A Graph Theoretical Approach for Identifying Fraudulent Transactions in Circular Trading

Circular trading is an infamous technique used by tax evaders to confuse tax enforcement officers from detecting suspicious transactions. Dealers using this technique superimpose suspicious transactions by several illegitimate sales transactions in a circular manner. In this paper, we address this problem by developing an algorithm that detects circular trading and removes the illegitimate cycles to uncover the suspicious transactions. We formulate the problem as finding and then deleting specific type of cycles in a directed edge-labeled multigraph. We run this algorithm on the commercial tax data set provided by the government of Telangana, India, and discovered several suspicious transactions

Proceedings of the 8th Cologne-Twente Workshop on Graphs and Combinatorial Optimization

International audienceThe Cologne-Twente Workshop (CTW) on Graphs and Combinatorial Optimization started off as a series of workshops organized bi-annually by either Köln University or Twente University. As its importance grew over time, it re-centered its geographical focus by including northern Italy (CTW04 in Menaggio, on the lake Como and CTW08 in Gargnano, on the Garda lake). This year, CTW (in its eighth edition) will be staged in France for the first time: more precisely in the heart of Paris, at the Conservatoire National d’Arts et Métiers (CNAM), between 2nd and 4th June 2009, by a mixed organizing committee with members from LIX, Ecole Polytechnique and CEDRIC, CNAM

LIPIcs, Volume 274, ESA 2023, Complete Volume

LIPIcs, Volume 274, ESA 2023, Complete Volum

Mathematical Foundations for Balancing the Payment System in the Trade Credit Market

The increasingly complex economic and financial environment in which we live makes the management of liquidity in payment systems and the economy in general a persistent challenge. New technologies make it possible to address this challenge through alternative solutions that complement and strengthen existing payment systems. For example, interbank balancing and clearing methods (such as real-time gross settlement) can also be applied to private payments, complementary currencies, and trade credit clearing to provide better liquidity and risk management. The paper defines the concept of a balanced payment system mathematically and demonstrates the effects of balancing on a few small examples. It then derives the construction of a balanced payment subsystem that can be settled in full and therefore that can be removed in toto to achieve debt reduction and payment gridlock resolution. Using well-known results from graph theory, the main output of the paper is the proof—for the general formulation of a payment system with an arbitrary number of liquidity sources—that the amount of liquidity saved is maximum, along with a detailed discussion of the practical steps that a lending institution can take to provide different levels of service subject to the constraints of available liquidity and its own cap on total overdraft exposure. From an applied mathematics point of view, the original contribution of the paper is two-fold: (1) the introduction of a liquidity node with a store of value function in obligation-clearing; and (2) the demonstration that the case with one or more liquidity sources can be solved with the same mathematical machinery that is used for obligation-clearing without liquidity. The clearing and balancing methods presented are based on the experience of a specific application (Tetris Core Technologies), whose wider adoption in the trade credit market could contribute to the financial stability of the whole economy and a better management of liquidity and risk overall.Peer reviewe

Book of Abstracts of the Sixth SIAM Workshop on Combinatorial Scientific Computing

Book of Abstracts of CSC14 edited by Bora UçarInternational audienceThe Sixth SIAM Workshop on Combinatorial Scientific Computing, CSC14, was organized at the Ecole Normale Supérieure de Lyon, France on 21st to 23rd July, 2014. This two and a half day event marked the sixth in a series that started ten years ago in San Francisco, USA. The CSC14 Workshop's focus was on combinatorial mathematics and algorithms in high performance computing, broadly interpreted. The workshop featured three invited talks, 27 contributed talks and eight poster presentations. All three invited talks were focused on two interesting fields of research specifically: randomized algorithms for numerical linear algebra and network analysis. The contributed talks and the posters targeted modeling, analysis, bisection, clustering, and partitioning of graphs, applied in the context of networks, sparse matrix factorizations, iterative solvers, fast multi-pole methods, automatic differentiation, high-performance computing, and linear programming. The workshop was held at the premises of the LIP laboratory of ENS Lyon and was generously supported by the LABEX MILYON (ANR-10-LABX-0070, Université de Lyon, within the program ''Investissements d'Avenir'' ANR-11-IDEX-0007 operated by the French National Research Agency), and by SIAM

LIPIcs, Volume 244, ESA 2022, Complete Volume

LIPIcs, Volume 244, ESA 2022, Complete Volum

Fast Construction of Relational Features for Machine Learning

Katedra kybernetik

Assembly, quantification, and downstream analysis for high trhoughput sequencing data

Next Generation Sequencing is a set of relatively recent but already well-established technologies with a wide range of applications in life sciences. Despite the fact that they are constantly being improved, multiple challenging problems still exist in the analysis of high throughput sequencing data. In particular, genome assembly still suffers from inability of technologies to overcome issues related to such structural properties of genomes as single nucleotide polymorphisms and repeats, not even mentioning the drawbacks of technologies themselves like sequencing errors which also hinder the reconstruction of the true reference genomes. Other types of issues arise in transcriptome quantification and differential gene expression analysis. Processing millions of reads requires sophisticated algorithms which are able to compute gene expression with high precision and in reasonable amount of time. Following downstream analysis, the utmost computational task is to infer the activity of biological pathways (e.g., metabolic). With many overlapping pathways challenge is to infer the role of each gene in activity of a given pathway. Assignment products of a gene to a wrong pathway may result in misleading differential activity analysis, and thus, wrong scientific conclusions. In this dissertation I present several algorithmic solutions to some of the enumerated problems above. In particular, I designed scaffolding algorithm for genome assembly and created new tools for differential gene and biological pathways expression analysis