The Evolution Of Information Technology And The Use Of Computer Systems Led To Increase Attention To The Use Of Modern Techniques In The Auditing Process , As It Will Overcome Some Of The Human Shortcomings In The Exercise Of Professional Judgment, Then It Can Improve The Efficiency And Effectiveness Of The Audit Process, Where The New Audit Methodologies Espouse The Concept Of Risk Which Includes Strategic Dimension With Regard To The Capacity Of The Entity To Achieve Its Goals, Which Requires Auditors To Rely On Advanced Technology That Can Identify The Factors Which Prevent The Entity From Achieving Its Objectives. The Idea Of Research Is To Preparing An Electronic Program Fer All Audit Work From Planning Through Sampling And Documentation Of Working Papers To Get A Draft Of The Report And The Report Of The Evaluation Of The Supervisory Work Performance From The Hypothesis (That The Adoption Of Artificial Intelligence Technique In The Audit Process Stages Will Lead To The Success Of The Audit Function And Improving Its Quality), Artificial Intelligence Is Related To The Representation Of A Computer Model Of Area, An Then Retrieve And Develop As Well As It Is Compared With The Status And Events Of Research To Draw Helpful Conclusions.
In this work, an enhanced Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) sensor using a sided polished structure for the detection of toxic ions Arsenic in water was designed and implemented. The SPR curve can be obtained by polishing the side of the PCF after coating the Au film on the side of the polished area, the SPR curve can be obtained. The proposed sensor has a clear SPR effect, according to the findings of the experiments. The estimated signal to Noise Ratio (SNR), sensitivity (S), resolution (R), and Figures of merit (FOM) are approaching; the SNR is 0.0125, S is 11.11 μm/RIU, the resolution is 1.8x〖10〗^(-4), and the FOM is 13.88 for Single-mode Fiber- Photonic Crystal Fiber- single mode Fiber (SMF-P
... Show MoreLeap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F
... Show MoreABSTRACT Pulmonary alveolar microlithiasis is rare infiltrative pulmonary disease characterized by intra-alveoli deposition of microliths. We present a familial case of an adult female with complaint of progressive shortness of breath on exertion. Chest radiograph showed innumerable tiny dense nodules, diffusely involving both lungs mainly the lower zones. High-resolution CT scan illustrated widespread intra-alveolar microliths, diffuse ground-glass attenuation areas and septal thickening predominantly in the basal regions. Chest radiograph is all that is needed for the diagnosis of this case but CT scan was done to demonstrate the extent and severity of this disease
A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.
... Show MoreIn many areas, such as simulation, numerical analysis, computer programming, decision-making, entertainment, and coding, a random number input is required. The pseudo-random number uses its seed value. In this paper, a hybrid method for pseudo number generation is proposed using Linear Feedback Shift Registers (LFSR) and Linear Congruential Generator (LCG). The hybrid method for generating keys is proposed by merging technologies. In each method, a new large in key-space group of numbers were generated separately. Also, a higher level of secrecy is gained such that the internal numbers generated from LFSR are combined with LCG (The adoption of roots in non-linear iteration loops). LCG and LFSR are linear structures and outputs
... Show MoreHomomorphic encryption became popular and powerful cryptographic primitive for various cloud computing applications. In the recent decades several developments has been made. Few schemes based on coding theory have been proposed but none of them support unlimited operations with security. We propose a modified Reed-Muller Code based symmetric key fully homomorphic encryption to improve its security by using message expansion technique. Message expansion with prepended random fixed length string provides one-to-many mapping between message and codeword, thus one-to many mapping between plaintext and ciphertext. The proposed scheme supports both (MOD 2) additive and multiplication operations unlimitedly. We make an effort to prove
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
... Show More