Spatio-temporal variation and relationship between agricultural efficiency and irrigation intensity in a semi-arid region of India

A surging population in Karnataka State,a semi-arid region in India,poses a threat to both food security and livelihood sustainability,necessitating a concentrated effort to bolster agricultural efficiency and achieve United Naton’s Sustainable Development Goal 2(zero hunger).Therefore,in order to address the pressing issue of food scarcity in Karnataka,this study meticulously examined the spatio-temporal variation of agricultural efficiency and irrigation intensity in Karnataka,uncovering its significant dependence of agricultural efficiency on irrigation intensity.Specifically,this study used a one-way analysis of variance(ANOVA)to ascertain significant differences in the means of agricultural efficiency and irrigation intensity during 2004-2005 and 2018-2019.This study showed that the maximum improvement in agricultural efficiency index was recorded in Belgaum(40.24),Gulbarga(24.77),and Yadgir districts(22.92)between 2004-2005 and 2018-2019,which indicated the progressing trend and better scope for agriculture extension.On the contrary,some districts expressed threat(a decline of above 20.00 of agricultural efficiency index)and needed special care for the improvement of agricultural efficiency in four northern districts(Bagalkot,Bidar,Raichur,and Bijapur),three southern districts(Chitradurga,Chikballapur and Hassan),and two southern districts(Koppal and Gadag)in Karnataka.During 2004-2005,irrigation intensity varied from 3.19%to 56.39%,with the lowest irrigation intensity in Kodagu District and the highest irrigation intensity in Shimoga District.During 2018-2019,irrigation intensity changed from 0.77%to 72.77%,with the lowest irrigation intensity in Kodagu District and the highest in Dakshin Kannad District.Moreover,the research scrutinized the complex relationship between agricultural efficiency and irrigation intensity,with the correlation coefficient increased from 0.162 during 2004-2005 to 0.255 during 2018-2019.It implies that in both periods,a low positive correlation existed between these two variables.Over time,several factors(high-yield seeds and chemical fertilizers)other than irrigation intensity gradually became essential for agricultural efficiency.This research offers a wealth of valuable insights for regional planners and policy-makers contending with comparable challenges in various regions of India and other developing countries.

Regression analysis of major parameters affecting the intensity of coal and gas outbursts in laboratory

Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coal and gas outbursts is significant in the evaluation of the intensity of the outburst. In this paper, we discuss the correlation between these major factors and the intensity of the outburst using Analysis of Variance(ANOVA) and Contingency Table Analysis(CTA). Regression analysis is used to evaluate the impact of these major factors on the intensity of outbursts based on physical experiments. Based on the evaluation, two simple models in terms of multiple linear and nonlinear regression were constructed for the prediction of the intensity of the outburst. The results show that the gas pressure and initial moisture in the coal mass could be the most significant factors compared to the weakest factor-porosity. The P values from Fisher's exact test in CTA are: moisture(0.019), geostress(0.290), porosity(0.650), and gas pressure(0.031). P values from ANOVA are moisture(0.094), geostress(0.077), porosity(0.420), and gas pressure(0.051). Furthermore, the multiple nonlinear regression model(RMSE: 3.870) is more accurate than the linear regression model(RMSE: 4.091).

Optimizing SUS 304 wire drawing process by grey relational analysis utilizing Taguchi method

In the stainless steel 304 （SUS 304） wire drawing process, optimizing the die life and wire tensile strength, which are the larger-the-better quality characteristics （QCH） types, is of main interest. Three control factors, involving reduction ratio, lubricant temperature, and drawing speed, were investigated utilizing L9（34） orthogonal array （OA）. The grey relational analysis was conducted for the normalized signal-to-noise （S/N） ratios. The ordinal value of the grey grade was then used to decide optimal factor levels. The anticipated improvements in die life and wire tensile strength were estimated 25.31 h and 22.50 kg/mm2, respectively. To decide the significant factor which had effect on each QCH and predict the average value of each QCH, analysis of variance （ANOVA） was performed for S/N ratio and QCH. Confirmation experiments were then conducted, where a good overlap was noticed between the predicted and confirnation intervals for each QCH. The Hotelling T2 and the sample generalized variance control charts were finally utilized in controlling and monitoring future production. In conclusion, the grey relational analysis utilizing Taguchi method is an effective approach for optimizing the die life and wire tensile strength for SUS wire drawing process. 2008 University of Science and Technology Beijing. All rights reserved.

Using Contrasts in One-Way Analysis of Variance with Control Groups and an Application

In this study, it was shown that, same comparisons can be made by using contrast coefficients instead of Dunnett＇s test in the experiments with control groups. It was also shown that, in situations with an ordinal scale and equal spacing quantitative grouping, a trend investigation could be done by contrast coefficients. For this purpose, a small part of the data from a TUBITAK project in the Soil Science Department, Agriculture Faculty, Kahramanmaras Sutcu Imam University, was used with permission. The soils were absorbed to natural zeolite in concentration of 0, 2.5, 5 and 10 mg/kg, and after two years, the available Zinc （Zn） amounts in the soil were analyzed. As a result, in both Dunnett＇s test and contrast methods, the Zn amounts in control and 2.5 mg/kg concentration groups were found similar （P 〉 0.01）; but were different （P 〈 0.01） between control and 5 mg/kg concentration groups, and control and 10 mg/kg concentration groups. Furthermore, when orthogonal polynomial contrast coefficients were investigated, linear effects were found significant （P 〈 0.01） and cubic effects were obtained significant （P 〈 0.05）, but quadratic effect was obtained insignificant （P 〉 0.05）.

Effect of Varieties on Tea Pigment and Chromatic Aberration of Black Tea Infusion

Effects of varieties on the content of tea pigment, L＊, a＊ and b＊ value of chromatic aberration of black tea infusion was studied. The correlation relationship between content of TF, TR, TB and L＊, a＊, b＊ value was extremely significant at P＆lt;0.05. Fresh tea leaves with plucking standard of 1 bud and 2 leaves could man-ufacture black tea with higher content of tea pigment, higher a＊ and b＊ value but lower L＊ value, than those of plucking standard of 1 bud and 3 leaves. But the discrepancy of certain parameter of the two plucking standards changed with vari-eties. Varieties’ quality potential could be concealed by improper plucking standards. Six varieties were divided into four groups on the basis of gross tea polyphenols in fresh tea leaves （GTP）, consumption of tea polyphenols to gross tea polyphenols ratio （CTP/GTP） and gross tea pigment to consumption of tea polyphenols ratio （GP/CTP）. Hybrid performed the very suitability of black tea manufacturing. To en-sure high quality of made black tea, suitable variety should be chosen and reason-able plucking standard also should be taken into consideration.

Protection efficiency assessment and quality of coastal shelterbelt for Dongshan Island at the coastal section scale

The coastal shelter forest in China is under threat of destruction and degradation because of the impact of human activities. Protection efficiency assessment of the coastal shelterbelt is an important component of shelterforest remediation planning and sustainable management. In this study, a protection efficiency index （PEI） model was established using the projection pursuit method to assess the protective quality of the coastal shelter forest at the coastal section scale of Dongshan Island, China. Three criteria were used, including forest stand structure, forest belt structure, and windbreak effect; each criterion further comprised multiple factors. Based on survey data of 31 plots in the coastal shelter forest of Dongshan Island, we calculated PEI values using a projection of a pursuit model. The result showed 64.5 % of the PEIs fell at or below the middle level, which can indicate the status of the coastal shelterbelt is unsatisfactory. To further explore whether the different bays and land use types create significant differences in PEIs and evaluation indices, we used an ANOVA to test the influence of various bays and forms of land use on coastal shelterbelts. The results showed that PEI and most of the indices differed significantly by bay; mean tree height, mean DBH, mean crown width, stand density, vegetation coverage, and wind velocity reduction differed significantly by land use. Therefore, relevant measures for different locations, bays and surrounding land use can be proposed to improve the existing conditions of the coastal shelterbelt. The results of this study provide a theoretical and technical framework for future changes and sustainable management of coastal shelterbelt on Dongshan Island.

Prediction and optimization of process parameter of friction stir welded AA5083-H111 aluminum alloy using response surface methodology

A systematic approach was presented to develop the empirical model for predicting the ultimate tensile strength of AA5083-H111 aluminum alloy which is widely used in ship building industry by incorporating friction stir welding(FSW) process parameters such as tool rotational speed,welding speed,and axial force.FSW was carried out considering three-factor five-level central composite rotatable design with full replications technique.Response surface methodology(RSM) was applied to developing linear regression model for establishing the relationship between the FSW process parameters and ultimate tensile strength.Analysis of variance(ANOVA) technique was used to check the adequacy of the developed model.The FSW process parameters were also optimized using response surface methodology(RSM) to maximize the ultimate tensile strength.The joint welded at a tool rotational speed of 1 000 r/min,a welding speed of 69 mm/min and an axial force of 1.33 t exhibits higher tensile strength compared with other joints.

Optimal Design for an End Face Engagement Worm Gear with Multiple Worm-wheel Meshing

To solve the problem for lacking a special mechanical transmission that could provide multiple outputs with high transmission efficiency and good lubrication in the modem industrial, a novel worm gear, named end face engagement worm gear, with multiple worm-wheel meshing is proposed for the first time. The essential parameters for the worm gear are optimized to enhance lubrication and meshing properties. Moreover, analysis of variance（ANOVA） is applied to determine the optimum levels and to determine the influence of parameters. The ANOVA results show that the novel end face engagement worm gear with multiple worm wheels provides high lubrication（the lubrication angle is more than 89~） and meshing performance（the induce normal curvature is less than 0.0002 mm ＇）. The interaction between center distance and roller slant distance most strongly influences the lubrication angle（contributed 51.6%）, followed by the parameters of center distance（contributed 25.0%）, roller slant distance（contributed 16.4%）, tooth angle of gear, gear ratio, and roller radius. In addition, roller radius most strongly influences the induced normal curvature（contributed 39.4%）, followed by roller slant distance（contributed 15.2%）, tooth angle of the gear（contributed 9.0%）, center distance, and gear ratio. The proposed worm gear helps to enrich the no-backlash high precision worm drive and the optimal design method can provide a useful reference on performance improvement of other worm gear.

Influence of tool material and rotational speed on mechanical properties of friction stir welded AZ31B magnesium alloy

In this investigation,the effect of friction stir welding(FSW)parameters such as tool material rotational speed,and welding speed on the mechanical properties of tensile strength,hardness and impact energy of magnesium alloy AZ31B was studied.The experiments were carried out as per Taguchi parametric design concepts and an L9 orthogonal array was used to study the influence of various combinations of process parameters.Statistical optimization technique,ANOVA,was used to determine the optimum levels and to find the significance of each process parameter.The results indicate that rotational speed(RS)and traverse speed(TS)are the most significant factors,followed by tool material(TM),in deciding the mechanical properties of friction stir processed magnesium alloy.In addition,mathematical models were developed to establish relationship between different process variables and mechanical properties.

An artificial neural network approach for prediction of long-term strength properties of steel fiber reinforced concrete containing fly ash

In this study, an artificial neural network (ANN) model for studying the strength properties of steel fiber reinforced concrete (SFRC) containing fly ash was devised. The mixtures were prepared with 0 wt%, 15 wt%, and 30 wt% of fly ash, at 0 vol.%, 0.5 vol.%, 1.0 vol.% and 1.5 vol.% of fiber, respectively. After being cured under the standard conditions for 7, 28, 90 and 365 d, the specimens of each mixture were tested to determine the corresponding compressive and flexural strengths. The pa- rameters such as the amounts of cement, fly ash replacement, sand, gravel, steel fiber, and the age of samples were selected as input variables, while the compressive and flexural strengths of the concrete were chosen as the output variables. The back propagation learning algorithm with three different variants, namely the Levenberg-Marquardt (LM), scaled conjugate gradient (SCG) and Fletcher-Powell conjugate gradient (CGF) algorithms were used in the network so that the best approach can be found. The results obtained from the model and the experiments were compared, and it was found that the suitable algorithm is the LM algorithm. Furthermore, the analysis of variance (ANOVA) method was used to determine how importantly the experimental parameters affect the strength of these mixtures.

Influence of tool pin profile and rotational speed on the formation of friction stir welding zone in AZ31 magnesium alloy

In this investigation,the effect of friction stir welding(FSW)parameters such as tool pin profiles,rotational speed and welding speed on the mechanical properties of tensile strength,hardness and impact energy of magnesium alloy AZ31 was studied.The experiments were carried out as per Taguchi parametric design concepts and an L9 orthogonal array was used to study the influence of various combinations of process parameters.Statistical optimization technique,ANOVA,was used to determine the optimum levels and to find the significance of each process parameter.The results indicate that rotational speed(RS)and transverse speed(TS)are the most significant factors,followed by tool pin profile(PF),in deciding the mechanical properties of friction stir welded magnesium alloy.In addition,mathematical models were developed to establish relationship between different process variables and mechanical properties.

Strain rate analyses during elliptical vibration cutting of Inconel 718 using finite element analysis,Taguchi method,and ANOVA

The high strain rate in metal cutting significantly affects the mechanical properties of the work piece by altering its properties.This study outlines the material strain rates during elliptical vibration cutting.The finite element analysis,Taguchi method,and analysis of variance(ANOVA)were employed to analyze the effects and contributions of cutting and vibration process parameters(feed rate,rake angle,tangential amplitude,and frequency of vibration)on the variation of strain rates during machining of Inconel 718.Taguchi signal-to-noise analysis on an L18(2^1×3^3)orthogonal array was used to determine the optimum parametric combination for the maximum strain rate,and ANOVA was applied to evaluate the significance of control parameter factors on the strain rate.The results of the finite element analysis under different conditions illustrated that the feed rate and rake angle were negatively related to the strain rate,whereas the tangential amplitude and frequency had a positive response.Furthermore,ANOVA results indicated that the effect of the feed rate,tool rake angle,vibration frequency,and tangential amplitude on the strain rate were all statistically significant,with a reliability level of 95%.Of these,the dominant parameter affecting the strain rate was the feed rate,with a percentage contribution of 40.36%.The estimation of the optimum strain rate and confirmation tests proved that the Taguchi method could successfully optimize the working conditions to obtain the desired maximum strain rate.

Do Satisfaction and Loyalty Have a Linear Relationship？ Effect of the Education Level on Arts Participation

This paper aims to explore the relationship between perceived satisfaction and loyalty of Spanish arts participants. Evidence suggests that customer satisfaction plays a key role in an organization＇s ability to maintain a relationship with its customers. We examined the link between satisfaction and loyalty within a theoretical framework based on an empirical study in which data from more than 14,000 respondents were obtained. This data allowed us to evaluate the arts consumer from an attitudinal and behavioral perspective looking at their interests, satisfaction level, frequency of attendance, and compare it using the participant＇s education level. A descriptive statistical analysis using ANOVA （analysis of variance）, correlation, partial correlation, and multiple regression provided evidence that, in the context of experiencing an arts show, satisfaction does not have any impact on loyalty but education level plays a significant role in people＇s interest and loyalty.

Optimization for aerodynamic performance of double serpentine nozzles with spanwise offsets using Taguchi-based CFD analysis

Serpentine nozzles are widely used in combat aircraft to realize strong stealth characteristics.Based on the layout characteristics within a confined space,a series of double serpentine nozzles with spanwise offsets are established.Using computational fluid dynamics and Taguchi method,the influence mechanisms of the Distribution of Area(DA),Distributions of Centerline for the first and second‘S’sections in the Vertical direction(DCV1 and DCV2),and Distribution of Centerline in the Spanwise direction(DCS)are analyzed.The impact of these factors on the total pressure recovery coefficient can be ranked as DA>DCV2>DCS>DCV1,whereas their impacts on the discharge coefficient and axial thrust coefficient can be ranked as DCV2>DCS>DA>DCV1.Considering the statistical significance of these factors,a nozzle in which DA changes rapidly at the exit and DCV1,DCV2,and DCS change rapidly at the entrance gives the best aerodynamic performance.Compared to the worst configuration,the total pressure recovery coefficient,discharge coefficient,and axial thrust coefficient are improved by 1.6%,3.5%and 3.6%,respectively.DA influences the gas flow acceleration in the entire serpentine channel,resulting in different wall shear stress and friction losses.The various centerline distributions influence the gas flow acceleration effects and form complex wave structures in the constantarea extension section,resulting in different local and friction losses.

Parametric optimization of dry sliding wear loss of copper-MWCNT composites

The wear behavior of multi-walled carbon nano-tubes(MWCNTs)reinforced copper metal matrix composites(MMCs)processed through powder metallurgy(PM)route was focused on and further investigated for varying MWCNT quantity viaexperimental,statistical and artificial neural network(ANN)techniques.Microhardness increases with increment in MWCNTquantity.Wear loss against varying load and sliding distance was analyzed as per L16orthogonal array using a pin-on-disctribometer.Process parameter optimization by Taguchi’s method revealed that wear loss was affected to a greater extent by theintroduction of MWCNT;this wear resistant property of newer composite was further analyzed and confirmed through analysis ofvariance(ANOVA).MWCNT content(76.48%)is the most influencing factor on wear loss followed by applied load(12.18%)andsliding distance(9.91%).ANN model simulations for varying hidden nodes were tried out and the model yielding lower MAE valuewith3-7-1network topology is identified to be reliable.ANN model predictions with R value of99.5%which highly correlated withthe outcomes of ANOVA were successfully employed to investigate individual parameter’s effect on wear loss of Cu?MWCNTMMCs.

Thermal optimization of MHD nanofluid over a wedge by using response surface methodology:Sensitivity analysis

It is well documented that heat transfer is enhanced with addition of nanosized particles in fluid.But,in a mechanical system there are variety of factors influences the heat transfer.Some factors are significant while others are not.In this paper,authors will discuss sensitivity of different input parameters such as Le,Nt and Nb on output responses𝑁Nu_(x)and Sh_(x).To achieve this goal,the problem is modeled using basic conservation laws.The formulated model is a set of PDEs,which are converted to set of non-linear ODEs by using similarity transformation.Then these ODEs are solved numerically by using MATLAB built in package bvp4c and compared the numerical results with existing work and found good results.Sensitivity analysis is performed by employing RSM to determine the relationship between the input parameters such that 0.1≤Le≤1,0.1≤Nt≤1 and 0.1≤Nb≤1 and the output responses(Nu_(x)and Sh_(x)).ANOVA tables are generated by using RSM.By using the ANOVA tables the correlations between input parameters and output response are developed.To check the validity of correlated equations,the residuals are plotted graphically and show best correlations between input parameters and output responses.The high values of R^(2)=98.65 and AdjR^(2)=97.43 for Nu_(x)and R^(2)=97.83 and AdjR^(2)=95.88 for Sh_(x)demonstrates the high validity of ANOVA results to perform sensitivity analysis.Finally,we have conducted a sensitivity analysis of the responses and came to the important results that Nt and Nb is most sensitive to Nusselt number and Sherwood number respectively.

Experimental study and simulation on the creep characteristics of machineharvested seed cotton

In view of the unclear understanding of the basic scientific problems such as the rheological mechanism of seed cotton,especially the lack of research on the creep characteristics of seed cotton,the machine-harvested seed cotton in the Xinjiang region was taken as the research object to find out the compression creep characteristics.The universal material testing machine was used to carry out a one-factor creep test,taking moisture content,feed quality,compression times,and trash content as test factors and instantaneous elastic modulus,hysteretic elastic modulus,viscosity coefficient,and delay time as test indicators.The ANOVA and correlation were analyzed by SPSS,and the creep process of the seed cotton was simulated by ADAMS.Results show that moisture content significantly affects the instantaneous elastic modulus,hysteretic elastic modulus,and viscosity coefficient(p<0.01).In addition,each value of which decreases with the increase in moisture content.Feed quality significantly affects the hysteretic elastic modulus and viscosity coefficient(p<0.05).Moreover,the hysteretic elastic modulus and viscosity coefficient increase with the increase in feed quality.The compression times significantly influence the instantaneous elastic modulus,hysteretic elastic modulus,and viscosity coefficient(p<0.01),each value of which increases with the increase of compression times.Furthermore,the trash content significantly influenced the hysteretic elastic modulus and viscosity coefficient(p<0.05).The absolute error between the simulated and experimental values ek is within−0.011-0.030 mm,and the relative errorφk is less than 7%.The experimental results can provide theoretical and data support for the study of rheological characteristics of machine-harvested seed cotton,the design of seed cotton packing devices,and the molding quality of cotton bale(mold).

Numerical investigation and optimisation of heat transfer performance in a vertical sinter cooling packed bed using Taguchi and ANOVA methods

The Taguchi and analysis of variance (ANOVA) methods were applied to investigate the effects of the structural and operational parameters on the heat transfer performance of a vertical sinter cooling packed bed. The analysed parameters were the gas flow rate, the air inlet temperature, the sinter inlet temperature, the cooling bed diameter and the cooling bed height, all of which contain three levels. The purpose was to improve the heat transfer performance of a vertical sinter cooling bed. A numerical analysis model was established to assess the heat transfer performance with respect to the varying parameters and their different levels. This mathematical model was validated by using data from practical industrial processes. The Taguchi method for the L27 (35) orthogonal design experiment was selected to evaluate the impacts of the design parameters on the heat transfer performance and to acquire the optimum combination of parameters. The analysis of variance was applied to assess the impact weights and the order of significance of the design parameters. The results show that the sinter inlet temperature and cooling bed diameter have great influences and impact the exergy of the wasted heat recovery by 61.65% and 23.31%, respectively. However, the gas flow rate and the air inlet temperature have small effects on the response. Furthermore, the air and sinter inlet temperatures have the most significant impacts on the efficiency of heat transfer by 68.83% and 23.31%, respectively. The optimal parameter combination (A1B1C3D3E3) was obtained, and the optimal results were validated by confirmation tests.

Modeling, analysis, and optimization of dimensional accuracy of FDM-fabricated parts using definitive screening design and deep learning feedforward artificial neural network

Additive manufacturing(AM)technologies such as fused deposition modeling(FDM)rely on the quality of manufactured products and the process capability.Currently,the dimensional accuracy and stability of any AM process is essential for ensuring that customer specifications are satisfied at the highest standard,and variations are controlled without significantly affecting the functioning of processes,machines,and product structures.This study aims to investigate the effects of FDM fabrication conditions on the dimensional accuracy of cylindrical parts.In this study,a new class of experimental design techniques for integrated second-order definitive screening design(DSD)and an artificial neural network(ANN)are proposed for designing experiments to evaluate and predict the effects of six important operating variables.By determining the optimum fabrication conditions to obtain better dimensional accuracies for cylindrical parts,the time consumption and number of complex experiments are reduced considerably in this study.The optimum fabrication conditions generated through a second-order DSD are verified with experimental measurements.The results indicate that the slice thickness,part print direction,and number of perimeters significantly affect the percentage of length difference,whereas the percentage of diameter difference is significantly affected by the raster-to-raster air gap,bead width,number of perimeters,and part print direction.Furthermore,the results demonstrate that a second-order DSD integrated with an ANN is a more attractive and promising methodology for AM applications.