New Weather Indices for China: Tool of Risk Control of International Supply Chain

China is at the core of the world’s supply chain because of its focus on production and consumption. However, as weather can significantly affect supply chain operations, China plans to introduce weather derivatives to secure the multinational supply chain. Using historical records over the decade, weather derivatives could be an important tool for hedging risk and meeting the needs of Chinese market. In this paper, new weather indices for China financial markets are experimentally created through simulated machine learning to assess the ability of the weather indices to reduce risk. Through a simulation test from 2008 to 2017, the indices were found to successfully match 98% of the risk with the situation across two dimensions: i). changing Chinese weather data; and ii). a connection with US weather indices

Dynamic characteristic analysis of two-stage quasi-zero stiffness vibration isolation system

A novel two-stage quasi-zero stiffness (QZS) vibration isolator was proposed for the purpose of low-frequency vibration isolation. Firstly, the dynamic model of the vibration isolation system was established; furthermore, the force transmissibility of the system under harmonic force excitation was derived by the averaging method; finally, the effects on the vibration isolation performance caused by excitation amplitude, mass ratio and damping ratio were discussed. Results show that, compared with the corresponding two-stage linear system, two-stage QZS system not only has better isolation performance, but also possesses a wider range of isolation frequency provided that the excitation amplitude, mass ratio and damping ratio is appropriate

A Hybrid Model to Analyze Air Pollution Spread Scales in Xi\u27 an and Surrounding Cities

Air quality analysis and prediction are very important in environmental research as airborne pollution has become a significant health threat, especially in Chinese urban agglomerations. Most previous analysis systems have been based on direct factors, such as pollutant concentrations, wind speeds and direction, relative humidity, and temperature; however, the air quality in a city is also affected by the air quality conditions in surrounding areas. This paper proposes a novel strategy for the analysis and forecast of air quality levels, for which Artificial Neural Networks (ANNs) are employed to elucidate the complex relationships between air quality and meteorological predictor variables. The experimental results in the study demonstrated that the normalized EEMD-ANN model outperformed other models in terms of the Precise, MAE and MAPE. The proposed model, therefore, demonstrated its potential as an administrative tool for issuing air pollution forecasts and for designing suitable abatement strategies

Readiness of Malaysian on Sustainable Development in Solar Energy Application

Solar energy is a non-vanishing renewable source of energy that is eco-friendly. However, the solar energy adoption rate in Malaysia remains low due to the low readiness level among the Malaysian. This phenomenon should be emphasized where solutions need to be figured out to encourage the adoption of solar energy in buildings. Thus, this research was conducted to explore the readiness and challenges of the Malaysians in adopting solar energy. A mixed research method was adopted where a total of 200 sets of online questionnaire surveys were distributed to the public, and a semi-structured interview was carried out to obtain the opinions from the expert in the industry. Based on the findings of the questionnaires, the top 3 challenges in solar energy adoption are (1) high setting up cost of solar panels, (2) limited public awareness of solar energy and (3) efficiency of the solar panel depends on the weather. Next, the qualitative study found that 48.9% of 139 respondents were willing to adopt solar energy in the future. The findings show that that breaking down the barriers of high investment cost and long return investment would further enhance the solar energy adoption rates at the residential scale. Since this study had explored the challenges and solution to these barriers, the outcomes of this study can be used by the policy maker as the fundamental to encourage the adoption of solar energy in the existing buildings where the current adoption rate is low

Yb-Doped: YCOB Laser (DIV)

A tunable, solid state laser device with both visible and infrared laser emission is developed with a trivalent ytterbium-doped yttrium calcium oxyborate crystal as the host crystal. The Yb:YCOB crystal generates an infrared fundamental light over a wide bandwidth, from approximately 980 nanometers (nm) to approximately 1100 nm. The bandwidth generated by the Yb:YCOB crystal is approximately 100 nm wide and supports the generation of pulsed infrared light or when self-frequency doubled provides a compact, efficient, source of tunable, visible, blue or green laser light in wavelengths of approximately 490 nm to approximately 550 nm