It is crucial for public users and service providers to stay abreast of the progress and trends on data exfiltration in computer security system. In cryptosystem, it is unnoticeable for computer and mobile users to realize that inaudible sound used to transmit signals carrying pervasive sensitive data was in the low frequency ultrasonic range. Acoustic attacks on ultrasonic signal emanated by electronic devices have long been investigated among researchers. This paper is an exploration on the practicality of ultrasonic data exfiltration between computers in term of computer security system. It will discuss some work done by previous researchers in general, based on scientific, technological, and security perspectives. There will be inclusions of practical applications already in existence as well as future studies in related fields.

Clustering is one of the most common automated segmentation techniques used in the fields of bioinformatics applications specifically for the microscopic image processing usage. Recently many scientists have performed tremendous research in helping the haematologists in the issue of segmenting the leukocytes region from the blood cells microscopic images in the early of prognosis. During the post processing, image filtering can cause some discrepancies on the processed image which may lead to insignificant result. This research aims to segment the blood cell microscopic images of patients suffering from acute leukaemia. In this research we are using three clustering techniques which are (Fuzzy C-Means (FCM), Classic K-Means (CKM) and Enhanced K-Means (EKM) then we performed filtering techniques which are Mean-shift Filtering (MSF) and Seeded Region Growing (SRG). We tested individual clustering, from the results it show Enhanced K-Means gives the best result. We performed hybrid between EKM and MSF gave a better result from other comparison. The integrated clustering techniques have produced tremendous output images with minimal filtering process to remove the background scene. � 2005 - 2015 JATIT & LLS. All rights reserved.

Clustering is one of the most common automated image segmentation techniques used in many fields including machine learning, pattern recognition, image processing, and bioinformatics. Recently many scientists have performed tremendous research in helping the hematologists in the issue of segmenting the blood cells in the early of prognosis. This paper aims to segment the blood cell images of patients suffering from acute leukemia using an adaptive K-Means clustering together with mean shift algorithm. The integrated clustering techniques have produced comprehensive output images with minimal filtering process to remove the background scene. � 2013 IEEE.