AbstractThe load deformation and failure behavior of shallow footings can be described in a macroelement formulation. This paper deals with the study of the failure surface and the definition and ...validation of plastic load deformation by single surface hardening models. The straightforward application of the plasticity theory to the soil-foundation system makes it possible to extend the given expression for the case of unsaturated soils. This paper studies a small-scale footing test on unsaturated sand for the formulation of the elastoplastic macroelement of shallow footings under a centrally applied vertical load. The influence of soil suction on different parameters associated with the macroelement is studied and calibrated against experimental results. The presented model shows good agreement with the experimental results. Finally, the limitations and still open questions of the approach are discussed in detail.
Celotno besedilo
Dostopno za:
DOBA, FGGLJ, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
•An optimized RBFN with grab cut segmentation was developed to detect the types of skin diseases.•Various skin disease images are collected and pre-processed using two various approaches such as ...resizing and BW-Net.•Using grab-cut segmentation, divide the diseased region in the pre-processed images.•Extract the features from the segmented images using a hybrid SHC model, which includes segmentation-based fractal texture analysis, Hu moment invariants and colour co-occurrence matrix.•These features are further proceeded for the classification process using a radial basis function network. The prediction accuracy is improved by selecting the optimal learning parameter values using red fox optimization.
Skin disorder is emerging as a dreadful disease because of drastic climatic changes prevailing all over the globe. Automated detection and classification of skin diseases in humans is essential for improving their living standards. However, existing skin disease prediction algorithms are expensive, time consuming and have poor performance. To overcome these drawbacks, a hybrid feature extraction with an optimized classifier was proposed to detect various skin diseases. Images of different skin diseases were gathered and pre-processed using BW-Net, a process that can recognize characteristics in both homogeneous and heterogeneous data. Then, the RO1 was segmented using the grab cut segmentation approach. The segmented images were subjected to the hybrid SHC model in order to facilitate feature extraction. Using Hu moment invariants, a colour co-occurrence matrix, and segmentation-based fractal texture analysis (SFTA), one may extract features like colour, shape, and texture from segmented images. Finally, the extracted features are trained and classified for different skin types using the optimized Radial Basis Function Network (RBFN) algorithm. The hyperparameter such as the learning rate in the classifier was tuned optimally with the use of the Red Fox Optimization (RFO) algorithm. The proposed optimised RBFN detects the exact type of skin disease based on extracted features. The proposed model is validated using three different datasets including the ISIC database which provides 94.2% recall, 5.79% FNR, 91.63% kappa, 98.02% accuracy and 17.95 sec execution time. Thus, the proposed optimized deep learning classifier and hybrid feature extraction model effectively detect skin disease with more accuracy.
Malgré la consommation énergétique en hausse, les émissions de carbone dans le monde liées à la consommation d’énergie ont été stables en 2014, pour la première fois depuis 40 ans, dans un contexte ...de croissance économique soutenue. Cette stabilisation est en partie due à une meilleure pénétration de ces technologies et à une meilleure efficacité énergétique, deux domaines qui ont enregistré des progrès considérables ces dernières années.
Moringa oleifera seeds are currently being used as a livestock feed across tropical regions of the world due to its availability and palatability. However, limited knowledge exists on the effects of ...the raw seeds on ruminant metabolism. As such, the rumen stimulation technique was used to evaluate the effects of substituting increasing concentrations of ground Moringa seeds (0, 100, 200 and 400 g/kg concentrate dry matter (DM)) in the diet on rumen fermentation and methane production. Two identical, Rusitec apparatuses, each with eight fermenters were used with the first 8 days used for adaptation and days 9 to 16 used for measurements. Fermenters were fed a total mixed ration with Urochloa brizantha as the forage. Disappearance of DM, CP, NDF and ADF linearly decreased (P<0.01) with increasing concentrations of Moringa seeds in the diet. Total volatile fatty acid production and the acetate to propionate ratio were also linearly decreased (P<0.01). However, only the 400 g/kg (concentrate DM basis) treatment differed (P<0.01) from the control. Methane production (%), total microbial incorporation of 15N and total production of microbial N linearly decreased (P<0.01) as the inclusion of Moringa seeds increased. Though the inclusion of Moringa seeds in the diet decreased CH4 production, this arose from an unfavourable decrease in diet digestibility and rumen fermentation parameters.
PDF
