On the solubility of aluminum in cryolitic melts

The solubility of aluminum in NaF-AlF₃-Al₂O₃ melts with various additives was found to increase with increasing NaF/AlF₃ molar ratio (CR) and increasing temperature and to decrease with additions of A1₂O₃, CaF₂, MgF₂, and LiF to the melts. With the use of literature data for the activities of NaF and A1F₃ in cryolitic melts, three dissolution reaction models were found to give a good fit to the experimental solubility data. According to the most probable of these models the total concentration of dissolved aluminum (aluminum and sodium species) is given by c_Al = c_Na(diss) + c_AlF2- + c_Al2F3- + c_Al3F4- + c_Al4F5- In NaF rich melts, aluminum will dominantly dissolve as sodium, while at cryolite ratios commonly used in aluminum electrowinning (CR = 2.25 to 2.7) the AlF _-2 ^- -ion is the predominant dissolved metal species. Other species (A1₂F₃ ^-, A1₃F₄-, A1₄F₅-) were found to be of some significance only in melts with high excess A1F₃ (CR < 2).     

Zirconium tetra-n-butylate modified with different organic acids: Hydrolysis and polymerization of the products

In this work, (a) complexation reaction of zirconium tetra-n-butylate, Zr(OBu ⁿ )₄, with MAc and different organic acids, (b) the hydrolysis reaction of modified Zr species, and (c) the polymerization reaction of complex products are studied. Zr(OBu ⁿ )₄ was reacted with different mole ratios of methacrylic acid (MAc) at room temperature and the maximum combination ratio was found to be 1:2 [Zr(OBu ⁿ )₄:MAc] by FT-IR. The modification of zirconium tetra-n-butylate with the acid mixtures [methacrylic acid-acetic acid (MeCOOH), methacrylic acid-propionic acid (EtCOOH), methacrylic acid-butyric acid (PrCOOH)] was made for a combination ratio of 1:1:1 [MAc:RCOOH:Zr(OBu ⁿ )₄; R: Me, Et, Pr] and the products were characterized by¹H-NMR, FT-IR, and UV spectroscopies. Following their synthesis, hydrolysis of the complexes with various amounts of water and polymerization with benzoyl peroxide were realized. The hydrolysis and polymerization products of the complexes were studied by Karl-Fischer coulometric titration and thermal analysis, respectively. Methyl ethyl ketone(MEK) and chloroform were chosen as solvents.     

Towards a comprehensive methodology for KBS development

Abstract: The vitality of effective methods and processes for developing knowledge-based systems (KBS) is examined. The paper discusses what should be expected from a methodology. Have their advocates been getting it all wrong all the way? That is certainly a suggested view put forward. The criticism includes an articulation of the major schools of thought in developing KBS; their implicit assumptions and philosophies, especially the prototyping options, are presented in the light of this paper. After the criticism, the philosophical basis of a new comprehensive KBS development methodology is presented. This breeds the line model of development, which in turn creates what is suspected to be an essential concept of thought in the developer's mind.     

Heat transfer and fluid flow characteristics in flash desalination units

The present work investigates the effects of different operating and geometrical parameters on the flashing efficiency of water in a single stage flashing chamber. This chamber uses a submerged rectangular orifice as flow control area. Experiments were performed to investigate the effects of flow rate, liquid level in the flashing chamber, liquid inlet temperature and flashing range, on the flashing efficiency under various design conditions. These comprise flow with baffle placed in the flashing chamber, and wire meshes placed at the orifice to increase the turbulence level.It was found that the efficiency increased with the increase of the turbulence levels, flashing range and liquid inlet temperature; the efficiency deceased with the increase of the flow rate and liquid level in the flashing chamber. The application of numerical procedure to predict flow pattern and heat transfer in the flashing chamber is introduced as a powerful design tool.     

Artificial Algae Optimization with Deep Belief Network Enabled Ransomware Detection in IoT Environment

The Internet of Things (IoT) has gained more popularity in research because of its large-scale challenges and implementation. But security was the main concern when witnessing the fast development in its applications and size. It was a dreary task to independently set security systems in every IoT gadget and upgrade them according to the newer threats. Additionally, machine learning (ML) techniques optimally use a colossal volume of data generated by IoT devices. Deep Learning (DL) related systems were modelled for attack detection in IoT. But the current security systems address restricted attacks and can be utilized outdated datasets for evaluations. This study develops an Artificial Algae Optimization Algorithm with Optimal Deep Belief Network (AAA-ODBN) Enabled Ransomware Detection in an IoT environment. The presented AAA-ODBN technique mainly intends to recognize and categorize ransomware in the IoT environment. The presented AAA-ODBN technique follows a three-stage process: feature selection, classification, and parameter tuning. In the first stage, the AAA-ODBN technique uses AAA based feature selection (AAA-FS) technique to elect feature subsets. Secondly, the AAA-ODBN technique employs the DBN model for ransomware detection. At last, the dragonfly algorithm (DFA) is utilized for the hyperparameter tuning of the DBN technique. A sequence of simulations is implemented to demonstrate the improved performance of the AAA-ODBN algorithm. The experimental values indicate the significant outcome of the AAA-ODBN model over other models.     

Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

Biomedical image processing is widely utilized for disease detection and classification of biomedical images. Tongue color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and anywhere. For removing the qualitative aspect, tongue images are quantitatively inspected, proposing a novel disease classification model in an automated way is preferable. This article introduces a novel political optimizer with deep learning enabled tongue color image analysis (PODL-TCIA) technique. The presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the tongue. To attain this, the PODL-TCIA model initially performs image pre-processing to enhance medical image quality. Followed by, Inception with ResNet-v2 model is employed for feature extraction. Besides, political optimizer (PO) with twin support vector machine (TSVM) model is exploited for image classification process, shows the novelty of the work. The design of PO algorithm assists in the optimal parameter selection of the TSVM model. For ensuring the enhanced outcomes of the PODL-TCIA model, a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.     

Non-Newtonian Fluids in Spout-Fluid Beds: Mass Transfer Coefficient at Low Reynolds Numbers

Following on from the work of Anabtawi et al. (2003), this study examined how the volumetric liquid-phase mass transfer coefficient, k_La, of oxygen in air in three-phase spout-fluid beds was affected by varying the system parameters of bed height, bed diameter, gas velocity, and liquid velocity. The liquid used was 0.1% CMC solution, displaying a pseudo-plastic rheology, with 1.75 mm glass spheres as packing. The values of the Sherwood number were lower than in previous studies (Anabtawi et al., 2003), in the range 9,000-186,000. Gas velocity had a similar effect on k_La as in a bubble column, with results also giving good agreement with previous work on two-phase and three-phase spouted bed systems. The correlation obtained for the effect of liquid velocity on k_La compared well with that of Schumpe et al. (1989). An increase in the height of packing increased k_La to the power of 0.319, with an increase in column diameter also causing an increase in k_La, which is in agreement with the results of Akita and Yoshida (1973).