The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

This study employs wavelet transforms to address the issue of boundary effects. Additionally, it utilizes probit transform techniques, which are based on probit functions, to estimate the copula density function. This estimation is dependent on the empirical distribution function of the variables. The density is estimated within a transformed domain. Recent research indicates that the early implementations of this strategy may have been more efficient. Nevertheless, in this work, we implemented two novel methodologies utilizing probit transform and wavelet transform. We then proceeded to evaluate and contrast these methodologies using three specific criteria: root mean square error (RMSE), Akaike information criterion (AIC), and log

Objective(s): To measure the level of job satisfaction and job performance of nurses and to find out
the association between participants' socio-demographic characteristic of nurse and their job
satisfaction and job performance.
Methodology: A descriptive analytic study design was carried out to measure the nurses' level of job
satisfaction and job performance in Al-Suwaira general hospital and to find out the association between
nurses and their socio-demographic characteristic. The study was started from March 5th, 2017 to
September 31th, 2017. The sample was Non - probability (purposive) sample of (100) nurses were
selected according to the study that are actual working in nursing department in Al-Suwaira General<

The Main Outfall drain pumping station in Nassiriyah is an important part in operation  system of the Main Outfall Drain (MOD) where it reduces the water levels in the U/S area of its and converted through Syphon freely under the Euphrates, its consists of several parts: U/S Basin, Station Building which contains 12 pumps, and Head Basin with Syphon, This station suffers from high levels especially in D/S area due to the current situation which is represented by establishing of dyke with pipes on MOD which located at 24 km from D/S of pumping station and Al-Khamisiyah Canal which located at 2.3 km from the U/S of dyke which feeds(Al Hammar Marsh) during drought season, several scenarios were adopted in order to expl

The current research aims to analyze the role of participatory budgeting in improving performance, especially during crises such as the Covid-19 crisis. The research used the descriptive analytical method to reach the results by distributing 100 questionnaires to a number of employees in Iraqi joint stock companies and at multiple administrative levels. The research came to several important conclusions, the most important of which is that the bottom-up approach to budgeting produces more achievable budgets than the top-down approach, which is imposed on the company by senior management with much less employee participation. Additionally, there is a better information flow from the lower levels of the organization to the upper management

       The current study aimed at identifying the impact of each of the full and part time summer enrichment programs on the performance of gifted students. Moreover, it aimed to study the difference between the full and part time programs on the performance of gifted students. The study sample consisted of (115) students from the full time programs and (137) students from the part time programs, they have been randomly selected from the gifted students participating in the full and part time summer enrichment programs. The researcher used the scale of student performance. The results indicated that there were statistically significant differences between the averages of the pre and post applications of the