the transforming abilities of microorganisms that greatly influence the scientific community. The advent of multi-omic technologies has revolutionized microbiotechnology,...
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Multimedia interface using head movements tracking
PublikacjaThe presented solution supports innovative ways of manipulating computer multimedia content, such as: static images, videos and music clips and others that can be browsed subsequently. The system requires a standard web camera that captures images of the user face. The core of the system is formed by a head movement analyzing algorithm that finds a user face and tracks head movements in real time. Head movements are tracked with...
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Proximal primal–dual best approximation algorithm with memory
PublikacjaWe propose a new modified primal–dual proximal best approximation method for solving convex not necessarily differentiable optimization problems. The novelty of the method relies on introducing memory by taking into account iterates computed in previous steps in the formulas defining current iterate. To this end we consider projections onto intersections of halfspaces generated on the basis of the current as well as the previous...
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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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Klasyfikator SVM w zastosowaniu do synchronizacji sygnału OFDM zniekształconego przez kanał wielodrogowy
PublikacjaW pracy przedstawiono analizę przydatności klasyfikatora SVM bazującego na uczeniu maszynowym do estymacji przesunięcia czasowego odebranego symbolu OFDM. Przedstawione wyniki wykazują, że ten klasyfikator potrafi zapewnić synchronizację dla różnych kanałów wielodrogowych o wysokim poziomie szumu. Eksperymenty przeprowadzone w Matlabie z użyciem modeli modulatora i demodulatora wykazały, że w większości przypadków klasyfikator...
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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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A Fortran-95 algorithm to solve the three-dimensional Higgs boson equation in the de Sitter space-time
Dane BadawczeA numerically efficient finite-difference technique for the solution of a fractional extension of the Higgs boson equation in the de Sitter space-time is designed. The model under investigation is a multidimensional equation with Riesz fractional derivatives of orders in (0,1)U(1,2], which considers a generalized potential and a time-dependent diffusion...
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Structural analysis as a supporting method for the research of the medieval brick architecture
PublikacjaChronology of brick historical buildings might be established much more precisely than the chronology of stone ones due to the architectural and metrical analysis of bricks, mortars and brickworks. Comparison of historical sources allows to reconstruct the previous stages of constructing monuments. Causations between transformations and developments of monuments are usually interpreted as the results of artistic or ideological...
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Computer-aided reconstruction of the railway track axis geometrical shape
PublikacjaIn the paper a method of the railway track axis geometrical shape identification in a horizontal plane, directly from the continuous satellite measurements, is presented. In this method, an algorithm for the design of railway track sections located in the horizontal arc is used. The algorithm uses an analytical description of the layout by means of suitable mathematical formulas. The design procedure has a universal character and...
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Arterial cannula shape optimization by means of the rotational firefly algorithm
PublikacjaThe article presents global optimization results of arterial cannula shapes by means of the newly modified firefly algorithm. The search for the optimal arterial cannula shape is necessary in order to minimize losses and prepare the flow that leaves the circulatory support system of a ventricle (i.e. blood pump) before it reaches the heart. A modification of the standard firefly algorithm, the so-called rotational firefly algorithm,...
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FDTD Method for Electromagnetic Simulations in Media Described by Time-Fractional Constitutive Relations
PublikacjaIn this paper, the finite-difference time-domain (FDTD) method is derived for electromagnetic simulations in media described by the time-fractional (TF) constitutive relations. TF Maxwell’s equations are derived based on these constitutive relations and the Grünwald–Letnikov definition of a fractional derivative. Then the FDTD algorithm, which includes memory effects and energy dissipation of the considered media, is introduced....
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Modelling of heat and mass transfer through wooden buildings
PublikacjaThe aim of this review paper is to examine the most recent available studies dealing with theoretical, numerical and experimental aspects related to modelling of heat and mass transfer through wooden buildings. The main thermophysical, mechanical and hygrometric properties of wood are firstly discussed. Then, the basic governing equations of heat and mass transfer phenomena are presented. A detailed description of the physical...