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Impact of sea-level change on coastal areas has long been a concern of the world, especially the coastal countries. It is an important part in the research of the marine environment. Sea-level change is caused by various social and environmental reasons, among which the contribution of the Antarctic ice caps mass change is a significant factor. In order to investigate the correlation between sea-level change of Chinese coastal areas and the Antarctic ice caps mass change, several geo-statistical methods were involved in this paper. The Antarctic equivalent water height and sea level anomaly datasets were applied. First, the periods of the two datasets above-mentioned are found though the spectrum analysis and a further analysis of these periods is made. Then the correlation analysis is carried out using the time series which span from January 2004 to March 2010. Through the rapid inverse Fourier transform we obtained the cross-correlation function, drew cross-correlation function diagram and analyzed correlation degree and the lag time of these two time series. Research shows that (1) the sea level change has a year cycle as the leading period, meanwhile equivalent water height change has a half year cycle as the leading factor and display a complicated multi-scale coupling fluctuation characteristic; (2) The cross-correlation function diagram indicates that these two time series highly positive correlated when the lag time is 8 month and highly negative correlated when the lag time is 26 month. There is a teleconnection between these two events. Sea level change has become more and more important part of the global change and closely related to people's life. Tiny sea level rise will cause aggravating flooding in large tracts of land and coastal erosion and consequence is unimaginable. China's mainland coastline is about 18, 000 km long. About more than 70% of the big cities and more than 50% of the population is concentrated in the eastern coastal areas, which are the most economically developed areas in China. But they are also the most serious vulnerable regions affected by sea level change that will aggravate natural disasters and influence the social economic development in the coastal areas. The fluctuation of the global sea-level change is mainly caused by the global sea water density and mass change. The former factor is mainly caused by the temperature and salinity changes and the latter is influenced by snow and ice ablation and cumulative, precipitation, evaporation, overland runoff and sea-air-land water circulating. With the aggravation of the greenhouse effect, thermal expansion caused by the snow and ice melting and temperature rising has become an important reason of global sea-level change. According to the results of ocean general circulation models (OGCMs) simulation, the thermal expansion is the largest contribution to the sea-level rise in the recent fifty years, which is about 0.3~0.7mm/yr. While the sea-level rise aroused by non polar glacier melting and by Greenland and Antarctic ice mass changes is 0.2~0.4mm/yr and 0.2~0.6mm/yr respectively (1). It's pointed that in the past decade sea-level change due to thermal expansion and non polar glacier change is totally 2.37mm/yr. Compared to the observation of 3.1mm/yr, there still is a discrepancy of 0.73mm/yr, which is the contribution of the polar ice caps changes (2).The polar ice areas are universally recognized to be sensitive and key areas in the research of global change. Investigating the mass balance of Antarctic ice caps plays a key role to make a further know about the global mean sea level changes and other related problems. Therefore, within the framework of a global change research project, the study of the correlation between sea-level change and the Antarctic ice caps melt, as a sub subject, is of great significance to the global climate and marine environment research, which can reduce the uncertainty of evaluating the contribution of the polar ice caps melt to the sea- level rise.

The performance analysis of manufacturing system originates from enterprise financial analysis, its purpose is to objectively analyze and evaluate the factors that can reflect the whole circumstance of the system by gathering all kinds of data in manufacturing system. This thesis mainly studies on the cash flow, which can reflect the managing and operating ability of modern manufacturing system, makes mapping between business indexes and manufacturing process indexes, builds evaluation model based on management accounting, which has the advantages of convenience, promptness and exactness. In the end, this thesis demonstrates the effectiveness of the model through example analysis.

Based on market-structure theory, targeted at the real estate industry in Tianjin, and adopted the data from 1996 till 2006, analyze the real estate market structure and the relationship between its performances. The results show that: the higher the degree of industrial concentration, the higher of the profit margin.

Resource-based cities have to optimize their industry structures to fulfill sustainable development. During this procedure, they should supervise the developing efficiency of those dominant industries, it helps to judge whether the structure adjustment is on the right way. The beyond-efficiency DEA (BE-DEA)model is perfect to such evaluation, it can trace the dynamic efficiency, avoid the passiveness and waste of afterward evaluation. This paper applies this BE-DEA model to an oil resource city, evaluates its dominant industries' developing efficiency both horizontal and vertical. The result offers quantitative proof to adjust the target or policy, and demonstrates BE-DEA model's superiority.