ABSTRAK: Data debit biasanya tersedia lebih sedikit dibandingkan data curah hujan, sehingga perlu dicari suatu hubungan antara aliran sungai yang diterapkan dalam periode tersedia data curah hujan di suatu wilayah DAS. Tujuan dari studi ini adalah untuk mengetahui kesesuaian metode berdasarkan analisis validasi data antara debit pengamatan dengan debit model. Metode yang dilakukan dengan pemodelan debit berdasarkan curah hujan dengan model Artificial Neural Network (ANN) program MATLAB R2014b. Sub DAS Brantas Hulu digunakan sebagai studi kasus karena sering mengalami permasalahan limpasan. Validasi dari metode ANN diuji dengan Root Mean Square Error (RMSE), Nash-Sutcliffe Efficiency (NSE), Koefisien Korelasi (R) dan Kesalahan Relatif (KR). Dari hasil kalibrasi menggunakan Model ANN diperoleh data yang paling baik terdapat pada data lima tahun epoch 500. Hasil verifikasi berdasarkan nilai R mempunyai hubungan yang relatif baik antara debit pengamatan dengan debit model. Hasil validasi menunjukkan kevalidan pada data satu tahun epoch 500.Kata kunci: limpasan, model artifical neural network (ANN), uji nash sutchlife efficient (NSE), koefisien korelasi (R). ABSTRACT:Discharge data is usually less available than rainfall data, so it is necessary to find a relationship between river flows that are applied in the period available rainfall data in a watershed area. The purpose of this study is to determine the suitability of the method based on the analysis of data validation between the observed discharge and the model discharge. The method is done by modeling the discharge based on rainfall with the Artificial Neural Network (ANN) MATLAB R2014b program. The Upper Brantas Watershed is used as a case study because it often has runoff problems. Validation of the ANN method was tested with Root Mean Square Error (RMSE), Nash-Sutcliffe Efficiency (NSE), Correlation Coefficient (R) and Relative Error (KR). From the results of calibration using the ANN Model, the best data is found in the five years data of epoch 500. Verification results based on the value of R have a relatively good relationship between observation discharges with model discharges. The validation results show the validity in a year data of epoch 500.

Various analytical techniques have been used for size analysis of selenium nanoparticles (SeNPs). These include flow field-flow fractionation (FlFFF), single particle inductively coupled plasma mass spectrometry (SP-ICP-MS), dynamic light scattering (DLS) and transmission electron microscopy (TEM).For hydrodynamic diameter estimation, the FlFFF technique was used and the results were compared with those analyzed by DLS. For core diameter estimation, the results obtained from SP-ICP-MS were compared with those from TEM. Two types of FlFFF channel were employed, i.e., symmetrical FlFFF (Sy-FlFFF) and asymmetrical FlFFF (Asy-FlFFF). Considering the use of FlFFF, optimization was performed on a Sy-FlFFF channel to select the most appropriate carrier liquid and membrane in order to minimize problems due to particle membrane interaction. The use of FL-70 and 10 kDa RC provided an acceptable compromise peak quality and size accuracy for all samples of SeNPs which were coated by proteins (positively charged SeNPs) and sodium dodecyl sulfate (negatively charged SeNPs). FlFFF always yielded the lower estimate of the hydrodynamic size than DLS as a reference method. The results obtained by SP-ICP-MS were consistent with the TEM method for the core diameter estimation. The results from FlFFF and the DLS reference method were significantly different as confirmed by paired ttest analysis, while the results provided by SP-ICP-MS and the TEM reference method were not significantly different. Furthermore, consecutive size analysis by SP-ICP-MS for the fractions collected from FlFFF was proposed for sizing of SeNP mixtures. The combined technique helps to improve the size analysis in the complex samples and shows more advantages than using only SP-ICP-MS.

Iron occurs in plant fluids principally in the form of various low molecular species of which the quantitative determination is hampered by the dynamic equilibria and unavailability of authentic standards....