Search results for: DEEP EUTECTIC SOLVENTS
-
Akustyczna analiza parametrów ruchu drogowego z wykorzystaniem informacji o hałasie oraz uczenia maszynowego
PublicationCelem rozprawy było opracowanie akustycznej metody analizy parametrów ruchu drogowego. Zasada działania akustycznej analizy ruchu drogowego zapewnia pasywną metodę monitorowania natężenia ruchu. W pracy przedstawiono wybrane metody uczenia maszynowego w kontekście analizy dźwięku (ang.Machine Hearing). Przedstawiono metodologię klasyfikacji zdarzeń w ruchu drogowym z wykorzystaniem uczenia maszynowego. Przybliżono podstawowe...
-
Vertical Temperature Stratification of the Gulf of Gdansk Water
PublicationThe Baltic Sea is characterized by variable hydroacoustic conditions, which depend on hydrological conditions throughout the year. The temperature of the water is the factor that has the greatest impact on the changes in the speed of the sound in this basin. Even at a small depth, we can observe a large temperature gradient affecting the accuracy of the conducted research using hydroacoustic devices. A characteristic feature of...
-
Enabling Deeper Linguistic-based Text Analytics – Construct Development for the Criticality of Negative Service Experience
PublicationSignificant progress has been made in linguistic-based text analytics particularly with the increasing availability of data and deep learning computational models for more accurate opinion analysis and domain-specific entity recognition. In understanding customer service experience from texts, analysis of sentiments associated with different stages of the service lifecycle is a useful starting point. However, when richer insights...
-
Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublicationWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
-
Long Distance Vital Signs Monitoring with Person Identification for Smart Home Solutions
PublicationAbstract— Imaging photoplethysmography has already been proved to be successful in short distance (below 1m). However, most of the real-life use cases of measuring vital signs require the system to work at longer distances, to be both more reliable and convenient for the user. The possible scenarios that system designers must have in mind include monitoring of the vital signs of residents in nursing homes, disabled people, who...
-
Metal dusting phenomena of 501 AISI furnace tubes in refinery fractional distillation unit
PublicationThe purpose of this investigation was to conduct the failure analysis of 501 AISI furnace tubes places before distillation column in fractional distillation unit. The investigated furnace tubes were planned to work for ten years however after just two years of exploitation <30% of the material left. The observed corrosion process had the intense and complex character. The well-adhered shiny black deposits and deep, round pits were...
-
Propagation of Acoustic Disturbances in Shallow Sea
PublicationPropagation of acoustic waves in shallow sea differs fundamentally from the same phenomenon occurring in deep sea in view of non-negligible distance from the sea bottom in the first case, where presence of two regions limiting the water layer results in the acoustic pressure distribution induced by a harmonic source has an interferential nature as a result of multi-path propagation of the acoustic signal. These interferential properties...
-
Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublicationCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
-
Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
-
Autoencoder application for anomaly detection in power consumption of lighting systems
PublicationDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
-
Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublicationRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
-
Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublicationRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
-
Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublicationPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
-
Robustness in Compressed Neural Networks for Object Detection
PublicationModel compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving...
-
BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublicationDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
-
Sathwik Prathapagiri
PeopleSathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
-
Mohsan Ali Master of Science in Computer Science
PeopleMohsan Ali is a researcher at the University of the Aegean. He won the Marie-Curie Scholarship in 2021 in the field of open data ecosystem (ODECO) to pursue his PhD degree at the University of the Aegean. Currently, he is working on the technical interoperability of open data in the information systems laboratory; this position is funded by ODECO. His areas of expertise are open data, open data interoperability, data science, natural...
-
Wpływ rodzaju zanieczyszczenia powierzchni odlewu ze staliwa LH14 na jakość napoin wykonanych elektrodą otuloną
PublicationNapawanie jest szeroko stosowaną metodą naprawiania powierzchni. Pozwala między innymi na uzupełnienie miejsc, w których uprzednio wystąpiły wżery korozyjne. Techniki napawania wykorzystywane są również do przywracania pierwotnego kształtu zużytych części. W pracy wykonano badania napoin wykonanych elektrodami otulonymi na czołowych powierzchniach cylindrycznych próbek ze staliwa LH14. Proces wykonywano dwoma rodzajami elektrod:...
-
Medical Image Dataset Annotation Service (MIDAS)
PublicationMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
-
Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublicationThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
-
Text Mining Algorithms for Extracting Brand Knowledge; The fashion Industry Case
PublicationBrand knowledge is determined by customer knowledge. The opportunity to develop brands based on customer knowledge management has never been greater. Social media as a set of leading communication platforms enable peer to peer interplays between customers and brands. A large stream of such interactions is a great source of information which, when thoroughly analyzed, can become a source of innovation and lead to competitive advantage....
-
Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublicationNon-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...
-
Coherent-wave Monte Carlo method for simulating light propagation in tissue
PublicationSimulating propagation and scattering of coherent light in turbid media, such as biological tissues, is a complex problem. Numerical methods for solving Helmholtz or wave equation (e.g. finite-difference or finite-element methods) require large amount of computer memory and long computation time. This makes them impractical for simulating laser beam propagation into deep layers of tissue. Other group of methods, based on radiative...
-
Effect of Thermal Treatment and Erosion Aggressiveness on Resistance of S235JR Steel to Cavitation and Slurry
PublicationS235JR steel is used in many applications, but its resistance to the erosion processes has been poorly studied. To investigate this resistance, cavitation, and slurry erosion tests were conducted. These tests were carried out at different erosion intensities, i.e., different flow rates in the cavitation tunnel with a system of barricades and different rotational speeds in the slurry pot. The steel was tested as-received and after...
-
Smartphones as tools for equitable food quality assessment
PublicationBackground: 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...
-
Preparation and characterization of TiO2 nanostructures for catalytic CO2 photoconversion
PublicationThe titanium dioxide target (99.7%) of 1 cm in dia was ablated in vacuum by laser pulses(6 ns) at 266 nm and at repetition rate of 10 Hz. During deposition the laser fluence between 1 and 3.5 J/cm2 and the O2 pressure from the range of 10-2 - 1 Pa were applied. The thin TiO2 films were deposited on glass substrate (1 × 1 cm2) heated up to 500 °C. The chemical composition of the film and samples produced by annealing were investigated...
-
The Processing Procedure for the Interpretation of Microseismic Signal Acquired from a Surface Array During Hydraulic Fracturing in Pomerania Region in Poland
PublicationHydraulic fracturing is a procedure of injecting high pressure fluid into the wellbore in order to break shell rock and facilitate gas flow. It is a very costly procedure and, if not conducted properly, it may lead to environmental pollution. To avoid costs associated with pumping fluid outside the perspective (gas rich) zone and improve one’s knowledge about the reservoir rock, microseismic monitoring can be applied. The method...
-
Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
-
Application of soil nailing technique for protection and preservation historical buildings
PublicationSoil nailing is one of the recent in situ techniques used for soil improvement and in stabilizing slopes. The process of soil nailing consists of reinforcing the natural ground with relatively small steel bars or metal rods, grouted in the pre-drilled holes. This method has a wide range of applications for stabilizing deep excavations and steep slopes. Soil nailing has recently become a very common method of slope stabilisation...
-
Bacterial community succession in an Arctic lake–stream system (Brattegg Valley, SW Spitsbergen)
PublicationThe factors affecting prokaryotic and virus structure dynamics and bacterial commu-nity composition (BCC) in aquatic habitats along a ca. 1500 m of the Brattegg Valley lake–stream system (SW Spitsbergen) composed of three postglacial lakes created by Brattegg Glacier meltwater were examined. A high number of small-volume prokaryotic cells were found in the recently-formed, deep, upper,...
-
Distortion of speech signals in the listening area: its mechanism and measurements
PublicationThe paper deals with a problem of the influence of the number and distribution of loudspeakers in speech reinforcement systems on the quality of publicly addressed voice messages, namely on speech intelligibility in the listening area. Linear superposition of time-shifted broadband waves of a same form and slightly different magnitudes that reach a listener from numerous coherent sources, is accompanied by interference effects...
-
Endohedral gallide cluster superconductors and superconductivity in ReGa5
PublicationWe present transition metal-embedded (T@Gan) endohedral Ga clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2 Ga9 are all previously known superconductors. The well-known exotic superconductor...
-
Damage of a post-tensioned concrete bridge – Unwanted cracks of the girders
PublicationThe cracking of a post-tensioned T-beam superstructure, which was built using the incremental launching method, is analyzed in the paper. The problem is studied in detail, as specific damage was observed in the form of longitudinal cracks, especially in the mid-height zone of the girder at the interface of two assembly sections. The paper is a case study. A detailed inspection is done and non-destructive testing results of the...
-
Mussel‐inspired biomaterials: From chemistry to clinic
PublicationAfter several billions of years, nature still makes decisions on its own to identify, develop, and direct the most effective material for phenomena/challenges faced. Likewise, and inspired by the nature, we learned how to take steps in developing new technologies and materials innovations. Wet and strong adhesion by Mytilidae mussels (among which Mytilus edulis—blue mussel and Mytilus californianus—California mussel are the most...
-
Effect of Polymerization Statistics on the Electronic Properties of Copolymers for Organic Photovoltaics
PublicationStatistical block copolymers, composed of donor (D) and acceptor (A) blocks, are a novel type of material for organic photovoltaics (OPVs) devices. In particular a new series of polymers based on PBTZT-stat-BDTT-8, recently developed by Merck, offers high solubility in different solvents, and a high power conversion efficiency (PCE) in different device architectures. Although it is known that the electronic properties of these...
-
Miniaturized solid phase microextratcion
PublicationWithout any doubt analytical laboratories have an essential role in environmental protection due to the fact that they takes an active part in the monitoring pollutants present in air, water or soil. From the other side, the analytical activity is involved in the generation of toxic waste what is associated with the use of not eco-friendly reagents and solvents. For these reasons, green analytical chemistry (GAC) was introduced...
-
Structure and properties comparison of poly(ether-urethane)s based on nonpetrochemical and petrochemical polyols obtained by solvent free two-step method
PublicationThe application of thermoplastic polyurethanes (TPU) is becoming more and more extensive, and the decreasing of used petrochemical monomers and reduction of energy for the polymerization and processing processes is getting increasingly important. In this paper, we confirmed the positive influence of high bio-based monomers contents (by replacing petrochemical polyol and glycol by bio-based counterparts) on processing and properties...
-
A Green Chemistry "environmentally friendly" approach to the synthesis of chloro-intermediates of ephedrine/pseudoephedrine
PublicationMethylamphetamine is an addictive stimulant drug that strongly activates certain systems in the brain. It is closely related chemically to amphetamine, but the central nervous system effects of methamphetamine are greater. There is much interest in methylamphetamine among scientists and therefore the synthesizes of methylamphetamine and its metabolites are carried out on a large scale in chemical laboratories. Globally, ephedrine...
-
Application of dispersive liquid - liquid microextraction for determination of pesticides from various chemical groups in water samples
PublicationPesticides are a global risk because they move with the wind, rain and sea currents from other regions, which makes getting to places which were never used before. Their presence was detected in all types of water circulating in the ecosystem, which is an easy source of exposure to life and health of all living organisms. Currently, it is considered one of the most dangerous and toxic pollutants, which fate and function is still...
-
A BODIPY‐Based Molecular Rotor in Giant Unilamellar Vesicles: A Case Study by Polarization‐Resolved Time‐Resolved Emission and Transient Absorption Spectroscopy
PublicationBODIPY and BODIPY-derived systems are widely applied as fluorophores and as probes for viscosity detection in solvents and biological media. Their orientational and rotational dynamics in biological media are thus of vital mechanistic importance and extensively investigated. In this contribution, polarization-resolved confocal microscopy is used to determine the orientation of an amphiphilic BODIPY-cholesterol derivative in homogeneous...
-
Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation 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...
-
Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation 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...
-
The Impact of Long-Time Chemical Bonds in Mineral-Cement-Emulsion Mixtures on Stiffness Modulus
PublicationDeep cold in-place recycling is the most popular method of reuse of existing old and deteriorated asphalt layers of road pavements. In Poland, in most cases, the Mineral-Cement-Emulsion mixture technology is used, but there are also applications combining foamed bitumen and cement. Mineral-Cement-Emulsion mixtures contain two different binding agents – cement as well as asphalt from the asphalt emulsion. Asphalt creates asphalt...
-
Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
-
Communication: Inside the water wheel: Intrinsic differences between hydrated tetraphenylphosphonium and tetraphenylborate ions
PublicationTetraphenylphosphonium tetraphenylborate (TPTB) is a common reference electrolyte in physical chemistry of solutions allowing for a convenient partitioning of thermodynamic properties into single-ion contributions. Here, we compute on the basis of ab initio molecular dynamics simulations the infrared (IR) spectra for hydrated constituent ions of the TPTB assumption. Using spectral decomposition techniques, we extract important...
-
Modelling charge transfer processes in C2+ -tetrahydrofuran collision for ion-induced radiation damage in DNA building blocks
PublicationInvestigations of collision-induced processes involving carbon ions and molecules of biological interest in particular DNA building blocks, are crucial to model the effect of radiation on cells in order to improve medical treatments for cancer therapy. Using carbon ions appears to be one of the most efficient ways to increase biological effectiveness to damage cancerous cells by irradiating deep-seated tumors. Therefore, interest...
-
An LC-MS/MS Method for a Comprehensive Determination of Metabolites of BTEX Anaerobic Degradation in Bacterial Cultures and Groundwater
PublicationBTEX (benzene, toluene, ethylbenzene, and the different xylene isomers), known for carcinogenic and neurotoxic effects, are common environmental contaminants. The first step for the development of the bioremediation technologies is the detection of intense microbial degradation in contaminated waters in the quest for the most active bacterial strains. This requires the multispecies analysis for BTEX metabolites which are considered...
-
Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
PublicationCurrent computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning,...
-
Preliminary Testing of the Influence of Modified Polycaprolactones on Anabaena Variabilis Growth in Seawater
PublicationSeveral new biodegradable polymer materials have recently come onto the global market. Mostly the results on degradation kinetic studies are presented. This paper suggests using one of the tests to estimate the impact of polymer packaging material on sea life. The microorganism chosen was Anabaena variabilis (identified in many waters, including those of the Baltic Sea, especially in the Gulf of Gdansk and Puck Bay; this cyanobacterium...
-
Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...