Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection

With the explosive growth of e-commerce, online transaction fraud has become one of the biggest challenges for e-commerce platforms. The historical behaviors of users provide rich information for digging into the users' fraud risk. While considerable efforts have been made in this direction, a long-standing challenge is how to effectively exploit internal user information and provide explainable prediction results. In fact, the value variations of same field from different events and the interactions of different fields inside one event have proven to be strong indicators for fraudulent behaviors. In this paper, we propose the Dual Importance-aware Factorization Machines (DIFM), which exploits the internal field information among users' behavior sequence from dual perspectives, i.e., field value variations and field interactions simultaneously for fraud detection. The proposed model is deployed in the risk management system of one of the world's largest e-commerce platforms, which utilize it to provide real-time transaction fraud detection. Experimental results on real industrial data from different regions in the platform clearly demonstrate that our model achieves significant improvements compared with various state-of-the-art baseline models. Moreover, the DIFM could also give an insight into the explanation of the prediction results from dual perspectives.Comment: 11 pages, 4 figure

The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family

A Ranking Procedure by Incomplete Pairwise Comparisons Using Information Entropy and Dempster-Shafer Evidence Theory

Decision-making, as a way to discover the preference of ranking, has been used in various fields. However, owing to the uncertainty in group decision-making, how to rank alternatives by incomplete pairwise comparisons has become an open issue. In this paper, an improved method is proposed for ranking of alternatives by incomplete pairwise comparisons using Dempster-Shafer evidence theory and information entropy. Firstly, taking the probability assignment of the chosen preference into consideration, the comparison of alternatives to each group is addressed. Experiments verified that the information entropy of the data itself can determine the different weight of each group’s choices objectively. Numerical examples in group decision-making environments are used to test the effectiveness of the proposed method. Moreover, the divergence of ranking mechanism is analyzed briefly in conclusion section

Risk Assessment of Falling Objects from Façades of Existing Buildings

Falling objects from façades often lead to serious accidents, which has become a technical problem to be solved urgently. This paper established a database of potential safety hazard of falling objects from façades via the statistics of detection façades in Shanghai. Some detailed insufficiencies and swelling defects were analyzed. A risk assessment system of falling objects from façades was established using the Fault Tree Analysis (FTA) method. The weight coefficient was determined by the Analytic Hierarchy Process (AHP). The beta distribution was used to fit the probability distribution of the occurrence probability of the elementary risk event. Based on the Monte Carlo model, the risk of falling objects from façades was assessed. A probability distribution of the risk probability of falling objects from façades and the importance of elementary risk factors were obtained. Some risk control measures of falling objects from façades were proposed

Adsorption Behavior of NO and NO₂ on Two-Dimensional As, Sb, and Bi Materials: First-Principles Insights

To address the most significant environmental challenges, the quest for high-performance gas sensing materials is crucial. Among numerous two-dimensional materials, this study investigates the gas-sensitive capabilities of monolayer As, Sb, and Bi materials. To compare the gas detection abilities of these three materials, we employ first-principles calculations to comprehensively study the adsorption behavior of NO and NO2 gas molecules on the material surfaces. The results indicate that monolayer Bi material exhibits reasonable adsorption distances, substantial adsorption energies, and significant charge transfer for both NO and NO2 gases. Therefore, among the materials studied, it demonstrates the best gas detection capability. Furthermore, monolayer As and Sb materials exhibit remarkably high capacities for adsorbing NO and NO2 gas molecules, firmly interacting with the gas molecules. Gas adsorption induces changes in the material’s work function, suggesting the potential application of these two materials as catalysts