A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

The laser micro-cutting process is the most widely commonly applied machining process which can be applied to practically all metallic and non-metallic materials. While this had challenges in cutting quality criteria such as geometrical precision, surface quality and numerous others. This article investigates the laser micro-cutting of PEEK composite material using nano-fiber laser, due to their significant importunity and efficiency of laser in various manufacturing processes. Design of experiential tool based on Response Surface Methodology (RSM)-Central Composite Design (CCD) used to generate the statistical model. This method was employed to analysis the influence of parameters including laser speed,

In this work, the copper metal was treated using Nd:YAG laser with energy 1Joul to enhance corrosion resistance and improve surface properties. The copper metal has many applications in industry as well as water, oil and gas pipes. The same conditions, (laser power density, scan speed, distance between paths, medium gas-air) were applied in the laser surface treatment, After laser treatment, the samples microstructures were investigated using optical microscope (OM) to examine micro structural changes due to laser irradiation. Specimen surfaces were investigated using atomic force microscopy (AFM), X-ray diffraction (XRD), macro hardness, and corrosion test before and after laser treatment to

The present studies are focused on the modification of the properties of epoxy resin with different additives namely aluminum, copper by preparing of composites systems with percentage (20%, 40% and 50%) of the above additives. The experimental results show that the D.C of conductivity on wt% filler content at ( 293-413 ) K electrical conductivity of all above composites increased with temperature for composites with filler contact and find the excellent electrical conductivity of copper and lie between (2.6*10-10 - 2.1*10-10)?.cm . The activation energy of the electrical conductivity is determined and found to decrease with increasing the filler concentration.

. 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