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Mono- and bimetallic (Pt/Cu) titanium(IV) oxide photocatalysts. Physicochemical and photocatalytic data of magnetic nanocomposites’ shell
PublikacjaSurface modification of titania with noble and semi-noble metals resulted in significant enhancement of photocatalytic activity. Presented data, showing the photocatalytic properties of TiO2-M (where M is Pt and/or Cu) photocatalysts were further used as Fe3O4@SiO2/TiO2-M magnetic nanocomposites shells in "Mono- and bimetallic (Pt/Cu) titanium(IV) oxide core-shell photocatalysts with Vis light activity and magnetic separability"...
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Single crystal growth and physical properties of MCo2Al9 (M= Sr, Ba)
PublikacjaSingle crystals of SrCo2Al and BaCo2Al9 were grown using a self-flux method. A LeBail analysis of the powder X-ray diffraction patterns show that both compounds crystallize in a hexagonal (P6/mmm) crystal structure with lattice parameters: a = 7.8995(1) Å, c = 3.9159(1) Å for SrCo2Al9, and a = 7.9162(2) Å, c = 3.9702(1) Å for BaCo2Al9 aluminide. The low temperature analysis of the heat capacity measurements give a Sommerfeld...
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Stress Monitoring System for Individuals with Autism Spectrum Disorders
PublikacjaIn this article, a stress monitoring system tailored for individuals with Autism Spectrum Disorders (ASD) and developed for the educational institution is presented. People with ASD face problems with effective stress management due to their high self-perceived levels of stress, poor ability to cope with it, and dificulties with the accurate detection of the source of stress. Consistently, being able to measure stress appears to...
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Vident-real: an intra-oral video dataset for multi-task learning
Dane BadawczeWe introduce Vident-real, a large dataset of 100 video sequences of intra-oral scenes from real conservative dental treatments performed at the Medical University of Gdańsk, Poland. The dataset can be used for multi-task learning methods including:
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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A CONTEXT IN RECOMMENDER SYSTEMS
PublikacjaRecommender systems aim to propose potentially interesting items to a user based on his preferences or previous interaction with the system. In the last decade, researcher found out that known recommendation techniques are not sufficient to predict user decisions. It has been noticed that user preferences strongly depend on the context in which he currently is. This raises new challenges for the researchers such as how to obtain...
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Periodic Solutions of Generalized Lagrangian Systems with Small Perturbations
PublikacjaIn this paper we study the generalized Lagrangian system with a small perturbation. We assume the main term in the system to have a maximum, but do not suppose any condition for perturbation term. Then we prove the existence of a periodic solution via Ekeland’s principle. Moreover, we prove a convergence theorem for periodic solutions of perturbed systems.
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Context-Aware Indexing and Retrieval for Cognitive Systems Using SOEKS and DDNA
PublikacjaVisual content searching, browsing and retrieval tools have been a focus area of interest as they are required by systems from many different domains. Context-based, Content-Based, and Semantic-based are different approaches utilized for indexing/retrieving, but have their drawbacks when applied to systems that aim to mimic the human capabilities. Such systems, also known as Cognitive Systems, are still limited in terms of processing...
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Perspectives of Transport Systems Development in the Light of Radio Communication Systems Evolution Towards 5G
PublikacjaIn the paper conditions of development and implementation of transport systems with reference to the development of radio communication networks towards 5G are presented. First, general properties of next generation systems are mentioned and their architecture. Moreover, planned characteristics of B4G and 5G systems are depicted which can significantly contribute to the promotion and development of transport systems. In particular...
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Is participation in music festivals a self-expansion opportunity? Identity, self-perception, and the importance of music’s functions
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Editorial: Applied intelligence and knowledge based systems: approaches and case studies - part 2
PublikacjaWydanie Cybernetics and Systems poswiecone zagadnieniom zarzadzania wiedza.
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Cognitive memory for intelligent systems of decision-making, based on human psychology
PublikacjaA model of memory, which allows to expand the functionality of autonomous decision-making systems for robotic and human-system-interface purposes, is discussed. The model provides functions and features which make the prospective robotic and interfacing systems more human-like as well as more efficient in solving interactive issues.
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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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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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Stateczność i niezawodność pełnomorskich platform wiertniczych
PublikacjaW pracy przedstawiono wieloletnie doświadczenia Autora w zakresie wybranych aspektów numerycznej analizy pełnomorskich platform wiertniczych, w szczególności stacjonarnych platform stalowych poddanych działaniu fal wiatrowych i wiatru. W opisie zachowania się platform uwzględniono współoddziaływanie trzech ośrodków: materiału konstrukcji, morskich fal wiatrowych i podłoża gruntowego. Przyjęcie do opisu stochastycznych właściwości...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublikacjaExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublikacjaHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Survey of Radio Navigation Systems
PublikacjaAt present, there is a growing demand for radio navigation systems, ranging from pedestrian navigation to consumer behavior analysis. These systems have been successfully used in many applications and have become very popular in recent years. In this paper we present a review of selected wireless positioning solutions operating in both indoor and outdoor environments. We describe different positioning techniques, methods, systems,...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublikacjaThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Engineering education for smart grid systems in the quasi-industrial environment of the LINTE^2 laboratory
PublikacjaSmart grid systems are revolutionising the electric power sector, integrating advanced technologies to enhance efficiency, reliability and sustainability. It is important for higher education to equip the prospective smart grid professional with the competencies enabling them to navigate through the related complexities and drive innovation. To achieve this, interdisciplinary education programmes are necessary, addressing inter...
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Introduction to the special issue on intelligent systems to aid the handicapped.
PublikacjaWśród wielu zastosowań sztucznej inteligencji i technologii bazodanowych pojawiają się zastosowania wspierające osoby niepełnosprawne. Z chwilą pojawienia są każdej nowej technologii komputerowej świat naukowy proponuje zastosowania tej technologii do celu poprawy komunikacji z osobami niepełnosprawnymi bądź technologie wspierające te osoby bezpośrednio. Niniejsze wydanie specjalne czasopisma Journal of Intelligent Information...
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Caffeine Inhibits Differentiation Of Lung Cancer Stem Cells By Modulating Their Respiratory Metabolism
PublikacjaIt is ell established that many tumor types contain a fraction of cells, with stem cell-like properties, called cancer stem cells (CSCs), that are resistant to apoptosis induced by therapeutic agents. The presence of CSCs may explain why a standard anticancer treatment, that eliminates only differentiated cancer cells, does not lead to cancer cure.We previously showed the existence of caffeine-sensitive mechanism that controls...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublikacjaPurpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...
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Deep Learning Approaches in Histopathology
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e-Learning in Tourism Education
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Online Learning Based on Prototypes
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Distributed Learning with Data Reduction
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Self-Censorship in a Workplace: The Role of Gender, Management Position, Procedural Justice and Organizational Climate
Dane BadawczeData consist of three studies. In study 1 (N = 948) we test whether women manifest more self-censorship than men and we verify whether this effect is maintained when women and men hold managerial position. Then, we analyse the effects of procedural justice (study 2, N = 98) and communal organizational climate (study 3, N = 567) on women’s and men’s...
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Dynamic Execution of Engineering Processes in Cyber-Physical Systems of Systems Toolchains
PublikacjaEngineering tools support the process of creating, operating, maintaining, and evolving systems throughout their lifecycle. Toolchains are sequences of tools that build on each others' output during this procedure. The complete chain of tools itself may not even be recognized by the humans who utilize them, people may just recognize the right tool being used at the right place in time. Modern engineering processes, however, do...
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Geometric methods in dynamical systems modelling: electrical, mechanical and control systems
PublikacjaRozważono zagadnienia modelowania systemów dynamicznych z zastosowaniem metod geometrii różniczkowej. Równania dynamiczne otrzymano w postaci inkluzji różniczkowych. Przestrzenie konstytucyjne przyjęto w postaci subwiązek włóknistych. Rozważono przestrzenie konstytucyjne układów elektrycznych, układów mechanicznych i układów sterowania. Podstawowe wyniki pracy dotyczą struktury przestrzeni rozwiązań rozważanych systemów.
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Multi agent grid systems
PublikacjaThis chapter presents an idea of merging grid and volunteer systemswith multi agent systems. It gives some basics concerning multi agentsystem and the most followed standard. Some deliberations concerningsuch an existing systems were made in order to finally present possibilities of introducing agents into the Comcute system.
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Developing Methods for Building Intelligent Systems of Information Resources Processing Using an Ontological Approach
PublikacjaThe problem of developing methods of information resource processing is investigated. A formal procedure description of processing text content is developed. A new ontological approach to the implementation of business processes is proposed. Consider that the aim of our work is to develop methods and tools for building intelligent systems of information resource processing, the core of knowledge bases of which are ontology’s, and...
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Perspektywy wykorzystania technologii internetowych typu E-learning w dydaktyce szkół wyższych.
PublikacjaArtykuł dotyczy nauczania przez Internet na poziomie uniwersyteckim. Zaprezentowany został model wirtualnego uniwersytetu, który obejmuje materiały dydaktyczne, komunikację, egzaminy i organizację. Artykuł koncentruje się na technicznych zagadnieniach. Przeanalizowano także wpływ wykorzystania technologii E-learning na różne aspekty życia wyższej uczelni.
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Security and Anonymity in Agent Systems
PublikacjaMany agent systems have been developed and suggested for commercial application. However, in spite of the significant potential offered by the agent paradigm, the lack of such important properties as security, anonymity and untracebility especially in open dynamical environment, such as the Internet, has blocked the active implementation of agent technologies. Protecting agent systems poses a more demanding challenge comparing...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Design Equation for Stirring Fluid by a Stream Pump in a Circulating Tank
PublikacjaA circulating tank is a very useful theoretical scheme for many fluid-flow objects in several branches of engineering. The motion of the fluid in such objects can be induced in different ways. A stream pump provides an especially interesting possibility; however, the quantitative description of such devices shows some shortcomings. Such a device is analogous to a jet pump, thus has similar advantages (simplicity of construction,...
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What is important for you makes you think about the pandemic differently: moral foundations, pandemic-related fears and convictions (Lo que cada uno consideramos importante nos hace reflexionar sobre la pandemia de forma distinta: fundamentos morales, temores y convicciones sobre la pandemia)
PublikacjaBuilding on the Moral Foundations Theory and findings regarding the linkage of values, convictions and beliefs, the aim of the study was to compare people displaying various constellations of moral foundations regarding their tolerance of ambiguity, fear of COVID-19 (FCV), endorsement of COVID-19 conspiracy theories and the extent to which they believed in the effectiveness of five COVID-19 preventive measures. This study was...
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Selected concentration techniques for gas chromatographic analysis of environmental samples
PublikacjaThe paper describes the role and tasks of environmental analysis and monitoring. It emphasises the leading role played by gas chromatography, especially when coupled with suitable sample preparation. This is demonstrated by some literature evidence and mainly by the author's original work on the design of sample preparation apparatus and development of GC-based methods of determination of a wide variety of organic pollutants in...