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Wyniki wyszukiwania dla: PROBLEM-BASED LEARNING
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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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Learning
Czasopisma -
Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Evolutionary Sets of Safe Ship Trajectories: problem dedicated operators
PublikacjaThe paper presents the optimization process of the evolutionary sets of safe ship trajectories method, with a focus on its problem-dedicated operators. The method utilizes a customized evolutionary algorithm to solve a constrained optimization problem. This problem is defined as finding a set of cooperating trajectories (a set is an evolutionary individual) of all the ships involved in the encounter situation. The resulting trajectories...
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A construction for the hat problem on a directed graph
PublikacjaA team of n players plays the following game. After a strategy session, each player is randomly fitted with a blue or red hat. Then, without further communication, everybody can try to guess simultaneously his own hat color by looking at the hat colors of the other players. Visibility is defined by a directed graph; that is, vertices correspond to players, and a player can see each player to whom he is connected by an arc. The...
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E-learning workshops with Norbert Berger
Kursy OnlineThe series of workshops supports MBA faculty in planning, designing, delivering and assessing blended and online modules for their cohorts. It is supplemented by individual coaching to create Moodle and conferencing solutions and their delivery.
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[ILiT, IŚGiE] Reliability-Based Optimization (RBO) - 2022/23
Kursy Online -
[ILiT, IŚGiE] Reliability-Based Optimization (RBO) - 2023/24
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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublikacjaE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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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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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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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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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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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Evolutionary algorithm and decisional DNA for multiple travelling salesman problem
PublikacjaIn the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization...
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Problem wspólnotowego kształtowania środowiska mieszkaniowego
PublikacjaCommunity based shaping of housing environmentA sustainable development of housing environment depends on socio-economical context. Interest towards locality in western countries has a completely different basis than in the post-communist ones. Social capital, which shows e.g. in trust, as well as ecological awareness are totally different. We do not belong to saturated societies. There is a distinct issue of community shaping...
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Concrete mix design using machine learning
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Overview of Scalability and Reliability Problem in SDN Networks
PublikacjaIn the paper an overview of scalability and reliability in the SDN (Software Defined Networks) networks has been presented. Problems and limitations for guaranteeing scalability and reliability in SDN networks have been indicated. Known methods for assuring scalability and reliability in SDN networks have been described. Projects from research communities for resolving issues with scalability and reliability in SDN networks have...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Air trapping problem during infiltration on the large areas
PublikacjaThe process of flow modeling in unsaturated porous medium is often found in many fields of sciences: geology, fluid mechanics, thermodynamics, microbiology or chemistry. Problem is relatively complicated due to complexity of the system which contains three phases: water, air and soil skeleton. The flow of water in such a medium can be described using two-phase (2PH) flow formulation, which accounts the inflow of air and water phases,...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Wyróżniki modelu biznesu przedsiębiorstwa inteligentnego
PublikacjaBurzliwa zmiana środowiska biznesowego wpływa na ludzi tak, że generują oczekiwania na wyroby i usługi zaspokajające ich dotychczasowe i nowe potrzeby w coraz większym stopniu. W ten sposób przed menedżerami powstają wciąż nowe, bardziej skomplikowane i wysublimowane wymagania. W takich uwarunkowaniach prowadzenia biznesu sukces osiąga to przedsiębiorstwo, które jest inteligentne. W takiej perspektywie celem badań było wyłonienie...
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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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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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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublikacjaPurpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...
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Projektowanie łuków koszowych dostosowane do pomiarów satelitarnych
PublikacjaW pracy przedstawiono nową metodę projektowania rejonu zmiany kierunku trasy kolejowej, dostosowaną do techniki ciagłych pomiarów satelitarnych. Metoda ta może się okazać szczególnie przydatna podczas projektowania regulacji osi istniejącego toru, kiedy określenie obu kierunków głównych trasy okazuje się niemożliwe. Jedynym rozwiązaniem staje się wówczas wprowadzenie do układu geometrycznego dwóch łuków kołowych o różnym promieniu,...
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Projektowanie układów geometrycznych toru z zastosowaniem optymalizacji wielokryterialnej
PublikacjaW pracy przedstawiono metodę projektowania odcinków trasy kolejowej położonych w łuku, dostosowaną do techniki mobilnych pomiarów satelitarnych. Rozwiązanie problemu projektowego wykorzystuje zapis matematyczny i polega na wyznaczeniu uniwersalnych równań opisujących całość układu geometrycznego. Odbywa się to sekwencyjnie, obejmując kolejne fragmenty tegoż układu. Procedura projektowania ma charakter uniwersalny, gdyż w ogólnym...
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Narzędzia treningu twórczości jako pomoc w kształceniu projektantów
PublikacjaKreatywność rozwijać. Na tym założeniu opiera się międzynarodowy program edukacyjny Odyssey of the Mind (Odyseja Umysłu). W programie zespoły młodych osób pracują metodą projektową, wykorzystując różnorodne techniki treningu twórczości, nad rozwiązaniem abstrakcyjnego problemu rozbieżnego. Część absolwentów programu wybiera kierunki kreatywne jako naturalną kontynuację procesu edukacji. Elementy treningu twórczości można wykorzystać...
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GreedyMAX-type Algorithms for the Maximum Independent Set Problem
PublikacjaA maximum independent set problem for a simple graph G = (V,E) is to find the largest subset of pairwise nonadjacent vertices. The problem is known to be NP-hard and it is also hard to approximate. Within this article we introduce a non-negative integer valued functionp defined on the vertex set V(G) and called a potential function of agraph G, while P(G) = max{vinV(G)| p(v)} is called a potential of G. For any graph P(G) <= D(G),...
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BEZCZUJNIKOWE STEROWANIE WOLNOOBROTOWYM SILNIKIEM PMSM Z KOMPENSACJĄ MOMENTU ZACZEPOWEGO
PublikacjaW pracy przedstawiono propozycję rozwiązania problemu bezczujnikowego sterowania wolnoobrotową maszyną synchroniczną z magnesami trwałymi PMSM. Przedstawiono silnik PMSM, który zastosowano w stanowisku badawczym. Omówiono problem występowania tętnień momentu napędowego wynikający głównie ze znacznego momentu zaczepowego. Pokazano rozwiązanie kompensujące tętnienia momentu napędowego w silniku PMSM. Przygotowano procedurę startową...
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Normal-form preemption sequences for an open problem in scheduling theory
PublikacjaStructural properties of optimal preemptive schedules have been studied in a number of recent papers with a primary focus on two structural parameters: the minimum number of preemptions necessary, and a tight lower bound on shifts, i.e., the sizes of intervals bounded by the times created by preemptions, job starts, or completions. These two parameters have been investigated for a large class of preemptive scheduling problems,...
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Problem hałasu drogowego na przykładzie Gdyni
PublikacjaGłównym zagrożeniem dla klimatu akustycznego w Polsce jak i pozostałych krajów Unii Europejskiej jest hałas drogowy, który dotyka głównie duże aglomeracje miejskie. Oddziałuje on negatywnie na samopoczucie i zdrowie osób narażonych na jago działanie. Artykuł przedstawia ten problem na przykładzie pomiarów hałasu drogowego w Gdyni. W celu wykonania pomiarów równoważnego poziomu dźwięku wybrano dwa punkty pomiarowe zlokalizowane...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublikacjaText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Determinanty kreowania wartości marki poprzez media społecznościowe w gospodarce sieciowej
PublikacjaGłównym problemem badawczym podejmowanym w pracy, jest określenie struktury czynników determinujących kreowanie wartości marki w mediach społecznościowych. Dla rozwiązania tego problemu wykonano dwa badania. Pierwsze z nich dotyczyło określenia relacji pomiędzy wartością marki a jej pozycją w sieciach społecznościowych (model BV). Badanie to zrealizowano w oparciu o metody ilościowe: analizę statystyczną danych wtórnych i danych...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublikacjaContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
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WIELOLEKOOPORNE ZAKAŻENIA CANDIDA - PROBLEM XXI WIEKU!
PublikacjaW ostatnich latach obserwuje się dramatyczny wzrost zakażeń grzybiczych, których przyczyną są grzyby z rodzaju Candida (C). Większość zakażeń wywoływana jest przez C. albicans, C. glabrata, C. krusei, C. parapsilosis i C. tropicalis. Dotychczas najczęściej stosowanymi lekami przeciwko Candida spp były azole, jednakże ze względu na występowanie naturalnej oporności na te antybiotyki (C. glabrata i C. krusei) coraz częściej azole...
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Redefining The Modifiable Areal Unit Problem Within Spatial Econometrics, The Case of the Scale Problem
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Redefining the Modifiable Areal Unit Problem Within Spatial Econometrics, the Case of the Aggregation Problem
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublikacjaWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Stability criteria as constraints in a fleet of ships optimisation problem
PublikacjaRozwiązano problem dotyczący matematycznej optymalizacji floty statków wielozadaniowych typu rzeka-morze, przeznaczonych dla europejskiej żeglugi przybrzeżnej i eksploatowanych w obszarze Mórz Północnego i Bałtyckiego, na poziomie zadania transportowego za pomocą metod programowania nieliniowego z ograniczeniami. Zaproponowano metodę włączenia istniejących kryteriów skuteczności statków jako ograniczeń w ogólnym modelu optymalizacji...
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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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Multimedia industrial and medical applications supported by machine learning
PublikacjaThis article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...
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Mikroplastik – wielki problem?
WydarzeniaPolitechnika Otwarta zaprasza na pierwsze spotkanie z cyklu #CiekawiNauki. O mikroplastikach, zagrożeniach z nimi związanych oraz o jakości wody i sposobach jej poprawy opowiedzą eksperci.
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GNIAZDA PRZEDSIĘBIORCZOŚCI W STREFIE PODMIEJSKIEJ METROPOLII
PublikacjaProblem suburbanizacji jest wciąż aktualny w analizach rozwoju miast. Przybiera często formy spontanicznego rozlewania się miast (urban sprawl). Badacze tego problemu skupiają się przeważnie na rozwoju funkcji mieszkaniowej w strefach podmiejskich. Specyficzny charakter polskiego procesu suburbanizacji polega na równoległym rozwoju klasycznej suburbanizacji osiedleńczej oraz rozwoju mikro- oraz małych i średnich przedsiębiorstw....
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The computational complexity of the backbone coloring problem for planar graphs with connected backbones
PublikacjaIn the paper we study the computational complexity of the backbone coloring problem for planar graphs with connected backbones. For every possible value of integer parameters λ≥2 and k≥1 we show that the following problem: Instance: A simple planar graph GG, its connected spanning subgraph (backbone) HH. Question: Is there a λ-backbone coloring c of G with backbone H such that maxc(V(G))≤k? is either NP-complete or polynomially...