High-Capacity Robust Image Steganography via Adversarial Network

( Beijing Chen ),( Jiaxin Wang ),( Yingyue Chen ),( Zilong Jin ),( Hiuk Jae Shim ),( Yun-qing Shi ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.1

Steganography has been successfully employed in various applications, e.g., copyright control of materials, smart identity cards, video error correction during transmission, etc. Deep learning-based steganography models can hide information adaptively through network learning, and they draw much more attention. However, the capacity, security, and robustness of the existing deep learning-based steganography models are still not fully satisfactory. In this paper, three models for different cases, i.e., a basic model, a secure model, a secure and robust model, have been proposed for different cases. In the basic model, the functions of high-capacity secret information hiding and extraction have been realized through an encoding network and a decoding network respectively. The high-capacity steganography is implemented by hiding a secret image into a carrier image having the same resolution with the help of concat operations, InceptionBlock and convolutional layers. Moreover, the secret image is hidden into the channel B of carrier image only to resolve the problem of color distortion. In the secure model, to enhance the security of the basic model, a steganalysis network has been added into the basic model to form an adversarial network. In the secure and robust model, an attack network has been inserted into the secure model to improve its robustness further. The experimental results have demonstrated that the proposed secure model and the secure and robust model have an overall better performance than some existing high-capacity deep learning-based steganography models. The secure model performs best in invisibility and security. The secure and robust model is the most robust against some attacks.

Renewable magnetic alginate-graphene oxide hybrid for efficient cationic dye removal

Wenju Liu,Hongjuan Bai,Weiqiang Gao,Zihan Chen,Zhuangzhuang Liu,Zilong Chen,Junhang Chen 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.10

A batch system was applied to investigate the behavior of adsorption of methylene blue (MB) and crystal violet (CV) from aqueous solution using a renewable magnetic alginate composite containing graphene oxide (M-GO/ Alg) in single and binary systems. The surface morphology and chemical structure of the adsorbent were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and vibrating sample magnetometer (VSM) analysis. The experimental data were fitted by the isotherm models and adsorption kinetics. And the maximum adsorption quantity of MB and CV reached 459.85 and 69.46mg/g at 298 K for M-GO/ Alg, respectively, as deduced from Langmuir model. After five successive adsorptive removal cycles for both dyes, no significant performance loss was observed for M-GO/Alg. Moreover, M-GO/Alg was easily separated under an external magnetic field. In binary system, MB and CV exhibited competitive adsorption. The obtained results suggested that M-GO/Alg can be used as an eco-friendly and recyclable adsorbent to remove cationic dyes from aqueous solutions.

High-breakdown-voltage GaN-based vertical FinFET design

Zilong Wang,Liang Liu,Peiyue Qi,Jiawei Chen,Lixia Zhao 전력전자학회 2024 JOURNAL OF POWER ELECTRONICS Vol.24 No.3

In this study, GaN-based vertical FinFET device using HfO 2 as a high-κ dielectric gate layer to improve the breakdown voltage is designed. Simulation results show that a breakdown voltage as high as 2139 V can be achieved for the optimized GaN-based FinFET with a fin channel width of 200 nm, a channel doping concentration of 1 × 10 16 cm −3 , and a drift layer thickness of 10 μm. In addition, the proposed device has a low specific on-state resistance of 0.84 mΩ cm 2 , resulting in a large Baliga optimum figure of merit (FOM) 5.45 GW cm −2 . This work could lay a foundation to further improve the electrical performance of GaN-based vertical FinFET devices.

A Triple Residual Multiscale Fully Convolutional Network Model for Multimodal Infant Brain MRI Segmentation

( Yunjie Chen ),( Yuhang Qin ),( Zilong Jin ),( Zhiyong Fan ),( Mao Cai ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.3

The accurate segmentation of infant brain MR image into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is very important for early studying of brain growing patterns and morphological changes in neurodevelopmental disorders. Because of inherent myelination and maturation process, the WM and GM of babies (between 6 and 9 months of age) exhibit similar intensity levels in both T1-weighted (T1w) and T2-weighted (T2w) MR images in the isointense phase, which makes brain tissue segmentation very difficult. We propose a deep network architecture based on U-Net, called Triple Residual Multiscale Fully Convolutional Network (TRMFCN), whose structure exists three gates of input and inserts two blocks: residual multiscale block and concatenate block. We solved some difficulties and completed the segmentation task with the model. Our model outperforms the U-Net and some cutting-edge deep networks based on U-Net in evaluation of WM, GM and CSF. The data set we used for training and testing comes from iSeg-2017 challenge (http://iseg2017.web.unc.edu).

An Interactive Perspective Scene Completion Framework Guided by Complanate Mesh

( Chuanyan Hao ),( Zilong Jin ),( Zhixin Yang ),( Yadang Chen ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.1

This paper presents an efficient interactive framework for perspective scene completion and editing tasks, which are available largely in the real world but rarely studied in the field of image completion. Considering that it is quite hard to extract perspective information from a single image, this work starts from a friendly and portable interactive platform to obtain the basic perspective data. Then, in order to make this interface less sensitive, easier and more flexible, a perspective-rectification based correction mechanism is proposed to iteratively update the locations of the initial points selected by users. At last, a complanate mesh is generated by the geometry calculations from these corrected initial positions. This mesh must approximate the perspective direction and the structure topology as much as possible so that the filling process can be conducted under the constraint of the perspective effects of the original image. Our experiments show the results with good qualities and performances, and also demonstrate the validity of our approaches by various perspective scenes and images.

Background Error Statistics for Aerosol Variables from WRF/Chem Predictions in Southern California

Zengliang Zang,Zilong Hao,Xiaobin Pan,Zhijin Li,Dan Chen,Li Zhang,Qinbin Li 한국기상학회 2015 Asia-Pacific Journal of Atmospheric Sciences Vol.51 No.2

Background error covariance (BEC) is crucial in data assimilation. This paper addresses the multivariate BEC associated with black carbon, organic carbon, nitrates, sulfates, and other constituents of aerosol species. These aerosol species are modeled and predicted using the Model for Simulating Aerosol Interactions and Chemistry scheme (MOSAIC) in the Weather Research and Forecasting/Chemistry (WRF/Chem) model at a resolution of 4 km in Southern California. The BEC is estimated from the differences between the 36-hour and 12-hour forecasts using the NMC method. The results indicated that the maximum background error standard deviation is associated with nitrate and is larger than that of black carbon, organic carbon, and sulfate. The horizontal and vertical scale of the correlation of nitrate is much smaller than that of other species. A significant cross-correlation is found between the species of black carbon and organic carbon. The cross-correlations between nitrate and other variables are relatively smaller and exhibit a relatively smaller length scale. Single observation data assimilation experiments are performed to illustrate the effect of the BEC on analysis increments.

Microwave Absorption Enhancement of Fe/C Core–Shell Hybrid Derived from a Metal-Organic Framework

Liuyang Heng,Zilong Zhang,Shuai Wang,Xiqiao Chen,Xiubo Jia,Zhixiang Tang,Yanhong Zou 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2019 NANO Vol.14 No.1

Core–shell structured Fe/C have been successfully derived from a metal-organic framework for microwave absorbing. Based on the measured electromagnetic parameters, it is found that the maximum reflection loss (RL) of Fe/C reaches 40 dB at 5.8 GHz with a thickness of 3.0 mm and the broadest absorption bandwidth (RL < -10 dB) is up to 6.0 GHz (from 11.2 to 17.2 GHz) with a thickness of 1.5 mm. The excellent microwave absorption is mainly ascribed to the multiple reflections, good impedance matching, dielectric loss and interface polarization originating from the core–shell structure. It is believed that Fe/C can be a promising microwave absorbing material.

Study on preparation of inorganic binder stabilized material with large dosage of phosphogypsum

Sun Qiqi,Tao Liangjing,Li Xin,Xu Wei,Yao Shuo,Li Jinpeng,Ren Qi-Fang,Chen Yue’e,Xu Chunshan,Wu Zilong,Zhu Yuelei,Ding Yi,오원춘 한국세라믹학회 2023 한국세라믹학회지 Vol.60 No.6

With the rapid development of the phosphorus chemical industry, a large amount of phosphogypsum (PG) is discharged. The impurities in PG pollute the surrounding soil, the groundwater and the air in the long-term storage. In this paper, PG as the main raw material is used to study the stable material of inorganic binder in the condition of large dosage of PG. With PG and graded gravel as stabilized materials, and cement and fly ash as binder, materials are mixed to determine the influence of PG ratio and the amount of activator on the mixture. The results show that the mechanical strength of the mixture increased first and then decreased with the increase in the proportion of PG replacing graded gravel in the mixture. The activator significantly improves the properties of the material system and makes a significant contribution to the curing of PG. The best ratio of pretreated PG: cement: fly ash: aggregate is 50:6:5:39. The amount of activator added by the external mixing method is 0.3%, which can make the unconfined compressive strength reach 4.1 MPa after 7d. Finally, water-soluble phosphorus leaching experiment is conducted for all the samples. The results show that phosphorus leaching is so little that no secondary pollution of the environment is caused.