A multi-criteria context-sensitive approach for social image collection summarization

Recent increase in the number of digital photos in the content sharing and social networking websites has created an endless demand for techniques to analyze, navigate, and summarize these images. In this paper, we focus on image collection summarization. Earlier methods in image collection summarization consider representativeness and diversity criteria while recent ones also consider other criteria such as image quality, aesthetic or appeal. In this paper, we propose a multi-criteria context-sensitive approach for social image collection summarization. In the proposed method, two different sets of features are combined while each one looks at different criteria for image collection summarization: social attractiveness features and semantic features. The first feature set considers different aspects that make an image appealing such as image quality, aesthetic, and emotion to create attractiveness score for input images while the second one covers semantic content of images and assigns semantic score to them. We use social network infrastructure to identify attractiveness features and domain ontology for extracting ontology features. The final summarization is provided by integrating the attractiveness and semantic features of input images. The experimental results on a collection of human generated summaries on a set of Flickr images demonstrate the effectiveness of the proposed image collection summarization approach.     

Electro-magneto temperature-dependent vibration analysis of functionally graded-carbon nanotube-reinforced piezoelectric Mindlin cylindrical shells resting on a temperature-dependent,orthotropic elastic medium

Vibration smart control analysis of a temperature-dependent functionally graded-carbon nanotube-reinforced piezoelectric cylindrical shell embedded in an orthotropic elastic medium is investigated. The mixture law is used for obtaining the material properties of the structure. The structure is subjected to a 2D magnetic field. Considering the first-order shear deformation theory, the motion equations are obtained. Based on an analytical method and differential quadrature method, the frequency is calculated. The effects of applied voltage, magnetic field, volume percent, and distribution type of carbon nanotubes, temperature, orthotropic elastic medium, and length to radius ratio of the shell are shown on system frequency.     

Generalized Gabor filters for palmprint recognition

Orientation-based coding approaches have recently been widely employed for face and palmprint recognition where generally, one starts with a set of Gabor filters to extract orientation information and then proceeds to code dominant orientations as features for each point of the palmprint. However, as the Gabor filter is developed to model two-dimensional receptive fields of simple cells in straits cortex, it might not be our best choice when dealing with curved and complex structures inherent in the palmprint texture. Motivated by this intuition, this paper shows that Gabor filters are a subset of a bigger family of filters which we refer to as generalized Gabor filter (GGF). Depending on the values of its parameters, a GGF takes a rather diverse shapes and orientations, which results in a potentially finer feature extraction capability. We show this improved capability by employing GGFs in the palmprint verification process. In applying our method, two different sub-banks of GGFs are defined for the orientation-based feature extraction of palmprints, and when compared with Gabor filters, it will be shown that GGFs have the upper hand in capturing orientation features. Furthermore, compared with the competitive code—one of the well-known orientation-based coding methods—the number of employed orientations is reduced to half. This would automatically compensate for a double usage of the filter banks, which otherwise could increase the time complexity of using GGFs. These ideas are further elaborated using a set of experiments on PolyU II and PolyU 2D/3D palmprint databases. The results show the preeminence of using GGFs both in terms of accuracy and efficiency.     

Design and implementation of a relational database of macroscopic cross-sections for steady-state and transient analysis in a medium sized PWR

This paper deals with the design and implementation of a relational database of macroscopic cross-sections as well as validation and its usage as a component in steady-state and transient analysis. These types of analysis are definitely designated as data-driven processes in which their behavior is changed based on data. The data in this manner can be the variation of fuel composition density as well as the fuel temperature during the reactor operation or in some accidents. In order to gain the accurate results in transient analysis, applying these variations is inevitable. Therefore, for each changing in fuel behavior, the new set of macroscopic cross-sections must be reproduced by performing the lattice calculations at run-time. During recent years some approaches have been done in both academic and commercial areas to take advantage of already calculated cross-sections instead of recalculate them by lattice codes during the analysis. Using this approach leverages the computation performance by reducing the floating point operations which can decrease the CPU load as well as the calculation time. Although this approach delivers a good performance in terms of time and computation, when a large number of fuel or reactor core circumstances are subjected to be analyzed the accuracy is became an important point. In this situation the cross-sections for all expected conditions must be already calculated. This cause the large number of cross-section data which must be stored and managed somehow. The system applied in this study to store and manage these cross-section data sets is a relational database management system (RDBMS) which is based on Microsoft SQL Server 2008 Management System. The node wise macroscopic cross-sections for each nominal and off-nominal of a typical medium sized PWR reactor core conditions which are calculated by WIMS-D5 and CITATION codes are tabulated in this system and can be retrieved by structured query language extremely rapid on demand.     

The release rate and antimicrobial activity of calcium-alginate films containing self-microemulsifying Thymus vulgaris essential oil against Escherichia coli and Staphylococcus aureus

The aim of this study was to fabricate antimicrobial calcium-alginate-based films containing the self-microemulsifying thyme essential oil (TEO) formulations using Tween 80 as the surfactant, and acetic (AA) or propionic (PA) acids as the cosurfactants. A Ca-alginate film containing nano-emulsified TEO as well as a neat Ca-alginate film were considered as the controls. The scanning electron microscopy micrographs showed a highly porous texture for SME films, which resulted in an increase in water vapor permeability and water absorption capacity of these films. The SME films released the TEO completely within 155 min and inhibited the growth of S. aureus and E. coli in in vitro antimicrobial tests. The population of S. aureus and E. coli reduced significantly in ground beef covered with SME films. The results of this study showed that self-microemulsifying TEO films could effectively increase the shelf life of ground beef by controlling its microbial population.     

Robust resource allocation scheme under channel uncertainties for LTE-A systems

Wireless Networks - Nowadays, resource allocation is one of the major problems in the cellular networks. Due to the increasing number of autonomous heterogeneous devices in future mobile networks,...     

Using the red-near infrared spectral to estimate ground cover based on vegetative indices

Rapid and accurate estimation of Ground Cover (GC) at regional and global scales for agricultural management application is only possible by using remote sensing (RS). In this study, two Vegetation Indices (VIs) including the Perpendicular Vegetation Index (PVI) and Normalized Difference Vegetation Index (NDVI) were used for estimating GC. Since the parameters of the bare soil line have an important role in calculating GC based on PVI, this line was extracted based on the red-NIRmin (minimum near infrared) method with different intervals (0.0001, 0.0005, and 0.0010). In addition to traditional statistics such as Root Mean Square Error (RMSE), the sensitivity analysis (S) was also used to sharpen the accuracy of the models' estimations. The results indicated that the PVI-based method, in contrast to the NDVI-based approach, had a better performance in estimating GC of wheat. The highest correlation between the observed GC and the estimated GC based on PVI method was achieved in interval length of 0.0005 (R2 = 0.91) with RMSE equal to 8.82. This regression line (GCEST = -3.47 + 0.96 GCOBS) was not significantly different from the 1:1 line. As expected, the best estimation was achieved when the sensitivity of estimated GC based on PVI (length of the interval: 0.0005) was almost constant and low compared to the other models.