The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. In this work, we implement an interaction between the feedforward neural network and the stream cipher, so the secret message will be encrypted by unsupervised neural network method in addition to the first encryption process which is performed by the stream cipher method. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding le

In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

The adsorption of hexavalent chromium by preparing activated carbon from date seeds with zinc chloride as chemical activator and granular date seeds was studied in a batch system. The characteristics of date seeds and prepared activated carbon (ZAC) were determined and found to have a surface area 500.01 m²/g and 1050.01  m²/g , respectively and  iodine number of 485.78 mg/g and 1012.91  mg/g, respectively. The effects of PH value (2-12), initial sorbate concentration(50-450mg/L), adsorbent weight (0.004-0.036g) and contact time (30-150 min) on the adsorption process were studied . For Cr(VI) adsorption on ZAC, at 120 min time contact, pH solution 2 and 0.02  adsorbent  weight  will ach

The surface finish of the machining part is the mostly important characteristics of products quality and its indispensable customers’ requirement. Taguchi robust parameters designs for optimizing for surface finish in turning of 7025 AL-Alloy using carbide cutting tool has been utilized in this paper. Three machining variables namely; the machining speeds (1600, 1900, and 2200) rpm, depth of cut (0.25, 0.50, 0.75) mm and the feed rates (0.12, 0.18, 0.24) mm/min utilized in the experiments. The other variables were considered as constants. The mean surface finish was utilized as a measuring of surface quality. The results clarified that increasing the speeds reduce the surface roughness, while it rises with increasing the depths and fee

This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Background: One effective second-generation triptan for migraine attacks is sumatriptan. Following oral use, it has a 40% restricted bioavailability because of the first-pass metabolism. Aim: To develop the best intranasal Solusomes formula as a substitute that delivers into the brain directly, improving its bioavailability, and removing the first-pass outcome was the aim of this effort. Methodology: We developed solute formulations based on the Box-Behnken design and subsequently produced them via thin-film hydration. The quality by design technique was used to establish a correlation between the formulation parameters (Soluplus® and phosphatidylcholine (PC) concentrations) and signif¬icant quality powers (entrapment efficiency (