ANFIS modeling of biodiesels' physical and engine characteristics: A review

 Population increase has resulted in an increase in the worldwide demand for alternative fuels due to depleting resources. There is a periodic increase in concern about the engine performance, pollutant emissions, and their predictions, from an engine using biodiesels. The use of intelligent algorithms in modeling and forecasting alternative fuels characteristics and their performance in engines are critically reviewed in this study. The paper aims at demonstrating with artificial intelligence methodologies the main conclusions of the recent research done for the above topic from 2012 to 2020. This article attempted to demonstrate an exploratory examination of the adaptive neuro-fuzzy inference system (ANFIS) soft computing technique used for the exact measurement and analysis of engine performance, emissions of exhaust engines when biodiesel is used as an alternative fuel. Additionally, the yield of biodiesel and their different characteristics predicted using ANFIS are also reviewed. Integration of particle swarm optimization (PSO), genetic algorithm (GA), and response surface methodology (RSM), either for comparison or optimization with ANFIS is presented. The summary of all studies is provided in tabular form. For the demonstration purpose, the ANFIS studies predicting different biodiesel and engine characters are provided with illustrative figures. The ANFIS prediction related to biodiesel used engine and biodiesel self-characteristics is found to be excellent. The ANFIS accuracy reported is better than the artificial neural network (ANN) accuracy. A minimum of 0.9 R² value is generally obtained which is around 5% greater than the ANN modeling results reported. However, the ANFIS predictions are much more fitter than the RSM predictions. The integration of ANFIS-PSO and ANFIS-GA provided much more optimized results.     

Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts

Cereal grains and nuts are represented as the economic backbone of many developed and developing countries. Kernels of cereal grains and nuts are prone to mold infection under high relative humidity and suitable temperature conditions in the field as well as storage conditions. Health risks caused by molds and their molecular metabolite mycotoxins are, therefore, important topics to investigate. Strict regulations have been developed by international trade regulatory bodies for the detection of mold growth and mycotoxin contamination across the food chain starting from the harvest to storage and consumption. Molds and aflatoxins are not evenly distributed over the bulk of grains, thus appropriate sampling for detection and quantification is crucial. Existing reference methods for mold and mycotoxin detection are destructive in nature as well as involve skilled labor and hazardous chemicals. Also, these methods cannot be used for inline sorting of the infected kernels. Thus, analytical methods have been extensively researched to develop the one that is more practical to be used in commercial detection and sorting processes. Among various analytical techniques, optical imaging and spectroscopic techniques are attracting growers’ attention for their potential of nondestructive and rapid inline identification and quantification of molds and mycotoxins in various food products. This review summarizes the recent application of rapid and nondestructive optical imaging and spectroscopic techniques, including digital color imaging, X-ray imaging, near-infrared spectroscopy, fluorescent, multispectral, and hyperspectral imaging. Advance chemometric techniques to identify very low-level mold growth and mycotoxin contamination are also discussed. Benefits, limitations, and challenges of deploying these techniques in practice are also presented in this paper.     

SBR-clay-carbon black hybrid nanocomposites for tire tread application

Styrene butadiene rubber-organoclay nanocomposites were prepared with Cloisite 15A via melt intercalation. X-ray diffraction and transmission electron microscopy indicated that the nanostructures are partially exfoliated and intercalated. The nanocomposites exhibited great improvements in tensile strength and tensile modulus. The incorporation of organoclay gave rise to considerable reduction of tan delta and increase in storage modulus in the rubbery region. It is shown that after 6 phr (parts per hundred rubber) clay loading there is not much increase in the properties. The effect of carbon black (N330) on mechanical properties, dynamic mechanical properties, heat build up, abrasion resistance in the nanocomposites having the optimized clay level (6 phr) was investigated. Optimum results were obtained with the addition of 25 phr carbon black. For comparison with the 6phr nanoclay and 25phr N330 (high abrasion furnace carbon black) filled SBR composites, 40 phr N330 filled SBR composites was used. The 6phr organoclay and 25phr N330 filled SBR nanocomposite showed better properties than 40phr carbon filled SBR compound. These results indicate that 6phr organoclay can be replaced by 15 phr carbon black from the conventional SBR-carbon black based tire tread compounds. The Dynamic mechanical analyzer (DMA) results revealed that the new tire tread compound gives better rolling resistance and comparable wet grip resistance and lower heat build up than that of conventional tread compound.     

Automatic generation control of a multi area hydrothermal system using reinforced learning neural network controller

This paper deals with automatic generation control (AGC) of a three unequal area hydrothermal system. Reheat turbines in thermal areas and electric governor in hydro area are considered. Appropriate generation rate constraints are considered in the areas. Bacterial foraging (BF) technique is used to simultaneously optimize the integral gains (K_Ii) and speed regulation parameter (R_i) keeping frequency bias fixed at frequency response characteristics. The integral controller in this case is termed as BFIC. The performance of a multilayer perception neural network (MLPNN) controller using reinforcement learning is evaluated for the system. In this reinforcement learning, the weights are dynamically adjusted online using backpropagation algorithm with error being the area control error (ACE). The performance of the MLPNN controller is compared with that of BFIC. Also, the performance of MLPNN controller over a wide range of system loading conditions and step load perturbations is compared with BFIC. Investigations clearly reveal the superior performance of MLPNN controller over BFIC. Sensitivity analysis subject to wide changes in system loading, inertia constant (H) and size and location of step load perturbation is carried out to investigate the robustness of the controller with the optimum K_Ii and R_i obtained at nominal condition.     

New technique for the fabrication of conductive polymer/insulating polymer composite films

The electrochemical polymerization of pyrrole on an ITO (indium‐tin oxide)‐coated glass electrode with an insulating film of poly(vinyl alcohol), PVA, produces a flexible composite polymer film with electrical, optical, and electrochemical properties very similar to polypyrrole (PPy). The rate of electrochemical polymerization depends on the diffusion of the electrolyte across the PVA film to the ITO electrode. In particular, hydrophilic solvents easily penetrate into the PVA film. By applying this new process, we demonstrate a unique method of forming electrically conductive patterns in PVA film. It will be possible to develop electrodes for electrical stimulation of the nervous system using a conducting polymer, PPy. By a similar technique we have fabricated poly(3,4‐ethylenedioxythiophene), PEDOT/PVA, composite films and have investigated their electrochemical basic properties. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 174(4): 1–8, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21055     

Fair round robin binary countdown to achieve QoS guarantee and fairness in WLANs

How to guarantee both quality of service (QoS) and fairness in wireless local area networks (WLANs) is a challenging issue. To touch this issue, a fair medium access control (MAC) scheme called fair round robin binary countdown (FRRBC) adopting the eminent concepts of allowance and binary countdown is proposed in this paper. FRRBC can guarantee QoS for both audio and video with the aid of adaptive adjustment on system parameters and some extra rules designed according to delay bounds. Using multiple mapping functions from allowances to fixed-bit binary numbers to indicate different priorities, FRRBC not only provides guaranteed system performance but also achieves good fairness. Finally, we demonstrate that FRRBC can significantly outperform the enhanced distributed channel access (EDCA) (IEEE 802.11 WG in IEEE Standard for Information technology—Telecommunications and information exchange between systems—Local and metropolitan area networks—Specific requirements—Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. Amendment 8: Medium Access Control (MAC) Quality of Service Enhancements, 2005) and the synchronized medium access control (SYN-MAC) (Wu HY et al. in Mobile Netw Appl 11:627–637, 2005) because of its superiority to offer guaranteed QoS for both audio and video, low delay jitter, low blocking ratio, and good fairness. Of course, FRRBC can be illustrated to be a better choice than the enhanced distributed elastic round robin (EDERR) (Ferng HW, Liau HY in IEEE Trans Mobile Comput 8(7):880–894, 2009).     

Fibrous growth of strontium substituted hydroxyapatite and its drug release

The effect of strontium on the crystallization of helical ribbon of hydroxyapatite (HAp) was investigated by single diffusion technique in silica gel matrix at 27 °C and physiological pH. Fibers of HAp were obtained on addition of strontium. The length of the HAp fibers, were found to decrease as the strontium substitution increases. The presence of strontium ion increased the crystallinity as well as crystallite size of HAp. The strontium substituted HAp (Sr-HAp) has similar stoichiometry to that of biological apatite. Sr-HAp was found to have increased surface area (35%) compared to control. Further, strontium substitution leads to an enhancement of in vitro bioactivity. The cumulative in-vitro amoxicillin drug release in phosphate buffer solution (PBS, pH 7.2) showed a prolonged release profile for Sr-HAp.     

Graphene oxide/ferrofluid/cement composites for electromagnetic interference shielding application

This paper deals with the preparation of graphene oxide-ferrofluid-cement nanocomposites to evaluate the electromagnetic interference (EMI) shielding effectiveness (SE) in the 8.2-12.4 GHz frequency range. It has been observed that incorporation of graphene oxide (30 wt%) along with an appropriate amount of ferrofluid in the cement matrix leads to a shielding effectiveness of 46 dB (>99% attenuation).The presence of graphene oxide and ferrofluid in the cement leads to strong polarizations and magnetic losses that consequently result in higher shielding effectiveness compared to pristine cement. The resulting nanocomposites have shown Shore hardness of 54 and dc conductivity of 10.40 S cm( - 1). SEM reveals the homogeneous dispersion of graphene oxide and ferrofluid in the cement matrix.     

Reaction kinetic,magnetic and microwave absorption studies of SrFe<Subscript>11.2</Subscript>Ni <Subscript>0.8</Subscript>O<Subscript>19</Subscript> hexaferrite nanoparticles

Nickel substituted strontium hexaferrite, SrFe_11.2Ni _0.8O₁₉ nanoparticles having super paramagnetic nature were synthesised by co-precipitation of chloride salts using 7.5 M sodium hydroxide solution. The resulting precursors were heat treated (HT) at 900 and 1,200 °C for 4 h in nitrogen atmosphere. During heat treatment, transformation proceeds as a constant rate of nucleation and three dimensional growth with activation energy of 183.724 kJ/mole. The hysteresis loops showed an increase in saturation magnetization from 1.045 to 65.188 emu/g with increasing HT temperatures. The ‘as-synthesised’ particles have size in the range of 20–25 nm with spherical and needle shapes. Further, these spherical and needle shaped nanoparticles tend to change their morphology to hexagonal plates with increase in HT temperatures. The effect of such a systematic morphological transformation of nanoparticles on dielectric (complex permitivity and permeability) and microwave absorption properties were estimated in X band (8.2–12.2 GHz). The maximum reflection loss of the composite powder reaches −24.92 dB at the thickness of 2.2 mm which suits its application in RADAR absorbing materials.