The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (k_La), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

Due to increased consumption of resources, especially energy it was necessary to find alternatives characterized by the same quality as well as being of less expensive, and most important of these alternatives are characterized by waste and the fact that humancannot stop consumption. So we  have consideredwaste as an  alternative and cheap economic resources and by using environmental index the MIP (input materials per unit ,unit / service) is based on the grounds that the product is not the end of itselfit is a product to meet the need  of a product or service, awarded a resource input and output within the five basic elements are the raw materials is ecological, Raw materials ecological, water, air and soil erosion for a

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

: The need for means of transmitting data in a confidential and secure manner has become one of the most important subjects in the world of communications. Therefore, the search began for what would achieve not only the confidentiality of information sent through means of communication, but also high speed of transmission and minimal energy consumption, Thus, the encryption technology using DNA was developed which fulfills all these requirements [1]. The system proposes to achieve high protection of data sent over the Internet by applying the following objectives: 1. The message is encrypted using one of the DNA methods with a key generated by the Diffie-Hellman Ephemeral algorithm, part of this key is secret and this makes the pro

This research had been achieved to identify the image of the subsurface structure representing the Tertiary period in the Galabat Field northeast of Iraq using 2D seismic survey measurements. Synthetic seismograms of the Galabat-3 well were generated in order to identify and pick the reflectors in seismic sections. Structural Images were drawn in the time domain and then converted to the depth domain by using average velocities. Structurally, seismic sections illustrate these reflectors are affected by two reverse faults affected on the Jeribe Formation and the layers below with the increase in the density of the reverse faults in the northern division. The structural maps show Galabat field, which consists of longitudinal Asymmetrical narr