Jiangxi University of Finance and Economics

About: Jiangxi University of Finance and Economics is a education organization based out in Nanchang, China. It is known for research contribution in the topics: Fuzzy logic & China. The organization has 2865 authors who have published 3556 publications receiving 41567 citations.

Exploring time- and frequency- dependent functional connectivity and brain networks during deception with single-trial event-related potentials.

Abstract: To better characterize the cognitive processes and mechanisms that are associated with deception, wavelet coherence was employed to evaluate functional connectivity between different brain regions. Two groups of subjects were evaluated for this purpose: 32 participants were required to either tell the truth or to lie when facing certain stimuli, and their electroencephalogram signals on 12 electrodes were recorded. The experimental results revealed that deceptive responses elicited greater connectivity strength than truthful responses, particularly in the θ band on specific electrode pairs primarily involving connections between the prefrontal/frontal and central regions and between the prefrontal/frontal and left parietal regions. These results indicate that these brain regions play an important role in executing lying responses. Additionally, three time- and frequency-dependent functional connectivity networks were proposed to thoroughly reflect the functional coupling of brain regions that occurs during lying. Furthermore, the wavelet coherence values for the connections shown in the networks were extracted as features for support vector machine training. High classification accuracy suggested that the proposed network effectively characterized differences in functional connectivity between the two groups of subjects over a specific time-frequency area and hence could be a sensitive measurement for identifying deception.

Does FDI Drive Economic Growth? Evidence from City Data in China

Abstract: Foreign Direct Investment (FDI) and government spending are two important drivers of economic growth. We use Chinese city level data and document an inverse U shape relation between FDI and GDP gro...

A probabilistic linguistic dominance score method considering individual semantics and psychological behavior of decision makers

Abstract: Psychological behavior could play a key role in many decision-making situations, therefore introducing it into the decision-making process might lead to better decisions being made. In those decision-making problems with uncertainty that are modelled by probabilistic linguistic information, the semantics of such information could be interpreted in different ways by different decision makers (DMs). Consequently, this paper aims at developing a prospect theory (PT) based on the gained and lost dominance score (GLDS) method for probabilistic linguistic multi-attribute group decision-making (MAGDM) to consider both individual semantics and DMs’ psychological behavior. As such, a new similarity degree is introduced to determine DMs’ weights and two programming models are constructed to obtain the individual numerical scales of linguistic terms and optimal individual weights of attributes. Then, the DMs’ psychological behavior is reflected by defining the individual prospect gained and lost dominance scores of alternatives on the basis of PT. The individual prospect dominance scores of alternatives are aggregated into collective prospect dominance scores of alternatives and the collective ranking of alternatives is then generated. Finally, an emission reduction device supplier selection example is analyzed and comparison analyses show the superiority and effectiveness of the proposed method.