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Wyniki wyszukiwania dla: LEASING PRACOWNICZY
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Application of multisensoral remote sensing data in the mapping of alkaline fens Natura 2000 habitat
PublikacjaThe Biebrza River valley (NE Poland) is distinguished by largely intact, highly natural vegetation patterns and very good conservation status of wetland ecosystems. In 20132014, studies were conducted in the upper Biebrza River basin to develop a remote sensing method for alkaline fen classification a protected Natura 2000 habitat (code 7230) using remote sensing technologies. High resolution airborne true colour (RGB) and...
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Graphene oxide, reduced graphene oxide and composite thin films NO2 sensing properties
PublikacjaA graphene oxide (GO), reduced graphene oxide (RGO) and poly(3,4-ethylenedioxytiophene)- reduced graphene oxide (PEDOT-RGO composite) gas sensors were successfully fabricated using an electrodeposition method. The electrodeposition was carried out in aqueous GO dispersions. In order to obtain RGO and PEDOT-RGO, the electrochemical reduction of GO and PEDOT-GO was carried out in 0.1 M KCl at constant potential of −0.85 V. The GO, RGO...
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Remote sensing in laboratory diagnostics of reinforced concrete elements – current development and vision for the future
PublikacjaContinuous emergence of new concrete types and kinds of reinforcement, as well as technological solutions in the field of structural engineering have made great demand for diagnostic tests of reinforced concrete elements. New challenges and problems facing people require new more efficient tools for laboratory diagnostics than those commonly used. Remote sensing may be the answer to this demand. In this paper the author describes...
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Field tests on hydrodynamic and hybrid operation of a bi-directional thrust bearing of a pump-turbine
PublikacjaIn vertical shaft pump turbines operating in pumped storage power plants an important role is played by a thrust bearing. Because of bi-directional character of operation, thrust bearing tilting pads have to be supported symmetrically, which is known to be unfavourable from the point of view of their performance. Large thrust bearings have to be carefully designed so as to minimise excessive thermo-elastic pad deformations. The...
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New trifunctional acrylic water-based paint with self-cleaning, biocidal and magnetic properties
PublikacjaIn the present study, we report the synthesis and application of ZnFe2O4/SiO2-TiO2 nanocomposites with nonstoichiometric content of Fe to Zn used for the first time for the preparation of new generation trifunctional paints with self-cleaning, biocidal and magnetic properties. Currently, there are no compositions on the market for obtaining protective coatings in the form of paint, which simultaneously exhibit biocidal, magnetic...
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Flicker Noise in Resistive Gas Sensors—Measurement Setups and Applications for Enhanced Gas Sensing
PublikacjaWe discuss the implementation challenges of gas sensing systems based on low-frequency noise measurements on chemoresistive sensors. Resistance fluctuations in various gas sensing materials, in a frequency range typically up to a few kHz, can enhance gas sensing by considering its intensity and the slope of power spectral density. The issues of low-frequency noise measurements in resistive gas sensors, specifically in two-dimensional...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric 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...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublikacjaDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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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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Consideration of Pseudo Strain Energy in Determination of Fatigue Life and Microdamage Healing of Asphalt Mastics
PublikacjaRest periods between cyclic loads can lead to recovery of damage and extension of fatigue life. This phenomenon is referred to as healing. Healing is clearly observed in bituminous materials, such as asphalt mastics, which belong to the components of asphalt mixtures. Due to the nature of road pavement traffic loading, which is characterized by series of intermittent pulses with rest periods, consideration of healing is necessary...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublikacjaAlthough 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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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublikacjaIn 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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The effect of aggregate characteristics on the fracture behaviour of fine-grained concrete under tensile loading
PublikacjaArtykuł przedstawia analizę wpływu kruszywa na zjawisko pękania drobnoziarnistego betonu podczas quasi-statycznego trzypunktowego zginania. Beton został opisany jako stochastyczny i niejednorodny materiał trzyfazowy. Dwuwymiarowe obliczenia numeryczne dla betonowych belek z nacięciem wykonano metodą elementów skończonych stosując izotropowy materiałowy model z degradacją sztywności rozszerzony o długość charakterystyczną mikrostruktury...
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Polyurethane based hybrid ciprofloxacin-releasing wound dressings designed for skin engineering purpose
PublikacjaPurpose Even in the 21st century, chronic wounds still pose a major challenge due to potentially inappropriate treatment options, so the latest wound dressings are hybrid systems that enable clinical management, such as a hybrid of hydrogels, antibiotics and polymers. These wound dressings are mainly used for chronic and complex wounds, which can easily be infected by bacteria. Materials and methods Six Composite Porous Matrices...
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublikacjaRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Transformational Leadership and Acceptance of Mistakes as a Source of Learning: Poland-USA Cross-Country Study
PublikacjaThis study explores the influence of transformational leadership on internal innovativeness mediated by mistakes acceptance, including country and industry as factors to be considered and gender and risk-taking attitude as moderators. General findings, primarily based on the US samples (healthcare, construction, and IT industry), confirmed that transformational leadership and internal innovativeness are mediated by mistakes acceptance...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Pursuing Analytically the Influence of Hearing Aid Use on Auditory Perception in Various Acoustic Situations
PublikacjaThe paper presents the development of a method for assessing auditory perception and the effectiveness of applying hearing aids for hard-of-hearing people during short-term (up to 7 days) and longer-term (up to 3 months) use. The method consists of a survey based on the APHAB questionnaire. Additional criteria such as the degree of hearing loss, technological level of hearing aids used, as well as the user experience are taken...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Experimental comparison of the transition speed of a hydrodynamic journal bearing lubricated with oil and magnetorheological fluid
PublikacjaA journal bearing test bench is used to find the transition speed between the hydrodynamic and mixed lubrication regimes for a modified magnetorheological (MR) fluid. It is shown that the transition speed of the bearing can be reduced by applying a local magnetic field near minimum film when it is lubricated with the MR fluid, and that this will only marginally increase friction. The lubricating performance of the MR fluid is compared...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Methods of deep modification of low-bearing soil for the foundation of new and spare air runways
PublikacjaAfter analyzing the impact of aircraft on the airport pavement (parking spaces, runways, startways), it was considered advisable to consider the problem of deep improvement or strengthening of its subsoil. This is especially true for low-bearing soil. The paper presents a quick and effective method of strengthening the subsoil intended for the construction of engineering structures used for civil...
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Effects of UV light irradiation on fluctuation enhanced gas sensing by carbon nanotube networks
PublikacjaThe exceptionally large active surface-to-volume ratio of carbon nanotubes makes it an appealing candidate for gas sensing applications. Here, we studied the DC and low-frequency noise characteristics of a randomly oriented network of carbon nanotubes under NO2 gas atmosphere at two different wavelengths of the UV light-emitting diodes. The UV irradiation allowed to sense lower concentrations of NO2 (at least 1 ppm) compared to...
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Overview of planar antenna loading metamaterials for gain performance enhancement: the two decades of progress
PublikacjaMetamaterials (MTMs) are artificially engineered materials with unique electromagnetic properties not occurring in natural materials. MTMs have gained considerable attention owing to their exotic electromagnetic characteristics such as negative permittivity and permeability, thereby a negative refraction index. These extraordinary properties enable many practical applications such as super-lenses, and cloaking technology, and are...
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Analysis of the Heating Process of Hydraulic Motors during Start-Up in Thermal Shock Conditions
PublikacjaConditions that prevail during harsh winters and hot summers pose a serious challenge for machine designers building devices suitable for operation in extreme weather. It is essential for the designers and the users to define the principles and conditions for the safe operation of machines and devices with hydraulic drive in low ambient temperatures. Bearing in mind the above, the author tested the hydraulic motors in thermal shock...
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A facile approach to fabricate load-bearing porous polymer scaffolds for bone tissue engineering
PublikacjaBiodegradable porous scaffolds with oriented interconnected pores and high mechanical are load-bearing biomaterials for bone tissue engineering. Herein, we report a simple, non-toxic, and cost-effective method to fabricate high-strength porous biodegradable scaffolds, composed of a polymer matrix of polycaprolactone (PCL) and water-soluble poly (ethylene oxide) (PEO) as a sacrificial material by integrating annealing treatment,...
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Regulation of LPS assembly via controlled proteolysis and sensing of LPS stress in Escherichia coli
PublikacjaLipopolysaccharide (LPS) is a complex glycolipid, essential for the bacterial viability and along with phospholipids, it constitutes the major amphiphilic component of outer membrane (OM) in most of the Gram-negative bacteria, including Escherichia coli. LPS molecules confer an effective permeability barrier to the OM and play a crucial role in bacteria-environment and -host interactions. The synthesis and accumulation of this...
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Determination of stepped plate thickness distribution using guided waves and compressed sensing approach
PublikacjaGuided waves recently have attracted significant interest as a very promising research area. The signals registered by a specially designed sensor network are processed to assess the state of the tested structure. Despite the constant development of novel damage detection algorithms employing guided waves, the phenomenon of wave propagation still needs detailed recognizing and understanding for the further progress of non-destructive...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue 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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Perception-based data processing in acoustics. Applications to music information retrieval and psychophysiology of hearing.
PublikacjaTematyka książki obejmuje w pierwszej kolejności opis mechanizmów kognitywnych leżących u podstaw percepcji muzyki. Przedstawione zostały również zagadnienia automatycznego rozpoznawania dźwięków instrumentów muzycznych i muzyki, zastosowanie nowych metod z dziedziny sztucznej inteligencji w szeroko rozumianej inżynierii dźwięku oraz komputerowych metod badania słuchu.
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The Influence of External Additional Loading on the Muscle Activity and Ground Reaction Forces during Gait
PublikacjaAsymmetrical external loading acting on the usculoskeletal system is generally considered unhealthy. Despite this knowledge, carrying loads in an asymmetrical manner like carrying on one shoulder, with one hand, or on the strap across the torso is a common practice. This study is aimed at presenting the effects of the mentioned load carrying methods on muscle activity assessed by using thermal field and ground reaction forces....
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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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...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Effect of dendrimer-based interlayers for enzyme immobilization on a model electrochemical sensing system for glutamate
PublikacjaIn this paper, we discuss dendrimer usage in enzyme-based electrochemical biosensors, particularly with respect to biomolecule loading on the sensing surface. A novel approach to design bioactive layers with immobilized enzymes for electrochemical biosensors using the surface plasmon resonance (SPR) method in combination with electrochemical impedance spectroscopy was presented. The gold surface was modified with linear linkers...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Enhancing environmental literacy through urban technology-based learning. The PULA app case
PublikacjaThis study addresses the need to enhance environmental literacy, focusing on urban adults through mobile applications, based on the example of PULA app that engages early adopters in gamified pro- environmental activities, offering insights into informal learning. Grounded in 'urban pedagogy,' the study combines semi-structured interviews with 17 application testers and quantitative data analysis, unveiling motivations, user feedback,...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs 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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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
PublikacjaThe effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...
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Perspektywy wykorzystania technologii internetowych typu E-learning w dydaktyce szkół wyższych.
PublikacjaArtykuł dotyczy nauczania przez Internet na poziomie uniwersyteckim. Zaprezentowany został model wirtualnego uniwersytetu, który obejmuje materiały dydaktyczne, komunikację, egzaminy i organizację. Artykuł koncentruje się na technicznych zagadnieniach. Przeanalizowano także wpływ wykorzystania technologii E-learning na różne aspekty życia wyższej uczelni.
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Neural network based control system architecture proposal for underwatership hull cleaning robot.
PublikacjaPrzedstawiono model matematyczny podwodnej głowicy roboczej, oraz określono metodę jej pozycjonowania i orientacji w lokalnym środowisku. Zaproponowano architekturę układu sterowania, opartego na bazie sieci neuronowych, za pomocą którego można sterować podwodnym robotem, przeznaczonym do czyszczenia burt statku.
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Spectral criterion for high-cycle fatigue of metals under multiaxial static and stochastic loading.
PublikacjaPraca dotyczy oceny zmęczenia metali ciągliwych w złożonych stanach wieloosiowych obciążeń statycznych i dynamicznych, przy założeniu, że składowe naprężenia są stacjonarnymi procesami stochastycznymi, które są stacjonarnie skorelowane i różniczkowalne w sensie średniokwadratowym. Przyjmując, że wartości średnie i gęstości widmowe mocy tych procesów są znane, sformułowano kryterium ograniczonej trwałości zmęczeniowej w dziedzinie...
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Open source learning management systems at civil engineering and environmental department: TeleCAD and Moodle.
PublikacjaW rozdziale zaprezentowano dwa systemy zarządzania kształceniem, służące do przygotowania i prowadzenia e-kursów. Pierwszy z nich TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). Ostanie użycie systemu miało miejsce w roku akademickim 2003/2004 i był on wykorzystany w projekcie CURE (V Program Ramowy, 2003-2006). W roku 2003 dzięki wsparciu projektu Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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