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    Wyświetlanie 1-4 z 4
    Tytuł:
    Are we prepared in Poland to promote genetic testing?
    Autorzy:
    Witt, Michał
    Powiązania:
    https://bibliotekanauki.pl/articles/1916640.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    genetic tests
    confidentiality of genetic data
    legal regulation of genetic procedures
    Opis:
    The extremely rapid development of modern techniques for analyzing the human genome, both in the field of scientific research and diagnostic applications, entails a variety of problems whose solution lags far behind our current technological capabilities. These problems appear in the ethical, social, legal or religious spheres and include such detailed issues as e.g. examination of children for diseases manifested in adulthood, accidental (secondary) results being a side effect of the analysis of the whole genome, the growing offer of tests directed directly to the recipient, patenting of genetic information, confidentiality of genetic data and their availability to third parties, availability of genetic counselling, etc. The legal regulation of these problems, the list of which is growing at an alarming rate, still remains in the sphere of declarations, and its shift to the sphere of real actions seems to be lagging further and further back in time. Do patients, laboratory diagnoses, doctors still have to be held hostage by the legislative impotence?
    Źródło:
    Nauka; 2020, 2
    1231-8515
    Pojawia się w:
    Nauka
    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:
    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:
    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
      Wyświetlanie 1-4 z 4

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