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Search results for: BLENDED E-LEARNING
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublicationAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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E-technologie w edukacji i terapii dzieci z autyzmem w Polsce
PublicationArtykuł dotyczy możliwości wsparcia technologiami informacyjnymi edukacji i terapii dzieci z za - burzeniami rozwoju ze spektrum autyzmu. Szczególna uwaga zostanie poświęcona aplikacjom przeznaczonym na urządzenia mobilne (tablety). Artykuł podsumowuje przesłanki zastosowania tabletów w pracy z dziećmi auty - stycznymi oraz pokazuje kategorie aplikacji, jakie mogą wspierać terapię i edukację dzieci. Zostały przedstawione wyniki...
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Evaluation of flavour profiles in e-cigarette refill solutions using gas chromatography–tandem mass spectrometry
PublicationMany flavour compounds that are present in e-liquids for e-cigarettes are responsible for specific tastes and smoking sensations for users. Data concerning content and specific types of flavours is often limited and unknown to users. The aim of the research was to define and compare flavour profiles of e-liquids with the same group taste from different manufacturers. Gas chromatography coupled with tandem mass spectrometry (GC–MS/MS)...
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Computational Analysis of Transformational Organisational Change with Focus on Organisational Culture and Organisational Learning: An Adaptive Dynamical Systems Modeling Approach
PublicationTransformative Organisational Change becomes more and more significant both practically and academically, especially in the context of organisational culture and learning. However computational modeling and formalization of organisational change and learning processes are still largely unexplored. This chapter aims to provide an adaptive network model of transformative organisational change and translate a selection of organisational...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublicationBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis 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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Recent advancements in molecularly imprinted polymers for the removal of heavy metal ions and dyes
PublicationContamination set off by highly toxic metal ions and dyes is a big threat to the environment and living beings. Various industries like metal plating, mining, pesticides, battery manufacturing, and dyeing release metal ions and toxic dyes directly into the water. It is necessary to remove these toxic substances from the environment. Molecular imprinting technology (MIT) got a lot of attention in the last two decades because of...
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Rigorous numerics for critical orbits in the quadratic family
PublicationWe develop algorithms and techniques to compute rigorous bounds for finite pieces of orbits of the critical points, for intervals of parameter values, in the quadratic family of one-dimensional maps fa(x)=a−x2. We illustrate the effectiveness of our approach by constructing a dynamically defined partition P of the parameter interval Ω=[1.4,2] into almost 4 million subintervals, for each of which we compute to high precision the...
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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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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Incorporating Iris, Fingerprint and Face Biometric for Fraud Prevention in e-Passports Using Fuzzy Vault
PublicationA unified frame work which provides a higher security level to e-passports is proposed. This framework integrates face, iris and fingerprint images. It involves three layers of security: the first layer maps a biometric image to another biometric image which is called biostego image. Three mapping schemes are proposed: the first scheme maps single biometric image to single biostego image, the second scheme maps dual biometric images...
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New approach for e-cigarette aerosol collection by an original automatic aerosol generator utilizing melt-blown non-woven fabric
PublicationCurrently, there is lack of standardized conditions for the collection and analysis of e-cigarette (EC) aerosol. Considering the urgent need for the development of these guidelines, a procedure for EC aerosol analysis was developed. A novel automatic e-cigarette aerosol generator was designed. For the first time, melt-blown non-woven fabric was applied for the effective uptake of compounds released from vaporized e-liquid. The...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Broadband communication solutions for maritime ITSs: Wider and faster deployment of new e-navigation services
Publicationn its initial part, the paper presents an overview of popular technologies and systems currently developed or employed in maritime communication. These solutions are used to provide both ship-to-ship and ship-to-shore communication for the purpose of supporting specific services, often dedicated to maritime safety and e-navigation. Utility of such communication systems have been thoroughly verified over the years and their strengths...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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A consensus-based approach to the distributed learning
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Prototype selection algorithms for distributed learning
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An agent-based framework for distributed learning
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Note on universal algoritms for learning theory
PublicationW 2001 Cucker i Smale zaproponowali nowe podejście do teorii uczenia się w oparciu o problematykę teorii aproksymacji.W 2005 i 2007 Bivev, Cohen, Dahmen, DeVore i Temlyakov opublikowali dwie prace z teorii uczenia się. W omawianej publikacji uogólniliśmy ich rezultaty jednocześnie upraszczając dowody.
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Structure and Randomness in Planning and Reinforcement Learning
PublicationPlanning in large state spaces inevitably needs to balance the depth and breadth of the search. It has a crucial impact on the performance of a planner and most manage this interplay implicitly. We present a novel method \textit{Shoot Tree Search (STS)}, which makes it possible to control this trade-off more explicitly. Our algorithm can be understood as an interpolation between two celebrated search mechanisms: MCTS and random...
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Ewolucyjny rozwój uczelnianej infrastruktury komunikacyjno-informacyjnej na potrzeby e-uczelni
PublicationStosowane i proponowane rozwiązania w obszarze technologii informacyjnych stwarzają szerokie możliwości w rozwoju i wdrażaniu systemów komunikacyjno-informacyjnych wspomagających i usprawniających specyficzną działalności uczelni a szczególnie wspierających e-Uczelnię. Wymaga to jednak wprowadzenia zmian w infrastrukturze technicznej i organizacji pracy. W artykule rozpa-trzono możliwości wykorzystania uczelnianych infrastruktur...
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Phage therapy as a novel strategy in the treatment of urinary tract infections caused by E. coli
PublicationUrinary tract infections (UTIs) are regarded as one of the most common bacterial infections affecting millions of people, in all age groups, annually in the world. The major causative agent of complicated and uncomplicated UTIs are uropathogenic E. coli strains (UPECs). Huge problems with infections of this type are their chronicity and periodic recurrences. Other disadvantages that are associated with UTIs are accompanying complications...
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Przyjazne aplikacje dla dzieci z autyzmem – e-edukacja na poziomie przedszkolnym
PublicationArtykuł dotyczy możliwości wykorzystania aplikacji na tablety do wspomagania terapii dzieci z zaburzeniami rozwojowymi ze spektrum autyzmu. Przedstawia studium przypadku skutecznego zastosowania e-technologii w kształceniu specjalnym na poziomie przedszkolnym. Artykuł opisuje zestaw aplikacji edukacyjnych o nazwie Przyjazne Aplikacje, których celem jest wspieranie terapii dzieci z autyzmem opartej o stosowaną...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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The supramolecular organization of self-assembling chlorosomal bacteriochlorophyll c, d, or e mimics
PublicationBacteriochlorophylls (BChls) c, d, and e are the main light-harvesting pigments of green photosynthetic bacteria that self-assemble into nanostructures within the chlorosomes forming the most efficient antennas of photosynthetic organisms. All previous models of the chlorosomal antennae, which are quite controversially discussed because no single crystals could be grown so far from these organelles, involve a strong hydrogen-bonding...
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e-JABAT – An Implementation of the Web-Based A-Team
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A longitudinal study of e-commerce diversity in Europe
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Arte e Género / Sztuka i płeć
PublicationKatalog wystawy towarzyszącej Konferencji na temat równości płci. Malarstwo i rysunek inspirowane tematyką konferencji przentowali artyści z Portugalii, Hiszpanii i z Polski. Jacek Krenz przedstawił cykl 7 akwarel pt. ''ENCOUNTER, Painting Haiku''.
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Factors affecting credibility of e-shops in Poland
PublicationArtykuł stanowi kontynuację tematu podjętego w poprzednich pracach autora nt. czynników wpływających na wiarygodność detalicznych sklepów internetowych. Przedstawiono w nim wstępne wyniki badań dokonanych przez autora. W artykule wskazano również na związki pomiędzy modelami wiarygodności i powszechnie stosowanymi modelami jakości.
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Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublicationW referacie zaprezentowano główne zadania oraz ofertę szkoleniową Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej (CEN PG) w kontekście realizowanych projektów Unii Europejskiej. Przedstawiono projekt Leonardo da Vinci EMDEL - European Model for Distance Education and learning - realizowany przez CEN PG w latach 2001-2005 oraz opisano doświadczenia w zakresie adaptacji i lokalizacji opracowanych przez partnerów projektu...
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An evaluation of sucrose as a possible contaminant in e-liquids for electronic cigarettes by hydrophilic interaction liquid chromatography–tandem mass spectrometry
PublicationThe influence of sucrose combustion products on smoking and nicotine addiction is still controversial because the presence of the sucrose may be treated as a source of aldehydes and organic acids. In e-liquids used as refills for electronic cigarettes, which are made primarily of poly(propylene glycol), glycerine and ethanol, sucrose may be present at trace levels, and its impact on mainstream smoke formation, and hence on human...
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CFD COUPLING OF VOF MODEL WITH ARRHENIUS EQUATION FOR ANALYSIS OF LASER-INDUCED THERMAL DEACTIVATION OF E. COLI
PublicationUnderstanding bacterial deactivation at the micro-scale, particularly with E. coli, is crucial for advancing microbiology and has promising applications in biomedical research. In this research contribution, we investigate the thermal inactivation of E. coli bacteria using gold nanoparticles irradiated by a green 1-W laser within a microfluidic chamber. The microfluidic device comprises a fluidic chamber filled with a thin film...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublicationThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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Chiral Pyrazolo[4,3-e][1,2,4]triazine Sulfonamides—Their Biological Activity, Lipophilicity, Protein Affinity, and Metabolic Transformations
PublicationReferring to our previous laboratory results related to the tyrosinase and urease inhibition by pyrazolo[4,3-e][1,2,4]triazine sulfonamides, we examined here in silico the mechanism of action at the molecular level of the investigated pyrazolotriazine sulfonamides by the molecular docking method. The studied compounds being evaluated for their cytotoxic effect against cancer cell lines (MCF-7, K-562) and for recombinant Abl and...
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Wiarygodność i zaufanie jako fundamenty budowania relacji w e-biznesie
PublicationInternet będący dla niektórych synonimem nowoczesności, dla innych jego użytkowników stał się codziennym narzędziem pracy, służącym do poszukiwania informacji o potencjalnych parterach biznesowych oraz komunikowania się z nimi. Z tego powodu odpowiedź na pytanie jak oceniana jest wiarygodność informacji internetowej, oraz jakim modyfikacjom podlega komunikacja zapośredniczona przez komputer (computer mediated communication) w porównaniu...
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Patomechanizm zakażeń dróg moczowych wywoływanych przez uropatogenne szczepy E. coli
PublicationZakażenia układu moczowego (ZUM) to jedne z najczęstszych i najbardziej powszechnych infekcji bakteryjnych, dotykających każdego roku nawet 150 milionów ludzi na świecie. Problem z tego typu infekcjami wynika z przewlekłości choroby, nawrotów i wzrastającej lekooporności powodujących je patogenów. Uropatogenne szczepy E. coli (UPEC) są głównym czynnikiem przyczynowym ZUM. Bakterie tej grupy zawierają wiele czynników adhezyjnych...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Type III Responses to Transient Inputs in Hybrid Nonlinear Neuron Models
PublicationExperimental characterization of neuronal dynamics involves recording both of spontaneous activity patterns and of responses to transient and sustained inputs. While much theoretical attention has been devoted to the spontaneous activity of neurons, less is known about the dynamic mechanisms shaping their responses to transient inputs, although these bear significant physiological relevance. Here, we study responses to transient...
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Adsorptive Capacity of Calcinated Hen Eggshell Blended with Silica Gel for Removal of Lead II Ions from Aqueous Media: Kinetics and Equilibrium Studies
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...