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Islands-Matrix-Dual-phase (I-M-DP) steel is received a great deal attention for better concern with the emissivity, fuel consumption and passengers safety. A number of deformation plasticity issues are yet to be fully understood. Complex deformation stages for various stain is predicted as the natural outfall of the plastic strain localization caused by the ill-assorted deformation between the martensite-island phase and the ferritic-matrix phase. Modeling is carried out both in macro level by bending under tension (BUT) for different roller radius/sheet thickness ratios to acquire strain and stress state deformation and micro scale by Representative Volume Element (RVE) according to element position. It can relate both the 2D, 3D micro and macro scale finite element based BUT model’s result of flow behavior. Systematically strain based severe deformation pattern arises from outfall of plastic strain localization and von Mises stress distribution in island-matrix steels are investigated on the microstructure by finite element method for ill-assorted deformation between phases.

Interstitial-free (IF) steel specimens were coated by hot-dip aluminizing process bearing bath composition as Al-6.9% Si-1.4% Mg and bath temperature at 800 °C. Dipping time varied for 0.5, 1, 3 and 6 min. The objective of the present study is to conduct a systematic investigation to identify and analyse the formation of various phases and compounds in the coating. Studies on aluminizing of steel had indicated the presence of an intermetallic layer adjacent to steel substrate. In this study, the morphological features obtained after hot dipping at 800 °C were investigated. For the application of aluminized steel sheets in industry for manufacture of tubes and pipes, the adherence of the aluminized coating must be ensured. This property of the coating is influenced by the morphological features of the coating. Aluminizing being thought of a possible substitution of galvanizing owing to its promise to evolve lesser volume fraction of intermetallic phases and consequently known to generate a ductile coating. The entire coating consists of an outer Al-Si topcoat and a thin intermetallic layer which composed of an outer θ-FeAl3 and inner η-Fe2Al5 layers. The thickness of intermetallic layers was found to increase with the increase of dipping time in a near parabolic manner.The phases formed on the IF steel substrates were characterized by scanning electron microscopy with EDS, X-ray diffraction, EPMA and EBSD techniques.Interesting findings from XRD include the presence of Al3FeSi2 (τ4) and Al2FeSi (τ3) phases, which normally appear after annealing of aluminised sheet. A distinct elemental Si peak was found in XRD study. Presence of Mg in the form of Mg2Si was also found in XRD and supported by EPMA investigation. Presence of several ternary Al-Fe-Si (τ3, τ4, τ5) and binary FeAl3 and Fe2Al5intermetallic phases were identified by composition profile analysis from SEM based EDS and GDOES and further confirmed by EBSD. Presence of Si humps in the top and intermetallic layer attributed by the presence of Si-bearing phases or elemental pro-eutectic Si in Al-Si alloy were also indicated in SEM-EDS and GDOES study. Variation of surface topographical features of the HDA steel substrates with increasing dipping durations were examined and reported for the first time by using AFM. Formability tests were conducted by bending the samples 180° over a mandrel. None of the specimens showed any tendency of flaking exhibiting excellent bonding of the coating with IF steel substrate.

Electrical conductivity is an essential property for machining of sintered boron carbide especially by wire electrical discharge machining (WEDM) process. Pure boron carbide was spark plasma sintered to full density at 2050 °C. Rietveld refinement on XRD analysis confirmed presence of B13C2 as the major phase in the powder as well as in the sintered samples.Electrical conductivity was found to be ~48 Ω−1m−1. The sintered specimens were successfully machined using WEDM technique. The microstructure of powder, machined and fractured surfaces of the sintered boron carbide were analyzed. At low power of WEDM with pulse current less than 140 A formation of molten, oxidized phases of boron carbide was observed as well as the development of surface cracks were minimum on the machined surface. Thus this work is aiming at achieving better product quality with sintered boron carbide specimens which are machined by WEDM.

The cyclic plastic deformation of an archetypal microstructure dual phase steels has been examined via micromechanics modelling based on representative volume elements technique. The dual phase steel has soft ferrite – matrix with hard martensite – islands, which are distributed in a discrete manner. In the field of automobile industries, the suitable combination of strain hardening, strength and ductility, and their lean combination represent them as an economically desire option for huge multiple lightweight options. In this numerical approach, different microstructures for micromechanical modelling were constructed to detailed examination and analysis for the tensile and cyclic deformation response of dual phase steels. Due to the distinct difference in the stress–strain responses of ferrite and martensite phases, incompatibility of strain between matrix-softer ferrite and island-harder martensite phase arises during tensile straining. The effect of strain partitioning in cyclic plastic deformation response of dual phase steel has been studied in the present investigation. Apart from this, effect of martensite volume fraction on cyclic stress–strain response of dual phase steels, cyclic plastic deformation distribution in individual phases and cyclic deformation inhomogeneity at microstructural level have been systematically investigated. Keywords: Cyclic plastic deformation, Dual phase steel, Martensite volume fraction, Plastic strain localization, Stress triaxiality, Material inhomogeneity

The surface scaling behavior of nanostructured Cu thin films, grown on glass substrates by the pulsed laser deposition technique, as a function of the deposition time has been studied using height–height correlation function analysis from atomic force microscopy (AFM) images. The scaling exponents α, β, 1/z and γ of the films were determined from AFM images. The local roughness exponent, α, was found to be ∼0.86 in the early stage of growth of Cu films deposited for 10 minutes while it increased to 0.95 with a longer time of deposition of 20 minutes and beyond this, it was nearly constant. Interface width w (rms roughness) scales with depositing time (t) as ∼ tβ, with the value of the growth exponent, β, of 1.07 ± 0.11 and lateral correlation length ξ following ξ = t1/z and the value of 1/z = 0.70 ± 0.10. These exponent values convey that the growth dynamics of PLD Cu films can be best described by a combination of local and non-local models under a shadowing mechanism and under highly sticking substrate conditions. From the scaling exponents and power spectral density function, it is concluded that the films follow a mound like growth mechanism which becomes prominent at longer deposition times. All the Cu films exhibited SPR properties where the SPR peak shifts towards red with increasing correlation length (ξ) whereas bandwidth increases initially with ξ and thereafter decreases gradually with ξ.

Growth dynamics of thin films expressed by scaling theory is a useful tool to quantify the statistical properties of the surface morphology of the thin films. To date, the growth mechanism for 2D van der Waals materials has been rarely investigated. In this work, an experimental investigation was carried out to identify the scaling behavior as well as the growth mechanism of 2D MoS2 thin films, grown on glass substrates by pulsed laser deposition for different deposition time durations, using atomic force microscopy images. The growth of MoS2 films evolved from layer-by-layer to layer plus island with the increase in deposition time from 20 s to 15 min. The film surface exhibited anisotropic growth dynamics in the vertical and lateral directions where RMS roughness varied with deposition time as w ∼ tβ with the growth exponent β = 0.85 ± 0.11, while the lateral correlation length ξ was ξ = t1/z with 1/z = 0.49 ± 0.09. The films showed a local roughness exponent αloc = 0.89 ± 0.01, global roughness exponent α = 1.72 ± 0.14 and spectral roughness exponent αs = 0.85 ± 0.03, suggesting that the growth of MoS2 thin films followed intrinsic anomalous scaling behavior (αs < 1, αloc = αs ≠ α). Shadowing owing to conical incoming particle flux distribution towards the substrate during deposition has been attributed to the anomalous growth mode. The optical properties of the films, extracted from ellipsometric analysis, were also correlated with RMS roughness and cluster size variation which unveiled the important role played by surface roughness and film density.

Deformation band localization modes, uniform tensile strength, and uniform elongation of Ferrite-Martensite Dual-Phase (DP) steels are analyzed by finite element (FE) study. Treating the microstructure inhomogeneity as the sole cause of imperfection, failure initiation is predicted as the natural fallout of plastic instability caused by load drop because of localized plastic strain in the Representative Volume Element (RVE) during straining. Strain partitioning between two phases (ferrite matrix and martensite island) are investigated on RVEs, and it reveals that the increase of martensite yield stress decreases the plastic deformation and increases the stress state in martensite. Whereas, a decrease in martensite island volume fraction (Vm) results in the reduction of plastic deformation and stress state in the island. Studies are then carried out to investigate the effects of the ferrite-martensite flow properties and martensite volume fraction on the macroscopic tensile deformation behavior and band localization of DP steels. Micromechanical based FE simulation results emphasize that an increase in initial yield strength and volume fraction of martensite increases the ultimate tensile stress (UTS) with the decrease in uniform elongation. Similarly, as the hardening rate of ferrite increases, it increases the ultimate tensile stress (UTS) and uniform elongation. Additionally, deformation band localization modes alter from inclined to perpendicular to the loading axis with an increase in martensite volume fraction and initial yield strength of martensite. The knowledge of this work can be used to design DP steels with desired mechanical properties.

The present work focuses on the effect of He pressure (vacuum, 10−2–5 mbar) on structural and optical properties of amorphous silicon carbide (a-SiC) thin films, deposited by pulsed laser deposition (PLD) technique onto fused silica. A stoichiometric change occurs in PLD a-SiC film, with increasing He deposition pressure, transforming a near stoichiometric SiC material to C-rich SiC films till 1 mbar of He pressure followed by drastic decrease in carbon (C) content at 5 mbar. The optical band gap of the films estimated using Tauc plot from UV–Vis–NIR transmittance spectra showed initial increase from 2.09 to 2.61 eV with increasing He pressure from 10−6 to 1 mbar, then decrease to 2.11 eV at 5 mbar. A broad band photoluminescence (PL) peak featured in each of the a-SiC films at room temperature. The PL spectra exhibited blue shift in peak energy from 1.8 to 2.2 eV with increase in atomic percentage of C from 49.4 to 62.4%. The origin of the PL exhibited in these films is clearly due to band tail emissions from amorphous SiC structures which has been explained by the observed variation of PL intensity and corresponding FWHM with band gap as well as Urbach energy.

In this paper, the effect of oxygen content on the linear and nonlinear optical properties of the nanostructured SiO x thin films on fused silica is reported. The films were fabricated by Pulsed Laser Deposition technique at a substrate temperature of 400 °C in presence of O 2 pressure, ranging from 10 −4 to 0.5 mbar. X-Ray Diffraction spectra confirmed the formation of polycrystalline Si. Energy Dispersive X-Ray spectra showed the increase in oxygen content with increasing O 2 pressure. Linear absorption coefficients and refractive index were estimated from UV–Vis–NIR transmission spectra. Static refractive index of the films was found to vary from 3.57 to 1.57, with the increase in O 2 pressure. The open Z -scan spectrum of the thin films, using He-Ne laser, exhibited strong reverse saturation absorption and the non linear absorption coefficient measured from it was observed to be decreasing from 21.4 to 2.0 cm/W, with increase in the O 2 pressure. The closed aperture Z -scan of SiO x films depicted self-focusing property and the nonlinear refraction coefficient found to be decreasing from 44.2 × 10 −5 to1.9 × 10 −5 cm 2 /W, with increasing O 2 pressure. The significantly large nonlinear third order susceptibility of the order of 10 −1 –10 −3 esu was observed in these films. The SiO x films except the one containing maximum oxygen content exhibited optical limiting, where limiting threshold increases with increasing transparency which in turn is modulated by oxygen content.

In this work, Pure boron carbide (B 4 C) was consolidated using spark plasma sintering (SPS) at 2050 °C with a dwell of 10 min under 50 MPa uniaxial pressure in Argon atmosphere. The sintered specimen was >99% dense and offered characteristic Vickers hardness and fracture toughness of 31.4 GPa and 4.21 MPa-m 0.5 , respectively, at 4.9 N indentation load. The specimen showed satisfactory wire electrical discharge machining (WEDM) performance because of its good electrical conductivity. The design of experiment (DOE) was arranged by L32 orthogonal array (OA) between the machining input parameters namely pulse on-time, pulse off-time, pulse peak current, dielectric fluid pressure and servo feed rate and the output responses like machining speed and surface roughness ( R a ). Regression models were employed to establish the numerical correlation between the machining parameters and output responses. Experimental observations were utilized to formulate the first-order regression models to predict responses of WEDM. The optimized input parameters were 27 μs pulse on time, 48 μs pulse off time, 180 A pulse peak current, 7 kg/cm 2 water pressure and 2200 mm/min servo feed rate for the WEDM performance to produce an optimum machining speed and R a .

Striving for the suppression of greenhouse emissions, the modern power network is facing fundamental changes with the utilization of renewable energies (REs) for the future carbon-free society. The utilization of intermittent renewable-green power needs a better power management system and virtual power plant (VPP) can be a vital candidate that meets this demand. This study investigates a coordinated control grid integrated virtual power plant (VPP) in the presence of Central Receiver Solar Thermal System (CRSTS), Wind Turbine Generator (WTG), and Electric Vehicle (EV). To this end, CRSTS employed with thermal storage acts as a dispatchable renewable generating unit and coordinated control of the system units are achieved using the available control strategy on interconnected microgrids in the modified form, employing communication time delay. The proposed control strategy employs the proportional-integral (PI) and PI-derivative (PID) controller. Coordinated power control with real-time communication delay in grid integrated VPP in presence of CRSTS, WTG, and EV is a novel approach. Genetic algorithm (GA), Particle Swarm Optimization (PSO), Slap Swarm Algorithm (SSA), and recent Butterfly Optimization Algorithm (BOA) are used for tuning the necessary control parameters. The results establish the superiority of the BOA over SSA and PSO in suppressing system frequency deviations and tie line power deviation. The analysis of the dynamic response reveals that the consideration of the communication delay in the system expressively impedes the stable operation of the power system.

The paper investigates some similarity measures in interval bipolar neutrosophic environment for multi-attribute decision making problems. At first, we define Hamming and Euclidean distances measures between interval bipolar neutrosophic sets and establish their basic properties. We also propose two similarity measures based on the Hamming and Euclidean distance functions. Using maximum and minimum operators, we define new similarity measures and prove their basic properties. Using the proposed similarity measures, we propose a novel multi attribute decision making strategy in interval bipolar neutrosophic set environment. Lastly, we solve an illustrative example of multi attribute decision making and present comparison analysis to show the feasibility, applicability and effectiveness of the proposed strategy.

The bipolar neutrosophic set is an important extension of the bipolar fuzzy set. The bipolar neutrosophic set is a hybridization of the bipolar fuzzy set and neutrosophic set. Every element of a bipolar neutrosophic set consists of three independent positive membership functions and three independent negative membership functions. In this paper, we develop cross entropy measures of bipolar neutrosophic sets and prove their basic properties. We also define cross entropy measures of interval bipolar neutrosophic sets and prove their basic properties. Thereafter, we develop two novel multi-attribute decision-making strategies based on the proposed cross entropy measures. In the decision-making framework, we calculate the weighted cross entropy measures between each alternative and the ideal alternative to rank the alternatives and choose the best one. We solve two illustrative examples of multi-attribute decision-making problems and compare the obtained result with the results of other existing strategies to show the applicability and effectiveness of the developed strategies. At the end, the main conclusion and future scope of research are summarized.

The paper proposes TOPSIS method for solving multi-objective multi-level programming problem (MO-MLPP) with fuzzy parameters via fuzzy goal programming (FGP). At first, - cut method is used to transform the fuzzily described MO-MLPP into deterministic MO-MLPP. Then, for specific , we construct the membership functions of distance functions from positive ideal solution (PIS) and negative ideal solution (NIS) of all level decision makers (DMs). Thereafter, FGP based multi-objective decision model is established for each level DM for obtaining individual optimal solution. A possible relaxation on decisions for all DMs is taken into account for satisfactory solution. Subsequently, two FGP models are developed and compromise optimal solutions are found by minimizing the sum of negative deviational variables. To recognize the better compromise optimal solution, the concept of distance functions is utilized. Finally, a novel algorithm for MO-MLPP involving fuzzy parameters is provided and an illustrative example is solved to verify the proposed procedure.

At an uncontrolled median opening, the limited priority situation and the high degree of heterogeneity in traffic stream make the merging manoeuvre of U-turning vehicles very much complex. This study is an attempt to understand this merging manoeuvre. The different types of merging manoeuvres have been identified in the field and accordingly classified into different categories. Depending upon the number of vehicles that can merge all together into the opposing through traffic by accepting a single gap, the merging has been classified into two types: single entry merging and multiple entry merging. On the other hand, based on the situation of priority of movement, the merging process is divided into another two categories: ideal merging and forced merging. More explicitly, the ideal merging is split into free merging and Swift Merging (SM). In addition, the forced entry merging is categorized into Gradual Merging (GM) and Aggressive Merging (AM). Time distance diagrams for different types of merging are presented for their better understanding. Field data collected at seven median openings located on various 6-lane divided urban roads are used to analyse different types of merging in a mixed traffic situation. All vehicles plying on the road are divided into 5 categories such as car, motorized two-wheeler (2-W), motorized three-wheeler (3-W), Sports Utility Vehicle (SUV), and Light Commercial Vehicle (LCV) and the merging behaviour of these categories of vehicles have been studied. The effect of influencing parameters like opposing traffic volume and delay on merging are investigated. Mathematical relations are developed between Merging Time (MT) of a vehicle type and the opposing traffic volume. To address the effect of Service Delay (SD) on the MT of a vehicle, models are proposed between SD and MT for all the five categories of vehicles. The two types of merging; gradual and swift are prominently observed in field. The time required by different categories of vehicles for these two merging at various traffic volume levels are determined. Finally, two-tailed t-test is conducted to see if the MT for the two different types of merging is statistically different. First published online 26 October 2016

This paper proposes hybrid vector similarity measures under single valued refined neutrosophic sets and proves some of its basic properties. The proposed similarity measure is then applied for solving multiple attribute decision making problems. Lastly, a numerical example of medical diagnosis is given on the basis of the proposed hybrid similarity measures and the results are compared with the results of other existing methods to validate the applicability, simplicity and effectiveness of the proposed method.

This paper proposes a new iso-parametric tool path generation scheme for trimmed parametric surface based on two discrete parameterization techniques, namely, the Partial Differential Equation method and the newly developed "Boundary Interpolation method". The efficiency of the scheme is measured in terms of path length and computational time for machining some typical surfaces. The side-steps and forward-steps have been formulated to suit the discrete nature of the surface representation. Conventionally the forward-step is calculated by approximating the cutting curve with osculating circle. Due to this approximation there is a possibility that the tolerance can go beyond given limit. In this paper an improved tolerance constraint method has been presented to keep the tolerance in forward-step under given value by considering the true profile of the cutting curve. Case studies show that the method presented here significantly improves the path profile by maintaining the tolerance limit.

Seed quality and health status of 11 vegetable crop seeds of viz. Cabbage ( Brassica oleraceae var. capitata ), Indian cabbage ( Brassica oleraceae var. indica), Indian spinach ( Basella alba ), Spinach ( Beta vulgaris var. bengalensis ), Red amaranth ( Amaranthus tricolor ), Bitter gourd ( Momordic acharantia ), Bottle gourd ( Lagenaria siceraria ), Sweet gourd ( Cucurbita moschata ), Carrot ( Daucuscarrota var . sativa ), Radish ( Raphanus sativus ), and Turnip ( Brassica rapa ) collected from the greater Mymensingh region of Bangladesh were tested. The germination percentage of seeds of the collected samples ranged from 11 to 100. The highest germination was recorded in indian cabbage (100%) followed by carrot (92%) and radish (90%), while the lowest was recorded in indian spinach seeds (11%). Altogether 10 fungi were found associated with the seeds which were Alternaria spp., Aspergillus flavus, Aspergillus niger, Botrytis cinerea , Chaetomium funicola, Curvularia spp., Fusarium spp., Penicillium spp., Phoma spp. and Rhizopus spp.. The highest total seed-borne fungal infection was found in bottle gourd (155%) followed by sweet gourd (145%). The lowest infection was found in turnip seeds (6%). The maximum number of dead seeds was found in indian spinach (89%) and no dead seed was found in indian cabbage. Among the vegetables seed samples, seedling vigour ranged from 59 to 3083, where the highest seedling vigour was observed in sweet gourd (3083) and the lowest was in indian spinach (59). DOI: http://dx.doi.org/10.3126/ijasbt.v2i1.9926 Int J Appl Sci Biotechnol, Vol. 2(1): 103-108

In CAD/CAM integrated environment, parametrically defined free-form surfaces may require to be truncated to suit the profile of an object to be machined. In such a case the truncated surface needs to be parameterized anew according to the boundaries. Bilinear Coons parameterization is a well known algebraic method which can be used for generating boundary-fitted iso-parametric curves depending on the boundary information. In this paper an iso-parametric tool path generation scheme has been presented based on Coons parameterization technique for free-form surface. The scheme has been tested on some typical surfaces. Limitations in application of this scheme have also been discussed in this paper.

The objective of the paper is to present neutrosophic soft multi attribute group decision making based on grey relational analysis involving multiple decision makers. The concept of neutrosophic soft sets is derived from the hybridization of the concepts of neutrosophic set and soft set. In the decision making process, the decision makers offer the rating of alternatives with respect to the parameters in terms of single valued neutrosophic set. We utilize AND operator of neutrosophic soft sets in order to aggregate the individual decision maker’s opinion into a common opinion based on choice parameters of the evaluator. Then, information entropy method is employed in order to attain the weights of the choice parameters. We determine the order of the alternatives and identify the most suitable alternative based on grey relational analysis. Finally, in order to show the effectiveness of the proposed approach, a numerical example is solved

This paper presents fuzzy goal programming approach to quadratic bi-level programming problem. In the model formulation of the problem, we construct the quadratic membership functions by determining individual best solutions of the quadratic objective functions subject to the system constraints. The quadratic membership functions are then transformed into equivalent linear membership functions by first order Taylor series approximation at the individual best solution point. Since the objectives of upper and lower level decision makers are potentially conflicting in nature, a possible relaxation of each level decisions are considered by providing preference bounds on the decision variables for avoiding decision deadlock. Then fuzzy goal programming approach is used for achieving highest degree of each of the membership goals by minimizing deviational variables. Numerical examples are provided in order to demonstrate the efficiency of the proposed approach.

paper deals with priority based fuzzy goal programming approach for solving multi-objective linear fractional programming problem. In the model formulation of the problem, we construct the fractional membership functions by determining the optimal solution of the objective functions subject to the system constraints. The fractional membership functions are then transformed into equivalent linear membership functions at the individual best solution point by first order Taylor series. In the solution process, fuzzy goal programming approach is used to solve problem by minimizing negative deviational variables. Then, sensitivity analysis is performed with the change of priorities of the fuzzy goals. Euclidean distance function is used to identify the appropriate priority structure in the decision-making situation. The efficiency of the proposed approach is illustrated by solving a numerical example.

paper deals with fuzzy goal programming approach to quadratic bilevel multiobjective programming prob lem involving a single decision maker with multiple objectives at the upper level and a single decision maker with multiple objectives at the lower level. The objective functions of each level decision maker are quadratic in nature and the system constraints are linear functions. In the model formulation of the problem, we first determine the individual best solution of the quadratic objective functions subject to the system constraints and construct the quadratic membership functions of the objective functions of both levels. The quadratic membership functions are then transformed into equivalent linear membership functions by first order Taylor series at the individual best solution point. A possible relaxation of each level decision is considered by providing preference bounds on the decision variables for avoiding decision deadlock. Fuzzy goal programming approach is then used to achieve maximum degree of each of the membership goals by minimizing negative deviational variables. To demonstrate the efficiency of the proposed approach, an illustrative numerical example is provided.

This paper presents priority based fuzzy goal programming approach to multi-objective quadratic programming problem. In the proposed approach, we construct the quadratic membership functions by determining the individual best solution of the objective functions subject to the system constraints. The quadratic membership functions are then transformed into equivalent linear membership functions at the individual best solution point by first order Taylor series approximation. Then fuzzy goal programming approach is used for achieving highest degree of each of the membership goals by minimizing negative deviational variables. Then, sensitivity analysis with the variations of the priority structure is performed to identify the most appropriate priority structure in the decision-making context by using distance function. A numerical example is solved in order to show the efficiency of the proposed approach. General Terms Multi-objective quadratic programming.

This paper presents fuzzy goal programming approach for bilevel linear fractional programming problem with a single decision maker at the upper level and a single decision maker at the lower level. Here, each level has single objective function, which are fractional in nature and the system constraints are linear functions. In the proposed approach, we first construct fractional membership functions by determining individual best solution of the objective functions subject to the system constraints. The fractional membership functions are then transformed into equivalent linear membership functions by first order Taylor polynomial series. Since the objectives of both level decision makers are potentially conflicting in nature, a possible relaxation of both level decisions is considered for avoiding decision deadlock. Then, the fuzzy goal programming approach is used for achieving highest degree of each of the membership goals to the maximum possible by minimizing the negative deviational variables. To demonstrate the efficiency of the proposed approach, an illustrative numerical example is solved and Euclidean distance function is used to obtain compromise optimal solution. General Terms Bi-level programming.

In this research work, development of a multi-response optimization technique was performed, using Genetic Algorithm (GA) optimization technique in wire electrical discharge machining (WEDM) keeping in mind about the priorities of multiple users. Boron carbide has been selected as work piece for experiment. The effect of five process parameters such as pulse on time (Ton), pulse off time (Toff), peak current (IP), water pressure (WP), servo feed (SF), were investigated on the responses such as machining speed and surface roughness (Ra) in WEDM operation. Further, two responses were modeled empirically through regression analysis. The developed models can be used by the machinists to predict the machining as well as the surface characteristics over a wide range of machining input parameters. The analysis of variance (ANOVA) is also applied to investigate the effect of influential input parameters. Finally, the confirmation experiments were conducted with optimal set of machining parameters and minor deviations have been found.

In this work, a ZrB2 based ceramic composites with 25 wt. % B4C sintered in spark plasma sintering furnace at 2000?C for 10 min under 50 MPa pressure has been machined with Wire electrical discharge machine (WEDM) and can readily be cut to intricate shapes to meet the requirements of industry. The adaptive neuro fuzzy inference systems (ANFIS) has been used to generate mapping relation between input parameters and output responses. ANFIS is a neuro fuzzy technique where the fusion is made between the neural network and the fuzzy inference system. Also the ANFIS models have been tested by a confirmative test and the results shows minimum root mean square error (RMSE) as 0.0416 for kerf width and 0.9605 for machining speed. This verification indicates that ANFIS modeling can be used to forecast the responses.

We investigate the incidence matrix of a finite plane of ordern which admits a (C, L)-transitivityG. The elation groupG affords a generalized Hadamard matrixH=(h ij ) of ordern and an incidence matrix for the plane is completely determined by the matrixR(H)=(R(h ij )), whereR(g) denotes the regular permutation matrix forg∈G. We prove that in the caseR(H) is symmetric thatG is an elementary abelian 2-group or elseG is a nonabelian group andn is a square. Results are obtained in the abelian case linking the roots of the incidence matrixR(H) to the roots of the complex matrix χ(H), χ a nontrivial character ofG.

Efficacy of Bion (benzothiodiazole), Amistar (azoxystrobin) and Tilt (propiconazole) was evaluated for controlling Brown spot and Narrow brown spot of rice cv. BR11 (Mukta). Bion, Amistar and Tilt @ 50 mg/L, 1 ml/L and 1 ml/L, respectively were sprayed at tillering and ear initiation stages that resulted in marked reduction of Brown spot and Narrow brown spot. Bion, Amistar and Tilt significantly increased number of grains/ear and number of healthy grains/ear by reducing number of diseased grains/ear. Bion, Amistar and Tilt resulted in 25.87, 32.17 and 26.76% higher grain yield, respectively over the untreated control when sprayed at tillering stage. DOI: http://dx.doi.org/10.3329/jbau.v9i2.10986 J. Bangladesh Agril. Univ. 9(2): 201–204, 2011

The objective of this paper is to present a technique for order preference by similarity to ideal solu- tion (TOPSIS) algorithm to linear fractional bi-level multi- objective decision-making problem. TOPSIS is used to yield most appropriate alternative from a finite set of alternatives based upon simultaneous shortest distance from positive ideal solution (PIS) and furthest distance from negative ideal solution (NIS). In the proposed approach, first, the PIS and NIS for both levels are deter- mined and the membership functions of distance functions from PIS and NIS of both levels are formulated. Lineari- zation technique is used in order to transform the non- linear membership functions into equivalent linear mem- bership functions and then normalize them. A possible relaxation on decision for both levels is considered for avoiding decision deadlock. Then fuzzy goal programming models are developed to achieve compromise solution of the problem by minimizing the negative deviational vari- ables. Distance function is used to identify the optimal compromise solution. The paper presents a hybrid model of TOPSIS and fuzzy goal programming. An illustrative numerical example is solved to clarify the proposed approach. Finally, to demonstrate the efficiency of the proposed approach, the obtained solution is compared with the solution derived from existing methods in the literature.