China has high incidence of gastric cancer (GC). However, the treatment outcomes of China were unsatisfactory compared to those of Korea. We performed this study to compare tumour characteristics, treatment parameters, and survival outcomes of GC patients between Korea and China based on the databases of two high-volume hospitals, with the aim of identifying indicators of GC prognosis. Data of patients undergoing gastrectomy for GC from 2006 to 2010 were analysed retrospectively. Subgroup survival analyses, stratified by clinicopathologic factors and multivariable analyses, were performed. The interactive roles of chemotherapy and D2 lymphadenectomy for overall survival were also investigated. Among 1365 Chinese and 4981 Korean patients, the proportion of early cancer detection in Chinese patients was much lower relative to that of Korean patients. There were no significant differences between countries in terms of surgical morbidity and mortality. The overall 5-year survival rates were 54.3% and 81.4%; when stratified by clinicopathologic factors, the survival were generally statistically higher in Korean patients. Gender, age, T stage, N stage, extent of lymphadenectomy, radicality of surgery, resection type, and chemotherapy were independently associated with survival in patients without metastasis. Survival rates for stage II and III GC differed significantly between the two countries, but this difference was eliminated among patients who underwent D2 lymphadenectomy or received chemotherapy. These treatments were given to patients with advanced-stage diagnoses (approximately 20% and 80% of patients, respectively). Treatment type was selected as independent prognostic factors in stage I–III and D2/D2+, with chemotherapy resulting in the best prognosis. Many differences in GC tumour characteristics exist between two countries. Early cancer detection and standardized treatment in Korea contribute to superior survival rates. Promotion of an early screening program, training and dissemination of standard D2 lymphadenectomy, and appropriate applications of chemotherapy would improve survival outcomes.

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This paper presents a detection algorithm for anomaly network traffic, which is based on spectral kurtosis analysis. Firstly, we turn network traffic into time-frequency signals at different scales. These time-frequency signals hold the more detailed nature corresponding to different scales. Secondly, the time-frequency signals at different scales are transformed into a series of new time signals by time-frequency analysis theory. These new time signals hold obvious narrowband nature and embody the local properties of network traffic. Thirdly, we calculate the spectral kurtosis values of the new time signals and then perform the feature extractions. As a result, the abnormal network traffic can be correctly identified. Simulation results show that our algorithm is feasible and promising.

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