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Wyniki wyszukiwania dla: neural network architecture search
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Poszukiwanie układów obiektów architektonicznych zgodnych z uwarunkowaniami przyrodniczymi Pojezierza Kaszubskiego. Studium autorskie
PublikacjaStudium docelowych form zamieszkiwania oparto o obserwacje przyrodnicze i próbę ich kulturowej transpozycji poprzez działania artystyczne. Metaforyczne wyobrażenia form zamieszkiwania prezentowane w wielu wariantach ukazują jej adaptowalność do różnorodnych, unikalnych uwarunkowań przyrodniczych. Kontekst stanowi zarówno inspirację jak i zadanie problemowe, na które odpowiedzią jest konkretna forma układu, spasowana do swojego...
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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublikacjaIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...
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High performance super-twisting sliding mode control for a maritime autonomous surface ship (MASS) using ADP-Based adaptive gains and time delay estimation
PublikacjaThis research addresses two kinds of problems related to optimal trajectory tracking of a Maritime Autonomous Surface Ship (MASS): those caused by the time-varying external disturbances including winds, waves and ocean currents as well as those resulting from inherent dynamical uncertainties. As the paper shows, an accurate and robust optimal controller can successfully deal with both issues. An improved Optimal Adaptive Super-Twisting...
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High performance super-twisting sliding mode control for a maritime autonomous surface ship (MASS) using ADP-Based adaptive gains and time delay estimation
PublikacjaThis research addresses two kinds of problems related to optimal trajectory tracking of a Maritime Autonomous Surface Ship (MASS): those caused by the time-varying external disturbances including winds, waves and ocean currents as well as those resulting from inherent dynamical uncertainties. As the paper shows, an accurate and robust optimal controller can successfully deal with both issues. An improved Optimal Adaptive Super-Twisting...
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Economical methods for measuring road surface roughness
PublikacjaTwo low-cost methods of estimating the road surface condition are presented in the paper, the first one based on the use of accelerometers and the other on the analysis of images acquired from cameras installed in a vehicle. In the first method, miniature positioning and accelerometer sensors are used for evaluation of the road surface roughness. The device designed for installation in vehicles is composed of a GPS receiver and...
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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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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CNN-CLFFA: Support Mobile Edge Computing in Transportation Cyber Physical System
PublikacjaIn the present scenario, the transportation Cyber Physical System (CPS) improves the reliability and efficiency of the transportation systems by enhancing the interactions between the physical and cyber systems. With the provision of better storage ability and enhanced computing, cloud computing extends transportation CPS in Mobile Edge Computing (MEC). By inspecting the existing literatures, the cloud computing cannot fulfill...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublikacjaAchieving compact size has emerged as a key consideration in modern microwave design. While structural miniaturization can be accomplished through judicious circuit architecture selection, precise parameter tuning is equally vital to minimize physical dimensions while meeting stringent performance requirements for electrical characteristics. Due to the intricate nature of compact structures, global optimization is recommended,...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublikacjaDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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On-line Search in Two-Dimensional Environment
PublikacjaWe consider the following on-line pursuit-evasion problem. A team of mobile agents called searchers starts at an arbitrary node of an unknown network. Their goal is to execute a search strategy that guarantees capturing a fast and invisible intruder regardless of its movements using as few searchers as possible. We require that the strategy is connected and monotone, that is, at each point of the execution the part of the graph...
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The Optimal Location of Ground-Based GNSS Augmentation Transceivers
PublikacjaModern Global Navigation Satellite Systems (GNSS) allow for positioning with accuracies ranging from tens of meters to single millimeters depending on user requirements and available equipment. A major disadvantage of these systems is their unavailability or limited availability when the sky is obstructed. One solution is to use additional range measurements from ground-based nodes located in the vicinity of the receiver. The highest...
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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...
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A Proposed Soft Computing Model for Ultimate Strength Estimation of FRP-Confined Concrete Cylinders
PublikacjaIn this paper, the feed-forward backpropagation neural network (FFBPNN) is used to propose a new formulation for predicting the compressive strength of fiber-reinforced polymer (FRP)-confined concrete cylinders. A set of experimental data has been considered in the analysis. The data include information about the dimensions of the concrete cylinders (diameter, length) and the total thickness of FRP layers, unconfined ultimate concrete...
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Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublikacjaAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
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EVALUATION OF LIQUID-GAS FLOW IN PIPELINE USING GAMMA-RAY ABSORPTION TECHNIQUE AND ADVANCED SIGNAL PROCESSING
PublikacjaLiquid-gas flows in pipelines appear in many industrial processes, e.g. in the nuclear, mining, and oil industry. The gamma-absorption technique is one of the methods that can be successfully applied to study such flows. This paper presents the use of thegamma-absorption method to determine the water-air flow parameters in a horizontal pipeline. Three flow types were studied in this work: plug, transitional plug-bubble,...
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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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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublikacjaIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublikacjaThis study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation...
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Assessing the attractiveness of human face based on machine learning
PublikacjaThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Predicting the peak structural displacement preventing pounding of buildings during earthquakes
PublikacjaThe aim of the present paper is to verify the effectiveness of the artificial neural network (ANN) in predicting the peak lateral displacement of multi-story building during earthquakes, based on the peak ground acceleration (PGA) and building parameters. For the purpose of the study, the lumped-mass multi-degree-of-freedom structural model and different earthquake records have been considered. Firstly, values of stories mass and...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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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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ESPAR Antenna-Based WSN Node With DoA Estimation Capability
PublikacjaIn this paper, we present a low-cost energy-efficient electronically steerable parasitic array radiator (ESPAR) antenna-based wireless sensor network (WSN) node designed for IEEE 802.15.4 standard that is capable of performing direction of arrival (DoA) estimation in real-life outdoor environments. To this end, we propose the WSN node architecture, design and realization that utilizes NXP JN5168 radio frequency (RF) wireless transceiver...
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Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublikacjaPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
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Dual-Activity Fluoroquinolone-Transportan 10 Conjugates offer alternative Leukemia therapy during Hematopoietic Cell Transplantation
PublikacjaHematopoietic cell transplantation (HCT) is often considered a last resort leukemia treatment, fraught with limited success due to microbial infections, a leading cause of mortality in leukemia patients. To address this critical issue, we explored a novel approach by synthesizing antileukemic agents containing antibacterial substances. This innovative strategy involves conjugating fluoroquinolone antibiotics, such as ciprofloxacin...
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Static in vitro digestion model adapted to the general older adult population: an INFOGEST international consensus
PublikacjaUnderstanding the mechanisms of food digestion is of paramount importance to determine the effect foods have on human health. Significant knowledge on the fate of food during digestion has been generated in healthy adults due to the development of physiologically-relevant in vitro digestion models. However, it appears that the performance of the oro-gastrointestinal tract is affected by ageing and that a model simulating the digestive...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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An ANN-Based Approach for Prediction of Sufficient Seismic Gap between Adjacent Buildings Prone to Earthquake-Induced Pounding
PublikacjaEarthquake-induced structural pounding may cause major damages to structures, and therefore it should be prevented. This study is focused on using an artificial neural network (ANN) method to determine the sufficient seismic gap in order to avoid collisions between two adjacent buildings during seismic excitations. Six lumped mass models of structures with a different number of stories (from one to six) have been considered in...
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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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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublikacjaIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Low-Cost Design Optimization of Microwave Passives Using Multi-Fidelity EM Simulations and Selective Broyden Updates
PublikacjaGeometry parameters of contemporary microwave passives have to be carefully tuned in the final stages of their design process to ensure the best possible performance. For reliability reasons, the tuning has to be to be carried out at the level of full-wave electromagnetic (EM) simulations. This is because traditional modeling methods are incapable of quantifying certain phenomena that may affect operation and performance of these...
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Web-based real-time simulation system
PublikacjaThe paper presents the development of a simulation system composed of a real-time plant simulator with real-time controller included in the software-in-the-loop structure using web-based communication. The client-server architecture build in a TCP/IP network environment was introduced, where the server is a computing unit for real-time high temporal resolution plant simulation (and optionally also as controllers' platform) and...
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Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task
PublikacjaGOAL: Activities of neuronal networks range from action potential firing of individual neurons, coordinated oscillations of local neuronal assemblies, and distributed neural populations. Here, we describe recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublikacjaObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Ensembling noisy segmentation masks of blurred sperm images
PublikacjaBackground: Sperm tail morphology and motility have been demonstrated to be important factors in determining sperm quality for in vitro fertilization. However, many existing computer-aided sperm analysis systems leave the sperm tail out of the analysis, as detecting a few tail pixels is challenging. Moreover, some publicly available datasets for classifying morphological defects contain images limited only to the sperm head. This...
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The value of less Light – Sustainable architectural lighting design
PublikacjaSince its beginning, the art of external illumination has substantially influ-enced the creation and the perception of architecture and the night-time urban environment. In her lecture, the author examines and defines the significant interdisciplinary conditions related to architectural lighting design that have evolved over the years, starting from the first simple exterior lighting projects to the more modern, complex concepts...
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Personal branding of artists and art-designers: necessity or desire?
PublikacjaPurpose Personal branding becomes a new in-demand skill for all professionals today. To be well-known helps to achieve success in the networked business environment. Personal relationships and a good reputation in the reality of network economy help young artists and art designers move up the career ladder. This paper aims to discuss a problem of artists who often find it difficult to define their artistic and self-distinction...
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NetBaltic System-Heterogenous Wireless Network for Maritime Communications
PublikacjaIn case of maritime communications, we observe a growing interest in deployment of multitask satellite-based solutions and development of new maritime-specific systems intended for improvements in safety of e-navigation. Analysis of different types of currently used maritime communication systems leads, however, to a conclusion that neither global and still very expensive satellite systems nor cheaper, but short-ranged transmission...
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Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations
PublikacjaThe fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where the canopy is sparse and there are well-defined tree crown boundaries. Here, the distinction...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Shaping Place Identity through Interaction on the Example of the European Solidarity Centre in Gdansk
PublikacjaThe article presents process of shaping place identity on the example of an important for Pomerania region investment - European Solidarity Centre. The realization of the European Solidarity Centre aims to be one of the essential elements of shaping Gdańsk’s identity of space. The article is an attempt to analyse how the presence of realization gradually affects the formation of the place identity of new urban space. Analysis...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublikacjaThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublikacjaIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....