Search results for: LEARNING-BY-DOING METHOD
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublicationTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
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The Efficiency of Public and Private Higher Education Institutions in Poland
PublicationChanges introduced to Poland’s education system in 2011 and 2014 amid efforts to adjust it to the needs of the labour market had an effect on the country’s institutions of higher learning. This paper provides an analysis of the efficiency of public and private Polish universities and examines the impact of selected factors in the years that followed. To estimate this efficiency, a Banker, Charnes and Cooper (BCC) model of the...
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Two-Step Model Based Adaptive Controller for Dissolved Oxygen Control in Sequencing Wastewater Batch Reactor
PublicationDissolved Oxygen (DO) concentration is a crucial parameter for efficient operation of biological processes taking place in the activated sludge Wastewater Treatment Plant (WWTP). High-quality DO control is difficult to achieve because of complex nonlinear behavior of the plant and substantial influent disturbances. A method to improve the Direct Model Reference Adaptive Control (DMRAC) technology in application to DO tracking for...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures
PublicationAbstract Background In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments...
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Instrument detection and pose estimation with rigid part mixtures model in video-assisted surgeries
PublicationLocalizing instrument parts in video-assisted surgeries is an attractive and open computer vision problem. A working algorithm would immediately find applications in computer-aided interventions in the operating theater. Knowing the location of tool parts could help virtually augment visual faculty of surgeons, assess skills of novice surgeons, and increase autonomy of surgical robots. A surgical tool varies in appearance due to...
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublicationThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
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Train the trainer course
PublicationThis chapter presents the concept, evaluation and evaluation results for the train the trainer. This concept of train the trainers is prepared within Workpackage 5 of EU-funded project: MASTER BSR (Erasmus+ Strategic Partnership Programme). Due to the nature of adult learning the content is designed for the use of participatory methods (involved, active). This method uses various techniques of active learning e.g. group work,...
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Tacit Knowledge Sharing and Project Performance. Does the Knowledge Workers' Personal Branding Matter?
PublicationTacit knowledge sharing is the real challenge for knowledge management today. Network economy has completely changed the role of knowledge workers who now become independent tacit knowledge producers. Bearing this fact in mind, the author studied how tacit knowledge sharing affects the process of building a personal brand and project performance. For this purpose, the authors conducted a study among Polish professionals with different...
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublicationShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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A New Critical Risk on the Block: Cyber Risks as an Example of Technical Knowledge Risks in Organizations
PublicationThe breakout of the COVID-19 pandemic has intensified the appearance of many additional technical knowledge risks in organizations. Cyber risks in particular are becoming a great challenge for organizations. At the same time, academic research on cyber risks, their costs, consequences and ability of overcoming them is still scarce and fragmented. In order to fill this gap, the paper is aimed to identify different types of cyber...
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The Business Environment of Georgia and Ukraine: Approaches to a Comparative Analysis
PublicationThe formation of a favourable business environment and the intensification of entrepreneurial activity on this basis is one of the priorities of economic policy of governments around the world. The aim of this article is to conduct a comparative analysis of some of the characteristics of the business environment of Georgia and Ukraine. The theoretical basis of the study is the understanding of the business environment as a necessary...
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Online sound restoration system for digital library applications
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit
PublicationThe general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublicationHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
PublicationThis study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company’s financial security using only economic indicators—as suggested in the existing literature—would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublicationTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Evaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modeling and Fuzzy Analytic Hierarchy Process
PublicationThe fourth industrial revolution known as Industry 4.0 is reshaping and evolving the way industries produce products and individuals live and work therefore, gaining massive attraction from academia, business and politics. The manufacturing industries are optimistic regarding the opportunities Industry 4.0 may offer such as, improved efficiency, productivity and customization. The present research contributes to the Industry 4.0...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublicationThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublicationThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Effective Collaboration of Entrepreneurial Teams—Implications for Entrepreneurial Education
PublicationIn the situation of a permanent change and increased competition, business ventures are more and more often undertaken not by individuals but by entrepreneurial teams. The main aim of this paper is to examine the team principles implemented by eective entrepreneurial teams and how they dier in nascent and established teams. We also focused on the relationship between the implementation of these rules by entrepreneurial team members...
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Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublicationMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublicationThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublicationHoneybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublicationPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Classification of Polish wines by application of ultra-fast gas chromatography
PublicationThe potential of ultra-fast gas chromatography (GC) combined with chemometric analysis for classification of wine originating from Poland according to the variety of grape used for production was investigated. A total of 44 Polish wine samples differing in the type of grape (and grape growth region) used for the production as well as parameters of the fermentation process, alcohol content, sweetness, and others which characterize...
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Introducing concurrent engineering to space and satellite technology undergraduate course
PublicationIn recent decade concurrent engineering has become a de facto leading methodology of work in space, aeronautics and sometimes even automotive industry. It has been used in designing ESA space missions for 20 years now, with rst Concurrent Design Facility (CDF) built in ESTEC in 1998. Still, it has not become a universal standard in engineering, and universities are specically reluctant to adopt it into their curricula. As a result,...
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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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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublicationIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Self-assessment of competencies of students and graduates participating in didactic projects – Case study
PublicationAim/purpose: the aim of this article is to examine the opinions of students and graduates of the faculty of economics of a technical university as regards their selfassessment of their preparation for entering the modern labour market. All the respondents participated during their studies in didactic projects aimed at improving their competencies taking into account the expectations of potential employers. Design/methodology/approach:...
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COVID-19 and digital deprivation in Poland
PublicationResearch background: The problem of digital deprivation is already known, but the COVID-19 pandemic has highlighted its negative consequences. A global change in the way of life, work and socialisation resulting from the epidemic has indicated that a basic level of digital integration is becoming necessary. During the lockdown, people were forced to use ICTs to adapt to a rapidly changing reality. Current experience with coronavirus...
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Herbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE)
Open Research DataHerbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE) is a research herbarium encompassing specimens of vascular plants and algae hosted by the Laboratory of Marine Plant Ecology at University of Gdańsk, Poland. The aim of Herbarium is to preserve marine plant and algae collections mostly from the Gulf of Gdańsk, but the herbarium...
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Proceedings of the fib Symposium 2019: Concrete - Innovations in Materials, Design and Structures 2019
PublicationDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublicationOpen Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...
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TF-IDF weighted bag-of-words preprocessed text documents from Simple English Wikipedia
Open Research DataThe SimpleWiki2K-scores dataset contains TF-IDF weighted bag-of-words preprocessed text documents (raw strings are not available) [feature matrix] and their multi-label assignments [label-matrix]. Label scores for each document are also provided for an enhanced multi-label KNN [1] and LEML [2] classifiers. The aim of the dataset is to establish a benchmark...
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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublicationGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...
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Predicting sulfanilamide solubility in the binary mixtures using a reference solvent approach
PublicationBackground. Solubility is a fundamental physicochemical property of active pharmaceutical ingredients. The optimization of a dissolution medium aims not only to increase solubility and other aspects are to be included such as environmental impact, toxicity degree, availability, and costs. Obtaining comprehensive...
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Developing competences for cooperation in international teams - tools and methods
PublicationThe article presents the training methods that can be used to develop intercultural competences which are extremely important while working in intercultural teams. The mentioned methods like: case-studies, collaborating, role-play simulations, team working, video presentations and others are presented on the basis of authors’ experiences while teaching the international groups of students at Faculty of Management and Economics...
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Marek Czachor prof. dr hab.
People -
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...