This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them in terms of accuracy.
The effect of compound machine on wheat "Tamuz cultivar" was studied based on some technical indicators which were tested under three practical speed (PS) of 2.015, 3.143, and 4.216 km.hr-1 and three tillage depth (TD) of 11, 13, and 15cm. The split-split plot arrangement in RCBD with three replications was used. The results showed that the PS of 2.015km.hr-1 was major best than other two speed in all studied conditions, physical properties (SBD and TSP), mechanical parameters (FD, (DP and LAS), and yield and growth parameters (PVI, BY and HI). The TD of 11cm was major effect to the other two levels TD of 13 and TD of 15cm in all studied conditions. All interactions were significant,
This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta
... Show MoreThis work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m
... Show MoreDuring the winter, in the industry region (Shaikh Omer) and by applying a passive radon detector (CR-39), lung cancer risk has been measured in twelve rooms of different workshops of two old factories in this site. The radon concentration is ranged from (123.345 Bq/m3) to (328.985 Bq/m3) with an average of (244.19±61.52 Bq/m3). Lung cancer risk ranged from 55.993 to 149.346 per million people and with an average of (110.855 per million people) which were lower than the recommended values (170-230 per million people), so there was no cancer risk on workers in these locations.
The research work represent a fast and simple method for the determination of methionine using chemiluminescence for the methionine-sodium hydroxide-luminol for the generation of a chemiluminesecent derivative of luminal. The emission was measured by continuous flow analysis made sample size of 83µL was used.Response versus concentration extended from 0.2-20 mM.L-1 with a percentage linearity of 96.17% or with 99.17% percentage of linearity for the range 0.6-20 mM.L-1. Reaching to a L.O.D. at (S/N=3) for 5 µM.L-1 from the gradual dilution for the minimum concentration in the calibration graph with a repeatability of less than 0.5% (n=10). A comparison was made between the new developed method with the classical method for the spectrophoto
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