Hiding secret information in the image is a challenging and painstaking task in computer security and steganography system. Certainly, the absolute intricacy of attacks to security system makes it more attractive.in this research on steganography system involving information hiding,Huffman codding used to compress the secret code before embedding which provide high capacity and some security. Fibonacci decomposition used to represent the pixels in the cover image, which increase the robustness of the system. One byte used for mapping all the pixels properties. This makes the PSNR of the system higher due to random distribution of embedded bits. Finally, three kinds of evaluation are applied such as PSNR, chi-square attack, a

Chaotic systems have been proved to be useful and effective for cryptography. Through this work, a new Feistel cipher depend upon chaos systems and Feistel network structure with dynamic secret key size according to the message size have been proposed. Compared with the classical traditional ciphers like Feistel-based structure ciphers, Data Encryption Standards (DES), is the common example of Feistel-based ciphers, the process of confusion and diffusion, will contains the dynamical permutation choice boxes, dynamical substitution choice boxes, which will be generated once and hence, considered static,

            While using chaotic maps, in the suggested system, called

A New ligand, N-(2-oxo-1,2- Dihydropyrimidin-4- ylcarbamothioyl) Acetamide (DPA) was prepared by reaction of iso thiosyanate derivative with Cytosine. The ligand has been characterized through elemental analysis, H1 NMR, C13NMR, FT-IR, and UV Visible spectra, such ligand’s transition metal complexes have been characterized through conductivity measurement, FT-IR, UV Visible spectra and magnetic susceptibility, all the complexes of this ligand are solid crystal and molar ratio (2:1) (ligand: metal). The form of molecular for these complexes octa hedral. The general formula [M(DPA)2Cl2], where M+2 = (Mn, Co, Ni, Cu, Zn, Cd, Hg).

Di Benzylidenes were prepared by condensation of 1,2-diamino benzene with o- hydroxy benzaldehyde. These dibenzylidenes when treated with one equivalent of malonic anhydride or 5-oxo-spiro[2,3]hexane-4,6-dione in dry benzene give 6-membered heterocyclic ring system of 3-{2-[(2-Hydroxy-benzylidene)-amino]-phenyl}-2-(2-hydroxy –phenyl)-[1,3]oxazinane-4,6-diones ( 1-3) or 7-{2-[(2-hydroxy-benzylidene)-amino]-phenyl}-6-(2-hydroxy-phenyl)-5-oxa-7-aza-spiro[2.5]octane-4,8-diones ( 7- 9 ) But when two equivalents of malonic anhydride or 5-oxo-spiro[2,3]hexane-4,6-dione were used and under sam conditions compounds (4-6 , 10-12 ) were obtained .

Fullerene nanotube was synthesized in this research by pyrolysis of plastic waste Polypropylene (PP) at 1000 ° C for two hours in a closed reactor made from stainless steel using molybdenum oxide (MoO₃) as a catalyst and nitrogen gas. The resultant carbon was purified and characterized by energy dispersive X-ray spectroscopy (EDX), X-ray powder diffraction (XRD). The surface characteristics of C₆₀ nanotubes were observed with the Field emission scanning electron microscopy (FESEM). The carbon is evenly spread and has the highest concentration from SEM-EDX characterization. The result of XRD and FESEM shows that C₆₀ nanotubes are present in Nano figures, synthesized at 1000 ° C and with pyrolysis tempera

Objective(s): In the present study, glycerin is used as a substitute for tin-foil and cold mold seal (Alginate mould seal)
in the process of curing heat and cold-cure acrylic resin denture base against stone and plaster.
Methodology: 60 specimens were prepared from heat-cure acrylic resin and cold-cure acrylic resin denture base. The
study includes 12 groups of specimens depending on the type of processing, investment material and type of
separating medium that are used in curing process. Each group of them contains 5 specimens for each test.
Some of physical properties of the processed acrylic denture base that (water sorption and solubility) have been
compared with those processed using tin-foil and tin-foil substitut

The guava plant, Psidium guajava L., serves as proof of the abundant donations of nature, providing a delicious guava fruit; this plant is rich in groups of medicinal and nutritional benefits. Guava belonging to the Myrtaceae family, many previous studies reported many phytochemical constituents in its leaves that have many pharmacological activities and medicinal properties; this study focuses on the isolation, structural elucidation and calculation concentration of flavonoids, assessment of the cytotoxic activityof hyperin from Psidium guajava leaves newly cultivated in Iraq. The isolation process involved the use of thin-layer chromatography (TLC) and preparative high-performance liquid chromatography (PHPLC) and structural eluci

A new design of manifold flow injection (FI) coupling with a merging zone technique was studied for sulfamethoxazole determination spectrophotometrically. The semiautomated FI method has many advantages such as being fast, simple, highly accurate, economical with high throughput . The suggested method based on the production of the orange- colored compound of SMZ with (NQS)1,2-Naphthoquinone-4-Sulphonic acid Sodium salt in alkaline media NaOH at λ_max 496nm.The linearity range of sulfamethoxazole was  3-100  μg. mL^-1, with (LOD) was 0.593 μg. mL^-1 and the RSD% is about 1.25 and the recovery is 100.73%. All various physical and chemical parameters that have an effect on the stability and development of

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class