Nanjing University of Information Science and Technology

About: Nanjing University of Information Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Precipitation & Aerosol. The organization has 14129 authors who have published 17985 publications receiving 267578 citations. The organization is also known as: Nan Xin Da.

Steganalysis of least significant bit matching using multi-order differences

Abstract: This paper presents a learning-based steganalysis/detection method to attack spatial domain least significant bit LSB matching steganography in grayscale images, which is the antetype of many sophisticated steganographic methods. We model the message embedded by LSB matching as the independent noise to the image, and theoretically prove that LSB matching smoothes the histogram of multi-order differences. Because of the dependency among neighboring pixels, histogram of low order differences can be approximated by Laplace distribution. The smoothness caused by LSB matching is especially apparent at the peak of the histogram. Consequently, the low order differences of image pixels are calculated. The co-occurrence matrix is utilized to model the differences with the small absolute value in order to extract features. Finally, support vector machine classifiers are trained with the features so as to identify a test image either an original or a stego image. The proposed method is evaluated by LSB matching and its improved version "Hugo". In addition, the proposed method is compared with state-of-the-art steganalytic methods. The experimental results demonstrate the reliability of the new detector. Copyright © 2013 John Wiley & Sons, Ltd.

Recent advances in understanding of the mechanism and control of Li2O2 formation in aprotic Li–O2 batteries

Abstract: Aprotic Li–O2 batteries represent promising alternative devices for electrical energy storage owing to their extremely high energy densities. Upon discharge, insulating solid Li2O2 forms on cathode surfaces, which is usually governed by two growth models, namely the solution model and the surface model. These Li2O2 growth models can largely determine the battery performances such as the discharge capacity, round-trip efficiency and cycling stability. Understanding the Li2O2 formation mechanism and controlling its growth are essential to fully realize the technological potential of Li–O2 batteries. In this review, we overview the recent advances in understanding the electrochemical and chemical processes that occur during the Li2O2 formation. In the beginning, the oxygen reduction mechanisms, the identification of O2−/LiO2 intermediates, and their influence on the Li2O2 morphology have been discussed. The effects of the discharge current density and potential on the Li2O2 growth model have been subsequently reviewed. Special focus is then given to the prominent strategies, including the electrolyte-mediated strategy and the cathode-catalyst-tailoring strategy, for controlling the Li2O2 growth pathways. Finally, we conclude by discussing the profound implications of controlling Li2O2 formation for further development in Li–O2 batteries.

Feature Learning for Image Classification Via Multiobjective Genetic Programming

Abstract: Feature extraction is the first and most critical step in image classification. Most existing image classification methods use hand-crafted features, which are not adaptive for different image domains. In this paper, we develop an evolutionary learning methodology to automatically generate domain-adaptive global feature descriptors for image classification using multiobjective genetic programming (MOGP). In our architecture, a set of primitive 2-D operators are randomly combined to construct feature descriptors through the MOGP evolving and then evaluated by two objective fitness criteria, i.e., the classification error and the tree complexity. After the entire evolution procedure finishes, the best-so-far solution selected by the MOGP is regarded as the (near-)optimal feature descriptor obtained. To evaluate its performance, the proposed approach is systematically tested on the Caltech-101, the MIT urban and nature scene, the CMU PIE, and Jochen Triesch Static Hand Posture II data sets, respectively. Experimental results verify that our method significantly outperforms many state-of-the-art hand-designed features and two feature learning techniques in terms of classification accuracy.

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds.

Abstract: Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol’s thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ∼27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3–5 W⋅m−2) and a surface cooling (−5 to −8 W⋅m−2). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments.