Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "time banks" wg kryterium: Temat


Wyświetlanie 1-7 z 7
Tytuł:
Time banks vs household production theory and threats to the fiscal security of the state
Banki czasu a teoria produkcji domowej i zagrożenia bezpieczeństwa fiskalnego państwa
Autorzy:
Stępnicka, Nina
Wiączek, Paulina
Powiązania:
https://bibliotekanauki.pl/articles/582294.pdf
Data publikacji:
2019
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
time banks
financial security
cooperation economy
household production
security threats
banki czasu
bezpieczeństwo finansowe
gospodarka współpracy
produkcja gospodarstwa domowego
zagrożenia bezpieczeństwa
Opis:
The aim of the article is to demonstrate that time banks are an example of one of the many models of a cooperation economy, including a shared way of life. We can place them in the category of so-called household production. The research on this issue was conducted by American economist Hazel Kyrk (1886-1957), a founder of the so-called home economics. According to Kyrk’s theory, time banks are a part of household production, which is free of charge and enables to use resources of households in a more efficient way. The authors used the historical method and the method of the critical analysis of literature.
Celem artykułu jest wykazanie, że banki czasu są jednym z wielu modeli gospodarki współpracy, w tym współdzielonego stylu życia. Możemy zakwalifikować je do kategorii tzw. produkcji domowej. Prekursorką badań dotyczących produkcji domowej była amerykańska ekonomistka Hazel Kyrk (1886-1957), twórczyni specjalności zwanej ekonomiką domu. Zgodnie z teorią H. Kyrk banki czasu są częścią produkcji gospodarstw domowych, mającej charakter nieodpłatny i pozwalających na wykorzystanie zasobów gospodarstwa domowego w bardziej efektywny sposób. Metodami wykorzystanymi w pracy są metoda historyczna i metoda krytycznej analizy literatury.
Źródło:
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu; 2019, 63, 7; 127-135
1899-3192
Pojawia się w:
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Joint time-frequency and wavelet analysis - an introduction
Autorzy:
Majkowski, A.
Kołodziej, M.
Rak, R. J.
Powiązania:
https://bibliotekanauki.pl/articles/220841.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
frequency analysis
time-frequency analysis
short-time Fourier transform
Gabor transform
Wigner-Ville transform
Cone-Shaped Transform
wavelet analysis
time-scale analysis
wavelet decomposition
filter banks
wavelet packets
Opis:
A traditional frequency analysis is not appropriate for observation of properties of non-stationary signals. This stems from the fact that the time resolution is not defined in the Fourier spectrum. Thus, there is a need for methods implementing joint time-frequency analysis (t/f) algorithms. Practical aspects of some representative methods of time-frequency analysis, including Short Time Fourier Transform, Gabor Transform, Wigner-Ville Transform and Cone-Shaped Transform are described in this paper. Unfortunately, there is no correlation between the width of the time-frequency window and its frequency content in the t/f analysis. This property is not valid in the case of a wavelet transform. A wavelet is a wave-like oscillation, which forms its own “wavelet window”. Compression of the wavelet narrows the window, and vice versa. Individual wavelet functions are well localized in time and simultaneously in scale (the equivalent of frequency). The wavelet analysis owes its effectiveness to the pyramid algorithm described by Mallat, which enables fast decomposition of a signal into wavelet components.
Źródło:
Metrology and Measurement Systems; 2014, 21, 4; 741-758
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Infrared devices and techniques (revision)
Autorzy:
Rogalski, A.
Chrzanowski, K.
Powiązania:
https://bibliotekanauki.pl/articles/221154.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
frequency analysis
time-frequency analysis
short-time Fourier transform
Gabor transform
Wigner-Ville transform
Cone-Shaped Transform
wavelet analysis
time-scale analysis
wavelet decomposition
filter banks
wavelet packets
Opis:
The main objective of this paper is to produce an applications-oriented review covering infrared techniques and devices. At the beginning infrared systems fundamentals are presented with emphasis on thermal emission, scene radiation and contrast, cooling techniques, and optics. Special attention is focused on night vision and thermal imaging concepts. Next section concentrates shortly on selected infrared systems and is arranged in order to increase complexity; from image intensifier systems, thermal imaging systems, to space-based systems. In this section are also described active and passive smart weapon seekers. Finally, other important infrared techniques and devices are shortly described, among them being: non-contact thermometers, radiometers, LIDAR, and infrared gas sensors.
Źródło:
Metrology and Measurement Systems; 2014, 21, 4; 565-618
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Execution time prediction model for parallel GPU realizations of discrete transforms computation algorithms
Autorzy:
Puchala, Dariusz
Stokfiszewski, Kamil
Wieloch, Kamil
Powiązania:
https://bibliotekanauki.pl/articles/2173530.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
graphics processing unit
GPU
execution time prediction model
discrete wavelet transform
DWT
lattice structure
convolution-based approach
orthogonal transform
orthogonal filter banks
time effectiveness
prediction accuracy
Opis:
Parallel realizations of discrete transforms (DTs) computation algorithms (DTCAs) performed on graphics processing units (GPUs) play a significant role in many modern data processing methods utilized in numerous areas of human activity. In this paper the authors propose a novel execution time prediction model, which allows for accurate and rapid estimation of execution times of various kinds of structurally different DTCAs performed on GPUs of distinct architectures, without the necessity of conducting the actual experiments on physical hardware. The model can serve as a guide for the system analyst in making the optimal choice of the GPU hardware solution for a given computational task involving particular DT calculation, or can help in choosing the best appropriate parallel implementation of the selected DT, given the limitations imposed by available hardware. Restricting the model to exhaustively adhere only to the key common features of DTCAs enables the authors to significantly simplify its structure, leading consequently to its design as a hybrid, analytically–simulational method, exploiting jointly the main advantages of both of the mentioned techniques, namely: time-effectiveness and high prediction accuracy, while, at the same time, causing mutual elimination of the major weaknesses of both of the specified approaches within the proposed solution. The model is validated experimentally on two structurally different parallel methods of discrete wavelet transform (DWT) computation, i.e. the direct convolutionbased and lattice structure-based schemes, by comparing its prediction results with the actual measurements taken for 6 different graphics cards, representing a fairly broad spectrum of GPUs compute architectures. Experimental results reveal the overall average execution time and prediction accuracy of the model to be at a level of 97.2%, with global maximum prediction error of 14.5%, recorded throughout all the conducted experiments, maintaining at the same time high average evaluation speed of 3.5 ms for single simulation duration. The results facilitate inferring the model generality and possibility of extrapolation to other DTCAs and different GPU architectures, which along with the proposed model straightforwardness, time-effectiveness and ease of practical application, makes it, in the authors’ opinion, a very interesting alternative to the related existing solutions.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 1; e139393, 1--30
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Execution time prediction model for parallel GPU realizations of discrete transforms computation algorithms
Autorzy:
Puchala, Dariusz
Stokfiszewski, Kamil
Wieloch, Kamil
Powiązania:
https://bibliotekanauki.pl/articles/2173636.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
graphics processing unit
GPU
execution time prediction model
discrete wavelet transform
DWT
lattice structure
convolution-based approach
orthogonal transform
orthogonal filter banks
time effectiveness
prediction accuracy
procesor graficzny
model przewidywania czasu wykonania
dyskretna transformata falkowa
struktura sieciowa
podejście oparte na splotach
przekształcenia ortogonalne
ortogonalne banki filtrów
efektywność czasowa
dokładność przewidywania
Opis:
Parallel realizations of discrete transforms (DTs) computation algorithms (DTCAs) performed on graphics processing units (GPUs) play a significant role in many modern data processing methods utilized in numerous areas of human activity. In this paper the authors propose a novel execution time prediction model, which allows for accurate and rapid estimation of execution times of various kinds of structurally different DTCAs performed on GPUs of distinct architectures, without the necessity of conducting the actual experiments on physical hardware. The model can serve as a guide for the system analyst in making the optimal choice of the GPU hardware solution for a given computational task involving particular DT calculation, or can help in choosing the best appropriate parallel implementation of the selected DT, given the limitations imposed by available hardware. Restricting the model to exhaustively adhere only to the key common features of DTCAs enables the authors to significantly simplify its structure, leading consequently to its design as a hybrid, analytically–simulational method, exploiting jointly the main advantages of both of the mentioned techniques, namely: time-effectiveness and high prediction accuracy, while, at the same time, causing mutual elimination of the major weaknesses of both of the specified approaches within the proposed solution. The model is validated experimentally on two structurally different parallel methods of discrete wavelet transform (DWT) computation, i.e. the direct convolutionbased and lattice structure-based schemes, by comparing its prediction results with the actual measurements taken for 6 different graphics cards, representing a fairly broad spectrum of GPUs compute architectures. Experimental results reveal the overall average execution time and prediction accuracy of the model to be at a level of 97.2%, with global maximum prediction error of 14.5%, recorded throughout all the conducted experiments, maintaining at the same time high average evaluation speed of 3.5 ms for single simulation duration. The results facilitate inferring the model generality and possibility of extrapolation to other DTCAs and different GPU architectures, which along with the proposed model straightforwardness, time-effectiveness and ease of practical application, makes it, in the authors’ opinion, a very interesting alternative to the related existing solutions.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 1; art. no. e139393
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Execution time prediction model for parallel GPU realizations of discrete transforms computation algorithms
Autorzy:
Puchala, Dariusz
Stokfiszewski, Kamil
Wieloch, Kamil
Powiązania:
https://bibliotekanauki.pl/articles/2173537.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
graphics processing unit
GPU
execution time prediction model
discrete wavelet transform
DWT
lattice structure
convolution-based approach
orthogonal transform
orthogonal filter banks
time effectiveness
prediction accuracy
procesor graficzny
model przewidywania czasu wykonania
dyskretna transformata falkowa
struktura sieciowa
podejście oparte na splotach
przekształcenia ortogonalne
ortogonalne banki filtrów
efektywność czasowa
dokładność przewidywania
Opis:
Parallel realizations of discrete transforms (DTs) computation algorithms (DTCAs) performed on graphics processing units (GPUs) play a significant role in many modern data processing methods utilized in numerous areas of human activity. In this paper the authors propose a novel execution time prediction model, which allows for accurate and rapid estimation of execution times of various kinds of structurally different DTCAs performed on GPUs of distinct architectures, without the necessity of conducting the actual experiments on physical hardware. The model can serve as a guide for the system analyst in making the optimal choice of the GPU hardware solution for a given computational task involving particular DT calculation, or can help in choosing the best appropriate parallel implementation of the selected DT, given the limitations imposed by available hardware. Restricting the model to exhaustively adhere only to the key common features of DTCAs enables the authors to significantly simplify its structure, leading consequently to its design as a hybrid, analytically–simulational method, exploiting jointly the main advantages of both of the mentioned techniques, namely: time-effectiveness and high prediction accuracy, while, at the same time, causing mutual elimination of the major weaknesses of both of the specified approaches within the proposed solution. The model is validated experimentally on two structurally different parallel methods of discrete wavelet transform (DWT) computation, i.e. the direct convolutionbased and lattice structure-based schemes, by comparing its prediction results with the actual measurements taken for 6 different graphics cards, representing a fairly broad spectrum of GPUs compute architectures. Experimental results reveal the overall average execution time and prediction accuracy of the model to be at a level of 97.2%, with global maximum prediction error of 14.5%, recorded throughout all the conducted experiments, maintaining at the same time high average evaluation speed of 3.5 ms for single simulation duration. The results facilitate inferring the model generality and possibility of extrapolation to other DTCAs and different GPU architectures, which along with the proposed model straightforwardness, time-effectiveness and ease of practical application, makes it, in the authors’ opinion, a very interesting alternative to the related existing solutions.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 1; e139393, 1--30
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Execution time prediction model for parallel GPU realizations of discrete transforms computation algorithms
Autorzy:
Puchala, Dariusz
Stokfiszewski, Kamil
Wieloch, Kamil
Powiązania:
https://bibliotekanauki.pl/articles/2173635.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
graphics processing unit
GPU
execution time prediction model
discrete wavelet transform
DWT
lattice structure
convolution-based approach
orthogonal transform
orthogonal filter banks
time effectiveness
prediction accuracy
procesor graficzny
model przewidywania czasu wykonania
dyskretna transformata falkowa
struktura sieciowa
podejście oparte na splotach
przekształcenia ortogonalne
ortogonalne banki filtrów
efektywność czasowa
dokładność przewidywania
Opis:
Parallel realizations of discrete transforms (DTs) computation algorithms (DTCAs) performed on graphics processing units (GPUs) play a significant role in many modern data processing methods utilized in numerous areas of human activity. In this paper the authors propose a novel execution time prediction model, which allows for accurate and rapid estimation of execution times of various kinds of structurally different DTCAs performed on GPUs of distinct architectures, without the necessity of conducting the actual experiments on physical hardware. The model can serve as a guide for the system analyst in making the optimal choice of the GPU hardware solution for a given computational task involving particular DT calculation, or can help in choosing the best appropriate parallel implementation of the selected DT, given the limitations imposed by available hardware. Restricting the model to exhaustively adhere only to the key common features of DTCAs enables the authors to significantly simplify its structure, leading consequently to its design as a hybrid, analytically–simulational method, exploiting jointly the main advantages of both of the mentioned techniques, namely: time-effectiveness and high prediction accuracy, while, at the same time, causing mutual elimination of the major weaknesses of both of the specified approaches within the proposed solution. The model is validated experimentally on two structurally different parallel methods of discrete wavelet transform (DWT) computation, i.e. the direct convolutionbased and lattice structure-based schemes, by comparing its prediction results with the actual measurements taken for 6 different graphics cards, representing a fairly broad spectrum of GPUs compute architectures. Experimental results reveal the overall average execution time and prediction accuracy of the model to be at a level of 97.2%, with global maximum prediction error of 14.5%, recorded throughout all the conducted experiments, maintaining at the same time high average evaluation speed of 3.5 ms for single simulation duration. The results facilitate inferring the model generality and possibility of extrapolation to other DTCAs and different GPU architectures, which along with the proposed model straightforwardness, time-effectiveness and ease of practical application, makes it, in the authors’ opinion, a very interesting alternative to the related existing solutions.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 1; art. no. e139393
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-7 z 7

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies