displaying 1000 best results Help
Search results for: PREDICTIVE MACHINE LEARNING-BASED TOOLS
-
Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
Publication -
Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
Publication -
Innovative e-learning approach in teaching based on case studies - Innocase project
PublicationThe article presents the application of innovative e-learning approach for the creation of case study content. Case study methodology is becoming more and more widely applied in modern education, especially in business and management field. Although case study methodology is quite well recognized and used in education, there are still few examples of developing e-learning content on the basis of case studies. This task is to be...
-
Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
-
Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
-
Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
-
BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
-
Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
-
A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
Publication -
A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
-
The comparative study of micellar TLC and RP-TLC as potential tools for lipophilicity assessment based on QSRR approach
Publication -
Assessing therapeutic relevance of biologically interesting, ampholytic substances based on their physicochemical and spectral characteristics with chemometric tools
Publication -
International Journal of Practice-Based Learning in Health and Social Care
Journals -
Michał Grochowski dr hab. inż.
PeopleProfessor and a Head of the Department of Intelligent Control and Decision Support Systems at Gdansk University of Technology (GUT). He is also a Member of the Board of the Digital Technologies Center of GUT. He received his M.Sc. degree in Control Engineering in 2000 from the Electrical and Control Engineering Faculty at the GUT. In 2004 he received a Ph.D. degree in Automatic Control and Robotics from this...
-
Modelling of First- and Second-order Chemical Reactions on ARUZ – Massively-parallel FPGA-based Machine
Publication -
Adapting new tools of urban freight management based on Gdynia’s dedicated delivery bays example – an analysis of the process
PublicationThe article presents an analysis of a process which ultimately helped Gdynia to designate pilot delivery sites in its downtown area using international experience. A verification was conducted of policy transfer theory and its practical implementation based on an URBACT Freight Tails project. While the choice of the solution was based on critical analysis of existing practical examples, it needed to be adapted to the local conditions...
-
Ecology In Tribology: Selected Problems of Eliminating Natural Oil-Based Lubricants from Machine Friction Couples
PublicationThe elimination of mineral oil-based lubricants from machines has multiple beneficial effects on the natural environment. Firstly – these lubricants are a direct threat to the environment in the event of leaks; secondly – their elimination reduces the demand for crude oil from which they are obtained. In addition, in many cases, e.g. when replacing traditional lubricants with water, friction losses in the bearings can also be reduced...
-
SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
Publication -
Fractional-Order PID Controller (FOPID)-Based Iterative Learning Control for a Nonlinear Boiler System
Publication -
Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
Publication -
Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
-
JOURNAL OF MACHINE LEARNING RESEARCH
Journals -
State tax policy and reform tools as a risk of running a business. Case study based on Polski Ład – Polish tax reform
PublicationThe aim of the article is to describe and present the Polish tax reform introduced at the beginning of 2022. Tax changes introduced in Poland had a strong impact on the risk of running a business in Poland because in their assumption they directly changed the rules of running a business. Due to the pace of the introduced changes, as well as the scope of the reform, the new tax law was subject to numerous criticisms of taxpayers...
-
Molecular Simulations Using Boltzmann’s Thermally Activated Diffusion - Implementation on ARUZ – Massively-parallel FPGA-based Machine
Publication -
Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
-
Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublicationQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
-
Dawid Zieliński dr inż.
PeopleDawid Zieliński uzyskał tytuł magistra inżyniera w 2017 roku na Wydziale Mechanicznych Politechniki Gdańskiej, kończąc kierunek: Mechanika i Budowa Maszyn, specjalność: Technologia Maszyn i Komputerowe Wspomaganie Produkcji. W okresie 2016-17 studiował na Uniwersytecie Technicznym w Berlinie (Technische Universität Berlin – TU Berlin) oraz pracował w instytucie naukowym – Institut für Werkzeugmaschinen und Fabrikbetrieb (IWF) Technische...
-
Modeling of small molecule's affinity to phospholipids using IAM-HPLC and QSRR approach enhanced by similarity-based machine algorithms
Publication -
Finite State Machine Based Modelling of Discrete Control Algorithm in LAD Diagram Language With Use of New Generation Engineering Software
Publication -
Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning
Publication -
Asian Conference on Machine Learning
Conferences -
International Conference on Machine Learning
Conferences -
An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
-
Source code - AI models (MLM1-5 - series I-III - QNM opt)
Open Research DataSource code - AI models (MLM1-5 - series I-III - QNM opt) for the paper "Computational Complexity and Its Influence on Concrete Compressive Strength Prediction Capabilities of Machine Learning Models for Concrete Mix Design Support" accepted for publication.
-
Management and Economics 2022
e-Learning CoursesIntroduction to Management and Economics, Learning by Doing method based upon trends in geopolitics and modern economics frameworks, strategy and Business Models Management Tools SEMESTR II Green Technologies and Monitoring
-
International Conference on Machine Learning and Cybernetics
Conferences -
International Conference on Machine Learning and Applications
Conferences -
BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublicationThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
-
Tool wear, surface roughness, cutting temperature and chips morphology evaluation of Al/TiN coated carbide cutting tools in milling of Cu–B–CrC based ceramic matrix composites
Publication -
Optimal spindle speed determination for vibration reduction during ball-end milling of flexible details
PublicationIn the paper a method of optimal spindle speed determination for vibration reduction during ball-end milling of flexible details is proposed. In order to reduce vibration level, an original procedure of the spindle speed optimisation, based on the Liao–Young criterion, is suggested. As the result, an optimal, constant spindle speed value is determined. For this purpose, on-stationary computational model of machining process is...
-
Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
-
Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
Publication -
Patryk Ziółkowski dr inż.
PeoplePatryk Ziolkowski is a graduate of the Faculty of Civil and Environmental Engineering at the Gdansk University of Technology, specializing in Building and Engineering Structures. He works as an Assistant Professor at the Department of Engineering Structures. He participated in international projects, including projects for the Ministry of Transportation of the State of Alabama (2015), he is also the winner of a grant from the Kosciuszko...
-
Aleksandra Parteka dr hab. inż.
PeopleAbout me: I am an associate professor and head of doctoral studies at the Faculty of Management and Economics, Gdansk University of Technology (GdanskTech, Poland). I got my MSc degree in Economics from Gdansk University of Technology (2003) and Universita’ Politecnica delle Marche (2005), as well as MA degree in Contemporary European Studies from Sussex University (2006, with distinction). I received my PhD in Economics...
-
PPAM 2022
EventsThe PPAM 2022 conference, will cover topics in parallel and distributed computing, including theory and applications, as well as applied mathematics.
-
Podstawy uczenia maszynowego AI
e-Learning CoursesPodstawy uczenia maszynowego. Machine Learning fundamentals.
-
Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
-
Krzysztof Goczyła prof. dr hab. inż.
PeopleKrzysztof Goczyła, full professor of Gdańsk University of Technology, computer scientist, a specialist in software engineering, knowledge engineering and databases. He graduated from the Faculty of Electronics Technical University of Gdansk in 1976 with a degree in electronic engineering, specializing in automation. Since then he has been working at Gdańsk University of Technology. In 1982 he obtained a doctorate in computer science...
-
Phong B. Dao D.Sc., Ph.D.
PeoplePhong B. Dao received the Engineer degree in Cybernetics in 2001, the M.Sc. degree in Instrumentation and Control in 2004, both from Hanoi University of Science and Technology in Vietnam, and the Ph.D. degree in Control Engineering in 2011 from the University of Twente, the Netherlands. In May 2020, Dr. Dao received the degree of D.Sc. (Habilitation) in Mechanical Engineering from the AGH University of Science and Technology, Poland....
-
Automated anonymization of sensitive data on production unit
PublicationThe article presents an approach to data anonymization with the use of generally available tools. The focus is put on the practical aspects of using open-source tools in conjunction with programming libraries provided by suppliers of industrial control systems. This universal approach shows the possibilities of using various operating systems as a platform for process data anonymization. An additional advantage of the described...