With the quick grow of multimedia contents, from among this content, face recognition has got a lot of significant, specifically in latest little years. The face as object formed of various recognition characteristics for detect; so, it is still the most challenge research domain for researchers in area of image processing and computer vision. In this survey article, tried to solve the most demanding facial features like illuminations, aging, pose variation, partial occlusion and facial expression. Therefore, it indispensable factors in the system of facial recognition when performed on facial pictures. This paper study the most advanced facial detection techniques too, approaches: Hidden Markov Models, Principal Component Analysis (PCA)

 

            This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.

 

 

In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

Technology is one of the important influences in the development of professions in general and the profession of tax auditing and examination in particular because of the importance of this section in the General Tax Authority because of the service it provides is auditing the financial accounts provided to the department by the taxpayers to ensure the correctness of revenue and the achievement of tax justice. Where the research aims at the importance of using electronic accounting information systems in developing the work of the Tax Audit and Examination Department, to reduce the difficulties that the department may be using using manual systems, which is the need for time and effort to accomplish it, and to develop methods and procedu

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

This research aims to identify the role of external environment factors on the quality of educational services, from the academic point of view, where the distribution of a questionnaire to a random sample of (100) university professors, and then analyzing a model, and test the validity of this model using structural modeling (SEM) (Structural Equation Modeling).
And then test the relationships between variables using the software of Statistical Package for Social Sciences (SPSS V.18), the research found a number of conclusions, the most important conclusion is: the external environment factors has significant impact on the quality of educational services.