Distinguishing Computer-generated Graphics from Natural Images Based on Sensor Pattern Noise and Deep Learning

Computer-generated graphics (CGs) are images generated by computer software. The~rapid development of computer graphics technologies has made it easier to generate photorealistic computer graphics, and these graphics are quite difficult to distinguish from natural images (NIs) with the naked eye. In this paper, we propose a method based on sensor pattern noise (SPN) and deep learning to distinguish CGs from NIs. Before being fed into our convolutional neural network (CNN)-based model, these images---CGs and NIs---are clipped into image patches. Furthermore, three high-pass filters (HPFs) are used to remove low-frequency signals, which represent the image content. These filters are also used to reveal the residual signal as well as SPN introduced by the digital camera device. Different from the traditional methods of distinguishing CGs from NIs, the proposed method utilizes a five-layer CNN to classify the input image patches. Based on the classification results of the image patches, we deploy a majority vote scheme to obtain the classification results for the full-size images. The~experiments have demonstrated that (1) the proposed method with three HPFs can achieve better results than that with only one HPF or no HPF and that (2) the proposed method with three HPFs achieves 100\% accuracy, although the NIs undergo a JPEG compression with a quality factor of 75.Comment: This paper has been published by Sensors. doi:10.3390/s18041296; Sensors 2018, 18(4), 129

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Thermodynamics of Black Holes in Massive Gravity

We present a class of charged black hole solutions in an ($n+2)$-dimensional massive gravity with a negative cosmological constant, and study thermodynamics and phase structure of the black hole solutions both in grand canonical ensemble and canonical ensemble. The black hole horizon can have a positive, zero or negative constant curvature characterized by constant $k$. By using Hamiltonian approach, we obtain conserved charges of the solutions and find black hole entropy still obeys the area formula and the gravitational field equation at the black hole horizon can be cast into the first law form of black hole thermodynamics. In grand canonical ensemble, we find that thermodynamics and phase structure depends on the combination $k -\mu^2/4 +c_2 m^2$ in the four dimensional case, where $\mu$ is the chemical potential and $c_2m^2$ is the coefficient of the second term in the potential associated with graviton mass. When it is positive, the Hawking-Page phase transition can happen, while as it is negative, the black hole is always thermodynamically stable with a positive capacity. In canonical ensemble, the combination turns out to be $k+c_2m^2$ in the four dimensional case. When it is positive, a first order phase transition can happen between small and large black holes if the charge is less than its critical one. In higher dimensional ($n+2 \ge 5$) case, even when the charge is absent, the small/large black hole phase transition can also appear, the coefficients for the third ($c_3m^2$) and/or the fourth ($c_4m^2$) terms in the potential associated with graviton mass in the massive gravity can play the same role as the charge does in the four dimensional case.Comment: Latex 19 pages with 8 figure

Determinants of Chinese cross-border M&As

This paper focuses on two of the key determinants of Chinese cross-border M&A performance, industry preference and currency appreciation. Our results show that although resource-related bidders may be motivated to pursue national strategic goals, they do not sacrifice their shareholders’ wealth. The substantial RMB appreciation following the exchange rate reform leads to higher bidder abnormal returns in the short-term, with no long-term reversal. We find that the insignificant long-term abnormal returns are mainly due to the enhanced empire building invectives and other agency costs of cash-rich firms in some of the currency-driven acquisitions

Carbonate-superstructured solid fuel cells with hydrocarbon fuels

A basic requirement for solid oxide fuel cells (SOFCs) is the sintering of electrolyte into a dense impermeable membrane to prevent the mixing of fuel and oxygen for a sufficiently high open-circuit voltage (OCV). However, herein, we demonstrate a different type of fuel cell, a carbonate-superstructured solid fuel cell (CSSFC), in which in situ generation of superstructured carbonate in the porous samarium-doped ceria layer creates a unique electrolyte with ultrahigh ionic conductivity of 0.17 S.cm21 at 550 °C. The CSSFC achieves unprecedented high OCVs (1.051 V at 500 °C and 1.041 V at 550 °C) with methane fuel. Furthermore, the CSSFC exhibits a high peak power density of 215 mW.cm22 with dry methane fuel at 550 °C, which is higher than all reported values of electrolyte-supported SOFCs. This provides a different approach for the development of efficient solid fuel cells

Using quantitative analysis to assess the appropriateness of infill buildings in historic settings

Over the past 40 years or so, and more recently in developing countries, increasing attention has been paid to the preservation of historic settings; however, with continued development and urbanization, a solution is needed for the problem of how to adapt historic settings for contemporary life. Consideration of how to conserve historic settings while introducing new development has been the subject of theoretical study for many years, and despite many mistakes, excellent architectural projects have been completed. However, most research has focused on assessing such projects only at a qualitative and cognitive level; a deeper exploration is therefore needed. Thus, the main goal of this paper is to apply a scientific, quantitative approach to investigating the contextual fit of infill buildings in historic settings. This research is approached mathematically within the framework of architectural theory and visual science. To assess the potential of this methodology, a case-study building facade is analyzed using three attributes: size, proportion, and color. The findings of this research can help in evaluating the contextual fit of architectural designs and thereby lead to improved design guidance for historic settings

Variation of productivity and nutritive values of oat (Avena sativa) with geographical locations in Gansu Province of Northwest China under irrigation and fertilization conditions

Field experiments were conducted in low, medium and high sites; Jingqianghe, Huangzangsi and Lanzhou areas of Gansu Province, China from 2000 to 2001 to investigate the effects of geographicallocations on herbage dry matter (DM) yield and nutritive values of oat. It was found that the plant growing in Jingqianghe area yielded the highest forages (16046.0 DM/hm2) at high accumulation rate(300 kg ha-1d-1) and within long growing season (120 d), the plant growing in Huazangsi area produced medium quantity of forages (13020.3 DM/hm2) at low accumulation rate (200 kg ha-1d-1) but within long growing season (120 d), and the plant growing in Lanzhou area had the lowest forage yield (12505.7 kg DM/hm2) at relatively high accumulation rate (270 kg ha-1d-1) but within extremely short growing season (50 d). The highest seed production of 3789.3 kg DM/hm2 annually was observed in Huangzangsi area, the lowest seed production of 933.7 kg DM/hm2 annually was found in Jingqianghearea, and the medium seed production of 1632.7 kg DM/hm2 annually was recorded in Lanzhou area. The plant growing in high site of Jinqianghe area concentrated more (P 0.05) in in sacco degradability (ISD) of the plant among different growing sites was observed in the whole growing season. It was concluded from this study forage productionshould be conducted in high site of Jingqianghe area and seed production of oat should be conducted in low site of Lanzhou area with enough water and fertilizer supply