Fraudulent credit card transactions must be when customers are charged for items that they did not purchase. Such problems can tackled with Data Science and its importance, along Machine Learning, cannot overstated. This project intends to illustrate the modelling of a data set using machine learning Identifying Fraud in Online Transactions. The Transactions problem includes past ones turned ou...

With dollar amounts in this lofty range, participants in the foreign exchange market could incur substantial losses if the other parties to their transactions ~s’ere to default on the payments required to settle their side of the transactions. To reduce the costs of transactions and limit the size of these possible losses, some banks engage in bilateral netting of their foreign exchange transac...

Long running transactions, such as online purchases, severely reduce throughput under standard locking protocols such as two-phase locking. We investigated the use of escrow transactions to remove the need to wait for locks, and thus reduced the average transaction runtime. Escrow transactions allow transactions to borrow a quantity from the record until the transaction aborts or commits and to...

This paper introduces the Mobile Nested Transactions (MNT) model for transaction processing coordination in groups of mobile devices. The model extends traditional approaches—centralized and distributed—for distributed transaction processing over mobile devices. Under the Nested Transactions approach, sub-transactions—logical work units—processing control is highly flexible and fault-tolerant. ...

Increasing successful rate of long running transactions is challenging in the heterogeneous environment because business processes become complex and the spanning time are unpredictable. This paper focuses on reducing the failure rate of completing transactions. A novel algorithm for flexible and semantic-based support to executing long running transactions is proposed. The algorithm is to prov...