Compact Deep Color Features for Remote Sensing Scene Classification

Neural Processing Letters - Aerial scene classification is a challenging problem in understanding high-resolution remote sensing images. Most recent aerial scene classification approaches are based...     

A novel finite rings based algebraic scheme of evolving secure S-boxes for images encryption

Multimedia Tools and Applications - Substitution-boxes have significant role in block ciphers as they are the only component which offers nonlinearity in the anticipated symmetric encryption...     

Numerical and sensitivity analysis of MHD bioconvective slip flow of nanomaterial with binary chemical reaction and Newtonian heating

The impact of Stefan blowing on the MHD bioconvective slip flow of a nanofluid towards a sheet is explored using numerical and statistical tools. The governing partial differential equations are nondimensionalized and converted to similarity equations using apposite transformations. These transformed equations are solved using the Runge–Kutta–Fehlberg method with the shooting technique. Graphical visualizations are used to scrutinize the effect of the controlling parameters on the flow profiles, skin friction coefficient, local Nusselt, and Sherwood number. Moreover, the sensitivities of the reduced Sherwood and Nusselt number to the input variables of interest are explored by adopting the response surface methodology. The outcomes of the limiting cases are emphatically in corroboration with the outcomes from preceding research. It is found that the heat transfer rate has a positive sensitivity towards the haphazard motion of the nanoparticles and a negative sensitivity towards the thermomigration. The thermal field is enhanced by the Stefan blowing aspect. Moreover, the fluid velocity can be controlled by the applied magnetic field.     

Model-based test case generation and prioritization: a systematic literature review

Software and Systems Modeling - Model-based test case generation (MB-TCG) and prioritization (MB-TCP) utilize models that represent the system under test (SUT) for test generation and...     

Thermally stable and durable superhydrophobic surfaces on stainless steel sheets with microholes via acid pretreatment and modification with self-assembled monolayers

Microfluidics and Nanofluidics - Single-cell nucleic acid analysis aims at discovering the genetic differences between individual cells which is well known as the cellular heterogeneity. This...     

Fuzzy Based Hybrid Focus Value Estimation for Multi Focus Image Fusion

Due to limited depth-of-field of digital single-lens reflex cameras, the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred (out-of-focus) in the image. Multi-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same scene. In this paper, a new Fuzzy Based Hybrid Focus Measure (FBHFM) for multi-focus image fusion has been proposed. Optimal block size is very critical step for multi-focus image fusion. Particle Swarm Optimization (PSO) algorithm has been used to find optimal size of the block of the images for extraction of focus measure features. After finding optimal blocks, three focus measures Sum of Modified Laplacian, Gray Level Variance and Contrast Visibility has been extracted and combined these focus measures by using intelligent fuzzy technique. Fuzzy based hybrid intelligent focus values were estimated using contrast visibility measure to generate focused image. Different sets of multi-focus images have been used in detailed experimentation and compared the results with state-of-the-art existing techniques such as Genetic Algorithm (GA), Principal Component Analysis (PCA), Laplacian Pyramid discrete wavelet transform (DWT), and aDWT for image fusion. It has been found that proposed method performs well as compare to existing methods.

     

Effects of feeding bentonite clay upon ochratoxin A–induced immunosuppression in broiler chicks

A presence of mycotoxins in feed is one of the most alarming issues in the poultry feed industry. Ochratoxins, produced by several Aspergillus and Penicillium species, are important mycotoxin regarding the health status of poultry birds. Ochratoxins are further classified into to several subtypes (A, B, C, etc) depending on their chemical structures, but ochratoxin A (OTA) is considered the most important and toxic. Bentonite clay, belonging to phyllosilicates and formed from weathering of volcanic ashes, has adsorbent ability for several mycotoxins. The present study was designed to study the effects of bentonite clay upon OTA-induced immunosuppression in broiler chicks. For this, 480 day-old broiler chicks were procured from a local hatchery and then different combinations of OTA (0.15, 0.3, or 1.0 mg/kg) and bentonite clay (5, 10, and 20 g/kg) were incorporated into their feed. At 13, 30, and 42 days of age, parameters such as antibody responses to sheep red blood cells, in situ lymphoproliferative responses to mitogen (PHA-P), and in situ phagocytic activity (i.e., via carbon clearance) were determined respectively. The results indicated there was a significant reduction of total antibody and immunoglobulin titres, lymphoproliferative responses, and phagocytic potential in OTA-treated birds, suggesting clear immunosuppression by OTA in birds in a dose-dependent manner. These results were also significantly lower in all combination groups (OTA with bentonite clay), suggesting few to no effects of feeding bentonite clay upon OTA- induced alterations in different immune parameters.