The efficiency of the Honeywords approach has been proven to be a significant tool for boosting password security. The suggested system utilizes the Meerkat Clan Algorithm (MCA) in conjunction with WordNet to produce honeywords, thereby enhancing the level of password security. The technique of generating honeywords involves data sources from WordNet, which contributes to the improvement of authenticity and diversity in the honeywords. The method encompasses a series of consecutive stages, which include the tokenization of passwords, the formation of alphabet tokens using the Meerkat Clan Algorithm (MCA), the handling of digit tokens, the creation of unique character tokens, and the consolidation of honeywords. The optimization of t

An approach for hiding information has been proposed for securing information using Slanlet transform and the T-codes. Same as the wavelet transform the Slantlet transform is better in compression signal and good time localization signal compression than the conventional transforms like (DCT) discrete cosine transforms. The proposed method provides efficient security, because the original secret image is encrypted before embedding in order to build a robust system that is no attacker can defeat it. Some of the well known fidelity measures like (PSNR and AR) were used to measure the quality of the Steganography image and the image after extracted. The results show that the stego-image is closed related to the cover image, with (PSNR) Peak Si

Renewable energy sources - realities of the present and future options

    Many of the directories indicate that the global energy system begin with a period of transition from total dependence on fossil energy sources, particularly oil, Into a new era in which renewable energy sources play an important role in meeting the growing needs of energy demand. There are many factors that will contribute to the strengthening of this trend towards transformation, which also will decide how quickly this transformation of renewable energy systems effectively in the global system of energy demand.

   These factors, In brief: the size of environmental pollution and cl

The optical energy gap(Eopt) and the width of the tails of localized states in the band gap (?E) for Se:2%Sb thin films prepared by thermal co-evaporation method as a function of annealing temperature are studied in the photon energy range ( 1 to 5.4)eV.Se2%Sb film was found to be indirect transition with energy gap of (1.973,2.077, 2.096, 2.17) eV at annealing temperature (295,370,445,520)K respectively. The Eopt and ?E of Se:2%Sb films as a function of annealing temperature showed an increase in Eopt and a decrease in ?E with increasing the annealing temperature. This behavior may be related to structural defects and dangling bonds.

In this study, the effect of pumping power on the conversion efficiency of nonlinear crystal (KTP) was investigated using laser pump-power technique. The results showed that the higher the pumping power values, the greater the conversion efficiency (η) and, as the crystal thickness increases within limitations, the energy conversion efficiency increases at delay time of (0.333 ns) and at room temperature. Efficiency of 80% at length of KTP crystal (L = 1.75 X 10^-3 m) and P_in = 28MW, and also, compare the experimental results with numerical results by using MATLAB program. 

Cognitive radio technology is used to improve spectrum efficiency by having the cognitive radios act as secondary users to access primary frequency bands when they are not currently being used. In general conditions, cognitive secondary users are mobile nodes powered by battery and consuming power is one of the most important problem that facing cognitive networks; therefore, the power consumption is considered as a main constraint. In this paper, we study the performance of cognitive radio networks considering the sensing parameters as well as power constraint. The power constraint is integrated into the objective function named power efficiency which is a combination of the main system parameters of the cognitive network. We prove the exi