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Wyniki wyszukiwania dla: DYNAMIC LEARNING

Wyniki wyszukiwania dla: DYNAMIC LEARNING

  • Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise

    Publikacja

    Purpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...

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  • Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective

    Publikacja

    Purpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...

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  • Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen

    Publikacja

    - MOLECULES - Rok 2024

    Deep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...

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  • Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen

    Publikacja
    • P. Cysewski
    • T. Jeliński
    • M. Przybyłek
    • A. Mai
    • J. Kułak

    - MOLECULES - Rok 2024

    Deep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...

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  • User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning

    Publikacja

    - SENSORS - Rok 2024

    In this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...

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  • Novel approach to ecotoxicological risk assessment of sediments cores around the shipwreck by the use of self-organizing maps

    Publikacja

    - ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY - Rok 2014

    Marine and coastal pollution plays an increasingly important role due to recent severe accidents which drew attention to the consequences of oil spills causing widespread devastation of marine ecosystems. All these problems cannot be solved without conducting environmental studies in the area of possible oil spill and performing chemometric evaluation of the data obtained looking for similar patterns among pollutants and optimize...

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  • Direct brain stimulation modulates encoding states and memory performance in humans

    Publikacja
    • Y. Ezzyat
    • J. E. Kragel
    • J. F. Burke
    • D. F. Levy
    • A. Lyalenko
    • P. Wanda
    • L. O'Sullivan
    • K. B. Hurley
    • S. Busygin
    • I. Pedisich... i 16 innych

    - CURRENT BIOLOGY - Rok 2017

    People often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting,...

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  • Bridging theory and practice in postgraduate education on development and planning: Gdynia Urban Summer Schools 2016-2018

    In this article, the authors discuss results achieved by the Gdynia Urban Summer School (GUSS) organised annually (between 2016 and 2018) in Gdynia, Poland. The GUSS was meant for young practitioners from various professions such as urban and regional planning, urban design, architecture, civil engineering and transport planning. The objective was to give workshop participantspractical interdisciplinary...

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  • The Neural Knowledge DNA Based Smart Internet of Things

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2020

    ABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...

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  • Investigating Feature Spaces for Isolated Word Recognition

    Publikacja
    • P. Treigys
    • G. Korvel
    • G. Tamulevicius
    • J. Bernataviciene
    • B. Kostek

    - Rok 2020

    The study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...

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  • Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review

    Publikacja

    - Applied Sciences-Basel - Rok 2023

    Background: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...

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  • Projektowanie środowiskowe - edukacja architektoniczna

    Publikacja

    - Rok 2009

    Przedstawiono krytykę obecnej edukacji architektonicznej oraz dyskusję nad kierunkami jej zmian. Omówiono dokumenty międzynarodowych organizacji zajmujących się teoria i praktyką edukacji architektonicznej ze szczególnym uwzględnieniem edukacji w zakresie projektowania środowiskowego oraz systemów samoksztalcenia (learning to learn) i kształcenia ustawicznego.

  • Perspektywy wykorzystania technologii internetowych typu E-learning w dydaktyce szkół wyższych.

    Publikacja

    Artykuł dotyczy nauczania przez Internet na poziomie uniwersyteckim. Zaprezentowany został model wirtualnego uniwersytetu, który obejmuje materiały dydaktyczne, komunikację, egzaminy i organizację. Artykuł koncentruje się na technicznych zagadnieniach. Przeanalizowano także wpływ wykorzystania technologii E-learning na różne aspekty życia wyższej uczelni.

  • Mobile Activity Plan Applications for Behavioral Therapy of Autistic Children

    This paper concerns technological support for behavioral therapy of autistic children. A family of tools dedicated for mobile devices is presented, that allows to design and perform an activity schedule in behavioral therapy. The paper describes the main challenges, that were encountered, especially in meeting the non-functional requirements of the application: simplicity, repeatability, robustness, personalization, re-usability...

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  • THE INFLUENCE OF QUESTION SET ON STUDENT QUIZ RESULTS

    The advent of e-Learning tools allowing for automated online test grading will probably increase the frequency of using tests in technical education. The same tools may provide for measures of test question quality. By purposely crafting question sets, test grading may serve different goals. The paper contains examples and test study with score histograms.

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  • Wspomaganie zajęć dydaktycznych z matematyki na kierunkach technicznych kursem e-Learningowym"

    W artykule przedstawiono doświadczenia w zakresie wspomagania przedmiotu matematyka na pierwszym roku studiów inżynierskich kursem e-learningowym. Wykonano analizę wyników testów przeprowadzonych podczas e-zajęć. Przedstawiono również wyniki ankiet ewaluacyjnych obrazujących stosunek studentów do wprowadzania kształcenia matematyki z wykorzystaniem blended learning.

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  • Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.

    Publikacja

    - Rok 2005

    W referacie zaprezentowano główne zadania oraz ofertę szkoleniową Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej (CEN PG) w kontekście realizowanych projektów Unii Europejskiej. Przedstawiono projekt Leonardo da Vinci EMDEL - European Model for Distance Education and learning - realizowany przez CEN PG w latach 2001-2005 oraz opisano doświadczenia w zakresie adaptacji i lokalizacji opracowanych przez partnerów projektu...

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

    Publikacja

    - Rok 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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  • MOOCs in SP4CE - case studies (Strategic Partnership for Creativity and Entrepreneurship)

    Publikacja

    - Rok 2016

    SP4CE stands for Strategic Partnership for Creativity and Entrepreneurship project which has been funded with support from the European Commission under the ERASMUS+ Programme in the period 1st September 2014 - 31st August 2017. The main purpose of SP4CE project is to design innovative e-learning tools for collaboration between students, enterprises and teachers. It concentrates on identifying users’ needs and supports the development...

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  • Machine Learning and Electronic Noses for Medical Diagnostics

    Publikacja

    The need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...

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  • Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks

    Publikacja

    - CMC-Computers Materials & Continua - Rok 2020

    The increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...

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  • WebCT - platforma i tłumaczenie.

    Publikacja

    W artykule przedstawiono doświadczenia Centrum Edukacji Niestacjonarnej i Międzywydziałowego Koła Naukowego Studentów Politechniki Gdańskiej DEC@TUG w tłumaczeniu i implementacji platform LMS (ang. Learning Management System). Krótko scharakteryzowano funkcjonalność platform BSCW I Moodle, których interfejsy zostały przetłumaczone przez członków Koła DEC@TUG w latach 2000-2003. Opisano główne funkcje platformy WebCT, takie jak...

  • BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION

    Publikacja

    - Rok 2018

    The 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...

  • Smart Knowledge Engineering for Cognitive Systems: A Brief Overview

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2022

    Cognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...

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  • Deep learning for ultra-fast and high precision screening of energy materials

    Publikacja
    • Z. Wang
    • Q. Wang
    • Y. Han
    • Y. Ma
    • H. Zhao
    • A. Nowak
    • J. Li

    - Energy Storage Materials - Rok 2021

    Semiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...

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  • Creating a radiological database for automatic liver segmentation using artificial intelligence.

    Publikacja

    - EJSO-EUR J SURG ONC - Rok 2022

    Imaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.

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  • COLLABORATIVE LEARNING ENVIRONMENT FOR ENGINEERING EDUCATION (COLED)

    Publikacja

    - Rok 2020

    Collaborative 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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  • Looking through the past: better knowledge retention for generative replay in continual learning

    Publikacja
    • V. Khan
    • S. Cygert
    • K. Deja
    • T. Trzciński
    • B. Twardowski

    - IEEE Access - Rok 2024

    In this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...

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  • Divide and not forget: Ensemble of selectively trained experts in Continual Learning

    Publikacja
    • G. Rypeść
    • S. Cygert
    • V. Khan
    • T. Trzciński
    • B. Zieliński
    • B. Twardowski

    - Rok 2024

    Class-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...

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  • Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment

    Publikacja
    • E. Sanchez
    • W. Peng
    • C. Toro
    • C. Sanin
    • M. Grana
    • E. Szczerbicki
    • E. Carrasco
    • F. Guijarro
    • L. Brualla

    - NEUROCOMPUTING - Rok 2014

    Clinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge imposes to CDSS the continuous update of the domain knowledge and decision criteria. Traditional approaches require costly tedious manual maintenance of the CDSS knowledge bases and repositories. Often, such an effort cannot be assumed by medical teams, hence...

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  • Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2024

    This guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...

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  • Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing

    Developing signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....

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  • Predictions of cervical cancer identification by photonic method combined with machine learning

    Publikacja
    • M. Kruczkowski
    • A. Drabik-Kruczkowska
    • A. Marciniak
    • M. Tarczewska
    • M. Kosowska
    • M. Szczerska

    - Scientific Reports - Rok 2022

    Cervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...

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  • DevEmo—Software Developers’ Facial Expression Dataset

    The COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...

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  • t-SNE Highlights Phylogenetic and Temporal Patterns of SARS-CoV-2 Spike and Nucleocapsid Protein Evolution

    Publikacja
    • G. Tamazian
    • A. Komissarov
    • D. Kobak
    • D. Polyakov
    • E. Andronov
    • S. Nechaev
    • S. Kryzhevich
    • Y. Porozov
    • E. Stepanov

    - Rok 2022

    We propose applying t-distributed stochastic neighbor embedding to protein sequences of SARS-CoV-2 to construct, visualize and study the evolutionary space of the coronavirus. The basic idea is to explore the COVID-19 evolution space by using modern manifold learning techniques applied to evolutionary distances between variants. Evolutionary distances have been calculated based on the structures of the nucleocapsid and spike proteins.

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  • Szkolenie elektroniczne narzędziem budowy kapitału ludzkiego.

    Publikacja

    - Rok 2004

    Autorka ukazuje proces szkoleń pracowników począwszy od tradycyjnego do bardziej nowoczesnego typu e-learning. W nowoczesnych przedsiębiorstwach odchodzxi sie od typowego, tradycyjnego szkolenia na rzecz bardziej efektywnych,tańszych i skutecznych czyli elektronicznych. W artykule pokazane są zalety i korzyści szkoleń elektronicznych w przygotowaniu pracowników do efektywnej pracy.

  • Study of various machine learning approaches for Sentinel-2 derived bathymetry

    Publikacja

    - PLOS ONE - Rok 2023

    In recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...

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  • ePBL – czyli nauka poprzez realizację projektu w środowisku wirtualnym

    Publikacja

    Kształcenie inżynierów stanowi niezwykle istotny element systemu edukacyjnego każdego nowoczesnego państwa, ponieważ to właśnie dobrze przygotowana kadra inżynierska decyduje o tempie rozwoju i poziomie infrastruktury danego kraju. Wykorzystanie najnowszych technologii w procesie edukacyjnym jest naturalną konsekwencją „informatyzacji” życia. Pokolenia dorastające w świecie wszechobecnych komputerów, urządzeń mobilnych i cyfrowej...

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  • Knowledge pills in Education and Training: A Literature Review

    Publikacja
    • E. Bolisani
    • E. Scarso
    • M. Zięba
    • S. Durst
    • A. Zbuchea
    • A. Lis
    • T. C. Kassaneh

    - Rok 2022

    Object and purpose: Knowledge pills (KPs) are a technique for transferring knowledge through short factual batches of content. In education and vocational training, they can help learners acquire specific pieces of knowledge in a few minutes, through a “microteaching” approach where learners can be involved in active and interactive exercises, quizzes, and games. Thanks to the advancements of multimedia platforms, they can contain...

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  • Porównanie systemu Ilias i Moodle - przypadek użycia.

    Publikacja

    W artykule przedstawiono koncepcję wykorzystania darmowych systemów LMS (ang. Learning Management System) jako narzędzi wspomagających prowadzenie zajęć metodą tradycyjną F2F (ang. Face to Face). Omówiono eksperyment przeprowadzony przez dwie uczelnie trójmiejskie: Akademię Morską i Politechnikę Gdańską. Celem eksperymentu było porównanie systemu Ilias (wersja 2.4.4) z systemem Moodle (wersja 1.2).

  • Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions

    Publikacja

    - Rok 2022

    Higher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...

  • Deep learning based thermal image segmentation for laboratory animals tracking

    Publikacja

    Automated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...

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  • Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends

    Publikacja

    - Information Fusion - Rok 2022

    Semantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...

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  • How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends

    Illegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....

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  • Are Pair Trading Strategies Profitable During COVID-19 Period?

    Publikacja
    • M. K. Sohail
    • A. Raheman
    • J. Iqbal
    • M. I. Sindhu
    • A. Staar
    • M. Mushafiq
    • H. Afzal

    - Journal of Information & Knowledge Management - Rok 2022

    Pair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting...

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  • Machine learning applied to acoustic-based road traffic monitoring

    The motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...

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  • Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters

    Publikacja

    - ENERGIES - Rok 2022

    Smart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...

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  • Travel agents and destination management organizations: eLearning as a strategy to train tourism trade partners.

    This article offers an overview of the existing online courses run by national destination management organizations (DMOs) in order to better equip travel agents and tour operators in the sales activities of the tourism destinations. These online courses represent one of the B2B offers by DMOs and an interesting opportunity for travel agents, who are trying to find their identity and competitive advantage within the context of...

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  • Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning

    Publikacja
    • K. Kąkol

    - Rok 2023

    The Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...

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  • Machine learning applied to acoustic-based road traffic monitoring

    Publikacja

    - Rok 2022

    The motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...

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