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Wyświetlanie 1-15 z 162
Tytuł:
Deformable cell and deformable tissue as an area for application of nanoscale mechanics
Autorzy:
Kaczmarek, J.
Powiązania:
https://bibliotekanauki.pl/articles/175397.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial muscle
deformable cell
nanoscale mechanics
Opis:
Materials undergoing deformation based on various mechanisms are frequently applied to manufacturing of artificial muscle actuators. In this paper we introduce a methodological step towards more precise determination of investigation object related to such actuators. One defines a deformable cell and a deformable tissue in order to indicate which functions of such objects should be integrated for further applications. One accentuates role of nanoscale models of mechanics of materials as important on way towards design of the deformable cells.
Źródło:
Transactions of the Institute of Fluid-Flow Machinery; 2011, 123; 99-112
0079-3205
Pojawia się w:
Transactions of the Institute of Fluid-Flow Machinery
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of a Committee of Artificial Neural Networks for the Performance Testing of Compressors for Thermal Machines in Very Reduced Times
Autorzy:
Coral, R.
Flesch, C. A.
Penz, C. A.
Borges, M. R.
Powiązania:
https://bibliotekanauki.pl/articles/221092.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
refrigeration compressor
artificial neural networks
performance test
Opis:
This paper presents a new test method able to infer - in periods of less than 7 seconds - the refrigeration capacity of a compressor used in thermal machines, which represents a time reduction of approximately 99.95% related to the standardized traditional methods. The method was developed aiming at its application on compressor manufacture lines and on 100% of the units produced. Artificial neural networks (ANNs) were used to establish a model able to infer the refrigeration capacity based on the data collected directly on the production line. The proposed method does not make use of refrigeration systems and also does not require using the compressor oil.
Źródło:
Metrology and Measurement Systems; 2015, 22, 1; 79-88
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Freezability and fertility of frozen-thawed boar semen supplemented with ostrich egg yolk lipoproteins
Autorzy:
Fraser, L.
Zasiadczyk, Ł.
Strzeżek, J.
Strzeżek, R.
Karpiesiuk, K.
Powiązania:
https://bibliotekanauki.pl/articles/2087726.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
boar
egg yolk lipoproteins
cryopreservation
artificial insemination
Źródło:
Polish Journal of Veterinary Sciences; 2018, 21, 2; 255-263
1505-1773
Pojawia się w:
Polish Journal of Veterinary Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Diatom colonization and community development in Antarctic marine waters – a short-term experiment
Autorzy:
Zidarova, Ralitsa
Ivanov, Plamen
Dzhembekova, Nina
Powiązania:
https://bibliotekanauki.pl/articles/2041801.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Antarctica
diatoms
colonization
artificial substrates
marine benthos
Źródło:
Polish Polar Research; 2020, 41, 2; 187-212
0138-0338
2081-8262
Pojawia się w:
Polish Polar Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ethical challenges of technoscience – information technologies
Etyczne wyzwania technonauki - techniki informacyjne
Autorzy:
Morawski, Roman Z.
Powiązania:
https://bibliotekanauki.pl/articles/2120312.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
technoscience
ethics
information technology
measurements
artificial intelligence
Źródło:
Nauka; 2022, 2; 7-33
1231-8515
Pojawia się w:
Nauka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Detection of Wood Boring Insects’ Larvae Based on the Acoustic Signal Analysis and the Artificial Intelligence Algorithm
Autorzy:
Bilski, P.
Bobiński, P.
Krajewski, A.
Witomski, P.
Powiązania:
https://bibliotekanauki.pl/articles/177879.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
wood boring insects identification
artificial intelligence classification
accelerometer
Opis:
The paper presents an application of signal processing and computational intelligence methods to detect presence of the wood boring insects larvae in the wooden constructions (such as the furniture of buildings). Such insects are one of the main sources of the degradation in such objects, therefore they should be detected as quickly as possible, before inflicting serious damage. The presented work involved the acoustic monitoring for detecting the presence of the larvae inside pieces of wood. An accelerometer was used to record the sound, further analyzed by a computer algorithm extracting features important for artificial-intelligence (AI) based classification employed to detect the old house borer’s (Hylotrupes bajulus L.) activity. The presented task is difficult, as the sounds made by the larvae are of relatively low amplitude and the background noise caused by people, electrical appliances or other sources may significantly degrade the accuracy of detection. The classification of sounds is needed to separate sources of noise which deteriorate the proper larva detection and should be suppressed if possible. The employed classification was based on features defined in the time domain followed by the support vector machine used as the binary classifier. The results allowed us to assess the effectiveness of the old house borer’s detection by the acoustic analysis enhanced with the AI algorithm.
Źródło:
Archives of Acoustics; 2017, 42, 1; 61-70
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Manufacturing lead time prediction for extrusion tools with the use of Neural Networks
Autorzy:
Sajko, Nika
Kovacic, Simon
Ficko, Mirko
Palcic, Iztok
Klancnik, Simon
Powiązania:
https://bibliotekanauki.pl/articles/407038.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
manufacturing lead time
Neural Network
Artificial Intelligence
extrusion
Opis:
Due to fast-paced technical development, companies are forced to modernise and update their equipment, as well as production planning methods. In the ordering process, the customer is interested not only in product specifications, but also in the manufacturing lead time by which the product will be completed. Therefore, companies strive towards setting an appealing but attainable manufacturing lead date. Manufacturing lead time depends on many different factors; therefore, it is difficult to predict. Estimation of manufacturing lead time is usually based on previous experience. In the following research, manufacturing lead time for tools for aluminium extrusion was estimated with Artificial Intelligence, more precisely, with Neural Networks. The research is based on the following input data; number of cavities, tool type, tool category, order type, number of orders in the last 3 days and tool diameter; while the only output data are the number of working days that are needed to manufacture the tool. An Artificial Neural Network (feed-forward neural network) was noted as a sufficiently accurate method and, therefore, appropriate for implementation in the company
Źródło:
Management and Production Engineering Review; 2020, 11, 3; 48-55
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Artificial Immune System Approach for Smart Air-Conditioning Control
Autorzy:
Chaczko, Z.
Aslanzadeh, S.
Kuleff, J. A.
Powiązania:
https://bibliotekanauki.pl/articles/227264.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial immune system
biologically inspired computing
evolutionary computation
Opis:
Biologically inspired computing that looks to nature and biology for inspiration is a revolutionary change to our thinking about solving complex computational problems. It looks into nature and biology for inspiration rather than conventional approaches. The Human Immune System with its complex structure and the capability of performing pattern recognition, self-learning, immune-memory, generation of diversity, noise tolerance, variability, distributed detection and optimisation - is one area that has been of strong interest and inspiration for the last decade. An air conditioning system is one example where immune principles can be applied. This paper describes new computational technique called Artificial Immune System that is based on immune principles and refined for solving engineering problems. The presented system solution applies AIS algorithms to monitor environmental variables in order to determine how best to reach the desired temperature, learn usage patterns and predict usage needs. The aim of this paper is to explore the AIS-based artificial intelligence approach and its impact on energy efficiency. It will examine, if AIS algorithms can be integrated within a Smart Air Conditioning System as well as analyse the impact of such a solution.
Źródło:
International Journal of Electronics and Telecommunications; 2012, 58, 2; 193-199
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of Artificial Neural Network: A Case of Single Point Incremental Forming (SPIF) of Cu67Zn33 Alloy
Autorzy:
Oraon, Manish
Sharma, Vinay
Powiązania:
https://bibliotekanauki.pl/articles/1841429.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
SPIF
input variable
artificial neural network
surface roughness
Opis:
Artificial neural network (ANN), a Computational tool that is frequently applied in the modeling and simulation of manufacturing processes. The emerging forming technique of sheet metal which is typically called single point incremental forming (SPIF) comes into the map and the research interest towards its technological parameters. The surface quality of the end product is a major issue in SPIF, which is more critical with the hard metals. The part of the brass metal is demanded in many industrial uses because of its high load-carrying capacity and its wear resistance property. Considering the industrial interest and demand of the brass metal products, the present study is done with the SPIF experiment on calamine brass Cu67Zn33 followed by an ANN analysis for predicting the absolute surface roughness. The modeling result shows a close agreement with the measured data. The minimum and maximum errors are found in experiment 3 and experiment 7 respectively. The error of predicted roughness is found in the range of –30.87 to 20.23 and the overall coefficient of performance of ANN modeling is 0.947 which is quite acceptable.
Źródło:
Management and Production Engineering Review; 2021, 12, 1; 17-23
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method for evaluation of transformer drying process using transfer function analysis and artificial neural network
Autorzy:
Firoozi, H.
Bigdeli, M.
Powiązania:
https://bibliotekanauki.pl/articles/141196.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
transformer
drying process
transfer function
artificial neural network
Opis:
Since a few years ago, there is an increasing interest for utilization of transfer functions (TF) as a reliable method for diagnosing of mechanical faults in transformer structure. However, this paper aims to develop the application of TF method in order to evaluate the drying quality of active part during the manufacturing process of transformer. To reach this goal, the required measurements are carried out on 50 MVA 132 KV/33 KV power transformer when active part is placed in the drying chamber. Two different features extracted from the measured TFs are then used as the inputs to artificial neural network (ANN) to give an estimate for required time in drying process. Results show that this new represented method could well forecast the required time. The results obtained from this method are valid for all the transformers which have the same design.
Źródło:
Archives of Electrical Engineering; 2013, 62, 1; 153-162
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial life forms: the strains of the future?
Autorzy:
Rajalingham, K.
Powiązania:
https://bibliotekanauki.pl/articles/80989.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
life form
artificial life
synthetic biology
biotechnology
future
Źródło:
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology; 2015, 96, 3
0860-7796
Pojawia się w:
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of adsorption efficiencies of Ni (II) in aqueous solutions with perlite via artificial neural networks
Autorzy:
Turp, S. M.
Powiązania:
https://bibliotekanauki.pl/articles/204724.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
wastewater
treatment efficiency
adsorption
perlite
artificial neural network
Opis:
This study investigates the estimated adsorption efficiency of artificial Nickel (II) ions with perlite in an aqueous solution using artificial neural networks, based on 140 experimental data sets. Prediction using artificial neural networks is performed by enhancing the adsorption efficiency with the use of Nickel (II) ions, with the initial concentrations ranging from 0.1 mg/L to 10 mg/L, the adsorbent dosage ranging from 0.1 mg to 2 mg, and the varying time of effect ranging from 5 to 30 mins. This study presents an artificial neural network that predicts the adsorption efficiency of Nickel (II) ions with perlite. The best algorithm is determined as a quasi-Newton back-propagation algorithm. The performance of the artificial neural network is determined by coefficient determination (R2), and its architecture is 3-12-1. The prediction shows that there is an outstanding relationship between the experimental data and the predicted values.
Źródło:
Archives of Environmental Protection; 2017, 43, 4; 26-32
2083-4772
2083-4810
Pojawia się w:
Archives of Environmental Protection
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial Life. Biologically-inspired algorithms
Autorzy:
Komosiński, Maciej
Powiązania:
https://bibliotekanauki.pl/articles/703205.pdf
Data publikacji:
2008
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial life
simulation
biologically-inspired algorithms
evolution
computing
Opis:
This article presents Artificial Life, an interdisciplinary field of study that helps understand life on Earth (life as we know it) and other, possible kinds of life (as it could be). Artificial Life research builds models of life and synthesizes related phenomena and processes in all currently available media – software, hardware and wetware. The first part of this work focuses on Artificial Life as a research field. In the second part, three exemplary computer science algorithms are shown that are inspired by biological processes. These are evolutionary and coevolutionary algorithms, swarm intelligence and ant algorithms, and artificial immune systems. The final part of this work provides a number of reflections on the goals of Artificial Life research, human nature and limitations, and our problems with evaluating complex outcomes of digital life experimentation.
Źródło:
Nauka; 2008, 4
1231-8515
Pojawia się w:
Nauka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of a thin-walled element geometry using a system integrating neural networks and finite element method
Autorzy:
Golewski, P.
Gajewski, J.
Sadowski, T.
Powiązania:
https://bibliotekanauki.pl/articles/351314.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial neural networks
numerical modelling
thin-walled element
Opis:
Artificial neural networks [ANNs] are an effective method for predicting and classifying variables. This article presents the application of an integrated system based on artificial neural networks and calculations by the finite element method [FEM] for the optimization of geometry of a thin-walled element of an air structure. To ensure optimal structure, the structure’s geometry was modified by creating side holes and ribs, also with holes. The main criterion of optimization was to reduce the structure’s weight at the lowest possible deformation of the tested object. The numerical tests concerned a fragment of an elevator used in the “Bryza” aircraft. The tests were conducted for networks with radial basis functions [RBF] and multilayer perceptrons [MLP]. The calculations described in the paper are an attempt at testing the FEM - ANN system with respect to design optimization.
Źródło:
Archives of Metallurgy and Materials; 2017, 62, 1; 435-442
1733-3490
Pojawia się w:
Archives of Metallurgy and Materials
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Automation of Information Security Risk Assessment
Autorzy:
Akhmetov, Berik
Lakhno, Valerii
Chubaievskyi, Vitalyi
Kaminskyi, Serhii
Adilzhanova, Saltanat
Ydyryshbayeva, Moldir
Powiązania:
https://bibliotekanauki.pl/articles/2124744.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
information security
audit
Bayesian network
artificial neural networks
Opis:
An information security audit method (ISA) for a distributed computer network (DCN) of an informatization object (OBI) has been developed. Proposed method is based on the ISA procedures automation by using Bayesian networks (BN) and artificial neural networks (ANN) to assess the risks. It was shown that such a combination of BN and ANN makes it possible to quickly determine the actual risks for OBI information security (IS). At the same time, data from sensors of various hardware and software information security means (ISM) in the OBI DCS segments are used as the initial information. It was shown that the automation of ISA procedures based on the use of BN and ANN allows the DCN IS administrator to respond dynamically to threats in a real time manner, to promptly select effective countermeasures to protect the DCS.
Źródło:
International Journal of Electronics and Telecommunications; 2022, 68, 3; 549--555
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 162

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