Data Mining and Knowledge Engineering

Satish Kumar Ray ¹, Toran Verma ¹, Sipi Dubey ²

Affiliations
1 Department of Computer Science, RCET, Bhilai-490024, C.G., IN
2 RCET, Bhilai-490024, C.G., IN

Abstract

This paper presented the architecture of Browser Operating System. The BOS runs the client-side component of each Web application (e.g., on-line banking, Web mail) in its own virtual machine. The BOS lets Web publishers limit the scope of their Web applications by specifying which URLs and other resources their browsers are allowed to access. The BOS treats Web applications as first class objects that users explicitly install and manage. It defines a new trusted system layer, the browser operating system (BOS), on top of which browser implementations (such as Netscape or IE) can run. It provides explicit support for Web applications. A Web application consists of a browser instance, which includes a client-side browser executing dynamic Web content and code, and a Web service, which is a collection of Web sites with which the browser instance is permitted to communicate. It enforces isolation between Web applications, prohibiting one application from spying on or interfering with other applications or host resources. Each Web application has an associated browser instance that is sandboxed within a virtual machine.

Keywords

Browser Operating System, Container Based System, Operating System, Virtualization.

Full Text

     

Toran Verma ¹, Lokesh K. Sharma ², Sourabh Rungta ²

Affiliations
1 Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai-4900245, CG, IN
2 Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai-490024, CG, IN

Abstract

Data mining is a process to extract useful information for decision making from available set of data. Blast is a fungal disease of rice and occurs in all the rice-growing regions. It causes complete destruction of the rice crop. Present day applications require automation of process to interprets and analyze the information by using various kinds of images and pictures as source of information for interpretation and analysis. The fuzzy set theory is incorporated to handle uncertainties and fuzzy clustering is a powerful method of data mining. FIS is an expert system to approximate input-output mapping according to defined rules. In this proposed approach, leaf blast infected image in rice crop is acquired by digital camera. Image's RGB features of pixels has been extracted and further used for clustering. This clustered data is categorized as Not Affected (NA), Medium Affected (MA) and Highly Affected (HA) by leaf blast disease according to colour information and previous acquired knowledge. For each of these three categories, minimum, medium and maximum RGB ranges has been evaluated. For that linguistic term RMIN, RMED, RMAX, GMIN, GMED, GMAX, BMIN, BMID and BMAX assumed and according to range of linguistic term, triangular membership function has been taken as an input in FIS. For easier implementation of FIS, range of NA, MA and HA is also assumed and taken in form of triangular membership function. According to evaluated data, assumed data and 14 fuzzy inference rules , FIS with three input Red, Green and Blue and any one possible outcome from NA, MA and HA has been implemented. After implementation, random 60 pixels RGB information of another image has been send as input in FIS for testing and it is successfully categorized by FIS, which help to approximate loss caused by leaf blast disease in rice crop.

Keywords

Rice Blast Disease, Image Acquisition, RGB, Fuzzy Logic, Fuzzy Inference System.

Full Text