Feasibility of biosorbent of England bamboo plant origin was tested for removal of priority metal ions such as Cu and Zn from aqueous solutions in single metal state. Batch single metal state experiments were performed to determine the effect of dosage (0.5, 1 and 1.5 g), pH (3, 4, 4.5, 5 and 6), mixing speed (90, 111, 131, 156 and 170 rpm), temperature (20, 25, 30 and 35 °C) and metal ion concentration (10, 50, 70, 90 and 100 mg/L) on the ability of dried biomass to remove metal from solutions which were investigated. Dried powder of bamboo removed (for single metal state) about 74 % Cu and 69% Zn and maximum uptake of Cu and Zn was 7.39 mg/g and 6.96 mg/g respectively, from 100 mg/L of synthetic metal solution in 120 min. of contact time at pH 4.5 and 25°C with continuous stirring at 170 rpm. Experimental results have been analyzed using Langmuir and Freundlich isotherms. Both equilibrium sorption isotherms were found to represent well the measured sorption data, but Freundlich isotherm was better than Langmuir isotherm. The effect of time was studied and the rate of removal of Cu (II) and Zn (II) ions from aqueous solution by bamboo plant was found. The rates of sorption of copper and zinc were rapid initially within 5-15 minutes and reached a maximum in about 60 minutes.
The current theoretical research targeted to construct a model of terrorist personality and its differentiation from psychopathic personality . Several assumptions or theories of perspectives of psychopathic personality have been compared with the terrorist personality studies that concerned . The suggested theoretical model is interrupting the terrorist personality . The conclusions , discussions are mentioned. Finally, recommendation is suggested .
The book presents a study of an archive comprising 290 cuneiform texts, all of which pertain to a significant yet relatively underexplored subject, commonly referred to as the “Treasure and Shoes Archive,” whose provenance has been attributed to the site of Drehem. The book also examines the scholarly debate surrounding Isakkidana-Nefar and Buzursh-Dagan. Furthermore, it explores the economic activities of the princes and princesses of the royal family during the Third Dynasty of Ur, shedding light on their economic roles and activities within the broader administrative and socioeconomic framework of the period.
The subject of the Internet of Things is very important, especially at present, which is why it has attracted the attention of researchers and scientists due to its importance in human life. Through it, a person can do several things easily, accurately, and in an organized manner. The research addressed important topics, the most important of which are the concept of the Internet of Things, the history of its emergence and development, the reasons for its interest and importance, and its most prominent advantages and characteristics. The research sheds light on the structure of the Internet of Things, its structural components, and its most important components. The research dealt with the most important search engines in the Intern
... Show MoreNeural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.
Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
... Show MoreThe penalized least square method is a popular method to deal with high dimensional data ,where the number of explanatory variables is large than the sample size . The properties of penalized least square method are given high prediction accuracy and making estimation and variables selection
At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and
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