Wyniki wyszukiwania - Biblioteka Nauki

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Proces internacjonalizacji małych i średnich przedsiębiorstw

100%

Mikołajczyk A. , Uniwersytet Łódzki K. M. S. G.

Acta Universitatis Lodziensis. Folia Oeconomica

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2004

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tom 180

EN

Governments world wide have come to recognize the importance of SMEs and their contribution to economic growth, employment, regional and local development. Globalization lhe acceleration of technological change and innovation create opportunities for SMEs to broaden their activities internationally. The internationalization process is described as a gradual development taking place in distinct stages and its traditional view is based on economies of scale and large firms. Small firms, however, cannot enjoy all the options in the internationalization process outlined in literature. A theoretical description of the internationalization process of SMEs is presented throughout five stages: Domestic Marketing Focus, Pre-export, Experimental Export Involvement, Active Involvement, Committed Involvement. Exporting is most common and widespread form of internationalization used by small and medium sized enterprises. The increasing internationalization of markets presents both opportunities and threats for SMEs in many countries. To face the challenges of an open economy the firms have to gear up and internationalize their business operations. The SMEs have the advantage of adaptability and flexibility, vital for maintaining competitiveness in the international market; but unfortunately limited resources, difficulty in acquiring information, lack of managerial experience with exporting and some other factors restrict the scope of their export business. The success of SMEs in the international market depends on: creating an enabling environment and the chance to acquire new knowledge and new skill, improving access to trade finance.

2

Długość telomerów – nowy biomarker w medycynie

51%

Kozłowska A. , Mikołajczyk A. , Pawlas N.

Medycyna Środowiskowa - Environmental Medicine

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2015

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tom 18

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nr 4

7-13

EN

A number of xenobiotics in the environment and workplace influences on our health and life. Biomarkers are tools for measuring such exposures and their effects in the organism. Nowadays, telomere length, epigenetic changes, mutations and changes in gene expression pattern have become new molecular biomarkers. Telomeres play the role of molecular clock, which influences on expectancy of cell life and thus aging, the formation of damages, development diseases and carcinogenesis. The telomere length depends on mechanisms of replication and the activity of telomerase. Telomere length is currently used as a biomarker of susceptibility and/or exposure. This paper describes the role of telomere length as a biomarker of aging cells, oxidative stress, a marker of many diseases including cancer, and as a marker of environmental and occupational exposure.

PL

Szereg szkodliwych czynników zewnętrznych w środowisku i w miejscu pracy oddziałuje na nasze zdrowie i życie. Biomarkery są narzędziem umożliwiającym pomiar takich oddziaływań i ich skutków w organizmie. Obecnie wśród nowych biomarkerów molekularnych wykorzystywanych w monitoringu biologicznym, medycynie i diagnostyce możemy wyróżnić długość telomerów, zmiany epigenetyczne, mutacje i zmiany w aktywności genów. Telomery pełnią rolę zegara molekularnego odmierzającego długość życia komórki a tym samym starzenia się organizmu, powstawania uszkodzeń, rozwijania chorób i nowotworzenia. Długość telomerów uzależniona jest od szeregu mechanizmów zachodzących podczas procesu replikacji oraz od aktywności telomerazy. Coraz częściej długość telomerów jest wykorzystywana jako biomarker wrażliwości lub ekspozycji. W niniejszej publikacji poruszono aspekt długości telomerów jako biomarkera starzenia się komórki, stresu oksydacyjnego, markera wielu chorób oraz zaprezentowano wykorzystanie jako markera ekspozycji środowiskowej i zawodowej.

3

Diagnosis of malignant melanoma by neural network ensemble-based system utilising hand-crafted skin lesion features

51%

Grochowski M. , Mikołajczyk A. , Kwasigroch A.

Metrology and Measurement Systems

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2019

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tom Vol. 26, nr 1

65--80

EN

Malignant melanomas are the most deadly type of skin cancer, yet detected early have high chances of successful treatment. In the last twenty years, the interest in automatic recognition and classification of melanoma dynamically increased, partly because of appearing public datasets with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task due to uneven sizes of datasets, huge intra-class variation with small interclass variation, and the existence of many artifacts in the images. One of the most recognized methods of melanoma diagnosis is the ABCD method. In the paper, we propose an extended version of this method and an intelligent decision support system based on neural networks that uses its results in the form of hand-crafted features. Automatic determination of the skin features with the ABCD method is difficult due to the large diversity of images of various quality, the existence of hair, different markers and other obstacles. Therefore, it was necessary to apply advanced methods of pre-processing the images. The proposed system is an ensemble of ten neural networks working in parallel, and one network using their results to generate a final decision. This system structure enables to increase the efficiency of its operation by several percentage points compared with asingle neural network. The proposed system is trained on over 5000 and tested afterwards on 200 skin moles. The presented system can be used as a decision support system for primary care physicians, as a system capable of self-examination of the skin with a dermatoscope and also as an important tool to improve biopsy decision making.

4

Machine learning system for automated blood smear analysis

38%

Grochowski M. , Wąsowicz M. , Mikołajczyk A. , Ficek M. , Kulka M. , Wróbel M. S. , Jędrzejewska-Szczerska M.

Metrology and Measurement Systems

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2019

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tom Vol. 26, nr 1

81--93

EN

In this paper the authors propose a decision support system for automatic blood smear analysis based onmicroscopic images. The images are pre-processed in order to remove irrelevant elements and to enhancethe most important ones – the healthy blood cells (erythrocytes) and the pathologic ones (echinocytes). The separated blood cells are analysed in terms of their most important features by the eigenfaces method. The features are the basis for designing the neural network classifier, learned to distinguish between erythrocytes and echinocytes. As the result, the proposed system is able to analyse the smear blood images in a fully automatic way and to deliver information on the number and statistics of the red blood cells, both healthy and pathologic. The system was examined in two case studies, involving the canine and human blood, and then consulted with the experienced medicine specialists. The accuracy of classification of red blood cells into erythrocytes and echinocytes reaches 96%.