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Search results for: deep learning, robotics

  • THE METHODS OF TEACHING / LEARNING STRUCTURAL MECHANICS

    Publication

    - Year 2024

    Structural mechanics is a key issue to study for engineers. A high rank and high social responsibility profession requires both a high graded and intuitive approach. The evolution of learning / teaching methodology follows the novel technical achievements of every decade. The aim remains the same: to produce a professional to perform advanced relevant analysis and safe, optimal structural design

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  • Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence

    Publication

    This research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...

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  • Computer-assisted assessment of learning outcomes in the laboratory of metrology

    Publication

    - Year 2015

    In the paper, didactic experience with broad and rapid continuous assessment of students’ knowledge, skills and competencies in the Laboratory of Metrology, which is an example of utilisation of assessment for learning, is presented. A learning management system was designed for manage, tracking, reporting of learning program and assessing learning outcomes. It has ability to provide with immediate feedback, which is used by the...

  • How Machine Learning Contributes to Solve Acoustical Problems

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

    - Journal of the Acoustical Society of America - Year 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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  • Machine Learning in Multi-Agent Systems using Associative Arrays

    Publication

    - PARALLEL COMPUTING - Year 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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  • Hydrophobic deep eutectic solvents in microextraction techniques–A review

    Over the past decade, deep eutectic solvents (DES) have been widely studied and applied in sample preparation techniques. Until recently, most of the synthesized DES were hydrophilic, which prevented their use in the extraction of aqueous samples. However, after 2015 studies on the synthesis and application of hydrophobic deep eutectic solvents (HDES) has rapidly expanded. Due to unique properties of HDES i.e. density, viscosity,...

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  • Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic

    Publication

    - Studies in Logic, Grammar and Rhetoric - Year 2021

    The national curricula of the EU member states are structured around learning outcomes, selected according to Bloom’s Taxonomy. The authors of this paper claim that using Bloom’s Taxonomy to phrase learning outcomes in medical education in terms of students’ achievements is difficult and unclear. This paper presents an efficient method of assessing course learning outcomes using Fuzzy Logic.

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  • A novel architecture for e-learning knowledge assessment systems

    Publication

    In this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge assessment products....

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  • A novel architecture for e-learning knowledge assessment systems

    Publication

    In this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge assessment products....

  • Social Learning in Cluster Organizations and Accumulation of Technological Capability

    Publication

    - Inzinerine Ekonomika-Engineering Economics - Year 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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  • Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model

    Publication

    This work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...

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  • Ionic Liquids and Deep Eutectic Mixtures: Sustainable Solvents for Extraction Processes

    Publication

    - CHEMSUSCHEM - Year 2014

    In recent years, ionic liquids and deep eutectic mixtures have demonstrated great potential in extraction processes relevant to several scientific and technological activities. This review focuses on the applicability of these sustainable solvents in a variety of extraction techniques, including but not limited to liquid- and solid-phase (micro) extraction, microwave-assisted extraction, ultrasound-assisted extraction and pressurized...

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  • Machine Learning Techniques in Concrete Mix Design

    Publication

    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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  • Introduction to the special issue on machine learning in acoustics

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

    - Journal of the Acoustical Society of America - Year 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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  • Deep Eutectic Solvents: Properties and Applications in CO2 Separation

    Nowadays, many researchers are focused on finding a solution to the problem of global warming. Carbon dioxide is considered to be responsible for the “greenhouse” effect. The largest global emission of industrial CO2 comes from fossil fuel combustion, which makes power plants the perfect point source targets for immediate CO2 emission reductions. A state-of-the-art method for capturing carbon dioxide is chemical absorption using...

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  • Fusion-based Representation Learning Model for Multimode User-generated Social Network Content

    As mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...

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  • Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks

    Estimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...

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  • An application of blended and collaborative learning in spatial planning course

    Publication

    Spatial Planning is a master course for graduate students of Environmental Engineering. The course is based on assumptions that students’ future work will be connected with spatial planning, and spatial issues will have an influence on their everyday lives. To familiarize students with environmental issues in planning, the teams of students get an assignment to design an urban space, waterfront along a stream. The whole project...

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  • Collaborative Data Acquisition and Learning Support

    With the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...

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

    Publication

    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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  • Employing Blended E-Learning to Improve Rate of Assignments Handing-In

    Publication

    - Year 2011

    It has been observed that students hand in homework assignments at a notably low rate in introductory C programming course. A survey has revealed that the real issue was not student learning but instructor work organization. Based on survey results, the physical course has been complemented with an e-learning component to guide the homework process. Assignment handing-in rate significantly improved, as e-learning allowed the homework...

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  • Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2019

    This work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...

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  • Enterprise Gamification - Learning as a Side Effect of Competition

    Publication

    - Year 2017

    Gmification in companies can be used for driving desired employees behaviour that are advantageous to their development and performance improvement. This paper presents tools acquired from online social networking services and game mechanisms to encourage managers to compete by providing extended statistics and user profiles features in e-learning system.

  • Are deep eutectic solvents useful in chromatography? A short review

    Publication

    A literature update has been done concerning Deep Eutectic Solvents (DES) use in chromatography applications. The literature survey was based on the period from 2010 till 2020 and manuscripts reported in the data bases Web of Science and Scopus. The use of DES as mobile phase and mobile phase additives, stationary phases and solid phase modifiers and the use of DES as reaction solvents for chromatography use, were evaluated. Emphasis...

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  • Application of deep eutectic solvents (DES) in analytical chemistry

    Recent years have been associated with efforts to reduce the impact on the natural environment. A greener approach has been introduced in various areas of science, including analytical chemistry. One of the basic procedures for preparing a sample for analysis is its extraction. Traditional methods involve the use of large amounts of organic compounds, often toxic, with an unfavorable impact on the environment. A representative...

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  • The role of water in deep eutectic solvent-base extraction

    Publication

    - JOURNAL OF MOLECULAR LIQUIDS - Year 2020

    Deep eutectic solvents (DESs) are currently being used in different sectors, such as electrochemistry, electrodeposition, organic synthesis, nanoparticle preparation, bioactive compound separation, etc. Their use in analytical chemistry has only recently begun to expand. Despite the publication of a sufficient number of DES-based analytical extraction procedures, some details, such as interaction of DESwith the sample and target...

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  • Remarks on use of the term “deep eutectic solvent” in analytical chemistry

    Publication

    About 20 years ago, Abbott and co-workers researched new solvents that were based on mixtures of choline chloride with urea and carboxylic acids and that were liquid at ambient temperature. The term “deep eutectic solvent” (DES) was later adopted for similar mixtures. As DESs have a number of interesting features, they quickly attracted the attention of researchers and found application in various branches of chemical and materials...

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  • Machine Learning and Electronic Noses for Medical Diagnostics

    Publication

    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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  • A novel architecture for e-learning knowledge assessment systems

    Publication

    Abstract. In this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture,while well suited for didactic content distribution systems is ill-suited for knowledge assessment...

  • Active Learning Based on Crowdsourced Data

    The paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...

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  • COLLABORATIVE LEARNING ENVIRONMENT FOR ENGINEERING EDUCATION (COLED)

    Publication

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

    Publication

    The paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...

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  • Outlier detection method by using deep neural networks

    Publication

    - Year 2017

    Detecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....

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  • Learning from Mistakes. A Study on Maturity and Adaptability to Change

    Publication

    - Year 2020

    Learning culture matters; company culture must support continuous improvement. Organizational learning is a process of identifying and modifying mistakes that result from interactions between co-workers. The article aims to explore the learning power via errors, using the level of organizational maturity as a moderator. Companies need to know how organizational maturity may moderate the adaptability to change via the acceptance...

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  • Assessment of student language skills in an e-learning environment

    Publication

    This article presents the role of various assessment structures that can be used in a VLE. e-Learning language courses offer tutors a wide range of traditional and computer-generated formative and summative assessment procedures and tools. They help to evaluate each student’s progress, monitor their activities and provide varied support, which comes from the tutor, the course structure and materials as well as other participants....

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  • Novel “acid tuned” deep eutectic solvents based on protonated L-proline

    Publication

    The paper presents new types of deep eutectic solvents (DESs) based on L-proline protonated using three different acids (hydrochloric, sulfuric and phosphoric)and playing the role of a hydrogen bond acceptor(HBA). Glucose and xylitol were used as hydrogen bond donors (HBD). A series of deep eutectic solvents with various mole ratios were obtained for the systems L-proline: glucose and L-proline: xylitol. Density, melting point,...

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  • Deep eutectic solvents vs ionic liquids: Similarities and differences

    Publication

    - MICROCHEMICAL JOURNAL - Year 2020

    Deep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The...

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  • Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers

    The process of organizational learning and proper knowledge management became today one of the major challenges for the organization acting in the knowledge-based economy. According to the observations of the authors of this paper the demand for formalization of knowledge management processes and organizational learning is particularly evident in research institutions, established either by the universities, or the companies. The...

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

    Publication

    - Year 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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  • Force transfer and stress distribution in short cantilever deep beams loaded throughout the depth with a various reinforcement

    Publication

    Deep beams used as the main reinforced concrete structural elements which taking over the load and stiffening construction are often found in high-rise buildings. The architecture of these buildings is sometimes sophisticated and varied, arouse the admiration of the majority of recipients, and thus causing an engineering challenge to correctly design the structural system and force transfer. In such structures is important to shape...

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  • Application of deep eutectic solvents in atomic absorption spectrometry

    Publication

    - TRAC-TRENDS IN ANALYTICAL CHEMISTRY - Year 2022

    Atomic absorption spectrometry (AAS) is a widely applied technique for metal quantification due to its practicality, easy use and low cost. However, to improve the metrological characteristics of AAS, in particular the sensitivity and the detection limit, sample pretreatment is commonly used before the detection step itself. In consideration of the principles of Green Analytical Chemistry, new solvents are being introduced into...

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  • Social media for e-learning of citizens in smart city

    Publication

    - Year 2018

    The rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...

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  • Evaluation of ChatGPT Applicability to Learning Quantum Physics

    Publication

    - Year 2023

    ChatGPT is an application that uses a large language model. Its purpose is to generate answers to various questions as well as provide information, help solve problems and participate in conversations on a wide range of topics. This application is also widely used by students for the purposes of learning or cheating (e.g., writing essays or programming codes). Therefore, in this contribution, we evaluate the ability of ChatGPT...

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  • Loosely-Tied Distributed Architecture for Highly Scalable E-Learning System

    Publication

    Vast majority of modern e-learning products are based on client-server architecture and utilization of web-based technologies (WBT). Such approach permits easy creation of e-learning systems that do not require a complex, operating system dependant client software. Unfortunately there are also drawbacks of such solution. Because of the majority of mechanisms are located on the server, its usage levels trend to build up quickly...

  • Informal Workplace Learning and Employee Development. Growing in the Organizational New Normal

    Publication

    - Year 2024

    The new paradigm in employee development assumes that employees should proactively direct their learning and growth. Most workplace learning is basically informal and occurs through daily work routines, peer-to-peer interactions, networking, and typically brings about significant positive outcomes to both individuals and organizations. Yet, workplace learning always occurs in a pre-defined context and this context has recently...

  • SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM

    The main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...

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  • Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits

    Publication

    The Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...

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  • Deep neural network architecture search using network morphism

    Publication

    The paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...

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  • Challenges and Possibilities of Deep Eutectic Solvent-Based Membranes

    Publication
    • R. Cabezas
    • E. Zurob
    • B. Gomez
    • G. Merlet
    • A. Plaza
    • C. Araya-Lopez
    • J. Romero
    • F. Olea
    • E. Quijada-Maldonado
    • L. Pino-Soto... and 2 others

    - INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH - Year 2022

    Deep eutectic solvents (DES) are a category of a new class of solvents that can overcome some of the main drawbacks of typical solvents and ionic liquids (ILs). DES have been widely investigated and applied by the research community in several applications since their invention. Over the past years, the use of DES has been directed to the production of new materials and items for new products and processes. This is the case for...

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  • Sorbents modified by deep eutectic solvents in microextraction techniques

    In recent years, considerable attention has been directed towards the employment of green solvents, specifically deep eutectic solvents (DES), in liquid phase microextraction techniques. However, comprehensive and organized knowledge regarding the modification of sorbent surface structures with DES remains limited. Therefore, this paper reviews the application of DES in modifying and improving the properties of sorbents for microextraction...

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