A Global Maximum Error Controller Based Nonlinearity Aware TPWL Method for Reducing Nonlinear Systems

Abstract

Model order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes.     

A comparative study on in vitro behavior of calcium silicate ceramics synthesized from biowaste resources

Calcium silicate ceramics have received significant attention for biomedical applications for their excellent bioactivity and osteoconduction properties. Sol-gel process is extensively used for the fabrication of calcium silicates. In sol-gel process, calcium nitrate tetra hydrate (Ca(NO₃)₂·4H₂O) and tetraethylorthosilicate (TEOS) are used as precursors. However, these precursors are expensive. The objective of this work was to compare in vitro behavior of calcium silicate (CaSiO₃) produced using biowaste such as rice husk ash (RHA) and eggshells (coded; NCS) with CaSiO₃ prepared using TEOS and Ca(NO₃)₂·4H₂O (coded; CCS). Thermal investigation results revealed that the crystallization temperature for NCS is relatively lower (772°C) than for CCS (870°C). Bioactivity was studied in vitro using simulated body fluid (SBF) with respect to mineralization rate of hydroxyapatite. Mineralization of a greater hydroxyapatite was observed on NCS ceramics than CCS ceramics after incubation for 3, 7, 14 days in SBF solution, which was confirmed using X-ray diffractometer, Fourier transform infrared spectroscopy, scanning electron microscopy-energy dispersive spectroscopy. Degradation studies were conducted in Tris-HCl solution and the test results revealed that NCS ceramics has lower dissolution rate than CCS ceramics. The antimicrobial assay has shown that NCS samples exhibit significant zone of inhibition against Escherichia coli and Staphylococcus aureus which confirmed that the CaSiO₃ prepared from RHA and eggshell can prevent bacteria from adhering to the surface. In addition cell culture studies revealed that NCS ceramics possess good cytocompatibility with MG-63 cells and significantly promoted cell proliferation.     

A Novel DUF569 Gene Is a Positive Regulator of the Drought Stress Response in Arabidopsis

In the last two decades, global environmental change has increased abiotic stress on plants and severely affected crops. For example, drought stress is a serious abiotic stress that rapidly and substantially alters the morphological, physiological, and molecular responses of plants. In Arabidopsis, several drought-responsive genes have been identified; however, the underlying molecular mechanism of drought tolerance in plants remains largely unclear. Here, we report that the “domain of unknown function” novel gene DUF569 (AT1G69890) positively regulates drought stress in Arabidopsis. The Arabidopsis loss-of-function mutant atduf569 showed significant sensitivity to drought stress, i.e., severe wilting at the rosette-leaf stage after water was withheld for 3 days. Importantly, the mutant plant did not recover after rewatering, unlike wild-type (WT) plants. In addition, atduf569 plants showed significantly lower abscisic acid accumulation under optimal and drought-stress conditions, as well as significantly higher electrolyte leakage when compared with WT Col-0 plants. Spectrophotometric analyses also indicated a significantly lower accumulation of polyphenols, flavonoids, carotenoids, and chlorophylls in atduf569 mutant plants. Overall, our results suggest that novel DUF569 is a positive regulator of the response to drought in Arabidopsis.     

A spatio‐temporal water quality assessment of the Beas and Sutlej Rivers at the Harike Wetland: A Ramsar site in Punjab,India

Lakes play a vital role in regulating water storage, flow of river water, and ultimately maintaining a balanced ecosystem. Spatial and temporal variations in physicochemical parameters of water in Harike Wetland, a Ramsar site in the northwestern state of Punjab, India, were studied. This study was conducted on a monthly basis from January to December 2015. The water quality was studied at ten locations from sites 1 to 10 upstream, central and downstream from Harike Lake for ten physicochemical parameters, including temperature, pH, electrical conductivity, turbidity, dissolved oxygen concentration biological oxygen demand, nitrate and phosphate concentrations and salinity. The findings of this study revealed that, except for temperature and pH, all parameters exhibited relatively higher values for the Sutlej River, compared with the Beas River, with sampling sites 5 to site 7 exhibiting intermediate results. The mean seasonal temperature variations ranged from 16.9 to 26.6 °C, the pH from 7.7 to 8.2, electrical conductivity from 223 to 303 μS cm^?1 and TDS concentration from 148.7 to 180.4 ppm. Correlation analysis was conducted to assess the relations between the variables. The electrical conductivity exhibited a high positive correlation with salinity and biological oxygen demand, whereas it correlated negatively with the dissolved oxygen concentration. Box and whisker plots were also plotted for the study results to better examine the data distribution.     

Geospatial technology applied to spatiotemporal assessment of Harike Wetland,Punjab

The Harike Wetland situated in Punjab is a Ramsar site and a wetland of national importance. The present study was undertaken to assess the spatiotemporal dynamics of the wetland on the basis of geospatial technology and ground‐based studies. Landsat images for the years 2002 and 2014 were acquired from the United States Geological Survey and classified digitally to generate landuse/land cover maps involving four classes (water, grassland (including water hyacinth), agriculture, built‐up (settlement), barren land). The total area of the Harike Wetland was found to be 8023.68 ha. Water sampling at eleven sites was carried out and evaluated for physicochemical parameters. The water quality at several sampling points was found to be severely degraded. Change detection analysis revealed the submerged area (area under water) and grassland (including water hyacinth) had decreased over the past 12 years, whereas that area under agriculture and built‐up land has increased, indicating a shrinkage in the total wetland area. The present study also indicated that the near‐infrared band is a good indicator of water quality parameters, as indicated by the significant positive correlation between the near‐infrared band and relevant water parameters. Because the wetland is important from both an ecological perspective and economic perspective, regular monitoring is recommended, for which geospatial technology has proven to be very useful.     

Memory effect of locally ordered α-phase in the melting and phase transformation behavior of β-isotactic polypropylene

Structural changes in β-isotactic polypropylene (β-iPP) during the heating were studied by means of differential scanning calorimetry and real-time in situ X-ray diffraction using a synchrotron source. Crystalline phase transformation and the memory effect caused by residual nuclei of α-iPP were observed during the heating of β-iPP. The memory effect observed in β-iPP during heating and crystallization is believed to be due to the existence of locally ordered α-from in the melt. The effect of local α-form order was probed by studying the behavior under heating of samples with a range of thermal histories. Samples were heated above the equilibrium melting temperature of iPP to remove all residual local order and the memory effect associated with this local order. The samples crystallized isothermally at different temperatures exhibited a significantly different melting and phase transformation behavior during heating. β-iPP is found to be an excellent material for the study of polymorphism, phase transformations, and characteristic memory effects in semicrystalline polymers.     

Simplified and efficient calibration of a mechanistic cutting force model for ball-end milling

Accurate evaluation of the empirical coefficients of a mechanistic cutting force model is critical to the reliability of the predicted cutting forces. This paper presents a simplified and efficient method to determine the cutting force coefficients of a ball-end milling model. The unique feature of this new method is that only a single half-slot cut is to be performed to calibrate the empirical force coefficients that are valid over a wide range of cutting conditions. The instantaneous cutting forces are used with the established helical cutting edge profile on the ball-end mill. The half-slot calibration cut enables successive determination of the lumped discrete values of the varying cutting mechanics parameters along the cutter axis whereas the size effect parameters are determined from the known variation of undeformed chip thickness with cutter rotation. The effectiveness of the present method in determining the cutting force coefficients has been demonstrated experimentally with a series of verification test cuts.     

Defect Prediction Using Akaike and Bayesian Information Criterion

Data available in software engineering for many applications contains variability and it is not possible to say which variable helps in the process of the prediction. Most of the work present in software defect prediction is focused on the selection of best prediction techniques. For this purpose, deep learning and ensemble models have shown promising results. In contrast, there are very few researches that deals with cleaning the training data and selection of best parameter values from the data. Sometimes data available for training the models have high variability and this variability may cause a decrease in model accuracy. To deal with this problem we used the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) for selection of the best variables to train the model. A simple ANN model with one input, one output and two hidden layers was used for the training instead of a very deep and complex model. AIC and BIC values are calculated and combination for minimum AIC and BIC values to be selected for the best model. At first, variables were narrowed down to a smaller number using correlation values. Then subsets for all the possible variable combinations were formed. In the end, an artificial neural network (ANN) model was trained for each subset and the best model was selected on the basis of the smallest AIC and BIC value. It was found that combination of only two variables’ ns and entropy are best for software defect prediction as it gives minimum AIC and BIC values. While, nm and npt is the worst combination and gives maximum AIC and BIC values.     

On l∞ and l2 robustness of spatially invariant systems

We consider spatiotemporal systems and study their l_∞ and l₂ robustness properties in the presence of spatiotemporal perturbations. In particular, we consider spatially invariant nominal models and provide necessary and sufficient conditions for system robustness for the cases when the underlying perturbations are linear spatiotemporal varying, and nonlinear spatiotemporal invariant, unstructured or structured. It turns out that these conditions are analogous to the scaled small gain condition (which is equivalent to a spectral radius condition and a linear matrix inequality for the l_∞ and l₂ cases, respectively) derived for standard linear time‐invariant models subject to time‐varying linear and time‐invariant nonlinear perturbations. Copyright © 2009 John Wiley & Sons, Ltd.     

Determination of dairy wastewater treatability by bio-trickling filter packed with lava rocks - case study PEGAH dairy factory

This paper investigates the effectiveness of a biological trickling filter for the treatment of wastewaters produced by a company manufacturing dairy products. First a bio-trickling column with a height of 150 cm was packed with lava rocks from north mountain of Tehran. It operates with the recirculation of liquid through the packing. In order to startup the pilot scale, steady state condition was gained by pumping activated sludge and dairy wastewater for 23 days. Afterwards, dairy wastewater was added to liquid tank for treatment. Hydraulic retention time (HRT) of treatment decreases from 5 days to 1 day then at HRT of 12, 8, 7, 6 and 4 h. Results show that the average chemical oxygen demand (COD) decreased from 2,750 to 98 mg/L at HRT of 7 h and efficiency of TKN removal was more than 70%. The microorganisms developed in the bio-trickling filter were able to efficiently remove COD levels up to 2,750 mg/L, under aerobic conditions at pH values between 6.8 and 7.2 under low temperature condition between 10 and 13 °C.