(2017) A novel ensemble classifier of rotation forest and Naïve Bayer for landslide susceptibility assessment at the Luc Yen district, Yen Bai Province (Viet Nam) using GIS, Geomatics, Natural Hazards and Risk, 8:2, 649-671, DOI: 10.1080/19475705.2016 ABSTRACTThe objective of this study is to attempt a new soft computing approach for assessment of landslide susceptibility in the Luc Yen district, Yen Bai province (Viet Nam) using a novel classifier ensemble model of Na€ ıve Bayes and Rotation Forest. First, history of 95 landslide locations was identified byfield investigations and interpretation of aerial photos. Also, the total ten landslide causal factors were selected (slope, aspect, elevation, curvature, lithology, land use, distance to roads, distance to rivers, distance to faults, and rainfall) to evaluate the spatial relationship with landslide occurrences. Information Gain technique is carried out to quantify the predictive capability of these factors. Second, landslide susceptibility assessment was carried out utilizing the novel classifier ensemble model. Finally, the performance of landslide model was validated using receiver operating characteristic curve technique, and statistical index-based evaluations. The novel classifier ensemble model indicates high prediction capability (AUC D 0.846) and relatively high accuracy (ACC D 78.77%). The study reveals that this model performs well in comparison to the other landslide models such as AdaBoost, Bagging, MultiBoost, and Random Forest. Overall, the novel classifier ensemble model is a promising method that could be used for landslide susceptibility assessment.

No abstract

In a time-varying transmission channel, the received signals are subject to frequency shifts due to the Doppler effect. The Doppler frequency is dependent on the carrier frequency and channel variation rate. In a fixed wireless channel, the channel variations are caused by scatterer motion. In this paper, we investigate analytically the Doppler effects generated by scatterer motion under different scatterer velocity distributions using the ring-of-scatterers geometric model. The proposed model considers Doppler frequency components caused by scatterer mobility to both received and reflected signals at each scatterer, and therefore is called the double Doppler model. The analytical curves are compared and statistically tested with several measurement results published in the literature. At low scatterer speeds, e.g., generated by moving foliage, the exponential velocity distribution is an appropriate model to describe the time-varying nature of the fixed wireless channels. The curve fitting results also show that our analytical model better approaches the empirical curves than the single Doppler model does. However, further investigation is still needed to find a suitable scatterer velocity distribution that closely describes the double Doppler effect in fast-variation fixed wireless channels, e.g., caused by passing vehicles.

No abstract

Gamma-aminobutyric acid (GABA) is an important bio-product, which is used in pharmaceutical formulations, nutritional supplements, and biopolymer monomer. The traditional GABA process involves the decarboxylation of glutamate. However, the direct production of GABA from glucose is a more efficient process. To construct the recombinant strains of Escherichia coli, a novel synthetic scaffold was introduced. By carrying out the co-localization of glutamate synthase, glutamate decarboxylase, and GABA transporter, we redirected the TCA cycle flux to GABA pathway. The genetically engineered E. coli strain produced 1.08 g/L of GABA from 10 g/L of initial glucose. Thus, with the introduction of a synthetic scaffold, we increased GABA production by 2.2-fold. The final GABA concentration was increased by 21.8% by inactivating competing pathways.