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EN
The number of subscribers in mobile networks is growing rapidly, which challenges network management and data delivery. Efficient management and routing are key solutions. One important solution is distributed mobility management (DMM), which handles the mobility of subscribers at the edges of mobile networks and load balancing. Otherwise, mobility anchors are distributed across a network that can manage the handover procedures. In this paper, we propose a novel mobility anchor-selection scheme based on the results of a cost function with three factors to select a suitable cell as well as an anchor for moving subscribers and improving the handover performances of networks. Our results illustrate that the proposed scheme provides significantly enhanced handover performance.
2
Content available remote Optymalizacja budowy „płytkich” wykopów
EN
Ocean wave energy is known as a renewable energy resource with high power potential and without negative environmental impacts. Wave energy has a direct relationship with the ocean’s meteorological parameters. The aim of the current study is to investigate the dependency between ocean wave energy flux and meteorological parameters by using data mining methods (DMMs). For this purpose, a feed-forward neural network (FFNN), a cascade-forward neural network (CFNN), and gene expression programming (GEP) are implemented as different DMMs. The modeling is based on historical meteorological and wave data taken from the National Data Buoy Center (NDBC). In all models, wind speed, air temperature, and sea temperature are input parameters. In addition, the output is the wave energy flux which is obtained from the classical wave energy flux equation. It is notable that, initially, outliers in the data sets were removed by the local distribution based outlier detector (LDBOD) method to obtain the best and most accurate results. To evaluate the performance and accuracy of the proposed models, two statistical measures, root mean square error (RMSE) and regression coefficient (R), were used. From the results obtained, it was found that, in general, the FFNN and CFNN models gave a more accurate prediction of wave energy from meteorological parameters in the absence of wave records than the GEP method.
4
PL
Artykuł przedstawia wyniki i analizę wstępnych badań wytrzymałości na jednoosiowe ściskanie zróżnicowanych kompozytów cement - torf, formowanych metodą mieszania. Badania prowadzone były w warunkach laboratoryjnych na próbkach sześciennych i cylindrycznych. Sposób formowania próbek przyjęto opierając się o wytyczne metody fińskiej oraz zastosowano własną metodykę wynikającą z rozpoznania problemu we wcześniejszych badaniach prowadzonych w Katedrze Geotechniki UTP w Bydgoszczy. Na obecnym etapie badań wykazano skuteczność stosowania cementu w odpowiednich proporcjach jako stabilizatora gruntów organicznych a szczególnie torfów.
EN
The article presents the results of preliminary research and analysis of uniaxial compressive strength test of different cement - peat composites formed by mixing method. The research was conducted in the laboratory on cubic and cylindrical samples. The sample forming method was taken on the basis of the Finnish method guidelines and the author's original methodology resulting from previous studies conducted in the Geotechnical Department of UTP in Bydgoszcz. At this stage the study has shown the efficacy of cement in the proper proportions as an organic soil stabilizer.
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