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Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublikacjaAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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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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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic 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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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublikacjaCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublikacjaOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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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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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis 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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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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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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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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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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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublikacjaEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublikacjaThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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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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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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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn 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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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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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublikacjaPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe 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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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis 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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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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The use of eLearning strategies among travel agents in the United Kingdom, India and New Zealand
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Travel agents and destination management organizations: eLearning as a strategy to train tourism trade partners.
PublikacjaThis article offers an overview of the existing online courses run by national destination management organizations (DMOs) in order to better equip travel agents and tour operators in the sales activities of the tourism destinations. These online courses represent one of the B2B offers by DMOs and an interesting opportunity for travel agents, who are trying to find their identity and competitive advantage within the context of...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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Phylogenetics and phylogeography of red deer mtDNA lineages during the last 50 000 years in Eurasia
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Experience-Oriented Knowledge Management for Internet of Things
PublikacjaIn this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional...
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Investigation of vortex assisted magnetic deep eutectic solvent based dispersive liquid–liquid microextraction for separation and determination of vanadium from water and food matrices: Multivariate analysis
PublikacjaA new and simple vortex assisted magnetic deep eutectic solvent dispersive liquid–liquid microextraction procedure (VA-MDES-DLLME) was developed for the determination of vanadium (V) in food and water samples by flame atomic absorption spectrometry (FAAS). In the extraction medium, a bis(acetylpivalylmethane) ethylenediimine (H2APM2en) was used for the complexation of V(V) in sample solution at pH 6. The VA-MDES-DLLME was optimized...
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Selectivity Tuning by Natural Deep Eutectic Solvents (NADESs) for Extraction of Bioactive Compounds from Cytinus hypocistis—Studies of Antioxidative, Enzyme-Inhibitive Properties and LC-MS Profiles
PublikacjaIn the present study, the extracts of Cytinus hypocistis (L.) L using both traditional solvents (hexane, ethyl acetate, dichloromethane, ethanol, ethanol/water, and water) and natural deep eutectic solvents (NADESs) were investigated in terms of their total polyphenolic contents and antioxidant and enzyme-inhibitive properties. The extracts were found to possess total phenolic and total flavonoid contents in the ranges of 26.47–186.13...
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An air-assisted dispersive liquid phase microextraction method based on a hydrophobic magnetic deep eutectic solvent for the extraction and preconcentration of melamine from milk and milk-based products
PublikacjaIn the current research, a fast and sustainable air-assisted hydrophobic magnetic deep eutectic solvent-based dispersive liquid phase microextraction followed by UV–Vis spectrophotometry measurements was optimized for the extraction and determination of melamine in milk and milk-based products. The central composite design was applied for the optimization of factors affecting the recovery of melamine. Quantitative extraction of...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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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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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublikacjaThis 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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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublikacjaNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Edu Inspiracje WZiE: Active Learning, czyli o mocy aktywnego przetwarzania informacji
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublikacjaPurpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...
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E-LEARNING NA POLITECHNICE GDAŃSKIEJ - HISTORIA ROZWOJU W LATACH 1995-2020
PublikacjaInternet oraz kształcenie oparte na wykorzystaniu e-technologii stały się nieodłącznym elementem edukacji. Artykuł przedstawia zarys historii rozwoju e-learningu na Politechnice Gdańskiej, przykładowe rozwiązania technologiczne, elementy tworzenia struktur organizacyjnych oraz związanych z legislacją, a także wybrane projekty wykorzystujące szeroko pojęte e-technologie w edukacji akademickiej realizowanej na Uczelni
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis 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...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublikacjaTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublikacjaIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...