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A novel visual tracking system with adaptive incremental extreme learning machine
( Zhihui Wang ),( Sook Yoon ),( Dong Sun Park ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.1
This paper presents a novel discriminative visual tracking algorithm with an adaptive incremental extreme learning machine. The parameters for an adaptive incremental extreme learning machine are initialized at the first frame with a target that is manually assigned. At each frame, the training samples are collected and random Haar-like features are extracted. The proposed tracker updates the overall output weights for each frame, and the updated tracker is used to estimate the new location of the target in the next frame. The adaptive learning rate for the update of the overall output weights is estimated by using the confidence of the predicted target location at the current frame. Our experimental results indicate that the proposed tracker can manage various difficulties and can achieve better performance than other state-of-the-art trackers.
Wang, Zhihui,Yoon, Sook,Xie, Shan Juan,Lu, Yu,Park, Dong Sun Hindawi Publishing Corporation 2014 The Scientific World Journal Vol.2014 No.-
<P>In pedestrian detection methods, their high accuracy detection rates are always obtained at the cost of a large amount of false pedestrians. In order to overcome this problem, the authors propose an accurate pedestrian detection system based on two machine learning methods: cascade AdaBoost detector and random vector functional-link net. During the offline training phase, the parameters of a cascade AdaBoost detector and random vector functional-link net are trained by standard dataset. These candidates, extracted by the strategy of a multiscale sliding window, are normalized to be standard scale and verified by the cascade AdaBoost detector and random vector functional-link net on the online phase. Only those candidates with high confidence can pass the validation. The proposed system is more accurate than other single machine learning algorithms with fewer false pedestrians, which has been confirmed in simulation experiment on four datasets.</P>
Bifurcation of a predator-prey system with generation delay and habitat complexity
Zhihui Ma,Haopeng Tang,Shufan Wang,Tingting Wang 대한수학회 2018 대한수학회지 Vol.55 No.1
In this paper, we study a delayed predator-prey system with Holling type IV functional response incorporating the effect of habitat complexity. The results show that there exist stability switches and Hopf bifurcation occurs while the delay crosses a set of critical values. The explicit formulas which determine the direction and stability of Hopf bifurcation are obtained by the normal form theory and the center manifold theorem.
Analysis on Association of a SNP in the Chicken OBR Gene with Growth and Body Composition Traits
Wang, Ying,Li, Hui,Zhang, YuanDan,Gu, ZhiLiang,Li, ZhiHui,Wang, QiGui Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.12
Leptin receptor (OBR) is a member of the class I cytokine receptor family. It signals mainly via the JAK/STAT pathway and plays an important role in regulating body energy storage and metabolism. This study was designed to investigate the effects of the OBR gene on chicken growth and body composition. Broiler lines selected divergently for or against abdominal fat were used. Primers for the exon9-region in the OBR gene were designed using chicken genomic sequences from the public genome domain. A C/A single nucleotide polymorphism (SNP) was found and its three genotypes (AA, AB and BB) were identified in this population. The results showed that the OBR polymorphism was associated with fatness traits, such as abdominal fat weight and abdominal fat percentage. This research suggests that OBR or a linked gene has effect on fat deposition in the chicken.
Camera Source Identification of Digital Images Based on Sample Selection
( Zhihui Wang ),( Hong Wang ),( Haojie Li ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.7
With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.
BIFURCATION OF A PREDATOR-PREY SYSTEM WITH GENERATION DELAY AND HABITAT COMPLEXITY
Ma, Zhihui,Tang, Haopeng,Wang, Shufan,Wang, Tingting Korean Mathematical Society 2018 대한수학회지 Vol.55 No.1
In this paper, we study a delayed predator-prey system with Holling type IV functional response incorporating the effect of habitat complexity. The results show that there exist stability switches and Hopf bifurcation occurs while the delay crosses a set of critical values. The explicit formulas which determine the direction and stability of Hopf bifurcation are obtained by the normal form theory and the center manifold theorem.
Zhihui Yu,Ning Wang,Gan Hu,Meihu Ma 한국식품과학회 2019 Food Science and Biotechnology Vol.28 No.4
This study compared the long-term effects of EYconsumption under two diet conditions: normal (ND ?EY) and high fat diet (HFD ? EY), on lipid metabolism inmice. ND ? EY did not increase serum triglycerides, totalcholesterol hepatic triglyceride concentrations, adiposetissue accumulation and glucose impairment, not leading tofatty liver. HFD ? EY markedly decreased adipose tissueaccumulation, the triglyceride and total cholesterol, andimproved serum HDL-C and blood glucose impairmentcompared with HFD. PLS-DA analyzes showed bothND ? EY and HFD ? EY could decrease serum C18:1and MUFA. HFD ? EY could further decrease hepaticC18:2 and PUFA and increase C18:1 and MUFA excretion,which were associated with lower expression of Elovl6 andhigher expression of Scd1 in liver. These results suggestthat HFD ? EY significantly improved dyslipidemiacaused by HFD through modifying lipid metabolism, andND ? EY did not adversely affect the biomarkersassociated with dyslipidemia risk, but showed less obviousregulation of lipid metabolism than HFD ? EY.