Application of ANFIS for modeling of layer thickness of chromium carbonitride coating

In the present work, layer thickness of duplex coating made from thermo-reactive deposition and diffusion has been predicted by Adaptive network-based fuzzy inference systems (ANFIS). A duplex surface treatment on five steels has been developed involving nitrocarburizing and followed by chromium thermo-reactive deposition (TRD) techniques. The TRD process was performed in molten salt bath at 550, 625 and 700 °C for 1–30 h. The process formed a thickness up to 9.5 μm of chromium carbonitride coatings on a hardened diffusion zone. A model based on ANFIS for predicting the layer thickness of duplex coating of the specimens has been presented. To build the model, training and testing using experimental results from 84 specimens were conducted. The data used as inputs in ANFIS models are arranged in a format of twelve parameters that cover the chemical composition (C, Mn, Si, Cr, Mo, V, W), the pre-nitriding time, ferro-chromium particle size, ferro-chromium weight percent, salt bath temperature and coating time. According to these input parameters, in the Adaptive network-based fuzzy inference system models, the layer thickness of duplex coating of each specimen was predicted. The training and testing results in ANFIS models have shown a strong potential for predicting the layer thickness of duplex coating.     

Optimum design of electromagnetic shielding rooms with minimum usage of absorbing materials

In this article, a novel method has been proposed to optimize the electromagnetic shielding rooms. This method is based on using minimum electromagnetic absorbing materials on the inner surface of the rooms. The positions of the absorbing materials are found optimally to produce a “best” performance for the shielding rooms. The ray‐tracing method is used to predict the shielding effectiveness (SE) of the electromagnetic shielding rooms with apertures. The performance of the proposed method is verified by a comprehensive example. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE 2010.     

A theory of mode of action of azolylalkylquinolines as DNA binding agents using automated flexible ligand docking

Azolylalkylquinolines (AAQs) are a family of quinolines with varying degrees of cytotoxic activity (comparable or moderately superior to adriamycin in some cases) developed in the past decade in our group where their exact mode of action is still unclear. In this study the most probable DNA binding mode of AAQs was investigated employing a novel flexible ligand docking approach by using AutoDock 3.0. Forty-nine AAQs with known experimental inhibitory activity were docked onto d(CGCAAATTTGCG)(2), d(CGATCG)(2) and d(CGCG)(2) oligonucleotides retrieved from the Protein Data Bank (PDB IDs: 102D, 1D12 and 1D32, respectively) as the representatives of the three plausible models of interactions between chemotherapeutic agents and DNA (groove binding, groove binding plus intercalation and bisintercalation, respectively). Good correlation (r(2)=0.64) between calculated binding energies and experimental inhibitory activities was obtained using groove binding plus intercalation model for phenyl-azolylalkylquinoline (PAAQ) series. Our findings show that the most probable mode of action of PAAQs as DNA binding agents is via intercalation of quinolinic moiety between CG base pairs with linker chain and azole moiety binding to the minor groove.     

Quantitative characterization of carrier injection across metal–organic interfaces using Bardeen theory

We have investigated the contact between a metal and an organic/polymeric (o/p) material and we have introduced a relation for carrier injection using Bardeen theory. A series of narrow barriers is considered in the semiconductor side to account for the localized nature of the carriers in the o/p material. As an application of the model, we have calculated the hopping rate of carriers in terms of the contact parameters. Also, we have discussed the hopping of carriers deep into the organic dielectric. Finally, we have explored the hopping rate in practical contacts between polyfluorene-based polymers and different electrodes.     

To reduce side lobe level of slotted array antennas using nonuniform waveguides

In this article, a method is presented to reduce the side lobe level of slotted waveguide array antennas while the gain to be constant. In this method, the H‐plane dimension of the waveguide is considered as the variable rather than constant. The nonuniformity of waveguide walls obviates the need for offset of slots and thereby reduces the side lobe level of radiation pattern. A slotted nonuniform waveguide is designed at frequency 10 GHz and then fabricated and tested. © 2015 The Authors International Journal of RF and Microwave Computer‐Aided Engineering Published by Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:42–46, 2016.     

Palladium nanoparticles as reusable catalyst for the synthesis of N-aryl sulfonamides under mild reaction conditions

An efficient palladium nanoparticles-catalyzed N-arylation of sulfonamides and sulfonyl azides is described. This procedure serves as an active protocol for intermolecular C–N bond formation using Pd(OAc)₂ in PEG-400 under air. Aryl bromides and triflates react at 35°C, while aryl chlorides require heating to 50°C and give the desired products only in low yields. This reaction proceeds smoothly in acceptable yields using low catalyst loading.     

Estimation of skew angle in text-image analysis bySLIDE: Subspace-based line detection

A new signal processing method is developed for estimating the skew angle in text document images. Detection of the skew angle is an important step in text processing tasks such as optical character recognition (OCR) and computerized filing. Based on a recently introduced multiline-fitting algorithm, the proposed method reformulates the skew detection problem into a special parameter-estimation framework such that a signal structure similar to the one in the field of sensor array processing is obtained. In this framework, straight lines in an image are modeled as wavefronts of propagating planar waves. Certain measurements are defined in this virtual propagation environment such that the large amount of coherency that exists between the locations of the pixels on parallel lines is exploited to enhance a subspace in the space spanned by the measurements. The well-studied techniques of sensor array processing (e.g., the ESPRIT algorithm) are then exploited to produce a closed form and high-resolution estimate for the skew angle.     

ANFIS-based prediction of the compressive strength of geopolymers with seeded fly ash and rice husk–bark ash

In the present work, compressive strength of geopolymers made from seeded fly ash and rice husk–bark ash has been predicted by adaptive network-based fuzzy inference systems (ANFIS). Different specimens, made from a mixture of fly ash and rice husk–bark ash in fine and coarse forms and a mixture of water glass and NaOH mixture as alkali activator, were subjected to compressive strength tests at 7 and 28 days of curing. The curing regimes were different: one set of the specimens were cured in water at room temperature until 7 and 28 days and the other sets were oven-cured for 36 h at the range of 40–90°C and then cured at room temperature until 7 and 28 days. A model based on ANFIS for predicting the compressive strength of the specimens has been presented. To build the model, training and testing using experimental results from 120 specimens were conducted. The used data as the inputs of ANFIS models are arranged in a format of six parameters that cover the percentage of fine fly ash in the ashes mixture, the percentage of coarse fly ash in the ashes mixture, the percentage of fine rice husk–bark ash in the ashes mixture, the percentage of coarse rice husk–bark ash in the ashes mixture, the temperature of curing, and the time of water curing. According to these input parameters in the ANFIS models, the compressive strength of each specimen was predicted. The training and testing results in ANFIS models showed a strong potential for predicting the compressive strength of the geopolymeric specimens.     

Repeated loading of soil containing granulated rubber and multiple geocell layers

Sandy soil/aggregate, such as might be required in a pavement foundation over a soft area, was treated by the addition of one or more geocell layers and granulated rubber. It was then subjected to cyclic loading by a 300 mm diameter plate simulative of vehicle passes. After an initial study (that established both the optimum depth of the uppermost geocell layer and of the geocell inter-layer spacing should be 0.2 times plate diameter), repeated loading was applied to installations in which the number of geocell layers and the presence or absence of shredded rubber layers in the backfill was changed. The results of the testing reveal the ability of the composite geocell-rubber-soil systems to ‘shakedown’ to a fully resilient behavior after a period of plastic deformation except when there is little or no reinforcement and the applied repeated stresses are large. When shakedown response is observed, then both the accumulated plastic deformation prior to a steady-state response being obtained and the resilient deformations thereafter are reduced. Efficiency of reinforcement is shown to decrease with number of reinforcement layers for all applied stress levels and number of cycles of applied loading. The use of granulated rubber layers are shown to reduce the plastic deformations and to increase the resilient displacements compared to the comparable non-rubber construction. By optimal use of geocells and granulated rubber, deformations can be reduced by 60–70% compared with the unreinforced case while stresses in the foundation soil are spread much more effectively. On the basis of the study, the concept of combining several geocell layers with shredded rubber reinforcement is recommended for larger scale trials and for economic study.