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| 1 | A Fusion Steganographic Algorithm Based on Faster R-CNN显示文摘The aim of information hiding is to embed the secret message in a normal cover media such as image,video,voice or text,and then the secret message is transmitted through the transmission of the cover media.The secret message should not be damaged on the process of the cover media.In order to ensure the invisibility of secret message,complex texture objects should be chosen for embedding information.In this paper,an approach which corresponds multiple steganographic algorithms to complex texture objects was presented for hiding secret message.Firstly,complex texture regions are selected based on a kind of objects detection algorithm.Secondly,three different steganographic methods were used to hide secret message into the selected block region.Experimental results show that the approach enhances the security and robustness. | Ruohan Meng Steven G.Rice Jin Wang Xingming Sun | 2018 | Computers, Materials & Continua2018，，4： | 4 |
| 2 | Donor-Acceptor Typed AIE Luminogens with Near-infrared Emission for Super-resolution Imaging显示文摘Aggregation-induced emission(AIE)luminogens(AIEgens)with high brightness in aggregates exhibit great potentials in biological imaging,but these AIEgens are seldom applied in super-resolution biological imaging,especially in the imaging by using the structural illumination microscope(SIM).Based on this consideration,we synthesized the donor-acceptor typed AIEgen of DTPA-BTN,which not only owns high brightness in the near-infrared(NIR)emission region from 600 nm to 1000 nm(photoluminescence quantum yield,PLQYs=11.35%),but also displays excellent photo-stability.In addition,AIE nanoparticles based on 4,7-ditriphenylamine-[1,2,5]-thiadiazolo[3,4-c]pyridine(DTPA-BTN)were also prepared with highly emissive features and excellent biocompatibility.Finally,the developed DTPA-BTN-based AIE nanoparticles were applied in the super-resolution cellular imaging via SIM,where much smaller full width at half-maximum values and high signal to noise ratios were obtained,indicating the superior imaging resolution.The results here imply that highly emissive AIEgens or AIE nanoparticles can be promising imaging agents for super-resolution imaging via SIM. | SHEN Qifei XU Ruohan WANG Zhi ZHAO Tianyu ZHOU Yu XU Yanzi YANG Zhiwei LEI Ming MENG Lingjie DANG Dongfeng | 2021 | Chemical Research in Chinese Universities2021，37，1： | 0 |
| 3 | Health benefits from the rapid reduction in ambient exposure to air pollutants after China’s clean air actions:progress in efficacy and geographic equality显示文摘Clean air actions(CAAs)in China have been linked to considerable benefits in public health.However,whether the beneficial effects of CAAs are equally distributed geographically is unknown.Using high-resolution maps of the distributions of major air pollutants(fine particulate matter[PM_(2.5)]and ozone[O_(3)])and population,we aimed to track spatiotemporal changes in health impacts from,and geographic inequality embedded in,the reduced exposures to PM_(2.5)and O_(3)from 2013 to 2020.We used a method established by the Global Burden of Diseases Study.By analyzing the changes in loss of life expectancy(LLE)attributable to PM_(2.5)and O_(3),we calculated the gain of life expectancy(GLE)to quantify the health benefits of the air-quality improvement.Finally,we assessed the geographic inequality embedded in the GLE using the Gini index(GI).Based on risk assessments of PM_(2.5)and O_(3),during the first stage of CAAs(2013 to 2017),the mean GLE was 1.87 months.Half of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed(GI 0.44).During the second stage of CAAs(2017 to 2020),the mean GLE increased to 3.94 months and geographic inequality decreased(GI 0.18).According to our assessments,CAAs were enhanced,from the first to second stages,in terms of not only preventing premature mortality but also ameliorating health inequalities.The enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM_(2.5)and O_(3)levels.Our findings will contribute to optimizing future CAAs. | Tao Xue Ruohan Wang Meng Wang Yanying Wang Dan Tong Xia Meng Conghong Huang Siqi Ai Fangzhou Li Jingyuan Cao Mingkun Tong Xueqiu Ni Hengyi Liu Jianyu Deng Hong Lu Wei Wan Jicheng Gong Shiqiu Zhang Tong Zhu | 2024 | National Science Review2024，11，2： | 0 |
| 4 | Synthesis of D-A typed AIE luminogens in isomeric architecture and their application in latent fingerprints imaging显示文摘Among the emitters in powder dusting to visualize the latent fingerprints(LFPs),aggregation-induced emission luminogens(AIEgens)are well employed for their high brightness and resistance to photobleaching.However,the serious background interference and low resolution still limit their fast development.Therefore,to further enhance the signal-to-noise ratio in LFPs imaging,especially to improve the analysis for level 3 details,donor-acceptor(D-A)typed AIEgens of DTPA-2,3-P,DTPA-2,5-P and DTPA-2,6-P are designed here.It is observed that strong emission covering from 450nm to 650nm can be obtained for all these molecules,especially that a high PLQY value of 10.06%in solids is achieved in DTPA-2,3-P.This is much higher than that of the other two cases(0.80%and 0.51%).By utilizing the DTPA-2,3-P in powder dusting,fluorescence imaging of LFPs can be clearly captured on both smooth and rough substrates.Moreover,confocal laser scanning microscope(CLSM)enables us to achieve high-resolution LFPs imaging in both 2D and 3D views,providing more detailed information of fingerprints pores in width,distance,distribution,and shapes.The results here demonstrate that highly emissive AIEgen of DTPA-2,3-P could be an excellent candidate for the visualization of fingerprints,thus providing the potential application in criminal investigation in the future. | Peijuan Zhang Qifei Shen Yu Zhou Fengyi He Bo Zhao Zhi Wang Ruohan Xu Yanzi Xu Zhiwei Yang Lingjie Meng Dongfeng Dang | 2023 | Chinese Chemical Letters2023，34，8： | 0 |
| 5 | A Novel Steganography Scheme Combining Coverless Information Hiding and Steganography显示文摘At present,the coverless information hiding has been developed.However,due to the limited mapping relationship between secret information and feature selection,it is challenging to further enhance the hiding capacity of coverless information hiding.At the same time,the steganography algorithm based on object detection only hides secret information in foreground objects,which contribute to the steganography capacity is reduced.Since object recognition contains multiple objects and location,secret information can be mapped to object categories,the relationship of location and so on.Therefore,this paper proposes a new steganography algorithm based on object detection and relationship mapping,which integrates coverless information hiding and steganography.In this method,the coverless information hiding is realized by mapping the object type,color and secret information in object detection method.At the same time,the object detection method is used to find the safe area to hide secret messages.The proposed algorithm can not only improve the steganographic capacity of the two information hiding methods but also make the coverless information hiding more secure and robust. | Ruohan Meng Zhili Zhou Qi Cui Xingming Sun Chengsheng Yuan | 2019 | Journal of Information Hiding and Privacy Protection2019，1，1： | 0 |
| 6 | A Survey of Image Information Hiding Algorithms Based on Deep Learning显示文摘With the development of data science and technology,information security has been further concerned.In order to solve privacy problems such as personal privacy being peeped and copyright being infringed,information hiding algorithms has been developed.Image information hiding is to make use of the redundancy of the cover image to hide secret information in it.Ensuring that the stego image cannot be distinguished from the cover image,and sending secret information to receiver through the transmission of the stego image.At present,the model based on deep learning is also widely applied to the field of information hiding.This paper makes an overall conclusion on image information hiding based on deep learning.It is divided into four parts of steganography algorithms,watermarking embedding algorithms,coverless information hiding algorithms and steganalysis algorithms based on deep learning.From these four aspects,the state-of-the-art information hiding technologies based on deep learning are illustrated and analyzed. | Ruohan Meng Qi Cui Chengsheng Yuan | 2018 | Computer Modeling in Engineering & Sciences2018，，12： | 0 |
| 7 | A Novel Steganography Algorithm Based on Instance Segmentation显示文摘Information hiding tends to hide secret information in image area where is rich texture or high frequency,so as to transmit secret information to the recipient without affecting the visual quality of the image and arousing suspicion.We take advantage of the complexity of the object texture and consider that under certain circumstances,the object texture is more complex than the background of the image,so the foreground object is more suitable for steganography than the background.On the basis of instance segmentation,such as Mask R-CNN,the proposed method hides secret information into each object's region by using the masks of instance segmentation,thus realizing the information hiding of the foreground object without background.This method not only makes it more efficient for the receiver to extract information,but also proves to be more secure and robust by experiments. | Ruohan Meng Qi Cui Zhili Zhou Chengsheng Yuan Xingming Sun | 2020 | Computers, Materials & Continua2020，，4： | 0 |
| 8 | A Derivative Matrix-Based Covert Communication Method in Blockchain显示文摘The data in the blockchain cannot be tampered with and the users are anonymous,which enables the blockchain to be a natural carrier for covert communication.However,the existing methods of covert communication in blockchain suffer from the predefined channel structure,the capacity of a single transaction is not high,and the fixed transaction behaviors will lower the concealment of the communication channel.Therefore,this paper proposes a derivation matrix-based covert communication method in blockchain.It uses dual-key to derive two types of blockchain addresses and then constructs an address matrix by dividing addresses into multiple layers to make full use of the redundancy of addresses.Subsequently,to solve the problem of the lack of concealment caused by the fixed transaction behaviors,divide the rectangular matrix into square blocks with overlapping regions and then encrypt different blocks sequentially to make the transaction behaviors of the channel addresses match better with those of the real addresses.Further,the linear congruence algorithm is used to generate random sequence,which provides a random order for blocks encryption,and thus enhances the security of the encryption algorithm.Experimental results show that this method can effectively reduce the abnormal transaction behaviors of addresses while ensuring the channel transmission efficiency. | Xiang Zhang Xiaona Zhang Xiaorui Zhang Wei Sun Ruohan Meng Xingming Sun | 2023 | Computer Systems Science & Engineering2023，46，7： | 0 |
| 9 | LKAW: A Robust Watermarking Method Based on Large Kernel Convolution and Adaptive Weight Assignment显示文摘Robust watermarking requires finding invariant features under multiple attacks to ensure correct extraction.Deep learning has extremely powerful in extracting features,and watermarking algorithms based on deep learning have attracted widespread attention.Most existing methods use 3×3 small kernel convolution to extract image features and embed the watermarking.However,the effective perception fields for small kernel convolution are extremely confined,so the pixels that each watermarking can affect are restricted,thus limiting the performance of the watermarking.To address these problems,we propose a watermarking network based on large kernel convolution and adaptive weight assignment for loss functions.It uses large-kernel depth-wise convolution to extract features for learning large-scale image information and subsequently projects the watermarking into a highdimensional space by 1×1 convolution to achieve adaptability in the channel dimension.Subsequently,the modification of the embedded watermarking on the cover image is extended to more pixels.Because the magnitude and convergence rates of each loss function are different,an adaptive loss weight assignment strategy is proposed to make theweights participate in the network training together and adjust theweight dynamically.Further,a high-frequency wavelet loss is proposed,by which the watermarking is restricted to only the low-frequency wavelet sub-bands,thereby enhancing the robustness of watermarking against image compression.The experimental results show that the peak signal-to-noise ratio(PSNR)of the encoded image reaches 40.12,the structural similarity(SSIM)reaches 0.9721,and the watermarking has good robustness against various types of noise. | Xiaorui Zhang Rui Jiang Wei Sun Aiguo Song Xindong Wei Ruohan Meng | 2023 | Computers, Materials & Continua2023，，4： | 0 |
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