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Search results for: NEURONAL OSCILLATIONS
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Direct brain stimulation modulates encoding states and memory performance in humans
PublicationPeople often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting,...
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Computational intelligence methods in production management
PublicationThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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Detecting type of hearing loss with different AI classification methods: a performance review
PublicationHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Design of a Shape-Memory-Alloy-Based Carangiform Robotic Fishtail with Improved Forward Thrust
PublicationShape memory alloys (SMAs) have become the most common choice for the development of mini- and micro-type soft bio-inspired robots due to their high power-to-weight ratio, ability to be installed and operated in limited space, silent and vibration-free operation, biocompatibility, and corrosion resistance properties. Moreover, SMA spring-type actuators are used for developing different continuum robots, exhibiting high degrees...
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Morphology and internal structure of small-scale washovers formed in the coastal zone of the semi-enclosed tideless basin, Gulf of Gdańsk, Baltic Sea
PublicationThis study explores the morphological features and internal structure of small-scale washovers along the southeastern Baltic Sea coast, providing insights into these most widespread yet often neglected deposits in the recent research of geomorphological and sedimentary record of storm surges. A 15-year-long record of morphological changes of the coast was acquired from regional orthophotos to analyse their geometry and spatial...
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Interannual Variability of the GNSS Precipitable Water Vapor in the Global Tropics
PublicationThis paper addresses the subject of inter-annual variability of the tropical precipitable water vapor (PWV) derived from 18 years of global navigation satellite system (GNSS) observations. Non-linear trends of retrieved GNSS PWV were investigated using the singular spectrum analysis (SSA) along with various climate indices. For most of the analyzed stations (~49%) the GNSS PWV anomaly was related to the El Niño Southern Oscillation...
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublicationThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
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1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type
PublicationA network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....
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Dynamic analysis of the railway bridge span under moving loads
PublicationThe first part of this paper provides a review of the state of knowledge of the dynamic behaviour of railway bridges under moving loads. Particular attention is paid to developments in modelling railway bridge loading and dynamic vehicle-span (structure) interaction. The most important aspects determining the advancements in this area of knowledge are identified. The contemporary techniques for defining bridge span finite element...
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Statistical evaluation of the changes in cellulose properties caused by the stepwise solvent exchange and esterification
PublicationThe objective of the research was to empirically confirm the changes in cellulose reactivity caused by the pre-treatment with solvents of different polarity. Therefore, 5 solvents varying in their polar component of surface tension from 0 to 4.6 mN/m were chosen. Their impact on the biopolymer properties was carefully analysed concerning chemical structure, crystallinity and surface characteristics. It was revealed that the length...
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Processing, Performance Properties, and Storage Stability of Ground Tire Rubber Modified by Dicumyl Peroxide and Ethylene-Vinyl Acetate Copolymers
PublicationIn this paper, ground tire rubber was modified with dicumyl peroxide and a variable content (in the range of 0–15 phr) of ethylene-vinyl acetate copolymers characterized by different vinyl acetate contents (in the range of 18–39 wt.%). Modification of ground tire rubber was performed via an auto-thermal extrusion process in which heat was generated during internal shearing of the material inside the extruder barrel. The processing,...
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Generalised heart rate statistics reveal neurally mediated homeostasis transients
PublicationDistributions of accelerations and decelerations, obtained from increments of heart rate recorded during a head-up tilt table (HUTT) test provide short-term characterization of the complex cardiovascular response to a rapid controlled dysregulation of homeostasis. A generalised statistic is proposed for evaluating the neural reflexes responsible for restoring the homeostatic dynamics. An evaluation of the effects on heart rate...
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An absorbing set for the Chialvo map
PublicationThe classical Chialvo model, introduced in 1995, is one of the most important models that describe single neuron dynamics. In order to conduct effective numerical analysis of this model, it is necessary to obtain a rigorous estimate for the maximal bounded invariant set. We discuss this problem, and we correct and improve the results obtained by Courbage and Nekorkin (2010). In particular, we provide an explicit formula for an...
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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Analiza drgań przewodów jezdnych sieci trakcyjnej w aspekcie oceny jej stanu technicznego
PublicationW pracy przedstawiono możliwości wykorzystania analizy drgań przewodów jezdnych sieci trakcyjnej do oceny jej stanu technicznego. Zaprezentowano wyniki badań laboratoryjnych, w których rejestrowano drgania odcinka przewodu jezdnego o zróżnicowanym stopniu zużycia i przy różnych warunkach jego zawieszenia. Na bazie przeprowadzonych analiz w dziedzinie czasu i częstotliwości, wskazano zależności między stanem sieci a wybranymi parametrami...
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Wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationW pracy opisano sposób doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej przy wykorzystaniu algorytmów ewolucyjnych. Zaproponowano funkcję celu opartą na rozkładzie biegunów obserwatora. Ze względu na wpływ prędkości maszyny na dynamikę obserwatora zaproponowano dobór wzmocnień obserwatora dla różnych przedziałów prędkości. Dla poszczególnych przedziałów zaprezentowano wyniki doboru wzmocnień w postaci tabel...
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Skuteczne prognozowanie krótkoterminowe mocy farm wiatrowych
PublicationPrognozowanie mocy wytwórczej konkretnej farmy wiatrowej (FW) w horyzoncie 24-godzinnymwymaga zarówno wiarygodnej prognozy wietrzności, jak i narzędzi wspomagających. Narzędzie to jest dedykowanym modelem mocy farmy. Model powinien uwzględniać nie tylko ogólne zasady przetwarzania energii wiatru na energię mechaniczną, ale także cechy szczególnekonkretnej farmy. Liczba czynników wpływających na moc farmy jest duża i dokładna prognozamocy,...
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A Comparative Study of Fuzzy SMC with Adaptive Fuzzy PID for Sensorless Speed Control of Six-Phase Induction Motor
PublicationMulti-phase motors have recently replaced three-phase induction motors in a variety of applications due to the numerous benefits they provide, and the absence of speed sensors promotes induction motors with variable speed drives. Sensorless speed control minimizes unnecessary speed encoder cost, reduces maintenance, and improves the motor drive’s reliability. The performance comparison of the fuzzy sliding mode controller (FSMC)...
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Ecological bearing systems for water turbines – research and development at Gdansk University of Technology
PublicationIncreasing requirements for environmental protection make it necessary to introduce new materials and designs. Hydroelectric power plants operating in direct contact with water reservoirs and rivers are potentially endangering water cleanliness, hence they should also be modernized in the way minimizing the environmental hazards. A lot of progress in this field has been achieved in last decades, but still there is much work to...
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Comparison of GPS tropospheric delays derived from two consecutive EPN reprocessing campaigns from the point of view of climate monitoring
PublicationThe main purpose of this research was to acquire information about consistency of ZTD (zenith total delay) linear trends and seasonal components between two consecutive GPS reprocessing campaigns. The analysis concerned two sets of the ZTD time series which were estimated during EUREF (Reference Frame Sub-Commission for Europe) EPN (Permanent Network) reprocessing campaigns according to 2008 and 2015 MUT AC (Military University...
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A Comparative Study of Fuzzy SMC with Adaptive Fuzzy PID for Sensorless Speed Control of Six-Phase Induction Motor
PublicationMulti-phase motors have recently replaced three-phase induction motors in a variety of applications due to the numerous benefits they provide, and the absence of speed sensors promotes induction motors with variable speed drives. Sensorless speed control minimizes unnecessary speed encoder cost, reduces maintenance, and improves the motor drive’s reliability. The performance comparison of the fuzzy sliding mode controller (FSMC)...
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Time travel without paradoxes: Ring resonator as a universal paradigm for looped quantum evolutions
PublicationA ring resonator involves a scattering process where a part of the output is fed again into the input. The same formal structure is encountered in the problem of time travel in a neighborhood of a closed timelike curve (CTC). We know how to describe quantum optics of ring resonators, and the resulting description agrees with experiment. We can apply the same formal strategy to any looped quantum evolution, in particular to the...
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Theoretical designing of selenium heterocyclic non-fullerene acceptors with enhanced power conversion efficiency for organic solar cells: a DFT/TD-DFT-based prediction and understanding
PublicationIn this study, we have designed and explored a new series of non-fullerene acceptors for possible applications in organic solar cells. We have designed four molecules named as APH1 to APH4 after end-capped modification of recently synthesized Y6-Se-4Cl molecule. Density functional theory and time dependent-density functional theory have been employed for computing geometric and photovoltaic parameters of the designed molecules....
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Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublicationThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublicationThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Hotspot of human verbal memory encoding in the left anterior prefrontal cortex
PublicationBackground: Treating memory and cognitive deficits requires knowledge about anatomical sites and neural activities to be targeted with particular therapies. Emerging technologies for local brain stimulation offer attractive therapeutic options but need to be applied to target specific neural activities, at distinct times, and in specific brain regions that are critical for memory formation. Methods: The areas that are critical...
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Jednofazowy falownik napięcia z aktywnym obwodem odsprzęgającym
PublicationZnanym zagadnieniem w jednofazowych falownikach napięcia jest pobieranie ze źródła napięcia stałego składowej przemiennej o częstotliwości dwukrotnie większej od częstotliwości generowanej przez falownik. Jednym z rozwiązań problemu jest stosowanie dużej baterii kondensatorów elektrolitycznych, lecz lepszym sposobem z punktu widzenia niezawodności i gęstości mocy przekształtnika jest stosowanie aktywnych układów odsprzęgania mocy....
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Wpływ sposobu odwzorowania pojazdu szynowego na odpowiedź dynamiczną przęsła mostowego
PublicationW pracy przedstawiono rezultaty analiz numerycznych oraz badań eksploatacyjnych dwóch przęseł mostowych wymuszonych ruchomym pojazdem szynowym. Pojazd odwzorowano za pomocą czterech modeli uproszczonych: strumienia sił skupionych, strumienia mas skupionych oraz strumieni oscylatorów jedno- i dwumasowych. Analizy numeryczne wykonano przy wykorzystaniu MES. Potrzebne parametry dynamiczne wyznaczono na podstawie wyników identyfikacji...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Towards Knowledge Sharing Oriented Adaptive Control
PublicationIn this paper, we propose a knowledge sharing oriented approach to enable a robot to reuse other robots' knowledge by adapting itself to the inverse dynamics model of the knowledge-sharing robot. The purpose of this work is to remove the heavy fine-tuning procedure required before using a new robot for a task via reusing other robots' knowledge. We use the Neural Knowledge DNA (NK-DNA) to help robots gain empirical knowledge and...
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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...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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A high-accuracy complex-phase method of simulating X-ray propagation through a multi-lens system
PublicationThe propagation of X-ray waves through an optical system consisting of many X-ray refractive lenses is considered. For solving the problem for an electromagnetic wave, a finite-difference method is applied. The error of simulation is analytically estimated and investigated. It was found that a very detailed difference grid is required for reliable and accurate calculations of the propagation of X-ray waves through a multi-lens...
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Starter for Voltage Boost Converter to Harvest Thermoelectric Energy for Body-Worn Sensors
PublicationThis paper examines the suitability of selected configurations of ultra-low voltage (ULV) oscilla-tors as starters for a voltage boost converter to harvest energy from a thermoelectric generator (TEG). Important properties of particularly promising configurations, suitable for on-chip imple-mentation are compared. On this basis, an improved oscillator with a low startup voltage and a high output voltage swing is proposed. The applicability...
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublicationSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...
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Hybrid System for Ship-Aided Design Automation
PublicationA hybrid support system for ship design based on the methodology of CBR with some artificial intelligence tools such as expert system Exsys Developer along with fuzzy logic, relational Access database and artificial neural network with backward propagation of errors.
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WARUNKI REZONANSOWE W WĘŹLE Z KOMPENSATOREM SVC
PublicationInstalowanie kompensatorów statycznych w sieciach rozdzielczych i przesyłowych służy poprawie profili napięciowych. Kompensatory jako źródła mocy biernej zwiększają stabilność napięciową systemu. Pozwalają także na szybszą odbudowę systemu w przypadku awarii napięciowej. W artykule zaprezentowano wpływ struktury i wysterowania układu SVC na zmianę impedancji w układzie zasilania. Ma to bezpośredni wpływ na częstotliwości, przy...
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Badania eksperymentalne i symulacyjne dynamiki modelowego odcinka sieci trakcyjnej
PublicationW pracy przedstawiono główne założenia i strukturę opracowanego modelu matematycznego odcinka kolejowej górnej sieci trakcyjnej, opartego na metodzie energetycznej Lagrange’a. W celu wyznaczenia wybranych parametrów modelu, jak również dla oceny stopnia zgodności odwzorowania przez utworzony program symulacyjny stanów statycznych i dynamicznych sieci zbudowano laboratoryjny model odcinka sieci jezdnej z użyciem rzeczywistych jej...
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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublicationConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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Importance of sign conventions on analytical solutions to the wave-induced cyclic response of a poro-elastic seabed
PublicationThis paper discusses the influence of different sign conventions for strains and stresses, i.e. the solid mechanics sign convention and the soil mechanics sign convention, on the form of governing partial differential equations (the static equilibrium equations and the continuity equation) used to describe the wave-induced cyclic response of a poro-elastic seabed due to propagation of a sinusoidal surface water-wave. Some selected...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Direct electrical brain stimulation of human memory: lessons learnt and future perspectives
PublicationModulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental...
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Processing, physico-mechanical and thermal properties of reclaimed GTR and NBR/reclaimed GTR blends as function of various additives
PublicationIn this work, ground tire rubber (GTR) was mechano-chemically reclaimed in the presence of bitumen and various additives. During studies three types of processing and curing additives: (i) peptizer P300; (ii) vulcanization accelerator tetramethylthiuram disulfide (TMTD) and (iii) organic peroxide di(2-tert-butyl-peroxyisopropyl)benzene (BIB1) were applied to enhance reclaiming of GTR. Reclaiming process was evaluated by oscillating...
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Interrelationship between total volatile organic compounds emissions, structure and properties of natural rubber/polycaprolactone bio-blends cross-linked with peroxides
PublicationNatural rubber/polycaprolactone (NR/PCL) bio-based blends with different organic peroxides were prepared using an internal batch mixer and subsequently cross-linked at 170°C. Two types of commonly used organic peroxides, dicumyl peroxide and di(tert-butylperoxyisopropyl)benzene peroxide, were applied as free-radical initiator. Cross-linking efficiency of NR/PCL blends were investigated using oscillating disc rheometer measurements,...