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Wyniki wyszukiwania dla: recurrent neural networks
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Runge-Kutta bicharacteristic methods for first order partial functional di- fferential equations
PublikacjaW pracy prezentujemy nową klasę metod numerycznych dla równań różniczkowo-funkcyjnych. Są to metody bicharakterystyk Rungego-Kutty. Ponadto porównuje-my wprowadzone metody z metodami klasycznymi.
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Badanie i analiza efektywności alokacji strumieni danych w heterogenicznej sieci WBAN
PublikacjaW niniejszej dysertacji doktorskiej poddano dyskusji efektywność alokacji strumieni danych w heterogenicznej radiowej sieci WBAN (Wireless Body Area Networks). Biorąc pod uwagę dynamiczny rozwój nowoczesnych sieci radiokomunikacyjnych piątej generacji (5G), którego część stanowią radiowe sieci działające w obrębie ciała człowieka, bardzo ważnym aspektem są metody maksymalizujące wykorzystanie dostępnych zasobów czasowo –częstotliwościowych...
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Infedeltà nel trasferimento delle collocazioni nella traduzione dei romanzi di Michel Houellebecq dal francese all’italiano
PublikacjaBuilding on my PhD project, this paper explores fidelity challenges in the transfer of verb-nominal collocations (VNC) in the Italian translations of seven of Michel Houellebecq’s novels. I examine various kinds of infidelity, such as omissions, errors, incongruence in constituent transmission, incoherence in recurrent VNC transmission, and infidelity at the level of phraseological coverage. The accurate transfer...
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Impact of R/X ratio of distribution network on selection and control of energy storage units
PublikacjaThe interest in energy storage is still increasing. Energy storage units are installed in high voltage networks, medium voltage networks and low voltage distribution networks as well. These units are often used to improve power quality. One of the criteria for improving power quality is reducing voltage deviations. Depending on the type of network and specifying its R/X ratio, this criterion can be fulfilled by control of active...
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A new multi-process collaborative architecture for time series classification
PublikacjaTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublikacjaThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublikacjaThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....
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Online sound restoration system for digital library applications
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublikacjaThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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Prognostic and diagnostic capabilities of OOBN in assessing investment risk of complex construction projects
PublikacjaModelling decision problems using Bayesian networks is extremely valuable especially in case of issues related to uncertainty; it is also very helpful in constructing and understanding visual representation of the elements and their relations. This approach facilitates subsequent application of Bayesian networks, however there can be situations where using simple Bayesian networks is impractical or even ineffective. The aim of...
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A Test-Bed Analysis of Simultaneous PMIPv6 Handover in 802.11 WLANs Environment
PublikacjaProviding mobility in access networks is a challenge that we have to deal with. Due to networks’ convergence and migration to all-IP networks, mobility management at the network layer is required. However, there is a need for cooperation mechanisms between the network layer and lower layers to support multimedia services and make handover more efficient. This paper presents experimental research on simultaneous handover performance...
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Silent Signals The Covert Network Shaping the Future
PublikacjaSilent Signals The Covert Network Shaping the Future In a world dominated by information flow and rapid technological advancements, the existence of hidden networks and unseen influences has never been more relevant. "Silent Signals: The Covert Network Shaping the Future" delves deep into the mysterious and often opaque world of covert communication networks. This influential work sheds light on the silent...
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Future research directions in design of reliable communication systems
PublikacjaIn this position paper on reliable networks, we discuss new trends in the design of reliable communication systems. We focus on a wide range of research directions including protection against software failures as well as failures of communication systems equipment. In particular, we outline future research trends in software failure mitigation, reliability of wireless communications, robust optimization and network design, multilevel...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublikacjaLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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Damage Detection Strategies in Structural Health Monitoring of Overhead Power Transmission System
PublikacjaOverhead power transmission lines, their supporting towers, insulators and other elements create a highly distributed system that is vulnerable to damage. Typical damage scenarios cover cracking of foundation, breakage of insulators, loosening of rivets, as well as cracking and breakage of lines. Such scenarios may result from various factors: groundings, lightning strikes, floods, earthquakes, aeolian vibrations, conductors galloping,...
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Problems of modelling toxic compounds emitted by a marine internal combustion engine for the evaluation of its structure parameters
PublikacjaThe paper presents the possibility of using an analytical study of the engine exhaust ignition to evaluate the technical condition of the selected components. Software tools available for the analysis of experimental data commonly use multiple regression model that allows the study of the effects and iterations between model input quantities and one output variable. The use of multi-equation models gives a lot of freedom in the...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublikacjaElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Exploring the influence of personal factors on physiological responses to mental imagery in sport
PublikacjaImagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublikacjaObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Synteza układu sterowania statkiem morskim dynamicznie pozycjonowanym w warunkach niepewności
PublikacjaNiniejsza monografia obejmuje zagadnienia związane z syntezą układu dynamicznego pozycjonowania statku w środowisku morskim z zastosowaniem wybranych nieliniowych metod sterowania. W ramach pracy autorka rozważała struktury sterowania z zastosowaniem wektorowej adaptacyjnej metody backstep oraz metod jej pokrewnych, takich jak regulatory MSS (ang. multiple surface sliding), DSC (ang. dynamic surface control), NB (ang. neural backstepping)....
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How to provide fair service for V2I communications in VANETs?
PublikacjaIn this paper, we focus on fairness issues of Vehicle-to-Infrastructure (V2I) communications. In particular, we show that under a common technique of selection of RSUs by OBUs based on the received signal strength, a vast variability of a number of OBUs connected to RSUs can be observed leading to inefficient/unfair service provided by RSUs. To overcome this problem, we propose an algorithm for RSU selection called RSEL to obtain...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Model neuronowy jako alternatywa dla numerycznego modelu okołodźwiękowego przepływu pary przez palisadę turbinową.
PublikacjaWystępowanie skośnej fali uderzeniowej w przepływie pary przez palisadę turbinową stanowi zagrożenie dla bezpiecznej pracy turbiny oraz dla jej elementów konstrukcyjnych. Detekcja oraz lokalizacja fali uderzeniowej, a także rozpoznanie przyczyny jej powstawania, nie są możliwe do osiągnięcia na drodze pomiarowej. Analizę zjawisk zachodzących wewnątrz kanału przepływowego umożliwiają natomiast modele numeryczne oraz neuronowe. Zaletą...
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Voltage profiles improvement in a power network with PV energy sources – results of a voltage regulator implementation
PublikacjaThe constant increase in the number of photovoltaic (PV) energy sources in distribution networks is the cause of serious voltage problems. The networks built at least a dozen years ago are not provided for the installation of a large number of micro-sources. It happens that the previously properly functioning power networks are not able to provide to consumers power with the required parameters, after installing many PV sources....
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Direct brain stimulation modulates encoding states and memory performance in humans
PublikacjaPeople 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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Leveraging spatio-temporal features for joint deblurring and segmentation of instruments in dental video microscopy
PublikacjaIn dentistry, microscopes have become indispensable optical devices for high-quality treatment and micro-invasive surgery, especially in the field of endodontics. Recent machine vision advances enable more advanced, real-time applications including but not limited to dental video deblurring and workflow analysis through relevant metadata obtained by instrument motion trajectories. To this end, the proposed work addresses dental...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublikacjaThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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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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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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Online sound restoration system for digital library applications.
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Technical State Assessment of Charge Exchange System of Self-Ignition Engine, Based On the Exhaust Gas Composition Testing
PublikacjaThis paper presents possible use of results of exhaust gas composition testing of self - ignition engine for technical state assessment of its charge exchange system under assumption that there is strong correlation between considered structure parameters and output signals in the form of concentration of toxic compounds (ZT) as well as unambiguous character of their changes. Concentration of the analyzed ZT may be hence considered...
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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects
PublikacjaWastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Artificial Intelligence Aided Architectural Design
PublikacjaTools and methods used by architects always had an impact on the way building were designed. With the change in design methods and new approaches towards creation process, they became more than ever before crucial elements of the creation process. The automation of architects work has started with computational functions that were introduced to traditional computer-aided design tools. Nowadays architects tend to use specified tools...
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1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type
PublikacjaA 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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Generalised heart rate statistics reveal neurally mediated homeostasis transients
PublikacjaDistributions 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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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms
PublikacjaThe study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. The experiments were carried out at three microwave powers of 180, 360, and 540 W and three thicknesses of 2, 4, and 6 mm for cantaloupe drying, and the weight variations were determined. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were exploited to investigate energy and exergy indices of...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Pedestrian detection in low-resolution thermal images
PublikacjaOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublikacjaFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
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Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
PublikacjaIn environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori...
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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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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublikacjaIn this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...