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Search results for: object detection, remote sensing images, optical images, machine learning, neural network, cnn, deep learning
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MACHINE VISION DETECTION OF THE CIRCULAR SAW VIBRATIONS
PublicationDynamical properties of rotating circular saw blades are crucial for both production quality and personnel safety. This paper presents a novel method for monitoring circular saw vibrations and deviations. A machine vision system uses a camera and a laser line projected on the saw’s surface to estimate vibration range. Changes of the dynamic behaviour of the saw were measured as a function of the rotational speed. The critical rotational...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Colour Terms in Five Linguistic Images of the World: The Semantic Perspective
PublicationSocial and cultural factors shape the linguistic perception of colour. At the same time, colour terms co-create the linguistic image of the world, which allows us to interpret reality and profile our statements and beliefs. This paper presents six basic colour terms: white, black, red, green, yellow, and blue (both as adjectives and as nouns) in the five different linguistic images of the world of the following languages: English,...
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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An application of blended and collaborative learning in spatial planning course
PublicationSpatial Planning is a master course for graduate students of Environmental Engineering. The course is based on assumptions that students’ future work will be connected with spatial planning, and spatial issues will have an influence on their everyday lives. To familiarize students with environmental issues in planning, the teams of students get an assignment to design an urban space, waterfront along a stream. The whole project...
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Network on Chip implementation using FPGAs resources
PublicationW artykule przedstawiono implementację sieci typu ''Network on Chip'' w układach FPGA. Sieci typu ''Network on Chip'' stały się bardzo interesującym i obiecującym rozwiązaniem dla systemów typu ''System on Chip'' które charakteryzują się intensywną komunikacją wewnętrzną. Ze względu na inne paradygmaty projektowania nie ma obecnie dostępnych efektywnych platform do budowy prototypów sieci typu ''Network on Chip'' i ich weryfikacji....
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Employing Blended E-Learning to Improve Rate of Assignments Handing-In
PublicationIt has been observed that students hand in homework assignments at a notably low rate in introductory C programming course. A survey has revealed that the real issue was not student learning but instructor work organization. Based on survey results, the physical course has been complemented with an e-learning component to guide the homework process. Assignment handing-in rate significantly improved, as e-learning allowed the homework...
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Enterprise Gamification - Learning as a Side Effect of Competition
PublicationGmification in companies can be used for driving desired employees behaviour that are advantageous to their development and performance improvement. This paper presents tools acquired from online social networking services and game mechanisms to encourage managers to compete by providing extended statistics and user profiles features in e-learning system.
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Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Use of radiography images and gray level co-occurrence matrix to investigate gravitational granular flow
PublicationThe paper presents analysis of granular gravitational flow based on radiography images processing. The investigations were conducted for silo model geometry with concentric/eccentric discharging modes. The continuous X-ray radiography scans of granular material distribution, acquired during flow, were obtained by means of an especially designed model silo with rectangular bin and different settings of hopper angles. Image processing...
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The Optical Coherence Tomography and Raman Spectroscopy for Sensing of the Bone Demineralization Process
PublicationThe presented research was intended to seek new optical methods to investigate the demineralization process of bones. Optical examination of the bone condition could facilitate clinical trials and improve the safety of patients. The authors used a set of complementary methods: polarization-sensitive optical coherence tomography (PS-OCT) and Raman spectroscopy. Chicken bone samples were used in this research. To stimulate in laboratory...
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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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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Remote sensing in laboratory diagnostics of reinforced concrete elements – current development and vision for the future
PublicationContinuous emergence of new concrete types and kinds of reinforcement, as well as technological solutions in the field of structural engineering have made great demand for diagnostic tests of reinforced concrete elements. New challenges and problems facing people require new more efficient tools for laboratory diagnostics than those commonly used. Remote sensing may be the answer to this demand. In this paper the author describes...
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Remote sensing in laboratory diagnostics of reinforced concrete elements – current development and vision for the future
PublicationContinuous emergence of new concrete types and kinds of reinforcement, as well as technological solutions in the field of structural engineering have made great demand for diagnostic tests of reinforced concrete elements. New challenges and problems facing people require new more efficient tools for laboratory diagnostics than those commonly used. Remote sensing may be the answer to this demand. In this paper the author describes...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe 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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Temporal Satellite Images in The Process of Automatic Efficient Detection of Changes of the Baltic Sea Coastal Zone
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Selected acoustic images of the Gdansk Bay
PublicationThe main goal of the paper is to describe the results of sounding the Gdansk Bay seabed by using a parametric sub-bottom profiler, multibeam echosounder and side scan sonar. Quality of dsata obtained during trials depends interalia on a proper location of antenna to reduce influence of pitch, roll and heave motions as well as ship noise.
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Registration and normalization of MRI/PET images
PublicationW artykule przedstawiono technikę rejestracji i normalizacji obrazów MRI/PET. Zawiera on porównanie sztywnej i elastycznej transformacji gemotrycznej. Porownano w nim rowniez manualne i proponowane automatyczne podejscie do problemu rejestracji i normalizacji obrazow.
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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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Optical Detection of Ketoprofen by Its Electropolymerization on an Indium Tin Oxide-Coated Optical Fiber Probe
PublicationIn this work an application of optical fiber sensors for real-time optical monitoring of electrochemical deposition of ketoprofen during its anodic oxidation is discussed. The sensors were fabricated by reactive magnetron sputtering of indium tin oxide (ITO) on a 2.5 cm-long core of polymer-clad silica fibers. ITO tuned in optical properties and thickness allows for achieving a lossy-mode resonance (LMR) phenomenon and it can be...
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COLLABORATIVE LEARNING ENVIRONMENT FOR ENGINEERING EDUCATION (COLED)
PublicationCollaborative Learning Environment for Engineering Education is a European project implemented under the Erasmus + program, The main goal of 5 partners from 4 different European countries – Bulgaria, Poland, Portugal and Romania is to develop an innovative collaborative training approach, encompassing curricula related to the introduction of enterprise automation. Project activities are carried out in the period from Dctober 2018...
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Controlling computer by lip gestures employing neural network
PublicationResults of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....
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Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
PublicationThe paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...
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Assessment of student language skills in an e-learning environment
PublicationThis article presents the role of various assessment structures that can be used in a VLE. e-Learning language courses offer tutors a wide range of traditional and computer-generated formative and summative assessment procedures and tools. They help to evaluate each student’s progress, monitor their activities and provide varied support, which comes from the tutor, the course structure and materials as well as other participants....
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Learning from Mistakes. A Study on Maturity and Adaptability to Change
PublicationLearning culture matters; company culture must support continuous improvement. Organizational learning is a process of identifying and modifying mistakes that result from interactions between co-workers. The article aims to explore the learning power via errors, using the level of organizational maturity as a moderator. Companies need to know how organizational maturity may moderate the adaptability to change via the acceptance...
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers
PublicationThe process of organizational learning and proper knowledge management became today one of the major challenges for the organization acting in the knowledge-based economy. According to the observations of the authors of this paper the demand for formalization of knowledge management processes and organizational learning is particularly evident in research institutions, established either by the universities, or the companies. The...
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Fluctuation-Enhanced Sensing for Biological Agent Detection and Identification
PublicationPrzedstawiono wcześniejsze wyniki badań dotyczące trzech różnych sposobów wykrywania obecności substancji biologicznych za pomocą zjawisk fluktuacyjnych: 1) wirusów wnikających do komórek, 2) zapachów emitowanych przez mikroby, 3) rozkładu widma i wartości chwilowych szumów podczas rozpraszania światła używanego do wykrywania zarodników na podstawie wyznaczenia współczynnika dyfuzji opisująceo ich ruch.We survey and show our earlier...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Machine Learning and data mining tools applied for databases of low number of records
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublicationA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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The Cultures of Knowledge Organizations: Knowledge, Learning, Collaboration (KLC)
PublicationThis book focuses on seeing, understanding, and learning to shape an organization’s essential cultures. The book is grounded on a fundamental assumption that every organization has a de facto culture. These “de facto cultures” appear at first glance to be serendipitous, vague, invisible, and unmanaged. An invisible and unrecognized de facto culture can undermine business goals and strategies and lead to business failures. The authors...
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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis chapter investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organisational culture results in better mistake management and thus better organisational learning, (2) Effective organisational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning...
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An object-based SAR image iceberg detection algorithm applied to the Amundsen Sea
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3D polypyrrole structures as a sensing material for glucose detection
PublicationIn this work, 3D polypyrrole (PPy) structures as material for glucose detection is proposed. Polypyrrole was electrochemically polymerized on platinum screen-printed electrode from an aqueous solution of lithium perchlorate and pyrrole. The growth mechanism of such PPy structures was studied by ex-situ scanning electron microscopy. Preliminary studies show that studied here PPy film is a good candidate as a sensing material for...
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublicationAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublicationThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....