Anti-Fraud Schema System for Identification and Prevention of Fraud Behaviors in E-Commerce Services

This study aims to determine the best practices and provide a model of the technical solutions that can effectively and systematically limit fraudulent transactions of online orders in e-commerce services, using the methods of analytical mining and case studies. Based on a process of fraud prevention and detection performed in the e-business Dangdang, Inc., a leading online retailer in China, twelve identifying features of fraudulent order data were extracted and compiled into a feature matrix. Logistic regression with this matrix was then used to build a model to judge if an order was fraudulent. The model was tested using various order data with machine learning techniques to meet the requirements of being effective, correct, adaptive, and persistent. Then an online detection and prevention schema was established and the hypothesis of so-called Behavior Pattern Change Assumption (BPCA) was proven. The results show the model can detect 94% of fraudulent orders. The Anti-fraud Schema System established for Dangdang is shown to be the best model for the determination and prevention of fraudulent behaviors in the e-commerce services

Rank Stability Radius for a Matrix with Structured Scalar Perturbations

In this paper, the rank stability radius problem is proposed for a real matrix under structured scalar perturbations and some interesting results are achieved based on polynomial analysis. In addition, a computable formula and a two-step procedure are obtained which nicely solves the problem in this simple set up. Finally, these results on rank stability radius are used to estimate the stability robustness of descriptor systems, and for a special class of symmetric descriptor systems, the rank stability radius is proved to be equal to the system stability radius

Inhibition of hepatocelluar carcinoma MAT2A and MAT2beta gene expressions by single and dual small interfering RNA

RNA interference (RNAi) has been successfully applied in suppression of hepatic cancer genes. In hepatocelluar carcinoma cell, one methionine adenosyltransferase (MAT) isozyme, MATII was found to have two catalytic subunits which were encoded by MAT2A and MAT2β respectively. During tumorigeness of hepatocelluar carcinoma, expressions of the two genes were discovered to be increased combining with a switch of MAT (form MATI to MATII), To figure out the role played by MATII in hepatic cancer, In this study, for the first time we established a dual small interfering RNA (siRNA) expression system, which could simultaneously express two different siRNA molecules specifically targeting two genes. To test the effectiveness of this system, we applied this approach to express simultaneously two different siRNA duplexes that specifically target MAT2A and MAT2β genes of hepatocelluar carcinoma respectively in HepG2 cell. Results indicated that dual siRNA could simultaneously inhibit the expression of MAT2A and MAT2β gene by 89.5% and 97.8% respectively, In addition, dual siRNA molecules were able to significantly suppress growth of hepatocelluar carcinoma cell in vitro as well as induce apoptosis which was involved in arrest cell cycle at the G1/S checkpoint and the expressions of p21, p27 and Bax

High-Tech Service Platform Ecosystem Evolution: A Simulation Analysis using Lotka-Volterra Model

Technical service platform exerts a strong effect on supporting the innovation of the high-tech industry as a critical constituent of the modern service industry, and it can effectively enhance the development potential of technological innovation, but the degree of separation from technical service chain to high-tech industry chain is currently high. To explore how to improve the utilization efficiency of scientific and technological resources and facilitate the sustainable development of the high-tech industry by relying on technical service platform,a high-tech service platform was constructed by using Lotka-Volterra (L-V) model on the basis of ecosystem theory, the evolution path and stability conditions of high-tech service platform were analyzed followed by numerical simulation by Matlab computing. Results show that the development of hightech service platform follows the evolution path of "bilateral platform → core platform → platform ecosystem"; population evolution pattern in high-tech service platform ecosystem is decided by interdependence coefficient between populations; populations inside high-tech service platform ecosystem generate natural selection and synergistic effect and realize ecological balance among populations through evolution. Evolution of high-tech service platform system in this study provides a new theoretical framework for effective fusion and collaboration of science and technology service and industry, which is significant for elevating scientific and technological innovation level and improving technical service system construction

Research on the Automatic Generation Control (AGC) Coordinated Control Modes between Provincial Dispatching and Regional Dispatching in Yunnan Power Grid

AbstractWith the constant expansion of Yunnan power grid, in current dispatching Automatic generation Control (AGC) mode, the use effect of small and medium-sized hydropower resources in the unified dispatching was not ideal. By building zoning control model artificially, the control targets and their coordinated relationship between main area and sub-areas are explicitly pointed out .The zoning and layered control mode of AGC between provincial dispatching and regional dispatching is put forward. Analysis and comparison are also made of the “independent zoning and layered control mode” and “coordinated zoning and layered control mode”, and then their existing problems are pointed out. The research can provide the foundation of further study on AGC coordinated control strategies between provincial dispatching and regional dispatching, which can realize single goal and multi-objects of AGC coordinated control in the power grid

Evolution and Biogeography of the Slipper Orchids: Eocene Vicariance of the Conduplicate Genera in the Old and New World Tropics

Intercontinental disjunctions between tropical regions, which harbor two-thirds of the flowering plants, have drawn great interest from biologists and biogeographers. Most previous studies on these distribution patterns focused on woody plants, and paid little attention to herbs. The Orchidaceae is one of the largest families of angiosperms, with a herbaceous habit and a high species diversity in the Tropics. Here we investigate the evolutionary and biogeographical history of the slipper orchids, which represents a monophyletic subfamily (Cypripedioideae) of the orchid family and comprises five genera that are disjunctly distributed in tropical to temperate regions. A relatively well-resolved and highly supported phylogeny of slipper orchids was reconstructed based on sequence analyses of six maternally inherited chloroplast and two low-copy nuclear genes (LFY and ACO). We found that the genus Cypripedium with a wide distribution in the northern temperate and subtropical zones diverged first, followed by Selenipedium endemic to South America, and finally conduplicate-leaved genera in the Tropics. Mexipedium and Phragmipedium from the neotropics are most closely related, and form a clade sister to Paphiopedilum from tropical Asia. According to molecular clock estimates, the genus Selenipedium originated in Palaeocene, while the most recent common ancestor of conduplicate-leaved slipper orchids could be dated back to the Eocene. Ancestral area reconstruction indicates that vicariance is responsible for the disjunct distribution of conduplicate slipper orchids in palaeotropical and neotropical regions. Our study sheds some light on mechanisms underlying generic and species diversification in the orchid family and tropical disjunctions of herbaceous plant groups. In addition, we suggest that the biogeographical study should sample both regional endemics and their widespread relatives

Active Implicit Object Reconstruction using Uncertainty-guided Next-Best-View Optimziation

Actively planning sensor views during object reconstruction is essential to autonomous mobile robots. This task is usually performed by evaluating information gain from an explicit uncertainty map. Existing algorithms compare options among a set of preset candidate views and select the next-best-view from them. In contrast to these, we take the emerging implicit representation as the object model and seamlessly combine it with the active reconstruction task. To fully integrate observation information into the model, we propose a supervision method specifically for object-level reconstruction that considers both valid and free space. Additionally, to directly evaluate view information from the implicit object model, we introduce a sample-based uncertainty evaluation method. It samples points on rays directly from the object model and uses variations of implicit function inferences as the uncertainty metrics, with no need for voxel traversal or an additional information map. Leveraging the differentiability of our metrics, it is possible to optimize the next-best-view by maximizing the uncertainty continuously. This does away with the traditionally-used candidate views setting, which may provide sub-optimal results. Experiments in simulations and real-world scenes show that our method effectively improves the reconstruction accuracy and the view-planning efficiency of active reconstruction tasks. The proposed system is going to open source at https://github.com/HITSZ-NRSL/ActiveImplicitRecon.git.Comment: 8 pages, 10 figures, Submitted to IEEE Robotics and Automation Letters (RA-L