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Wyniki wyszukiwania dla: e-learning
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Encouraging Pro-environmental Behaviour Through an Educational Mobile Application: Preliminary Insights from Early Adopters
PublikacjaThis article aims to explore the extent to which the educational mobile application PULA supports and promotes pro-environmental behaviours, identify the most utilised functionalities by early adopters, and explore the least engaged functionalities. The study employs a quantitative approach based on data collected from the application. The analysis provides a comprehensive understanding of users' experiences and behaviours within...
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Deep learning-based waste detection in natural and urban environments
PublikacjaWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Dysfunctional prefrontal cortical network activity and interactions following cannabinoid receptor activation.
PublikacjaCoordinated activity spanning anatomically distributed neuronal networks underpins cognition and mediates limbic-cortical interactions during learning, memory, and decision-making. We used CP55940, a potent agonist of brain cannabinoid receptors known to disrupt coordinated activity in hippocampus, to investigate the roles of network oscillations during hippocampal and medial prefrontal cortical (mPFC) interactions in rats. During...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis 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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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublikacjaThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublikacjaDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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The evaluation of eGlasses eye tracking module as an extension for Scratch
PublikacjaIn this paper we present the possibility of using eGlasses eye tracking module as an extension for Scratch programming tool which is a visual programming language supporting computer skills learning. The main concept behind this project is to setup the interface for rapid interaction design. Eye tracking is a powerful tool for hands free communication but for that requires a dedicated software. This software is rarely tailored...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Encouraging pro-environmental behaviour through an educational mobile application: Preliminary insights from early adopters
PublikacjaThis article aims to explore the extent to which the educational mobile application PULA supports and promotes pro-environmental behaviours, identify the most utilised functionalities by early adopters, and explore the least engaged functionalities. The study employs a quantitative approach based on data collected from the application. The analysis provides a comprehensive understanding of users' experiences and behaviours within...
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Comparative study on the effectiveness of various types of road traffic intensity detectors
PublikacjaVehicle detection and speed measurements are crucial tasks in traffic monitoring systems. In this work, we focus on several types of electronic sensors, operating on different physical principles in order to compare their effectiveness in real traffic conditions. Commercial solutions are based on road tubes, microwave sensors, LiDARs, and video cameras. Distributed traffic monitoring systems require a high number of monitoring...
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Adaptive Positioning Systems Based on Multiple Wireless Interfaces for Industrial IoT in Harsh Manufacturing Environments
PublikacjaAs the industrial sector is becoming ever more flexible in order to improve productivity, legacy interfaces for industrial applications must evolve to enhance efficiency and must adapt to achieve higher elasticity and reliability in harsh manufacturing environments. The localization of machines, sensors and workers inside the industrial premises is one of such interfaces used by many applications. Current localization-based systems...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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CERTIFICATION SYSTEM AS A TOOL FOR IMPROVING THE SAFETY AND SUSTAINABILITY OF SCHOOL-RELATED TRAVELS
PublikacjaDespite the well-established physical, social, emotional, cognitive, and spatial benefits of active and autonomous school commuting of children and adolescents', many are driven by car. Pilot surveys and field research held in 2019 in 10 Gdansk primary schools confirmed this trend. The article presents a certification system for schools, commissioned by the City of Gdańsk, which is an element of a systemic solution shaping patterns...
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Resource productivity and environmental degradation in EU-27 countries: context of material footprint
PublikacjaThis study explores the relationship between the resource productivity and environmental degradation in European Union-27 countries. This study tests this relationship in context of high, moderate, and low material footprint sub-samples; these samples are formed utilizing the expectation–maximization machine learning algorithm. Using the panel data set of EU-27 countries from 2000 to 2020, linear and non-linear autoregressive distributed...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Kriging-assisted hybrid reliability design and optimization of offshore wind turbine support structure based on a portfolio allocation strategy
PublikacjaIn recent years, offshore wind power generation technology has developed rapidly around the world, making important contributions to the further development of renewable energy. When designing an Offshore Wind Turbine (OWT) system, the uncertainties in parameters and different types of constraints need to be considered to find the optimal design of these systems. Therefore, the Reliability-Based Design Optimization (RBDO) method...
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Activation of Metabotropic Glutamate Receptor (mGlu2) and Muscarinic Receptors (M1, M4, and M5), Alone or in Combination, and Its Impact on the Acquisition and Retention of Learning in the Morris Water Maze, NMDA Expression and cGMP Synthesis
PublikacjaThe Morris water maze (MWM) is regarded as one of the most popular tests for detecting spatial memory in rodents. Long-term potentiation and cGMP synthesis seem to be among the crucial factors involved in this type of learning. Muscarinic (M1, M4, and M5 receptors) and metabotropic glutamate (mGlu) receptors are important targets in the search for antipsychotic drugs with the potency to treat cognitive disabilities associated with...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublikacjaFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublikacjaPartial 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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Do clusters help companies to "go green"? Experience of Polish National Key Clusters
PublikacjaThis study aims to explore cluster activity in the field of green transformation, taking into account the green, low-carbon and circular economy. Our intention was to identify the main green practices used by cluster organizations, which we showed through the lens of the attributes of both the cluster and the cluster organization. Through our study, we sought to answer the question: what is the role of cluster organizations in...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Briding the communicational gap between client and software developer
PublikacjaOften is it the case that people find it difficult to bridge thecommunicational gap between themselves and others. This is something of a problem, to say the least. My aim is to explain and to clarify the reasons behind this and to hopefully overcome any obstacles, to allow for a much smoother and more accurate means of fulfilling client and software developer needs.I have found through my own personal experience something which...
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Interactive Prototypes in Teaching User-Centred Design and Business Process Modelling
PublikacjaThis publication describes experiences gathered during the use of interactive prototyping in two areas: design of user interfaces for a touch screen information kiosk and interactive prototyping of business processes. Prototyping is promoted here as a technique useful for both visualizing design concepts and for stimulating communication within relevant teams. Developing interactive prototypes of use interfaces is discussed here...
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Cooperative control in production and logistics
PublikacjaClassical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety...
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Self-assessment of competencies of students and graduates participating in didactic projects – Case study
PublikacjaAim/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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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublikacjaThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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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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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublikacjaThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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ARIMA vs LSTM on NASDAQ stock exchange data
PublikacjaThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
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Vision Zero in Poland
PublikacjaPoland’s experience of road safety work is relatively short. In the early 1990s road deaths soared to a staggering 8000 a year. A diagnosis found that Poland’s lack of systemic road safety action was to blame for those figures. In response, the state set up road safety bodies and commissioned road safety programs. In 2005, Poland followed the example of Sweden and adopted Vision Zero as a far-reaching concept of changes in road...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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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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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublikacjaDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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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
PublikacjaIntroduction: 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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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublikacjaIn 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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Impact of AlphaFold on structure prediction of protein complexes: The CASP15‐CAPRI experiment
PublikacjaWe present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody–antigen complexes, and 7 large assemblies. On average 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Towards Scalable Simulation of Federated Learning
PublikacjaFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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How to teach architecture? – Remarks on the edge of Polish transformation processes after 1989
PublikacjaThe political changes in Poland after 1989 have resulted in a whole range of dynamic processes including the transformation of space. Until that time the established institutional framework for spatial, urban and architectural planning policy was based on uniform provisions of the so-called planned economy. The same applied to the training of architects, which was based on a unified profile of education provided at the state’s...
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Exploring the preferences of Polish EFL teachers towards the accents of English
PublikacjaThis language attitudes study investigates the preferences of EFL (English as a foreign language) teachers from Poland towards the accents of English they speak and teach. Despite the substantial amount of research on EFL learners, little has been done to investigate the impact of preferences of Polish teachers for different variations of English language on their...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Introducing concurrent engineering to space and satellite technology undergraduate course
PublikacjaIn 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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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublikacjaConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....