International Conference on Global Engineering & Management Trends

 

Credit Card Fraud Detection In Online Transactions Using Machine Learning Algorithms

Authors- M.Tech. Scholar Ramireddy Himabindu, Asst.Prof. N Surendra, Asst.Prof. V Subhasini

Abstract- – People can use credit cards for online transactions as it provides an efficient and easy-to-use facility. With the increase in usage of credit cards, the capacity of credit card misuse has also enhanced. Credit card frauds cause significant financial losses for both credit card holders and financial companies.In this research study, the main aim is to detect such frauds, including the accessibility of public data, high-class imbalance data, the changes in fraud nature, and high rates of false alarm.Machine learning and deep learning algorithms have been used to detect frauds, but there is still a need to apply state-of-the-art deep learning algorithms to reduce fraud losses. Comparative analysis of both machine learning and deep learning algorithms was performed to find efficient outcomes. The European card benchmark dataset was used to evaluate the proposed model, which outperformed the state-of-the-art machine learning and deep learning algorithms..

 

Prediction of Diabetes with Web-Application using Machine Learning Algorithms

Authors- M.Tech. Student Abbareddi Anjali, Asst. Prof. R Althaf,Asst. Prof. V Subhasini

Abstract- – Manufacturing decisions inherently face uncertainties and imprecision. Fuzzy logic, and tools based on fuzzy logic, allow for the inclusion of uncertainties and imperfect information in decision making models, making them well suited for manufacturing decisions. In this study, we first review the progression in the use of fuzzy tools in tackling different manufacturing issues during the past two decades. We then apply fuzzy linear programming to a less emphasized, but important issue in manufacturing, namely that of product mix prioritization. The proposed algorithm, based on linear programming with fuzzy constraints and integer variables, provides several advantages to existing algorithm as it carries increased ease in understanding, in use, and provides flexibility in its application.

Employees Stress Detection With Facial Expressions Using Machine Learning

Authors- M.Tech. Scholar G.V.Devi, Asst.Prof. V Dakshayani, Asst.Prof V Subhasini

Abstract- – The objective of this paper is to apply machine learning and visual processing to identify overworked IT employees. Our technology is an improved version of older stress detection systems that did not include live detection or personal counseling. Stress detection methods that don’t include real-time monitoring or individual counselling are being updated in this research. A survey is used to collect data on employees’ mental stress levels in order to provide effective stress management solutions. In order to get the most out of your employees, this paper will look at stress management and how to create a healthy, spontaneous work environment.

Effects of Dietary Sodium Restriction on Blood Pressure and Cardiovascular Disease Outcome: A Review

Authors- Paradis Honarvar

Abstract- – The effect of reduction of dietary sodium intake on blood pressure has been an important topic for discussion among physicians and researchers. In the past decades, the contribution of excessive sodium intake as a risk factor for developing cardiovascular diseases has remained controversial. The objective of this manuscript was to evaluate current epidemiological studies in order to determine what effects have been observed on the blood pressure of individuals with modest reduction of dietary sodium intake and what impact this dietary modification might have on the future of cardiovascular diseases. The search strategy was based on PubMed/MEDLINE database in order to gather information on the testing hypothesis, which is that a modest reduction of dietary sodium intake has no adverse effects on health and reduces the risk of developing future cardiovascular diseases in both normotensive and hypertensive adults. The search was not limited to the country of origin, however it was limited to only peer-reviewed publications written in English. The result of this review reveals that the majority of the current studies and public guidelines support giving 5-6 g of salt/day for lowering blood pressure in both normotensive and hypertensive adults in order to lower the risk of developing non-communicable diseases, including cardiovascular disease. In conclusion, the data collected from systematic reviews, randomized control clinical trials and prospective studies all suggest that modest reduction of dietary sodium intake has a positive outcome in lowering the risk of developing cardiovascular diseases and attenuating difficulties in both normotensive and hypertensive adult population. Word Count: 250 .