An Investigation of Landslide Susceptibility Using Logistic Regression and Statistical Index Methods in Dailekh District, Nepal

Landslide distribution and susceptibility mapping are the fundamental steps for landslide-related hazard and disaster risk management activities, especially in the Himalaya region which has resulted in a great deal of death and damage to property. To better understand the landslide condition in the Nepal Himalaya, we carried out an investigation on the landslide distribution and susceptibility using the landslide inventory data and 12 different contributing factors in the Dailekh district, Western Nepal. Based on the evaluation of the frequency distribution of the landslide, the relationship between the landslide and the various contributing factors was determined.Then, the landslide susceptibility was calculated using logistic regression and statistical index methods along with different topographic(slope, aspect, relative relief, plan curvature, altitude, topographic wetness index) and non-topographic factors(distance from river, normalized difference vegetation index(NDVI), distance from road, precipitation, land use and land cover, and geology), and 470(70%) of total 658 landslides. The receiver operating characteristic(ROC) curve analysis using 198(30%) of total landslides showed that the prediction curve rates(area under the curve, AUC) values for two methods(logistic regression and statistical index) were 0.826, and 0.823with success rates of 0.793, and 0.811, respectively. The values of R-Index for the logistic regression and statistical index methods were83.66 and 88.54, respectively, consisting of high susceptible hazard classes. In general, this research concluded that the cohesive and coherent natural interplay of topographic and non-topographic factors strongly affects landslide occurrence, distribution, and susceptibility condition in the Nepal Himalaya region. Furthermore, the reliability of these two methods is verified for landslide susceptibility mapping in Nepal’s central mountain region.

On improving the statistical index system of the circulation industry in China

With the rapid development of China economy,especially the rapid spread of information technology,circulation industry develops quickly and plays a more and more important role in macro economy,so it is very necessary to scientifically and effectively measure the industry operation and the impact on national economy.This paper analyzes the problems of the present statistical index system and setting of indicators and proposes some suggestions on improving the statistical index system and setting of indicators in domestic trade,so as to improve the statistical system in circulation industry,thus make a better evaluation and assessment of the operation and development of the industry and furthermore provide a more scientific and precise basis for policy-making in economic activities.

On the Statistical Index System for Towns

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Research on the statistics index system and evaluation method of high and new technology industry development

During the evolution of the global economic, high and new technology industry has become the main driver to impel the global economy growth via technological advancement, and the main means to guarantee the sustainable development of the global economy. In the view of China’s situation, this article analyzes the experiences of OECD in high and new technology industry and gives a statistics index system along with the evaluation method to estimate the development of high and new technology industry.

Fault Detection Based on Incremental Locally Linear Embedding for Satellite TX-I

A fault detection method based on incremental locally linear embedding(LLE)is presented to improve fault detecting accuracy for satellites with telemetry data.Since conventional LLE algorithm cannot handle incremental learning,an incremental LLE method is proposed to acquire low-dimensional feature embedded in high-dimensional space.Then,telemetry data of Satellite TX-I are analyzed.Therefore,fault detection are performed by analyzing feature information extracted from the telemetry data with the statistical indexes T2 and squared prediction error(SPE)and SPE.Simulation results verify the fault detection scheme.

Quantified evaluation of particle shape effects from micro-to-macro scales for non-convex grains

Particle shape plays an important role in both the micro and macro scales responses of a granular assem- bly. This paper presents a systematic way to interpret the shape effects of granular material during quasi-static shearing. A more suitable shape descriptor is suggested for the quantitative analysis of the macroscale strength indexes and contact parameters for non-convex grains, with special consid- eration given to the peak state and critical state. Through a series of numerical simulations and related post-processing analysis, particle shape is found to directly influence the strain localisation patterns, microscale fabric distributions, microscale mobilisation indexes, and probability distribution of the nor- malised contact normal force. Additionally, the accuracy of the stress-force-fabric relationship can be influenced by the average normal force and the distribution of contact vectors. Moreover, particle shape plays a more important role than do the confining pressures in determining the friction angle. Strong force chains and the dilation effect are also found to be strongly influenced by the high confinin~ oressure.