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Search results for: MARKDOWN, BOOKDOWN, R-EXAMS, TUTORIALS, MOODLE, E- LEARNING, WEBEXERCISES, GITHUB, DATA ANALYSIS.
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A comprehensive review of open data platforms, prevalent technologies, and functionalities
PublicationOpen data can play a crucial role in different sectors of the world,such as government, science, research, technology, culture, andfinance. There are several necessary measures that every organiza-tion needs to consider before opening data. There are three majorsteps to opening the data: (1) Preparation stage, and (2) launchingthe open data initiative (3) In this case, the feedback mechanismstudy such as expand and sustain stage,...
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Multimedia industrial and medical applications supported by machine learning
PublicationThis 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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Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers
PublicationThe process of organizational learning and proper knowledge management became today one of the major challenges for the organization acting in the knowledge-based economy. According to the observations of the authors of this paper the demand for formalization of knowledge management processes and organizational learning is particularly evident in research institutions, established either by the universities, or the companies. The...
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublicationOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
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Data in Brief
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Gdansk 2020, Grunwaldzka (E) street - video data - pedestrian, bicycles, vehicles
Open Research DataGdansk 2020, Grunwaldzka (E) street - video data - pedestrian, bicycles, vehicles
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Wykorzystanie Data Envelopment Analysis do porównania polityki wiekowej w krajach Unii Europejskiej
PublicationCelem artykułu jest zbudowanie modelu, bazującego na Data Envelopment Analysis (DEA), pozwalającego na porównanie działań związanych z polityką wiekową w krajach Unii Europejskiej. Zastosowano model z ograniczeniami na wagi, pozwalający na stworzenie rankingu i określenie kierunków kształtowania polityki wiekowej. Wykorzystano dane pochodzące z bazy danych Global AgeWatch Index 2013.
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Comprehensive determination of flavouring additives and nicotine in e-cigarette refill solutions. Part II: Gas-chromatography–mass spectrometry analysis
PublicationFlavouring compounds are an essential part of e-liquid products for cigarettes. In general, they are regarded as safe for ingestion, but they may have unrecognized risks when they are inhaled. In some cases, manufactures do not currently abide by the Tobacco Products Directive (2014/40/EU) and do not declare the detailed contents of e-liquids on their labels. To help evaluate the health impact of flavouring substances, there is...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Results of EIS measuremnts and DRT analysis of SrTi0.30Fe0.70O3-d oxygen electrode at 800 °C and 1% oxygen partial pressure by using three R-CPE fiting elements
Open Research DataThis dataset contains electrochemical impedance spectroscopy and Distribution of Relaxation Times analysis results for symmetrical cell with porous SrTi0.30Fe0.70O3-d oxygen electrodes sintered at 800 °C. EIS spectra were measured at 800 °C and 1% of oxygen partial pressure. EIS and DRT spectra of simmulated three R-CPE elements from equivalent circuit,...
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Results of EIS measuremnts and DRT analysis of SrTi0.30Fe0.70O3-d oxygen electrode at 800 °C and 1% oxygen partial pressure by using two R-CPE fiting elements
Open Research DataThis dataset contains electrochemical impedance spectroscopy and Distribution of Relaxation Times analysis results for symmetrical cell with porous SrTi0.30Fe0.70O3-d oxygen electrodes sintered at 800 °C. EIS spectra were measured at 800 °C and 1% of oxygen partial pressure. EIS and DRT spectra of simmulated two R-CPE elements from equivalent circuit,...
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublicationThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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E-cohomological Conley index
PublicationIn this thesis we continue with developing the E-cohomological Conley index which was introduced by A.Abbondandolo. In particular, we generalize the index to non-gradient flows, we show that it an possesses additional multiplicative structure and we prove the continuation principle. Then, using continuation principle, we show how the computation of the E-cohomological Conley index can be reduced to the computation of the classical...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublicationTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Trust and Distrust in e-Democracy
PublicationIn the digital government research literature, the concept of trust is typically used as a precondition for the adoption of digital technology in the public sector or an outcome of a roadmap leading up to such adoption. The concept plays a central role in many decisions linked to the planning, adoption and management of the public sector technology. In contrast, the concept of distrust is almost neglected in such literature but,...
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The operation mode of E/E/PE system and its influence on determining and verifying the safety integrity level = Rodzaj pracy systemu E/E/PE i jego wpływ na określanie i weryfikację poziomu nienaruszalności bezpieczeństwa
PublicationNorma PN-EN 61508 wprowadza kryteria probabilistyczne dla wyróżnionych rodzajów pracy systemów E/E/PE, które związane są z poziomami nienaruszalności bezpieczeństwa SIL. Dla systemów sterowania i zabezpieczeń, pracujących w trybie rzadkiego przywołania do działania, kryterium tym jest przeciętne prawdopodobieństwo niewypełnienia funkcji bezpieczeństwa na żądanie PFDavg. W przypadku systemów realizujących funkcje bezpieczeństwa...
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Trust and Distrust in e-Democracy
PublicationIn the digital government research literature, the concept of trust is typically used as a precondition for the adoption of digital technology in the public sector or an outcome of a roadmap leading up to such adoption. The concept plays a central role in many decisions linked to the planning, adoption and management of the public sector technology. In contrast, the concept of...
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Decisions Analysis STAC 22/23
e-Learning CoursesThis is content to the subject: "Decisions Analysis" 22/23
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Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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International Journal of Data Analysis Techniques and Strategies
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Sampling Theory, Signal Processing, and Data Analysis
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Data Mining 2022/2023
e-Learning CoursesThis is a web page for our course in Data Mining.
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Data Mining 2021/2022
e-Learning CoursesThis is a web page for our course in Data Mining.
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DRUGS IN R&D
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HVAC&R RESEARCH
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R&D MAGAZINE
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R & D MANAGEMENT
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Analysis of effect of overloaded vehicles on fatigue life of flexible pavements based on weigh in motion (WIM) data
PublicationOverloaded vehicles have a significant impact on pavement fatigue life and distress. As the studies show, the phenomena intensify when the control of traffic is poor. The paper presents the results of the research including analysis of weigh in motion data from eight stations and analysis of asphalt pavement fatigue caused by mixed traffic. Distributions of vehicles axles load including the multiple axles effects are presented....
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E-textbook technologies for academics in medical education
PublicationPublic universities in Poland receive fairly limited financial support for creating e-textbooks and lack the appropriate ICT competences among teaching staff, especially in the case of non-technical universities. The authors propose a pedagogical and technological paradigm for e-textbooks in medical education using open source software with minimal IT skills required. Technologies used to develop e-textbooks are connected with:...
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Classification and fingerprinting of kiwi and pomelo fruits by multivariate analysis of chromatographic and spectroscopic data
PublicationThe fingerprinting capacity of two analytical techniques, HPLC and UV-Vis spectroscopy in the case of fruits samples (kiwi and pomelo) has been investigated. The multivariate exploratory techniques were used for sample discrimination according to the fruit species and subspecies. The combination of principal component analysis with linear discriminant analysis is opening new directions in the fingerprinting analysis. The classifications...
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Emergent Versus Deliberate Knowledge Management Strategy: Literature Review and Case Study Analysis
PublicationThis paper discusses emergent and deliberate knowledge management (KM) strategies on the basis of literature review and case study analysis. It grounds on the results of a comprehensive analysis of the literature on KM strategies and approaches adopted by companies of various sizes. Although KM strategies have been abundantly examined by scholars, not many studies compare deliberate and emergent approaches. By examining the case...
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Enhancing environmental literacy through urban technology- based learning. The PULA app casebased learning. The PULA app case
PublicationThis study addresses the need to enhance environmental literacy, focusing on urban adults through mobile applications, based on the example of PULA app that engages early adopters in gamified pro- environmental activities, offering insights into informal learning. Grounded in 'urban pedagogy,' the study combines semi-structured interviews with 17 application testers and quantitative data analysis, unveiling motivations, user feedback,...
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How Machine Learning Contributes to Solve Acoustical Problems
PublicationMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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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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Discriminating macromolecular interactions based on an impedimetric fingerprint supported by multivariate data analysis for rapid and label-free Escherichia coli recognition in human urine
PublicationThis manuscript presents a novel approach to address the challenges of electrode fouling and highly complex electrode nanoarchitecture, which are primary concerns for biosensors operating in real environments. The proposed approach utilizes multiparametric impedance discriminant analysis (MIDA) to obtain a fingerprint of the macromolecular interactions on flat glassy carbon surfaces, achieved through self-organized, drop-cast,...
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Supporting First Year Students Through Blended-Learning - Planning Effective Courses and Learner Support
PublicationHigher education has been actively encouraged to find more effective and flaxible delivery models to provide all students with access to good quality learning experiences. This paper describes students opinion about using e-learning techniques and their participation in courses provided in different ways as additional help and expectations of first year students.
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Kolbudy 2021 E - video data - pedestrian, bicycles, vehicles
Open Research DataKolbudy 2021 E - video data - pedestrian, bicycles, vehicles
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Uwarunkowania rozwoju e-administracji w Polsce
PublicationCelem opracowania są w szczególności: - Ocena poziomu rozwoju e-administracji w Polsce oraz innych, w szczególności europejskich, krajach w okresie transformacji. - Identyfikacja i ocena wpływu czynników determinujących poziom rozwoju e-administracji. - Wskazanie korzyści wynikających ze stosowania rozwiązań e-administracji oraz barier w ich wdrażaniu. - Identyfikacja problemów i niespójności w planowaniu i realizacji e-usług publicznych. -...
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Neural networks and deep learning
PublicationIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
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Comprehensive Comparison of a Few Variants of Cluster Analysis as Data Mining Tool in Supporting Environmental Management
PublicationA few variants of hierarchical cluster analysis (CA) as tool of assessment of multidimensional similarity in environmental dataset are compared. The dataset consisted of analytical results of determination of metals (Na, K, Ca, Sc, Fe, Co, Zn, As, Br, Rb, Mo, Sb, Cs, Ba, La, Ce, Sm, Hf and Th) in ambient air dried and kept alive, by the means of hydroponics, moss baskets collected in 12 locations on the area of Tricity (Poland)....
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Architektoniczne aspekty e-Uczelni
PublicationProces informatyzacji uczelni polega na tworzeniu wirtualnych węzłów funkcjonalnych usprawniających organizację kampusu i dostęp do informacji. Węzły te budowane są w oparciu o specjalne urządzenia elektroniczne oraz odpowiednie oprogramowanie prowadząc tym samym do rozwoju e-uczelni. Z architektonicznego punktu widzenia nie jest to jednak podejście kompleksowe. Istotne jest całościowe potraktowanie struktury kampusu jako ośrodka...
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Data Structures (Doctoral Studies)
e-Learning CoursesThe course covers basic data structures and computer algorithms used in information tehcnology applications.
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Price bubbles in commodity market – A single time series and panel data analysis
PublicationThis paper examines thirty-five commodities, grouped into three market sectors (energy, metals, agriculture & livestock) in terms of the occurrence of price bubbles. The study was based on monthly data for each commodity separately and, in a panel approach, for selected sectors and for all commodities combined. The GSADF test and its version for panel data – panel GSADF – were used to identify bubbles. The beginning and end of...
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Deep learning for ultra-fast and high precision screening of energy materials
PublicationSemiconductor 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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DATA INTEROPERABILITY AND THE OPEN DATA ECOSYSTEM: ROLES AND RESEARCH AREAS
PublicationSustainability and value-creation are considered important parameters to measure the success of an open data system. Unfortunately, existing open data systems are not meeting their promises to achieve a sustainable and value-based open data system. Van Loenen et al. (2021) proposed a sustainable and value-creating open data ecosystem. According to their study, the open data ecosystem needs to be user-driven, inclusive, circular,...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...