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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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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublicationBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublicationWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Probability distribution of flicker noise in AuNPdecorated graphene–Si Schottky barrier diode
PublicationWe present results of the probability distribution analysis of flicker noise generated in Au nanoparticle (AuNP) decorated graphene–Si Schottky barrier diodes with and without yellow light illumination (592 nm), close to the localized surface plasmon resonance in the AuNPs (586 nm). The AuNPs occupy imperfections in the single-layer graphene and reduce the flicker noise intensity generated in the graphene layer. The estimated probability...
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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublicationAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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Tripping limitations of residual current devices in photovoltaic installations
PublicationIn electrical installations with photovoltaic sources of energy, earth fault current may comprise alternating current component and direct current component. The waveform shape of this earth fault current mainly depends on the point of the fault and the properties of a photovoltaic power electronics converter. The waveform shape of the current influences operation of protection devices, especially tripping threshold of residual...
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Probability modelling of vessel collisions
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Residual current devices in electric vehicles charging installations
PublicationThe main requirements of national regulations and international standards regarding protection against electric shock in electric vehicle charging installations are presented. The principles of using residual current devices (RCDs) in such installations are discussed. It is pointed out that RCDs are mandatory equipment for safe charging of electric vehicles. It is noted that the standards require the use of RCDs having an appropriate...
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Transition curve with smoothed curvature at its ends for railway roads
PublicationIn the paper, in view of a railway ballasted track, a new concept of transition curve of linear form of curvature along its length and smoothed extreme regions is presented. For this purpose use has been made of an original, universal method for identifying transition curves by means of differential equations. Some general curvature equations for three regions investigated have been determined to be followed by appropriate parametric...
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The effect of current delay angle on tripping of residual current devices
PublicationPower electronics converters applied in domestic or similar installations may utilize current delay (phase) angle control to change the level of transferred power. Due to application of such types of converters, earth fault current in the installation may be strongly distorted. The current distortion level depends on a value of current delay angle. This delay angle also influences the tripping threshold of residual current devices....
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Application of linear buckling sensitivity analysis to economic design of cylindrical steel silos composed of corrugated sheets and columns
PublicationThe paper deals with global stability of steel cylindrical silos composed of corrugated walls and vertical columns with loads imposed by a bulk solid following Eurocode 1. The optimum silo design with respect to the steel weight was based on a sensitivity analysis method. The changes of silo column profiles at each design step were performed by means of influence lines for the buckling load factor due to the unit column bending...
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Tripping of F-type RCDs for High-Frequency Residual Currents
PublicationResidual current devices (RCDs) are apparatus commonly used for protection against electric shock in low-voltage electrical installations. They protect people in the case of an earth fault or even in the case of direct contact with the live parts. However, to be effective protective devices, RCDs have to detect residual currents of various waveform shapes which appear in modern electrical installations. For this purpose, RCDs...
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Tripping of F-type RCDs for high-frequency residual currents
PublicationResidual current devices (RCDs) are apparatus commonly used for protection against electric shock in low-voltage electrical installations. They protect people in the case of an earth fault or even in the case of direct contact with the live parts. However, to be effective protective devices, RCDs have to detect residual currents of various waveform shapes which appear in modern electrical installations. For this purpose, RCDs are...
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Correlation between natural frequencies and buckling load in a stiffened shell
PublicationThe paper deals with correlation between natural frequencies and buckling load of a stiffened shell composed of corrugated sheets and vertical stiffeners (columns). The simplified shell segment represents the buckling behaviour of a whole silo with sparsely distributed columns. The paper covers variants of linear buckling anal-yses, dynamic eigenvalue analyses and geometrically non-linear analyses of a segment modelled with shell...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Numerical investigation on behaviour of cylindrical steel tanks during mining tremors and moderate earthquakes
PublicationCylindrical steel tanks are important components of industrial facilities. Their safety becomes a crucial issue since any failure may cause catastrophic consequences. The aim of the paper is to show the results of comprehensive FEM numerical investigation focused on the response of cylindrical steel tanks under mining tremors and moderate earthquakes. The effects of different levels of liquid filling, the influence of non-uniform...
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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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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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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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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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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...