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Search results for: Deep soil mixing
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The influence of changes of soil parameters due to consolidation on the interaction of piles and soft soil layer
PublicationZaprezentowano problem wyznaczania bocznego parcia gruntu o małej wytrzymałości na pale. Opisano przypadki występowania bocznego obciążenia pali. Scharakteryzowano właściwości i zachowanie gruntów słabych stanowiących warstwę podłoża o małej wytrzymałości. Zaprezentowano propozycje obliczania bocznego parcia według różnych autorów. Przedstawiono wpływ konsolidacji na zmianę wytrzymałości gruntów słabych w czasie oraz na obliczanie...
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Comparative model tests of SDP and CFA pile groups in non-cohesive soil
PublicationThe research topic relates to the subject of deep foundations supported on continuous flight auger (CFA) piles and screw displacement piles (SDP). The authors have decided to conduct model tests of foundations supported on the group of piles mentioned above and also the tests of the same piles working alone. The tests are ongoing in Geotechnical Laboratory of Gdańsk University of Technology. The description of test procedure, interpretation...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Simultaneous removal of heavy metals and dyes in water using a MgO-coated Fe3O4 nanocomposite: Role of micro-mixing effect induced by bubble generation
PublicationThis study focused on the development of a nano-adsorbent for contaminant removal without the use of any external energy. An eco-friendly Fe3O4@MgO core-shell nanocomposite was synthesized and tested for the removal of a heavy metal, lead (Pb2+) and a dye, rhodamine B (RhB). The addition of H2O2 into the system enabled the self-mixing of the aqueous solution containing Fe3O4@MgO through the generation of bubbles. This system showed...
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The impact of the shape of deep drilled well screen openings on the filtration process in full saturation conditions
PublicationThe authors propose a supplementary method of modelling seepage flow around the deep drilled well screen. The study applies 3D numerical modelling (FEM) in order to provide an in-depth analysis of the seepage process. The analysis of filtration parameters (flow distribution q(x,t) and pressure distribution p) was conducted using the ZSoil.PC software system. The analysis indicates that the shape of perforation is of secondary importance...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Soil enzymes in a changing climate
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A Strategy to Locate Fixed Points and Global Perturbations of ODE’s: Mixing Topology with Metric Conditions
PublicationIn this paper we discuss a topological treatment for the planar system z' = f (t, z) + g(t, z) where f and g are T -periodic in time and g(t, z) is bounded. Namely, we study the effect of g(t, z) in two different frameworks: isochronous centers and time periodic systems having subharmonics. The main tool employed in the proofs consists of a topological strategy to locate fixed points in the class of orientation preserving embedding...
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Hybrid Approach in Project Management - Mixing Capability Maturity Model Integration with Agile Practices
PublicationThis paper introduces an idea of hybrid approach in managing software development projects. The main goal of this research is to prove that it is possible to design consistent method for managing software development projects which is based on different corporate standards and methods. Authors also want to show that this new hybrid approach is beneficial for IT organization, triggers synergy effects and brings software development...
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Evaluation of bacterial strains for developing effective plant growth promoting strain on chickpea growth and physico chemical properties of soil
PublicationThe study was intended to isolate and characterize the plant growth-promoting properties. A collection of microbial consortia called plant growth-promoting microorganisms (PGPM) work to increase crop growth and yield through a variety of direct mechanisms, including as nitrogen fixation, phosphate solubilization, synthesis of PGH, ammonia, and siderophore, as well as indirect mechanisms. The aim of the study was to evaluate the...
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The Effect of the Selection of Three-Dimensional Random Numerical Soil Models on Strip Foundation Settlements
PublicationThis paper delivers a probabilistic attempt to prove that the selection of a random three-dimensional finite element (FE) model of a subsoil affects the computed settlements. Parametricanalysis of a random soil block is conducted, assuming a variable subsoil Young’s modulus inparticular finite elements. The modulus is represented by a random field or different-sized setsof random variables; in both cases, the same truncated...
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Probabilistic estimation of diverse soil condition impact on vertical axis tank deformation
PublicationThe calculations of fuel tanks should take into account the geometric imperfections of the structure as well as the variability of the material parameters of the foundation. The deformation of the tank shell can have a significant impact on the limit state of the structure and its operating conditions. The paper presents a probabilistic analysis of a vertical-axis, floating-roof cylindrical shell of a tank with a capacity of 50000...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Probabilistic assessment of SMRFs with infill masonry walls incorporating nonlinear soil-structure interaction
PublicationInfill Masonry Walls (IMWs) are used in the perimeter of a building to separate the inner and outer space. IMWs may affect the lateral behavior of buildings, while they are different from those partition walls that separate two inner spaces. This study focused on the seismic vulnerability assessment of Steel Moment-Resisting Frames (SMRFs) assuming different placement of IMWs incorporating nonlinear Soil-Structure Interaction (SSI)....
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No apparent effect of invasive alien goldenrod on soil microbial communities or soil fauna feeding activity
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Assessment of soil microbial diversity measurements as indicators of soil functioning in organic and conventional horticulture systems
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Long-term effect of ZnO and CuO nanoparticles on soil microbial community in different types of soil
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Ionic Liquid Assisted Dissolution of Dissolved Organic Matter and PAHs from Soil Below the Critical Micelle Concentration
PublicationIncreased use and production of ionic liquids (ILs) may result in emissions into the environment. Particularly vulnerable are industrial areas and landfills where ILs are utilized and ultimately disposed of. This study investigates how IL contamination can affect soil properties and the sorption of pre-existing contaminants. The commonly used IL 1-methyl-3-octyl imidazolium chloride ([OMIM][Cl]) was added at various quantities...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublicationQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Seismic pounding between adjacent buildings: Identification of parameters, soil interaction issues and mitigation measures
PublicationStructural pounding has been observed in many previous earthquakes due to insufficient gap commonly provided between adjacent structures. The collisions usually generate large impact forces and short duration acceleration pulses which may result in significant damage to the colliding buildings. Because of that, earthquake induced structural pounding has been intensively studied and investigated for the last three decades. Results...
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Deep Learning Approaches in Histopathology
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Influence of soil anisotropic stiffness on the deformation induced by an open pit excavation.
PublicationIn this paper, the problem of deformation induced by an open pit excavation in anisotropic stiff soils is analysed by FE modelling. The presented research is focused on the influence of material model with anisotropic stiffness on the accuracy of deformation predictions as compared with the field measurements. A new hyperelastic-plastic model is applied to simulate anisotropic mechanical behaviour of stiff soils. It is capable...
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Extractive detoxification of hydrolysates with simultaneous formation of deep eutectic solvents
PublicationThe hydrolysis of lignocellulosic biomass results in the production of so-called fermentation inhibitors, which reduce the efficiency of biohydrogen production. To increase the efficiency of hydrogen production, inhibitors should be removed from aqueous hydrolysate solutions before the fermentation process. This paper presents a new approach to the detoxification of hydrolysates with the simultaneous formation of in-situ deep eutectic...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Charge-based deep level transient spectroscopy of B-doped and undoped polycrystalline diamond films
PublicationThe undoped and B-doped polycrystalline diamond thin film was synthesized by hot filament chemical vapor deposition and microwave plasma, respectively. The structural characterization was performed by scanning electron microscopy, X-ray diffraction and Raman spectroscopy. The electrical properties of synthesized diamond layer were characterized by dc-conductivity method and charge deep level transient spectroscopy. The B-doped...
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Purification of model biogas from toluene using deep eutectic solvents
PublicationBiogas from landfills and wastewater treatment facilities typically contain a wide range of volatile organic compounds (VOCs), that can cause severe operational problems when biogas is used as fuel. Among the contaminants commonly occur aromatic compounds, i.e. benzene, ethylbenzene, toluene and xylenes (BTEX). In order to remove BTEX from biogas, different processes can be used. A promising process for VOCs removal is their absorption...
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Some Aspects of Shear Behavior of Soft Soil–Concrete Interfaces and Its Consequences in Pile Shaft Friction Modeling
PublicationThis paper examines the stiffness degradation and interface failure load on soft soil–concrete interface. The friction behavior and its variability is investigated. The direct shear tests under constant normal load were used to establish parameters to hyperbolic interface model which provided a good approximation of the data from instrumented piles. Four instrumented piles were used to obtain reference soil–concrete interface behavior....
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Soil and groundwater fecal contamination as a result of sewage sludge land application.
PublicationThe release of sludge-born bacteria and their further transport in subsurface was studied. The migration of bacteria was investigated in column experiments which were carried out under the conditions corresponding to naturally occurring extreme rainfall. Coal fly ash as well as coarse and medium grained sand, which properties are similar to the soils present in degraded areas, were used as column beds. Sewage sludge was applied...
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Testing of the longest span soil-steel bridge in Europe – new quality in measurements
PublicationThe article describes interdisciplinary and comprehensive diagnostic tests of final bridge inspection and acceptance proposed for a soil – steel bridge made of corrugated sheets, being the European span length record holder (25.74 m). As an effect of an original concept a detailed and precise information about the structure response was collected. The load test design was based on the nonlinear numerical simulations performed by...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Study of a Flame Kernel Evolution in a Turbulent Mixing Layer Using LES with a Laminar Chemistry Model
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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LDFEM analysis of pore water pressure development in cohesive soil due to FDP auger drilling
PublicationThis paper presents the preliminary modelling of FDP auger drilling in soft soil with emphasis on excess pore water pressure (EPWP) development using CEL formulation and Abaqus software suit. The EPWP generation in single points is investigated and the results of a numerical analysis are compared with the field measurements. It is found that numerical model qualitatively reflects the field measurements. However,...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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OPTICAL STRAIN MEASUREMENT OF CONCRETE VERSUS MANUAL EXTENSOMETER MEASUREMENT BASED ON THE TEST RC DEEP BEAM IN A COMPLEX STATE OF STRESS
PublicationThe purpose of this study is to compare the strain measurement techniques of concrete in R-C element subjected to the monotonic load up to the failure. In the analysis manual extensometer methods of measurements and the optical system ARAMIS for non-contact three-dimensional measurements of deformation was used. The test sample was a cantilever deep beam loaded throughout the depth which was a part of the reinforced concrete deep...
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Soil mechanics and old buildings foundations
PublicationPraca dotyczy sposobów fundamentowania obiektów zabytkowych. Przeanalizowano historyczny rozwój sposobów posadowienia poczynając od starożytności, poprzez średniowiecze aż do czasów nowożytnych. Omówiono charakterystyczne dla kolejnych okresów historycznych rodzaje fundamentów. Przedstawiono przykłady dobrego i złego fundamentowania.
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Reasearch on reinforced soil and geosynthetics in Poland.
PublicationOmówienie badań wzmocnienia gruntu w Polsce zapoczątkowane w latach 70-tych w Katedrze Geotechniki Politechniki Gdańskiej i Instytucie Budownictwa Wodnego PAN w Gdańsku. Ponadto przedstawiono: badania tarcia w geomembranach teksturowanych; nośność wzmocnionego geotekstyliami podłoża gruntowego obciążonego fundamentem wyciąganym; badania na wyciąganie (''pull-out'') geogrydów wzmacniających podłoża.
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Soil improvement by short stone columns.
PublicationW artykule przedstawiono sposób dogęszczania podłoża gruntowego wykorzystywany do renowacji istniejących nawierzchni placów składowych i dróg. Proponowany sposób polega na formowaniu w gruncie kolumny o niewielkiej średnicy. Kolumnę tą formuje się poprzez wbijanie w rozluźnione podłoże trzpienia stalowego, z jednoczesnym dosypywaniem gruntu.Sposób ten stosuje się przede wszystkim jako metodę wzmocnienia podłoża pod nawierzchniami...
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On the mechanisms of soil remediation with use of surfactants
PublicationPrzedstawiono problem zanieczyszczenia gruntów substancjami olejowymi. Zaprezentowano metodę remediacji za pomocą przemywania roztworami surfaktantów. Omówiono mechanizmy biorące udział w usuwaniu zanieczyszczeń z gruntu podczas tego procesu.
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FE simulations of a soil structure interface.
PublicationPrzedstawiono warunki brzegowe do opisu szorstkości ściany konstrukcji w kontakcie z gruntem. Wykonano doświadczenia i symulacje MES na bazie mikropolarnego prawa hipoplastycznego.
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Deep eutectic solvents in analytical sample preconcentration Part B: Solid-phase (micro)extraction
PublicationOne of the key challenges of modern analytical chemistry is the monitoring of trace amounts of contaminants using sensitive and selective instrumental techniques. Due to the variety and complexity of some samples, it is often necessary to properly prepare a sample and to perform a preconcentration of trace amounts of analytes. In line with the principles of Green Analytical Chemistry (GAC), it is important for an analytical procedure...