Steganography is one of the most popular techniques for data hiding in the different media such as images, audio or video files. This paper introduced the improved technique to hide the secret message using the LSB algorithm inside the RGB true color image by encrypting it using the secret key transformation function. The key is selecting randomly in the GF (2n) with condition it has an inverse value to retrieve the encrypted message. Only two bits are used for the low byte in each pixel (the blue byte) to hide the secret message, since the blue color has a weak effect on human eyes. The message hidden by the suggested algorithm is less vulnerable to be stolen than other similar applications.

Background: e cerebellum is divided into two hemispheres and contains a narrow midline zone called thevermis. A set of large folds are conventionally used to divide the overall structure into ten smaller "lobules". evermis receives fibres from the trunk and proximal portions of limbs, But the question is that does the cerebellum have the same measurementvalues in males and females of the same age?Material and method: e present study used 80 sectional brain MRI images (40: males, 40: females); 35-50 years old as indices of size for thevermian structures of the Cerebellum. is middle age group was taken because as known generally it could be neither an age of growth as inthe young nor of atrophy as in old individuals. e aim rega

) were taken from three stations at Al-Razzazah lake,by using a range of gill nets and seine nets. A total of 318 fish were taken from all stations. The age data determined from the scales showed that there were eight age classes present in station 1 and 2 and seven age classes in station 3. The increment in length of A. latus at the area of study showed a tendency to decrease with the increase in age after the fourth year of life.  The length- weight relationships of both sexes specimens are expressed by the following equations: Log  = -1.93 + 2.67 Log ….. for station (1) fish Log = -2.08 + 2.74 Log   …. For station (2) fish Log = -2.02 + 2.39 Log  …. For station (3) fish&n

The aim of this paper is to compare between classical and fuzzy filters for removing different types of noise in gray scale images. The processing used consists of three steps. First, different types of noise are added to the original image to produce a noisy image (with different noise ratios). Second, classical and fuzzy filters are used to filter the noisy image. Finally, comparing between resulting images depending on a quantitative measure called Peak Signal-to-Noise Ratio (PSNR) to determine the best filter in each case.
The image used in this paper is a 512 * 512 pixel and the size of all filters is a square window of size 3*3. Results indicate that fuzzy filters achieve varying successes in noise reduction in image compared to

The process of evaluating data (age and the gender structure) is one of the important factors that help any country to draw plans and programs for the future. Discussed the errors in population data for the census of Iraqi population of 1997. targeted correct and revised to serve the purposes of planning. which will be smoothing the population databy using nonparametric regression estimator (Nadaraya-Watson estimator) This estimator depends on bandwidth (h) which can be calculate it by two ways of using Bayesian method, the first when observations distribution is Lognormal Kernel and the second is when observations distribution is Normal Kernel

This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

      Iodine-131 has become an essential radionuclide used in nuclear medicine for clinical and research purposes. The increase use of this radionuclide in medicine for diagnostic and treatment of thyroid diseases creates a demand to obtain a feasible methodology for occupational or accidental monitoring of internal contamination. In this study, two techniques were employed to find an appropriate one of in vivo bioassay for evaluating Iodine-131 body content. A scanning Whole Body Counter (WBC) equipped with 6NaI (Tl) scintillation detector, an anthropomorphic phantom and point source were used. The results showed that the counter sensitivity, as a first approach (conventional method), had a logarithmic and significant correlation w

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect