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Wyniki wyszukiwania dla: Deep Eutectic Solvents
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Brain-Inspired Deep Networks for Facial Expression Recognition. Frontiers in Biomedical Technologies
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Herstellung von Dichtwaenden in alten Deichen mittels der Deep Mixing Method
PublikacjaOpisano zastosowanie metody wgłębnego mieszania gruntu na mokro do wykonania przesłon przeciw filtracyjnych w wałach przeciwpowodziowych Wisły i Rudawy. Przytoczono pierwsze przykłady zastosowania w Polsce, obejmujące budowy w Krakowie (3) oraz w Tarnobrzegu (1). W Krakowie wykonano przesłonę zbrojoną dwuteownikami w celu posadowienia murków oporowych umieszczonych na koronie wału. W okolicach Wawelu przesłona umożliwia ustawienie...
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A survey of automatic speech recognition deep models performance for Polish medical terms
PublikacjaAmong the numerous applications of speech-to-text technology is the support of documentation created by medical personnel. There are many available speech recognition systems for doctors. Their effectiveness in languages such as Polish should be verified. In connection with our project in this field, we decided to check how well the popular speech recognition systems work, employing models trained for the general Polish language....
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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The results of analyses of deep excavation walls using two different methods of calculation
PublikacjaPrzedstawiono wyniki obliczeń obudowy głębokiego wykopu dwukrotnie rozpieranej i dwukrotnie kotwionej w gruncie jednorodnym niespoistym. Obliczenia numeryczne wykonano metodą podpór sprężysto-plastycznych i metodą elementów skończonych. Zwrócono uwagę na istotne różnice w wynikach obliczeń. Zaproponowano wyjaśnienie przyczyn zaobserwowanych różnic w wynikach obliczeń otrzymanych z obu metod.
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Understanding the early-stage release of volatile organic compounds from rapeseed oil during deep-frying of tubers by targeted and omics-inspired approaches using PTR-MS and gas chromatography
PublikacjaDuring deep-frying, a plethora of volatile products is emitted with the fumes. These compounds could act as oil quality indicators and change the indoor air composition leading to health risks for occupants. The presented experiments focus on deep-frying of different tubers in rapeseed oil at different frying temperatures. Here, two scenarios for real-time monitoring of volatile organic compounds (VOCs) using proton transfer reaction...
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Use of Bioluminescence for Monitoring Brown Coal Mine Waters from Deep and Surface Drainage
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Increasing the Durability of Critical Parts in Heavy-Duty Industrial Machines by Deep Cryogenic Treatment
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Monitoring of deep foundation deflection in model experiments by means of a magnetic method: theoretical study.
PublikacjaZaproponowano oryginalną nieinwazyjną metodę pomiaru ugięcia pali bocznie obciążonych niespoistymi i małospoistymi gruntami suchymi lub wilgotnymi. Metoda ma zastosowanie do pomiaru ugięcia pali i ścian szczelnych oraz określania położenia innych fundamentów lub elementów zagłębionych w gruncie.
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine 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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Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine
PublikacjaAbstract— The aim of this work was to examine the potential of thermal imaging as a cost-effective tool for convenient, non- intrusive remote monitoring of elderly people in different possible head orientations, without imposing specific behavior on users, e.g. looking toward the camera. Illumination and pose invariant head tracking is important for many medical applications as it can provide information, e.g. about vital signs, sensory...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublikacjaThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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The effect of deep pectoral myopathy on the properties of broiler chicken muscles characterised by selected instrumental techniques
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Methylation of estrogen receptor 2 (ESR2) in deep paravertebral muscles and its association with idiopathic scoliosis
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Prediction of NOx Emission Based on Data of LHD On-Board Monitoring System in a Deep Underground Mine
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublikacjaShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Thermodynamic properties of inorganic salts in nonaqueous solvents. II. Apparent molar volumes and compressibilities of divalent transition-metal perchlorates in acetonitrile
PublikacjaW oparciu w wyniki pomiarów gęstości wykonanych w temperaturze 15,20,25,30,35,40 i 50 stopni Celsjusza oraz pomiaru szybkości dżwięku w temperaturze 25 stopni Celsjusza, wyznaczono pozorne objętości molowe oraz ściśliwości adiabatyczne roztworów nadchloranów manganu(II), kobaltu(II), niklu(II) i cynku(II). Obliczono odpowiednie wartości standardowe oraz rozszerzalności izobaryczne. Przeanalizowano związki między strukurą elektronową...
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Geochemical Changes in Aquatic Environment Caused by Deep Dredging - A Case Study: The Puck Bay (Baltic Sea)
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Abdominoplasty Skin-Based Dressing for Deep Wound Treatment—Evaluation of Different Methods of Preparation on Therapeutic Potential
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Microbial Diversity in Deep-Subsurface Hot Brines of Northwest Poland: from Community Structure to Isolate Characteristics
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublikacjaSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublikacjaThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublikacjaQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Thermodynamic properties of inorganic salt in nonaqeous solvents. IV. Apparent molar volumes and compressibilities of divalent transition-metal bromides and chlorides in acetonitrile
PublikacjaWykonano pomiary gęstości roztworów chlorków i bromków w acetonitrylu w temperaturze 288.15, 293.15, 298.15, 303.15, 308.15, 313.15 K oraz pomiar szybkości rozchodzenia się dźwięku w badanych roztworach w temperaturze 298.15 K. Uzyskane wartości pozwoliły wyznaczyć pozorne objętości molowe oraz pozorne adiabatyczne ściśliwości, których wartości oraz zmiany ze stężeniem tłumaczone są obecnością złożonych układów komplesów w roztworze.
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Deep analysis of Loop L1 HVRs1-4 region of the hexon gene of adenovirus field strains isolated in Poland
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Pore water alkalinity below the permanent halocline in the Gdańsk Deep (Baltic Sea) - Concentration variability and benthic fluxes
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Deep submarine groundwater discharge indicated by pore water chloride anomalies in the Gulf of Gdańsk, southern Baltic Sea
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Association of LBX1 Gene Methylation Level with Disease Severity in Patients with Idiopathic Scoliosis: Study on Deep Paravertebral Muscles
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Thermodynamic properties of inorganic salts in nonaqueous solvents. V. Apparent molar volumes and compressibilities of divalent transition metal bromides in N,N-dimethylformamide
PublikacjaZmierzono gęstości i szybkości rozchodzenia się dźwięku roztworów bromków dwuwartościowych metali przejściowych w N,N-dimetyloformamidzie. W oparciu o uzyskane parametry wyznaczono pozorne objętości i ściśliwości molowe. Dokonano analizy oraz zbadano wpływ kompleksowania na wyznaczone wielkości.
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Thermodynamic properties of inorganic salts in nonaqueous solvents. III. Apparent molar volumes and compressibilities of divalent transition-metal chlorides in N,N-dimethylformamide
PublikacjaZmierzono gęstości i szybkości dźwięku dla roztworów chlorków dwuwartościowych metali przejściowych w N,N-dimetyloformamidzie. W oparciu o uzyskane wyniki wyznaczono pozorne objętości molowe, cząstkowe objętości molowe, rozszerzalności izobaryczne oraz ściśliwości adiabatyczne. Dokonano analizy oraz zbadano wpływ kompleksowania na wyznaczone wielkości.
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Thermodynamic properties of inorganic salts in nonaqueous solvents. I. Apparent molar volumes and compressibilities of divalent transition-metal perchlorates in N,N-dimethylformamide.
PublikacjaZmierzono gęstości i szybkość dźwięku dla roztworów nadchloranów dwuwartościowych metali przejściowych w N,N-dimetyloformamidzie. W oparciu o uzyskane wyniki wyznaczono pozorne objętości molowe, cząstkowe objętości molowe, rozszerzalności izobaryczne oraz ściśliwości adiabatyczne. Dokonano analizy oraz zbadano wpływ rodzaju kationu metalu.
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Thermodynamic Properties of Inorganic Salts in Nonaqueous Solvents. VI. Apparent Molar Volumes, Expansibilities, and Compressibilities of Divalent Transition Metal Ions in Methanol and Dimethylsulfoxide
PublikacjaThe temperature dependence of the density of divalent transition metal perchlorates in dimethylsulfoxide as well as cobalt(II), nickel(II) perchlorates, and copper(II) trifluoromethanesulfonate in methanol was determined. Moreover, sound velocities for solutions of cobalt(II), nickel(II) perchlorates, and copper(II) trifluoromethanesulfonate in methanol have been measured at 298.15 K. From these data, the partial molar volumes,...
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STUDY IN MECHANICAL FAULT ELEMENT THERMOGRAPHY THROUGH THE MACHINE: The case of deep groove ball bearings of a career without screen.
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Proline, glutamic acid, and leucine rich protein 1 (PELP1) expression in deep paravertebral muscles in idiopathic scoliosis girls
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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Deep insight into the pore size distribution of N-doped porous carbon materials on electrochemical energy storage and CO2 sorption
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On-line assessment of oil quality during deep frying using an electronic nose and proton transfer reaction mass spectrometry
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Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning
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The origin and mobilization of deep brines to the aquifer system by considering the circulation systems existing on the polish western coast of the Baltic sea
PublikacjaW pracy przedstawiono stan wód podziemnych w przybrzeżnych warstwach wodonośnych polskiego wybrzeża Bałtyku. Obliczono czas przebywania wód odpływających do Bałtyku. Wiek wód i czas przebywania oszacowano również za pomocą izotopów środowiskowych.
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Heterogeneous distribution of surface electrochemical activity in polycrystalline highly boron-doped diamond electrodes under deep anodic polarization
PublikacjaThe surface homogeneity of boron-doped diamond electrodes is variable and depends on anodic polarization conditions. The differentiation factor is the gradual and localized change in surface termination. A series of measurements under different polarization conditions was performed in order to investigate the scale of this effect. Nanoscale impedance microscopy (NIM) revealed large variation of surface resistance in individual...
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Sleep assessment in obsessive-compulsive disorder treated with deep brain stimulation - double case report of morning and evening chronotype patients
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The influence of combination of binding agents on fatigue properties of deep cold in-place recycled mixtures in Indirect Tensile Fatigue Test (ITFT)
PublikacjaThe publication presents fatigue properties of cold recycled mixtures for eight combinations of binding agents (cement and bituminous emulsion). Cold recycled mixtures were evaluated in Indirect Tensile Fatigue Test (ITFT) at the temperature of 20 C in controlled stress mode. As a function of horizontal stress, fatigue life is strongly influenced by combination of the binding agents. When fatigue life is analyzed as a function...
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland—Swietokrzyskie Voivodeship
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