Page 63 - Book of Abstracts 2023

Book of Abstracts | 2023
Are lecture recordings the students' new books?
IEM-6-1
By: Or Brel iphoneorbrel@gmail com com Linoy Bitan linoy5994@gmail com com Advisor: Dr Gali Naveh
Shamoon College of Engineering Beer-Sheva
In In this project we examine the the the the the ways students use lecture lecture recordings their their purpose and the the the the the perception of their their contribution today as as as lecture-recording usage has become more widespread In In the the the the the the past books and and face-to-face lectures were were the the the main means for for academic learning and and recordings were were used infrequently To collect information we we we we created a a a a a a a a a a a a a a a a a a a a questionnaire which which will be distributed to to students students students and and from which which we we can learn learn about the the the the the students' usage habits with lecture recording and and the the the the the the the students’ perception of their contribution to to learning Analyzing the the the the the the the results gathered will allow us us to to answer the the the the the the research question regarding how the the the the the the lecture lecture recordings recordings are used among students students students Keywords: academia lecture recordings students A model for machine learning in in in in order to identify financial data fraud
IEM-6-2
By: Or Chen orchen28@gmail com com Keren Ovadia kerenovadia2@gmail com com Advisor: Dr Dima Alberg Shamoon College of Engineering Beer-Sheva
Fraud is one of of the the the biggest threats to to financial financial institutions institutions it it it it can lead to to financial financial loss loss and and the the the loss loss of of of clients’ and and shareholders’ trust in in in in in in in in those institutions institutions In addition there are are an an an an an an an an increasing number of of of cases requiring analysis where an an an an an an an immediate decision needs to to be be taken The ability to to detect detect deviations in in in in in in in in real-time financial data is is is is is minimal and the human eye is is is is is not capable of of of detecting all types of of fraud
fraud
For this project we built different models based on
on
machine learning in in in in in in in in order to examine which model model model most accurately identifies whether or or or not fraud
fraud
fraud
has occurred Keywords: financial fraud
machine learning models 63