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Wyniki wyszukiwania dla: SUPERVISED CONTROL
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Supervised model predictive control of wastewater treatment plant
PublikacjaAn optimizing control of a wastewater treatment plant (WWTP), allowing for cost savings over long time period and fulfilling effluent discharge limits at the same time, requires application of advanced control techniques. Model Predictive Control (MPC) is a very suitable control technology for a synthesis of such a truly multivariable controller that can handle constraints and accommodate model-based knowledge combined with hard...
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Supervised Model Reference Adaptive Control of Chlorine Residuals in Water Distribution Systems
PublikacjaControl of integrated quality and quantity in Drinking Water Distribution Systems within recently proposed hierarchical framework is considered in the paper. A supervised nonlinear Indirect Model Reference Adaptive Controller is derived for the lower control level of the control structure to operate as the fast feedback controller of chlorine residuals in the monitored nodes. The major supervisor role is to manage switching between...
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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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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublikacjaTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
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Weakly-Supervised Word-Level Pronunciation Error Detection in Non-Native English Speech
PublikacjaWe propose a weakly-supervised model for word-level mispronunciation detection in non-native (L2) English speech. To train this model, phonetically transcribed L2 speech is not required and we only need to mark mispronounced words. The lack of phonetic transcriptions for L2 speech means that the model has to learn only from a weak signal of word-level mispronunciations. Because of that and due to the limited amount of mispronounced...
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DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images
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New supervised alignment method as a preprocessing tool for chromatographic data in metabolomic studies
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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Integrated monitoring, control and security of Critical Infrastructure Systems
PublikacjaModern societies have reached a point where everyday life relies heavily on desired operation of critical infrastructures, in spite of accidental failures and/or deliberate attacks. The issue of desired performance operation of CIS at high security level receives considerable attention worldwide. The pioneering generic methodologies and methods are presented in the paper project for designing systems capable of achieving these...
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Algorithms and Tools for Intelligent Control of Critical Infrastructure Systems
PublikacjaCritical Infrastructure Systems (CIS) are spatially distributed and of a network structure. The dynamics are nonlinear, uncertain and with several time scales. There is a variety of different objectives to be reliably met under a wide range of operational conditions. The operational conditions are influenced by the disturbance inputs, operating ranges of the CIS, faults in the sensors and actuators and abnormalities occurring in...
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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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Leszek Jarzębowicz dr hab. inż.
OsobyLeszek Jarzębowicz ukończył studia jednolite magisterskie na Wydziale Elektrotechniki i Automatyki Politechniki Gdańskiej w 2005 r. Na tym samym wydziale uzyskał stopień doktora nauk technicznych (2010 r.) oraz doktora habilitowanego nauk inżynieryjno-technicznych (2019 r.). Jego zainteresowania naukowe koncentrują się na: sterowaniu i modelowaniu elektrycznych układów napędowych, diagnostyce pojazdów szynowych, efektywności energetycznej...
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Human Factors and Cognitive Engineering in Functional Safety Analysis
PublikacjaHuman factors and cognitive engineering are considered nowadays as important multidisciplinary domains that focus on improving the relations between humans, technology and systems to be supervised and operated. The industrial automation and control systems (IACS) in hazardous plants are increasingly computerized and perform various safety functions. These are usually designed and implemented according to the functional safety requirements....
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Cognitive engineering and functional safety technology for reducing risks in hazardous plants
PublikacjaCognitive engineering is considered nowadays as interesting multidisciplinary domain that focuses on improving the relations between humans and the systems that are supervised and operated. The industrial automation and control systems (IACS) in hazardous plants are increasingly computerized and perform various safety functions. These are designed and implemented according to the functional safety concept. The objective is to maintain...
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Quadrotor Flight Controller Design Using Classical Tools
PublikacjaA principal aspect of quadrocopter in-flight operation is to maintain the required attitude of the craft’s frame, which is done either automatically in the so-called supervised flight mode or manually during man-operated flight mode. This paper deals with the problem of flight controller (logical) structure and algorithm design dedicated for the man-operated flight mode. The role of the controller is to stabilise the rotational...
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublikacjaVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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Video Classification Technology in a Knowledge-Vision-Integration Platform for Personal Protective Equipment Detection: An Evaluation
PublikacjaThis work is part of an effort for the development of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. This paper focuses on hazards resulted from the non-use of personal protective equipment (PPE), and examines a few supervised learning techniques to compose the proposed system for the purpose of recognition of three protective...
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Context Search Algorithm for Lexical Knowledge Acquisition
PublikacjaA Context Search algorithm used for lexical knowledge acquisition is presented. Knowledge representation based on psycholinguistic theories of cognitive processes allows for implementation of a computational model of semantic memory in the form of semantic network. A knowledge acquisition using supervised dialog templates have been performed in a word game designed to guess the concept a human user is thinking about. The game,...
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Shoreline Extraction Based on LiDAR Data Obtained Using an USV
PublikacjaThis article explores the use of Light Detection And Ranging (LiDAR) derived point clouds to extract the shoreline of the Lake Kłodno (Poland), based on their geometry properties. The data collection was performed using the Velodyne VLP‐16 laser scanner, which was mounted on the HydroDron Unmanned Surface Vehicle (USV). A modified version of the shoreline extraction method proposed by Xu et al. was employed, comprising of the following...
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Vident-synth: a synthetic intra-oral video dataset for optical flow estimation
Dane BadawczeWe introduce Vident-synth, a large dataset of synthetic dental videos with corresponding ground truth forward and backward optical flows and occlusion masks. It can be used for:
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Voice command recognition using hybrid genetic algorithm
PublikacjaAbstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...
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Robert Piotrowski dr hab. inż.
OsobyRobert Piotrowski jest absolwentem Wydziału Elektrotechniki i Automatyki (2001r., kierunek: Automatyka i Robotyka) oraz Wydziału Zarządzania i Ekonomii (2002r., kierunek: Organizacja Systemów Produkcyjnych) Politechniki Gdańskiej. Od 2005 roku jest zatrudniony na Wydziale Elektrotechniki i Automatyki, aktualnie w Katedrze Inteligentnych Systemów Sterowania i Wspomagania Decyzji. W 2005 roku obronił rozprawę doktorską (Automatyka...
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Novel analytical method for detection of orange juice adulteration based on ultra-fast gas chromatography
PublikacjaThe food authenticity assessment is an increasingly important issue in food quality and safety. The application of an electronic nose based on ultra-fast gas chromatography technique enables rapid analysis of the volatile compounds from food samples. Due to the fact that this technique provides chemical profiling of natural products, it can be a powerful tool for authentication in combination with chemometrics. In this article,...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublikacjaBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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Parameter and delay estimation of linear continuous-time systems
PublikacjaIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous identification...
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Modelling Object Behaviour in a Video Surveillnace System Using Pawlak's Flowgraph
PublikacjaIn this paper, methodology of acquisition and processing of video streams for the purpose of modelling object behaviour is presented. Multilevel contextual video processing was also mentioned. The Pawlak’s flowgraph is used as a container for the knowledge related to the behaviour of objects in the area supervised by a video surveillance system. Spatio-temporal dependencies in transitions between cameras can be easily changed in...
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Parameter and delay estimation of linear continuous-time systems
PublikacjaIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is usually described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous...
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On–line Parameter and Delay Estimation of Continuous–Time Dynamic Systems
PublikacjaThe problem of on-line identification of non-stationary delay systems is considered. The dynamics of supervised industrial processes are usually modeled by ordinary differential equations. Discrete-time mechanizations of continuous-time process models are implemented with the use of dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures mechanized in recursive forms are applied for simultaneous...
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Complexity analysis of the Pawlak’s flowgraph extension for re-identification in multi-camera surveillance system
PublikacjaThe idea of Pawlak’s flowgraph turned out to be a useful and convenient container for a knowledge of objects’ behaviour and movements within the area observed with a multi-camera surveillance system. Utilization of the flowgraph for modelling behaviour admittedly requires certain extensions and enhancements, but it allows for combining many rules into a one data structure and for obtaining parameters describing how objects tend...
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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublikacjaA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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Tryton Supercomputer Capabilities for Analysis of Massive Data Streams
PublikacjaThe recently deployed supercomputer Tryton, located in the Academic Computer Center of Gdansk University of Technology, provides great means for massive parallel processing. Moreover, the status of the Center as one of the main network nodes in the PIONIER network enables the fast and reliable transfer of data produced by miscellaneous devices scattered in the area of the whole country. The typical examples of such data are streams...
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Adaptive Method of Adjusting Flowgraph for Route Reconstruction in Video Surveillance Systems
PublikacjaPawlak’s flowgraph has been applied as a suitable data structure for description and anal- ysis of human behaviour in the area supervised with multicamera video surveillance system. Infor- mation contained in the flowgraph can be easily used to predict consecutive movements of a partic- ular object. Moreover, utilization of the flowgraph can support reconstructing object route from the past video images. However, such a flowgraph with...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Automatic Clustering of EEG-Based Data Associated with Brain Activity
PublikacjaThe aim of this paper is to present a system for automatic assigning electroencephalographic (EEG) signals to appropriate classes associated with brain activity. The EEG signals are acquired from a headset consisting of 14 electrodes placed on skull. Data gathered are first processed by the Independent Component Analysis algorithm to obtain estimates of signals generated by primary sources reflecting the activity of the brain....
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Exploring Cause-and-Effect Relationships Between Public Company Press Releases and Their Stock Prices
PublikacjaThe aim of the work is to design and implement a method of exploring the cause-and-effect relationships between company announcements and the stock prices on NASDAQ stock exchange, followed by a brief discussion. For this purpose, it was necessary to download the stock quotes of selected companies from the NASDAQ market from public web sources. Additionally, media messages related to selected companies had to be downloaded, and...
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Flood Classification in a Natural Wetland for Early Spring Conditions Using Various Polarimetric SAR Methods
PublikacjaAbstract--- One of the major limitations of remote sensing flood detection is the presence of vegetation. Our study focuses on a flood classification using Radarsat-2 Quad-Pol data in a natural floodplain during leafless, dry vegetation (early spring) state. We conducted a supervised classification of a data set composed of nine polarimetric decompositions and Shannon entropy followed by the predictors' importance estimation to...
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Artificial intelligence models in prediction of response to cardiac resynchronization therapy: a systematic review
PublikacjaThe aim of the presented review is to summarize the literature data on the accuracy and clinical applicability of artificial intelligence (AI) models as a valuable alternative to the current guidelines in predicting cardiac resynchronization therapy (CRT) response and phenotyping of patients eligible for CRT implantation. This systematic review was performed...
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A Parallel Genetic Algorithm for Creating Virtual Portraits of Historical Figures
PublikacjaIn this paper we present a genetic algorithm (GA) for creating hypothetical virtual portraits of historical figures and other individuals whose facial appearance is unknown. Our algorithm uses existing portraits of random people from specific historical period and social background to evolve a set of face images potentially resembling the person whose image is to be found. We then use portraits of the person's relatives to judge...
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Rapid Evaluation of Poultry Meat Shelf Life Using PTR-MS
PublikacjaThe use of proton transfer reaction mass spectrometry (PTR-MS) for freshness classification of chicken and turkey meat samples was investigated. A number of volatile organic compounds (VOCs) were selected based on the correlation (> 95%) of their concentration during storage at 4 °C over a period of 5 days with the results of the microbial analysis. In order to verify if the selected compounds are not sample-specific, a number...
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Greencoin: prototype of a mobile application facilitating and evidencing pro-environmental behavior of citizens
PublikacjaAmong many global challenges, climate change is one of the biggest challenges of our times. While it is one of the most devastating problems humanity has ever faced, one question naturally arises: can individuals make a difference? We believe that everyone can contribute and make a difference to the community and lives of others. However, there is still a lack of effective strategies to promote and facilitate pro-environmental...
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seafloor characterisation combined approach using multibeam sonar echo signal processing and image analysis
PublikacjaThe authors propose the approach to seafloor characterisation which relies on the combined, concurrent use of two different techniques: (i) multibeam sonar image analysis and (ii) multibeam seabed echoes processing. The first technique is based on constructing the grey-level sonar images of the seabed extracted from the echoes received in the consecutive soundings. Then, the set of parameters describing the local region of sonar...
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Using angular dependence of multibeam echo features in seabed classification
PublikacjaThe new approach to seabed classification based on processing multibeam sonar echoes is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry measurements or underwater object imaging, are also the promising tool in seafloor identification and classification, having several advantages over conventional single beam echosounders. The proposed seabed classification...
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Environmental risk assessment of Polish wastewater treatment plant activity
PublikacjaWastewater treatment plants (WWTPs) play an extremely important role in shaping modern society's environmental wellbeing and awareness, however only well operated and supervised systems can be considered as environmentally sustainable. For this reason, an attempt was undertaken to assess the environmental burden posed by WWTPs in major Polish cities by collecting water samples prior to and just after wastewater release points....
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublikacjaShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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Expedited optimization of antenna input characteristics with adaptive Broyden updates
PublikacjaSimulation-driven adjustment of geometry and/or material parameters is a necessary step in the design of contemporary antenna structures. Due to their topological complexity, other means, such as supervised parameter sweeping, does not usually lead to satisfactory results. On the other hand, rigorous numerical optimization is computationally expensive due to a high cost of underlying full-wave electromagnetic (EM) analyses, otherwise...
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Monitoring Trends of Land Use and Land Cover Changes in Rajang River Basin
PublikacjaIn this study, the spatiotemporal changes in land use and land cover (LULC) were evaluated from 1992 to 2015 for the Rajang River Basin (RRB) located in the Sarawak State of Malaysia. The changes in water bodies cropped lands, and forests were assessed based on the available remotely sensed satellite data. Supervised classification with the Maximum-Likelihood-Algorithm technique was adopted for monitoring the LULC changes using...