The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.

In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

A simple and novel membraneless paper-based microfluidic fuel cell was presented in this study. The occurrence of laminar flow was employed to ensure no mixing of the fuel and oxidant fluids along the bath of reaction. The acidic wastewater was used as a fuel. It was an air-breathing cell, so air and tab water were used as oxidants. Both the fuel and tab water flowed continuously under gravity. Whatman filter paper was used for preparation of the fuel cell channel and two carbon fibre electrodes were used and firmed on the edges of the cell. The performance of the cell was examined over three consecutive days. The results indicated that the present cell has the potential to generate electric power, but an extensive study is required to harv

This research after financial ratios in the detection of fraud to the financial statements published which enables specialists from the work of their studies and their conclusions to obtain the information they seek on the activities of the entity. Has provided researchers what these relics They then field study to test the validity and sincerity of the findings of the suggestions that have been upheld the need to study all financial ratios extracted in general, organized and used in decision-making processes necessary administrative.And that the financial management attention more financial analysis and extraction of financial ratios and compare them with industry standards taken from historical norms

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order  PI^aD^b (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to  torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of

The execution phase  of the project is most dangerous and the most drain on the resources during project life cycle, therefore, its need to monitor and control by specialists to exceeded obstructions and achieve the project goals. The study aims to detect the actual reasons behind mismanagement of the execution phase. The study begins with theoretical part, where it deals with the concepts of project, project selection, project management, and project processes. Field part consists of three techniques: 1- brainstorming, 2- open interviews with experts and 3- designed questionnaire (with 49 reason. These reasons result from brainstorming and interviewing with experts.), in order to find the real reasons behind misman