A loS.sless (reversible) data hiding (embedding) method  inside  an image  (translating medium)  - presented   in  the  present  work  using  L_SB (least  significant  bit). technique  which  enables  us to translate   data  using an  image  (host  image),  using  a  secret  key, to  be  undetectable  without losing  any  data  or  without   changing   the  size  and  the  external   scene (visible  properties) of the image, the hid-ing data is then can  be extracted (without  losing)   by reversing &n

In recent years, due to the economic benefits and technical advances of cloud
computing, huge amounts of data have been outsourced in the cloud. To protect the
privacy of their sensitive data, data owners have to encrypt their data prior
outsourcing it to the untrusted cloud servers. To facilitate searching over encrypted
data, several approaches have been provided. However, the majority of these
approaches handle Boolean search but not ranked search; a widely accepted
technique in the current information retrieval (IR) systems to retrieve only the top–k
relevant files. In this paper, propose a distributed secure ranked search scheme over
the encrypted cloud servers. Such scheme allows for the authorized user to

Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

In the present work, different remote sensing techniques have been used to analyze remote sensing data spectrally using ENVI software. The majority of algorithms used in the Spectral Processing can be organized as target detection, change detection and classification. In this paper several methods of target detection have been studied such as matched filter and constrained energy minimization.
The water body mapping have been obtained and the results showed changes on the study area through the period 1995-2000. Also the results that obtained from applying constrained energy minimization were more accurate than other method comparing with the real situation.

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Data compression offers an attractive approach to reducing communication costs using available bandwidth effectively. It makes sense to pursue research on developing algorithms that can most effectively use available network. It is also important to consider the security aspect of the data being transmitted is vulnerable to attacks. The basic aim of this work is to develop a module for combining the operation of compression and encryption on the same set of data to perform these two operations simultaneously. This is achieved through embedding encryption into compression algorithms since both cryptographic ciphers and entropy coders bear certain resemblance in the sense of secrecy. First in the secure compression module, the given text is p

The current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1^st, 2^nd and 3^rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition