Page 44 - Book of Abstracts 2023

Process improvement and implementation of a a a a a a a a a customer relationship management system at at 'Alum Shahar'
IEM-2-1
By: Efrat Avni efratavni1@gmail com com Shoval Yaniv shovaly19@gmail com com Advisor: Dr Gali Naveh
Shamoon College of Engineering Beer-Sheva
This project was conducted in in in a a a a a a a a a a small manufacturing company company called "Alum Shahar" which specializes in in in in in aluminum fixtures (windows and and doors) The company company was facing issues in in in in in in managing business processes and and customer customer relations for example: prolonged customer customer service times employee coordination delivery delays and and repeated production and and installation due to to to failures The project aimed to to to design design an an an information system to to to address these issues After analyzing the the the current status we designed a a a a a a a a a a a a a solution that meets the the the organization's requirements An acquisition strategy was was selected and and a a a a a a a a a a a a a a system was was implemented in in the the organization organization Keywords: aluminum solutions analysis and and design information systems customer relationship management process improvement Deep learning model for detecting pneumonia in in in X-rays
IEM-2-2
By: Lior Cohen liorc9595@gmail com com Arad Peleg aradpls2@gmail com com Advisor: Dr Dima Alberg Shamoon College of Engineering Beer-Sheva
Pneumonia is is is is a a a a a a a a a a a a a a a a common disease that causes respiratory tract infection and and is is is is the leading infectious cause cause of death among infants and and children worldwide For this project we developed a a a a a a a a a a a a a a a a a a a a a a medical- decision support tool that is is is based on on on on on on on deep learning to to detect pneumonia in in in in in in x-ray x-ray scans During the project we we trained a a a a a a a a a a a a a a a a a a convolutional neural network (CNN) on on on on on on on an an an array of childrens' chest x-rays in in in in in in which all images were tested and and quality-controlled by expert doctors before using them The model achieved a a a a a a a a a a a a a a a a a high accuracy of of about 95% in in in in detecting pneumonia and and and has the the potential to to optimize clinical processes and help medical professionals Keywords: chest x-ray convolutional neural network deep learning pneumonia 44