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Search results for: deep learning, genetic algorithm, artificial neural networks, predictive maintenance, cost efficient maintenance
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Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice
PublicationThe vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron,...
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Measures of region failure survivability for wireless mesh networks
PublicationWireless mesh networks (WMNs) are considered as a promising alternative to wired local, or metropolitan area networks. However, owing to their exposure to various disruptive events, including natural disasters, or human threats, many WMN network elements located close to the failure epicentre are frequently in danger of a simultaneous failure, referred to as a region failure. Therefore, network survivability, being the ability...
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Design of dimensionally stable composites using efficient global optimization method
PublicationDimensionally stable material design is an important issue for space structures such as space laser communication systems, telescopes, and satellites. Suitably designed composite materials for this purpose can meet the functional and structural requirements. In this paper, it is aimed to design the dimensionally stable laminated composites by using efficient global optimization method. For this purpose, the composite plate optimization...
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Magnetic deep eutectic solvents as efficient media for extraction of furfural and 5-hydroxymethylfurfural from aqueous samples
PublicationThe extraction of furfural (FF) and 5-hydroxymethylfurfural (HMF) from hydrolysates is currently one of the main challenges in bio-refinery. In this work, the separation of FF and HMF from the aqueous phase was carried out using a new type of green solvents – Magnetic Deep Eutectic Solvents (MDES). A conductor-like screening model for realistic solvents (COSMO-RS) was used for the preselection of 400 MDES. MDES which exhibit the...
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Supervised model predictive control of wastewater treatment plant
PublicationAn optimizing control of a wastewater treatment plant (WWTP), allowing for cost savings over long time period and fulfilling effluent discharge limits at the same time, requires application of advanced control techniques. Model Predictive Control (MPC) is a very suitable control technology for a synthesis of such a truly multivariable controller that can handle constraints and accommodate model-based knowledge combined with hard...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry
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Efficient calculation of the resonant frequencies of a SIW resonator with FDFD-based macromodel algorithm
PublicationW pracy przedstawiono efektywną metodę do analizy struktur ze integrowanym podłożem (SIW). W celu szybkiego obliczenia częstotliwości rezonansowych używany jest algorytm FDFD z zaimplementowanymi makromodelami.
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Jarosław Bąkowski dr inż. arch.
Peopledr inż. Jarosław Bąkowski, assistant professor in the Department of Marine and Industrial Architecture, Faculty of Architecture, Gdansk University of Technology.The subject of his interest is the programming and designing methodology of functionally complex buildings (especially the healthcare architecture buildings, mainly hospitals). He conducts research on optimization of the design process for functional and utility analysis....
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Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network
PublicationArtificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper pesents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to...
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Concurrent DNA Copy-Number Alterations and Mutations in Genes Related to Maintenance of Genome Stability in Uninvolved Mammary Glandular Tissue from Breast Cancer Patients
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ZASTOSOWANIE OPROGRAMOWANIA ERP Z ZAKRESU „PLANT MAINTENANCE” NA PRZYKŁADZIE SAP PM JAKO NARZĘDZIA DLA SŁUŻB UTRZYMANIA RUCHU OBIEKTU OFFSHORE
PublicationW artykule poruszono kwestię planowania zasobów przedsiębiorstwa z wykorzystaniem oprogramowania ERP. Efektywne planowanie zarządzania całością zasobów przedsiębiorstwa polega głównie na: - zapewnieniu wysokiej jakości produktów, - maksymalizacji ekonomicznego okresu użytkowania parku maszynowego, -maksymalizacji zdolności produkcyjnych, - minimalizacji kosztów utrzymania sprzętu w sprawności operacyjnej, - zapewnieniu bezpiecznych...
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Hierarchical predictive control of integrated wastewater treatment systems
PublicationThe paper proposes an approach to designing the control structure and algorithms for optimising control of integrated wastewater treatment plant-sewer systems (IWWTS) under a full range of disturbance inputs. The optimised control of IWWTS allows for significant cost savings, fulfilling the effluent discharge limits over a long period and maintaining the system in sustainable operation. Due to the specific features of a wastewater...
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Artificial Intelligence-Based Weighting Factor Autotuning for Model Predictive Control of Grid-Tied Packed U-Cell Inverter
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Federated Learning in Healthcare Industry: Mammography Case Study
PublicationThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Genetic Programming with Negative Selection for Volunteer Computing System Optimization
PublicationVolunteer computing systems like BOINC or Comcute are strongly supported by a great number of volunteers who contribute resources of their computers via the Web. So, the high efficiency of such grid system is required, and that is why we have formulated a multi-criterion optimization problem for a volunteer grid system design. In that dilemma, both the cost of the host system and workload of a bottleneck host are minimized. On...
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Brain-Inspired Deep Networks for Facial Expression Recognition. Frontiers in Biomedical Technologies
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Aerodynamic excitations generated in turbine shroud clearance determined bymeans of neural networks
PublicationSiły aerodynamiczne generowane w uszczelnieniach turbinowych z reguły opisywane są modelem liniowym. Przy dużych drganiach wirnika sposób ten daje niezbyt dokładne wyniki. Zaproponowano wykorzystanie sieci neuronowych do określania sił ciśnieniowych powstających w uszczelnieniu. Wyniki porównano z badaniami eksperymentalnymi.
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Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
PublicationThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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Low Cost Method for Location Service in the WCDMA System
PublicationA new and low cost method for a location service (LCS) in the Wideband Code Division Multiple Access (WCDMA) system is outlined. This method, which is called TDOA + RTT, enables calculation of the geographical position of a mobile station (MS) without knowledge of relative time differences (RTDs) between base stations (BSs). The TDOA+RTT method is based on the measurement of round trip times (RTTs) between the MS and the serving...
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Evolution of Animats Following a Moving Target in an Artificial Ecosystem
PublicationMany biological animals, even microscopically small, are able to track moving sources of food. In this paper, we investigate the emergence of such behavior in artificial animals (animats) in a 2-dimensional simulated liquid environment. These "predators" are controlled by evolving artificial gene regulatory networks encoded in linear genomes. The fate of the predators is determined only by their ability to gather food and reproduce—no...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Sensorless predictive control of three-phase parallel active filter
PublicationThe paper presents the control system of parallel active power filter (APF) with predictive reference current calculation and model based predictive current control. The novel estimator and predictor of grid emf is proposed for AC voltage sensorless operation of APF, regardless of distortion of this voltage. Proposed control system provides control of APF current with high precision and dynamics limited only by filter circuit parameters....
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Peroxymonosulfate-assisted photocatalytic degradation of artificial sweeteners in water
PublicationIn the present study, peroxymonosulfate (PMS) activation was proposed for efficient photocatalytic degradation of aspartame, acesulfame, saccharin, and cyclamate - artificial sweeteners frequently present in wastewaters and surface waters worldwide. The TiO2 nanosheets with exposed {0 0 1} facets were synthesised using the fluorine-free lyophilisation technique as a green concept for the synthesis and used for the photodegradation...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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e-Learning - user's guide for students
e-Learning Coursese-Learning - user's guide for students
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International Conference on Artificial Neural Networks and Genetic Algorithms
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Recent progress in research on the cutting processes of wood. A review COST Action E35 2004-2008: Wood machining - micromechanics and fracture
PublicationZaprezentowano postępy w badaniach przecinania drewna ze szczególnym uwzględnieniem nowych metod dedykowanych zwiększeniu wydajności materiałowej w tartacznictwie. Zademonstrowano przydatność współczesnej mechaniki pękania do szacowania mocy skrawania dla pił, których wartości rozwarcia są różne od pił użytych w badaniach skrawalnościowych. W tych ostatnich wyznaczano wiązkość materiału obrabianego oraz naprężenia tnące. Badania...
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Recent progress in research on the cutting processes of wood. A review COST Action E35 2004-2008: Wood machining - micromechanics and fracture
PublicationZaprezentowano postępy w badaniach przecinania drewna ze szczególnym uwzględnieniem nowych metod dedykowanych zwiększeniu wydajności materiałowej w tartacznictwie. Zademonstrowano przydatność współczesnej mechaniki pękania do szacowania mocy skrawania dla pił, których wartości rozwarcia są różne od pił użytych w badaniach skrawalnościowych. W tych ostatnich wyznaczano wiązkość materiału obrabianego oraz naprężenia tnące. Badania...
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An optimal sliding mode control based on immune-wavelet algorithm for underwater robotic manipulator
PublicationIn this paper, a robust optimal Sliding Mode Controller (SMC) based on new algorithm of Artificial Immune System (AIS) is proposed for trajectory tracking of underwater manipulators. A new AIS algorithm is used to derive optimal values of surface parameters and boundary layer thickness in SMC with considering minimum torques and error. Surface parameters and boundary layer thickness are considered as antibody in AIS and Morlet...
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Adding Intelligence to Cars Using the Neural Knowledge DNA
PublicationIn this paper we propose a Neural Knowledge DNA based framework that is capable of learning from the car’s daily operation. The Neural Knowledge DNA is a novel knowledge representation and reasoning approach designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. We examine our framework for drivers' classification based on their driving behaviour. The experimental...
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The QDMC Model Predictive Controller for the Nuclear Power Plant Steam Turbine Control
PublicationThere are typically two main control loops with PI con trollers operating at each turbo-generator set. In this paper a model predictive controller QDMC for the steam turbine is proposed - instead of a typical PI controller. The QDMC controller utilize a step-response model for the controlled system. This model parameters are determined, based on the simplified and linear model of turbo-generator set, which parameters are identified...
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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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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Jacek Poplatek dr inż. arch.
PeopleJacek Poplatek – Assistant Professor at the Faculty of Architecture, Gdańsk University of Technology. In research work his interests focuses mainly on issues of programming and designing of healthcare architecture facilities, including general and specialist hospitals. The second field of research is 19th century historical architecture of Sopot city and protection of its architectural and cultural heritage. He is the author of...
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Methods of estimating the cost of traffic safety equipment’s life cycle
Publicationn the article, the authors discuss the preliminary information necessary to determine the scope and direction of further research conducted within the project called “The influence of time and operating conditions on the durability and functionality of road safety elements”. The main objective of the project is to develop the concept of a method for optimizing the life cycle costs of road safety devices. The authors draw attention...
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New approach to railway noise modeling employing Genetic Algorithms
PublicationMain goal of this paper was to describe an innovative method of noise prediction based on Genetic Algorithms. First part of the paper addresses the problem of growing noise, mainly in the context of a unified method for measuring noise. Further, Genetic Algorithms are described with regards to their fundamental features. Further a description is provided as to how Genetic Algorithms were used in the area of noise modeling. Next...
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Comparison of Two Nonlinear Predictive Control Algorithms for Dissolved Oxygen Tracking Problem at WWTP
PublicationThe wastewater treatment plant is classified as a complex system, due to its nonlinear dynamics, large uncertainty of disturbance inputs, multiple time scales in the internal process dynamics, and multivariable structure. The aeration process, in turn, is an important and expensive part of wastewater treatment plant operation. All operating parameters of the aeration in biological processes are to be precisely controlled to provide...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublicationIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Efficient Gradient-Based Algorithm with Numerical Derivatives for Expedited Optimization of Multi-Parameter Miniaturized Impedance Matching Transformers
PublicationFull-wave electromagnetic (EM) simulation tools have become ubiquitous in the design of microwave components. In some cases, e.g., miniaturized microstrip components, EM analysis is mandatory due to considera¬ble cross-coupling effects that cannot be accounted for otherwise (e.g., by means of equivalent circuits). These effects are particularly pronounced in the structures in¬volving slow-wave compact cells and their numerical...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublicationCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublicationSolubility 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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DentalSegmentator: Robust open source deep learning-based CT and CBCT image segmentation
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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Reduced-Cost Microwave Modeling Using Constrained Domains and Dimensionality Reduction
PublicationDevelopment of modern microwave devices largely exploits full-wave electromagnetic (EM) simulations. Yet, simulation-driven design may be problematic due to the incurred CPU expenses. Addressing the high-cost issues stimulated the development of surrogate modeling methods. Among them, data-driven techniques seem to be the most widespread owing to their flexibility and accessibility. Nonetheless, applicability of approximation-based...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...