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Search results for: EMBEDDED SYSTEMS, DEEP LEARNING, EDGE COMPUTING, MACHINE LEARNING
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International Conference on Embedded Wireless Systems and Networks
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International Workshop on Software and Compilers for Embedded Systems
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ACM Conference on Embedded Networked Sensor Systems
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublicationThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Remote measurement of building usable floor area - Algorithms fusion
PublicationRapid changes that are taking place in the urban environment have significant impact on urban growth. Most cities and urban regions all over the world compete to increase resident and visitor satisfaction. The growing requirements and rapidity of introducing new technologies to all aspects of residents' lives force cities and urban regions to implement "smart cities" concepts in their activities. Real estate is one of the principal...
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublicationIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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Mikroekonomia_2 lato 2023/24
e-Learning CoursesKontynuacja zajęć z mikroekonomii z sem. 1. Prowadząca dr Aniela Mikulska. Uczymy się wg metody flip blended learning.
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublicationIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Basic evaluation of limb exercises based on electromyography and classification methods
PublicationSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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IEEE/IFIP International Conference on Embedded and Ubiquitous Computing
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Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment
PublicationClinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge imposes to CDSS the continuous update of the domain knowledge and decision criteria. Traditional approaches require costly tedious manual maintenance of the CDSS knowledge bases and repositories. Often, such an effort cannot be assumed by medical teams, hence...
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Category-Based Workload Modeling for Hardware Load Prediction in Heterogeneous IaaS Cloud
PublicationThe paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.
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Chosen Methods Supporting Didacts of Descriptive Geometry
PublicationThe article presents reflections on the practical ways of supporting the teaching processes of descriptive geometry in the context of psychological theories of learning and motivation.
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublicationIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Leveraging spatio-temporal features for joint deblurring and segmentation of instruments in dental video microscopy
PublicationIn dentistry, microscopes have become indispensable optical devices for high-quality treatment and micro-invasive surgery, especially in the field of endodontics. Recent machine vision advances enable more advanced, real-time applications including but not limited to dental video deblurring and workflow analysis through relevant metadata obtained by instrument motion trajectories. To this end, the proposed work addresses dental...
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Bayesian Optimization for solving high-frequency passive component design problems
PublicationIn this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all...
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Computing methods for fast and precise body surface area estimation of selected body parts
PublicationCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
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Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublicationThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
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Analysis of Factors Influencing the Prices of Tourist Offers
PublicationTourism is a significant branch of many world economies. Many factors influence the volume of tourist traffic and the prices of trips. There are factors that clearly affect tourism, such as COVID-19. The paper describes the methods of machine learning and process mining that allow for assessing the impact of various factors (micro, mezzo and macro) on the prices of tourist offers. The methods were used on large sets of real data...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublicationLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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The influence of reinforcement on load carrying capacity and cracking of the reinforced concrete deep beam joint
PublicationThe paper presents the results of experimental research of the spatial reinforced concrete deep beam systems orthogonally reinforced and with additional inclined bars. Joint of the deep beams in this research was composed of the longitudinal deep beam with a cantilever suspended at the transversal deep beam. The cantilever deep beam was loaded throughout the depth and the transversal deep beam was loaded at the mid-span by longitudinal...
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Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje
PublicationGeneratywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...
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Tacit knowledge acquisition & sharing, and its influence on innovations: A Polish/US cross-country study
PublicationThis study measures the relationship between tacit knowledge sharing and innovation in the Polish (n=350) and US (n=379) IT industries. Conceptually, the study identifies the potential sources of tacit knowledge development by individuals. That is, the study examines how “learning by doing” and “learning by interaction” lead to a willingness to share knowledge and, as a consequence, to support process and product/service innovation....
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Wiktoria Wojnicz dr hab. inż.
PeopleDSc in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2009 (with distinction) List of papers (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E., Analysis of...
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Occupational Health and Safety Ergonomics - L-15/Ć-0/L-0/P-0, FMEST, ENERGY TECHNOLOGIES, I degree, se 01, stationary, (PG_00041987), winter semester 2022/2023
e-Learning CoursesDefinitions of ergonomics, its subject, purpose and application. Description of the human-machine system environment. The concept of sustainable development. Environmental management systems. Human model and its characteristics. Human possibilities and industrial processes. Human work environment - material conditions. Principles of human work environment design. Safety and reliability of the human - machine - environment system....
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Occupational Health and Safety Ergonomics - L-15/C-0/L-0/P-0, ENERGY TECHNOLOGIES, se 01, (PG_00041987), winter semester, 2024/2025
e-Learning CoursesDefinitions of ergonomics, its subject, purpose and application. Description of the human-machine system environment. The concept of sustainable development. Environmental management systems. Human model and its characteristics. Human possibilities and industrial processes. Human work environment - material conditions. Principles of human work environment design. Safety and reliability of the human - machine - environment system....
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Occupational Health and Safety Ergonomics - L-15/C-0/L-0/P-0, ENERGY TECHNOLOGIES, se 01, (PG_00041987), winter semester, 2023/2024
e-Learning CoursesDefinitions of ergonomics, its subject, purpose and application. Description of the human-machine system environment. The concept of sustainable development. Environmental management systems. Human model and its characteristics. Human possibilities and industrial processes. Human work environment - material conditions. Principles of human work environment design. Safety and reliability of the human - machine - environment system....
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe 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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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Early warning models against bankruptcy risk for Central European and Latin American enterprises
PublicationThis article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warningmodels for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange...
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Building collective intelligence through experience: a survey on the use of the KREM model
PublicationThis article presents a survey on the use of KREM, a generic knowledge-based framework for building collective intelligence through experience. After a discussion on the disadvantages of the traditional architecture used to deploy intelligent systems, the KREM architecture (Knowledge, Rules, Experience, Meta-Knowledge) is presented. The novelty of the proposal comes from the inclusion of the capitalisation of experience and the...
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Moduł Warsztaty - narzędzie w procesie edukacji na uczelni wyższej
PublicationObecnie istnieje bardzo szeroka gama narzędzi informatycznych, które wspierają proces edukacji przy wykorzystaniu internetu na uczelniach wyższych. Wśród nieodpłatnych narzędzi powszechnie znana jest platforma Moodle. W artykule zaprezentowano jeden z jej modułów – Warsztaty. Przedstawiono jego funkcjonalność. Opisano jego zalety i wady w nauczaniu łączącym techniki online i tradycyjne na uczelni wyższej (blended-learning). W artykule...
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Anna Czaja mgr inż.
PeopleAfter completing Master's studies in Computer Science (Gdansk University of Technology, Faculty of Electronics, Telecommunications and Informatics), she worked as a programmer for several years. Currently employed as an assistant at the Department of Applied Informatics in Management (Gdańsk University of Technology, Faculty of Management and Economics). Participant in third degree doctoral studies at the Faculty of Management...
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Podejście nauczycieli akademickich do rozwoju narzędzi e-learningowych na wyższych uczelniach technicznych
PublicationPlatforma edukacyjna na uczelni wyższej stała się już standardem. Jest wyznacznikiem nowoczesno- ści danej uczelni. Wpływa na jej konkurencyjność. Mimo to, istnieje przekonanie że środowisko nauczycieli akademickich nie jest gotowe do akceptacji nowych środków nauczania. Postanowiono zbadać ten problem. Artykuł zawiera odpowiedź na pytanie jaki stosunek do metod e-nauczania panuje wśród nauczycieli akademickich, nie posiadających...
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Considerations of Computational Efficiency in Volunteer and Cluster Computing
PublicationIn the paper we focus on analysis of performance and power consumption statistics for two modern environments used for computing – volunteer and cluster based systems. The former integrate computational power donated by volunteers from their own locations, often towards social oriented or targeted initiatives, be it of medical, mathematical or space nature. The latter is meant for high performance computing and is typically installed...
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Kształcenie ustawiczne – trendy w krajach regionu Morza Bałtyckiego
PublicationKwestie kształcenia ustawicznego i dostosowania kwalifikacji do potrzeb rynku pracy są przedmiotem dyskusji zarówno na szczeblu europejskim, jak i poszczególnych krajów. Działania administracji powinny zmierzać w kierunku określenia zapotrzebowania na określone umiejętności oraz aktywizacji społeczeństwa poprzez realizację idei uczenia się przez całe życie. Doświadczenia krajów skandynawskich dostarczają wielu przykładów dobrych...
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Bewertung der qualität von online lernmodulen = Próba oceny jakości e-Lerningowych modułów online
PublicationW pracy dokonano klasyfikacji rozwiązań modułów (systemów) e-Learning wg. sposobu ich tworzenia (tj. systemy autorskie, komercyjne, otwarte, zamknięte, standardowe, niestandardowe), funkcjonalności, interaktywności, obciążania sieci. Przedstawiono również wybrane kryteria (tj. merytoryczne, dydaktyczne i multimedialne) oceny jakości modułów dostępnych online pod kątem ich wykorzystywania w systemach zdalnego nauczania. Na zakończenie...
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Joint Conference on New Methods in Language Processing and Computational Natural Language Learning
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Hybrid Laboratory of Radio Communication With Online Simulators and Remote Access
PublicationContribution: Two toolsets for the remote teaching of radio communication laboratory classes: 1) online simulators for individual work of students and 2) a remote access system to laboratory workstations for group work. Initial assumptions and method of implementation of both tools are presented. Background: The COVID-19 pandemic has forced a change in teaching at all levels of education. The specificity of practical classes, such...
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Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
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Management and Economics 2022
e-Learning CoursesIntroduction to Management and Economics, Learning by Doing method based upon trends in geopolitics and modern economics frameworks, strategy and Business Models Management Tools SEMESTR II Green Technologies and Monitoring
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublicationThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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The Double Cognitive Bias of Mistakes: A Measurement Method
PublicationThere is no learning without mistakes. However, making mistakes among knowledge workers is s�ll seeing shameful. There is a clash between posi�ve a�tudes and beliefs regarding the power of gaining new (tacit) knowledge by ac�ng in new contexts and nega�ve a�tudes and beliefs toward accompanying mistakes that are sources of learning. These contradictory a�tudes create a bias that is doubled by the other shared solid belief...
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Method of selecting the LS-SVM algorithm parameters in gas detection process
PublicationIn this paper we showed the method of resistive gas sensors data processing. The UV irradiation and temperature modulation was applied to improve gas sensors’ selectivity and sensitivity. Noise voltage across the sensor’s terminals (proportional to its resistance fluctuations) was recorded to estimate power spectral density. This function was an input data vector for LS-SVM (least squares – support vector machine) algorithm, which...
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Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry
PublicationWe describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublicationTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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International Conference on Compilers, Architecture, and Synthesis for Embedded Systems
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Experience based knowledge representation for Internet of Things and Cyber Physical Systems with case studies
PublicationCyber Physical Systems and Internet of Things have grown significant attention from industry and academia during the past decade. The main reason behind this interest is the capabilities of such technologies to revolutionize human life since they appear as seamlessly integrating classical networks, networked objects and people to create more efficient environments. However, enhancing these technologies with intelligent skills becomes...