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Wyniki wyszukiwania dla: SELF-SUPERVISED LEARNING
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Self-Organization in Multi-Agent Systems Based on Examples of Modeling Economic Relationships between Agents
PublikacjaThe goal of the research was to observe and analyze self-organization patterns in Multi-Agent Systems (MAS) by modeling basic economic relationships between agents forming a closed loop of relations necessary for their survival. The paper describes a worked-out MAS including an example of a production cycle and used economic rules. A special focus is put on behavior rules and decision systems of an individual agent such as: product...
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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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Application of TMS320c67xx signal processors for SONIC-self-optimizing narrowband interference canceler
PublikacjaThe paper presents a laboratory system for testing active control algorithms of acoustics noise in ducts. An applied algorithm - self-optimizing narrowband interference canceller (SONIC), allows one to remove narrowband disturbances of constant or slowly time-varying frequencies. Example experimental results of using the laboratory system for supression of sinusoidal disturbance are described. An electronic part of the system was...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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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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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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Is participation in music festivals a self-expansion opportunity? Identity, self-perception, and the importance of music’s functions
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Estimation of the minimal number of periodic points for smooth self-maps of odd dimensional real projective spaces
PublikacjaLet f be a smooth self-map of a closed connected manifold of dimension m⩾3. The authors introduced in [G. Graff, J. Jezierski, Minimizing the number of periodic points for smooth maps. Non-simply connected case, Topology Appl. 158 (3) (2011) 276-290] the topological invariant NJD_r[f], where r is a fixed natural number, which is equal to the minimal number of r-periodic points in the smooth homotopy class of f. In this paper smooth...
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Minimization of the number of periodic points for smooth self-maps of closed simply-connected 4-manifolds
PublikacjaLet M be a smooth closed simply-connected 4-dimensional manifold, f be a smooth self-map of M with fast grow of Lefschetz numbers and r be a product of different primes. The authors calculate the invariant equal to the minimal number of r-periodic points in the smooth homotopy class of f.
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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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Microfluidically Frequency-Reconfigurable Self-Quadruplexing Antenna Based on Substrate Integrated Square-Cavity
PublikacjaIn this article, a novel concept of self-quadruplexing tunable antenna (SQTA) enabled by microfluidic channels is investigated. The operating channels are either filled with air or dielectric liquids to enable frequency tunability. The proposed SQTA is implemented on the substrate-integrated square-cavity (SISC). A swastika-shaped slot is milled on the top-surface of the SISC to create four quarter-mode resonators. The resonators...
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Self-optimizing narrowband interference canceller - can reference signal help?
PublikacjaSONIC (Self-Optimizing Narrowband Interference Canceller) is an acronym of the recently proposed active noise control algorithm with interesting adaptivity and robustness properties. SONIC is a purely feedback controller, capable of rejecting nonstationary sinusoidal disturbances (with time-varying amplitudes and/or frequencies) in the presence of plant (secondary path) uncertainties. We show that even though SONIC can work reliably...
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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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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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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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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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Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation
PublikacjaThe present study investigates the potential of using fecal ash as an adsorbent and demonstrates a self-sustaining, optimized approach for urea recovery from wastewater streams. Fecal ash was prepared by heating synthetic feces to 500 °C and then processing it as an adsorbent for urea adsorption from synthetic urine. Since this adsorption approach based on fecal ash is a promising alternative for wastewater treatment, it increases...
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Thermodynamics and kinetics of amphotericin B self-association in aqueous solution characterized in molecular detail
PublikacjaAmphotericin B (AmB) is a potent but toxic drug commonly used to treat systemic mycoses. Its efficiency as a therapeutic agent depends on its ability to discriminate between mammalian and fungal cell membranes. The association of AmB monomers in an aqueous environment plays an important role in drug selectivity, as oligomers formed prior to membrane insertion – presumably dimers – are believed to act differently on fungal (ergosterol-rich)...
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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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Ultra-Compact Self-Quadruplexing Microfluidically Frequency Reconfigurable Slot Antenna Using Half-Mode SIW
PublikacjaIn this brief, the design of an ultra-compact self-quadruplexing frequency reconfigurable antenna (SQFRA) utilizing a half-mode substrate-integrated waveguide (HMSIW) and microfluidic channels is discussed. Four HMSIW cavities fed by four microstrip lines and slots are used to construct a highly compact antenna. The microstrip feedings to the HMSIW cavities are applied in such a way that the proposed antenna exhibits self-quadruplexing...
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Can Evaluation Patterns Enable End Users to Evaluate the Quality of an e-learning System? An Exploratory Study.
PublikacjaThis paper presents the results of an exploratory study whose main aim is to verify if the Pattern-Based (PB) inspection technique enables end users to perform reliable evaluation of e-learning systems in real work-related settings. The study involved 13 Polish and Italian participants, who did not have an HCI background, but used e-learning platforms for didactic and/or administrative purposes. The study revealed that the participants...
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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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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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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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Systemy z Uczeniem Maszynowym / Systems with Machine Learning
Kursy Online -
Online Learning Based on Prototypes
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Distributed Learning with Data Reduction
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Deep Learning Approaches in Histopathology
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e-Learning in Tourism Education
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Substrate Integrated Waveguide-Based Frequency-Tunable Self-Octaplexing Antenna
PublikacjaThis communication presents the first-ever substrate integrated waveguide (SIW)-based frequency-tunable self-octaplexing antenna (SOA) for wireless communication. The structure is arranged by implementing eight distinct patches with planar 50-ohm feedlines at the top of the SIW cavity, which realize eight distinct resonant frequencies. Independent tuning of each resonant frequency is achieved by incorporating appropriately allocated...
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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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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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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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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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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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Minimization of the number of periodic points for smooth self-maps of simply-connected manifolds with periodic sequence of Lefschetz numbers
PublikacjaLet f be a smooth self-map of m-dimensional, m ≥ 4, smooth closed connected and simply-connected manifold, r a fixed natural number. For the class of maps with periodic sequence of Lefschetz numbers of iterations the authors introduced in [Graff G., Kaczkowska A., Reducing the number of periodic points in smooth homotopy class of self-maps of simply-connected manifolds with periodic sequence of Lefschetz numbers, Ann. Polon. Math....
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Ultra-Compact SIRC-Based Self-Triplexing Antenna with High Isolation
PublikacjaAn ultra-compact self-triplexing antenna realized on a substrate-integrated rectangular cavity (SIRC) is discussed in this study. The proposed structure employs two L-shaped slots and an in-verted U-shaped slot to radiate at three independent operating frequency bands. Three 50-ohm microstrip feed lines are used to excite the radiation in these slots. The operating frequency is individually tuned using the slot size. The slot placement...
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Scale effect in the self-propulsion prediction for Ultra Large Container Ship with contra-rotating propellers
PublikacjaThis article addresses the problem of the scale effect for an Ultra Large Container Ship (ULCS) with a novel twin-crp-pod propulsion system. Twin-crp-pod steering-propulsion arrangement is an innovative solution that gains from three well-known systems: twin-propeller, contra-rotating propellers and pod propulsors. It is expected that applying the twin-crp-pod system to the analysed Ultra Large Container Ship will increase propulsion...
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Impressions about people with intellectual disability of Polish high school students who participated in a workshop led by self-advocates
PublikacjaThe research question is whether participation in a two-session workshop led by self-advocates with mild intellectual disability, supported by professional staff, affects high school students’ impression of people with intellectual disability, measured by a self-report questionnaire based on a semantic differential. The study was paper-pencil questionnaire-based and anonymous, conducted in Warsaw, Poland. Three measurements...
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Microfluidically Frequency-Reconfigurable Compact Self-Quadruplexing Tunable Antenna with High Isolation Based on Substrate Integrated Waveguide
PublikacjaThis communication presents a novel concept of microfluidically frequency-reconfigurable self-quadruplexing tunable antenna for quad-band applications. At the initial design stage, a substrate-integrated square cavity is divided into four unequal quarter-mode cavity resonators by inserting an X-shaped slot on the top surface of the cavity. Applying four 50-ohm microstrip feed-lines to these four quarter-mode cavity resonators enables...
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A method of self-testing of an analog circuit terminated by an ADC in electronic embedded systems controlled by microcontrollers
PublikacjaA new self-testing method of analog parts terminated by an ADC in electronic embedded systems controlled by microcontrollers is presented. It is based on a new fault diagnosis method based on on-line (i.e. during measurement), transformations of voltage samples of the time response of a tested part to a square pulse - onto localization curves placed in the measurement space. The method can be used for fault detection and single...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublikacjaThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Application of Complementary Signals in Built-In Self Testers for Mixed-Signal Embedded Electronic Systems
PublikacjaThis paper concerns the implementation of shape-designed complementary signals (CSs), matched to the frequency characteristic of the circuit under test, in built-in self testers (BISTs), dedicated to mixed-signal embedded electronic systems for testing their analog sections. The essence of the proposed method and solution of CS BIST is low-cost realization on the base of hardware and software resources of microcontrollers used...
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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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A method of self-testing of analog circuits based on fully differential op-amps with theTCBF classifier
PublikacjaA new approach of self-testing of analog circuits based on fully differential op-amps of mixed-signal systems controlled by microcontrollers is presented. It consists of a measurement procedure and a fault diagnosis procedure. We measure voltage samples of a time response of a tested circuit on a stimulation of a unit step function given at the common-mode reference voltage input of the op-amp. The fault detection and fault localization...
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Assessment of the water quality of Kłodnica River catchment using self-organizing maps
PublikacjaRisk assessment of industrial areas heavily polluted due to anthropogenic actions is of increasing concern worldwide. So is the case of Polish Silesia region where mostly heavy industry like smelters, mining, chemical industries as well as heat and electricity production facilities are being located. Such situation raises numerous questions about environmental state of local water bodies with special attention paid to the Kłodnica...