The whole world today, is facing the COVID-19 pandemic. This situation make people must adapt to the new normal, for example: work from home, online communication, keep clean to reduce transmission of COVID-19. Moreover, research has found that wearing a mask is one way to reduce the risk of viral transmission. It makes many public places have a measure about their customer must keep a distance between people and wearing the face mask correctly. But public service providers are not feasible to thoroughly check whether all a customer wear the mask or not. So, in this project, we propose face mask detection via webcam cameras using image recognition which is one of the high-accuracy and efficient face mask detector. This proposed system consists of three methods to detect face mask: 1) Image preprocessing 2) Face detection and crop 3) Classification of face mask. This system can detection a face mask, not wearing a face mask and incorrect face mask. This system will help public service providers ensure that all people in this place wear face mask correctly, promote people to use a face masks and it ensure that these public places have a safe environment.

Because the online recruiting system has progressed, a large number of resumes were submitted. As a consequence, hiring new employees and reviewing a large number of resumes is a challenge for the human resource department or employer. Therefore, this system has helped employers by using an automated intelligent system based on natural language processing. This system can convert various formats of resumes to text format and can extract some important information. It is also possible to compare the applicant's resume and the job description to see the percentage of similarity as well. This system can assist the human resource department or employer in screening resumes before conducting interviews and finding the best candidate for the job position.