Chengdu, China

Southwestern University of Finance and Economics or SWUFE is a prominent national university located in Chengdu, China. It is one of the top 3 specialist finance and economic universities under direct administration of the Ministry of Education and has been selected as a Project 211 and 985 Innovative Platforms for Key Disciplines Project university by the Chinese government as part of the national endeavor to build world-class universities in the 21st century. Wikipedia.


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Li H.,Southwestern University of Finance and Economics | Huang X.,Lehigh University | He L.,Digital Conversion Service
IEEE Transactions on Pattern Analysis and Machine Intelligence | Year: 2013

In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm. © 2012 IEEE.


SHANGHAI, Nov 2, 2016 /PRNewswire/ -- SPI Energy Co., Ltd. ("SPI Energy" or the "Company") (Nasdaq: SPI), a global provider of photovoltaic (PV) solutions for business, residential, government and utility customers and investors, today announced changes to the senior management team and board of directors of the Company (the "Board"), effective on October 29, 2016: Mr. Roger Dejun Ye has resigned as Executive Vice President in charge of the Company's solar business but will remain as a non-executive director of the Board; Mr. Minghua Zhao, who currently serves as Joint Chief Operating Officer ("COO") of the Company's China domestic business, has been appointed as a director to the Board; and Mr. Fei Yun, who previously served as General Manager of Xinghang PV Technology (Suzhou) Co., Ltd., has joined the Company as Senior Vice President in charge of R&D and Solar Technology Development. "I would like to thank Roger for his contributions to the development of Company's solar business during his tenure and we look forward to continuing to work closely with Roger in his role as a director of the Board. On behalf of the management team and the Board, I also would like to extend our warm welcome to Minghua in joining the Board and Fei in joining the Company," said Xiaofeng Peng, Chairman and Chief Executive Officer of SPI Energy. Mr. Minghua Zhao currently serves as Joint COO of the Company's China domestic business and previously served as Senior Vice President of the Company's finance service business between February 2015 and June 2016. Before he joined the Company in February 2015, Mr. Zhao served as general manager of Suzhou Industrial Park Chengcheng Enterprises Guarantee Co., Ltd., a financial services company, and from 2003 to 2009 as president of Suzhou Industrial Park Branch of Suzhou Bank. Prior to that, he worked at CITIC Bank for six years. Mr. Zhao graduated from Jiangsu Province Business School in 1997 with a degree in Business Administration and from Southwestern University of Finance and Economics in 2008 with a degree in Business Management. Mr. Fei Yun has more than 30 years of experience in the research and development of solar cells, PV systems and senior management role in the industry in Australia and China. Mr. Fei Yun joined us from Xinghang PV Technology (Suzhou) Co., Ltd. where he has served as General Manager since July 2014. Previously, Mr. Yun held senior management positions at various solar companies, including as Vice President of Technology at LDK Solar Co., Ltd. from February 2010 to June 2013; Chief Technology Officer at Solar Enertech Corp. from December 2007 to January 2010; Vice President of Technology at SolarFun (Now Hanwha Solar One) from July 2006 to November 2007; General Manager and Chief Engineer at Tera Solar Technologies from March 2004 to June 2006. Mr. Yun received his bachelor's degree in Physics from Jinan University, his master's degree in Solar Energy from the Asian Institute of Technology(AIT) in Bangkok, Thailand. He also had nearly 10 years of research and development experience in silicon-based solar cells at the ARC Photovoltaics Centre of Excellence at the University of New South Wales in Sydney, Australia, his expertise is focused on the high efficiency silicon solar cell. About SPI Energy Co., Ltd. SPI Energy Co., Ltd. is a global provider of photovoltaic (PV) solutions for business, residential, government and utility customers and investors. SPI Energy focuses on the downstream PV market including the development, financing, installation, operation and sale of utility-scale and residential solar power projects in China, Japan, Europe and North America. The Company operates an innovative online energy e-commerce and investment platform, www.solarbao.com, which enables individual and institutional investors to purchase innovative PV-based investment and other products; as well as www.solartao.com, a B2B e-commerce platform offering a range of PV products for both upstream and downstream suppliers and customers. The Company has its operating headquarters in Shanghai and maintains global operations in Asia, Europe, North America and Australia. For additional information, please visit: www.spisolar.com, www.solarbao.com or www.solartao.com. This release contains certain "forward-looking statements." These statements are forward-looking in nature and subject to risks and uncertainties that may cause actual results to differ materially. All forward-looking statements included in this release are based upon information available to the Company as of the date of this release, which may change, and the Company undertakes no obligation to update or revise any forward-looking statements, except as may be required under applicable securities law. For investors and media inquiries please contact: To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/spi-energy-co-ltd-announces-new-director-and-management-appointments-to-strengthen-its-board-and-executive-leadership-300355730.html


Chen X.,Southwestern University of Finance and Economics | Onal H.,University of Illinois at Urbana - Champaign
American Journal of Agricultural Economics | Year: 2012

Mathematical programming models are widely used in agricultural sector analysis. However, the lack of micro-level data, as well as computational requirements, necessitate the aggregation of individual producers into representative units when working at the sectoral level.This usually leads to unrealistic extreme specialization in supply responses. In 1982, McCarl introduced the "historical crop mixes" approach to avoid extreme specialization.We extend this approach by generating additional synthetic crop mixes using supply response elasticities and systematically varied commodity prices. In addition to avoiding extreme specialization, this approach provides flexibility when future supply responses can be vastly different from past responses.An application to U.S. biofuel policy analysis is presented. © The Author (2012).


Meng D.,Southwestern University of Finance and Economics | Pei Z.,Xihua University
Information Sciences | Year: 2013

We generalize linguistic evaluation values and their weights in group decision-making (GDM) problems based on unbalanced linguistic terms. The GDM problems include two types of weights: belief degrees of linguistic evaluation values and experts' weights. Due to the time pressure and conflict of multi-source of information, etc., experts may have various evaluations values on alternatives. The belief degree is used to represent the confidence level of the values. The experts' weight is used to represent the differences among experts' importance which caused by experts' experience or knowledge distinction. We propose the weighted unbalanced linguistic aggregation operators to synthesize linguistic evaluation value, belief degree and experts' weights. Some desired properties of the operator are then studied, these properties show that the operator extends the linguistic weighted averaging operator (LWA) and the linguistic ordered weighted averaging (LOWA) operator. Finally, an illustrative example of human resource performance appraisal based on the linguistic aggregation operator is provided. © 2012 Elsevier Inc. All rights reserved.


Kou G.,Southwestern University of Finance and Economics | Peng Y.,University of Electronic Science and Technology of China | Wang G.,University of Electronic Science and Technology of China
Information Sciences | Year: 2014

The evaluation of clustering algorithms is intrinsically difficult because of the lack of objective measures. Since the evaluation of clustering algorithms normally involves multiple criteria, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper presents an MCDM-based approach to rank a selection of popular clustering algorithms in the domain of financial risk analysis. An experimental study is designed to validate the proposed approach using three MCDM methods, six clustering algorithms, and eleven cluster validity indices over three real-life credit risk and bankruptcy risk data sets. The results demonstrate the effectiveness of MCDM methods in evaluating clustering algorithms and indicate that the repeated-bisection method leads to good 2-way clustering solutions on the selected financial risk data sets. © 2014 Elsevier Inc. All rights reserved.


Lu Y.,Pennsylvania State University | Yang D.,Southwestern University of Finance and Economics
Decision Support Systems | Year: 2011

This study proposes a model to examine the mechanism by which social capital contributes to information exchange in virtual communities. A hierarchical model is employed to analyze data from survey and online networks in the context of a major natural disaster. Results suggest that structural capital has a significant effect on cognitive capital, but it has no effect on relational capital. Cognitive capital shows a significant effect on relational capital. This research also finds that structural capital increases information quantity, whereas relational capital and cognitive capital increase information quality. This study reveals the characteristics of online social networks and then proposes socio-technical design principles to address the communication challenges under uncertain emergency. © 2010 Elsevier B.V. All rights reserved.


Jiang Z.,Shanghai University of Finance and Economics | Tan J.,Southwestern University of Finance and Economics
Energy Policy | Year: 2013

In China, most energy prices are controlled by the government and are under-priced, which means energy subsidies existing. Reforming energy subsidies have important implications for sustainable development through their effects on energy price, energy use and CO2 emission. This paper applies a price-gap approach to estimate China's fossil-fuel related subsidies with the consideration of the external cost. Results indicate that the magnitude of subsidies amounted to CNY 1214.24 billion in 2008, equivalent to 4.04% of GDP of that year. Subsidies for oil products are the largest, followed by subsidies for the coal and electricity. Furthermore, an input-output model is used to analyze the impacts of energy subsidies reform on different industries and general price indexes. The findings show that removal of energy subsidies will have significant impact on energy-intensive industry, and consequently push up the general price level, yet with a small variation. Removing oil products subsidies will have the largest impact, followed by electricity, coal and natural gas. However, no matter which energy price increases, PPI is always the most affected, then GDP deflator, with CPI being the least. Corresponding compensation measures should be accordingly designed to offset the negative impact caused by energy subsidies reform. © 2013 Elsevier Ltd.


Zou G.L.,Southwestern University of Finance and Economics
Energy Policy | Year: 2012

To reduce its consumption of coal and oil in its primary energy consumption, China promotes the development of renewable energy resources. I have analysed the long-term relationship among China's primary energy consumption sources. Changes in coal consumption lead those in the consumption of other energy sources in the long term. Coal and oil fuels substitute for each other equally. The long-term elasticities of China's coal consumption relative to its hydroelectricity consumption were greater than one and nearly equal during the two sample periods. Therefore, increased hydroelectricity consumption did not imply a reduction in coal consumption. China holds abundant hydroelectricity, wind and, solar energy potential. China must prevent an excessive escalation of its economy and resultant energy demand to realise a meaningful substitution of coal with hydroelectricity. Moreover, China must develop and use wind and solar energy sources. Natural gas can be a good substitute for coal, given its moderate price growth and affordable price levels. © 2012 Elsevier Ltd.


Chen X.,Southwestern University of Finance and Economics
Applied Energy | Year: 2016

Using a mathematical programming model, we estimate the economic potential of biomass supply from crop residues in China at various exogenously-given biomass prices and identify the areas that are likely to produce crop residues. Our analysis indicates that China can potentially produce about 174.4-248.6. million dry metric tons of crop residues per year when biomass prices are larger than $100 per metric ton. Rice straw is expected to account for about 47% of total residue production across the different biomass prices and residue production scenarios that we considered. Corn stover and wheat straw can contribute 28% and 25%, respectively, to total biomass production in China. © 2016.


Yunong H.,Southwestern University of Finance and Economics
Ageing and Society | Year: 2012

This paper examined the relationships between family relations and life satisfaction between the two groups of older people with different hukous in Putian, Fujian, China. Five factors related to family relations: family support network, satisfaction with family support, family harmony, filial support and filial discrepancy, were included in the study. A total of 532 valid questionnaires, 263 and 269 being filled in by older people with agricultural and non-agricultural hukous, respectively, were obtained. Bivariate analyses indicated that five factors were correlated significantly with life satisfaction for both groups of older people. The results of hierarchical regression analyses showed that when controlling for socio-demographic variables, filial support was associated with life satisfaction for both groups of older people; satisfaction with family support and filial discrepancy was only associated with life satisfaction among older people with agricultural hukous; family harmony only contributed to explaining life satisfaction among older people with non-agricultural hukous. The present study confirmed some previous empirical findings, which indicated the importance of family relations to older people's lives, and extended our understanding about the correlates of life satisfaction for the two groups of older people with different hukous in China. Limitations and direction of future studies were also addressed. Meanwhile, the policy and practice implications of the study were discussed in the context of China's social and economic changes. © 2011 Cambridge University Press.

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