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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe 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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Metal dusting phenomena of 501 AISI furnace tubes in refinery fractional distillation unit
PublicationThe purpose of this investigation was to conduct the failure analysis of 501 AISI furnace tubes places before distillation column in fractional distillation unit. The investigated furnace tubes were planned to work for ten years however after just two years of exploitation <30% of the material left. The observed corrosion process had the intense and complex character. The well-adhered shiny black deposits and deep, round pits were...
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Vertical Temperature Stratification of the Gulf of Gdansk Water
PublicationThe Baltic Sea is characterized by variable hydroacoustic conditions, which depend on hydrological conditions throughout the year. The temperature of the water is the factor that has the greatest impact on the changes in the speed of the sound in this basin. Even at a small depth, we can observe a large temperature gradient affecting the accuracy of the conducted research using hydroacoustic devices. A characteristic feature of...
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Propagation of Acoustic Disturbances in Shallow Sea
PublicationPropagation of acoustic waves in shallow sea differs fundamentally from the same phenomenon occurring in deep sea in view of non-negligible distance from the sea bottom in the first case, where presence of two regions limiting the water layer results in the acoustic pressure distribution induced by a harmonic source has an interferential nature as a result of multi-path propagation of the acoustic signal. These interferential properties...
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BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublicationDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublicationRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublicationRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Learning & Memory
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Adult 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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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublicationPurpose: 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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Settlement Networks in Polish Spatial Development Regional Plans
PublicationIn 1999, ten years after the great political changes in Poland, 16 self-governed regions (in Polish: voivodeship) were created. According to Polish law, voivodeship spatial development plans, or regional plans in short, determine basic elements of the settlement network. No detailed regulations indicate the specific elements of the settlement network or what features of these elements should be determined. For this reason, centres...
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Generation-recombination and 1/f noise in carbon nanotube networks
PublicationThe low-frequency noise is of special interest for carbon nanotubes devices, which are building blocks for a variety of sensors, including radio frequency and terahertz detectors. We studied noise in as-fabricated and aged carbon nanotube networks (CNNs) field-effect transistors. Contrary to the majority of previous publications, as-fabricated devices demonstrated the superposition of generation-recombination (GR) and 1/f noise...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe 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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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublicationSemantic-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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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – 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
PublicationText-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
PublicationCatheter-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...
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Integrated Control in High-Speed Networks Using Constrained Model Predictive Control
PublicationThis paper studies congestion control in high-speed communication networks using Model Predictive Control (MPC). Network traffic is assumed to consist of best-effort and priority traffic sources. An integrated controller consisting of two control parts is designed. The controller calculates the capacity for priority sources and the input rate of best-effort sources. MPC is desirable as it can take into account the constraints on...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublicationThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Comments on "Decomposition of Permutation Networks"
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Neuromorphic Binarized Polariton Networks
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Survivability issues in multilayer networks
PublicationW artykule rozważa się zagadnienia zabezpieczenia i odtwarzania w wielowarstwowych architekturach sieciowych w celu osiągnięcia określonego poziomu przeżywalności po awarii węzła lub łącza. Problem optymalizacji polega na znalezieniu dla każdej optycznej ścieżki aktywnej, przenoszącej dany strumień IP, węzłowo-rozłącznej optycznej ścieżki zabezpieczającej w taki sposób, by awaria pojedyńczego węzła lub łącza spowodowana atakiem...
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Connectivity in Multi-Interface Networks
PublicationRozważano zagadnienie minimalizacji energii w sieciach bezprzewodowych bez infrastruktury, w których niektóre węzły są wyposażone w więcej, niż jeden interfejs. W przyjętym modelu sieci podano nowe algorytmy przybliżone oraz wyniki dotyczące złożoności obliczeniowej dla problemu najtańszej spójnej podsieci spinającej.
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Monitoring objects over networks
PublicationW pracy rozważa się uniwersalny pomysł na monitorowanie obiektów przemysłowych, firmowych i prywatnych, z inteligentnymi budynkami włšcznie. Rozmaite zadania diagnostyczne, sterownicze i zarzšdcze łatwo mogš być zintegrowane w taki projekt. Współczesne narzędzia technologii informacyjnych (IT) mogš być spożytkowane w celu stworzenia kompletnych i efektywnych systemów realizujšcych takie zadania. Oparłszy się na wysokich technologiach...
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Multistage optical switching networks
PublicationEwolucja sieci szkieletowej w kierunku sieci DWDM o dużych szybkościach generuje nowe problemy dla kontynuacji. Ten element funkcjonalny musi także być oparty na technologii optycznej. Dla dużych pojemności nie może on być zrealizowany jako pojedynczy komutator, lecz jako wielosekcyjne pole komutacyjne. W artykule opisano trzy typy komutatorów: komutator światłowodów(FX), komutator długości fal (WSX) i komutator z konwersją długości...
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Reliable Networks Design and Modeling
PublicationSłowo wstępne numeru specjalnego czasopisma Telecommunication Systems Journal
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Scanning networks with cactus topology
PublicationThe family of Pursuit and Evasion problems is widelystudied because of its numerous practical applications,ranging from communication protocols to cybernetic andphysical security. Calculating the search number of a graphis one of most commonly analyzed members of this problemfamily. The search number is the smallest number of mobileagents required to capture an invisible and arbitrarily fastfugitive, for instance piece of malicious...
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VNFs reconfiguration in 5G networks
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Graph models of clos networks
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Design and modeling of reliable networks
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