Wyniki wyszukiwania dla: LINGUISTICS , SENTIMENT ANALYSIS, MACHINE LEARNING, ORGANIZATIONS - MOST Wiedzy

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Wyniki wyszukiwania dla: LINGUISTICS , SENTIMENT ANALYSIS, MACHINE LEARNING, ORGANIZATIONS

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Wyniki wyszukiwania dla: LINGUISTICS , SENTIMENT ANALYSIS, MACHINE LEARNING, ORGANIZATIONS

  • A new multi-process collaborative architecture for time series classification

    Publikacja

    - KNOWLEDGE-BASED SYSTEMS - Rok 2021

    Time series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...

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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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  • Bimodal deep learning model for subjectively enhanced emotion classification in films

    Publikacja

    - INFORMATION SCIENCES - Rok 2024

    This research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....

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  • Audio-visual aspect of the Lombard effect and comparison with recordings depicting emotional states.

    In this paper an analysis of audio-visual recordings of the Lombard effect is shown. First, audio signal is analyzed indicating the presence of this phenomenon in the recorded sessions. The principal aim, however, was to discuss problems related to extracting differences caused by the Lombard effect, present in the video , i.e. visible as tension and work of facial muscles aligned to an increase in the intensity of the articulated...

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  • Towards semantic-rich word embeddings

    Publikacja

    - Annals of Computer Science and Information Systems - Rok 2019

    In recent years, word embeddings have been shown to improve the performance in NLP tasks such as syntactic parsing or sentiment analysis. While useful, they are problematic in representing ambiguous words with multiple meanings, since they keep a single representation for each word in the vocabulary. Constructing separate embeddings for meanings of ambiguous words could be useful for solving the Word Sense Disambiguation (WSD)...

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  • The Reference Model of Tools Adaptation in the Perspective of Technological Agile Transformaton in IT Organizations

    Publikacja
    • C. Orłowski
    • B. Chrabski
    • A. Ziółkowski
    • T. Deręgowski
    • M. Kurzawski

    - Rok 2016

    The scientific aim of the presented paper is the analysis of agile transformation processes in IT organizations in technological perspective of such transformation. The phenomenon of agile transformation becomes a complex challenge for an IT organization, since it has not been analysed in detail so far. There is not any research on the readiness of IT organizations for the realization of agile transformation processes, and such...

  • 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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  • The Use of Information and Communication Technologies in Cluster Organizations

    Publikacja

    - Rok 2019

    The purpose of the paper is to explore how cluster organizations (COs) take advantage of Information and Communication Technologies (ICT). The paper addresses the research question: “How do cluster organizations take advantage of ICT in fulfilling their main roles?”. The research was carried out in the first half of 2016 in four purposefully selected cluster organizations. The main research strategy involved Grounded Theory; the...

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  • THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN

    Publikacja

    - Rok 2021

    In the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...

  • Knowledge Risks in the Sharing Economy

    Publikacja

    - Rok 2018

    This chapter presents a theoretical analysis of potential risks connected with knowledge that organizations operating in the sharing economy might potentially face. Nowadays, it can be stated that an increasing amount of individuals and organizations participate in sharing and exchanging data, information, and knowledge, as well as physical goods and services (Botsman & Rogers, 2011). The development of the sharing economy has...

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  • Przegląd metod szybkiego prototypowania algorytmów uczenia maszynowego w FPGA

    W artykule opisano możliwe do wykorzystania otwarte narzędzia wspomagające szybkie prototypowanie algorytmów uczenia maszynowego (ML) i sztucznej inteligencji (AI) przy użyciu współczesnych platform FPGA. Przedstawiono przykład szybkiej ścieżki przy realizacji toru wideo wraz z implementacją przykładowego algorytmu prze-twarzania w trybie na żywo.

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  • Analysis of results of large-scale multimodal biometric identity verification experiment

    An analysis of a large set of biometric data obtained during the enrolment and the verification phase in an experimental biometric system installed in bank branches is presented. Subjective opinions of bank clients and of bank tellers were also surveyed concerning the studied biometric methods in order to discover and to explore relations emerging from the obtained multimodal dataset. First, data acquisition and identity verification...

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  • Religious social action and its organizational profiles

    Publikacja

    - Journal of Organizational Ethnography - Rok 2019

    Purpose Social action implemented by the Church via its affiliated entities, foundations and associations may be viewed as a uniform activity. In reality, however, several organizational profiles exist that depend on the origin of these organizations (lay or religious), the scope of their activities (local or general) and their dependence on resources (whether from public administration or civil society). The paper aims to discuss...

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  • IFE: NN-aided Instantaneous Pitch Estimation

    Publikacja

    Pitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...

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  • Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry

    We describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular...

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  • Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents

    Publikacja
    • S. Donghui
    • L. Zhigang
    • J. Zurada
    • A. Manikas
    • J. Guan
    • P. Weichbroth

    - KNOWLEDGE AND INFORMATION SYSTEMS - Rok 2024

    The construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...

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

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

    - Rok 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

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

    - Journal of Optical Communications and Networking - Rok 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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  • Wpływ struktur wsparcia na efektywność nauczania języka pisanego w środowisku e-learningowym

    Publikacja

    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...

  • Development of cooperation in localized cooperation networks: A comparative study of cluster organizations and technology parks

    Publikacja

    - Rok 2020

    The main aim of the paper is to analyze the level of development of cooperative relationships in localized cooperation networks – among enterprises associated in cluster organizations and park tenants. The author reports the findings from the quantitative study carried out in the selected cluster organizations and technology parks functioning in Poland. The basic method of data collection was a survey questionnaire. The research...

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

    Publikacja

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

    Publikacja

    - Informatica - Rok 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?

    Publikacja

    - Rok 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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  • Sustainability of Cluster Organizations as Open Innovation Intermediaries

    Publikacja

    The purpose of the paper is to identify the most important open innovation practices used by cluster organizations (COs). To reflect these practices, the paper uses the concept of the trajectory of relationship development in COs, applied in the Interizon cluster organization. Additionally, this paper introduces the potential sustainability-related implications of open innovation adoption in cluster organizations. An in-depth direct...

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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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  • Inter-governmental Collaborative Networks for Digital Government Innovation Transfer -Structure, Membership, Operation

    Publikacja

    Digital government refers to the transformation of government organizations and their relationships with citizens, business and each other through digital technology. It entails digital innovation in processes, services, organizations, policies, etc. which are increasingly developed and tested in one country and transferred, after adaptation, to other countries. The process of innovation transfer and the underlying information...

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

    Publikacja

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

    Publikacja
    • 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 - Rok 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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  • Intelligent Decision Forest Models for Customer Churn Prediction

    Publikacja
    • F. E. Usman-Hamzah
    • A. O. Balogun
    • L. F. Capretz
    • H. A. Mojeed
    • S. Mahamad
    • S. A. Salihu
    • A. G. Akintola
    • S. Basri
    • R. T. Amosa
    • N. K. Salahdeen

    - Applied Sciences-Basel - Rok 2022

    Customer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....

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

    Publikacja

    - Diagnostyka - Rok 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

    Publikacja

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

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

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

    Publikacja

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

    Publikacja

    - Rok 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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  • How does the Relationship Between the Mistakes Acceptance Component of Learning Culture and Tacit Knowledge-Sharing Drive Organizational Agility? Risk as a Moderator

    Publikacja

    - Rok 2024

    Changes in the business context create the need to adjust organizational knowledge to new contexts to enable the organizational agile responses to secure competitiveness. Tacit knowledge is strongly contextual. This study is based on the assumption that business context determines tacit knowledge creation and acquisition, and thanks to this, the tacit knowledge-sharing processes support agility. Therefore, this study aims to expose...

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  • Do clusters help companies to "go green"? Experience of Polish National Key Clusters

    Publikacja

    - Rok 2024

    This study aims to explore cluster activity in the field of green transformation, taking into account the green, low-carbon and circular economy. Our intention was to identify the main green practices used by cluster organizations, which we showed through the lens of the attributes of both the cluster and the cluster organization. Through our study, we sought to answer the question: what is the role of cluster organizations in...

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  • Augmenting digital documents with negotiation capability

    Publikacja

    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

    Publikacja

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

    Publikacja

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

    Publikacja

    - Rok 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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  • Social Media in the Fashion Industry. Fundamentals, Strategy and Research Methods

    Publikacja
    • S. Patricia
    • H. T. Nobile
    • C. Sánchez-Blanco
    • N. Sabatini

    - Rok 2024

    This book introduces social network fundamentals in the fashion domain. It addresses the creation of social media marketing plans, highlighting strategic approaches that allow fashion brands to differentiate themselves in the ephemeral and challenging fashion context. Through a variety of academic and professional sources and by sharing the results of their own research, the authors present research methodologies, including netnography,...

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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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  • 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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  • Investigation of educational processes with affective computing methods

    Publikacja

    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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