Development of Deep Learning based Intelligent Approach for Credit Card Fraud Detection

Credit card fraud (CCF) has long been a major concern of institutions of financial groups and business partners, and it is also a global interest to researchers due to its growing popularity. In order to predict and detect the CCF, machine learning (ML) has proven to be one of the most promising techniques. But, class inequality is one of the main and recurring challenges when dealing with CCF tasks that hinder model performance. To overcome this challenges, a Deep Learning (DL) techniques are used by the researchers. In this research work, an efficient CCF detection (CCFD) system is developed by proposing a hybrid model called Convolutional Neural Network with Recurrent Neural Network (CNN-RNN). In this model, CNN acts as feature extraction for extracting the valuable information of CCF data and long-term dependency features are studied by RNN model. An imbalance problem is solved by Synthetic Minority Over Sampling Technique (SMOTE) technique. An experiment is conducted on European Dataset to validate the performance of CNN-RNN model with existing CNN and RNN model in terms of major parameters. The results proved that CNN-RNN model achieved 95.83% of precision, where CNN achieved 93.63% of precision and RNN achieved 88.50% of precision

Comparative assessment-conventional manufacturing and remanufacturing of heavy vehicles drum brake shoe by life cycle assessment

Brake shoe remanufacturing is the best alternative mode of sustainable manufacturing when compared to conventional manufacturing”. This fact was evolved mainly due to the less remanufacturing costs and lesser processing steps than a conventionally manufactured brake shoe. The knowledge about the environmental impacts of conventionally manufactured brake shoe and remanufactured brake shoe is null. When searched for published study or articles of life cycle assessment about this automobile component there are no results relating to this study.Master of Science (Computer Integrated Manufacturing

Synthesis, spectral, crystallographic, and computational investigation of a novel molecular hybrid 3-(1-((benzoyloxy)imino)ethyl)-2H-chromen-2-ones

Synthesis of 3-(1-((benzoyloxy)imino)ethyl)-2H-chromen-2-ones (1-5) was accomplished and it was characterized experimentally using various analytical techniques. Computational studies have been carried out for all compounds 1-5 using B3LYP method with 6-311++G(d,p) basis set. The optimized structural features viz. bond lengths, bond angles, and dihedral angles are compared with their single-crystal X-ray diffraction results of compound 1 (Crystal data for C18H13NO4 (M = 307.29 g/mol): Monoclinic, space group P21/c (no. 14), a = 11.399(5) Å, b = 5.876(5) Å, c = 21.859(5) Å, β = 91.060(5)°, V = 1463.9(14) Å3, Z = 4, T = 293(2) K, μ(MoKα) = 0.100 mm-1, Dcalc = 1.394 g/cm3, 13555 reflections measured (3.58° ≤ 2Θ ≤ 56.98°), 3669 unique (Rint = 0.0235) which were used in all calculations. The final R1 was 0.0444 (>2sigma(I)) and wR2 was 0.1506 (all data)), which are in good conformity with each other. Normal modes of vibrational frequencies of compounds 1-5 acquired from density-functional theory (DFT) method coincided with the experimental ones. The 1H and 13C chemical shifts of compounds 1-5 have been calculated by GIAO method and the results have been compared with the experimental ones. The first-order hyperpolarizability and their related properties of the novel molecules 1-5 are calculated computationally. The other parameters like natural bond orbital, zero-point vibrational energy, EHOMO, ELUMO, heat capacity and entropy have also been discussed