Wyniki wyszukiwania dla: covid-19, x-ray images, deep learning, convolutional neural network
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Evaluation of the Cathodic Electrodeposition Effectiveness of the Hydroxyapatite Layer Used in Surface Modification of Ti6Al4V-Based Biomaterials
PublikacjaThe important issue associated with the design and the fabrication of the titanium and titanium alloy implants is the increase of their biointegration with bone tissue. In the presented paper, the research results concerning the conditions used in the cathodic deposition of hydroxyapatite on the surface Ti6Al4V substrates primarily modified by the production of TiO2 nanoporous coatings, TiO2 nanofibers, and titanate coatings, are...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Conversion of waste biomass into activated carbon and evaluation of environmental consequences using life cycle assessment
PublikacjaIn this article, activated carbon was produced from Lantana camara and olive trees by H3PO4 chemical activation. The prepared activated carbons were analyzed by characterizations such as scanning electron microscopy, energy-dispersive X-ray spectroscopy, Brunauer–Emmett–Teller, X-ray diffraction, thermogravimetric analysis, and Fourier transform infrared spectroscopy. H3PO4 is used as an activator agent to create an abundant pore...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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EXPERIMENTAL AND NUMERICAL INVESTIGATIONS OF CONCRETE BEHAVIOUR AT MESO-LEVEL DURING QUASI-STATIC SPLITTING TENSION
PublikacjaThe paper describes experimental and numerical results of quasi-static splitting tensile tests on concrete specimens at meso-scale level. The loading strip was made of plywood or steel. Fracture in concrete was detected at the aggregate level by means of three non-destructive methods: 3D x-ray micro-computed tomography, 2D scanning electron microscope and manual 2D digital microscope. The discrete element method was used to directly...
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Novel Tools as New Challenges to HRM Communicational Practices (and the Increasingly Important Social Role of the Manager)
PublikacjaEach communicational process consists inseparably of three aspects: the linguistic (which means the whole language content of the message), technical (which states the form of the message) and the social (meaning social relations, emotions, behaviours). The recent COVID-19 pandemic deeply influenced several layers of our lives. But the main aim of this chapter is to focus on the communicational processes that normally take place...
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LDRAW based renders of LEGO bricks moving on a conveyor belt with extracted models
Dane BadawczeThe set contains renders of LEGO bricks moving on a white conveyor belt. The images were prepared for training neural network for recognition of LEGO bricks. For each brick starting position, alignment and color was selected (simulating the brick falling down on the conveyour belt) and than 10 images was created while the brick was moved across the...
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Structure and paramagnetism in weakly correlated Y8Co5
PublikacjaWe report the basic physical properties of monoclinic Y8Co5 determined by means of magnetic susceptibility, electrical resistivity, and specific heat measurements. The crystal structure of Y8Co5 is monoclinic (P21/c) with lattice parameters a = 7.0582(6) Å, b = 7.2894(6) Å, c = 24.2234(19) Å, and β = 102.112(6)° as refined by using synchrotron powder x-ray diffraction data. The compound shows temperature independent paramagnetism...
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Bis(ammonium) Zoledronate Dihydrate
PublikacjaNeutralization of 2-(1-imidazole)-1-hydroxyl-1,1`-ethylidenediphosphonic acid (zoledronic acid) by an excess of ammonia yielded bis(ammonium) zoledronate dihydrate, {C5H8N2O7P2 2−, 2(H4N+), 2(H2O)}. The product is readily soluble in water and forms monocrystals for which the X-ray structural analysis was carried out. The zoledronic anion is of double negative charge due to deprotonation of three P–OH groups and protonation of the...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublikacjaAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublikacjaAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Changes in psychological distress among Polish medical university teachers during the COVID-19 pandemic
PublikacjaOur study aims to update knowledge about psychological distress and its changes in the Polish group of academic medical teachers after two years of a global pandemic. During the coronavirus disease, teachers were challenged to rapidly transition into remote teaching and adapt new assessment and evaluation systems for students, which might have been...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Discrete element method simulations of fracture in concrete under uniaxial compression based on its real internal structure
PublikacjaThe paper describes experimental and numerical results of concrete fracture under quasi-static uniaxial compression. Experimental uniaxial compression tests were performed on concrete cubic specimens. Fracture in concrete was detected at the aggregate level by means of three non-destructive methods: three-dimensional X-ray microcomputed tomography, two-dimensional scanning electron microscope and manual two-dimensional digital...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublikacjaThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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LDRAW based renders of LEGO bricks moving on a conveyor belt
Dane BadawczeThe set contains renders of 5237 LEGO bricks moving on a white conveyor belt. The images were prepared for training neural network for recognition of LEGO bricks. For each brick starting position, alignment and color was selected (simulating the brick falling down on the conveyour belt) and than 10 images was created while the brick was moved across...
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Transmission electron microscope (TEM) and optical microscope images of pristine and silica-coated bismuth oxide and gadolinium oxide particles
Dane BadawczeCollection of raw transmission electron microscope (TEM) micrographs and optical microscope images used in the associated manuscript. All data in accessible *.tif format. Zip package contains:
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Nanocrystallization as a tool for controlling in vitro dissolution of borophosphate glass
PublikacjaThe controlled nanocrystallization of sodium-calcium-borophosphate glass (Na16.6Ca5.1B10.5Al0.8P10.5 O56.5 in at %) was conducted to investigate its influence on in vitro dissolution. Three temperatures (570 ◦C, 590 ◦C, and 610 ◦C) were selected based on thermal analysis and investigation of the morphology, structure, and in vitro dissolution of glass and glass-ceramics was conducted. The results of X-ray diffraction confirmed...
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Elective Project I _ Shelter_learning by doing
Kursy OnlineElective Project I _ Shelter - learning by doing “Your creativity and skills play an important role in making an impact in responding to humanitarian challenges and global crises” The world seems to be reeling from one crisis to another. Recently we experienced climate crises, global pandemic (Covid-19), economic uncertainty, wars, floods, wildfire, and earthquakes. Proceeding from the challenges facing humanity at the global...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Silica Gel Impregnated by Deep Eutectic Solvents for Adsorptive Removal of BTEX from Gas Streams
PublikacjaThe paper presents the preparation of new adsorbents based on silica gel (SiO2) impregnated with deep eutectic solvents (DESs) to increase benzene, toluene, ethylbenzene, and p-xylene (BTEX) adsorption efficiency from gas streams. The DESs were synthesized by means of choline chloride, tetrapropylammonium bromide, levulinic acid, lactic acid, and phenol. The physico-chemical properties of new sorbent materials, including surface...
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Comparative study on the effectiveness of various types of road traffic intensity detectors
PublikacjaVehicle detection and speed measurements are crucial tasks in traffic monitoring systems. In this work, we focus on several types of electronic sensors, operating on different physical principles in order to compare their effectiveness in real traffic conditions. Commercial solutions are based on road tubes, microwave sensors, LiDARs, and video cameras. Distributed traffic monitoring systems require a high number of monitoring...
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Deep learning-based waste detection in natural and urban environments
PublikacjaWaste 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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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublikacjaData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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Developing Polycentricity to Shape Resilient Metropolitan Structures: The Case of the Gdansk–Gdynia–Sopot Metropolitan Area
PublikacjaMaking the metropolitan area resilient, in many cases, calls for amending its spatial structures. This may take various forms, including both reshaping the metropolitan core and redeveloping the entire regional network of cities and centres, making them part of a coherent structure. The latter strategy is associated with reinforcing secondary urban centres as well as shaping new connections between them. In this case, the term...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Smartphones as tools for equitable food quality assessment
PublikacjaBackground: The ubiquity of smartphones equipped with an array of sophisticated sensors, ample processing power, network connectivity and a convenient interface makes them a promising tool for non-invasive, portable food quality assessment. Combined with the recent developments in the areas of IoT, deep learning algorithms and cloud computing, they present an opportunity for advancing wide-spread, equitable and sustainable food...
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Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublikacjaNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
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Superhydrophobic sponges based on green deep eutectic solvents for spill oil removal from water
PublikacjaThe paper described a new method for crude oil-water separation by means of superhydrophobic melamine sponges impregnated by deep eutectic solvents (MS-DES). Due to the numerous potential of two-component DES formation, simple and quick screening of 156 non-ionic deep eutectic solvents using COSMO-RS (Conductor-like Screening Model for Real Solvents) computational model was used. DES which were characterized by high solubility...
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The influence of Be addition on the structure and thermal properties of alkali-silicate glasses
PublikacjaBe-Na-(Li)-Si oxide glasses containing up to 15 mol% of BeO were prepared. Their structure was characterized by X-ray powder diffraction and Raman as well as infrared spectroscopic techniques, while their chemical compositions were examined by Inductively Coupled Plasma Optical Emission Spectrometry. All materials were found to be amorphous and contain Al contaminations from minor dissolution of the alumina crucibles. The results...
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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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Evolution of Ag nanostructures created from thin films: UV–vis absorption and its theoretical predictions
PublikacjaAg-based plasmonic nanostructures were manufactured by thermal annealing of thin metallic films. Structure and morphology were studied using scanning electron microscopy (SEM), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS). SEM images show that the formation of nanostructures is influenced by the initial layer thickness as well as the...
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Nano soil improvement technique using cement
PublikacjaNano soil-improvement is an innovative idea in geotechnical engineering. Nanomaterials are among the newest additives that improve soil properties. Herein, laboratory tests, such as unconfined compressive strength, direct shear test, and initial tests, were conducted to investigate the geotechnical properties of Kelachay clay with micro- and nanosized cement to evaluate its particles in untreated soil and observe changes in the...
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublikacjaThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Influence of synthesis conditions on glass formation, structure and thermal properties in the Na 2 O-CaO-P 2 O 5 system doped with Si 3 N 4 and Mg
PublikacjaOxynitride phosphate glasses and glass-ceramics were prepared using new synthesis routes for phosphate glasses. Materials were melted from pre-prepared glass samples in the system Na-Ca-P-O with addition of Mg and/or Si3N4 powders under different preparation conditions. The melting process was conducted at 1000–1500 °C either under air or nitrogen atmosphere to obtain materials with different nitrogen content. Their topography...
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Raman investigation of the patina layers on Hungarian copper ingots from a fifteenth century shipwreck
PublikacjaWe report results of the patina study of underwater archeological finding ofmedieval copper objects performed by means of the Raman and complementary spectroscopic techniques. The objects were found submerged in the sea as cargo part of the ship which sunk in the Gulf of Gdańsk in 1408. The excavated collection consists of 230 oval ingots of the size and mass up to about 60 cm and 18 kg (total of 2 tons), respectively. In the Raman...
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Fabrication of the cross-linked PVA/TiO2/C nanocomposite membrane for alkaline direct methanol fuel cells
PublikacjaA crosslinked Poly(vinyl alcohol) based composite membrane was developed through a phase inversion process for use in alkaline direct methanol fuel cells (ADMFCs). The titanium dioxide (TiO2) and carbon nanoparticles (NPs) have been incorporated into the PVA polymer matrix to improve the mechanical and thermal properties. The membrane samples were further modified with maleic acid, a carboxylic acid acting as the cross-linker,...
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EVALUATION OF LIQUID-GAS FLOW IN PIPELINE USING GAMMA-RAY ABSORPTION TECHNIQUE AND ADVANCED SIGNAL PROCESSING
PublikacjaLiquid-gas flows in pipelines appear in many industrial processes, e.g. in the nuclear, mining, and oil industry. The gamma-absorption technique is one of the methods that can be successfully applied to study such flows. This paper presents the use of thegamma-absorption method to determine the water-air flow parameters in a horizontal pipeline. Three flow types were studied in this work: plug, transitional plug-bubble,...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublikacjaFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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Vehicle detector training with minimal supervision
PublikacjaRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...
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Narzędzia i metody obliczeń z użyciem MATLABa
WydarzeniaDn. 19.03.2020 w godz. 10.00–13.15 na Politechnice Gdańskiej odbędzie się seminarium w języku angielskim poświęcone wykorzystaniu MATLABa w badaniach naukowych i dydaktyce.
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Silica-Based Ionogels: Nanoconfined Ionic Liquid-Rich Fibers for Headspace Solid-Phase Microextraction Coupled with Gas Chromatography–Barrier Discharge Ionization Detection
PublikacjaIn this work, hybrid silica-based materials with immobilized ionic liquids (ILs) were prepared by sol–gel technology and evaluated as solid-phase microextraction (SPME) fiber coatings. High loadings of the IL 1-methyl-3-butylimidazolium bis(trifluoromethylsulfonyl)imide ([C4MIM][TFSI]) were confined within the hybrid network. Coatings composition and morphology were evaluated using scanning electron microscopy and energy dispersive...
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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublikacjaGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...