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Loosely-Tied Distributed Architecture for Highly Scalable E-Learning System
PublicationVast 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...
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Informal Workplace Learning and Employee Development. Growing in the Organizational New Normal
PublicationThe 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...
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The time of the first transition of the semi-Markov process in the evaluation of diesel engine operation
PublicationW referacie przedstawiono rozwinięcie prezentowanej w literaturze metody ilościowej oceny działania na przykładzie okrętowego silnika głównego z zapłonem samoczynnym. Według tej interpretacji, działanie silnika może zostać przedstawione jako wielkość fizyczna. W tym aspekcie, na przykładzie okrętowego silnika napędu głównego dokonano oceny przydatności tej wielkości do opisu własności niezawodnościowych silnika. Precyzyjne określenie...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe 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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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublicationThe 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...
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Semi-transparent ordered TiO2 nanostructures prepared by anodization of titanium thin films deposited onto the FTO substrate
PublicationIn a significant amount of cases, the highly ordered TiO2nanotube arrays grow through anodic oxidationof a titanium metal plate immersed in electrolyte containing fluoride ions. However, for some practicalapplications, e.g. solar cells or electrochromic windows, the semi-transparent TiO2formed directly onthe transparent, conductive substrate is very much desired. This work shows that high-quality Ti coatingcould be formed at room...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Internet photogrammetry as a tool for e-learning
PublicationAlong with Internet development, there were interactive applications which allow for remote sensing and photogrammetric analysis. An example of an application that can provide Earth images and make it possible to measure distances in these images is Google Earth. The authors, who have experience from 2001-2015 argue that it is possible and it is important to create more advanced photogrammetric network applications. In this there...
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Innovative e-learning approach in teaching based on case studies - Innocase project
PublicationThe article presents the application of innovative e-learning approach for the creation of case study content. Case study methodology is becoming more and more widely applied in modern education, especially in business and management field. Although case study methodology is quite well recognized and used in education, there are still few examples of developing e-learning content on the basis of case studies. This task is to be...
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Explainable machine learning for diffraction patterns
PublicationSerial 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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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis 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,...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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A model of fuel combustion process in the marine reciprocating engine work space taking into account load and wear of crankshaft-piston assembly and the theory of semi-Markov processes
PublicationThe ar ticle analyses the operation of reciprocal internal combu stion engines, with mar ine engines u sed a s an example. The analysis takes into account types of energy conversion in the work spaces (cylinders) of these engines, loads of their crankshaft-piston assemblies, and types of fuel combustion which can take place in these spaces during engine operation. It is highlighted that the analysed time-dependent loads of marine...
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Morphology and local chain structure of polyamide 6 modified in the solid state with a semi-aromatic nylon salt
PublicationStructural and conformational differences between the polyamide 6 (PA6) homopolymer and two copolymers of PA6 modified in the solid state with 20 and 30 wt% of the semi-aromatic nylon salt of 1,5-diamino-2-methylpentane (Dytek A) and isophthalic acid (IPA) in the feed were investigated. Room temperature wide-angle X-ray diffraction (WAXD) analysis together with 13C{1H} cross-polarization/magic-angle spinning solid-state (CP/MAS)...
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Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublicationThe paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...
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Towards Scalable Simulation of Federated Learning
PublicationFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublicationPurpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...
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Semi complex navigation with an active optical gesture sensor
PublicationThis paper presents the methods of diversified touchless interactions between a user and a mobile platform utilizing the optical gesture sensor. The sensor uses 8 photodiodes to measure the reflected light in the active mode (using embedded LEDs) or it measures shadows caused by fingers in the passive mode. Several algorithms were implemented: automatic mode switching, adaptive illumination level compensation, resolution improvements...
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Semi-adaptive feedback active control of MRI noise
PublicationA feedback controller is proposed for cancellation of magnetic resonance imaging (MRI) noise. The design of the controller takes into account specific features of the MRI noise signal. Simulation results show that a considerable rejection rate of the MRI noise can be obtained.
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Semi-incremental addition of strings to a cyclic finite automaton
PublicationMaszyny o skończonej liczbie stanów są szeroko stosowane jako słowniki w przetwarzaniu języka naturalnego. Odznaczają się szybkim czasem przetwarzania i małymi wymaganiami pamięciowymi. Przedstawiamy nowy algorytm dodawania nowych słów do języka cyklicznego automatu skończonego. Algorytm jest rozszerzeniem na automaty cykliczne półprzyrostowego algorytmu Watsona dla automatów acyklicznych. Przekształcenie jest dokonane w duchu...
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Semi-Markov model of diesel engines' operating process.
PublicationNajistotniejszym problemem eksploatacji silników o zapłonie samoczynnym jest problem racjonalnego (a zwłaszcza optymalnego) sterowania procesem eksploatacji tych silników. Sterowanie takie może ułatwić zastosowanie iteracyjnego algorytmu wyznaczania optymalnych strategii opracowanego przez R.A. Howarda. Wykorzystanie jednak tego algorytmu do sterowania procesem eksploatacji silników wymaga między innymi opracowania modelu procesu...
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Incremental and Semi-Incremental Construction of Pseudo-Minimal Automata
PublicationPrzedstawione zostają modyfikacje trzech algorytmów przyrostowego i półprzyrostowego tworzenia automatów minimalnych w taki sposób, aby tworzyły automaty pseudominimalne. Istniejący od dawna algorytm Revuza tworzy takie automaty szybciej i zużywając mniej pamięci, ale wymaga kłopotliwego sortowania. Nie nadaje się też do dodawania nowych słów do automatu - ważnej czynności w realizacji dynamicznej doskonałej funkcji mieszającej....
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublicationAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublicationIn this chapter, the authors 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. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublicationContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
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Determination of rectification corrections for semi gantry crane rail axes in the local 3D coordinate system
PublicationElectronic tacheometers are currently the standard instruments used in geodetic work, including also geodetic engineering measurements. The main advantage connected with this equipment is among others high accuracy of the measurement and thus high accuracy of the final determinations represented for example by the points’ coordinates. One of many applications of the tacheometers is the measurement of crane rail axes. This measurement...
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Bandwidth-Controllable Third-Order Band Pass Filter Using Substrate Integrated Full- and Semi-Circular Cavities
PublicationThe article presents a novel circular substrate integrated waveguide (SIW) bandpass filter (BPF) with controllable bandwidth. The proposed BPF is configured using two microstrip feedlines, semi- circular SIW cavities, capacitive slots, and inductive vias. The circular cavity is bisected into two halves, with the two copies thereof being cascaded. Two bisected and cascaded structures obtained this way are subsequently connected...
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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublicationClass-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...
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Multimedia industrial and medical applications supported by machine learning
PublicationThis 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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Necessity for and possibility of application of the theory of semi-markov processes to determine reliability of diagnising systems
PublicationW opracowaniu uzasadniono konieczność określenia niezawodności systemów diagnozujących (SDG) do sformułowania diagnozy o stanie dowolnego urządzenia technicznego jako systemu diagnozowanego (SDN). Wykazano, że znajomość niezawodności SDG umożliwia określenie wiarygodności diagnozy. Przyjęto, że wiarygodność diagnozy może być określona jako właściwość diagnozy określająca stopień rozpoznania przez system diagnozujący (SDG) rzeczywistego...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe 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
PublicationThe 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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Enhancing Seismic Performance of Semi-rigid Connection Using Shape Memory Alloy Bolts Considering Nonlinear Soil–Structure Interaction
PublicationSteel Moment-Resisting Frames (SMRFs) have their lateral resistance for their rigid connections, while real conditions have shown that the rigidity of a connection depends on the bolts and the end-plate thickness, which may not provide the assumed rigidity in design process. In this research, the main goal is to enhance the semi-rigid connections using shape memory alloy (SMA) bolts and explore their effects on the seismic limit-state...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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The influence of phosphorus fractions in bottom sediments on phosphate removal in semi-natural systems as the 3rd stage of biological wastewater treatment
PublicationThe research was carried out in two semi-natural systems (the polishing ponds in Swarzewo and the free water surface constructed wetland in Zarnowiec) in Poland. They were built as the 3rd stage of a conventional mechanical–biological wastewater treatment plant. These systems were built to improve the quality of the effluent of treated wastewater. In the polishing ponds and FWS wetland system, suspended solids, organic matter as...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Study on effective front region thickness of PCM in thermal energy storage using a novel semi-theoretical model
PublicationThermal energy storage in mobile applications, particularly battery of electric vehicles, is currently gaining a lot of importance. In this paper, a semi-theoretical time-dependent mathematical model of the phase change in a double shell thermal energy storage module has been developed where the inner tube is a heat exchange surface. An effective front region thickness for the melting and solidification process has been studied....
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Ammonia amendment promotes high rate lactate production and recovery from semi-continuous food waste fermentation
PublicationIn this study, a reliable approach using ammonia nitrogen was proposed to increase lactate production during semi-continuous food waste (FW) fermentation under mesophilic conditions. Both free ammonia nitrogen (FAN) and ammonium ion (NH4+-N) were present in mesophilic reactors, with a wide FAN/NH4+-N ratio variation due to the intermittent pH control. The investigation of responsible mechanisms revealed that the increased production...
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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis chapter investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organisational culture results in better mistake management and thus better organisational learning, (2) Effective organisational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Modelling of saturated, subcooled and post-dryout flow boiling with the energy dissipation based semi-empirical model
PublicationA comprehensive semi-empirical model for saturated, subcooled and post dryout heat transfer is presented based on considerations of energy dissipation in the flow. The fundamental hypothesis in the model is the fact that heat transfer during flow boiling can be treated as a sum of two contributions constituting the total energy dissipation in the flow, namely the energy dissipation due to the shearing flow without the bubbles and...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Visually validated semi-automatic high-frequency oscillation detection aides the delineation of epileptogenic regions during intra-operative electrocorticography
PublicationOBJECTIVE: To test the utility of a novel semi-automated method for detecting, validating, and quantifying high-frequency oscillations (HFOs): ripples (80-200 Hz) and fast ripples (200-600 Hz) in intra-operative electrocorticography (ECoG) recordings. METHODS: Sixteen adult patients with temporal lobe epilepsy (TLE) had intra-operative ECoG recordings at the time of resection. The computer-annotated ECoG recordings were visually...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublicationIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublicationNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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Deep learning for ultra-fast and high precision screening of energy materials
PublicationSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublicationOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...