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- Mobile wallets; Technology acceptance model (TAM); Expectation confirmation model (ECM); Covid-19; Perceived Trust; Continued usage intention (1)
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Articles 1 - 5 of 5
Full-Text Articles in Business
Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta
Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta
Electronic Theses, Projects, and Dissertations
This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or eliminate credit card fraud, and how do these techniques compare in terms of fraud detection accuracy and efficiency? Q2. To what extent do synthetic data generation methods effectively mitigate the challenges posed by imbalanced datasets in credit card fraud detection, and how do these methods impact classification performance? Q3. To what extent can the combination of transfer learning and innovative data resampling techniques …
Early-Warning Prediction For Machine Failures In Automated Industries Using Advanced Machine Learning Techniques, Satnam Singh
Early-Warning Prediction For Machine Failures In Automated Industries Using Advanced Machine Learning Techniques, Satnam Singh
Electronic Theses, Projects, and Dissertations
This Culminating Experience Project explores the use of machine learning algorithms to detect machine failure. The research questions are: Q1) How does the quality of input data, including issues such as outliers, and noise, impact the accuracy and reliability of machine failure prediction models in industrial settings? Q2) How does the integration of SMOTE with feature engineering techniques influence the overall performance of machine learning models in detecting and preventing machine failures? Q3) What is the performance of different machine learning algorithms in predicting machine failures, and which algorithm is the most effective? The research findings are: Q1) Effective outlier …
Accounting And Financial Statements Auto Analysis System, Zhen Jia
Accounting And Financial Statements Auto Analysis System, Zhen Jia
Electronic Theses, Projects, and Dissertations
This project was motivated by the need to revolutionize the generation of financial statements and financial analysis process thus speeding up business decision making. The research questions were: 1) How can machine learning increase the speed of financial statement preparation and automate financial statements analysis? 2) How can businesses balance the benefits of automating financial analysis with potential concerns around privacy, data security, and bias? 3) Can the Java J2EE framework provide a reliable running environment for machine learning?
The findings were: 1) Machine learning can significantly increase the accuracy and speed of financial analysis. Using machine learning algorithms, financial …
Short-Term Prediction Of Icu Admission For Covid-19 Inpatients, Yoon Sang Lee, Riyaz T. Sikora
Short-Term Prediction Of Icu Admission For Covid-19 Inpatients, Yoon Sang Lee, Riyaz T. Sikora
Journal of International Technology and Information Management
Since the COVID-19 outbreak, many hospitals suffered from a surge of some high-risk inpatients needing to be admitted to the ICU. In this study, we propose a method
predicting the likelihood of COVID-19 inpatients’ admission to the ICU within a time frame of 12 hours. Four steps, the Bayesian Ridge Regression-based missing value imputation, the synthesis of training samples by the combination of two rows (the first and another row) of each patient, customized oversampling, and XGBoost classifier, are used for the proposed method. In the experiment, the AUC-ROC and F-score of our method is compared with those of other …
Determinants Of Continuance Intention To Use Mobile Wallets Technology In The Post Pandemic Era: Moderating Role Of Perceived Trust, Shailja Tripathi
Determinants Of Continuance Intention To Use Mobile Wallets Technology In The Post Pandemic Era: Moderating Role Of Perceived Trust, Shailja Tripathi
Journal of International Technology and Information Management
The Covid-19 pandemic amplified the volume and importance of mobile payments using digital wallets and placed a basis for their continued adoption. The objective of the study is to formulate and test a comprehensive model by integration of the technology acceptance model (TAM) and expectation confirmation model (ECM) with the addition of three constructs, namely perceived trust, perceived risk, and subjective norm, to identify the determinants of continuance intention to use mobile wallets. Questionnaire-based survey method was used to gather the data from 550 users having experience using mobile wallets for more than six months. The data were analyzed using …