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.

Political regimes, business cycles, seasonalities, and returns

Abstract: This paper provides a method for testing for regime differences when regimes are long-lasting. Standard testing procedures are generally inappropriate because regime persistence causes a spurious regression problem – a problem that has led to incorrect inference in a broad range of studies involving regimes representing political, business, and seasonal cycles. The paper outlines analytically how standard estimators can be adjusted for regime dummy variable persistence. While the adjustments are helpful asymptotically, spurious regression remains a problem in small samples and must be addressed using simulation or bootstrap procedures. We provide a simulation procedure for testing hypotheses in situations where an independent variable in a time-series regression is a persistent regime dummy variable. We also develop a procedure for testing hypotheses in situations where the dependent variable has similar properties.

Social support and the 'left behind' elderly in rural China: a case study from Jiangxi Province.

Abstract: This study examines the living situation of elderly people in rural China whose children have left to work in other areas [the 'left behind' elderly (LBE)] and explores policy implications associated with their care. Based on survey data and interviews conducted in three villages in Jiangxi Province, China, we compare the living situation of the LBE and the 'non-left behind' elderly (NLBE). The data reveal that the LBE are relatively more isolated and that they spend less time interacting with neighbors and more time watching television. The study shows that the LBE have a much greater need for care services than income maintenance. Also, the LBE group has less social capital than the NLBE group. Based on our findings, it is clear that the proposal to use social capital and informal care cannot effectively meet all the needs of the LBE group. Instead, it is recommended that a comprehensive system of social support is developed.

Energy-Efficient Algorithm for Broadcasting in Ad Hoc Wireless Sensor Networks

Abstract: Broadcasting is a common and basic operation used to support various network protocols in wireless networks. To achieve energy-efficient broadcasting is especially important for ad hoc wireless sensor networks because sensors are generally powered by batteries with limited lifetimes. Energy consumption for broadcast operations can be reduced by minimizing the number of relay nodes based on the observation that data transmission processes consume more energy than data reception processes in the sensor nodes, and how to improve the network lifetime is always an interesting issue in sensor network research. The minimum-energy broadcast problem is then equivalent to the problem of finding the minimum Connected Dominating Set (CDS) for a connected graph that is proved NP-complete. In this paper, we introduce an Efficient Minimum CDS algorithm (EMCDS) with help of a proposed ordered sequence list. EMCDS does not concern itself with node energy and broadcast operations might fail if relay nodes are out of energy. Next we have proposed a Minimum Energy-consumption Broadcast Scheme (MEBS) with a modified version of EMCDS, and aimed at providing an efficient scheduling scheme with maximized network lifetime. The simulation results show that the proposed EMCDS algorithm can find smaller CDS compared with related works, and the MEBS can help to increase the network lifetime by efficiently balancing energy among nodes in the networks.

Linkages and relationships between Emerging European and Developed Stock Markets before and after the Russian Crisis of 1997-1998

Abstract: We examine the relationship between Russian and other Central and Eastern European equity markets over the 1995-2004 period. Using traditional Johansen and Juselius multivariate cointegration approaches and examining Impulse Response Functions from VECM's we find that the extent of the relationship differs markedly before and after the Russian crisis of 1998. However, further examination, using the Gregory-Hansen approach, indicates that the effect of the Russian crisis is more complex, and that Russian market shows significantly more evidence of integration with developed markets since, albeit the extent of interdependencies differs in case of the US and European markets. A DCC model indicates that the conditional relationship between the Russian market and the main developed markets is, as shown by the Gregory-Hansen approach, shifting.

Visual Attention Prediction for Stereoscopic Video by Multi-Module Fully Convolutional Network

Abstract: Visual attention is an important mechanism in the human visual system (HVS) and there have been numerous saliency detection algorithms designed for 2D images/video recently. However, the research for fixation detection of stereoscopic video is still limited and challenging due to the complicated depth and motion information. In this paper, we design a novel multi-module fully convolutional network (MM-FCN) for fixation detection of stereoscopic video. Specifically, we design a fully convolutional network for spatial saliency prediction (S-FCN), where the initial spatial saliency map of stereoscopic video is learned by image database of object detection. Furthermore, the fully convolutional network for temporal saliency prediction (T-FCN) is constructed by combining saliency results from S-FCN and motion information from video frames. Finally, the fully convolutional network for depth fixation prediction (D-FCN) is designed to compute the final fixation map of stereoscopic video by learning depth features with spatiotemporal features from T-FCN. The experimental results show that the proposed MM-FCN can predict fixation results for stereoscopic video more effectively and efficiently than other related fixation prediction methods.