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Wyniki wyszukiwania dla: DEEP LEARNING, ROBOTICS
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublikacjaThe 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...
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Paladyn, Journal of Behavioral Robotics
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Journal of Micro-Bio Robotics
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International Journal of Imaging & Robotics
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International Journal of Robotics Applications
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IEEE Robotics and Automation Letters
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International Journal of Social Robotics
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IEEE ROBOTICS & AUTOMATION MAGAZINE
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INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
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IET Cyber-systems and Robotics
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Journal of Robotics and Control (JRC)
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Journal of Medical Robotics Research
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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
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INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION
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International Journal of Humanoid Robotics
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Natural Deep Eutectic Solvents as Agents for Improving Solubility, Stability and Delivery of Curcumin
PublikacjaPurpose Study on curcumin dissolved in natural deep eutectic solvents (NADES) was aimed at exploiting their beneficial properties as drug carriers. Methods The concentration of dissolved curcumin in NADES was measured. Simulated gastrointestinal fluids were used to determine the concentration of curcumin and quantum chemistry computations were performed for clarifying the origin of curcumin solubility enhancement in NADES. Results NADES...
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Deep eutectic solvents – A new platform in membrane fabrication and membrane-assisted technologies
PublikacjaDeep eutectic solvents (DESs) are a new class of solvents that can offset some of the primary drawbacks of typical solvents and ionic liquids (ILs). Since DESs fall into the guidelines of “Twelve Principles of Green Chemistry”, their implementation in several types of applications has exponentially increased over the last years. The usage of DESs has been directed to the designing, manufacture and purification of new materials...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-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...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-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 strengths...
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Learning & Memory
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Adult Learning
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Open Learning
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For the Learning of Mathematics
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Teaching & Learning
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Vocations and Learning
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LEARNing Landscapes
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Action Learning
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Support for Learning
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E-Learning
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Ubiquitous Learning
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Learning Disabilities
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Online Learning
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LEARNING & MEMORY
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MACHINE LEARNING
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LEARNING & BEHAVIOR
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LANGUAGE LEARNING
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Learning and Instruction
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MANAGEMENT LEARNING
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LEARNING AND MOTIVATION
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Metacognition and Learning
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublikacjaWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublikacjaPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublikacjaThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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New Carvone-Based Deep Eutectic Solvents for Siloxanes Capture from Biogas
PublikacjaDuring biogas combustion, siloxanes form deposits of SiO2 on engine components, thus shortening the lifespan of the installation. Therefore, the development of new methods for the purification of biogas is receiving increasing attention. One of the most effective methods is physical absorption with the use of appropriate solvents. According to the principles of green engineering, solvents should be biodegradable, non-toxic, and...
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublikacjaSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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Quenching of bright and dark excitons via deep states in the presence of SRH recombination in 2D monolayer materials
PublikacjaTwo-dimensional (2D) monolayer materials are interesting systems due to an existence of optically non-active dark excitonic states. In this work, we formulate a theoretical model of an excitonic Auger process which can occur together with the trap-assisted recombination in such 2D structures. The interactions of intravalley excitons (bright and spin-dark ones) and intervalley excitons (momentum-dark ones) with deep states located...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublikacjaPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublikacjaText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...