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Search results for: LIFE-LONG LEARNING
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Effect of Long-Term Potato Starch Retention with Citric Acid on Its Properties
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Durability of snow cover and its long-term variability in the Western Sudetes Mountains
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Long-term air temperature variation in the Karkonosze mountains according to atmospheric circulation
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Reverse splits in international stock markets: Reconciling the evidence on long-term returns
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Long chain polyunsaturated fatty acids in smoked Atlantic mackerel and Baltic sprats
PublicationWyniki pracy wykazały, że zmienność w składzie kwasów tłuszczowych w surowcu, (makrela, szprot), pochodzącym z różnych dostaw, była większa niż zmiany wywołane wędzeniem i przechowywaniem wędzonego produktu.
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The phenomenon of HbA1c stability and the risk of hypoglycemia in long-standing type 1 diabetes
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Local and long range potentials for heparin‐protein systems for coarse‐grained simulations
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Long-Term Outcomes of Laparoscopic Sleeve Gastrectomy—a Single-Center, Retrospective Study
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Long-term simulation of the activated sludge process at the Hanover-Gümmerwald pilot WWTP
PublicationCelem badań było uzyskanie zweryfikowanego modelu ASM3P, który mógłby być wykorzystany jako narzędzie decyzyjne do wyznaczania maksymalnych przepływów w oczyszczalniach ścieków. Symulacje przeprowadzono w oparciu o wyniki badań obciążeń hydraulicznych w pilotowej oczyszczalni ścieków Hanower-Gummerwald. Wyniki symulacji zostały porównane z wynikami pomiarów on-line w komorach osadu czynnego (N-NH4, N-NO3) oraz w odpływie z osadnika...
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Long-term researches of stress corrosion cracking of Al-Zn-Mg alloys
PublicationPraca przedstawia wyniki odporności na korozję naprężeniową stopów Al-Zn-Mg uzyskane w warunkach stacjonarnych. Dodatkowo określono wpływ składu chemicznego oraz obróbki cieplnej na odporność korozyjną tych stopów. Badania prowadzono w 3% NaCl w warunkach stałego obciążenia σ = 0.8R0.2 przez 1500 godzin. Stwierdzono, iż zawartość Zn i Mg oraz szybkość chłodzenia to główne czynniki wpływające na podatność tych stopów na korozje...
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LONG RANGE PLANNING
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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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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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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How does the Relationship Between the Mistakes Acceptance Component of Learning Culture and Tacit Knowledge-Sharing Drive Organizational Agility? Risk as a Moderator
PublicationChanges in the business context create the need to adjust organizational knowledge to new contexts to enable the organizational agile responses to secure competitiveness. Tacit knowledge is strongly contextual. This study is based on the assumption that business context determines tacit knowledge creation and acquisition, and thanks to this, the tacit knowledge-sharing processes support agility. Therefore, this study aims to expose...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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The role of purpose in life and social support in reducing the risk of workaholism among women in Poland
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The role of purpose in life and social support in reducing the risk of workaholism among women in Poland
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Multiaxial fatigue life assessment in notched components based on the effective strain energy density
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Brain Fog and Quality of Life at Work in Non-Hospitalized Patients after COVID-19
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Economic Aspects of Algae Biomass Harvesting for Industrial Purposes. The Life-Cycle Assessment of the Product
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Blood plasma protein and lipid profile changes in calves during the first week of life
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Aquaporin 2: Identification and analysis of expression in calves’ urine during their first month of life
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Dietary Habits Among Young Triathlonists as a Result of Proecological Style of Life - Preliminary Study
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Mutual Relationship Between Sleep Disorders, Quality of Life and Psychosocial Aspects in Patients With Psoriasis
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Effects of traumatic life events, cognitive biases and variation in dopaminergic genes on psychosis proneness
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Physical activity, life satisfaction and adjustment to illness in women after treatment of breast cancer
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Tool Life and Process Dynamics in High Speed Ball End Milling of Hardened Steel
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Life Cycle Analysis of Ecological Impacts of an Offshore and a Land-Based Wind Power Plant
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Comparison Analysis of Blade Life Cycles of Land-Based and Offshore Wind Power Plants
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New Life of an Old Drug: Caffeine as a Modulator of Antibacterial Activity of Commonly Used Antibiotics
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Self-esteem, readiness for self-improvement and life satisfaction in Indian and Polish female students
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Fracture surface topography investigation and fatigue life assessment of notched austenitic steel specimens
PublicationThe objectives of this study were to investigate the fracture surface topography of X8CrNiS18-9 austenitic stainless-steel specimens for different loadings and notch radii and to supplement the knowledge about the fracture mechanisms for fatigue performance. Cases with three different values of the notch radius ρ and the stress amplitude σa were analysed. The fracture topographies were quantified by the areas over their entire...
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Prediction of corrosion fatigue crack propagation life for welded joints under cathodic potentials
PublicationPrzy ochronie katodowej poniżej potencjału optymalnego obserwuje się przyspieszenie propagacji pęknięcia korozyjno-zmęczeniowego w porównaniu do konstrukcji nie chronionej. Zaproponowano własną formułę empiryczną na wpływ potencjału ochronnego na prędkość propagacji pęknięcia oraz własny wzór na [delta]K w złączu pachwinowym. Wyprowadzono wzór na krzywą ''S-Np'' (naprężenie - długość okresu propagacji pęknięcia). Zaprezentowana...
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Fatigue ''safe-life'' criterion for metal elements under multiaxial constant and periodic loads.
PublicationRozpatrywane jest okresowe naprężenie którego kartezjańskie składowe są zadane w postaci szeregów Fouriera. Dla uwzględnienia naprężenia średniego wykorzystano uogólnioną formułę Soderberga dla materiałów ciągliwych. Zdefiniowano naprężenie równoważne o synchronicznych składowych i sformułowano kryterium zmęczenia, które obejmuje warunki zarówno wytrzymałości statycznej jak i bezpieczeństwa zmęczeniowego. Kryterium to zawiera stałe...
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The efficiency and technological reliability of biogenic compounds removal during long-term operation of a one-stage subsurface horizontal flow constructed wetland
PublicationThe paper presents the results of a study of the efficiency and technological reliability of total nitrogen and total phosphorus removal during long term operation of a one-stage constructed wetland system with subsurface horizontal wastewater flow. The flow rate of the wastewater treatment plant was 1.2m3/d during the research period. Physical and chemical analyses of raw wastewater and treated effluent were carried out in the...
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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublicationConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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Becoming a Learning Organization Through Dynamic Business Process Management
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Deep learning-based waste detection in natural and urban environments
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Scheduling Repetitive Construction Processes Using the Learning-Forgetting Theory
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Generation of microbial colonies dataset with deep learning style transfer
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Meta-Design and the Triple Learning Organization in Architectural Design Process
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