Asian Journal of Engineering and Applied Technology https://ojs.trp.org.in/index.php/ajeat <p>Asian Journal of Engineering and Applied Technology (AJEAT) is a half-yearly international journal devoted to the publication of peer-reviewed original high-quality research papers and review papers in all disciplines of engineering and applied technology.</p> en-US editor.trp@trp.org.in (Dr.M.Ramya) submissions@trp.org.in (Ms. S. Sukanya) Wed, 26 Oct 2022 06:59:30 +0000 OJS 3.3.0.8 http://blogs.law.harvard.edu/tech/rss 60 Utilizing Prediction Intervals for Unsupervised Detection of Fraudulent Transactions: A Case Study https://ojs.trp.org.in/index.php/ajeat/article/view/3348 <p>Money laundering operations have a high negative impact on the growth of a country’s national economy. As all financial sectors are increasingly being integrated, it is vital to implement effective technological measures to address these fraudulent operations. Machine learning methods are widely used to classify an incoming transaction as fraudulent or non-fraudulent by analyzing the behaviour of past transactions. Unsupervised machine learning methods do not require label information on past transactions, and a classification is made solely based on the distribution of the transaction. This research presents three unsupervised classification methods: ordinary least squares regression-based (OLS) fraud detection, random forest-based (RF) fraud detection and dropout neural network-based (DNN) fraud detection. For each method, the goal is to classify an incoming transaction amount as fraudulent or non-fraudulent. The novelty in the proposed approach is the application of prediction interval calculation for automatically validating incoming transactions. The three methods are applied to a real-world dataset of credit card transactions. The fraud labels available for the dataset are removed during the model training phase but are later used to evaluate the performance of the final predictions. The performance of the proposed methods is further compared with two other unsupervised state-of-the-art methods. Based on the experimental results, the OLS and RF methods show the best performance in predicting the correct label of a transaction, while the DNN method is the most robust method for detecting fraudulent transactions. This novel concept of calculating prediction intervals for validating an incoming transaction introduces a new direction for unsupervised fraud detection. Since fraud labels on past transactions are not required for training, the proposed methods can be applied in an online setting to different areas, such as detecting money laundering activities, telecommunication fraud and intrusion detection.</p> Isuru Hewapathirana Copyright (c) 2022 Asian Journal of Engineering and Applied Technology https://ojs.trp.org.in/index.php/ajeat/article/view/3348 Fri, 28 Oct 2022 00:00:00 +0000 Assessment of Surface Quality in Extrusion Honing Process Using Dimensional Analysis Approach https://ojs.trp.org.in/index.php/ajeat/article/view/3369 <p>It is critical to obtain the desired surface quality on the internal and external portions of machined part. The estimated level of surface texture can be induced on the exterior regions using traditional finishing processes such as grinding, honing, and so on. While the problem emerges when processing core miniature components such as micro bores, inlet/outlet valves etc. The EH process overcomes this limitation of conventional finishing method. It is a novel micro machining process that extrudes the pressured flow of carrier media blended with abrasives into the confined passage to generate desired level of surface texture. Owing to abrasion process micro machining occurs by taking away the negligible amount of stock material. The present study focuses on the impact of number of passes at the specimen’s entry and exit sides of the carrier media. The improvements in surface finish (R<sub>a</sub>) on both side i.e., entry and exit are evaluated as well. A dimensionless expression for R<sub>a</sub> is also developed. The relationship is implemented using Buckingham’s π theorem and comparison of developed model is performed with experimental results. SEM analysis is made to portray surface texture produced by selected process parameters such as number of passes, volume fraction and grit size of abrasive grains.</p> S. L. N. Jayasimha, N. L. Murali Krishna, H. P. Raju Copyright (c) 2022 Asian Journal of Engineering and Applied Technology https://ojs.trp.org.in/index.php/ajeat/article/view/3369 Thu, 10 Nov 2022 00:00:00 +0000 Acute Toxicity of Monocrotophos on Histological Alterations in the Anomuran Crab, Emerita asiatica (H. Milne Edwards, 1837) https://ojs.trp.org.in/index.php/ajeat/article/view/3382 <p>This study characterized the acute toxicity of Monocrotophos on histological alterations in the different organs like gills, Hepatopancreas and ovary of Anomuran Crab, Emerita asiatica. Though Emerita asiatica is not a commercially viable crab, but it plays a vital role in the coastal environment to maintain a stable marine ecosystem. Several steps and precautions measures should be taken to consume these members of the marine food chain to have aunwavering ecosystem and also to protect this species from extinction. Thus, it can be concluded that the use of Monocrotophos which has been legally banned in India is justified. It has been proved by several workers and has been conformed in present investigation that use of this organophosphate causes serious damage to the vital organ of sand crabs gill, hepatopancreas and ovary. The utilization of Monocrotophos should be minimized in the agricultural field area near to the coastal ecosystem.</p> J. Sivakumar, S. Bhuvaneswari, S. Venu, J. Jemima Ezhilarasi, C. Shanmugasundaram, P. Sankarganesh Copyright (c) 2022 Asian Journal of Engineering and Applied Technology https://ojs.trp.org.in/index.php/ajeat/article/view/3382 Wed, 30 Nov 2022 00:00:00 +0000