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

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

               The bank deposits is fuel banking activity and raw material products for the commercial bank and the basis of its activity and its lifetime So the bank, which seeks to continue the successful development of the volume of cash deposits has translated the work of the bank to meet the needs of different sectors by providing the necessary funding, and from this point of view was the research problem a lack of interest departments of banking services to commercial banks as a means for the development of electronic cash deposits have, and which represents the basis for the supplier commercial bank fund.

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

Experimental tests were conducted to investigate the thermal performance (cooling effect) of water mist system consisting of 5μm volume median diameter droplets in reducing the heat gain entering a room through the roof and the west wall by reducing the outside surface temperature due to the evaporative cooling effect during the hot dry summer of Baghdad/Iraq. The test period
was Fifty one days during the months May, June, and July 2012. The single test day consists of 16 test hours starting from 8:00 am to 12:00 pm. The results showed a reduction range of 1.71 to 15.5℃ of the roof outside surface temperature and 21.3 to 76.6% reduction in the daily heat flux entering the room through the roof compared with the case of not using w

A characteristic study of a passively Q-switched diode pumped solid state laser system is presented in this work. For laser a comparison study for the theoretically calculated results with a simulation results using a software which calculates the Q-switched solid state laser parameters was such as energy, peak power and pulse width were performed. There was a good agreement between our theoretical calculations and the simulation values.

Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro