Browsing by Subject "artificial intelligence"

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Analiza cech osobniczych sygnału głosowego
(Data obrony: 2018-01-29) Pacułt, Rafał
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
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Aplikacja desktopowa do rozpoznawania gestów
(Data obrony: 2018-07-06) Dobrzyński, Kamil
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
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Application of artificial intelligence in selected issues of game theory
(Data obrony: 2016-09-19) Słyś, Przemysław
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Open Access ,
Application of Basic Machine-Learning Classifiers for Automatic Anomaly Detection in Shewhart Control Charts
(Wydawnictwa AGH, 2024) Woźniak, Aleksander; Krawiec, Klaudia; Książek, Roger
In today’s dynamic technological environment, innovation plays a crucial role – especially for manufacturing enterprises that constantly strive to improve the quality of their products. This article examines the quality-management issue in a company producing car rims. It was identified that real-time quality control can sometimes be unreliable due to controller fatigue, leading to erroneous data interpretation or delayed responses to deviations in the production process. The study aimed to investigate the possibility of eliminating or significantly reducing these errors by employing a tool that is based on artificial intelligence. The article covers the preparation of training data, the training of classifiers, and the evaluation of their effectiveness in analyzing control charts in real time. The adopted hypothesis assumes that machine-learning classifiers can be effective methods of support for quality controllers. The research began with collecting measurement data from the machine and dividing it into training and test sets. The obtained results were evaluated using standard quality measures for machine-learning models. The results showed that the use of artificial intelligence can bring significant benefits in improving quality supervision in the production process of car rims.
Access status: Open Access ,
Application of Fuzzy Cognitive Maps to analysis of development scenarios for academic units
(Wydawnictwa AGH, 2013) Szwed, Piotr
Dla wielu klas zagadnień podejmowanie decyzji, określenie strategii postępowania lub formułowanie ocen na podstawie precyzyjnych modeli ilościowych może być bardzo trudne w realizacji. Rozmyte mapy kognitywne (ang. FCM - Fuzzy Cognitive Maps) są znanym narzędziem jakościowej analizy systemów wykorzystującym prostą reprezentację wiedzy w postaci grafu pojęć i zależności przyczynowych pomiędzy nimi. Ich zaletą jest zarówno łatwość gromadzenia wiedzy, jak i prostota technik wnioskowania bliska sieciom neuronowym. Celem artykułu jest opisanie eksperymentu polegającego zastosowaniu FCM dla analizy zagadnienia słabo poddającego się ocenie ilościowej, jakim jest prognoza rozwoju jednostek naukowo-dydaktycznych. Praca podsumowuje rezultaty analizy w postaci scenariuszy rozwoju dla czterech reprezentatywnych klas jednostek: silnych, średnich, słabych z potencjałem i słabych oraz omawia zebrane obserwacje dotyczące wnioskowania z wykorzystaniem rozmytych map kognitywnych.
Access status: Open Access ,
Artificial intelligence approaches to determine graphite nodularity in ductile iron
(AGH University of Science and Technology Press, 2021) Brait, Maximilian; Koppensteiner, Eduard; Schindelbacher, Gerhard; Li, Jiehua; Schumacher, Peter
The complex metallurgical interrelationships in the production of ductile cast iron can lead to enormous differences in graphite formation and local microstructure by small variations during production. Artificial intelligence algorithms were used to describe graphite formation, which is influenced by a variety of metallurgical parameters. Moreover, complex physical relationships in the formation of graphite morphology are also controlled by boundary conditions of processing, the effect of which can hardly be assessed in everyday foundry operations. The influence of relevant input parameters can be predetermined using artificial intelligence based on conditions and patterns that occur simultaneously. By predicting the local graphite formation, measures to stabilise production were defined and thereby the accuracy of structure simulations improved. In course of this work, the most important dominating variables, from initial charging to final casting, were compiled and analysed with the help of statistical regression methods to predict the nodularity of graphite spheres. We compared the accuracy of the prediction by using Linear Regression, Gaussian Process Regression, Regression Trees, Boosted Trees, Support Vector Machines, Shallow Neural Networks and Deep Neural Networks. As input parameters we used 45 characteristics of the production process consisting of the basic information including the composition of the charge, the overheating time, the type of melting vessel, the type of the inoculant, the fading, and the solidification time. Additionally, the data of several thermal analysis, oxygen activity measurements and the final chemical analysis were included. Initial programme designs using machine learning algorithms based on neural networks achieved encouraging results. To improve the degree of accuracy, this algorithm was subsequently adapted and refined for the nodularity of graphite.
Access status: Open Access ,
Attractiveness of Games and Business Simulations in Teaching Process
(Wydawnictwa AGH, 2023) Wieroński, Tomasz
This study aims to assess the attractiveness of games and business simulations in the teaching process. The presented overview concerns their application in primary and secondary schools, at universities and in business. Among the most important benefits were the development of participants’ creativity and the use of games as effective tools for imparting practical knowledge. The chapter presents the results of a survey completed by 97 participants. The study showed that the use of games and business simulations is positively perceived by trainees and students, but this form of knowledge transfer must be used with awareness of its limitations relative to other forms. The last section focuses on conclusions and suggested possibilities for further development of games and simulations in the teaching process. Colloquially: does the use of business games make learning a more enjoyable and less boring process? Is the preferred option for acquiring practical knowledge the choice of a book or attending a lecture, or would participants prefer game- and simulation-based learning?
Access status: Open Access ,
Autentyczność osobowa w perspektywie teorii dezintegracji pozytywnej
(Wydawnictwa AGH, 2012) Branicki, Wacław
The problems discussed in the first part of the paper include relations between phenomenon of authenticity and influence of pharmacology on the human psyche and the issue of artificial intelligence. In the second part of the article the relationship between the notion of authenticity and naturalness has been analysed. In the third part, the above problem has been presented within the framework of Kazimierz Dąbrowski's concept.
Access status: Open Access ,
Choroba Alzheimera jako przykład desynchronizacji funkcjonowania i zbiór neurokognitywnych wzorców stanowiących potencjalne źródło zasobów dla rozwoju sztucznej inteligencji
(Wydawnictwa AGH, 2022) Kaszyńska, Anna Aleksandra
The review article focuses on the potential development of Artificial Intelligence by extracting fixed patterns and regularities that enable the improvement and refinement of advanced analyses in the field of artificial neural network learning. Is conducted through the prism of the neurocognitive view of Alzheimer’s disease as a potential set of neurocognitive patterns constituting a potential source of resources for the development of artificial intelligence. It is closely related to encephalography, both used to detect pathological dementia changes, and the analysis of brain activity itself, showing the existence of repeated regularities. These patterns, analogic in the astrophysical Lagrandrean mapping analysis of the galaxy, seem to have the potential to develop Artificial Intelligence. Especially, following the idea of perceiving Alzheimer’s disease as a global functional desynchronisation, global neurodegenerative changes may provide potential resources that, through mathematical and algebraic transformations, to serve as a foundation for the development of Artificial Intelligence.
Computer Methods in Materials Science
AGH University Press (2020-)
ISSN: 2720-4081 e-ISSN: 2720-3948
Access status: Open Access ,
Explainable Spark-based PSO clustering for intrusion detection
(Wydawnictwa AGH, 2024) Ben Ncir, Chiheb Eddine; Ben Haj Kacem, Mohamed Aymen; Alattas, Mohammed
Given the exponential growth of available data in large networks, the existence of rapid, transparent, and explainable intrusion detection systems has become of highly necessity to effectively discover attacks in such huge networks. To deal with this challenge, we propose a novel explainable intrusion detection system based on Spark, Particle Swarm Optimization (PSO) clustering, and eXplainable Artificial Intelligence (XAI) techniques. Spark is used as a parallel processing model for the effective processing of large-scale data, PSO is integrated to improve the quality of the intrusion detection system by avoiding sensitive initialization and premature convergence of the clustering algorithm and finally, XAI techniques are used to enhance interpretability and explainability of intrusion recommendations by providing both micro and macro explanations of detected intrusions. Experiments are conducted on large collections of real datasets to show the effectiveness of the proposed intrusion detection system in terms of explainability, scalability, and accuracy. The proposed system has shown high transparency in assisting security experts and decision-makers to understand and interpret attack behavior.
Access status: Open Access ,
Grafowe języki obrazowe w znaczeniowym opisie przestrzennych struktur naczyń wieńcowych
(2005) Ogiela, Marek; Trzupek, Mirosław
In this paper has been proposed developing the new syntactic - semantic meaning description of spatial coronary arteries structure. Thanks such description will be possible to make essentially steered semantic interpretation of section coronary arteries morphology, what will allow us fast identification and automatisation of lumen structure detection. In this aim has been used graph image languages based on the expansive graph grammars of edNLC type, enabling creation the universal and informative meaning description of spatial coronary arteries structure. Application of such semantic description in the integrated modules of intelligent systems medical diagonosis, supporting the early detection stricture which defect the flow of oxidizing blood to given area of cardiac muscle.
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Informatyka w ogólnym zarysie
(Wydawnictwa Naukowo-Techniczne, 2003) Brookshear, Glenn J.
Access status: Open Access ,
Intelligent control of CO₂-EOR process
(Wydawnictwa AGH, 2018) Mikołajczak, Edyta; Stopa, Jerzy; Wojnarowski, Paweł; Janiga, Damian; Czarnota, Robert
One of the enhanced oil recovery methods, which enables to recover an additional 15-20% of oil resources is the $CO_2$-EOR method based on carbon dioxide injection into partially depleted reservoirs. Determination of the optimal process control facilitates effective use of natural resources. The idea of this paper is to develop an algorithm that optimizes the $CO_2$-EOR process. This algorithm is based on the combination of artificial intelligence, control theory and computer simulation of hydrocarbon reservoirs. The effect of the proposed solution is the $CO_2$-EOR process control, which is optimal in the case of the adopted objective function expressing the economic value of the project. The obtained results suggest that the use of artificial intelligence methods in the hydrocarbon production allows to improve the process efficiency by an additional 31% compared to the project carried out with the use of engineering knowledge.
Access status: Restricted ,
Machine learning in intrusion detection
(Data obrony: 2019-07-12) Faber, Kamil
Wydział Informatyki, Elektroniki i Telekomunikacji
Access status: Open Access ,
Measure happiness – a contribution to Stanislaw Lem’s definition of happiness. Part 2: Limits of approach
(Wydawnictwa AGH, 2024) Sierotowicz, Tadeusz; Sierotowicz, Tomasz
In the fable Kobyszczę, Stanisław Lem proposes a definition of Happiness that allows for the formulation of a mathematical model describing the intensity level of Happiness, which can be experienced by humans in different situations. Completing, correcting, and contextualization of the existing model are the main issues addressed in this article. The proposed mathematical model is not about the same Happiness experienced by different individuals. It is about the measure of intensity level of Happiness, which is experienced by an individual in many situations. That is why the proposed model describes Happiness in a new area of research located in digital humanities, where AI can be used to continue future work. The issue related to model reflects on the possibility of translating complex issues, e.g. philosophical ones, into the language of science specifically mathematics. The definitional procedure and the contextualization of the issues of good and evil and Happiness proposed by Lem in the fable Kobyszczę flow from his conception of the art of writing as the art of translating literary, philosophical, or theological issues into the language of biology, chemistry, physics, mathematics, or computer science, thus contributing to the trend of considerations in the field of digital humanities and developing by use of Artificial Intelligence (AI). Consequently, an analysis of the narrative structure of the fairytale will identify the limits of applying this kind of approach to the question of translatability. Issues linking Kobyszczę to some of the matters being discussed in the context of artificial intelligence (AI) will also be identified.
Access status: Open Access ,
Metoda wymuszania wewnętrznych wzorców w jednokierunkowej sieci klasyfikującej
(Wydawnictwa AGH, 2006) Kolibabka, Marcin; Cader, Andrzej
Creating and later learning of one-way neural networks depends from many factors. Selection of many them has estimated and experimental character. The proposed in the article method allows to the weakness of the influence of the not optimal choice of the net structure, also speed and momentum values are less influential then in classic Back Propagation Method.
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Metody i techniki sztucznej inteligencji
(Wydawnictwo Naukowe PWN, 2009) Rutkowski, Leszek
Access status: Restricted ,
Metody i techniki sztucznej inteligencji : inteligencja obliczeniowa
(Wydawnictwo Naukowe PWN, 2006) Rutkowski, Leszek
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Metody inteligencji komputerowej w analizie danych geofizycznych
(Data obrony: 2018-01-29) Stachura, Gabriel
Wydział Geologii, Geofizyki i Ochrony Środowiska
W pracy przedstawiono model statystyczny ośrodka geologicznego, na którym dokonano klasyfikacji litologicznej na podstawie danych profilowań otworowych. Model utworzono z wykorzystaniem metod sztucznej inteligencji komputerowej. Przeanalizowano 3 odmienne typy sieci neuronowych: klasyczne (ANN), sieci wektorów nośnych (SVM) oraz głębokiego uczenia. Głębokie uczenie jest najbardziej nowatorską metodą maszynowego uczenia, użyteczną zwłaszcza w przypadku pracy z dużymi bazami danych. Metody testowano w dwóch odmiennych środowiskach obliczeniowych – pakiecie R oraz środowisku STATISTICA. Uzyskane rezultaty na poziomie ponad 80% poprawności klasyfikacji pozwalają stwierdzić, iż opracowany model z dość dobrą precyzją oddaje rzeczywisty stan górotworu. Ze względu na dynamiczny rozwój tego rodzaju metod eksploracji danych, należy spodziewać się ich większej dokładności oraz szerszego zastosowania.