Zhanjiang, China

Guangdong Ocean University

www.gdou.edu.cn/
Zhanjiang, China

Guangdong Ocean University was established in 1997 to provide courses in oceanography and maritime science. It is situated in the Zhanjiang District, Guangdong Province, China. Wikipedia.

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Kalueff A.V.,Guangdong Ocean University | Kalueff A.V.,Neuroscience Research Laboratory | Kalueff A.V.,Saint Petersburg State University | Stewart A.M.,Neuroscience Research Laboratory | And 6 more authors.
Nature Reviews Neuroscience | Year: 2016

Self-grooming is a complex innate behaviour with an evolutionarily conserved sequencing pattern and is one of the most frequently performed behavioural activities in rodents. In this Review, we discuss the neurobiology of rodent self-grooming, and we highlight studies of rodent models of neuropsychiatric disorders-including models of autism spectrum disorder and obsessive compulsive disorder-that have assessed self-grooming phenotypes. We suggest that rodent self-grooming may be a useful measure of repetitive behaviour in such models, and therefore of value to translational psychiatry. Assessment of rodent self-grooming may also be useful for understanding the neural circuits that are involved in complex sequential patterns of action. © 2016 Macmillan Publishers Limited. All rights reserved.


Yue Z.,Guangdong Ocean University
Expert Systems with Applications | Year: 2011

The purpose of this paper is to develop a new approach for measuring the decision makers' weights in group decision making setting, in which the decision information, provided by multiple decision makers, is expressed in interval-valued intuitionistic fuzzy numbers. There are two key issues being addressed in this approach. The first one is to develop an ideal decision of group, which is the mean of group decision. The second one is to select the similarity measure between each individual decision and the ideal decision according to the idea of the TOPSIS of Hwang and Yoon (1981). A numeric example is also given to clarify the developed approach and to demonstrate its effectiveness. © 2011 Elsevier Ltd. All rights reserved.


Yue Z.,Guangdong Ocean University
Expert Systems with Applications | Year: 2011

In this paper, we investigate the multiple attribute group decision making (MAGDM) problems, of which the attribute values in the group decision matrices provided by each decision maker (DM) is characterized by interval numbers. First, we define the concepts of attribute satisfactory interval and attribute dissatisfactory interval, respectively, according to the attribute values. Then we develop an approach for aggregating attribute satisfactory interval and attribute dissatisfactory interval into the collective attribute interval-valued intuitionistic fuzzy number (IVIFN), and then we obtain the collective interval valued intuitionistic fuzzy decision matrix for group decision making. Next, we use the interval-valued intuitionistic fuzzy weighted averaging operator to aggregate all attribute values characterized by interval- valued intuitionistic fuzzy information to get the overall IVIFNs of alternatives. And then we use the score function and accuracy function to calculate the score and accuracy degree of each alternative value, and then rank the alternatives according to the score and accuracy degree of each alternative and select the most desirable one(s). And finally, we give an example for comprehensive pre-evaluation of air quality in Guangzhou, China during 16th Asian Olympic Games to illustrate in detail the decision process by the developed approach. © 2010 Elsevier Ltd. All rights reserved.


Ye G.,Guangdong Ocean University
Pattern Recognition Letters | Year: 2010

This paper presents an image scrambling encryption algorithm of pixel bit based on chaos map. The algorithm takes advantage of the best features of chaos maps, such as their pseudorandom property, system parameters, sensitive dependence on initial conditions and un-periodicity, combined with the pixel value bits. The new algorithm uses a single chaos map only once to implement the gray scrambling encryption of an image, in which the pixel values ranging from 0 to 255 are distributed evenly, the positions of all pixels are also permutated. In this way, the proposed method transforms drastically the statistical characteristic of original image information, so, it increases the difficulty of an unauthorized individual to break the encryption. Finally, the numerical experimental results show that the image encryption algorithm suggested has perfect hiding ability including large key space, sensitive key to initial conditions, high gray scrambling degree, and is suitable for practical use to protect the security of digital image information over the Internet. © 2009 Elsevier B.V. All rights reserved.


Yue Z.,Guangdong Ocean University
Knowledge-Based Systems | Year: 2011

In this paper, we develop a method for determining weights of decision makers under group decision environment, in which the each individual decision information is expressed by a matrix in interval numbers. We define the positive and negative ideal solutions of group decision, which are expressed by a matrix, respectively. The positive ideal solution is expressed by the average matrix of group decision and the negative ideal solution is maximum separation from positive ideal solution. The separation measures of each individual decision from the ideal solution and the relative closeness to the ideal solution are defined based on Euclidean distance. According to the relative closeness, we determine the weights of decision makers in accordance with the values of the relative closeness. Finally, we give an example for integrated assessment of air quality in Guangzhou during 16th Asian Olympic Games to illustrate in detail the calculation process of the developed approach. © 2010 Elsevier B.V. All rights reserved.


Yue Z.,Guangdong Ocean University
Expert Systems with Applications | Year: 2012

In traditional TOPSIS method, the ideal solutions for alternatives are expressed in vectors. An important step in the process of group decision making is to determine the relative importance of each decision maker. In this paper, the weights of decision makers derived from individual decision are determined by using an extended TOPSIS method with interval numbers. The ideal decisions for all individual decisions are expressed in matrices. The positive ideal decision is the intersection of all individual decisions; the negative ideal decision is the union of all individual decisions. Comparisons with other methods are also made. A numerical example is examined to show the potential applications of the proposed method. © 2011 Elsevier Ltd. All rights reserved.


Huang X.,Guangdong Ocean University
Nonlinear Dynamics | Year: 2012

In this paper, we present a chaotic image encryption algorithm in which the key stream is generated by nonlinear Chebyshev function. The novel method of designing pseudorandom chaotic sequence is carried out with the created secret keys depending on with each other. We then make multiple permutation of pixels to decrease the strong correlation between adjacent pixels in original plain image. Further, a two-dimensional Chebyshev function is considered to avoid known-plaintext and chosen-plaintext attacks in diffusion process, i.e., even with a one-bit change in original plain image, the encrypted image would become different greatly. Simulation results are given to show that the proposed method can offer us an efficient way of encrypting image. © 2011 Springer Science+Business Media B.V.


Yue Z.,Guangdong Ocean University
Information Fusion | Year: 2013

The aim of this paper is to present a group decision making methodology, in which the decision information, including the attribute values, attribute weights and weights of decision makers, is expressed in interval data. An extended TOPSIS technique is twice used in the proposed method, which is first used to determine the weights of decision makers, and second used to rank the preference order of alternatives. There is no aggregation of decision information in decision process, except that the ideal decisions as auxiliary decision tools are used in decision process. We give a comparison with another method for group decision making to show the technical advance of reported method. Additionally, we also give a real life application for supplier selection and a discussion to test the effectiveness and practical implications of the proposed method. © 2013 Elsevier B.V. All rights reserved.


Yue Z.,Guangdong Ocean University
Information Sciences | Year: 2014

Managers face with many decision-making problems that affect directly viability of their organization. Group decision-making (GDM) can help the managers to make more accurate decisions. The aim of this paper is to develop a new methodology for GDM problems in an intuitionistic fuzzy environment. In this model, the weights of decision makers are determined by using an extended TOPSIS technique. The individual decisions of decision makers are then converted into the group decision of alternatives. The preference of alternatives is ranked by using an extended TOPSIS technique. Comparisons between the proposed method and other methods are also done in order to show the major technical advances in this model. For the purposes of illustration and verification, a numerical example is presented. © 2014 Elsevier Inc. All rights reserved.


Zhang J.,Guangdong Ocean University
International Journal of Advancements in Computing Technology | Year: 2012

Particle swarm optimization (PSO) is one of the most successful optimization techniques of swarm intelligence and has been fast developed in recent years. However, the performance of PSO is significantly depended on the acceleration coefficients c 1 and c 2 which control the exploration and convergence abilities. Parameters c 1 and c 2 are the "self-cognitive" coefficient and "social-influence" coefficient respectively and are both set to 2.0 in traditional studies. Even though some studies have been conducted and argued that the c 1 and c 2 are unnecessary to be 2.0 for good performance, few literatures that based on the experimental study of the two parameters can be found. This paper gives a comprehensive investigation on the acceleration coefficients c 1 and c 2 through a set of 13 unimodal and multimodal benchmark functions, in order to study how to set these two parameters for different functions in order to obtain better performance. The experimental results indicate a conclusion that the sum of c1 and c2 should be clamped in the interval of [3.5, 4.5]. This conclusion would be the guidelines and rule for adapting c 1 and c 2 during the running phases of PSO.

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