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

In today's digital era, the importance of securing information has reached critical levels. Steganography is one of the methods used for this purpose by hiding sensitive data within other files. This study introduces an approach utilizing a chaotic dynamic system as a random key generator, governing both the selection of hiding locations within an image and the amount of data concealed in each location. The security of the steganography approach is considerably improved by using this random procedure. A 3D dynamic system with nine parameters influencing its behavior was carefully chosen. For each parameter, suitable interval values were determined to guarantee the system's chaotic behavior. Analysis of chaotic performance is given using the

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

Abstract: The aim of the present work is to measure radon concentration in wood. Solid state nuclear track detectors of type CR – 39 was used as measurement device. Eight different samples of imported and local wood were collected from markets. Samples were grinded, dried in order to measure radon concentrations in it. Cylindrical diffusion tube was used as detection technique. Results show that the higher concentration was in Iraqi sample 1 which recorded (14.02 ± 0.9) Bq / m3, while the less was in Emirates Sample which recorded (5.35 ± 1.2) Bq / m3. From the present work, all wood samples were with lowest concentrations of radon gas than other building materials.

The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)

ABSTRACT— In primary teeth, root canal treatment is a time consuming and challenging procedure, particularly during the most important step in endodontic treatment which is the preparation of the canal. Pulpectomy is the treatment of choice in all the necrotic primary teeth. For better treatment protocol, advancing technology brought the rotary system to reduce the manual dexterity and improve the quality of treatment for pulpectomy. This study aimed to compare and assess the efficacy of cleaning and the time required for the instrumentation during the preparation of root canals of the primary molars using the rotary and the manual (conventional) systems. Thirty root canals of primary teeth were selected. These teeth submitted to a

The present work is an attempt to develop design data for an Iraqi roof and wall constructions using the latest ASHRAE Radiant Time Series (RTS) cooling load calculation method. The work involves calculation of cooling load theoretically by introducing the design data for Iraq, and verifies the results experimentally by field measurements. Technical specifications of Iraqi construction materials are used to derive the conduction time factors that needed in RTS method calculations. Special software published by Oklahoma state university is used to extract the conduction factors according to the technical specifications of Iraqi construction materials.  Good agreement between the average theoretical and measured cooli