A comparison of multi-classification methods for credit risk assessment in commercial banks

Credit Risk Assessment problem belongs essentially to an ordinal classification problem. How to construct an available assessing model is an important part in commercial banks credit management. In this paper, several multi-classification strategies, such as "One-against-rest", "One-against-one", "Directed Acyclic Graph", and "Embedded Space", are compared and applied them to construct credit risk assessment models respectively. By experiments, their assessing performances are compared and DAGSVM and ESSVM are more suitable for our purpose

Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)

Validation of remote-sensing reflectance (Rrs) products is necessary for the quantitative application of ocean color satellite data. While validation of Rrs products has been performed in low to moderate turbidity waters, their performance in highly turbid water remains poorly known. Here, we used in situ Rrs data from Hangzhou Bay (HZB), one of the world’s most turbid estuaries, to evaluate agency-distributed Rrs products for multiple ocean color sensors, including the Geostationary Ocean Color Imager (GOCI), Chinese Ocean Color and Temperature Scanner aboard HaiYang-1C (COCTS/HY1C), Ocean and Land Color Instrument aboard Sentinel-3A and Sentinel-3B, respectively (OLCI/S3A and OLCI/S3B), Second-Generation Global Imager aboard Global Change Observation Mission-Climate (SGLI/GCOM-C), and Visible Infrared Imaging Radiometer Suite aboard the Suomi National Polar-orbiting Partnership satellite (VIIRS/SNPP). Results showed that GOCI and SGLI/GCOM-C had almost no effective Rrs products in the HZB. Among the others four sensors (COCTS/HY1C, OLCI/S3A, OLCI/S3B, and VIIRS/SNPP), VIIRS/SNPP obtained the largest correlation coefficient (R) with a value of 0.7, while OLCI/S3A obtained the best mean percentage differences (PD) with a value of −13.30%. The average absolute percentage difference (APD) values of the four remote sensors are close, all around 45%. In situ Rrs data from the AERONET-OC ARIAKE site were also used to evaluate the satellite-derived Rrs products in moderately turbid coastal water for comparison. Compared with the validation results at HZB, the performances of Rrs from GOCI, OLCI/S3A, OLCI/S3B, and VIIRS/SNPP were much better at the ARIAKE site with the smallest R (0.77) and largest APD (35.38%) for GOCI, and the worst PD for these four sensors was only −13.15%, indicating that the satellite-retrieved Rrs exhibited better performance. In contrast, Rrs from COCTS/HY1C and SGLI/GCOM-C at ARIAKE site was still significantly underestimated, and the R values of the two satellites were not greater than 0.7, and the APD values were greater than 50%. Therefore, the performance of satellite Rrs products degrades significantly in highly turbid waters and needs to be improved for further retrieval of ocean color components

Comparative Pharmacokinetic Study of Forchlorfenuron in Adult and Juvenile Rats

Forchlorfenuron (CPPU) is a plant growth regulator extensively used in agriculture. However, studies on CPPU pharmacokinetics are lacking. We established and validated a rapid, sensitive, and accurate liquid chromatography–mass spectrometry method for CPPU detection in rat plasma. CPPU pharmacokinetics was evaluated in adult and juvenile rats orally treated with 10, 30, and 90 mg/kg of the compound. The area under the plasma drug concentration–time curve from 0 to 24 h (AUC), at the final time point sampled (AUC0–t), and the maximum drug concentration of CPPU increased in a dose-dependent manner. The pharmacokinetic parameters AUC0–t and absolute bioavailability were higher in the juvenile rats than in adult rats. The mean residence time and AUC0–t of juvenile rats in the gavage groups, except for the 10 mg/kg dose, were significantly higher in comparison to those observed for adult rats (p < 0.001). The plasma clearance of CPPU in juvenile rats was slightly lower than that in the adult rats. Taken together, juvenile rats were more sensitive to CPPU than adult rats, which indicates potential safety risks of CPPU in minors

Evaluating Atmospheric Correction Methods for Sentinel−2 in Low−to−High−Turbidity Chinese Coastal Waters

Inaccuracies in the atmospheric correction (AC) of data on coastal waters significantly limit the ability to quantify the parameters of water quality. Many studies have compared the effects of the atmospheric correction of data provided by the Sentinel−2 satellites, but few have investigated this issue for coastal waters in China owing to a limited amount of in situ spectral data. The authors of this study compared four processors for the atmospheric correction of data provided by Sentinel−2—the Atmospheric Correction for OLI ‘lite’(ACOLITE), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System (SeaDAS), Polynomial-based algorithm applied to MERIS (POLYMER), and Case 2 Regional Coast Colour (C2RCC)—to identify the most suitable one for water bodies with different turbidities along the coast of China. We tested the algorithms used in these processors for turbid waters and compared the resulting inversion of the remote sensing reflectance (Rrs) using in situ reflectance data from three stations with varying levels of coastal turbidity (HTYZ, DONG’OU, and MUPING). All processors significantly underestimated the results on data from the HTYZ station, which is located along waters with high turbidity, with the SeaDAS delivering the best performance, with an average band RMSE of 0.0146 and an average MAPE of 29.80%. It was followed by ACOLITE, with an average band RMSE of 0.0213 and an average MAPE of 43.43%. The performance of two AC algorithms used in ACOLITE, dark spectrum fitting (DSF) and exponential extrapolation (EXP), was also evaluated by comparing their results with in situ measurements at the HTYZ site. The ACOLITE-EXP algorithm delivered a slight improvement in results for the blue band compared with the DSF algorithm in highly turbid water, but led to no significant improvement in the green and red bands. C2RCC delivered the best performance on data from the DONG’OU station, which is located along water with medium turbidity, and from the MUPING station (water with low turbidity), with values of the MAPE of 18.58% and 28.41%, respectively