http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Multi-focus Image Fusion with Cartoon-Texture Image Decomposition
Yongxin Zhang,Hongan Li,Zhihua Zhao 보안공학연구지원센터(IJSIP) 2015 International Journal of Signal Processing, Image Vol.8 No.1
Multi-focus image fusion can fuse multiple source images with different focus settings into a single image that appears sharper. How to effectively and completely represent the source images is the key to multi-focus image fusion. A multi-component fusion method is proposed for multi-focus image fusion. The registered source images are decomposed into cartoon and texture components by cartoon-texture image decomposition. The salient features are selected from the cartoon and texture components respectively to form a composite feature space. The local features that represent the salient information of the source images are integrated to construct the fused image. According to the visual perception and objective evaluations on the fused images, the proposed method works better in extracting the focused regions and improving the fusion quality, compared with the other existing single-component fusion methods.
Tursun, Xirali,Zhao, Yongxin,Talat, Zulfiya,Xin, Xuelei,Tursun, Adila,Abdulla, Rahima,AkberAisa, Haji The Korean Society of Applied Pharmacology 2016 Biomolecules & Therapeutics(구 응용약물학회지) Vol.24 No.2
Rosa rugosa Thunb, a deciduous shrub of the genus Rosa, has been widely used to treat stomach aches, diarrhoea, pain, and chronic inflammatory disease in eastern Asia. In recent years, our research team has extensively studied the Rosa rugosa flower extract, and specifically undertook pharmacological experiments which have optimized the extraction process. Our methods have yielded a standard extract enriched in phenolic compounds, named PRE. Herein, we expand our efforts and evaluated the anti-inflammatory activity of PRE on lipopolysaccharide (LPS)-induced inflammation in RAW 264.7 macrophages. PRE significantly inhibited production of nitric oxide (NO), prostaglandin $E_2(PGE_2)$, tumor necrosis factor (TNF)-${\alpha}$, interleukin (IL)-6, and interleukin $1{\beta}$ (IL-$1{\beta}$), as well as expression of their synthesizing enzymes, inducible nitric oxide synthase (iNOS) and cyclooxygenase2 (COX-2). Furthermore, PRE inhibited activity of mitogen-activated protein kinases (MAPK) as well as nuclear factor-kappa B (NF-${\kappa}B$) signaling pathway. Our findings are the first to explain the anti-inflammatory mechanism by PRE in LPS-stimulated macrophages. Given these results, we propose that PRE has therapeutic potential in the prevention of inflammatory disorders.
Xirali Tursun,Yongxin Zhao,Zulfiya Talat,Xuelei Xin,AdilaTursun,Rahima Abdulla,Haji AkberAisa 한국응용약물학회 2016 Biomolecules & Therapeutics(구 응용약물학회지) Vol.24 No.2
Rosa rugosa Thunb, a deciduous shrub of the genus Rosa, has been widely used to treat stomach aches, diarrhoea, pain, and chronic inflammatory disease in eastern Asia. In recent years, our research team has extensively studied the Rosa rugosa flower extract, and specifically undertook pharmacological experiments which have optimized the extraction process. Our methods have yielded a standard extract enriched in phenolic compounds, named PRE. Herein, we expand our efforts and evaluated the antiinflammatory activity of PRE on lipopolysaccharide (LPS)-induced inflammation in RAW 264.7 macrophages. PRE significantly inhibited production of nitric oxide (NO), prostaglandin E2 (PGE2), tumor necrosis factor (TNF)-α, interleukin (IL)-6, and interleukin 1β (IL-1β), as well as expression of their synthesizing enzymes, inducible nitric oxide synthase (iNOS) and cyclooxygenase2 (COX-2). Furthermore, PRE inhibited activity of mitogen-activated protein kinases (MAPK) as well as nuclear factor-kappa B (NF-κB) signaling pathway. Our findings are the first to explain the anti-inflammatory mechanism by PRE in LPS-stimulated macrophages. Given these results, we propose that PRE has therapeutic potential in the prevention of inflammatory disorders.
A Method for Generating Malware Countermeasure Samples Based on Pixel Attention Mechanism
Xiangyu Ma,Yuntao Zhao,Yongxin Feng,Yutao Hu 한국인터넷정보학회 2024 KSII Transactions on Internet and Information Syst Vol.18 No.2
Studies have shown that malware has become a primary means of attacking the Internet. Therefore, adversarial samples have become a vital breakthrough point for studying malware. By studying adversarial samples, we can gain insights into the behavior and characteristics of malware, evaluate the performance of existing detectors in the face of deceptive samples, and help to discover vulnerabilities and improve detection methods for better performance. However, existing adversarial sample generation methods still need help regarding escape effectiveness and mobility. For instance, researchers have attempted to incorporate perturbation methods like Fast Gradient Sign Method (FGSM), Projected Gradient Descent (PGD), and others into adversarial samples to obfuscate detectors. However, these methods are only effective in specific environments and yield limited evasion effectiveness. To solve the above problems, this paper proposes a malware adversarial sample generation method (PixGAN) based on the pixel attention mechanism, which aims to improve adversarial samples' escape effect and mobility. The method transforms malware into grey-scale images and introduces the pixel attention mechanism in the Deep Convolution Generative Adversarial Networks (DCGAN) model to weigh the critical pixels in the grey-scale map, which improves the modeling ability of the generator and discriminator, thus enhancing the escape effect and mobility of the adversarial samples. The escape rate (ASR) is used as an evaluation index of the quality of the adversarial samples. The experimental results show that the adversarial samples generated by PixGAN achieve escape rates of 97%, 94%, 35%, 39%, and 43% on the Random Forest (RF), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Convolutional Neural Network and Recurrent Neural Network (CNN_RNN), and Convolutional Neural Network and Long Short Term Memory (CNN_LSTM) algorithmic detectors, respectively.
BAO WU,GUOGUANG RONG,JUNWEI ZHAO,SHULIN ZHANG,YONGXIN ZHU,BOYONG HE 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2012 NANO Vol.7 No.6
One third of the world population is estimated to have Mycobacterium tuberculosis infection. It is urgent to develop a rapid, inexpensive and convenient diagnostic method for detection of tuberculosis. Porous silicon material has taken more and more attention in recent years for biosensing applications and some useful results have been obtained. In this paper, we report the feasibility of applying porous silicon microcavity biosensor in a novel and relatively rapid serodiagnostic approach. Nowadays, most of serodiagnostic tests are based on labeled detection. Applying label-free detection methods can help develop fast and e±cient tuberculosis diagnostic tools, which can meet the current demand. In this study, we use this label-free sensing platform (i.e., porous silicon microcavity) to detect the interaction between 16 kDa antigen and anti-16 kDa antibody. Through a series of experiments, we verify the speci¯city and examine the sensitivity of this new diagnostic technique. The results show that it is feasible to apply porous silicon microcavity in the tests of tuberculosis.
Lu Yan,Huiyuan Wang,Yifan Jiang,Jinhua Liu,Zhao Wang,Yongxin Yang,Shengwu Huang,Yongzhuo Huang 한국고분자학회 2013 Macromolecular Research Vol.21 No.4
Macromolecular drugs become an essential part in neuroprotective treatment. However, the nature of ineffective delivery crossing the blood brain barrier (BBB) renders those macromolecules undruggable for clinical practice. Recently, brain target via intranasal delivery have provided a promising solution to circumventing the BBB. Despite the direct route from nose to brain (i.e. olfactory pathway), there still are big challenges for large compounds like proteins to overcome the multiple delivery barriers such as nasal mucosa penetration, intracellular transport along the olfactory neuron, and diffusion across the heterogeneous brain compartments. Herein presented is an intranasal strategy mediated by cell-penetrating peptide modified poly(lactic-co-glycolic acid) (PLGA) nanoparticles for the delivery of insulin to the brain, a potent therapeutic against Alzheimer’s disease. The results revealed that the cell-penetrating peptide can potentially deliver insulin into brain via the nasal route, showing a total brain delivery efficiency of 6%. It could serve as a potential treatment for neurodegenerative diseases.