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Wyniki wyszukiwania dla: federated learning
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublikacjaTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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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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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublikacjaEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublikacjaThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe 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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Looking through the past: better knowledge retention for generative replay in continual learning
PublikacjaIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublikacjaWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublikacjaCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublikacjaOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis 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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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Szymon Zaporowski mgr inż.
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Zastosowanie systemów e-learningu w szkolnictwie wyższym
PublikacjaWzrost dostępności internetu oraz rozwój systemów informatycznych przyczyniły się do zmian w zakresie edukacji. Poprzez wykorzystanie narzędzi informatycznych coraz popularniejszą formą nauczania stał się e-learning. Obecnie większość uczelni wyższych stosuje wybrany przez siebie system e-learningowy, którego głównym zadaniem jest wsparcie procesu dydaktycznego. Celem pracy jest analiza zastosowania kilku przykładowych systemów...
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Brushing with additional cleaning restrictions
PublikacjaIn graph cleaning problems, brushes clean a graph by traversing it subject to certain rules. We consider the process where at each time step, a vertex that has at least as many brushes as incident, contaminated edges, sends brushes down these edges to clean them. Various problems arise, such as determining the minimum number of brushes (called the brush number) that are required to clean the entire graph. Here, we study a new variant...
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Edyta Gołąb-Andrzejak dr hab.
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Application of Intelligent Conversational Agents in E-learing Environments
PublikacjaThe paper concerns intelligent tutoring systems and concentrates on apliaction of virtual mentors in distance learning environments. Different educational agent types are described. The prototype of an agent developed at Gdansk University of Technology is also presented, as well as its internal representation and construction. Benefits of virtual mentors applied in distance learning are also pointed out.
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Effect of Sieve Drum Inclination Angle on Wheat Grain Cleaning in a Novel Rotary Cleaning Device
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Analysis of the Sieve Unit Inclination Angle in the Cleaning Process of Oat Grain in a Rotary Cleaning Device
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The properties of fish silage produced with addition of sludge generated in coagulation of fish processing water
PublikacjaProces koagulacji przy pomocy soli żelaza stosowany jest do usuwania z wód poprocesowych przemysłu spożywczego zanieczyszczeń tłuszczowych i białkowych. Tak uzyskany osad pokoagulacyjny może być dodawany do produkcji rybnych hydrolizatów białkowych. Wytwarzano hydrolizaty białkowe ze szprota z dodatkiem osadów pokoagulacyjnych z przemysłu rybnego. Zmodyfikowano metodę wytwarzania rybnych hydrolizatów białkowych przez zmianę kwasu...
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The use of a simulation model to analyze the impact of heavy transport generated by the port to the city traffic.
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User-generated images and its impact on consumer-based brand equity and on purchase intention
PublikacjaResearchers and brand managers have limited knowledge of the effects that different types of user-generated content (UGC) have on consumers’ perception of brands and behavior. In this study we investigated 301 authors of a specific category of UGC, i.e., user-generated images (UGI) on a social networking site to confirm the relationships of four drivers reported in literature (co-creation, empowerment, community, and self-concept)...
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Optical activity of the guest azobenzene molecule generated by inclusion complexation with steroidal bile acids.
PublikacjaZsyntetyzowano krystaliczne kompleksy inkluzyjne azobenzenu z kwasami cholowym i deoksycholowym. Otrzymane związki inkluzyjne poddano badaniom przy wykorzystaniu spektroskopii dichroizmu kołowego w fazie stałej (KBr). Dodatni efekt Cottona, odpowiadający niskoenergetycznemu przejściu elektronowemu n-pi*, skorelowano z helikalnością M,M skręconej cząsteczki azobenzenu. Ponadto w celach porównawczych zmierzono dichroizm kołowy w...
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Optical activity of benzophenone and thiobenzophenone generated by spontaneous crystallization and inclusion complexation with cholic acid.
PublikacjaOtrzymano związki inkluzyjne benzofenonu i jego tioanalogu z kwasem cholowym. W zależności od stosowanej metody syntezy kompleksów inkluzyjnych benzofenonu powstawały one w dwóch różnych postaciach polimorficznych. Jedna z nich wykazuje istnienie cząsteczek gościa w czterech konformacjach, przy czym dominuje konformer o helikalności M. Struktura krystalograficzna kompleksu tiobenzofenonu z kwasem cholowym ujawniła obecność tylko...
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The laboratory experiments on reduction of organic pollutants load in was-tewater generated in fish processing industry
PublikacjaPrzeprowadzono próby obniżenia ładunku zanieczyszczeń w ściekach z przemysłu rybnego przed ich odprowadzeniem do sieci kanalizacji miejskiej. Wykorzystano koagulację do wydzielenia ze ścieków białek i tłuszczów. Uzyskany osad pokoagulacyjny dodawano do produkcji rybnych hydrolizatów białkowych. Zmodyfikowano metodę wytwarzania hydrolizatów poprzez zamianę kwasu siarkowego na fosforowy. Dzięki tej zmianie obniżono zawartość żelaza...
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Response of cylindrical steel tank under stochastically generated non-uniform earthquake excitation
PublikacjaCylindrical steel tanks are very important structures in industrial facilities since their application is related to storing different types of products. Their safety and reliability have become a crucial issue because any damage may cause significant consequences, including ecological disaster. The most dangerous dynamic load acting on cylindrical steel tanks is related to earthquakes, especially that the seismic excitation may...
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Engineering Federated Information (Database) Systems
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Edu Inspiracje WZiE: Active Learning, czyli o mocy aktywnego przetwarzania informacji
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