Application of Integrated Artificial Neural Networks Based on Decomposition Methods to Predict Streamflow at Upper Indus Basin, Pakistan

Consistent streamflow forecasts play a fundamental part in flood risk mitigation. Population increase and water cycle intensification are extending not only globally but also among Pakistan’s water resources. The frequency of floods has increased in the last few decades in the country, which emphasizes the importance of efficient practices needed to adopt for various aspects of water resource management such as reservoir scheduling, water sustainability, and water supply. The purpose of this study is to develop a novel hybrid model for streamflow forecasting and validate its efficiency at the upper Indus basin (UIB), Pakistan. Maximum streamflow in the River Indus from its upper mountain basin results from melting snow or glaciers and climatic unevenness of both precipitation and temperature inputs, which will, therefore, affect rural livelihoods at both a local and a regional scale through effects on runoff in the Upper Indus basin (UIB). This indicates that basins receive the bulk of snowfall input to sustain the glacier system. The present study will help find the runoff from high altitude catchments and estimated flood occurrence for the proposed and constructed hydropower projects of the Upper Indus basin (UIB). Due to climate variability, the upper Indus basin (UIB) was further divided into three zone named as sub-zones, zone one (z1), zone two (z2), and zone three (z3). The hybrid models are designed by incorporating artificial intelligence (AI) models, which includes Feedforward backpropagation (FFBP) and Radial basis function (RBF) with decomposition methods. This includes a discrete wavelet transform (DWT) and ensemble empirical mode decomposition (EEMD). On the basis of the autocorrelation function and the cross-correlation function of streamflow, precipitation and temperature inputs are selected for all developed models. Data have been analyzed by comparing the simulation outputs of the models with a correlation coefficient (R), root mean square errors (RMSE), Nash-Sutcliffe Efficiency (NSE), mean absolute percentage error (MAPE), and mean absolute errors (MAE). The proposed hybrid models have been applied to monthly streamflow observations from three hydrological stations and 17 meteorological stations in the UIB. The results show that the prediction accuracy of the decomposition-based models is usually better than those of AI-based models. Among the DWT and EEMD based hybrid model, EEMD has performed significantly well when compared to all other hybrid and individual AI models. The peak value analysis is also performed to confirm the results’ precision rate during the flood season (May-October). The detailed comparative analysis showed that the RBFNN integrated with EEMD has better forecasting capabilities as compared to other developed models and EEMD-RBF can capture the nonlinear characteristics of the streamflow time series during the flood season with more precision

The reliability and diagnostic value of radiographic criteria in sagittal spine deformities: Comparison of the vertebral wedge ratio to the segmental Cobb angle

STUDY DESIGN. A prospective, radiographic cohort study. OBJECTIVES. This study assessed the radiographic reliability and diagnostic value of the vertebral wedge ratio (WR) to the more segmental Cobb angle (CA) regarding sagittal spine deformities. SUMMARY OF BACKGROUND DATA. The use of the CA has been used to assist in the radiographic diagnosis of various sagittal spine deformities. However, the reliability and diagnostic aptitude of the CA remains speculative and may not be as receptive to individual variations of vertebral integrity in sagittal spine deformities. METHODS. Sixty patients (age range, 8-21 years) who were diagnosed with Scheuermann's kyphosis (Group 1; n = 16), with postural roundback (Group 2; n = 23), or who were regarded normal (Group 3; n = 21) were radiographically evaluated to assess the reliability and diagnostic potential of the vertebral WR (apex of the curve and 2 adjacent vertebrae) and segmental CA. Radiographic assessment was conducted by 3 independent blinded observers on 3 separate occasions. RESULTS. Very strong intraobserver (WR a = 0.85-0.99; CA a = 0.97-0.99) and interobserver (WR a = 0.79-0.89; CA a = 0.95) reliabilities were noted. A greater degree of WR reliability was noted in Group 1, whereas CA reliability remained consistent in all Groups. A statistically significant difference was found between all Groups in relation to vertebral WR and segmental CA (P < 0.05). Based on relative risk ratio analyses, an apex wedge ratio of ≤0.80 and/or a segmental Cobb angle of ≥20° is highly and significantly associated with Scheuermann's kyphosis. CONCLUSION. The segmental CA exhibited a higher degree of reliability than the vertebral WR. The apex vertebral WR exhibited the greatest amount of wedging in the Scheuermann's patients; whereas in the other groups it remained largely consistent with the adjacent vertebral WRs. An apex vertebral WR ≤0.80 and/or a segmental CA of ≥20° are highly associated with the clinical diagnosis of Scheuermann's kyphosis. If the segmental CA cannot be ascertained, the apex vertebral WR is a relatively strong reliable alternative, primarily with regards to Scheuermann's kyphosis. In addition, the type of deformity may potentially dictate the ideal measuring method. © 2007 Lippincott Williams & Wilkins, Inc.link_to_subscribed_fulltex

Excitation of autoionization states in O₂ by using high-order harmonics

Photoionization of oxygen molecules by high-order harmonics was investigated. High-order harmonics of a Ti:sapphire laser produced in a Kr gas cell were used to excite autoionization states of O₂. Since the high-order harmonic source used contains several harmonic orders, the resulting photoelectron spectrum also showed multiple peaks coming from different orders of harmonics. A subtraction method using known photoionization cross-sections was employed to separate out individual contributions from the harmonics. The photoelectron spectrum from the 11th harmonic shows a clean contribution from an autoionizing state