Abstract:
Abstract— In the traditional attendance system of Bangladesh, the teachers either call the name or identity number of the students to which the students respond or pass the attendance sheet to the students to sign. With the increase of the number of students in the last two decades, the difficulties in attendance management system has increased remarkably. Again, in case of passing attendance sheet to the students, some students sign multiple times and proxy attendance is taken. These two systems are very
time consuming. To overcome these inconveniencies, this paper represents a smart attendance system prototype. In this paper radio frequency identification, biometric fingerprint sensor and password based technologies are integrated to develop a cost effective, reliable attendance management system. A desktop application is developed in C# environment to monitor the attendance system.
Abstract - Segmentation of images means a great matter for the medical field treatment purpose. For the extraction of brain polyps, magnetic resonance image (MRI) processing contributes in a wide range. Usually it works in two ways: white matter and
gray matter. The extraction of any type of issues helps in submissions of image segmentation like in medical report analysis, in preparation of radiotherapy, in formation of medical treatment etc. The main purpose of this paper is the Fuzzy CMeans (FCM) clustering exploitation by the help of Wavelet and Bi-dimensional Empirical Mode Decomposition (BEMD), as for the aim of improving the eminence of MR noisy images. To gain the best image segmentation method, in this paper the signal to noise ratio (SNR) rates were calculated by the data set of FCM clustering. As in the medical term of MRI segmentation, the experiment has done with synthetic WEB Images of brain that has verified the robustness and proved with efficiency with the applicable approach.
