Image Aesthetics Assessment Using Composite Features from off-the-Shelf Deep Models

Deep convolutional neural networks have recently achieved great success on image aesthetics assessment task. In this paper, we propose an efficient method which takes the global, local and scene-aware information of images into consideration and exploits the composite features extracted from corresponding pretrained deep learning models to classify the derived features with support vector machine. Contrary to popular methods that require fine-tuning or training a new model from scratch, our training-free method directly takes the deep features generated by off-the-shelf models for image classification and scene recognition. Also, we analyzed the factors that could influence the performance from two aspects: the architecture of the deep neural network and the contribution of local and scene-aware information. It turns out that deep residual network could produce more aesthetics-aware image representation and composite features lead to the improvement of overall performance. Experiments on common large-scale aesthetics assessment benchmarks demonstrate that our method outperforms the state-of-the-art results in photo aesthetics assessment.Comment: Accepted by ICIP 201

Exploring Network Effects of Point-to-Point Networks: An Investigation of the Spatial Entry Patterns of Southwest Airlines

This paper explores network effects in Point-to-Point airline networks by examining the spatial entry patterns of Southwest airlines during the 1990-2006 period. Estimation results from a spatial probit model reveal clear spatial dependence in profitability across different routes served by the carrier. Detailed investigation suggests two main sources of network effects, namely: (1) airport and regional presence, and (2) substitutability of markets. Findings of the paper suggest also that the network effects embedded in Southwest’s Point-to-Point network have many distinguishing features as compared to those identified in a typical Hub-and-Spoke network. This study brings some fresh insights on airline network effects in general, as well as explaining the pattern of aggressive network expansions of LCCs in particular.Point-to-Point Networks, spatial entry patterns, Southwest airlines, spatial probit model

Social inclusion of Chinese immigrants in Portugal: The roles of length of residence and social networks

Focusing on Chinese immigrants, this study investigated the role of length of residence and social networks on social inclusion, which we operationalized as psychological adaptation, socio-cultural adaptation, economic adaptation and political participation in the Portuguese society. The study found that:(a) Chinese immigrants’ overall social networks was positively correlated with psychological adaptation and socio-cultural adaptation; (b)Chinese immigrants’ length of residence in the host society was positively related to psychological adaptation and socio-cultural adaptation; (c) The overall social networks but not differentiated networks mediated the relationship between immigrants’ length of residence and their socio-cultural adaptation and the relationship between length of residence and psychological adaptation. Limitations of the study and implications for further research were discussed

Atomistic Simulation of Anistropic Crystal Structures at Nanoscale

Multiscale simulations of atomistic/continuum coupling in computational materials science, where the scale expands from macro-/micro- to nanoscale, has become a hot research topic. These small units, usually nanostructures, are commonly anisotropic. The development of molecular modeling tools to describe and predict the mechanical properties of structures reveals an undeniable practical importance. Typical anisotropic structures (e.g. cubic, hexagonal, monoclinic) using DFT, MD, and atomic finite element methods are especially interesting, according to the modeling requirement of upscaling structures. It therefore connects nanoscale modeling and continuous patterns of deformation behavior by identifying relevant parameters from smaller to larger scales. These methodologies have the prospect of significant applications. I would like to recommend this book to both beginners and experienced researchers