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Search Results: 1 - 10 of 13819 matches for " Lili Luo "
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A novel method for blood vessel detection from retinal images
Lili Xu, Shuqian Luo
BioMedical Engineering OnLine , 2010, DOI: 10.1186/1475-925x-9-14
Abstract: In this paper, we present a novel method to segment retinal blood vessels to overcome the variations in contrast of large and thin vessels. This method uses adaptive local thresholding to produce a binary image then extract large connected components as large vessels. The residual fragments in the binary image including some thin vessel segments (or pixels), are classified by Support Vector Machine (SVM). The tracking growth is applied to the thin vessel segments to form the whole vascular network.The proposed algorithm is tested on DRIVE database, and the average sensitivity is over 77% while the average accuracy reaches 93.2%.In this paper, we distinguish large vessels by adaptive local thresholding for their good contrast. Then identify some thin vessel segments with bad contrast by SVM, which can be lengthened by tracking. This proposed method can avoid heavy computation and manual intervention.The retina is the only location where blood vessels can be directly captured non-invasively in vivo. Over the past decade, the retinal image analysis has been widely used in medical community for diagnosing and monitoring the progression of diseases [1,2]. And retinal blood vessels are important structures in retinal images. The information obtained from the examination of retinal blood vessels offers many useful parameters for the diagnosis or evaluation of ocular or systemic diseases. For example, the retinal blood vessel has shown some morphological changes such as diameter, length, branching angles or tortuosity for vascular or nonvascular pathology, such as hypertension, diabetes, cardiovascular diseases [3]. Blood vessels are also used as landmarks for registration of retinal images of a same patient gathered from different sources. Sometimes, retinal blood vessel must be excluded for easy detection of pathological lesions like exudates or microaneurysms. In all cases, proper segmentation of retinal blood vessel is crucial.Actually, automatic detection of the blood
Preprocessing of Separating Leukocytes Based on Setting Parameters of Lightness Transformation  [PDF]
Jianyong Cai, Lili Luo, Rongtai Cai, Lijin Lin, Juan Cai
Journal of Signal and Information Processing (JSIP) , 2013, DOI: 10.4236/jsip.2013.44051
Abstract: This paper proposed a new algorithm to separate leukocytes from cytological image by setting parameters of lightness transformation based on the RGB color space, which can make the targets’ color in different areas. In our procedure, an operator is employed in using color features. According to their histogram distribution of hue component in HSL color space after enhancing the contrast of image in RGB color space, the threshold of segmentation between leukocyte and erythrocyte could be achieved well. Especially, this algorithm is more efficient than monochrome for leukocyte segmentation, and the results of experiments show that it provides a good tool for cytological image, which can increase accuracy of segmentation of leukocyte.
Effective connectivity of dorsal and ventral visual pathways in chunk decomposition
QiYuan Wu,LiLi Wu,Jing Luo
Science China Life Sciences , 2010, DOI: 10.1007/s11427-010-4088-z
Abstract: Chunk decomposition is defined as a cognitive process which breaks up familiar items into several parts to reorganize them in an alternative approach. The present study investigated the effective connectivity of visual streams in chunk decomposition through dynamic causal modeling (DCM). The results revealed that chunk familiarity and perceptual tightness made a combined contribution to highlight not only the “what” and the “where” streams, but also the effective connectivity from the left inferior temporal gyrus to the left superior parietal lobule.
Drought risk assessment of China’s mid-season paddy
Yongdeng Lei,Jing’ai Wang,Lili Luo
International Journal of Disaster Risk Science , 2011, DOI: 10.1007/s13753-011-0009-4
Abstract: China has the world’s largest population and a large and critically important agricultural sector. Sixty-five percent of the Chinese population lives on paddy rice. However, drought disasters frequently afflict China’s rural population and threate n its food security. It is therefore of paramount importance to assess the drought risk of paddy in China. We establish a quantitative risk assessment model for the drought risk of mid-season paddy and regional-specific vulnerability curves, evaluate the drought risk of mid-season paddy, and compile a series of risk maps. The drought disaster risk rating results indicate that risk is highest in Northeast China, followed by Northwest China, North China, and South China, showing a decreasing trend from north to south. The mid-season paddy area of Northeast China has the highest mean risk index (0.58–0.71), followed by northwestern provinces such as Inner Mongolia and Xinjiang (0.5–0.6), while risk indices in provinces of North China such as Hebei and Shandong range from 0.3–0.5, and the southern provinces show a relatively low level of risk. This article presents the preliminary results of a scientific inquiry on where the high drought risk areas of mid-season paddy are and how high the risk is. These results provide a regional-specific basis for drought risk governance of paddy in China.
Growth Characteristic of the Oleaginous Mi-croalga Chlorella ellipsoidea SD-0701 with Lipid Accumulation  [PDF]
Wenyu Luo, Wenya Du, Yi Su, Jiejie Hui, Jing Zhuang, Lili Liu
Natural Resources (NR) , 2015, DOI: 10.4236/nr.2015.62012
Abstract: Microalgae have great advantages as a new biomass source for fuel production. But microalgae are photosynthetic microorganisms, which normally grow in the light. Because of this growth condition, the commercial viability of microalgal biofuel is limited by current production systems. To obtain microalgal biofuel, fermentation is a more convenient, more economical and practical industry model. In this study, we asked whether and why the dark fermentation of C. ellipsoidea SD-0701 could be achieved by changing the culture medium formula. We focused the research on carbon-containing compounds and the initial pH of media. The results indicated that glucose was the optimum carbon-containing compound, which provided C. ellipsoidea SD-0701 with energy and carbon skeleton for accumulating organic compounds including lipids. When C. ellipsoidea SD-0701 was cultivated in the add-nutrition medium containing glucose, the optimum initial pH for the growth of C. ellipsoidea SD-0701 was pH 7.71. Therefore, if the suitable medium is used, C. ellipsoidea SD-0701 can grow normally in the dark, which is the same condition as the fermenter, and high microalgal biomass (0.50 g·L-1) and lipid yield (232.90 mg·L-1) can be achieved.
Individual Differences in Detecting Rapidly Presented Fearful Faces
Dandan Zhang, Lili Wang, Yi Luo, Yuejia Luo
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0049517
Abstract: Rapid detection of evolutionarily relevant threats (e.g., fearful faces) is important for human survival. The ability to rapidly detect fearful faces exhibits high variability across individuals. The present study aimed to investigate the relationship between behavioral detection ability and brain activity, using both event-related potential (ERP) and event-related oscillation (ERO) measurements. Faces with fearful or neutral facial expressions were presented for 17 ms or 200 ms in a backward masking paradigm. Forty-two participants were required to discriminate facial expressions of the masked faces. The behavioral sensitivity index d' showed that the detection ability to rapidly presented and masked fearful faces varied across participants. The ANOVA analyses showed that the facial expression, hemisphere, and presentation duration affected the grand-mean ERP (N1, P1, and N170) and ERO (below 20 Hz and lasted from 100 ms to 250 ms post-stimulus, mainly in theta band) brain activity. More importantly, the overall detection ability of 42 subjects was significantly correlated with the emotion effect (i.e., fearful vs. neutral) on ERP (r = 0.403) and ERO (r = 0.552) measurements. A higher d' value was corresponding to a larger size of the emotional effect (i.e., fearful – neutral) of N170 amplitude and a larger size of the emotional effect of the specific ERO spectral power at the right hemisphere. The present results suggested a close link between behavioral detection ability and the N170 amplitude as well as the ERO spectral power below 20 Hz in individuals. The emotional effect size between fearful and neutral faces in brain activity may reflect the level of conscious awareness of fearful faces.
Marine Meteorology Research Progress of China from 2003 to 2006

WANG Dongxiao,ZHANG Yan,ZENG Lili,LUO Lin,

大气科学进展 , 2009,
Abstract: The progress in marine meteorology research achieved by scientists in China during the four-year period from 2003 to 2006 is summarized under four categories: marine disaster study, typhoon over the ocean, ocean-atmosphere monitoring technology, and ocean-atmosphere forecasting technology. Compared to the previous four years, many more first-hand datasets have been obtained and more scientific issues have been addressed. In particular, many contributions have been made by young scientists. A brief statement on the research strategy of marine meteorology in China for the coming years is given at the end.
Optimization of Actuators in Smart Truss Based on Genetic Algorithms
Jingjun Zhang,Minghui Luo,Ruizhen Gao,Lili He
TELKOMNIKA : Indonesian Journal of Electrical Engineering , 2012, DOI: 10.11591/telkomnika.v10i7.1552
Abstract: Actuators formed from piezoelectric ceramics were embedded in truss rods to make up active rods. The paper used mechanical knowledge, static stiffness method and the finite element method to analyze the active rod and the smart truss structure and then model them. In order to solve the difficult problem of number optimization, the paper put forward the actuator existence variable and optimized number and locations of actuators at the same time, made the structure have the best output effect, so it can reduce the displacement at the designated location of the truss structure and the structure vibration. It also can improve the truss structure accuracy. Then find the optimal solution by genetic algorithms(GA) and MATLAB programming. The results of the example show that the model this paper builds is correct and genetic algorithms are effective in solving the optimization question.
The Complete Mitochondrial Genome of Bean Goose (Anser fabalis) and Implications for Anseriformes Taxonomy
Gang Liu, Lizhi Zhou, Lili Zhang, Zijun Luo, Wenbin Xu
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0063334
Abstract: Mitochondrial DNA plays an important role in living organisms, and has been used as a powerful molecular marker in a variety of evolutionary studies. In this study, we determined the complete mtDNA of Bean goose (Anser fabalis), which is 16,688 bp long and contains 13 protein-coding genes, 2 rRNAs, 22 tRNAs and a control region. The arrangement is similar to that of typical Anseriform species. All protein-coding genes, except for Cyt b, ND5, COI, and COII, start with an ATG codon. The ATG start codon is also generally observed in the 12 other Anseriform species, including 2 Anser species, with sequenced mitochondrial genomes. TAA is the most frequent stop codon, one of three–TAA, TAG, and T- –commonly observed in Anseriformes. All tRNAs could be folded into canonical cloverleaf secondary structures except for tRNASer(AGY) and tRNALeu(CUN), which are missing the dihydrouridine (DHU) arm. The control region of Bean goose mtDNA, with some conserved sequence boxes, such as F, E, D, and C, identified in its central domain. Phylogenetic analysis of complete mtDNA data for 13 Anseriform species supports the classification of them into four major branches: Anatinae, Anserinae, Dendrocygninae and Anseranatidae. Phylogenetic analyses were also conducted on 36 Anseriform birds using combined Cyt b, ND2, and COI sequences. The results clearly support the genus Somateria as an independent lineage classified in its own tribe, the Somaterini. Recovered topologies from both complete mtDNA and combined DNA sequences strongly indicate that Dendrocygninae is an independent subfamily within the family Anatidae and Anseranatidae represents an independent family. Based on the results of this study, we conclude that combining ND2, Cyt b, and COI sequence data is a workable solution at present for resolving phylogenetic relationships among Anseriform species in the absence of sufficient complete mtDNA data.
Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model
Shaojiang Dong,Shirong Yin,Baoping Tang,Lili Chen,Tianhong Luo
Shock and Vibration , 2014, DOI: 10.1155/2014/717465
Abstract: Predicting the degradation process of bearings before they reach the failure threshold is extremely important in industry. This paper proposed a novel method based on the support vector machine (SVM) and the Markov model to achieve this goal. Firstly, the features are extracted by time and time-frequency domain methods. However, the extracted original features are still with high dimensional and include superfluous information, and the nonlinear multifeatures fusion technique LTSA is used to merge the features and reduces the dimension. Then, based on the extracted features, the SVM model is used to predict the bearings degradation process, and the CAO method is used to determine the embedding dimension of the SVM model. After the bearing degradation process is predicted by SVM model, the Markov model is used to improve the prediction accuracy. The proposed method was validated by two bearing run-to-failure experiments, and the results proved the effectiveness of the methodology. 1. Introduction Bearing is one of the most important components in rotating machinery. Accurate bearing degradation process prediction is the key to effective implement of condition based maintenance and can prevent unexpected failures and minimize overall maintenance costs [1, 2]. To achieve effective degradation process prediction of the bearing, firstly, the features should be extracted from the collected vibration data. Then, based on the extracted features effectively prediction models should be selected [3]. Feature extraction is the process of transforming the raw vibration data collected from running equipment to relevant information of health condition. There are three types of methods to deal with the raw vibration data: time domain analysis, frequency domain analysis, and time-frequency domain analysis. The three types of methods are often chosen to extract the feature. For example, Yu [4] chose the time domain and the frequency domain transform to describe the characteristics of the vibration signals. Yan et al. [5] chose the short-time Fourier transform to extract the features. Ocak et al. [6] chose the wavelet packet transform to extract the feature of bearing wear information. Because the frequency features from FFT analysis results often tend to average out transient vibrations and thus not providing a wholesome measure of the bearing health status, in this paper, the time domain and the time-frequency domain characteristics are used to extract the original features. Although the original features can be extracted, they are still with high dimension and include
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