Search results for: machine learning, music analysis, tonality - Bridge of Knowledge

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Search results for: machine learning, music analysis, tonality

Search results for: machine learning, music analysis, tonality

  • MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences

    Publication
    • S. R. Gupte
    • D. S. Jain
    • A. Srinivasan
    • R. Aduri

    - Year 2020

    —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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  • Introduction to the ONDM 2022 special issue

    Publication
    • J. Turkiewicz
    • T. Gomes
    • M. Klinkowski
    • J. Rak
    • M. Tornatore

    - Journal of Optical Communications and Networking - Year 2023

    This JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...

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  • TF-IDF weighted bag-of-words preprocessed text documents from Simple English Wikipedia

    Open Research Data

    The 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...

  • Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour

    Publication

    The growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...

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  • Wpływ struktur wsparcia na efektywność nauczania języka pisanego w środowisku e-learningowym

    Publication

    The process of knowledge and language skills development during an online course can be very effective if student engagement in learning is achieved. This can be attained by introducing general and specific support mechanisms prior to the commencement of the course and during it. The former relates to the technological aspect, that is to familiarizing students with the functionalities of the virtual learning environment they will...

  • Abdalraheem Ijjeh Ph.D. Eng.

    People

    The primary research areas of interest are artificial intelligence (AI), machine learning, deep learning, and computer vision, as well as modeling physical phenomena (i.e., guided waves in composite laminates). The research interests described above are utilized for SHM and NDE applications, namely damage detection and localization in composite materials.  

  • Examining Feature Vector for Phoneme Recognition

    Publication

    - Year 2018

    The aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...

  • Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets

    Publication

    - Informatica - Year 2021

    This 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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  • Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?

    Publication

    - Year 2022

    In this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...

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  • Categorization of Cloud Workload Types with Clustering

    The paper presents a new classification schema of IaaS cloud workloads types, based on the functional characteristics. We show the results of an experiment of automatic categorization performed with different benchmarks that represent particular workload types. Monitoring of resource utilization allowed us to construct workload models that can be processed with machine learning algorithms. The direct connection between the functional...

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  • Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease

    In this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...

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  • Piotr Figura dr inż.

    Piotr Figura is employed as an assistant professor at the Department of Finance at the Faculty of Management and Economics, Gdansk University of Technology. He is a member of Commission for the Verification of Learning Outcomes, as well as an academic reviewer of the Central Exemination Booard. He is the author or co-author of several scientific monographs including: Standard financial indicators for stock enterprises; Classical...

  • Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection

    Publication
    • A. G. Akintola
    • A. O. Balogun
    • L. F. Capretz
    • H. A. Mojeed
    • S. Basri
    • S. A. Salihu
    • F. E. Usman-Hamza
    • P. O. Sadiku
    • G. B. Balogun
    • Z. O. Alanamu

    - Applied Sciences-Basel - Year 2022

    As a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem,...

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  • Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning

    Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...

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  • A study on signal processing methods applied to hearing aids

    Publication

    - Year 2016

    This paper presents a short survey on current technology available in hearing aids with a focus on digital signal processing techniques used. First, factors influencing the hearing aid effectiveness are introduced. Then, examples of the present DSP methods and strategies are provided. Also, a description of current limitations of hearing aids and future trends of development are shown. Finally, the notion of computational auditory...

  • Limitations of Emotion Recognition from Facial Expressions in e-Learning Context

    Publication

    The 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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  • Dynamic state assessment of the water turbine with the power of 600 kW

    Publication

    - Diagnostyka - Year 2013

    The article discusses the results of experimental studies to assess the dynamic state of the turbine set with the Kaplan turbine. The dynamic assessment was made on the basis of appropriate standards, based on the measurement results of selected parameters of vibration, which have been measured for several states of the machine load. In addition, we attempted to identify the causes of the increased vibration levels based on the...

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  • AffecTube — Chrome extension for YouTube video affective annotations

    Publication

    - SoftwareX - Year 2023

    The shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...

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  • University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies

    Publication

    - Year 2021

    Leading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...

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  • Asking Data in a Controlled Way with Ask Data Anything NQL

    Publication
    • A. Seganti
    • P. Kapłański
    • J. Campo
    • K. Cieśliński
    • J. Koziołkiewicz
    • P. Zarzycki

    - Year 2016

    While to collect data, it is necessary to store it, to understand its structure it is necessary to do data-mining. Business Intelligence (BI) enables us to make intelligent, data-driven decisions by the mean of a set of tools that allows the creation of a potentially unlimited number of machine-generated, data-driven reports, which are calculated by a machine as a response to queries specified by humans. Natural Query Languages...

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  • LOS and NLOS identification in real indoor environment using deep learning approach

    Visibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...

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  • Profile irregularities of turned surfaces as a result of machine tool interactions

    The paper describes the influence of the machining operation on a surface, which disturbs the projection of the tool profile in the form of its relative movements with respect to the object. The elements of the machine tool undergo constant wear during the machining process, it is therefore important to recognize the effects of their influence on the surface's irregularities. Amplitude-frequency analysis of lateral profiles has...

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  • Comparison of Lithuanian and Polish Consonant Phonemes Based on Acoustic Analysis – Preliminary Results

    Publication

    - Archives of Acoustics - Year 2019

    The goal of this research is to find a set of acoustic parameters that are related to differences between Polish and Lithuanian language consonants. In order to identify these differences, an acoustic analysis is performed, and the phoneme sounds are described as the vectors of acoustic parameters. Parameters known from the speech domain as well as those from the music information retrieval area are employed. These parameters are...

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  • Novel proposal for V2X systems and WBAN cooperation to improve road safety

    Publication

    - Year 2017

    In this paper, a novel proposal of the automotive Vehicle-to-Everything system solution is presented. In this proposal, there are included the Machine to Machine type communication system and the sensor system based on a short-range the Wireless Body Area Network communication. The aim of this paper is the analysis of the model for communication, especially its architecture and signals structure for the proposed solution. The use...

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  • Separability Assessment of Selected Types of Vehicle-Associated Noise

    Music Information Retrieval (MIR) area as well as development of speech and environmental information recognition techniques brought various tools in-tended for recognizing low-level features of acoustic signals based on a set of calculated parameters. In this study, the MIRtoolbox MATLAB tool, designed for music parameter extraction, is used to obtain a vector of parameters to check whether they are suitable for separation of...

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  • Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices

    Publication

    - CHAOS - Year 2023

    We introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...

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  • Augmenting digital documents with negotiation capability

    Publication

    Active digital documents are not only capable of performing various operations using their internal functionality and external services, accessible in the environment in which they operate, but can also migrate on their own over a network of mobile devices that provide dynamically changing execution contexts. They may imply conflicts between preferences of the active document and the device the former wishes to execute on. In the...

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  • Improving all-reduce collective operations for imbalanced process arrival patterns

    Publication

    Two new algorithms for the all-reduce operation optimized for imbalanced process arrival patterns (PAPs) are presented: (1) sorted linear tree, (2) pre-reduced ring as well as a new way of online PAP detection, including process arrival time estimations, and their distribution between cooperating processes was introduced. The idea, pseudo-code, implementation details, benchmark for performance evaluation and a real case example...

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  • Topological-numerical analysis of a two-dimensional discrete neuron model

    We conduct computer-assisted analysis of a two-dimensional model of a neuron introduced by Chialvo in 1995 [Chaos, Solitons Fractals 5, 461–479]. We apply the method of rigorous analysis of global dynamics based on a set-oriented topological approach, introduced by Arai et al. in 2009 [SIAM J. Appl. Dyn. Syst. 8, 757–789] and improved and expanded afterward. Additionally, we introduce a new algorithm to analyze the return times...

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  • SpamVis: A Visual Interactive System for Spam Review Detection

    Publication

    - Year 2024

    In recent times, the number of spam reviews through various online platforms has emerged as a prime challenge, profoundly impacting businesses and consumers. These fake reviews not only distort clients’ perceptions of products and services but also erode trust within the digital ecosystem. Despite the advent of machine learning (ML) techniques for identifying spam reviews, comparing text, and pinpointing groups of spammers, there...

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  • Basic Hand Gestures Classification Based on Surface Electromyography

    This paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...

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  • Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023

    Publication

    - Data in Brief - Year 2024

    The dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...

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  • Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks

    Publication

    - IEEE Access - Year 2022

    Object detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...

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  • Automatic classification and mapping of the seabed using airborne LiDAR bathymetry

    Publication
    • Ł. Janowski
    • P. Tysiąc
    • R. Wróblewski
    • M. Rucińska
    • A. Kubowicz- Grajewska

    - ENGINEERING GEOLOGY - Year 2022

    Shallow 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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  • Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning

    Publication

    - Year 2023

    This 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 Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning

    Publication

    - Year 2022

    This paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational 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 effects....

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  • An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning

    Publication

    - Year 2023

    This paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational 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 effects....

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  • Investigation of educational processes with affective computing methods

    Publication

    This paper concerns the monitoring of educational processes with the use of new technologies for the recognition of human emotions. This paper summarizes results from three experiments, aimed at the validation of applying emotion recognition to e-learning. An analysis of the experiments’ executions provides an evaluation of the emotion elicitation methods used to monitor learners. The comparison of affect recognition algorithms...

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  • From Knowledge based Vision Systems to Cognitive Vision Systems: A Review

    Publication

    - Year 2018

    Computer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...

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  • Engineering education for smart grid systems in the quasi-industrial environment of the LINTE^2 laboratory

    Smart grid systems are revolutionising the electric power sector, integrating advanced technologies to enhance efficiency, reliability and sustainability. It is important for higher education to equip the prospective smart grid professional with the competencies enabling them to navigate through the related complexities and drive innovation. To achieve this, interdisciplinary education programmes are necessary, addressing inter...

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  • Adaptacyjny system oświetlania dróg oraz inteligentnych miast

    Publication

    - Year 2024

    Przedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...

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  • Insights in microbiotechnology: 2022.Editorial

    Publication
    • M. Bilal

    - Frontiers in Microbiology - Year 2024

    This Research Topic serves as an invaluable resource for readers interested in staying updated with the latest progress and developments in the field of microbiotechnology. It spotlights the innovative research conducted by up-and-coming experts in the field, specifically emphasizing the transforming abilities of microorganisms that greatly influence the scientific community. The advent of multi-omic technologies has revolutionized microbiotechnology,...

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  • Instantaneous power signal measurements for bearing diagnostics

    Open Research Data

    Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous current and voltage power supplied to the engines. Bearing damage causes the appearance of deformations, which are in the form of additional harmonic components...

  • Analysis of the instantaneous power signal for bearing diagnostics - bearing undamaged

    Open Research Data

    The attached dataset contains the measurement results of the instantaneous values of current and voltage, recorded during the diagnostics of an undamaged bearing. Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous...

  • Analysis of the instantaneous power signal for bearing diagnostics -bearing damaged

    Open Research Data

    The attached dataset contains the measurement results of the instantaneous values of current and voltage, recorded during the diagnostics of a damaged bearing. Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous...

  • A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine

    The article presents the method for the evaluation of selected manufacturing processes using the analysis of vibration and sound signals. This method is based on the use of sensors installed outside the machining zone, allowing to be used quickly and reliably in real production conditions. The article contains a developed measurement methodology based on the specific location of microphones and vibration transducers mounted on...

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  • Voice command recognition using hybrid genetic algorithm

    Publication

    Abstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...

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  • Agata Kot-Wasik prof. dr hab. inż.

    Agata Kot-Wasik, born in 1964 in Siedlce, graduated in 1988 from the Faculty of Chemistry, Gdańsk University of Technology in Industrial and Technical Analysis. In 1988-1992 she was employed in the Department of Organic Chemistry. In 1990, she completed postgraduate studies "Instrumental techniques in the traces analysis and Environmental Protection" at GUT, and in 1992 began PhD Studies at the Faculty of Chemistry, GUT, which...

  • Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2022

    The entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance...

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  • Classification of Polish wines by application of ultra-fast gas chromatography

    The 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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