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Field oceanographic and meteorological data are required for ocean engineering. In response to the requirement of field data, an operational coastal ocean monitoring network was established around Taiwan coast, including nine deep-water data buoys, one shallow-water pile station, 10 coastal weather stations and 10 tide stations. Data quality check procedures are necessary to ensure the accuracy of measurements. This paper presents the data quality check procedures on ocean wave data which includes automatic and manual check procedures. The checking criteria are derived using statistical theory in this paper. In addition, a sea-state-dependent algorithm is presented in this study in order to derive checking criteria of time-continuity check. It is showed to have better performance of picking up suspicious data than using fixed threshold process. This data quality check program is now used on the operational monitoring network.

A methodology is proposed for constructing a flood forecast model using the adaptive neuro-fuzzy inference system (ANFIS). This is based on a self-organizing rule-base generator, a feedforward network, and fuzzy control arithmetic. Given the rainfall-runoff patterns, ANFIS could systematically and effectively construct flood forecast models. The precipitation and flow data sets of the Choshui River in central Taiwan are analysed to identify the useful input variables and then the forecasting model can be self-constructed through ANFIS. The analysis results suggest that the persistent effect and upstream flow information are the key effects for modelling the flood forecast, and the watershed's average rainfall provides further information and enhances the accuracy of the model performance. For the purpose of comparison, the commonly used back-propagation neural network (BPNN) is also examined. The forecast results demonstrate that ANFIS is superior to the BPNN, and ANFIS can effectively and reliably construct an accurate flood forecast model. Copyright © 2005 John Wiley & Sons, Ltd.

To evaluate the effect of laparoscopic ovarian cystectomy for endometrioma on the clinical outcome of IVF treatment.Patients who received IVF treatment were retrospectively classified into two groups. Group 1 included 95 patients who received IVF due to tubal occlusion. Group 2 included 127 patients who had received laparoscopic ovarian cystectomy for endometrioma(s) followed by IVF treatment. Clinical outcomes of IVF treatment were compared between two groups.More oocytes were harvested per retrieval in Group 1 than Group 2 (p0.05). The fertilization rate was higher in Group 1 than Group 2 (p0.05). Although the implantation rate was higher in Group 2 (p0.05), the clinical pregnancy rate revealed no statistically significant difference between the two groups.Women who received ovarian cystectomy for endometriomas have fewer oocytes harvested during IVF treatment. However, their chance of pregnancy was comparable to patients with tubal problems who underwent IVF treatment.