Medical Image Fusion in NSCT Domain Combining with Compressive Sensing

AiliWang,Jiaying Zhao,Yuji Iwahori,Shiyu Dai 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.5

In recent years, with the development of compressive sensing (CS) theory, it has been widely applied to each field including image fusion, and obtained better fusion effect. And CS can reduce dimensions and the amount of data characteristics as well as the large amount and high computation complex. Therefore, this paper proposes a novel medical image fusion method based on compressive sensing theory in non-subsampled contourlet transform (NSCT) domain. First, NSCT transform is applied to the source images, and the coefficients in low frequency subband are fused by mean rules. For high frequency subband, CS is applied and the coefficients are fused by neighborhood-energy-MAX (NE-MAX) rule, then inverse CS is used to get fused coefficients. Finally, inverse NSCT is applied to get the reconstructed image. The experimental results show that the fusion algorithm proposed in this paper is superior to fusion method based on WT-MAX and CS-MAX、CS-MEAN.

Medical Image Fusion based on Pulse Coupled Neural Network Combining with Compressive Sensing

AiliWang,Jiaying Zhao,Shiyu Dai,Yuji Iwahori,Yangyang Zhao 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.5

Image fusion is an important branch of information fusion, widely used in various fields, especially in medical field. So increasing the quality and efficiency of medical image fusion has great significance. Combining the advantages of pulse coupled neural networks with Compressive Sensing; this paper puts forward a novel image fusion method in NSCT transform domain. First, NSCT transform is applied to the source images, and the coefficients in low frequency coefficient are fused by mean rules. For high frequency coefficient, CS is applied and PCNN. Finally, inverse NSCT is applied to get the reconstructed image. The experimental results show that the fusion algorithm proposed in this paper in the performance and integration efficiency has better fusion results.

Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community Atmosphere Model

Siyu Zhao,Jiaying Zhang,Yi Deng,Na Wang 한국기상학회 2022 Asia-Pacific Journal of Atmospheric Sciences Vol.58 No.3

The past four decades have seen an increase of terrestrial hot extremes during summer in the northern extratropics, accompanied by the Northern Hemisphere (NH) sea surface temperature (SST) warming (mainly over 10°–70°N, 0°–360°) and CO2 concentration rising. This study aims to understand possible causes for the increasing hot extremes, which are defined on a daily basis. We conduct a series of numerical experiments using the Community Atmosphere Model version 5 model for two periods, 1979–1995 and 2002–2018. The experiment by changing the CO2 concentration only with the climatological SST shows less increase of hot extremes days than that observed, whereas that by changing the NH SST (over 10°–70°N, 0°–360°) with constant CO2 concentration strengthens the hot extremes change over mid-latitudes. The experiment with both SST and CO2 concentration changes shows hot extremes change closer to the observation compared to the single-change experiments, as well as more similar simulations of atmospheric circulations and feedbacks from cloud and radiative processes. Also discussed are roles of natural variability (e.g., Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation) and other factors (e.g., Arctic sea ice and tropical SST).

A Novel Feature Detection Algorithm Based on Improved 2DPCA- SIFT

AiliWang,Yangyang Zhao,Jiaying Zhao,Yuji Iwahori,Xinyuan Wang 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.6

Stable local feature and representation is a fundamental component of many image registration, 3D reconstruction and object recognition algorithms. SIFT is a good descriptor that encodes the salient aspects of the image gradient in the feature point’s neighborhood. This paper improved SIFT- based local image descriptor and proposed a SIFT feature matching algorithm based on improved 2DPCA which can eliminate both rows and columns of relevance. Experimental results show that improved 2DPCA-SIFT algorithm is relatively stable, accurate and fast.

A Novel Image Fusion Algorithm Combining with Classification in NCST Domain

Jitao Zhang,Aili Wang,Jiaying Zhao 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.10

Image fusion is an important branch of information fusion, which is widely used in various fields. At present, the image fusion method is mainly aimed at the different frequency information of the images, the images are fused in transform domain. But in practical application, image fusion is used to improve the credibility of the target information and the demand of background information of is not high. Therefore, this paper puts forward an image fusion method combining with image classification. Firstly, the NSCT transform is used to transform the source images, and the K-Means method is used to realize the classification of the target and the background, and the different fusion criteria are used to get the target and the background. The experimental results show that the image fusion based classification method has a better effect on the subjective visual effect and objective evaluation index.

OsSPL13 controls grain size in cultivated rice

Si, Lizhen,Chen, Jiaying,Huang, Xuehui,Gong, Hao,Luo, Jianghong,Hou, Qingqing,Zhou, Taoying,Lu, Tingting,Zhu, Jingjie,Shangguan, Yingying,Chen, Erwang,Gong, Chengxiang,Zhao, Qiang,Jing, Yufeng,Zhao, Y Nature Publishing Group, a division of Macmillan P 2016 Nature genetics Vol.48 No.4

<P>Although genetic diversity has a cardinal role in domestication, abundant natural allelic variations across the rice genome that cause agronomically important differences between diverse varieties have not been fully explored. Here we implement an approach integrating genome-wide association testing with functional analysis on grain size in a diverse rice population. We report that a major quantitative trait locus, GLW7, encoding the plant-specific transcription factor OsSPL13, positively regulates cell size in the grain hull, resulting in enhanced rice grain length and yield. We determine that a tandem-repeat sequence in the 5'UTR of OsSPL13 alters its expression by affecting transcription and translation and that high expression of OsSPL13 is associated with large grains in tropical japonica rice. Further analysis indicates that the large-grain allele of GLW7 in tropical japonica rice was introgressed from indica varieties under artificial selection. Our study demonstrates that new genes can be effectively identified on the basis of genome-wide association data.</P>

Experimental investigation and stability analysis on dense-phase pneumatic conveying of coal and biomass at high pressure

Liang Cai,Cai Jiaying,Xu Guiling,Xu Pan,Chen Xiaoping,Zhao Changsui 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.2

Conveying characteristics and flow stability are very important for design and control of a conveying system at high pressure. The influences of operating parameters and material properties on conveying characteristics were investigated in an experimental test facility with a conveying pressure up to 4MPa. Wavelet transform and Shannon entropy analysis were applied to analyzing pressure drops through horizontal pipe in order to obtain the stability criterion. Results indicated that the mass flow rate of biomass decreased, while the mass flow rate of pulverized coal increased at first and then decreased with the increase in fluidization velocity. Solid loading ratios for four kinds of powders decreased with the increase in fluidization velocity. Conveying phase diagrams and pressure drops through different test sections of pulverized coal and biomass at high pressure were obtained and analyzed. The influences of coal category,fracture characteristics and particle size on conveying characteristics were determined.

Research on Intelligent Service Construction of Exhibition Venues Based on the Needs of Exhibitors

WU JIALIN,Li Jiaying,Zhao Zhipei 한국무역전시학회 2023 무역전시연구 Vol.18 No.1

Under the background of the information age and the post-pandemic era, the construction of smart exhibition venues has become a hot topic in the exhibition industry. Smart service, as an important direction for the construction of smart venues, has aroused scholars to make relevant discussions. However, there have been some researches on specific exhibition intelligent services, little researches on exhibition hall intelligent services from the perspective of users. In addition, there are also various subjects using intelligent services in the exhibition hall. As a component of exhibitions, the subjects using intelligent services can be divided into exhibition organizers, exhibitors, visitors, service providers, etc. Due to the diverse types of intelligent services required by various subjects, the demand for intelligent services may also vary. Therefore, research on intelligent services in exhibition halls should also vary according to the needs of each subject. Exhibitors, a bridge between organizers and visitors are playing an important role in the exhibition. The income of the organizers is closely related to the satisfaction of exhibitors, which has great significance for the future development of the exhibition. In addition, from the perspective of visitors, exhibitors are the most important element of the exhibition. As one of the important exhibition subjects, exhibitors have their own foundational and particular needs for smart services. Based on the perspective of exhibitors’ needs, this research utilizes literature survey and interview methods to define exhibitors’ demand indicators for smart services in exhibition venues, and combines the Kano model to design a two-factor questionnaire to conduct research. After collecting the data, compare it to the Kano model classification comparative table to classify the demand attributes of the demand indicators, and then prioritize all demand indicators through the Better-Worse coefficient. This study found that exhibitors’ demand for smart services in exhibition venues is mostly type of charismatic demand, and the demand for smart parking lots and mobile charging stations, cloud display, and audience behavior data is of higher priority. Therefore, this research suggests that exhibition venues and exhibition organizers should use the above-mentioned higher priority demand indicators as the core to build a smart service system for exhibition venues. This research provides new ideas for the construction of smart exhibition venues and at the same time makes up for the deficiencies of academic research in this area.