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Search results for: BUCKLING-RESTRAINED BRACED FRAME MACHINE-LEARNING ALGORITHM RESIDUAL INTERSTORY DRIFT SEISMIC RETROFIT SEISMIC PERFORMANCE CURVE SEISMIC FAILURE PROBABILITY
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MODAL ANALYSIS OF REAL TIMBER FRAME HOUSES WITH DIFFERENT INSULATION MATERIALS
PublicationThe aim of this article is to present the results of a numerical modal analysis of two actual structures of timber frame buildings and the different behaviour due to the used insulation material. One model of the timber structure was filled with mineral wool, while the other with polyurethane foam. During the modal analysis, eigenvalues for both models have been determined. The results of the analysis clearly show the increase...
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Edge-Computing based Secure E-learning Platforms
PublicationImplementation of Information and Communication Technologies (ICT) in E-Learning environments have brought up dramatic changes in the current educational sector. Distance learning, online learning, and networked learning are few examples that promote educational interaction between students, lecturers and learning communities. Although being an efficient form of real learning resource, online electronic resources are subject to...
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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Superresolution algorithm to video surveillance system
PublicationAn application of a multiframe SR (superresolution) algorithm applied to video monitoring is described. The video signal generated by various types of video cameras with different parameters and signal distortions which may be very problematic for superresolution algorithms. The paper focuses on disadvantages in video signal which occur in video surveillance systems. Especially motion estimation and its influence on superresolution...
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On the Handling of Outliers in the GNSS Time Series by Means of the Noise and Probability Analysis
PublicationThe data pre-analysis plays a significant role in the noise determination. The most important issue is to find an optimum criterion for outliers removal, since their existence can affect any further analysis. The noises in the GNSS time series are characterized by spectral index and amplitudes that can be determined with a few different methods. In this research, the Maximum Likelihood Estimation (MLE) was used. The noise amplitudes...
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The J-curve phenomenon revisited
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Method of selecting the LS-SVM algorithm parameters in gas detection process
PublicationIn 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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Requirements for Residual Current Devices Intended for Electric Vehicle Charging Systems
PublicationThe properties of residual current devices have been presented from the point of view of their ability to detect a specific shape of the residual current waveform. Moreover, the standard requirements relating to residual current protection used in electric vehicle charging installations have been pointed out. The operating characteristics of the IC-CPD and RDC-DD protections, which are intended for charging electric vehicles in...
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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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Analytical approach for membrane action in laterally-restrained reinforced concrete square slabs under uniformly distributed loads
PublicationLaterally-restrained reinforced concrete slabs can mobilise compressive membrane action and subsequent tensile membrane action under extreme loading conditions, thereby enhancing the load resistance under uniformly distributed loads. Previous analytical study focuses primarily on tensile membrane action in simply-supported slabs. This paper describes an analytical approach for membrane action in laterally-restrained square slabs....
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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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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Improving sensitivity of residual current transformers to high frequency earth fault currents
PublicationFor protection against electric shock in low voltage systems residual current devices are commonly used. However, their proper operation can be interfered when high frequency earth fault current occurs. Serious hazard of electrocution exists then. In order to detect such a current, it is necessary to modify parameters of residual current devices, especially the operating point of their current transformer. The authors proposed...
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Evaluation the P-Delta Effect on Collapse Capacity of Adjacent Structures Subjected to Far-field Ground Motions
PublicationIn urban areas, adjacent structures can be seen in any insufficient distance from each other, because of economic reasons and refusal of acquired minimum separation distance according to seismic previsions. Collapse capacity assessment of structures is one of the important objectives of performance-based seismic engineering. The purpose of this study is to consider the pounding phenomenon and P-Delta effect in seismic collapse...
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Lifelong Learning Idea in Architectural Education
PublicationThe recent advances in IT and technology are forcing changes in the approach to educating society. In the 20th century, life-long learning was understood as educating adults in order to improve their occupational qualifications. Life-long learning allows the needs of the present-day world to be addressed through providing the individual with education at every stage of his/her life various forms. The search for a new model...
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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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Voice command recognition using hybrid genetic algorithm
PublicationAbstract: 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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Determination of Failure Causes of a Steam Turbine Casing
PublicationThe paper presents results of research and failure analysis undertaken to determine failure causes of a steam turbine casing. After 130,000 hours of service the crack in a outer shell of the turbine casing was found. The inner shell of the casing was made of cast steel grade G21CrMoV5-7, and the outer shell of grade G20CrMo4-5. Following research were performed in order to determine causes of the casing failure: chemical analysis;...
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Experimental dynamic study on a timber-frame house using shaking table
PublicationThe aim of this paper is to show the results of the shaking table experimental study concerning the behaviour of the model of the timber-frame house under earthquake excitation and impact loading. In order to determine the basic dynamic properties of the undamaged structure, the free vibration and the sweep-sine tests were first conducted. Then, the model was excited using the time history record of the El Centro earthquake of...
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FEM simulation of laminate failure in the three point bending
PublicationThe paper presents a FEM simulation of failure of laminate subjected to the three point bending. The numeri-cal model is based on the equivalent single layer approach with 6-paramater non-linear shell theory kinematics. It is implemented in the non-commercial FEM code. The failure initiation is detected with the use of Tsai-Wu criterion. After the failure onset the progressive failure process is modelled through the appropriate...
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A cumulative probability function of instantaneous flicker sensation values measured in the industrial power system supplying the rolling mill motors
Open Research DataThe dataset presents a cumulative probability function CPF of the instantaneous flicker sensation level measured on the bus bars of the main switchgear of the industrial power network for the supply of rolling mills. The data were obtained during an experiment whose purpose was to determine a level of short-term and long-term flicker caused by voltage...
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Buckling Analysis of Cold Formed Silo Column
PublicationThe paper is devoted to stability analysis of different models of steel cold formed silo column. The steel cylindrical silos are often composed of corrugated walls and vertical open-sectional columns uniformly placed along the silo circumference. Both the whole 3D silo, a simplified model consisting of one column with a part of the silo walls, and a single column resting on elastic foundation provided by the silo walls were analyzed....
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Buckling and shape control of prestressable trusses using optimum number of actuators
PublicationThis paper describes a method to control the nodal displacement of prestressable truss structures within the desired domains. At the same time, the stress in all members is unleashed to take any value between the allowable tensile stress and critical buckling stress. The shape and stresses are controlled by actuating the most active members. The technique considers the members’ initial crookedness, residual stresses, and slenderness...
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Performance evaluation of the parallel object tracking algorithm employing the particle filter
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Buckling analyses of cylindrical metal silos containing bulk solids
PublicationThe paper presents quasi-static 3D buckling analysis results of thin-walled cylindrical metal silos with and without bulk solids. The behaviour of the bulk solid was described with a hypoplastic constitutive model. Non-linear analyses with geometric and material non-linearity were performed with a perfect and an imperfect silo shell. Different initial geometric imperfections were considered. The influence of internally stored bulk...
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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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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Towards spectral sensitivity curve for two-photon vision mechanism
PublicationAbstract Purpose: The perceived brightness of different visible light sources can be compared with photometric units based on the standardized luminosity curves (300-780nm range). As reported previously (PNAS 111(50), pp. E5445-E5454 (2014)), near-infrared (NIR) radiation can cause isomerization of visual pigments by one- or two-photon absorption. The perceived color of the stimulus is red in the case of one-photon vision (1PV)...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Family business experience and the probability of starting a venture: gender differences in Poland
PublicationThe aim of this study is to analyse whether the experience of working in a family member’s business is related differently to the assessed probabilities of men and women starting their own new venture in the future. The research is conducted on a sample of 334 Polish undergraduate students. Poland is an efficiency-driven European economy with a substantial gender gap in entrepreneurship. The results obtained indicate that the relationship...
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Edyta Gołąb-Andrzejak dr hab.
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Effect of initial imperfection on buckling of thin-walled I columns
PublicationEffects of initial geometrical imperfections on critical buckling loads of thin-walled I columns are investigated. Torsional and flexural buckling are taken into account. The column behaviour is described in accord to the theory of thin-walled beams with nondeformable cross-section. Some numerical examples and conclusions related to effects of imperfections on properties of the critical loads are presented.
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Modelling in machine design (PG_00057377)
e-Learning Coursesgoal of the subject is to show how simple enginnering models reflect the reality and how contemporary FEM calulations can illustrate the operation of machine elements
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Immunity of residual current devices to the impulse leakage current in circuits with variable speed drives
PublicationThis paper concerns reliability of supply in variable speed drive circuits with residual current devices. During normal operation of these circuits high value of leakage current causes unwanted tripping of residual current devices. Immunity of residual current devices to the impulse leakage current should be evaluated. The system for testing of residual current devices and results of the test are presented
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublicationPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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Granulometric characterization of Arctic driftwood sawdust from frame sawing process
PublicationArctic driftwood can be used as an alternative source of wood as construction timber and furniture material, especially in Iceland and Greenland. The use of Arctic driftwood can help in the fight against climate change, by developing land reforestation processes and reducing the volume harvested wood from forests and sustainability of harvesting processes. In this paper the results of an analysis of the effect of long-term residence...
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Earthquake-induced pounding between superstructure segments of isolated bridge
PublicationThe use of seismic isolation in bridges is considered as one of the most promising advanced technologies to enhance the structural safety during earthquakes. However, the method results in larger displacements of superstructure segments increasing the probability of pounding between them. Reports after severe ground motions show that the earthquake-induced structural pounding may lead to significant damage in isolated bridges....
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Buckling of thin-walled columns accounting for initial geometrical imperfections
PublicationThe paper is devoted to the effect of some geometrical imperfections on the critical buckling load of axially compressed thin-walled I-columns. The analytical formulas for the critical torsional and flexural buckling loads accounting for the initial curvature of the column axis or the twist angle respectively are derived. The classical assumptions of theory of thin-walled beams with non-deformable cross-sections are adopted. The...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublicationMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Identification of residual force in static load tests on instrumented screw displacement piles
PublicationOccurrence of the so-called residual force of an unknown value significantly disturbs interpretation of static load tests performed on piles equipped with additional measuring instruments. Screw displacement piles are the piling technology in which the residual force phenomenon is very common. Its formation mechanism is closely related to the installation method of this type of piles, which initiates generation of negative pile...
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AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS
PublicationSymptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....
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SELECTED PROBLEMS OF MACHINE DYNAMICS (2024)
e-Learning CoursesThe course is devoted towards lectures assocuated with the novel issues of machine and structures dynamics. The following lectures will be given during the SPMD course: - introduction to selected problems of machine dynamics, - definition of the machine and structure working environment, - internal and external loads on machines and structures, - dynamics of machines and structures, - strength of machines and structures, - special...
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A new quantum-inspired approach to reduce the blocking probability of demands in resource-constrained path computation scenarios
PublicationThis article presents a new approach related with end-to-end routing, which, owing to quantum-inspired mecha-nisms of prediction of availability of network resources, results in improved blocking probability of incoming requests to establish transmission paths. The proposed scheme has been analyzed for three network topologies and several scenarios of network load. Obtained results show a significant (even twofold) reduction of...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...