In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform

    Glaucoma is one of the most dangerous eye diseases. It occurs as a result of an imbalance in the drainage and flow of the retinal fluid. Consequently, intraocular pressure is generated, which is a significant risk factor for glaucoma. Intraocular pressure causes progressive damage to the optic nerve head, thus leading to vision loss in the advanced stages. Glaucoma does not give any signs of disease in the early stages, so it is called "the Silent Thief of Sight". Therefore, early diagnosis and treatment of retinal eye disease is extremely important to prevent vision loss. Many articles aim to analyze fundus retinal images and diagnose glaucoma. This review can be used as a guideline to help diagnose glaucoma. It presents 63 artic

 The vast majority of EC applications are the web-based deployed in 3-tire Server-Client environment, the data within such application often resides within several heterogeneous data sources. Building a single application that can access each data sources can be a matter of challenging; this paper concerns with developing a software program that runs transparently against heterogeneous environment for an EC-application.
 

User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract

     Financial fraud remains an ever-increasing problem in the financial industry with numerous consequences. The detection of fraudulent online transactions via credit cards has always been done using data mining (DM) techniques. However, fraud detection on credit card transactions (CCTs), which on its own, is a DM problem, has become a serious challenge because of two major reasons, (i) the frequent changes in the pattern of normal and fraudulent online activities, and (ii) the skewed nature of credit card fraud datasets. The detection of fraudulent CCTs mainly depends on the data sampling approach. This paper proposes a combined SVM- MPSO-MMPSO technique for credit card fraud detection. The dataset of CCTs which co

     Task scheduling in an important element in a distributed system. It is vital how the jobs are correctly assigned for each computer’s processor to improve performance. The presented approaches attempt to reduce the expense of optimizing the use of the CPU. These techniques mostly lack planning and in need to be comprehensive. To address this fault, a hybrid optimization scheduling technique is proposed for the hybridization of both First-Come First-Served (FCFS), and Shortest Job First (SJF). In addition, we propose to apply Simulated Annealing (SA) algorithm as an optimization technique to find optimal job’s execution sequence considering both job’s entrance time and job’s execution time to balance them to reduce the job

The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

     This work presents an approach for the applying Triple DES (TRIPLE DES) based on using genetic algorithm by adding intelligent feature for TRIPLE DES with N round for genetic algorithm. Encapsulated cipher file with special program which send an acknowledgment to a sender to know who decipher or  broken to  crash it , Thus it is considered as the initial step to improve privacy. The outcome for proposed system gives a good indication that it is a promising system compared with other type of cipher system.

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima