An Empirical Model for Thyroid Disease Classification using Evolutionary Multivariate Bayseian Prediction Method

Thyroid diseases are widespread worldwide. In India too, there is a significant problems caused due to thyroid diseases. Various research studies estimates that about 42 million people in India suffer from thyroid diseases [4]. There are a number of possible thyroid diseases and disorders, including thyroiditis and thyroid cancer. This paper focuses on the classification of two of the most common thyroid disorders are hyperthyroidism and hypothyroidism among the public. The National Institutes of Health (NIH) states that about 1% of Americans suffer from Hyperthyroidism and about 5% suffer from Hypothyroidism. From the global perspective also the classification of thyroid plays a significant role. The conditions for the diagnosis of the disease are closely linked, they have several important differences that affect diagnosis and treatment. The data for this research work is collected from the UCI repository which undergoes preprocessing. The preprocessed data is multivariate in nature. Curse of Dimensionality is followed so that the available 21 attributes is optimized to 10 attributes using Hybrid Differential Evolution Kernel Based Navie Based algorithm. The subset of data is now supplied to Kernel Based NaEF;ve Bayes classifier algorithm in order to check for the fitness

Image Compression using Wavelet and Modified Extreme Learning Machine

The development of Internet and multimedia technologies that grow exponentially, resulting in the amount of information managed by computer is necessary. This causes serious problems in storage and transmission image data. Therefore, should be considered a way to compress data so that the storage capacity required will be smaller. This paper presents a method of compressing still images combining the powerful features of modified extreme learning machine (MELM) for learning with discrete wavelet transform (DWT) in image transformation. DWT, based on the haar wavelet, has been used to transform the image and the coefficients acquired from DWT are then trained with MELM. MELM has the property that it selects a minimal number of coefficients to model the training data. The coefficients are then quantized and encoded using the Huffman coding algorithm. The performance of the proposed method is aspiring and comparable with the existing image compression standards

Software Piracy Forensics: Impact and Implications of Post‐Piracy Modifications

Piracy is potentially possible at any stage of the lifetime of the software. In a post-piracy situation, however, the growth of the respective versions of the software (both the original and pirated) is expected to be in different directions as a result of expectedly different implementation strategies. This paper shows how such post-piracy modifications are of special interest to a cyber crime expert investigating software piracy and suggests that the present software piracy forensic (or software copyright infringement investigation) approaches require amendments to take in such modifications. For this purpose, the paper also presents a format that is jargon-free, so as to present the findings in a more intelligible form to the judicial authorities. Keywords: Piracy, post-piracy modifications, software piracy, source code, copyright, software copyright infringement, software piracy forensics, database forensics, MIS forensics, AFC, SCAP, technical expert, substantial similarity test, CDA

Content Based Image Retrieval based on Shape with Texture Features

In areas of state, domain and hospitals, massive collections of digital pictures are being created. These image collections are the merchandise of digitizing existing collections of analogue images, diagrams, drawings, paintings, and prints. Retrieving the specified similar image from a large dataset is very difficult. A new image retrieval system is obtainable in this paper, for feature extraction HSV color space and wavelet transform approach are used. Initially constructed one dimension feature vector and represented the color feature it is made by that the color space is quantified in non-equal intervals. Then with the help of wavelet texture feature extraction is obtained. At last by using of wavelet transform combined the color feature and texture feature method. The illustration features are susceptible for different type images in image retrieval experiments. The color features opted to the rich color image with simple variety. Texture feature opted to the complex images. At the same time, experiments reveal that HSV texture feature based on wavelet transform has better effective performance and stability than the RGB. The same work is performed for the RGB color space and their results are compared with the proposed system. The result shows that CBIR with the HSV color space is retrieves image with more accuracy and reduced retrieval time. Keywords--Content Based Image Retrieval, HSV, RG

A Study on Enhancement of the Security of the Routing Protocols in Adhoc Networks

An ad hoc wireless network is a set of wireless mobile nodes that self-configure to build a network without the requirement for any reputable infrastructure or backbone. Mobile nodes are utilized by the Ad hoc networks to facilitate effective communication beyond the wireless transmission range. As ad hoc networks do not impose any fixed infrastructure, it becomes very tough to handle network services with the available routing approaches, and this creates a number of problems in ensuring the security of the communication. Majority of the existing ad hoc protocols that deal with security issues depends on implicit trust relationships to route packets among participating nodes. The general security objectives like authentication, confidentiality, integrity,availability and nonrepudiation should not be compromised in any circumstances. Thus, security in ad hoc networks becomes an active area of research in the field of networking. There are various techniques available in the literature for providing security to the ad hoc networks. This paper focuses on analyzing the various routing protocols available in the literature for ad hoc network environment and its applications in security mechanisms

An Efficient CBIR Technique with YUV Color Space and Texture Features

In areas of government, academia and hospitals, large collections of digital images are being created. These image collections are the product of digitizing existing collections of analogue photographs, diagrams, drawings, paintings, and prints. Retrieving the specified similar image from a large dataset is very difficult. A new image retrieval system is presented in this paper, which used YUV color space and wavelet transform approach for feature extraction. Firstly, the color space is quantified in non-equal intervals, then constructed one dimension feature vector and represented the color feature. Similarly, the texture feature extraction is obtained by using wavelet. Finally, color feature and texture feature are combined based on wavelet transform. The image retrieval experiments specified that visual features were sensitive for different type images. The color features opted to the rich color image with simple variety. Texture feature opted to the complex images. At the same time, experiments reveal that YUV texture feature based on wavelet transform has better effective performance and stability than the RGB and HSV. The same work is performed for the RGB and HSV color space and their results are compared with the proposed system. The result shows that CBIR with the YUV color space retrieves image with more accuracy and reduced retrieval time. Keywords---Content based image retrieval, Wavelet transforms, YUV, HSV, RG

Cluster Based Analysis and Consumption of Food Products in Targeted Public Distribution System

The Public Distribution System in India is 50 years old. At present it is being carried on as an anti-inflationary and antipoverty system. Tamil Nadu, the southernmost State in the country, is adopting the Universal Public Distribution System covering its entire population and supplying regularly rice, wheat, sugar, kerosene and other products like pulses, edible oil etc. The PDS is a centrally sponsored scheme that entitles beneficiaries to subsidized food grains every month. Several challenges have been identified in the implementation of PDS like (i) Targeting errors (ii) Large leakages or diversion (iii) The elimination of bogus cards and (iv) The problems in Fair Price Shops. This paper analyses and evaluates the problems and finds the possible solutions using the data mining techniques based on preprocessing and clustering. The K-means and K-harmonic means algorithms are combined to cluster the data based on the type of food commodities for rice and wheat

Enhancing the Security and Quality Image Steganography using Hiding Algorithm based on Minimizing the Distortion

In this paper, highest state-of-the-art binary image Steganographic approach considers the spinning misinterpretation according to the personal visual structure, which will be not secure when they are attacked by Steganalyzers. In this paper, a binary image Steganographic scheme that aims to reduce the hiding misinterpretation on the balance is presented. We excerpt the complement, turn, and following-invariant local balance arrangement from the binary image first. The weighted sum of Complement, Turn, And Following-Invariant Local Balance changes when spinning one pixel is then employed to allot the spinning misinterpretation corresponding to that pixel. By examining on both simple binary images and the composed image constructed message set, we show that the advanced appraisal can well describe the misinterpretations on both visual aspect and statistics. Based on the proposed measurement, a practical Steganographic scheme is develope