Wyszukiwarka
prof. dr hab. inż. Zdzisław Kowalczuk
Zatrudnienie
- Kierownik katedry w Katedra Systemów Decyzyjnych i Robotyki
- Profesor w Katedra Systemów Decyzyjnych i Robotyki
Publikacje
Filtry
wszystkich: 219
Katalog Publikacji
Rok 2021
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Inteligentny system decyzyjny jako maszynowa realizacja procesów poznawczych i motywacyjnych
PublikacjaW niniejszej książce przedstawiono własny, kompletny i spójny oraz realizowalny model Inteligentnego Systemu Decyzji (ISD), oparty na wiedzy zaczerpniętej z psychologii z elementami motywacyjnymi, w skład którego wchodzi podsystem xEmotion. Wykorzystuje on funkcję i strukturę ludzkich procesów decyzyjnych oraz pewne szczegółowe mechanizmy dedykowane dla obliczeniowych systemów emocji. Model ISD jest w szczególności przeznaczony...
Rok 2022
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublikacjaDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublikacjaDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is not uncommon for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected...
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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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Autonomous pick-and-place system based on multiple 3Dsensors 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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Categorization of emotions in dog behavior based on the deep neural network
PublikacjaThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublikacjaThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Qualia: About Personal Emotions Representing Temporal Form of Impressions - Implementation Hypothesis and Application Example
PublikacjaThe aim of this article is to present the new extension of the xEmotion system as a computerized emotional system, part of an Intelligent System of Decision making (ISD) that combines the theories of affective psychology and philosophy of mind. At the same time, the authors try to find a practical impulse or evidence for a general reflection on the treatment of emotions as transitional states, which at some point may lead to the...
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublikacjaIn this article, specific methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublikacjaIn this study, dedicated methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...
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System diagnostyki oddechowej oparty na konwolucyjnych sieciach neuronowych
PublikacjaChoroby układu oddechowego człowieka od zawsze były obciążeniem dla całego społeczeństwa. Sytuacja stała się szczególnie trudna po wybuchu pandemii COVID-19. Jednak nawet teraz nierzadko zdarza się, że ludzie konsultują się ze swoim lekarzem zbyt późno, już po niepożądanym rozwinięciu się choroby. W celu ochrony pacjentów przed ciężką chorobą płuc, zaleca się jak najwcześniejsze wykrycie wszelkich objawów zaburzających pracę układu...
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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...
Rok 2023
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Cognitive motivations and foundations for building intelligent decision-making systems
PublikacjaConcepts based on psychology fit well with current research trends related to robotics and artificial intelligence. Biology-inspired cognitive architectures are extremely useful in building agents and robots, and this is one of the most important challenges of modern science. Therefore, the widely viewed and far-reaching goal of systems research and engineering is virtual agents and autonomous robots that mimic human behavior in...
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Discrete identification of continuous non-linear and non-stationary dynamical systems that is insensitive to noise correlation and measurement outliers
PublikacjaThe paper uses specific parameter estimation methods to identify the coefficients of continuous-time models represented by linear and non-linear ordinary differential equations. The necessary approximation of such systems in discrete time in the form of utility models is achieved by the use of properly tuned `integrating filters' of the FIR type. The resulting discrete-time descriptions retain the original continuous parameterization...
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International Conference on Diagnostics of Processes and Systems 2022
PublikacjaWydarzenie stanowiło 15 ogniwo cyklu organizowanego od 1996 roku, naprzemiennie przez Politechnikę Warszawską, Uniwersytet Zielonogórski oraz Politechnikę Gdańską. Tegoroczna edycja konferencji została objęta patronatem JM Rektora Politechniki Gdańskiej, prof. Krzysztofa Wilde, Komitetu Automatyki i Robotyki Polskiej Akademii Nauk, Towarzystwa Konsultantów Polskich (FSNT-NOT) oraz Polskiego Stowarzyszenia Pomiarów Automatyki i...
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Zarząd POLSPAR w latach 2020-2023
PublikacjaW trakcie kadencji 2020-2023 na zebraniach Zarządu Członkowie często podejmowali dyskusję na temat najbardziej dokuczliwych problemów działania uczelni wynikających ze zmian w ustawie Prawo o Szkolnictwie Wyższym i Nauce, kompetencjach i formach naukowej aktywności rad naukowych dyscyplin, procedur nadawania stopni i tytułów naukowych, czy w końcu o nowej nazwie dyscypliny Automatyka, Elektronika, Elektrotechnika i Technologie...
Rok 2024
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Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming
PublikacjaIn order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming (ADP) technique based on the internal model principle (IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback, merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization...
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