Wyniki wyszukiwania dla: machine learning - MOST Wiedzy

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Wyniki wyszukiwania dla: machine learning

Wyniki wyszukiwania dla: machine learning

  • Sounding Mechanism of a Flue Organ Pipe—A Multi-Sensor Measurement Approach

    Publikacja

    - SENSORS - Rok 2024

    This work presents an approach that integrates the results of measuring, analyzing, and modeling air flow phenomena driven by pressurized air in a flue organ pipe. The investigation concerns a Bourdon organ pipe. Measurements are performed in an anechoic chamber using the Cartesian robot equipped with a 3D acoustic vector sensor (AVS) that acquires both acoustic pressure and air particle velocity. Also, a high-speed camera is employed...

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  • Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?

    Publikacja

    - ENERGIES - Rok 2023

    The estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related...

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  • Automatic labeling of traffic sound recordings using autoencoder-derived features

    Publikacja

    An approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...

  • A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors

    Publikacja

    In recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones,...

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

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

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

    Publikacja

    - IEEE Access - Rok 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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  • Computer-assisted pronunciation training—Speech synthesis is almost all you need

    Publikacja

    - SPEECH COMMUNICATION - Rok 2022

    The research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...

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  • How personality traits, sports anxiety, and general imagery could influence the physiological response measured by SCL to imagined situations in sports?

    Dane Badawcze
    open access

    The data were collected to understand how individual differences in personality (e.g. neuroticism), general imagery, and situational sports anxiety are linked to arousal measuring with skin conductance level (SCL) in situational imagery (as scripted for sport-related scenes). Thirty persons participated in the study, aged between 14 and 42 years, with...

  • Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures

    Publikacja

    - Materials - Rok 2023

    Dapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS:...

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  • Can Web Search Queries Predict Prices Change on the Real Estate Market?

    Publikacja

    This study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...

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  • Adam Władziński

    Osoby

    Adam Władziński, doktorant na Politechnice Gdańskiej, specjalizuje się w inżynierii biomedycznej, skupiając się na uczeniu maszynowym do przetwarzania obrazów z druku 3D układów pomiarowych i tkanek biologicznych, a także na komercyjnym zastosowaniu technologii blockchain. Posiadając wykształcenie z dziedziny elektroniki na Wydziale Elektroniki, Telekomunikacji i Informatyki (ETI), praca magisterska Adama Władzińskiego koncentrowała...

  • Alhassan Ali Ahmed

    Osoby

    Alhassan Ali Ahmed BSc of pharmacy, MSc in Bioinformatics and Biotechnology, and currently doing his PhD in Bioinformatics and Machine Learning. Alhassan has considerable experience in the pharmaceutical industry as he worked before in different positions such as; Community pharmacist, Medical advisor, Antibiotics production specialist, Quality assurance specialist, Key account manager for Immunotherapeutic medications, and currently,...

  • Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit

    The general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...

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  • Energy-Aware Scheduling for High-Performance Computing Systems: A Survey

    Publikacja

    High-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...

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  • Data governance: Organizing data for trustworthy Artificial Intelligence

    Publikacja
    • M. Janssen
    • P. Brous
    • E. Estevez
    • L. S. Barbosa
    • T. Janowski

    - GOVERNMENT INFORMATION QUARTERLY - Rok 2020

    The rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....

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  • Metal–Organic Frameworks (MOFs) for Cancer Therapy

    Publikacja
    • M. Saeb
    • N. Rabiee
    • M. Mozafari
    • F. Verpoort
    • L. G. Voskressensky
    • R. Luque

    - Materials - Rok 2021

    MOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...

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  • Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting

    Publikacja

    - Resources-Basel - Rok 2022

    Forecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...

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  • How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?

    Publikacja

    - Rok 2023

    Electrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...

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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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  • Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility

    Publikacja

    - Materials - Rok 2021

    Solubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived...

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  • Psychophysiological strategies for enhancing performance through imagery – skin conductance level analysis in guided vs. self-produced imagery

    Publikacja

    - Scientific Reports - Rok 2024

    Athletes need to achieve their optimal level of arousal for peak performance. Visualization or mental rehearsal (i.e., Imagery) often helps to obtain an appropriate level of activation, which can be detected by monitoring Skin Conductance Level (SCL). However, different types of imagery could elicit different amount of physiological arousal. Therefore, this study aims: (1) to investigate differences in SCL associated with two instructional...

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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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  • Anna Czaja mgr inż.

    Osoby

     Po ukończeniu studiów magisterskich na kierunku Informatyka (Politechnika Gdańska, Wydział Elektroniki, Telekomunikacji i Informatyki) przez szereg lat pracowała jako programista. Obecnie zatrudniona na stanowisku asystenta w Katedrze Zastosowań Informatyki w Zarządzaniu (Politechnika Gdańska, Wydział Zarządzania i Ekonomii). Uczestniczka studiów doktoranckich III stopnia na wydziale Zarządzania i Ekonomii na Politechnice Gdańskiej....

  • Bartosz Szostak mgr inż.

    Osoby

    Bartosz Szostak w 2019 r. ukończył studia inżynierskie na Politechnice Gdańskiej na kierunku Geodezja i Kartografia. W 2021 r. ukończył studia magisterskie również w dziedzinie Geodezji i Kartografii na Politechnice Gdańskiej. Tematyka jego prac dyplomowych dotyczyła uczenia maszynowego i detekcji obiektów.

  • Detection of anomalies in bee colony using transitioning state and contrastive autoencoders

    Honeybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...

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  • Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems

    Publikacja
    • A. Kwaśniewska
    • S. Raghava
    • C. Davila
    • M. Sevenier
    • D. Gamba
    • J. Rumiński

    - Rok 2022

    The rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...

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  • Review of Segmentation Methods for Coastline Detection in SAR Images

    Synthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...

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  • A note on the applications of artificial intelligence in the hospitality industry: preliminary results of a survey

    Publikacja

    - Rok 2021

    Intelligent technologies are widely implemented in different areas of modern society but specific approaches should be applied in services. Basic relationships refer to supporting customers and people responsible for services offering for these customers. The aim of the paper is to analyze and evaluate the state-of-the art of artificial intelligence (AI) applications in the hospitality industry. Our findings show that the major...

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  • Muhammad Jamshed Abbass Phd in Electrical Engineering

    Osoby

    Muhammad Jamshed Abbass received the M.S. degree in electrical engineering from Riphah International University, Islamabad. He is currently pursuing the Ph.D. degree with the Wrocław University of Science and Technology, Wroclaw, Poland. His research interests include machine learning, voltage stability within power systems, control design, analysis, the modeling of electrical power systems, the integration of numerous decentralized...

  • Machine Translation Summit

    Konferencje

  • Machine Vision Applications

    Konferencje

  • Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool

    GPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...

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  • Empirical analysis of tree-based classification models for customer churn prediction

    Publikacja
    • F. E. Usman-Hamza
    • A. O. Balogun
    • S. K. Nasiru
    • L. F. Capretz
    • H. A. Mojeed
    • S. A. Salihu
    • A. G. Akintola
    • M. A. Mabayoje
    • J. B. Awotunde

    - Scientific African - Rok 2023

    Customer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...

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  • Cooperative control in production and logistics

    Publikacja
    • L. Monostori
    • P. Valckenaers
    • A. Dolgui
    • H. Panetto
    • M. Brdyś
    • B. Csáji

    - ANNUAL REVIEWS IN CONTROL - Rok 2015

    Classical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety...

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  • Resource productivity and environmental degradation in EU-27 countries: context of material footprint

    This study explores the relationship between the resource productivity and environmental degradation in European Union-27 countries. This study tests this relationship in context of high, moderate, and low material footprint sub-samples; these samples are formed utilizing the expectation–maximization machine learning algorithm. Using the panel data set of EU-27 countries from 2000 to 2020, linear and non-linear autoregressive distributed...

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  • Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction

    Ionic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...

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  • Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations

    Publikacja

    - Rok 2019

    The aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...

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  • Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors

    Modern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...

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  • Adaptive Positioning Systems Based on Multiple Wireless Interfaces for Industrial IoT in Harsh Manufacturing Environments

    Publikacja
    • J. Mongay Batalla
    • C. X. Mavromoustakis
    • G. Mastorakis
    • N. Xiong, Naixue
    • J. Woźniak

    - IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS - Rok 2020

    As the industrial sector is becoming ever more flexible in order to improve productivity, legacy interfaces for industrial applications must evolve to enhance efficiency and must adapt to achieve higher elasticity and reliability in harsh manufacturing environments. The localization of machines, sensors and workers inside the industrial premises is one of such interfaces used by many applications. Current localization-based systems...

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  • Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review

    Publikacja

    The segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents...

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  • Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje

    Publikacja
    • J. Kreft
    • M. Boguszewicz-kreft
    • B. Cyrek

    - Roczniki Nauk Społecznych - Rok 2024

    Generatywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...

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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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  • Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction

    Publikacja

    - ENVIRONMENTAL POLLUTION - Rok 2023

    Mobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...

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  • Melanoma skin cancer detection using mask-RCNN with modified GRU model

    Publikacja

    - Frontiers in Physiology - Rok 2024

    Introduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...

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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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  • Expedited Metaheuristic-Based Antenna Optimization Using EM Model Resolution Management

    Publikacja

    - Rok 2017

    Design of modern antenna systems heavily relies on numerical opti-mization methods. Their primary purpose is performance improvement by tun-ing of geometry and material parameters of the antenna under study. For relia-bility, the process has to be conducted using full-wave electromagnetic (EM) simulation models, which are associated with sizable computational expendi-tures. The problem is aggravated in the case of global optimization,...

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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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  • Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems

    Publikacja

    - Rok 2022

    In this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...

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  • International Conference on Machine Vision

    Konferencje

  • Mechatronics and Machine Vision in Practice

    Konferencje