Would the reputation and behaviour of the Chinese stock exchange be a disincentive to investors considering a Chinese REIT?

China has drawn the world’s attention with the emergence, rapid growth and increasing maturity of its real estate market in the past twenty years. Currently the world’s third largest economy, China was the second largest Asian country for commercial property transaction capital flows in 2006 (JLL, 2007). International investors have recently shown considerable interest regarding property investment in China, via both direct and indirect property and changes to the rules governing internal funds are likely to initiate high levels of effective demand from domestic institutions too. China is yet to develop a Real Estate Investment trust (REIT) market; despite this investment demand encouragement for development of pilot REITs by the PRC government has waxed and waned with political imperatives to manage market and economic volatility. Chinese REITs would theoretically provide the opportunity for investors to access Chinese “property” returns with liquidity and flexibility and might further play a significant role in stabilising the Chinese capital market in the medium and long term. The purpose of this paper is to examine whether the reputation and behaviour of the Chinese stock exchanges is a disincentive to investors considering a Chinese REIT. This is addressed firstly by assessing Chinese stock market volatility compared to that of the Hong Kong and Singapore stock exchanges. Secondly, a survey was used to explore Chinese domestic investors’ attitudes to investment in Chinese property REITs and their preferences amongst the three main Asian stock exchanges where Chinese REITs might potentially be available

3D Holographic Millimeter-Wave Imaging for Concealed Metallic Forging Objects Detection

This chapter investigates the feasibility of using 3D holographic millimeter-wave (HMMW) imaging for diagnosis of concealed metallic forging objects (MFOs) in inhomogeneous medium. A 3D numerical system, including radio frequency (RF) transmitters and detectors, various realistic MFOs models and signal and imaging processing, is developed to analyze the measured data and reconstruct images of target MFOs. Simulation and experimental validations are performed to evaluate the HMMW approach for diagnosis of concealed MFOs. Results show that various concealed objects can be clearly represented in the reconstructed images with accurate sizes, locations and shapes. The proposed system has the potential for further investigation of concealed MFOs under clothing in the future, which has the potential applications in on body concealed weapon detection at security sites or MFOs detection in children

Product design selection using online customer reviews

Product design selection is heavily constrained by its customer preference data acquisition process. Traditionally, the customer preference data is collected through survey-based methods such as conjoint; sometimes product prototypes are generated and evaluated by focused groups of customers. In this way, the data acquisition process can become costly and require a significant amount of time. The goal of this dissertation is to overcome the limitation of the traditional customer preference data acquisition process by making use of a new type of customer data - online customer reviews. Because online customer reviews are, to a large extent, freely available on the Internet copiously, using them for product design can significantly reduce the cost as well as the time. Of course, the data obtained from online reviews have some disadvantages too. For example, online reviews are freely expressed and can contain a lot of noise. In this dissertation, a new methodology is developed to extract useful data from online customer reviews from a single website, construct customer preference models and select a product design that provides a maximum expected profit. However, online customer reviews from a single website may not represent the market well. Furthermore, different websites may have their own procedures and formats to acquire customer reviews. A new approach is developed to systematically elicit customer data from multiple websites, construct customer preference models by considering website heterogeneity, and select a product design. The model from multiple websites is also extended to account for customer preference heterogeneity. The models obtained from the online customer reviews for single and multiple websites are compared and validated using a set of out-of-sample data. To demonstrate the applicability of the proposed models, a smartphone case study is used throughout the dissertation

Inventory Management in China: Evidence from Micro Data

Inventory management has become a favorite topic in the literature. However, research focusing on inventory performance and management in China is quite limited. A good understanding of inventory control would provide valuable information about the mechanism through which a firm determines its target inventory level and adjusts the inventory volume. Moreover, this study also contributes to examine inventory management improvement and its implement in developing country. This research uses a large sample of firm-level panel data from China to study inventory management and performance from three aspects. First, using a variant of error-correction model, we empirically study the adjustment pattern of inventory and the effects of certain determinants on firms’ target inventory level with emphasis on industry heterogeneity over the period 2000-2009. We find strong evidence indicating a partial adjustment mechanism in short-run and the speeds of adjustment are various among different industries. From a long-run perspective, sales, ownership structure, political affiliation and managerial fixed cost are detected to be significant indicators of target inventory level. Second, we employ an asymmetric error-correction model to study the adjustment mechanism of inventory in different macro business regimes. We find that an asymmetric adjustment mechanism could be commonly claimed in short-run: firms tend to be more sensitive when they confront negative demand shocks. However, the indicators of target inventory level work symmetrically regardless of external business environment. Last, we test whether there is a link between innovation and inventory reduction. We find that total factor productivity (TFP) is a better indicator of innovation, and higher TFP contributes to a lower inventory volume. Moreover, when allowing the asymmetric adjustment mechanism, the impact of TPF is symmetric between the upswing and downswing of business cycle, which means the benefits of innovations are lasting and cannot be discharged by adverse economic environments

Intercultural Comparison of Metaphors

Metaphorical concepts play an important role in the course of human cognition and remoulding of the world, and figurative language is the best way of presenting metaphorical concepts. Comparative analysis of metaphorical phenomena in the Chinese and English languages is helpful in exploring the formation and development of metaphorical concepts all over the world and their internal relations with cultural value orientation of various nations

On the nonintegrability of equations for long- and short-wave interactions

We examine the integrability of two models used for the interaction of long and short waves in dispersive media. One is more classical but arguably cannot be derived from the underlying water wave equations, while the other one was recently derived. We use the method of Zakharov and Schulman to attempt to construct conserved quantities for these systems at different orders in the magnitude of the solutions. The coupled KdV-NLS model is shown to be nonintegrable, due to the presence of fourth-order resonances. A coupled real KdV - complex KdV system is shown to suffer the same fate, except for three special choices of the coefficients, where higher-order calculations or a different approach are necessary to conclude integrability or the absence thereof.Comment: 9 pages, presented as a poster at The Tenth IMACS International Conference on Nonlinear Evolution Equations and Wave Phenomena: Computation and Theor

Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection

Early cancer detection and suitable treatment improve the 5-year survival rates of lung cancer significantly. Many cancer diagnostic approaches have been investigated, including mammography, magnetic resonance imaging, ultrasound, computerized tomography, positron emission tomography and biopsy. However, these techniques have some drawbacks such as expensive and time-consuming. Electromagnetic tomography (EMT) has been proposed as a promising diagnostic tool for lung cancer detection. In addition, developing label-free and cost-effective biosensors for target tumor markers detection have attracted attentions worldwide. This chapter reviews the recently developed EMT and bio-sensing techniques for early-stage lung cancer detection