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Search results for: sztuczna inteligencja
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Managing Unemployment under COVID-19 Conditions (States of Emergency or Crisis)
PublicationRising unemployment is one of the consequences of the COVID-19 pandemic in many countries. This, in turn, has forcedpolicymakers to respond immediately with policy tools to minimize unemployment. The purpose of our study is to contribute toempirical knowledge by looking at activities of 40 local government units to counteract unemployment in the cross-border regionon the Polish side. In doing this, our study contributes to the...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublicationThis 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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Wieloobszarowa rozmyta regulacja PID mocy reaktora jądrowego
PublicationW artykule przedstawiono wieloobszarowy regulator rozmyty z lokalnymi regulatorami PID dla sterowania mocą reaktora jądrowego typu PWR. Wykorzystano model matematyczny o parametrach skupionych reaktora PWR obejmujący procesy generacji i wymiany ciepła oraz efektów reaktywnościowych. Nastawy lokalnych regulatorów PID zostały dobrane w sposób optymalny, minimalizując całkowy wskaźnik jakości ISE. Na przykładzie pokazano że zastosowane...
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System oceny efektywności użytkowania aparatów słuchowych
PublicationCelem rozprawy jest opracowanie metody oceny efektywności protezowania słuchu przy użyciu aparatów słuchowych, która pozwoli w łatwy sposób poddawać ocenie korzyść z użytkowania protez słuchowych w najbardziej typowych sytuacjach akustycznych. Przedstawiono genezę podjętych badań i na tej podstawie zaproponowano cele i tezy rozprawy doktorskiej. W pracy w pierwszej kolejności zawarto przegląd dotyczący rodzajów ubytku słuchu i...
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The Crowd as a Source of Knowledge - From User Feedback to Fulfilling Requirements
PublicationCrowd-based and data-intensive requirements engineering (RE) strategy is an approach for gathering and analyzing information from the general public or the so-called crowd to derive validated user requirements. This study aims to conceptualize the process of analyzing information from a crowd to achieve the fulfillment of user requirements. The created model is based on the ADO framework (Antecedents-Decisions-Outcomes). In the...
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AI-Powered Cleaning Robot: A Sustainable Approach to Waste Management
PublicationThe world is producing a massive amount of single use waste, especially plastic waste made from polymers. Such waste is usually distributed in large areas within cities, near roads, parks, forests, etc. It is a challenge to collect them efficiently. In this work, we propose a Cleaning Robot as an autonomous vehicle for waste collection, utilizing the Nvidia Jetson Nano platform for precise arm movements guided by computer...
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Application of Shape From Shading Technique for Side Scan Sonar Images
PublicationSide scan sonar (SSS) is one of the most widely used imaging systems in the underwater environment. It is relatively cheap and easy to deploy in comparison with more powerful sensors like multibeam echosounder or synthetic aperture sonar. Although, the SSS does not provide directly the seafloor bathymetry measurements. Its outputs are usually in a form of grey level acoustic images of seafloor. However, the analysis of such images...
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Compact global association based adaptive routing framework for personnel behavior understanding
PublicationPersonnel behavior understanding under complex scenarios is a challenging task for computer vision. This paper proposes a novel Compact model, which we refer to as CGARPN that incorporates with Global Association relevance and Adaptive Routing Pose estimation Network. Our framework firstly introduces CGAN backbone to facilitate the feature representation by compressing the kernel parameter space compared with typical algorithms,...
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublicationIn this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking...
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Improved energy management technique in pipe-embedded wall heating/cooling system in residential buildings
PublicationEffective and environmentally responsive techniques of energy management in residential buildings are desirable for the resulting reduction of energy costs and consumption. In this paper, an improved and efficient technique of energy management in pipe-embedded wall heating/cooling systems, called the Thermal Barrier, is described. Specifically, the Thermal Barrier is a technique focused on the management and control of heat...
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Improved energy management technique in pipe-embedded wall heating/cooling system in residential buildings
PublicationEffective and environmentally responsive techniques of energy management in residential buildings are desirable for the resulting reduction of energy costs and consumption. In this paper, an improved and efficient technique of energy management in pipe-embedded wall heating/cooling systems, called the Thermal Barrier, is described. Specifically, the Thermal Barrier is a technique focused on the management and control of heat supply...
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Metody wyszukiwania informacji w bazach multimedialnych.
PublicationW artykule przedstawiono przegląd zagadnień związanych z wyszukiwaniem informacji zawartych w bazach multimedialnych. Przegląd ten został oparty o zrealizowany projekt badawczy pt.: "Nowe metody wyszukiwania informacji multimedialnej w sieciach telekomunikacyjnych". Eksperymenty badawcze prowadzone w ramach projektu obejmowały wdrożenie wybranych metod sztucznej inteligencji do celów akwizycji i rozpoznawania obiektów muzycznych,...
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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
PublicationNitrous 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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Active learning on stacked machine learning techniques for predicting compressive strength of alkali-activated ultra-high-performance concrete
PublicationConventional ultra-high performance concrete (UHPC) has excellent development potential. However, a significant quantity of CO2 is produced throughout the cement-making process, which is in contrary to the current worldwide trend of lowering emissions and conserving energy, thus restricting the further advancement of UHPC. Considering climate change and sustainability concerns, cementless, eco-friendly, alkali-activated UHPC (AA-UHPC)...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Comparison and Analysis of Service Selection Algorithms
PublicationIn Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...
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To Survive in a CBRN Hostile Environment: Application of CAVE Automatic Virtual Environments in First Responder Training
PublicationThis paper is of a conceptual nature and focuses on the use of a specific virtual reality environment in civil-military training. We analyzed the didactic potential of so-called CAVE automatic virtual environments for First Responder training, a type of training that fills the gap between First Aid training and the training received by emergency medical technicians. Since real training involves live drills based on unexpected situations,...
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Decisional DNA and Optimization Problem
PublicationMany researchers have proved that Decisional DNA (DDNA) and Set of Experience Knowledge Structure (SOEKS or SOE) is a technology capable of gathering information and converting it into knowledge to help decision-makers to make precise decisions in many ways. These techniques have a feature to combine with different tools, such as data mining techniques and web crawlers, helping organization collect information from different sources...
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Analysis of results of large-scale multimodal biometric identity verification experiment
PublicationAn analysis of a large set of biometric data obtained during the enrolment and the verification phase in an experimental biometric system installed in bank branches is presented. Subjective opinions of bank clients and of bank tellers were also surveyed concerning the studied biometric methods in order to discover and to explore relations emerging from the obtained multimodal dataset. First, data acquisition and identity verification...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublicationIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Computing methods for fast and precise body surface area estimation of selected body parts
PublicationCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
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Analiza sentymentu jako narzędzie monitorowania wyników finansowych przedsiębiorstwa
PublicationMedia społecznościowe tworzą globalną platformę do dzielenia się interesującymi pomysłami lub nowościami, komentarzami i recenzjami. Stanowią bogate źródło danych do eksploracji opinii w celu pozyskania wcześniej nieznanej i użytecznej wiedzy biznesowej, która umożliwi nie tylko zwinne zarządzanie na rzecz skutecznej obsługi klienta, ale również powinna mieć odzwierciedlenie w finansowych wynikach przedsiębiorstwa. Za główny cel...
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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...
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Clothes Detection and Classification Using Convolutional Neural Networks
PublicationIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...
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A PROPOSAL FOR ONE-IMAGE PHOTOGRAMMETRY SYSTEM FOR MEASURING THE CLEARANCE DISTANCE. CASE STUDY
PublicationMeasurement of the clearance distance (both in the context of the rail and road) is one of the current and increasingly discussed topics in the context of photogrammetric and image processing (computer vision) methods. The article presents a description of a simple and rapid method of measure the clearance distance between the obstacles by using one-image photogrammetry. The proposed method was tested for the railway, tram and...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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Data-driven Models for Predicting Compressive Strength of 3D-printed Fiber-Reinforced Concrete using Interpretable Machine Learning Algorithms
Publication3D printing technology is growing swiftly in the construction sector due to its numerous benefits, such as intricate designs, quicker construction, waste reduction, environmental friendliness, cost savings, and enhanced safety. Nevertheless, optimizing the concrete mix for 3D printing is a challenging task due to the numerous factors involved, requiring extensive experimentation. Therefore, this study used three machine learning...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublicationThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
PublicationThe effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublicationThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublicationABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
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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...
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Analysis-by-synthesis paradigm evolved into a new concept
PublicationThis work aims at showing how the well-known analysis-by-synthesis paradigm has recently been evolved into a new concept. However, in contrast to the original idea stating that the created sound should not fail to pass the foolproof synthesis test, the recent development is a consequence of the need to create new data. Deep learning models are greedy algorithms requiring a vast amount of data that, in addition, should be correctly...
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Technique for reducing erosion in large-scale circulating fluidized bed units
PublicationThis paper presents a methodology, implemented for a real industrial-scale circulating fluidized bed boiler, to mitigate the risk of heating surfaces exposed to an intensive particle erosion process. For this purpose, a machine learning algorithm was developed to support the boiler reliability management process. Having a tool that can help mitigate the risk of uncontrolled power unit failure without expensive and technically complex...
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Listening to Live Music: Life beyond Music Recommendation Systems
PublicationThis paper presents first a short review on music recommendation systems based on social collaborative filtering. A dictionary of terms related to music recommendation systems, such as music information retrieval (MIR), Query-by-Example (QBE), Query-by-Category (QBC), music content, music annotating, music tagging, bridging the semantic gap in music domain, etc. is introduced. Bases of music recommender systems are shortly presented,...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublicationSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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Metoda oceny wiarygodności pomiarów wpływających na jakość diagnostyki cieplno-przepływowej w energetyce
PublicationW rozprawie doktorskiej podjęto problem uwiarygodnienia pomiarów wpływających na jakość diagnostyki cieplno-przepływowej w energetyce. W pracy wykazano potrzebę rzetelnej informacji pozyskanej po przez pomiar parametrów, która jest niezbędna dla przeprowadzenia diagnozy badanego systemu. Jednocześnie zwrócono uwagę na zmienny charakter pracy systemów energetycznych, która wpływa na niestabilność pozyskanych danych, co prowadzi...
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublicationWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Reinforced Secure Gossiping Against DoS Attacks in Post-Disaster Scenarios
PublicationDuring and after a disaster, the perceived quality of communication networks often becomes remarkably degraded with an increased ratio of packet losses due to physical damages of the networking equipment, disturbance to the radio frequency signals, continuous reconfiguration of the routing tables, or sudden spikes of the network traffic, e.g., caused by the increased user activity in a post-disaster period. Several techniques have...
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Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover
PublicationThe process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus)...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublicationThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Music information analysis and retrieval - a review
PublicationW referacie przedstawiono wybrane zagadnienia związane z analizą i wyszukiwaniem informacji muzycznej. Przegląd ten został oparty na literaturze związanej z dziedziną informatyki muzycznej i koncentruje się wokół problemu parametryzacji dźwięków muzycznych i sygnałów fonicznych oraz analizie przydatności wybranych metod tzw. sztucznej inteligencji (ang. computational intelligence) do akwizycji i rozpoznawania obiektów muzycznych...
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Evolutionary Sets of Safe Ship Trajectories Within Traffic Separation Schemes
PublicationThe paper presents the continuation of the author's research on Evolutionary Sets of Safe Ship Trajectories (ESoSST) methodology. In an earlier paper (Szlapczynski, 2011) the author described the foundations of this methodology, which used Evolutionary Algorithms (EA) to search for an optimal set of safe trajectories for all the ships involved in an encounter. The methodology was originally designed for open waters or restricted...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir 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...