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Tytuł:
Exchange Rates: Predictable but not Explainable? Data Mining with Leading Indicators and Technical Trading Rules
Możliwości modelowania i prognozowania kursów walutowych: wskaźniki wyprzedzające i analiza techniczna
Autorzy:
Brandl, Bernd
Powiązania:
https://bibliotekanauki.pl/articles/907593.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
exchange rates
data mining
artificial neural networks
genetic algorithms
Opis:
This paper presents a data mining approach to forecasting exchange rates. It is assumed that exchange rates are determined by both fundamental and technical factors. The balance of fundamental and technical factors varies for each exchange rate and frequency. It is difficult for forecasters to establish the relative relevance of different kinds of factors given this mixture; therefore the utilization of data mining algorithms is advantageous. The approach applied uses a genetic algorithm and neural networks. Out-of-sample forecasting results are illustrated for five exchange rates on different frequencies and it is shown that data mining is able to produce forecasts that perform well.
W artykule przedstawiono proces eksploracji danych statystycznych w prognozowaniu kursów walutowych. Zakładamy, że kursy walutowe pozostają pod wpływem zarówno czynników o charakterze fundamentalnym, jak i czynników pozaekonomicznych. Równowaga pomiędzy tymi czynnikami różni się w zależności od rodzaju kursu walutowego i częstotliwości jego pomiaru. Prognostykom trudno jest ustalić względną siłę wpływu różnych czynników, stąd analiza polegająca na eksploracji danych ma określone zalety. W proponowanym podejściu wykorzystano algorytmy genetyczne i sztuczne sieci neuronowe. Przedstawiliśmy wyniki eksperymentów prognostycznych poza próbą statystyczną w odniesieniu do pięciu kursów walutowych, obserwowanych z różną częstotliwością. Pokazaliśmy, że metoda eksploracji danych może stanowić skuteczne narzędzie prognostyczne.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2005, 192
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy modelling as a way of estimating the exploitation parameters
Modelowanie rozmyte wartości parametrów eksploatacyjnych
Autorzy:
Pająk, M.
Kalotka, J.
Powiązania:
https://bibliotekanauki.pl/articles/258276.pdf
Data publikacji:
2006
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Technologii Eksploatacji - Państwowy Instytut Badawczy
Tematy:
modelowanie rozmyte
algorytmy genetyczne
analiza rozmyta
duże systemy przemysłowe
modelowanie lingwistyczne
fuzzy model
genetic algorithm
fuzzy statistic
data analysis
large-scale system
linguistic modeling
Opis:
To carry out the exploitation process in the proper way, it is necessary to know the values of the exploitation parameters for each moment of the process. It is especially important for large industrial objects. A lot of exploitation parameters are measured on-line, but some of them should be calculated. There are situations when the input information for the calculations are included in the measured data, but its form is entangled. In this paper a fuzzy modelling is proposed as a solution of the described problem. As an example, a fuzzy model of the temperature difference in a condenser of 13K215 steam turbine is considered.
Do poprawnego sterowania procesem eksploatacji niezbędna jest znajomość wartości parametrów eksploatacyjnych w każdy momencie procesu. Jest to szczególnie istotne w przypadku dużych obiektów przemysłowych. Większość parametrów jest mierzona w sposób ciągły. Występują jednak parametry, które są wielkościami wyliczalnymi. Wartości parametrów wyliczalnych określane są na podstawie wielkości mierzonych. Nie zawsze jednak parametry wejściowe do obliczeń są zawarte w wartościach mierzonych w formie jawnej. W opracowaniu zaprezentowana została metoda modelowania rozmytego pozwalająca na stworzenie modelu procesu w przypadku, gdy dane wejściowe dostarczone są w postaci uwikłanej. Jako przykład zastosowania metody przedstawiony został sposób opracowania modelu rozmytego spiętrzenia temperatury w skraplaczu turbiny parowej 13K215.
Źródło:
Problemy Eksploatacji; 2006, 2; 215-229
1232-9312
Pojawia się w:
Problemy Eksploatacji
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy modelling of temperature difference in 200 MW power unit condenser using genetic fuzzy systems
Autorzy:
Pająk, M.
Powiązania:
https://bibliotekanauki.pl/articles/970605.pdf
Data publikacji:
2008
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
learning
fuzzy models
genetic algorithms
fuzzy statistics and data analysis
large-scale systems
linguistic modelling
Opis:
Energy generation is one of the most complicated industrial processes. Because of its complexity, there is no accurate conventional model of a power unit. Fuzzy logic concepts might be effectively implemented in this field. In the paper a universal method of creating a fuzzy logic model is presented. To check the usefulness of the method in the case of real industrial issues, a fuzzy model of temperature difference in a condenser was automatically generated. The modelling experiment and the assessment of model quality are presented in the paper.
Źródło:
Control and Cybernetics; 2008, 37, 3; 565-583
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Measurement data in genetic fuzzy modelling of dynamic systems
Dane pomiarowe w genetyczno-rozmytym modelowaniu systemów dynamicznych
Autorzy:
Gorzałczany, M. B.
Rudziński, F.
Powiązania:
https://bibliotekanauki.pl/articles/153292.pdf
Data publikacji:
2010
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
inteligencja obliczeniowa
systemy rozmyte
algorytmy genetyczne
systemy genetyczno-rozmyte
dane pomiarowe
computational intelligence
fuzzy systems
genetic algorithms
genetic fuzzy systems
measurement data
Opis:
The paper presents a genetic fuzzy rule-based approach to the modelling of complex dynamic systems and processes using measurement data that describe their behaviour. The application of the proposed technique to modelling an industrial gas furnace system (the so-called Box-Jenkins benchmark) using measurement data available from the repository at the University of Wisconsin at Madison (http://www.stat.wisc.edu/~reinsel/ bjr-data) is also presented in the paper.
Artykuł prezentuje podejście genetyczno-rozmyte do modelowania (z wykorzystaniem zestawów reguł rozmytych) złożonych, dynamicznych systemów i procesów na bazie danych pomiarowych opisujących ich zachowanie. Najpierw sformułowany został problem budowy modeli (w formie zestawów reguł rozmytych) systemów dynamicznych z wykorzystaniem danych opisujących ich zachowanie. Następnie przedstawiono proces syntezy reguł rozmytych z danych z wykorzystaniem zaproponowanego przez autorów zmodyfikowanego podejścia typu Pittsburgh z obszaru algorytmów genetycznych. Z kolei, przedstawiono zastosowanie proponowanej techniki do modelowania systemu przemysłowego pieca gazowego (tzw. benchmark Box'a-Jenkins'a) z wykorzystaniem danych pomiarowych dostępnych w repozytorium Uniwersytetu Wisconsin w Madison, USA (http://www.stat.wisc. edu/~reinsel/bjr-data). Uzyskany model, w formie zestawu reguł rozmytych, przetestowano w trybie pracy predyktora jednokrokowego oraz wielokrokowego (na pełnym horyzoncie symulacji). Dokonano również analizy zależności pomiędzy dokładnością a przejrzystością (mierzoną liczbą reguł) modelu oraz przetestowano model ze zredukowaną bazą reguł.
Źródło:
Pomiary Automatyka Kontrola; 2010, R. 56, nr 12, 12; 1420-1423
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Mining Pharmacy Database Using Evolutionary Genetic Algorithm
Autorzy:
Ykhlef, M.
ElGibreen, H.
Powiązania:
https://bibliotekanauki.pl/articles/226717.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
data mining
evolutionary algorithms
genetic algorithm
pharmacy database
sequential patterns
Opis:
Medication management is an important process in pharmacy field. Prescribing errors occur upstream in the process, and their effects can be perpetuated in subsequent steps. Prescription errors are an important issue for which conflicts with another prescribed medicine could cause severe harm for a patient. In addition, due to the shortage of pharmacists and to contain the cost of healthcare delivery, time is also an important issue. Former knowledge of prescriptions can reduce the errors, and discovery of such knowledge requires data mining techniques, such as Sequential Pattern. Moreover, Evolutionary Algorithms, such as Genetic Algorithm (GA), can find good rules in short time, thus it can be used to discover the Sequential Patterns in Pharmacy Database. In this paper GA is used to assess patient prescriptions based on former knowledge of series of prescriptions in order to extract sequenced patterns and predict unusual activities to reduce errors in timely manner.
Źródło:
International Journal of Electronics and Telecommunications; 2010, 56, 4; 427-432
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
ISSR analysis points to relict character of Aconitum bucovinense Zapal. (Ranunculaceae) at the range margin
Autorzy:
Boron, P.
Zalewska-Galosz, J.
Sutkowska, A.
Zemanek, B.
Mitka, J.
Powiązania:
https://bibliotekanauki.pl/articles/59093.pdf
Data publikacji:
2011
Wydawca:
Polskie Towarzystwo Botaniczne
Tematy:
Carpathians Mountains
conservation genetics
endemic species
marginal population
schizo-endemism
relict population
Aconitum bucovinense
Ranunculaceae
Polish Red Data Book of Plants
genetic diversity
genetic structure
ISSR technique
Opis:
Aconitum bucovinense, a high-mountain species endemic to the Eastern and Southern Carpathians, including the Apuseni Mountains, is legally protected and classified in the Polish Red Data Book of Plants. It attains its NW geographical range in two peripheral populations in the Western Bieszczady Mountains (Polish Eastern Carpathians), isolated by a distance of 13.1 km. PCR-ISSR analysis has been used to elucidate the within- and among-populational levels of species genetic diversity. A UPGMA and block clustering showed discreteness of the populations and subpopulations based on ISSR banding pattern. Analysis of Molecular Variance (AMOVA) revealed significant divergence (P = 0.024) of the two marginal populations and highly significant (P < 0.001) differentiation of subpopulations within populations. The theta index calculated for the two marginal populations and the core population in the Carpathians was 0.131 ±0.030 S.D. Most of the population-genetic diversity indices of the marginal populations were not different from those in the core area but the Shannon’s and rarity indices were lower in the marginal populations. It seems that founder effect and subsequent genetic bottleneck resulted in a fine-scale population genetic structure. The marginal populations under study need a relevant recovery program to maintain their genetic diversity.
Źródło:
Acta Societatis Botanicorum Poloniae; 2011, 80, 4
0001-6977
2083-9480
Pojawia się w:
Acta Societatis Botanicorum Poloniae
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Minig rules of concept drift using genetic algorithm
Autorzy:
Vivekanandan, P.
Nedunchezhian, R.
Powiązania:
https://bibliotekanauki.pl/articles/91705.pdf
Data publikacji:
2011
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
genetic algorithm
CDR-tree algorithm
rules
data mining
Opis:
In a database the data concepts changes over time and this phenomenon is called as concept drift. Rules of concept drift describe how the concept changes and sometimes they are interesting and mining those rules becomes more important. CDR tree algorithm is currently used to identify the rules of concept drift. Building a CDR tree becomes a complex process when the domain values of the attributes get increased. Genetic Algorithms are traditionally used for data mining tasks. In this paper, a Genetic Algorithm based approach is proposed for mining the rules of concept drift, which makes the mining task simpler and accurate when compared with the CDR-tree algorithm.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 2; 135-145
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sekwencjonowanie genomu/eksomu człowieka - aspekt bioetyczny
Human genome/exome sequencing – the bioethical aspect
Autorzy:
Kochański, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/470512.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Kardynała Stefana Wyszyńskiego w Warszawie
Tematy:
confidentiality of data
genetic discrimination
genetic and clinical determinism
incidental findings
exome sequencing
genome sequencing
Opis:
In recent years we have observed a technological revolution in genetics. For years molecular diagnostics in genetic disorders was limited to a single gene or to a group of genes. The technological breakdown in molecular genetics relies on the change of perspective from analysis of a single gene to the whole genome sequencing (WGS) or whole exome sequencing (WES). The exome is defined as a coding part of the genome consisting of the coding parts (exons) of all genes. Thus, at present geneticists have access to the whole genome instead of separate/selected genes. Clinical genetics in the era of genomic sequencing has to cope with new challenges concerning confidentiality of genetic data, genetic discrimination, genetic and clinical determinism or incidential findings detected in genome analysis. This short review attempts to demonstrate the ethical challenges faced in the era of genome sequencing.
Źródło:
Studia Ecologiae et Bioethicae; 2014, 12, 1; 29-38
1733-1218
Pojawia się w:
Studia Ecologiae et Bioethicae
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Reducing transfer costs of fragments allocation in replicated distributed database using genetic algorithms
Autorzy:
Sourati, N. K
Ramezni, F
Powiązania:
https://bibliotekanauki.pl/articles/102446.pdf
Data publikacji:
2015
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
distributed database
genetic algorithms
communication costs
GA
data segmentation
Fitness
Crossover
node
fragment data
Opis:
Distributed databases were developed in order to respond to the needs of distributed computing. Unlike traditional database systems, distributed database systems are a set of nodes that are connected with each other by network and each of nodes has its own database, but they are available by other systems. Thus, each node can have access to all data on entire network. The main objective of allocated algorithms is to attribute fragments to various nodes in order to reduce the shipping cost. Thus, firstly fragments of nodes must be accessible by all nodes in each period, secondly, the transmission cost of fragments to nodes must be reduced and thirdly, the cost of updating all components of nodes must be optimized, that results in increased reliability and availability of network. In this study, more efficient hybrid algorithm can be produced combining genetic algorithms and previous algorithms.
Źródło:
Advances in Science and Technology. Research Journal; 2015, 9, 25; 1-6
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An analysis of the performance of genetic programming for realised volatility forecasting
Autorzy:
Yin, Z.
O’Sullivan, C.
Brabazon, A.
Powiązania:
https://bibliotekanauki.pl/articles/91765.pdf
Data publikacji:
2016
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
realised volatility
genetic programming
high frequency data
Opis:
Traditionally, the volatility of daily returns in financial markets is modeled autoregressively using a time-series of lagged information. These autoregressive models exploit stylised empirical properties of volatility such as strong persistence, mean reversion and asymmetric dependence on lagged returns. While these methods can produce good forecasts, the approach is in essence atheoretical as it provides no insight into the nature of the causal factors and how they affect volatility. Many plausible explanatory variables relating market conditions and volatility have been identified in various studies but despite the volume of research, we lack a clear theoretical framework that links these factors together. This setting of a theory-weak environment suggests a useful role for powerful model induction methodologies such as Genetic Programming (GP). This study forecasts one-day ahead realised volatility (RV) using a GP methodology that incorporates information on market conditions including trading volume, number of transactions, bid-ask spread, average trading duration (waiting time between trades) and implied volatility. The forecasting performance from the evolved GP models is found to be significantly better than those numbers of benchmark forecasting models drawn from the finance literature, namely, the heterogeneous autoregressive (HAR) model, the generalized autoregressive conditional heteroscedasticity (GARCH) model, and a stepwise linear regression model (SR). Given the practical importance of improved forecasting performance for realised volatility this result is of significance for practitioners in financial markets.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 3; 155-172
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Shape Optimisation of Multi-Chamber Acoustical Plenums Using BEM, Neural Networks, and GA Method
Autorzy:
Chang, Y.-C.
Cheng, H.-C.
Chiu, M.-C.
Chien, Y.-H.
Powiązania:
https://bibliotekanauki.pl/articles/177780.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
boundary element method
plenum
centre-opening baffle
polynomial neural network model
group method of data handling
optimisation
genetic algorithm
Opis:
Research on plenums partitioned with multiple baffles in the industrial field has been exhaustive. Most researchers have explored noise reduction effects based on the transfer matrix method and the boundary element method. However, maximum noise reduction of a plenum within a constrained space, which frequently occurs in engineering problems, has been neglected. Therefore, the optimum design of multi-chamber plenums becomes essential. In this paper, two kinds of multi-chamber plenums (Case I: a two-chamber plenum that is partitioned with a centre-opening baffle; Case II: a three-chamber plenum that is partitioned with two centre-opening baffles) within a fixed space are assessed. In order to speed up the assessment of optimal plenums hybridized with multiple partitioned baffles, a simplified objective function (OBJ) is established by linking the boundary element model (BEM, developed using SYSNOISE) with a polynomial neural network fit with a series of real data – input design data (baffle dimensions) and output data approximated by BEM data in advance. To assess optimal plenums, a genetic algorithm (GA) is applied. The results reveal that the maximum value of the transmission loss (TL) can be improved at the desired frequencies. Consequently, the algorithm proposed in this study can provide an efficient way to develop optimal multi-chamber plenums for industry.
Źródło:
Archives of Acoustics; 2016, 41, 1; 43-53
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Noise Elimination of Reciprocating Compressors Using FEM, Neural Networks Method, and the GA Method
Autorzy:
Chang, Y.-C.
Chiu, M.-C.
Xie, J.-L.
Powiązania:
https://bibliotekanauki.pl/articles/178126.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
finite element method
polynomial neural network model
genetic algorithm
group method of data handling
reciprocating compressor
optimization
Opis:
Industry often utilizes acoustical hoods to block noise emitted from reciprocating compressors. However, the hoods are large and bulky. Therefore, to diminish the size of the compressor, a compact discharge muffler linked to the compressor outlet is considered. Because the geometry of a reciprocating compressor is irregular, COMSOL, a finite element analysis software, is adopted. In order to explore the acoustical performance, a mathematical model is established using a finite element method via the COMSOL commercialized package. Additionally, to facilitate the shape optimization of the muffler, a polynomial neural network model is adopted to serve as an objective function; also, a Genetic Algorithm (GA) is linked to the OBJ function. During the optimization, various noise abatement strategies such as a reverse expansion chamber at the outlet of the discharge muffler and an inner extended tube inside the discharge muffler, will be assessed by using the artificial neural network in conjunction with the GA optimizer. Consequently, the discharge muffler that is optimally shaped will decrease the noise of the reciprocating compressor.
Źródło:
Archives of Acoustics; 2017, 42, 2; 189-197
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on intelligent avoidance method of shipwreck based on bigdata analysis
Autorzy:
Li, W.
Huang, Q.
Powiązania:
https://bibliotekanauki.pl/articles/260002.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
big data analysis
shipwreck
intelligent avoidance
genetic algorithm
Opis:
In order to solve the problem that current avoidance method of shipwreck has the problem of low success rate of avoidance, this paper proposes a method of intelligent avoidance of shipwreck based on big data analysis. Firstly,our method used big data analysis to calculate the safe distance of approach of ship under the head-on situation, the crossing situation and the overtaking situation.On this basis, by calculating the risk-degree of collision of ships,our research determined the degree of immediate danger of ships.Finally, we calculated the three kinds of evaluation function of ship navigation, and used genetic algorithm to realize the intelligent avoidance of shipwreck.Experimental result shows that compared the proposed method with the traditional method in two in a recent meeting when the distance to closest point of approach between two ships is 0.13nmile, they can effectively evade.The success rate of avoidance is high.
Źródło:
Polish Maritime Research; 2017, S 3; 113-120
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Soft Law in International Governance
Autorzy:
Kwiatkowski, Paweł
Powiązania:
https://bibliotekanauki.pl/articles/684983.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet im. Adama Mickiewicza w Poznaniu
Tematy:
public international law
soft law
human genetic data
Opis:
The purpose of the article is to assess how the provisions resulting from international programmatic norms in the field of human genetic data are implemented. The presented study, adopting the perspective of institutional rationalism extended to the paradigm of legalism, considers examples of the implementation of these standards in selected legal systems – Germany, the United States of America and France. The selection of the research paradigm is preceded by a theoretical introduction, which presents three ways of conceptualizing the notion of soft law in the legal sciences. Following an outline of this legal regime in positivism, and the theories of rationalization and constructivism, the author focuses on the provisions of the International Declaration on Human Genetic Data of 16 October, 2003, which are compared with the legislative initiatives of Germany, the United States of America and France, to show the influence that the choices of states has on selection of the implemented standards and how they are implemented.
Źródło:
Adam Mickiewicz University Law Review; 2017, 7; 93-103
2450-0976
Pojawia się w:
Adam Mickiewicz University Law Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An efficient approach for view selection for data warehouse using tree mining and evolutionary computation
Autorzy:
Thakare, A.
Deshpande, P.
Powiązania:
https://bibliotekanauki.pl/articles/305413.pdf
Data publikacji:
2018
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
database management systems
data warehousing and data mining
query optimization
graph mining
algorithms for parallel computing
evolutionary computations
genetic algorithms
Opis:
The selection of a proper set of views to materialize plays an important role in database performance. There are many methods of view selection that use different techniques and frameworks to select an efficient set of views for materialization. In this paper, we present a new efficient scalable method for view selection under the given storage constraints using a tree mining approach and evolutionary optimization. The tree mining algorithm is designed to determine the exact frequency of (sub)queries in the historical SQL dataset. The Query Cost model achieves the objective of maximizing the performance benefits from the final view set that is derived from the frequent view set given by the tree mining algorithm. The performance benefit of a query is defined as a function of query frequency, query creation cost, and query maintenance cost. The experimental results show that the proposed method is successful in recommending a solution that is fairly close to an optimal solution.
Źródło:
Computer Science; 2018, 19 (4); 431-455
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł

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