The design of safe pedestrian facilities usually depends on the assessment of pedestrian characteristics and behavior. In this investigation, pedestrian walking speed through the religious occasion have been monitored at three locations, Al- Kadhimiya (Imam AL-Kadim), Najaf and Karbala (Imam AL-Husain) holy shrines. Video captures of the pedestrian through their walking to the two holy shrines have been prepared and analyzed for walking speed, gender, age groups, and clothing tradition. The pedestrian sample size is 468, 501, and 447 for Al- Kadhimiya, Karbala, and Najaf respectively. When the gender is taken into consideration, it can be noted that the walking speed of male and female pedestrian is (0.97, 1.68, and 1.63

Saudi Arabia’s banking sector plays an important role in the country’s development as it is among the leading sectors in the financial sector. Considering, two main Saudi banks (The National Commercial Bank and Saudi American bank), the present study aims to observe the impact of emotional intelligence on employee performance. The components of emotional intelligence affecting employee performance include self-management, relationship management, self-awareness, and social awareness. A quantitative methodology was applied to analyse the survey results of 300 respondents over the period from 2018 to 2019. The results show that there was a significant positive impact of self-management, self-awareness, and relationship manageme

Communicating effectively by gaining productive skills in a classroom setting is one of the critical goals of learning the English language. The current study was conducted to explore the correlation of EFL learners’ level of academic intelligence with their productive skills. The study tries to find an answer to what is the correlation between EFL learners’ academic intelligence and level of production skills. The study population represents EFL students at the departments of English language of the Iraqi Colleges of Education for the academic year (2022-2023). The sample includes 310 EFL students selected from the 3rd year of the Department of English of the College of Education, Ibn-Rushd for Human Sciences/University of Bagh

This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor

Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.