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 unique mark is used later as a watermark to be embedded into host PMI using blind watermarking-based singular value decomposition (SVD) algorithm. This is a new solution that we also proposed to applying SVD into a blind watermarking image. Our algorithm preserves PMI content authentication during the transmission and PMR ownership to the patient for subsequently transmitting associated diagnosis to the correct patient via a mobile telemedicine application. The performance of experimental results is high compare to previous results, uses recovered watermarks demonstrating promising results in the tamper detection metrics and self-recovery capability, with 30db PSNR, NC value is 0.99.
Abstract
This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m
... Show MoreConcentrated research topic in the study of key variables in the work of the inspectors general offices , which are in the application of quality management standards audit work and reduce the incidence of corruption. It highlights the importance of current research in being a serious attempt aimed at highlighting the role of the importance of standards of quality management audit work , because they represent a router and leader of the accountant or ( Sergeant ) in the performance of his work and the extent of compliance with these standards , as well as highlight the role of quality audit in reducing the incidence of corruption , of during the professional performance of Higher auditors and determine the responsibilities entrus
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The underlying objective of the international standard No. (6) to assist in accounting applications for the extractive industries, taking into consideration the goals and objectives contained in the sixteenth of the private International Accounting Standards criterion accounting for land, machinery and equipment, as well as Standard No. axes (38) relating to intangible assets, and in order to create a vision of a comprehensive development needs oil in order to exact evaluation of policies related to the particular needs and draw a comprehensive frameworks with respect to treatment of expenditures and revenues in the oil production industry, is also interested in Standard No. (6) within the primary objectiv
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreThe drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
Porous Silicon (PS) layer has been prepared from p-type silicon by electrochemical etching method. The morphology properties of PS samples that prepared with different current density has been study using atom force measurement (AFM) and it show that the Layer of pore has sponge like stricture and the average pore diameter of PS layer increase with etching current density increase .The x-ray diffraction (XRD) pattern indicated the nanocrystaline of the sample. Reflectivity of the sample surface is decrease when etching current density increases because of porosity increase on surface of sample. The photolumenses (PL) intensity increase with increase etching current density. The PL is affected by relative humidity (RH) level so we can use
... Show MoreRecently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in
... Show MoreConsistent "with the thought of tax talk is unified tax natural evolution for him, as the application leads to the inclusion of tax all branches of income and its sources and through truncated part of this entry through the application of price ascending it, it means the procedures of tax reform. Taxes on total income characterized by giving a clear picture of the total income of the taxpayer and its financial situation and its burden family which allows granting exemptions, downloads, and application of prices that fit this case. This requires reconsideration of the structure of the tax system in force and the transition from a system specific taxes to the tax system on the total income of the integration of income from the rental of re
... Show MoreThis paper aims at studying the illocutionary speech acts: direct and indirect to show the most dominant ones in a presidential speech delivered by the USA president. The speech is about the most critical health issue in the world, COVID-19 outbreak. A descriptive qualitative study was conducted by observing the first speech delivered by president Trump concerning coronavirus outbreak and surveying the illocutionary acts: directive, declarative, commissive, expressive, and representative. Searle's (1985) classification of illocutionary speech acts is adopted in the analysis.
What are the main types of the illocutionary speech acts performed by Trump in his speech?; Why does
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