Most 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

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me

This research deals with the risks of non-compliance and its impact on the profitability of Islamic banks. Research variables were measured and analyzed as the risk of non-compliance as an independent variableand profitability as a dependent variable. The profitability was measured by three indicators ((rate of return on assets, rate of return on equity and rate of return on Total deposits)) The results of the research showed a significant relationship between the risk of non-compliance and the rate of return on assets and rate of return on total deposits, while there was no relationship between the risk of non-compliance and rate of return on ownership. The research recommended that the senior management of the Islamic Investment Bank s

The aim of this paper is to examine cases of deletion not dependent on linguistic context. Perlmutter (1971) claims that any sentence other than an imperative¹ in which there is an S that does not contain a subject in the surface structure is ungrammatical. Dillon (1978) counts elliptical sentences such as ^ Beg your pardon² as grammatically incomplete (and hence as strictly ungrammatical). Such statements are, however, not without problems for reasons that will be given below.

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

In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot

This study aimed to measure the innovative thinking and cognitive cessation among university students. The sample consisted of (400) male and female students at al Mustansiriya University for the academic year (2018/2019). The results of the study showed that there are differences in innovative thinking and cognitive inhibition according to the gender variable in favor of males. There is a positive relationship between innovative thinking and cognitive inhibition. In light of these findings, the researcher presented a set of conclusions and recommendations.