Levels Of Different Parameters Research Articles

Optimizing neural network algorithms for submerged membrane bioreactor: A comparative study of OVAT and RSM hyperparameter optimization techniques.

Hyperparameter tuning is an important process to maximize the performance of any neural network model. This present study proposed the factorial design of experiment for screening and response surface methodology to optimize the hyperparameter of two artificial neural network algorithms. Feed-forward neural network (FFNN) and radial basis function neural network (RBFNN) are applied to predict the permeate flux of palm oil mill effluent. Permeate pump and transmembrane pressure of the submerge membrane bioreactor system are the input variables. Six hyperparameters of the FFNN model including four numerical factors (neuron numbers, learning rate, momentum, and epoch numbers) and two categorical factors (training and activation function) are used in hyperparameter optimization. RBFNN includes two numerical factors such as a number of neurons and spreads. The conventional method (one-variable-at-a-time) is compared in terms of optimization processing time and the accuracy of the model. The result indicates that the optimal hyperparameters obtained by the proposed approach produce good accuracy with a smaller generalization error. The simulation results show an improvement of more than 65% of training performance, with less repetition and processing time. This proposed methodology can be utilized for any type of neural network application to find the optimum levels of different parameters.

Fixed charge 4-dimensional transportation problem for breakable incompatible items with type-2 fuzzy random parameters under volume constraint

Real-life problems are full of uncertainties combined with impreciseness and randomness. Transportation problems become difficult when its parameters are type-2 fuzzy random type. This paper presents a 4-dimensional fixed charge transportation problem for incompatible and compatible breakable items with type-2 fuzzy random parameters under the availability, demand, conveyance’s weight and volume capacity constraint. The model is developed for usual transportation cost minimization objective, where transportation costs, fixed charges, availabilities, demands, conveyances’ weights and volume capacities are type-2 fuzzy random. A type-2 fuzzy random parameter is converted to type-1 fuzzy random one by critical value-based reduction method and then converted to a random parameter using two different methods-generalized credibility measure and centroid method. The random parameter is converted to crisp parameter using probability chance constraint method for constraints and expectation for objective. A detailed conversion procedure from type-2 fuzzy random to crisp is also presented. The reduced deterministic problem is solved by the Generalized Reduced Gradient method using Lingo 11.0 and numerically illustrated. A real-life example is introduced. Particular models are deduced for non-breakable items or different pairwise incompatible items. The sensitivity analyses against different generalized credibility levels of different parameters are presented for total transportation cost. The numerical results show the efficiency of the proposed critical value reduction-generalized credibility-chance constraint, and expectation method. The importance of uncertainty, multi-path and vehicles’ volume capacity in transportation problems is demonstrated.

Status and Variations of Ecological Parameters of Domestic Sewage Inflow at Niccopark and Vanivihar Wetlands of Bhubaneswar, India

To assess the status of water quality of municipal wastewater and to quantify the sewage flow in two important locations of Bhubaneswar City, Orissa, viz., Vanivihar and Niccopark wetlands, composite samplings at hourly intervals were carried out for 96 hours in every three months during 2003-05. In general, the inflow of wastewater at both the sites was maximum during 9-11 am, and the variations were in line with the probable water use pattern of the surrounding community and time of travel from different sources. However, the variations in rainy season sampling were largely influenced by the rainfall pattern. At Vanivihar, the nutrient load during pre-monsoon, monsoon and post-monsoon season were 11.72, 7.55 and 9.58 mg/l as total inorganic nitrogen and 2.05, 3.46 and 2.67 mg/l as phosphate, while the BOD5 level was 132, 103 and 126 mg/l, respectively. The mean population of total coliforms were 7.6, 5.71 and 5.27 x 105 CFUs/100 ml; faecal coliforms 3.59, 2.69 and 2.73 x 105 CFUs/100 ml; faecal streptococci 2.83, 2.78 and 2.29 x 105 CFUs/100 ml; and Salmonella 0.88, 0.76 and 1.6 x 105 CFUs/100 ml during pre-monsoon, monsoon and post-monsoon samplings, respectively. The corresponding levels of different parameters at Niccopark were 13.86, 8.68 and 11.1 mg/l; 2.58, 3.72 and 4.19 mg/l; 145, 109 and 134 mg/l; 7.87, 6.94 and 4.23 x 105 CFUs/100 ml; 4.35, 3.8 and 2.85 x 105 CFUs/100 ml; 4.02, 2.6 and 2.4 x 105 CFUs/100 ml; 1.1, 0.83 and 1.01 x 105CFUs/100 ml. Record of high concentration of nutrients, organic load and microbial pathogens in two sampling sites throughout the sampling period indicated that water drained into the downstream is heavily contaminated.

Families of Extended Exponentiated Generalized Distributions and Applications of Medical Data Using Burr III Extended Exponentiated Weibull Distribution

In this article, four new families named as Weibull extended exponentiated-X (WEE-X), Lomax extended exponentiated-X (LEE-X), Logistic extended exponentiated-X (LGCEE-X), and Burr III extended exponentiated-X (BIIIEE-X) with their quantile functions are proposed. The expressions for distribution function and density function of BIIIEE-X family are written in terms of linear combinations of the exponentiated densities based to parent model. New models, i.e., Weibul extended exponentiated Weibull (WEEW), Lomax extended exponentiated Weibull (LEEW), Logistic extended exponentiated Weibull (LGCEEW), and Burr III extended exponentiated-Weibull (BIIIEEW) distributions are derived, were plotted for functions of probability density and hazard rate at different levels of parameters. Some mathematical properties of the BIIIEEW model are disclosed. The maximum likelihood method for the BIIIEEW model are described. Numerical applications of the BIIIEEW model to disease of cancer datasets are provided.

Enhancement of strength of blast furnace flue dust – iron oxide – fly ash composite briquette using ANOVA-based mathematical model

ABSTRACT Utilisation of by-products of an integrated steel plant improves productivity with diverse mix of raw materials used for iron making. The strength of a briquette made with Blast furnace flue dust and iron oxide with fly ash as a binder depends upon the briquetting pressure, particle size of fly ash, fly ash quantity, and curing temperature. In this study, the effect of process variables on the strength was investigated with ANOVA. The correlation between the process parameters and the strength was examined experimentally and RSM-based optimisation was performed during the preparation of briquettes. The RSM provided optimisation with a confidence level of 95% using the CCD design. This paper demonstrates the correlation between applied pressure, particle size, fly ash quantity, and curing temperature. The developed mathematical model would help in predicting the variation in the compressive strength with the change in the level of different parameters. This model can be useful for setting the optimum value of the parameters for achieving the target compressive strength.

Physiological Characterization of Tripidium arundinaceum and Sugarcane (Saccharum spp.) Germplasm for Salinity Stress Tolerance at the Formative Stage

A total of sixteen accessions of Tripidium arundinaceum (Retz.) Welker, Voronts. & E.A. Kellogg (previously known as Erianthus arundinaceus (Retz.) Jeswiet) were evaluated for salinity tolerance at the bud germination stage by irrigating with 175 mM salinized Hoagland solution in perlite-sand hydroponics. Six accessions, IND99-907, IND01-1134, IND01-1136, IK76-48, and Bethuadahari, were germinated with healthy roots as compared to other accessions. These six accessions were further evaluated for morphological, physiological, and root anatomical parameters for different levels of salinity stress at the formative phase. Young leaf elongation was ceased after the fourth and twelfth day in Co 97010 and Co 86032, respectively, at 175 mM of salinity stress. The growth of young leaves in Co 97010 and Co 86032 was observed up to 25 mM of salinity stress only, whereas in T. arundinaceum accessions viz., IND99-907 and Bethuadahari, growth was recorded even at 175 mM. Lignification of cell walls, thickening of protoxylems, and vacuolization of cortex regions were observed in Co 97010, Co 86032, Bethuadahari, and IND01-1134 as compared to the normal anatomical structures in IND99-907. The accession IND99-907 recorded the lowest Na/K ratio, followed by IND99-1136 at 175 mM of salinity stress. The accession IND99-907 was identified as a salinity-tolerant genotype and suitable for utilization in the sugarcane crop improvement programmes.

Development of a Zero-Dimensional Model for a Low-Speed Two-Stroke Marine Diesel Engine with Exhaust Gas Bypass and Performance Evaluation

Most large commercial vessels are propelled by low-speed two-stroke diesel engines due to their fuel economy and reliability. With increasing international concern about emissions and the rise in oil prices, improvements in engine efficiency are urgently needed. In the present work, a zero-dimensional model for a low-speed two-stroke diesel engine is developed that considers the exhaust gas bypass and geometry structures for the gas exchange model. The model was applied to a low-speed two-stroke 7G80 ME-C9 marine diesel engine and validated with engine shop test data, which consisted of the main engine performance parameters and cylinder pressure diagrams at different loads. The simulation results were in good agreement with the experimental data. Thus, the model has the ability to predict engine performance with good accuracy. After model validation, the variations in compression ratio, fuel injection timing, exhaust gas bypass valve opening portion, exhaust valve opening timing, and exhaust valve closing timing effects on engine performance were tested. Finally, the influence level of different parameters on engine performance was summarized, which can be used as a reference to determine the reasons for high fuel consumption in some cases. The developed engine performance model is considerable in digital twins for performance simulation, health management, and optimization.

Gas Porosity Defect – What It Means and How to Respond

The foundries are facing problem-related to the selection of the parameter’s value for minimum rejection and maximum productivity. The furan no-bake binders system guaranteed dimensional stability and a comparative good surface finish of the casting. Based on past data in the industry, it is found that gas porosity defect is one of the highest. The phenomenon of the formation of the bubble in the fissures of the mould-metal interface, and later on trapping during the solidification leads to gas porosity. The current research work is focused on the minimization of the defect by the selection of the optimum range of input variables. Based on rigorous literature survey and industrial expert’s opinion, it is found that the parameters like grain fineness number (GFN) of the sand, loss on ignition (LoI) of the used sand, the sand temperature at the mixing time, potential of hydrogen (pH) are important parameters for gas porosity defect in the casting.Design-Expert software and particularly response surface methodology (RSM) and sequential approach using the face-centered central composite design is used for the experiments. The results show that a quadratic model with the removal of some insignificant term is a comparatively best fit for gas porosity defects. After analysis, various favorable levels of different parameters are obtained. The research work is based on realistic problems of the foundries and based on the experimental work. Thus, the provided solution is very much useful for foundries to reduce the rejection, particularly for furan no-bake with furfuryl alcohol as resin and sulphonic acid as catalyst. The research problem addressed in the paper is a genuine problem of the foundries and the sole work is based on experimental evidence.

Performance enhancement through parameter optimization for a rechargeable zinc-air flow battery

Owing to their large specific energy density and eco-friendliness, zinc-air batteries (ZABs) are seen to be potential large-scale rechargeable batteries. In recent years, numerous attempts have been made to develop zinc-air flow batteries (ZAFBs) with the premise that a flowing electrolyte can alleviate the shortcomings of zinc electrodes. Herein, the effects of electrolyte flow rate, current density, initial ZnO concentration, and electrolyte temperature on the performance and efficiency of a ZAFB are systematically explored. In addition, the paper discusses the morphological evolution of a zinc electrode with respect to different levels of parameters as well as gravity. Optimal parameters are determined by employing a combination of orthogonal array (OA) sampling and response surface methodology. Results demonstrate that a two-factor interaction regression model can effectively predict actual results with quite an acceptable accuracy. Applying optimal conditions, the battery obtains 99.27 % charge efficiency, 97.65 % discharge efficiency, 73.52 % overall round-trip efficiency, and charge and discharge overpotentials as low as 0.36 V and 0.09 V, respectively. The optimized ZAFB is able to attain superior performance with enhanced round-trip efficiency, making it appropriate for large-scale development.

Comprehensive Assessment of Laser Tube Bending Process by Response Surface Methodology

The laser beam can be used as a powerful tool for bending tubes and sheets by local heating and buckling mechanism. Herein, the bending of mild steel tubes is investigated by irradiation of the laser beam. To consider the effect of the interaction of process parameters despite previous research, six laser tube bending process parameters in different levels including laser power, scanning speed, laser beam diameter, irradiation length, number of irradiation passes, and irradiation scheme are selected and a set of 92 experimental tests is planned according to the response surface methodology (RSM). The tests have been carried out by using a continuous wave (CW) CO2 laser. The influencing parameters affecting the main bending angle and the lateral bending angle are determined. The effect of main process parameters and their interaction on the main and lateral bending angles are discussed. The axial irradiation scheme (AIS) creates a higher main bending angle compared to the circumferential scanning strategy. The results show that the main bending angle and lateral bending angle increase by increasing the laser power, irradiation length, and the number of irradiation passes and reducing the scanning speed and laser beam diameter. The main and lateral bending angles are determined by a regression equation with about 96% goodness of fitting. The results show that 1100 W laser power, 14.6 mm s−1 scanning speed, 4 mm laser beam diameter, 28.27 mm irradiation length, 1 pass of irradiation, and AIS lead to a simultaneous maximum bending angle of 1.80° and minimum lateral bending angle of 0.152°.

Beneficial effects of ascorbic acid and calcium in fluoride induced changesin some biochemical parameters in testes of Swiss Albino Mice

The present investigation was undertaken to elucidate the effects of sodium fluoride on mice understanding the mechanism of fluoride action on metabolism of testis through sequential biochemical changes in level of different parameters and its reversibility by ascorbic acid or calcium and combined effects of both ascorbic and calcium. The healthy, adult Swiss albino mice (Mus musculus) were divided into two equal groups. Group I (fed on standard diet), Group IIA (NaF 5ppm and 50ppm), Group IIB (withdrawal of treatment), Group II C Recovery was also observed in with simultaneously administration of A.A +Ca respectively. Animals from each group were autopsied by cervical dislocation at each post treatment intervals of 10, 20, and 30 days. The changes in the biochemical parameters were dose and duration dependent. Total protein, acid phosphatase, ascorbic acid DNA and RNA decreased while, alkaline phosphatase, showed an increase in all experimental groups. Whereas after the cessation of the treatment recovery was observed and it was more pronounced with ascorbic acid+ calcium. The experimental findings indicate that both testicular protein and DNA synthesis decreased suggesting that fluoride in some way interfere with the RNA metabolism and consequently interfere with the synthesis of specific testicular enzymes etc.

On Order Selection of Arima Models for Stationary Normal and Non-Normal Data Structures

The study is aimed at identifying the orders of time series models in stationary and non-stationary non-normal data from different distributions; with a view to determining the best Autoregressive/ Moving Average orders from different time series, ARIMA models were considered for different underline distributions of data. The data is generated under normal uniform and exponential distribution using a second-order autoregressive model. Data were generated in two forms, these are, when stationarity is observed and when it is violated. Each case of data simulated is fitted to different models and the values of AIC, BIC, HQIC, and FPE are computed. The effect of different levels of parameters (0.3, 0.6, and -0.3, -0.6) at the sample size of 20, 40, 60, 80, 100, 120, 140, 160, 180, and 200 which we considered to represent moderate and large sample sizes respectively on the simulated data from the stationary normal and non-normal data. We concluded in general that the selections of the order for the models considered in this study are tied more to the underlying distribution of the series in relation to the Stationarity and non-Stationarity of the series as it will lead to the identification of the proper model. Since the selection are almost identical in the stationary and non-stationary from both normal and non-normal data structure but varies with the variation in the distribution of the series. And it was also observed that for the ARIMA models the order stocked to the principle of parsimony i.e. models with lower-order selected at most of the sample sizes considered. The need to develop a methodology for model selection that combines both objective and subjective techniques is strongly recommended.

Electrochemical Dissolution of WC-Co Micro-Tool in Micro-WECM Using an Eco-Friendly Citric Acid Mixed NaNO3 Electrolyte

The present study analyzes the efficient electrochemical dissolution of tungsten carbide–cobalt alloy (WC-Co) micro-tools for micromachining operations with an eco-friendly electrolyte. One of the essential factors in efficient anodic dissolution is the selection of appropriate electrolytes. Sulphuric acid (H2SO4) is extensively used in the electrochemical process to dissolve WC-Co due to its higher dissolution rate and efficiency. But toxicity of H2SO4, even at moderate concentration, poses a significant threat to the operator and the environment. Hence in this investigation, an eco-friendly electrolyte has been proposed which is a combination of sodium nitrate (NaNO3) and a complexing agent citric acid (C6H8O7), that not only gives a higher dissolution rate of WC-Co but also gives similar dissolution efficiency that of H2SO4. A detailed experimentation to optimize the concentration of complexing agent in the eco- friendly electrolyte was carried out through micro wire-electrochemical machining (micro-WECM) and was analyzed using yield parameters, topographical and material surface analysis as well as electrochemical analysis. This eco-friendly electrolyte produces higher dissolution rate and better surface finish in different levels of parameters in comparison to H2SO4. Potentiodynamic polarization test through linear sweep voltammetry (LSV) showed maximum current density for WC-Co alloy in the proposed eco-friendly electrolyte.

Optimization of adhesive wear behaviour of B4C/AZ91D-Mg composites

ABSTRACT This study elaborates about wear analysis of developed B4C/AZ91D-Mg metal matrix composites (MMCs) by a vacuum-based stir casting process having 2, 4 and 6 wt.% of B4C reinforcement in the AZ91D matrix. To illustrate the wear effect and its parameters of B4C/AZ91D-Mg MMCs, a set-up of a pin-on disc is used by employing the orthogonal L27 Taguchi and ANOVA method. For investigation, different loads, sliding speed and distance of 5 N, 10 N and 15 N, 1, 1.5, 2 m/s and 500 m, 750 m and 1000 m, respectively, have been considered. However, the statistical values signify the maximum significant wear resistance parameter and the signal-to-noise ratio measures the influence level of different parameters. Metallographic results conclude the uniform dispersion of B4C in the AZ91D-matrix, as well as the existence of the alpha Mg matrix and beta Mg17Al12 phases in B4C/AZ91D-Mg MMCs. Worn surfaces reveal acute delamination under high load conditions. However, statistical wear results conclude that load has a maximum influence on the wear rate as well as distance and velocity. Then, the results of ANOVA regression demonstrate the optimum correlation between the wear rate and its parameters. Finally, tabulated confirmation proofing and the percentage error results show less than 10% error.

Magnetic field assisted finishing (MFAF) process for internal finishing of alumina ceramic tube

Nowadays, fine surface finish is in great demand for many industrial applications. An MFAF process is discussed in this conference paper to achieve a highly finished internal surface of non-ferromagnetic Alumina ceramic tube. Conventional grinding and polishing techniques cannot be used to finish this material because they cannot achieve high surface precision and produce surface defects like micro cracks. Therefore, MFAF process is an alternative method as it minimizes the surface damage because of flexible finishing conditions. MFAF Process, has flexible abrasive brush which can easily finish complex geometry of the workpiece. The workpiece material is alumina ceramic which is in higher demand as a substrate in electronic device applications. The MFAF process was done on alumina ceramic tube and 3 parameters, each having 2 different levels was selected. The parameters considered in the study are chuck speed (rpm), quantity of Diamond abrasive and iron power, machining time. 4 experiments with different levels of parameters were conducted. After finishing experiment using MINITAB 19 software, optimum parameters were determined. From the results of experiment, it was concluded that quantity of diamond abrasive and iron powder did not have much influence on finishing time compare to the chuck speed (r.p.m).

Synchronous Inference for Multilingual Neural Machine Translation

Multilingual neural machine translation allows a single model to translate between multiple language pairs, which greatly reduces the cost of model training and receives much attention recently. Previous studies mainly focus on training stage optimization and improve positive knowledge transfer among languages with different levels of parameter sharing, but ignore the multilingual knowledge transfer during inference although the translation in one language may help the generation of other languages. This work enhances knowledge sharing among multiple target languages in the inference phase. To achieve this, we propose a synchronous inference method that can simultaneously generate translations in multiple languages. During generation, the model predicts the next word of each language not only based on source sentence and previously predicted segments, but also based on predicted words of other target languages. To maximize the inference stage knowledge sharing, we design a cross-lingual attention module which allows the model to dynamically select the most relevant information from multiple target languages. The synchronous inference model requires multi-way parallel training data which is scarce. We therefore propose to adopt multi-task learning to incorporate large-scale bilingual data. We evaluate our method on three multilingual translation datasets and prove that the proposed method significantly improve the translation quality and the decoding efficiency compared to strong bilingual and multilingual baselines.

Restricted estimation of distributed lag model from a Bayesian point of view

This article addresses the issue of multicollinearity for the distributed lag model via Bayesian approach. We introduce the Bayes Almon ridge estimator under this approach by employing prior information. Specifically, the resulting estimator is a new Bayesian estimator that is the mean of posterior density function for the coefficient of the Almon model. Also, a restricted version of this estimator is proposed by using Lagrange multipliers to optimize the coefficients under the additional exact linear constraints. In mathematical sense, theoretical comparisons are carried out by employing mean squared error utilizing matrix theory. Additionally, we investigate a selection method for the biasing parameter of the new estimators with the help of the mean squared error comparisons. To test the theoretical suggestions, we perform a real-life data analysis as a means of applied mathematics. Moreover, we benefit from Monte Carlo simulation techniques where we use several levels of different parameters. The outcomes of numerical example and simulation study favor the new estimators and, hence we succeed in eliminating the multicollinearity.

Reliability Evaluation of Piston Pump Based on Comprehensive Evaluation Index

Abstract After focusing on the randomness of the degradation process of the piston pump, the randomness lead to the proposal of a method based on the comprehensive evaluation index to select the characteristic parameters of different levels and characteristics. It was aimed to characterize the process of degradation. Initially the sensitive characteristics of the piston pump degradation were screened out, followed by the short-time test with a small sample for reliability assessment performed on the piston pump valve plate. The local characteristic-scale decomposition was employed to decompose the vibrational signal. Features characterizing the degradation of the valve plate were selected on the basis of the comprehensive evaluation index. Further application of the Principal Component Analysis algorithm was used to transform the degraded feature data to reduce dimension and extract the feature quantities. Then these feature quantities were substituted into the Weibull proportional reliability model. It aimed to calculate the reliability of the piston pump under different degradation states. The bizarre results showed that the combination of real-time effective features and reliability models not only fully reflect the operating state of the piston pump but also effectively evaluate the reliability of the piston pump.

KANATÇIKLI DİKDÖRTGEN KESİTLİ MİKROKANALDA NANOAKIŞKAN AKIŞININ SAYISAL İNCELENMESİ

A numerical study and parameter optimization was carried out to find the effects of geometric parameters and nanofluid concentration on heat transfer and pressure drop characteristics of a finned microchannel. Six dual rectangular fins with different layouts were placed in a single microchannel having rectangular cross section. The hydraulic diameter of the microchannel was kept constant and the length, width and angle of fin between the horizontal axes were determined as parameters. The water was selected as base fluid and the effect of volumetric concentration of nanofluids (Al2O3 (0% to 0.4%)) on fluid flow and heat transfer were investigated. Volumetric concentration of nanofluids and fin geometry was optimized with Response Surface Optimization method for the levels of different parameters and Computational Fluid Dynamics (CFD) analyses (ANSYS Fluent 18) was performed at different flow rates. CFD results calculated for the optimum finned microchannel were compared to those of the straight (finless) microchannel. As a result of the study, nanofluid concentration increment and fins improved the heat transfer and increased the pressure drop.

Accommodating the Heterogeneity in Traveller’s Responsiveness in Safe Route Choice Experiment – Study from India

Developing countries like India lacks research works to examine how the heterogeneity in responsiveness affect the outcome of a stated choice experiment. This study is an attempt to observe the effects of variation in the responsiveness of a person to different levels of parameters in the selection of a safer route in a country like India. This paper applies a Mixed Logit (ML) model to analyze the safer route choices done by the two-wheeler road users. This model is extended to account for the heterogeneity and explain its impact on the willingness to pay (WTP) for accident reduction. The empirical study shows that if the heterogeneity across individuals are not accounted adequately it leads to a statistically inferior data fit and also to inappropriate evaluations. The calculated WTP values suggest that these values are sensitive to preference heterogeneity and are underestimated if an assumption of preference homogeneity is made.