displaying 1000 best results Help
Search results for: Deep soil mixing
-
Simulation of Residence Time Distribution and Mixing in Reactors with Recirculation Using 2D Approach
PublicationIn this paper, we propose a 2D approach in order to create a mathematical model for the determination of the residence time distribution for a flow reactor with recirculation. Apart from characterizing the functional residence time distribution, this model can help improve the operation of the reactor at the design stage. The mathematical model was validated by comparison with experiments carried out in a hydraulic laboratory.
-
Application of deep eutectic solvents in atomic absorption spectrometry
PublicationAtomic absorption spectrometry (AAS) is a widely applied technique for metal quantification due to its practicality, easy use and low cost. However, to improve the metrological characteristics of AAS, in particular the sensitivity and the detection limit, sample pretreatment is commonly used before the detection step itself. In consideration of the principles of Green Analytical Chemistry, new solvents are being introduced into...
-
Catabolic response and phospholipid fatty acid profiles as microbial tools to assess soil functioning
Publication -
Incremental dynamic analysis and fragility assessment of buildings founded on different soil types experiencing structural pounding during earthquakes
PublicationThe effect of the soil type on buildings experiencing pounding during earthquakes is investigated in this study using the incremental dynamic analysis and fragility assessment methods. Three 3-D structures with different number of storeys (4, 6 and 8) were considered in this study. Three pounding scenarios between these three buildings were taken into account, i.e. pounding between 4-storey and 6-storey buildings, between 4-storey...
-
Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
-
Nutrients, oxygen and suspended matter - Gdansk Deep (2001-2005)
Open Research DataThe results show short-term changes in the concentration of nutrients (nitrates, nitrites, ammonium ions, phosphates and total forms of nitrogen and phosphorus), dissolved oxygen and suspended particulate matter - SPM and its main components (organic carbon - POC, nitrogen - PON, phosphorus - TPP) in the water column of the Gdańsk Deep (Gdańsk Bay).
-
A comparison of indexing methods to evaluate quality of horticultural soils. Part II. sensitivity of soil microbiological indicators
Publication -
Application of discrete wavelet transform in seismic nonlinear analysis of soil–structure interaction problems
PublicationSimulation of soil-structure interaction (SSI) effects is a time-consuming and costly process. However, ignoring the influence of SSI on structural response may lead to inaccurate results, especially in the case of seismic nonlinear analysis. In this paper, wavelet transform methodology has been utilized for investigation of the seismic response of soil-structure systems. For this purpose, different storey outrigger braced buildings...
-
Numerical Modelling for Prediction of Compression Index from Soil Index Properties in Jimma town, Ethiopia
PublicationIn this study, correlations are developed to predict compression index (Cc) from index parameters so that one can be able to model Jimma soils with compression index using simple laboratory tests. Undisturbed and disturbed soil samples from twelve different locations in Jimma town were collected. Laboratory tests like specific gravity, grain size analysis, Atterberg limit, and one-dimensional consolidation test for a total of twenty-four...
-
SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublicationThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
-
Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
-
Challenges and Possibilities of Deep Eutectic Solvent-Based Membranes
PublicationDeep eutectic solvents (DES) are a category of a new class of solvents that can overcome some of the main drawbacks of typical solvents and ionic liquids (ILs). DES have been widely investigated and applied by the research community in several applications since their invention. Over the past years, the use of DES has been directed to the production of new materials and items for new products and processes. This is the case for...
-
Natalia Anna Wójcik dr hab. inż.
People -
Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
-
Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
-
Behaviour of Colliding Multi-Storey Buildings under Earthquake Excitation Considering Soil-Structure Interaction
PublicationThis paper investigates the coupled effect of the supporting soil flexibility and pounding between neighbouring, insufficiently separated buildings under earthquake excitation. Two adjacent three-storey structures, modelled as inelastic lumped mass systems with different structural characteristics, have been considered in the study. The models have been excited using the time history of the Kobe earthquake of 1995. A nonlinear...
-
Sorbents modified by deep eutectic solvents in microextraction techniques
PublicationIn recent years, considerable attention has been directed towards the employment of green solvents, specifically deep eutectic solvents (DES), in liquid phase microextraction techniques. However, comprehensive and organized knowledge regarding the modification of sorbent surface structures with DES remains limited. Therefore, this paper reviews the application of DES in modifying and improving the properties of sorbents for microextraction...
-
Numerical Study on Seismic Response of a High-Rise RC Irregular Residential Building Considering Soil-Structure Interaction
PublicationThe objective of the present study is to investigate the importance of soilstructure interaction effects on the seismic response of a high-rise irregular reinforced-concrete residential building. In order to conduct this research, a detailed three-dimensional structure model was subjected to various earthquake excitations, also including a strong mining tremor. Soil-foundation flexibility was represented using the spring-based...
-
Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublicationThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
-
Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
-
Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublicationIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
-
Effective Equations for the Optimum Seismic Gap Preventing Earthquake-Induced Pounding between Adjacent Buildings Founded on Different Soil Types
PublicationThe best approach to avoid collisions between adjacent structures during earthquakes is to provide sufficient spacing between them. However, the existing formulas for calculating the optimum seismic gap preventing pounding were found to provide inaccurate results upon the consideration of different soil types. The aim of this paper is to propose new equations for the evaluation of the sufficient in-between separation gap for buildings...
-
Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
-
Soil chemical properties affect the reaction of forest soil bacteria to drought and rewetting stress
Publication -
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...
-
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...
-
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...
-
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...
-
Microbiological condition of sediments and bottom water in the area of Gdańsk Deep in Gulf of Gdańsk
Open Research DataThis dataset contains the results of microbiological analysis of bottom water and bottom sediments in the area of Gdańsk Deep in Gulf of Gdańsk. The tested samples were collected at 5 sites on 15th of December 2007. 5 samples of bottom water and 10 samples of sediments were collected for microbiological testing. Each of these samples were analysed for...
-
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...
-
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...
-
Soil enzymes in a changing climate
Publication -
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
Suspended matter, composition and fluxes, Gdansk Deep, late spring 2001
Open Research DataParticulate organic carbon (POC) and nitrogen (PON) concentrations and fluxes were measured in the Gdańsk Deep (Gulf of Gdansk) from 30.05 to 06.06.2001. The vertical profiles of POC and PON were characterised by the highest values in the euphotic layer, a gradual decrease with depth, and an increase below the halocline. The hydrophysical conditions...
-
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)....
-
No apparent effect of invasive alien goldenrod on soil microbial communities or soil fauna feeding activity
Publication -
Assessment of soil microbial diversity measurements as indicators of soil functioning in organic and conventional horticulture systems
Publication -
Long-term effect of ZnO and CuO nanoparticles on soil microbial community in different types of soil
Publication -
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...
-
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...
-
Angelika Duszyńska dr inż.
PeopleAbsolwentka kierunku Budownictwo Wodne Wydziału Hydrotechniki Politechniki Gdańskiej, doktor nauk technicznych w dziedzinie Geotechnika, nauczyciel akademicki (od 2020 roku pracuje na stanowisku profesora uczelni na wydziale Inżynierii Lądowej i Środowiska PG). Prowadzi zajęcia z przedmiotów: Geoinżynieria, Geotechnika, Budowle Ziemne i Wzmacnianie podłoża, Geosyntetyki w Budownictwie, Budowle Hydrotechniczne. Od ponad 20 lat...
-
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....
-
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...
-
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...