: The need for means of transmitting data in a confidential and secure manner has become one of the most important subjects in the world of communications. Therefore, the search began for what would achieve not only the confidentiality of information sent through means of communication, but also high speed of transmission and minimal energy consumption, Thus, the encryption technology using DNA was developed which fulfills all these requirements [1]. The system proposes to achieve high protection of data sent over the Internet by applying the following objectives: 1. The message is encrypted using one of the DNA methods with a key generated by the Diffie-Hellman Ephemeral algorithm, part of this key is secret and this makes the process of predicting the key very difficult. 2. Ensuring the integrity and reliability of the transmitted data using the HMAC-HASH256 algorithm that is resistant to attacks, where the 256 hash function is used with a key generated from the Diffie-Hellman Ephemeral algorithm. 3. Analyzing the system by trying to measuring the impact of using encryption with authentication on cost and speed and calculating the time taken to implement the HMAC-SHA256 algorithm. System implementation was done by using IntelliJ IDEA with java FX.
The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
... Show MoreThis work discusses the beginning of fractional calculus and how the Sumudu and Elzaki transforms are applied to fractional derivatives. This approach combines a double Sumudu-Elzaki transform strategy to discover analytic solutions to space-time fractional partial differential equations in Mittag-Leffler functions subject to initial and boundary conditions. Where this method gets closer and closer to the correct answer, and the technique's efficacy is demonstrated using numerical examples performed with Matlab R2015a.
A simple, accurate, and cost-efficient UV-Visible spectrophotometric method has been developed for the determination of naphazoline nitrate (NPZ) in pure and pharmaceutical formulations. The suggested method was based on the nucleophilic substitution reaction of NPZ with 1,2-naphthoquinone-4-sulfonate sodium salt in alkaline medium at 80°C to form an orange/red-colored product of maximum absorption (λmax) at 483 nm. The stoichiometry of the reaction was determined via Job's method and limiting logarithmic method, and the mechanism of the reaction was postulated. Under the optimal conditions of the reaction, Beerʼs law was obeyed within the concentration range 0.5–50 μg/mL, the molar absorptivity value (ε) was 5766.5 L × mol–1 × c
... Show MoreIn recent years, various methods have been developed to enhance the characteristics of asphalt pavement in order to face the continuous challenges of increasing traffic loads and changing climate conditions. One of the most popular and successful methods is modifying the asphalt mixtures or asphalt binder with the addition of polymers. Therefore, two types of Polyethylene (PE) polymer, High-Density PE (HDPE) and Low-Density PE (LDPE), are used in this research. Two methods were applied to prepare PE-modified asphalt mixtures: Semi-Wet Method (S-WM) and Dry Method (DM). The findings of the investigation indicated that the addition of PE polymer can reduce the wear loss of aggregate. In general, the experimental results revealed that asphalt
... Show MoreUnderstanding, promoting, and teaching media literacy is an important societal challenge. STEM educators are increasingly looking to incorporate 21st century skills such as media literacy into core subject education. In this paper we investigate how undergraduate Computer Science (CS) students can learn media literacy as a by-product of collaborative video tutorial production. The paper presents a study of 34 third-year CS undergraduates who, as part of their learning, were each asked to produce three video tutorials on Raspberry Pi programming, using a collaborative video production tool for mobile phones (Bootlegger). We provide results of both quantitative and qualitative analysis of the production process and resulting video tutorials,
... Show MoreObjective: The study aims to determine the effect of Toxoplasma gondii infection on the
genetic sequence of breast cancer patients in the Medical City Hospital – Tumor Unit /
Iraq-Baghdad.
Methodology: A study was carried out in the City of Medicine / Oncology Unit / Baghdad,
during the period 1st June 2016 to 15
th March 2017. Forty samples of tissue and serum
were collected from patients who complaining from Breast cancer and infected with
Toxoplasmosis. Forty sera samples were taken from patients complaining from parasitic
infection only; without breast cancer as control group. Data is analyzed by using of
descriptive and inferential data analysis methods.
Results: The results show that there is an effe
This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them
Deep 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 aim of this research was to study the concentrations of Uranium in the phosphorus fertilizers using Nuclear track detector (CR-39). Our present investigation is based on the study of 10 types samples for different kinds of phosphorus fertilizers which were available in the local market Some of them were Iraqi made and the others from different countries like, (Iran, Italy, Holland, Lebanon and Jordan) .. The result obtained shows that the Uranium concentration in phosphorus fertilizers samples varies from (3.59ppm) to(2.59ppm). Based on the radioactive concentration of Uranium in the samples all the results obtained between(3.59ppm) in the Iraqi super phosphate to (2.59ppm) in the mixture Iraqi phosphate fertilizer are withi
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