ANALYSIS ON GRAY NODES AND GRAYNESS DEGREE IN COMPLEX NETWORK

Based on the theory of complex network and gray system, the sugesstion that there exist two types of gray nodes in complex networks, Gray Node I and Gray Node II, is concluded. The first one refers to the existent unknown gray nodes, and the second the evolution gray nodes. The relevant definitions are also given. Further- more, grayness degree in complex networks is described and divided into two forms--the relative grayness degree （RGD） and the absolute grayness degree （AGD）, which are proved respectively.

Pore Size Distribution and Its Quantitative Relationship with Strength of Corundum Based Castables

A series of corundum based castables with 0,2%,4%,6%,and 8% α-Al2O3 micropowders were prepared using tabular alumina aggregates （6-3,3-1 and ≤1 mm） and fines （≤0.088 and ≤0.045 mm）,calcium aluminate cement,and α-Al2O3 micropowders （d50=1.754 μm） as starting materials. Cold mechanical strength and pore size distribution of the castables specimens after heat treatment at 110,1 100 and 1 500 ℃ were tested,respectively. The quantitative relationship between strength and apparent porosity,and that between strength and median pore diameter were verified by Atzeni equation. The correlation between interval of pore size and mechanical strength of specimens was also studied by means of gray relational theory. The results show that：（1） the pore size distribution of castables is strongly influenced by both micropowders filling and matrix sintering; the addition of micropowders decreases median pore diameter while the sintering process increases it; （2） when adding a constant correction term,Atzeni equation can substantially describe the quantitative relationship between median pore diameter and strength of castables specimens after heat treatment at the same temperature; the significant differences of the gray relational degree between the interval of pore size and castables strength are characterized; it is also found that for the same interval of pore size,the gray relational degree isaffected by the heat treatment temperature; the pore size interval 〈0.5 μm has the highest gray relational degree with the strength at 110-1 500 ℃.

Nutrients Determination in Nuts from Different Torreya grandis Cultivars

[Objectives]This study aimed to investigate the differences in nutritional properties of nuts from different Torreya grandis cultivars.[Methods]Seven T.grandis cultivars were selected to analyze the protein,soluble carbohydrate,vitamin E,amino acids and fatty acid composition,and evaluate nutritional value of T.grandis nuts from different cultivars using gray correlation analysis.[Results]The kernels of T.grandis contained 9.47%-13.3% protein,1.92%-2.36% soluble carbohydrate,0.16-0.22 mg/g vitamin E,8.40%-11.55% amino acids,and 42.09%-49.29% fatty acid including 35.14%-40.14% oleic acid.And the coefficient of variation ranged from 5.02% to 18.9% among different cultivars.Meanwhile,the average contents of essential amino acids(E),nonessential amino acids(N)and children essential amino acids(C)were 3.88%,6.07% and 0.99%,respectively.The ratios of E/T and E/N were quite stable and in fully compliance with the recommendation standards of amino acids composition from WHO/FAO.[Conclusions]Overall,the nutritional value of tested seven cultivars could be ranked in the following decreasing order using gray correlation analysis:T.grandis cv.Dong No.2>T.grandis cv.Longfeng>T.grandis cv.Dingshan>T.grandis cv.Merrilli>T.grandis cv.Dong No.3>T.grandis cv.Dong No.1>T.grandis cv.Zhuyan.

Impact of demographic dynamics on CO_2 emissions in Sichuan,China

Global climate change is one of the major environmental issues faced by humans.Existing evidence indicates that the anthropogenic push for a rise in the atmospheric concentration of greenhouse gases(GHGs)(particularly CO_2) has been a primary cause for global warming.Aside from economic and teclinological factors,demographic dynamics(including human consumption in a broad demographic sense) has been a major driver for CO_2 emissions.In this paper,we performed both nonlinear regression analysis(based on the STIRPAT model) and gray correlation degree analysis(based on gray system theory) on the impact of demographic dynamics on CO_2 emissions.Our results reveal that CO_2 emissions are positively correlated with population size and GDP per capita and negatively correlated with energy intensity.We also show that gray con-elation degree with CO_2 emissions for five variables(i.e.,household consumption,urbanization rate,household size,population aging rate,population size) varies substantially:household consumption > urbanization rate >household size > population aging rate > population size,with household consumption being the highest,and population size the lowest.To mitigate the impact of demographic dynamics on CO_2 emissions,it is of vital significance to nurture people's awareness of sustainable consumption and to adhere to current population control policies.

Dynamic Evaluation and Analysis of Regional Innovation Capability in Eastern China from the Perspective of High-quality Development

The economy of China has turned to the stage of high-quality development. In this sense,the connotation of regional innovation capacity should reflect more aspects, such as better economic effectiveness, people-centered philosophy of development and better living conditions. This study aims at establishing the evaluation index system of regional innovation capacity under high-quality perspective.Then the dynamic evaluation method based on gray correlation degree and TOPSIS is improved. And the improved method is applied to evaluate the regional innovation capacity under high-quality development perspective. The results show that: 1) The regional innovation capacity of Jiangsu, Zhejiang,Shanghai and Guangdong under high-quality development perspective is better than other regions,while the regional innovation capacity of Beijing-Tianjin-Hebei is imbalanced. Regional innovation capability of Fujian, Shandong, and Hainan from a high-quality perspective is at the middle and lower levels. 2) From the perspective of development trends, the gap of regional innovation capacity between Beijing, Jiangsu, Zhejiang, Shanghai, Guangdong and Fujian, Hebei, Shandong is gradually narrowing.3) An in-depth analysis of the regional innovation capability of the eastern provinces and cities from the perspective of high-quality development through different dimensions shows that Beijing, Guangdong, Jiangsu perform well in all dimensions, while Fujian and Hainan need to pay more attention to innovation input and the creation of a better innovation environment to enhance innovation output and promote innovation effectiveness. At last, based on above analysis, relevant policy recommendations are proposed.

Cellular automata-based approach for digital image scrambling

Purpose–The purpose of this paper is to investigate two-dimensional outer totalistic cellular automata(2D-OTCA)rules other than the Game of Life rule for image scrambling.This paper presents a digital image scrambling(DIS)technique based on 2D-OTCA for improving the scrambling degree.The comparison of scrambling performance and computational effort of proposed technique with existing CA-based image scrambling techniques is also presented.Design/methodology/approach–In this paper,a DIS technique based on 2D-OTCA with von Neumann neighborhood(NvN)is proposed.Effect of three important cellular automata(CA)parameters on gray difference degree(GDD)is analyzed:first the OTCA rules,afterwards two different boundary conditions and finally the number of CA generations(k)are tested.The authors selected a random sample of gray-scale images from the Berkeley Segmentation Data set and Benchmark,BSDS300(www2.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/)for the experiments.Initially,the CA is setup with a random initial configuration and the GDD is computed by testing all OTCA rules,one by one,for CA generations ranging from 1 to 10.A subset of these tested rules produces high GDD values and shows positive correlation with the k values.Subsequently,this sample of rules is used with different boundary conditions and applied to the sample image data set to analyze the effect of these boundary conditions on GDD.Finally,in order to compare the scrambling performance of the proposed technique with the existing CA-based image scrambling techniques,the authors use same initial CA configuration,number of CA generations,k紏10,periodic boundary conditions and the same test images.Findings–The experimental results are evaluated and analyzed using GDD parameter and then compared with existing techniques.The technique results in better GDD values with 2D-OTCA rule 171 when compared with existing techniques.The CPU running time of the proposed algorithm is also considerably small as compared to existing techniques.Originality/value–In this paper,the authors focused on using von Neumann neighborhood(NvN)to evolve the CA for image scrambling.The use of NvN reduced the computational effort on one hand,and reduced the CA rule space to 1,024 as compared to about 2.62 lakh rule space available with Moore neighborhood(NM)on the other.The results of this paper are based on original analysis of the proposed work.