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

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

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

  • Introduction to the special issue on machine learning in acoustics

    Publikacja
    • Z. Michalopoulou
    • P. Gerstoft
    • B. Kostek
    • M. A. Roch

    - Journal of the Acoustical Society of America - Rok 2021

    When we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...

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  • Social Learning in Cluster Organizations and Accumulation of Technological Capability

    Publikacja

    - Inzinerine Ekonomika-Engineering Economics - Rok 2022

    The purpose of the paper is to present how members of cluster organizations perceive their role in the accumulation of technological capability through social learning. The paper presents the results of a qualitative study of four cluster organizations. The theoretical foundation of the study are the communities of practice and the organizational inertia theories. The study indicates that the dynamics of technological capability...

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  • Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers

    Publikacja
    • T. Shmelova
    • Y. Sikirda
    • N. Rizun
    • V. Lazorenko
    • V. Kharchenko

    - Rok 2020

    This chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...

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  • TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads

    TensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...

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  • Sentiment Analysis of Facebook Posts:the Uber case

    Publikacja

    - Rok 2017

    This article analyses the sentiment of opinions, i. e. its classification as phrases with a neutral, positive and negative emotional tone. Data used as a basis for the analysis were opinions expressed by Facebook users about Uber and collected in the period between July 2016 and July 2017. The primary objective of the study was to obtain information about the perceptions of Uber over thirteen consecutive months. The study confirms...

  • Speech Analytics Based on Machine Learning

    In this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...

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  • SACAM A Model for Describing and Classifying Sentiment Analysis Methods

    Publikacja

    In this paper we introduce SACAM — a model for describing and classifying sentiment analysis (SA) methods. The model focuses on the knowledge used during processing textual opinions. SACAM was designed to create informative descriptions of SA methods (or classes of SA methods) and is strongly integrated with its accompanying graphical notation suited for presenting the descriptions in diagrammatical form. The paper discusses applications...

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  • The Cultures of Knowledge Organizations: Knowledge, Learning, Collaboration (KLC)

    Publikacja

    - Rok 2023

    This book focuses on seeing, understanding, and learning to shape an organization’s essential cultures. The book is grounded on a fundamental assumption that every organization has a de facto culture. These “de facto cultures” appear at first glance to be serendipitous, vague, invisible, and unmanaged. An invisible and unrecognized de facto culture can undermine business goals and strategies and lead to business failures. The authors...

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  • How Machine Learning Contributes to Solve Acoustical Problems

    Publikacja
    • M. A. Roch
    • P. Gerstoft
    • B. Kostek
    • Z. Michalopoulou

    - Journal of the Acoustical Society of America - Rok 2021

    Machine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...

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  • Raw data of AuAg nanoalloy plasmon resonances used for machine learning method

    Raw data used for machine learning process. UV-vis measurements of AuAg alloyed nanostructures created from thin films. Plasmonic band position dependence on fabrication parameters. Small presentation reviewing achieved structures and their properties.

  • Machine Learning Techniques in Concrete Mix Design

    Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...

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  • Machine Learning in Multi-Agent Systems using Associative Arrays

    Publikacja

    - PARALLEL COMPUTING - Rok 2018

    In this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...

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  • Business Sentiment Analysis. Concept and Method for Perceived Anticipated Effort Identification

    Publikacja

    - Rok 2019

    Representing a valuable human-computer interaction interface, Sentiment Analysis (SA) is applied to a wide range of problems. In the present paper, the researchers introduce a novel concept of Business Sentiment (BS) as a measurement of a Perceived Anticipated Effort (PAE) in the context of business processes (BPs). BS is considered as an emotional component of BP task contextual complexity perceived by a process worker after reading...

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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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  • 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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  • 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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  • Examining Government-Citizen Interactions on Twitter using Visual and Sentiment Analysis

    Publikacja

    - Rok 2018

    The goal of this paper is to propose a methodology comprising a range of visualization techniques to analyze the interactions between government and citizens on the issues of public concern taking place on Twitter, mainly through the official government or ministry accounts. The methodology addresses: 1) the level of government activity in different countries and sectors; 2) the topics that are addressed through such activities;...

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  • Multimedia industrial and medical applications supported by machine learning

    Publikacja

    - Rok 2023

    This article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...

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  • Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection

    Publikacja
    • A. G. Akintola
    • A. O. Balogun
    • H. A. Mojeed
    • F. Usman-Hamza
    • S. A. Salihu
    • K. S. Adewole
    • G. B. Balogun
    • P. O. Sadiku

    - International Journal of Interactive Mobile Technologies - Rok 2022

    Due to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...

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  • Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions

    Publikacja

    - Polimery w Medycynie - Rok 2024

    Background. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...

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  • Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning

    Publikacja

    Concrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....

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  • Assessing the attractiveness of human face based on machine learning

    Publikacja

    The attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...

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  • Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines

    Publikacja

    The acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...

  • MACHINE LEARNING

    Czasopisma

    ISSN: 0885-6125 , eISSN: 1573-0565

  • MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS

    In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...

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  • MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES

    Automatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...

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  • MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG

    Publikacja
    • A. Kastrau
    • M. Koronowski
    • M. Liksza
    • P. Jasik

    - Rok 2021

    This study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...

  • An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations

    Publikacja

    - Rok 2024

    Although making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...

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  • Designing acoustic scattering elements using machine learning methods

    Publikacja

    - Rok 2021

    In the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...

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  • Concrete mix design using machine learning

    Publikacja

    Designing a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...

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  • A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings

    Publikacja

    Traffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...

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  • Predicting emotion from color present in images and video excerpts by machine learning

    Publikacja

    This work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...

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  • Explainable machine learning for diffraction patterns

    Publikacja
    • S. Nawaz
    • V. Rahmani
    • D. Pennicard
    • S. P. R. Setty
    • B. Klaudel
    • H. Graafsma

    - Journal of Applied Crystallography - Rok 2023

    Serial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...

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  • Model-Based Adaptive Machine Learning Approach in Concrete Mix Design

    Publikacja

    Concrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...

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  • Ireneusz Czarnowski Prof.

    Osoby

    IRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...

  • Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data

    Publikacja

    - Rok 2024

    This paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...

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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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  • Development and Learning in Organizations

    Czasopisma

    ISSN: 1477-7282

  • Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy

    Publikacja
    • G. V. Nguyen
    • P. Sharma
    • Ü. Ağbulut
    • H. S. Le
    • T. H. Truong
    • M. Dzida
    • M. H. Tran
    • H. C. Le
    • V. D. Tran

    - Biofuels Bioproducts & Biorefining-Biofpr - Rok 2024

    Biochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...

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  • Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning

    Publikacja

    - PLOS ONE - Rok 2022

    In this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...

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  • Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools

    Publikacja

    A high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...

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  • 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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  • Robust and Efficient Machine Learning Algorithms for Visual Recognition

    Publikacja

    - Rok 2022

    In visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...

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  • 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...

  • Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance

    Publikacja

    - Procedia Computer Science - Rok 2021

    Machine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...

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  • Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment

    The study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...

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  • Noise profiling for speech enhancement employing machine learning models

    Publikacja

    - Journal of the Acoustical Society of America - Rok 2022

    This paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...

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  • Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method

    Plasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....

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  • Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results

    Publikacja

    The continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...

  • Machine learning-based prediction of preplaced aggregate concrete characteristics

    Preplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...