An Image Steganography Algorithm based on the Quantitative Features of Higher Order Local Model

Hao Huang,Zhiping Zhou 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.7

HUGO is the content-based adaptive steganography method for spatial images which can approximately preserve the joint statistic of differences between up to four neighboring pixels in four different directions. But the steganalysis method based on the higher order local model can fail HUGO. In view of the above problem, an improved steganography is proposed. Firstly, by analyzing the higher order local model, the distortion function is defined based on the quantitative MINMAX features. Then, combined with the theoretical framework of the Gibbs construction in steganography, the improved image steganography algorithm is proposed. The experimental results show that the proposed algorithm can not only resist the detection of the steganalysis method based on the quantitative MINMAX features , but also resist the detection of the steganalysis method based on the hybrid quantitative MINMAX features.

Temporal expression profiling of long noncoding RNA and mRNA in the peripheral blood during porcine development

Gu, Yiren,Zhou, Rui,Jin, Long,Tao, Xuan,Zhong, Zhijun,Yang, Xuemei,Liang, Yan,Yang, Yuekui,Wang, Yan,Chen, Xiaohui,Gong, Jianjun,He, Zhiping,Li, Mingzhou,Lv, Xuebin Asian Australasian Association of Animal Productio 2020 Animal Bioscience Vol.33 No.5

Objective: We investigated the temporal expression profiles of long noncoding RNA (lncRNA) and mRNA in the peripheral blood of pigs during development and identified the lncRNAs that are related to the blood-based immune system. Methods: Peripheral blood samples were obtained from the pigs at 0, 7, 28, and 180 days and 2 years of age. RNA sequencing was performed to survey the lncRNA and mRNA transcriptomes in the samples. Short time-series expression miner (STEM) was used to show temporal expression patterns in the mRNAs and lncRNAs. Gene ontology and Kyoto encyclopedia of genes and genomes analyses were performed to assess the genes' biological relevance. To predict the functions of the identified lncRNAs, we extracted mRNAs that were nearby loci and highly correlated with the lncRNAs. Results: In total of 5,946 lncRNA and 12,354 mRNA transcripts were identified among the samples. STEM showed that most lncRNAs and mRNAs had similar temporal expression patterns during development, indicating the expressional correlation and functional relatedness between them. The five stages were divided into two classes: the suckling period and the late developmental stage. Most genes were expressed at low level during the suckling period, but at higher level during the late stages. Expression of several T-cell-related genes increased continuously during the suckling period, indicating that these genes are crucial for establishing the adaptive immune system in piglets at this stage. Notably, lncRNA TCONS-00086451 may promote blood-based immune system development by upregulating nuclear factor of activated T-cells cytoplasmic 2 expression. Conclusion: This study provides a catalog of porcine peripheral blood-related lncRNAs and mRNAs and reveals the characteristics and temporal expression profiles of these lncRNAs and mRNAs during peripheral blood development from the newborn to adult stages in pigs.

A Novel Spectral Clustering Based on Nonlinear Low Dimensional Embedding Feature Selection

Daowen Zhang,Zhiping Zhou 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.8

Spectral clustering is a clustering method based on algebraic graph theory. It has solid theoretical foundation and good performance of clustering. However, during the process of nonlinear low rank approximation, the traditional spectral clustering algorithm can’t effectively remove redundant features leading to the phenomenon that the local area can not distinguish. It also suffers from the high computational complexity of eigen-decomposition when dealing with the high dimensional data. In order to resolve the aforementioned problems, in this paper a novel Spectral clustering algorithm called LF-SC is proposed. Firstly, based on the nonlinear low dimensional embedding feature selection, we realize dimension reduction. The multi clustering structure of the data is captured, the potential manifold structure is fully discovered, and the geometry structure of the low dimensional manifold clustering is well maintained. Secondly, utilizing the SVD instead of EVD to obtain the eigenvectors reduces the computational complexity and maintain the local structure of the data as well as low dimensional manifold. Extensive experiments show the effectiveness and efficiency of our approach.

Graphene oxide template-confined fabrication of hierarchical porous carbons derived from lignin for ultrahigh-efficiency and fast removal of ciprofloxacin

Wenna Ge,Zhiping Zhou,Peng Zhang,Qingfang Zhang,Zhen Cao,Ruilong Zhang,Yongsheng Yan,Jiangdong Dai 한국공업화학회 2018 Journal of Industrial and Engineering Chemistry Vol.66 No.-

Here, a new hierarchical porous carbon was first prepared from sodium lignosulphonate (SLS), an industrial by-product, via a confined carbonization and alkali activation methods using graphene oxide (GO) as template, and was used for ciprofloxacin (CIP) removal. The addition of GO nanosheets remarkably affected the morphology and pore structure. GLHPC-1, obtained at GO/SLS weight ratio of 1:100, possess a largest specific surface area of 3223 m2 g−1 and pore volume of 2.275 cm3 g−1, and thus exhibited an ultrahigh adsorption of 980.4 mg g−1 at 318 K and fast adsorption rate, as well as a good recycle ability in practice.

An Image Spatial Domain Steganography Algorithm with High Payload, Commendable Perceptual Quality and High Statistical Un-detectability

Hao Huang,Zhiping Zhou 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.9

The Octonary PVD algorithm is the method that simultaneously achieves three contradicting objectives, high payload, commendable perceptual quality and high statistical un-detectability. However, the Octonary PVD algorithm has a major defect that it does not embed the secret data in the optimum locations because it does not consider the use of different pixel groups will have different effects on the statistical undetectability and payload of the stego image in the process of embedding. In view of the above problem, an improved steganography is proposed. An improved objective function which is used by the PSO module is defined at first in this proposed method. Then, an improved data hiding scheme is proposed. The proposed algorithm is an improved method based on the Octonary PVD algorithm, and the improved objective function which be used by the PSO module is set in such a way that both perceptual quality and statistical un-detectability are considered. This proposed algorithm has high statistical un-detectability and high payload with commendable visual quality. An extensive experimental evaluation has demonstrated the excellent performance of the proposed algorithm compared with other existing image spatial domain steganography algorithms.

Affinity Propagation Algorithm Based on Locality Preserving Projections and Particle Swarm Optimization

Lele Liu,Zhiping Zhou,Jiefeng Wang 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.6

Affinity propagation algorithm is a new powerful and effective clustering method. One of the major problems in clustering is the determination of the optimal number of clusters. In this paper, the particle swarm optimization algorithm is utilized to cope with this problem by using the parameter p as each particle and Silhouette index as the fitness, which can search for the optimal value of p and determine the optimal number of clusters automatically. Moreover, the problem of information overlap is the main drawback of affinity propagation algorithm in dealing with complex structure or high dimensional data for clustering. Hence the enhanced Locality preserving projections method is proposed to integrate with affinity propagation algorithm to reduce the dimension of the data as a processing step. As the result of experiment shows, the proposed method can simultaneously obtain the optimal number of clusters accurately and improve the clustering accuracy by eliminating the redundant information of the data without losing the internal nonlinear structure.

A 3-prismatic-revolute-spherical compliant parallel platform for optoelectronic packaging

Hongwei Xu,Haibo Zhou,Shuaixia Tan,Zhiping Kong,Ji-An Duan 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.6

To align the optical channels of optoelectronic appliances, a 3-prismaticrevolute-spherical (3-PRS) compliant parallel platform (CPP) is proposed in this work. The platform has special large stroke compliant joints. Attention is paid to the establishment of the inverse kinematics model and the analysis of the parasitic motion (PM) of the platform. A prototype of the platform is also presented, and its accuracy is experimentally evaluated. Besides, the platform is employed as a 3 degree-of-freedom (DOF) platform for optoelectronic packaging. Furthermore, the closed-loop control strategy requires merely one optical power meter to avoid the use of complex multiple DOF detection devices. In this respect, the influence of the precision of inverse kinematics solution on the optoelectronic packaging is reduced. Moreover, a compensation rule is employed to minimize the effect of PM on the motion accuracy of the platform. The results show that the proposed 3-PRS CPP is highly efficient for optoelectronic packaging.

A tailored molecular imprinting ratiometric fluorescent sensor based on red/blue carbon dots for ultrasensitive tetracycline detection

Xiqing Liu,Tao Wang,Wenjuan Wang,Zhiping Zhou,Yongsheng Yan 한국공업화학회 2019 Journal of Industrial and Engineering Chemistry Vol.72 No.-

The molecular imprinting ratiometricfluorescence sensor has exhibited great potential in biological andenvironmental detection because of the combination between the excellent selectivity of molecularimprinting technique and outstanding robustness of ratiometric measurement methods On this basis,two kinds of different well-resolved wavelengths and high-fluorescent carbon dots (CDs) were preparedby various solvent extraction using osmanthus fragrans leaves as carbon source. Then the ratiometricfluorescence sensor (MIPs@rCDs/bCDs@SiO2) has been constructed by the obtained CDs which the redemissionCDs (rCDs) were used to responsive signal and the blue-emission CDs (bCDs) was served asreference signal and applied for highly selective and excellent sensitive detection of tetracycline (TC). Under optimum conditions, the ratiometricfluorescence MIPs@rCDs/bCDs@SiO2 sensor has alsoexhibited lower detection limit of 1.19 nM and the linear range of 0–50 nM. The ratiometricfluorescencesensor was further successfully employed to the determination of TC in water samples gathered fromlocal river water and tap water, indicating its great worth toward water sample analysis in complicatedenvironments.

Dependence of Dishing on Fluid Pressure during Chemical Mechanical Polishing

C. Fred Higgs,Sum Huan Ng,Chunhong Zhou,Inho Yoon,Robert Hight,Zhiping Zhou,LipKong Yap,Steven Danyluk 한국트라이볼로지학회 2002 한국트라이볼로지학회 학술대회 Vol.2002 No.10

Chemical mechanical polishing (CMP) is a manufacturing process that uses controlled wear to planarize dielectric and metallic layers on silicon wafers. CMP experiments revealed that a sub-ambient film pressure developed at the wafer/pad interface. Additionally, dishing occurs in CMP processes when the copper-in-trench lines are removed at a rate higher than the barrier layer. In order to study dishing across a stationary wafer during polishing, dishing maps were created. Since dishing is a function of the total contact pressure resulting from the applied load and the fluid pressure, the hydrodynamic pressure model was refined and used in an existing model to study copper dishing. Density maps, highlighting varying levels of dishing across the wafer face at different radial positions, were developed. This work will present the results.

Nicotinamide Mononucleotide Adenylyl Transferase 2 Inhibition Aggravates Neurological Damage after Traumatic Brain Injury in a Rat Model

Xiaoyu Gu,Haibo Ni,XuGang Kan,Chen Chen,Zhiping Zhou,Zheng Ding,Di Li,Bofei Liu 대한신경외과학회 2023 Journal of Korean neurosurgical society Vol.66 No.4

Objective : Nicotinamide mononucleotide adenylyl transferase 2 (NMNAT2) is a crucial factor for the survival of neuron. The role of NMNAT2 in damage following traumatic brain injury (TBI) remains unknown. This study was designed to investigate the role of NMNAT2 in TBI-induced neuronal degeneration and neurological deficits in rats. Methods : The TBI model was established in Sprague-Dawley rats by a weight-dropping method. Real-time polymerase chain reaction, western blot, immunofluorescence, Fluoro-Jade C staining, and neurological score analyses were carried out. Results : NMNAT2 mRNA and protein levels were increased in the injured-side cortex at 6 hours and peaked 12 hours after TBI. Knocking down NMNAT2 with an injection of small interfering RNA in lateral ventricle significantly exacerbated neuronal degeneration and neurological deficits after TBI, which were accompanied by increased expression of BCL-2-associated X protein (Bax). Conclusion : NMNAT2 expression is increased and NMNAT2 exhibits neuroprotective activity in the early stages after TBI, and Bax signaling pathway may be involved in the process. Thus, NMNAT2 is likely to be an important target to prevent secondary damage following TBI.