Entropy generation was studied for new type of heat exchanger (shell and double concentric tubes heat exchanger). Parameters of hot oil flow rate, temperature of inlet hot oil and pressure drop were investigated with the concept of entropy generation. The results showed that the value of entropy generation increased with increasing the flow rate of hot oil and when cold water flow rate was doubled from 20 to 40 l/min, these values were larger. On the other hand, entropy generation increased with increasing the hot oil inlet temperature at a certain flow rate of hot oil. Furthermore, at a certain hot oil inlet temperature, the entropy generation increased with the pressure drop at different hot oil inlet flow rates. Final

This study concerns a new type of heat exchangers, which is that of shell-and-double concentric tube heat exchangers. The case studies include both design calculations and performance calculations.

       The new heat exchanger design was conducted according to Kern method. The volumetric flow rates were 3.6 m³/h and 7.63 m³/h for the hot oil and water respectively. The experimental parameters studied were: temperature, flow rate of hot oil, flow rate of cold water and pressure drop.

A comparison was made for the theoretical and experimental results and it was found that the percentage error for the hot oil outlet temperature was (- 1.6%). The percentage

   This research presents a comparison of performance between recycled single stage and double stage hydrocyclones in separating water from water/kerosene emulsion. The comparison included several factors such as: inlet flow rate (3,5,7,9, and 11 L/min), water feed concentration (5% and 15% by volume), and split ratio (0.1 and 0.9). The comparison extended to include the recycle operation; once and twice recycles. The results showed that increasing flow rate as well as the split ratio enhancing the separation efficiency for the two modes of operation. On the contrary, reducing the feed concentration gave high efficiencies for the modes. The operation with two cycles was more efficient than one cycle. The maximum obtained effici

The concept of entransy dissipation was determined for new type of heat exchanger (shell and double concentric tubes heat exchanger). Three parameters, hot oil flow rate, temperature of inlet hot oil and pressure drop of system were investigated with this concept (entransy dissipation). The results showed that the value of entransy dissipation of oil and of system which represents the summation of entransy dissipation of both oil and water increased with increasing the flow rate of hot oil and these values were larger when cold water flow rate was doubled. Also they were increased with increasing the hot oil inlet temperature at a certain flow rate of hot oil. Furthermore, the pressure drops for hot oil in both shell side and inner tubes

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

The process of transformation from the central economy to a free economy requires restructuring the economy according to a new economic philosophy that relies on activating the role of private economic activity in which private and medium-sized institutions occupy an essential axis for their active role in the economies of all countries, especially those countries that have directed towards the market mechanism and sector leadership. The special process of economic development and the role that commercial banks can play in advancing the financing of these projects by establishing specialized business incubators for financing.

What encouraged countries to pay attention to these institutions is the ease of