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Wyniki wyszukiwania dla: MEMORY
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Simulating propagation of coherent light in random media using the Fredholm type integral equation
PublikacjaStudying propagation of light in random scattering materials is important for both basic and applied research. Such studies often require usage of numerical method for simulating behavior of light beams in random media. However, if such simulations require consideration of coherence properties of light, they may become a complex numerical problems. There are well established methods for simulating multiple scattering of light (e.g....
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Compressive Sensing Approach to Harmonics Detection in the Ship Electrical Network
PublikacjaThe contribution of this paper is to show the opportunities for using the compressive sensing (CS) technique for detecting harmonics in a frequency sparse signal. The signal in a ship’s electrical network, polluted by harmonic distortions, can be modeled as a superposition of a small number of sinusoids and the discrete Fourier transform (DFT) basis forms its sparse domain. According to the theory of CS, a signal may be reconstructed...
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Refinement of the Hardening Soil model within the small strain range
PublikacjaThe popularity of the elasto-plastic Hardening Soil (HS) model is based on simple parameter identification from standard testing and empirical formulas. The HS model is implemented in many commercial FE codes designed to analyse geotechnical problems. In its basic version, the stress–strain behaviour within the elastic range is subject to the hypoelastic power law, which assures the barotropy of the elastic stiffness. However,...
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Enhancing seismic performance of rigid and semi-rigid connections equipped with SMA bolts incorporating nonlinear soil-structure interaction
PublikacjaNowadays, using smart connections can improve the performance of buildings with some recentering features that are from the superelastic behavior of Shape Memory Alloys (SMAs). It seems that there is different rigidity between the designed connection and the real one in Steel Moment-Resisting Frames (SMRFs), which can be considered as a problematic issue due to the importance of connections in seismic performance assessment. This...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Time fractional analysis of Casson fluid with application of novel hybrid fractional derivative operator
PublikacjaA new approach is used to investigate the analytical solutions of the mathematical fractional Casson fluid model that is described by the Constant Proportional Caputo fractional operator having non-local and singular kernel near an infinitely vertical plate. The phenomenon has been expressed in terms of partial differential equations, and the governing equations were then transformed in non-dimensional form. For the sake of generalized...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublikacjaTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Embedded gas sensing setup for air samples analysis
PublikacjaThis paper describes a measurement setup (eNose) designed to analyze air samples containing various volatile organic compounds (VOCs). The setup utilizes a set of resistive gas sensors of divergent gas selectivity and sensitivity. Some of the applied sensors are commercially available and were proposed recently to reduce their consumed energy. The sensors detect various VOCs at sensitivities determined by metal oxide sensors’ technology...
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Enhancing seismic performance of buckling-restrained brace frames equipped with innovative bracing systems
PublikacjaNowadays, to improve the performance of conventional bracing systems, in which, buckling in the pressure loads is the main disadvantage, the buckling-restrained brace (BRB) is introduced as a solution. In this study, the performance of the BRB system was improved with innovative lateral-resisting systems of double-stage yield buckling-restrained brace (DYB), and a combination of DYB improved with shape memory alloy (SMA) materials...
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Functional Materials
Kursy OnlinePrerequisites: The course is primarily open to all PhD students at Gdansk University of Technology. This course is compulsory for PhD students assigned to Automation, Electronics, Electrical Engineering and Space Technologies tracks at Doctoral School at Gdańsk University of Technology Content During the course students will learn about different classes of intelligent materials and a strong emphasis will be placed on their practical...
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Behavioral state classification in epileptic brain using intracranial electrophysiology
PublikacjaOBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublikacjaCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublikacjaDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
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Concurrent Video Denoising and Deblurring for Dynamic Scenes
PublikacjaDynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning pixel-to-pixel mappings, which is commonly enhanced by larger region awareness. This is a difficult yet simplified scenario because noise is neglected when it is omnipresent in a wide...
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Discussion of Derivability of Local Residual Stress Level from Magnetic Stray Field Measurement
PublikacjaThe NDT procedure dubbed ‘metal magnetic memory’ method and the related ISO 24497 standard has found wide industrial acceptance in some countries, mainly in Russia and China. The method has been claimed by some researchers (Roskosz and Bieniek in NDT&E Int 45:55–62, 2012; Wilson et al. in Sens Actuators A 135:381–387, 2007) as having potential for quantitative determination of local residual stress state in engineering structures,...
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Smart Materials in Architecture: Useful Tools with Practical Applications or Fascinating Inventions for Experimental Design?
PublikacjaFor at least several decades smart or so-called intelligent materials, being the result of great advancements in material engineering, appear in architecture in different applications. Most of them are called "smart" because of their inherent properties: a real-time response to environmental stimuli. There are also those considered to be "smart" due to smart design: their original structure or the composition of their materials...
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Glucosinolates from lepidium peruvianum as potential antiamnestic drugs
PublikacjaLepidium peruvianum (maca) (Brassicaceae) is a naturally occurring plant mainly in the high Andes of Peru. In recent years, it has been intensively researched in terms of its influence on various diseases and towards health improvement. Alzheimer’s disease is an incurable disease that most often affects adults over the age of 60. As since 2003 the US Food and Drug Administration (FDA) did not approve any new drug for Alzheimer’s...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Comparing Apples and Oranges: A Mobile User Experience Study of iOS and Android Consumer Devices
PublikacjaWith the rapid development of wireless networks and the spread of broadband access around the world, the number of active mobile user devices continues to grow. Each year more and more terminals are released on the market, with the smartphone being the most popular among them. They include low-end, mid-range, and of course high-end devices, with top hardware specifications. They do vary in build quality, utilized type of material,...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublikacjaAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...