The Murchison meteorite is a carbonaceous chondrite containing a small amount of chondrules, various inclusions, and matrix with occasional porphyroblasts of olivine and/or pyroxene. It also contains amino acids that may have served as... more
The Murchison meteorite is a carbonaceous chondrite containing a small amount of chondrules, various inclusions, and matrix with occasional porphyroblasts of olivine and/or pyroxene. It also contains amino acids that may have served as the necessary components for the origin of life. Magnetic analyses of Murchison identify an ultrasoft magnetic component due to superparamagnetism as a significant part of the magnetic remanence. The rest of the remanence may be due to electric discharge in the form of lightning bolts that may have formed the amino acids. The level of magnetic remanence does not support this possibility and points to a minimum ambient field of the remanence acquisition. We support our observation by showing that normalized mineral magnetic acquisition properties establish a calibration curve suitable for rough paleofield determination. When using this approach, 1-2% of the natural remanence left in terrestrial rocks with TRM and/or CRM determines the geomagnetic field intensity irrespective of grain size or type of magnetic mineral (with the exception of hematite). The same method is applied to the Murchison meteorite where the measured meteorite remanence determines the paleofield minimum intensity of 200-2000 nT during and/or after the formation of the parent body.
"Forecasting reservoir inflow is important to hydropower reservoir management and scheduling. An Adaptive-Network-based Fuzzy Inference System (ANFIS) is successfully developed to forecast the long-term discharges in Manwan Hydropower.... more
"Forecasting reservoir inflow is important to hydropower reservoir management and scheduling. An Adaptive-Network-based Fuzzy Inference System (ANFIS) is successfully developed to forecast the long-term discharges in Manwan Hydropower. Using the long-term observations of discharges of monthly river flow discharges during 1953-2003, different types of membership functions and antecedent input flows associated with ANFIS model are tested. When compared to the ANN model, the ANFIS model has shown a significant forecast improvement. The training and validation results show that the ANFIS model is an effective algorithm to forecast the long-term discharges in Manwan Hydropower. The ANFIS model is finally employed in the advanced water resource project of Yunnan Power Group.
"The nature of construction claims is highly complicated and the cost involved is high. It will be advantageous if the parties to a dispute may know with some certainty how the case would be resolved if it were taken to court. The recent... more
"The nature of construction claims is highly complicated and the cost involved is high. It will be advantageous if the parties to a dispute may know with some certainty how the case would be resolved if it were taken to court. The recent advancements in artificial neural networks may render a cost-effective technique to help to predict the outcome of construction claims, on the basis of characteristics of cases and the corresponding past court decisions. In this paper, a split-step particle swarm optimization (PSO) model is applied to train perceptrons in order to predict the outcome of construction claims in Hong Kong. It combines the advantages of global search capability of PSO algorithm in the first step and the local convergence of back-propagation algorithm in the second step. It is shown that, through a real application case, its performance is much better than the benchmark backward propagation algorithm and the conventional PSO algorithm.
