the advent of internet, large numbers of text documents are published and shared every day .Each of these documents is a collection of vast amount of information. Publically sharing of some of this information may affect the privacy of the document, if they are confidential information. So before document publishing, sanitization operations are performed on the document for preserving the privacy and inorder to retain the utility of the document. Various schemes were developed to solve this problem but most of them turned out to be domain specific and most of them didn't consider the presence of semantically correlated terms. This paper presents a generalized sanitization method that discovers the sensitive information based on the concept of information content. The proposed method removes the confidential information from the text document by first finding the independent sensitive terms. Then with the use of these sensitive terms the correlated terms that cause a disclosure threat are discovered. Again with the help of a generalization algorithm these sensitive and correlated terms with high disclosure risk are generalized.
Many different wireless sensor nodes for gas pipeline leak detection and location has been proposed but still there are challenges particularly on environmental issues and signal accuracy. This paper discusses theories and environmental constraints for wireless sensor nodes, a case study of Dar es Salaam Tanzania and finally presents a design and simulation results of the proposed wireless sensor node using Proteus Design Suite for detecting frequency of sound exited by jetting gas, leaking from higher pressurised gas pipeline. This kind of proposed system can be useful to gas companies or industries whereby gas transportation is done. General Terms Sensor node, Gas leak detection, Pipeline monitoring, Acoustic sensor, Speed of sound in air
edge detection is considered as a verysignificant technique in the field of Computer Vision. The term: 'edges' is used to define the boundaries between regions in a particular image, which supports with object segmentation and also in recognition of an object. In this paper authors focus a comparative study of edge detection techniques such as Sobel, Robert, Prewitt and impact of noise on it. The Experiment results find the edges of original image with the help of different type of edge detection technique such as Robert, Sobel and Prewitt and then we notice the quality of image with the help of PSNR, SNR, and Correlation Coefficient.
paper focuses edge extraction from dental x-ray images for the root canal procedure, using the linear prediction (LP). The major issues of processing the dental X-ray images are caused due to the misalignment and the variation in the contrast, by the very modality of acquisition. Also the differences in the shapes and orientations of the teeth pose yet another difficulty in the processing. Thus, in order to overcome these challenges, the LP residual based approach is used in this paper to obtain better root canal edge information. In the present work, the input image is processed by the 10 th order LP method to obtain LP residual image. The LP residual of the input image is found to provide better edges as compared to the conventional methods. Also the edge map obtained by the LP method is compared with previous work (7) on zero frequency resonator (ZFR) based edge extraction and is found to give a better edge map. Effectiveness of the LP residual method is confirmed by the visual inspection of the edge map and also from the subjective evaluation.