Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

Objective: The objective of this study was to prepare nanosuspension of a practical water insoluble antiulcer drug which is lafutidine to enhance the solubility, dissolution rate with studying the effect of different formulation variables to obtain the best formula with appropriate physical properties and higher dissolution rate.Methods: Nanosuspension of lafutidine was prepared using solvent anti-solvent precipitation method using Polyvinylpyrrolidone K-90(PVP K-90) as the stabilizer. Ten formulations were prepared to show the effect of different variables in which two formulations showed the effect of stabilizer type, three formulations showed the effect of stabilizer concentration, two formulations showed the effect of combinatio

the most important purposes and uses of the test results in the educational sector. This is because the quality of tests is related to their ability to predict the learner's behavior in the future, and the accuracy of the educational and administrative decisions that are taken in light of their results. The study aimed accordingly to reveal the predictive ability of the university Grade Point Average (GPA) in the Score of the specialized test for the position of teacher in the Ministry of Education in the Sultanate of Oman. It further aimed to investigate the differences in the predictive ability according to the specialization and academic year using the descriptive approach. The sample of the study consisted of (349) s/he students enro

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim