a. kumar

This research aims to study the effect of different tool pin shapes on the mechanical properties of friction stir processed (FSP) surface composites. The focus is on fabricating 6061-T6 Al/SiC composites using cylindrical, triangular, tapered cylinder, square, and hexagonal tool pin geometries. The experiments were conducted on a vertical milling machine with H13 tool steel at a transverse speed of 20 mm/min and a rotational speed of 1000 rpm, with three passes. Dye penetrant tests confirmed the absence of surface defects. Microhardness testing using the Vickers method showed that the square pin geometry achieved the maximum hardness value (120 HV). Surface topography analysis using optical and scanning electron microscopy revealed significant grain refinement and fragmentation of silicon carbide particles. Wear tests using a pin-on-disk tribometer indicated that 6061-T6 aluminum alloy without reinforcement exhibited the highest wear rate, while the square tool pin geometry resulted in the least wear rate due to increased microhardness. The processed Al/SiC composites demonstrated a lower average friction coefficient compared to the base metal.

In this article, we develop an efficient numerical method for one-dimensional time-delayed singularly perturbed parabolic problems. The proposed nu-merical approach comprises an upwind difference scheme with modified graded mesh in the spatial direction and a backward Euler scheme on uni-form mesh in the temporal direction. In order to capture the local behavior of the solutions, stability and error estimations are obtained with respect to the maximum norm. The proposed numerical method converges uniformly with first-order up to logarithm in the spatial variable and also first-order in the temporal variable. Finally, the outcomes of the numerical experiments are included for two test problems to validate the theoretical findings.

In the family of Flexible AC Transmission Systems (FACTS) controllers, the distributed power flow controller (DPFC) can control powerfully all the system's parameters like bus voltages magnitude, transmission angle, and line impedances with high redundancy and a wide range of compensation. In this paper, IEEE-14 bus IEEE-30 bus, and IEEE-118 bus systems are taken for the testing of the proposed approach. The optimal placement of the series and shunt converters of the DPFC is decided by the most critical bus and most critical line associated with that bus respectively. The sizing of the DPFC is decided based on the minimization of active power losses of the systems. The loss function is considered an objective function and the limits of the bus voltages magnitudes, bus voltage angles, thermal limits of the lines, and level of compensation of the DPFC are taken as the system's constraints. To solve complex problems in various fields, meta-heuristic optimizations are more popular. Among the meta-heuristic optimizers, the jellyfish optimizer is one that is based on the behavior of jellyfish in the ocean. The optimization of the objective function with constraints has been solved by time-varying acceleration coefficients (TVAC) particle swarm optimization (PSO), artificial bee colony (ABC), genetic algorithm (GA), and metaheuristic optimizer jellyfish methods. Results show that all the optimization techniques provide solutions with minimum losses. Among these methods, the solution of the jellyfish optimizer has the lowest active power losses, highest convergence rate, less number of iterations, and also takes less computational time.

Future wireless networks will use Universal Filtered Multicarrier (UFMC) as a new waveform modulation technique. The UFMC waveform sensibly considers the sub-band filter specifications such as filter order, and shape to combine the key benefits of the present generation modulation waveforms while averting their disadvantages. Therefore, in UFMC-based systems, it is important to pay attention to how the sub-band filter is made. In this paper, the sub-band filter configuration is adapted according to the sub-band size such that the UFMC symbol generates the minimum level of interference with minimum frequency selectivity. Also, the total interference caused by inter-carrier interference (ICI) and inter-sub-band interference (ISBI) was studied by finding the closed form of its change in the UFMC signal with sub-band size and filter length. From this analysis, we determined the ICI increases and ISBI decreases with filter length.  Therefore, the proposed method optimizes the filter length in terms of sub-band size and interference. By this approach, the filter length is shorter than the conventional method and hence improves the symbol utilization. With the proposed method, the overall signal-to-interference ratio (SIR) improved by 1 to 3 dB.

Disease prediction of a human means predicting the probability of a patient’s disease after examining the combinations of the patient’s symptoms. Monitoring a patient's condition and health information at the initial examination can help doctors to treat a patient's condition effectively. This analysis in the medical industry would lead to a streamlined and expedited treatment of patients. The previous researchers have primarily emphasized machine learning models mainly Support Vector Machine (SVM), K-nearest neighbors (KNN), and RUSboost for the detection of diseases with the symptoms as parameters. However, the data used by the prior researchers for training the model is not transformed and the model is completely dependent on the symptoms, while their accuracy is poor. Nevertheless, there is a need to design a modified model for better accuracy and early prediction of human disease. The proposed model has improved the efficacy and accuracy model, by resolving the issue of the earlier researcher’s models. The proposed model is using the medical dataset from Kaggle and transforms the data by assigning the weights based on their rarity. This dataset is then trained using a combination of machine learning algorithms: Random Forest, Long Short-Term Memory (LSTM), and SVM. Parallel to this, the history of the patient can be analyzed using LSTM Algorithm. SVM is then used to conclude, the possible disease. The proposed model has achieved better accuracy and reliability as compared to state-of-the-art methods. The proposed model is useful to contribute towards development in the automation of the healthcare industries.

Employing FVM, we have investigated numerically the rheological behavior of bifurcation phenomena of blood flow at various Reynolds numbers (Re) and at various values of contraction ratio (h), defined as the ratio of the inlet to narrow sections width of a two-dimensional planner contraction-expansion channel. Blood flow bifurcation through a planar contraction-expansion channel is analogous to the case of regurgitation (i.e., abnormal leakage of blood) in the mitral valve. In this work, we have studied the blood flow bifurcation characteristics including the normalized axial velocity profile, velocity gradient, dimensionless pressure, dimensionless longitudinal pressure gradient, pressure and skin friction coefficients on both the channel walls and analyzed the pressure drop, excess pressure drop for different values of Re. Secondly, blockage in the mitral valve is studied for different values of h. Pressure drops for various values of h are also studied to measure blood pressure. Correlation analyses are presented for normalized vortex length in terms of critical values of Re and h. It is revealed that if Re goes on increasing to 14.4 or more, flow breaks the symmetry at h = 15, and for each , recirculation length increases linearly with the increase in Re but decreases valve flaps that reduce blood flow to the heart muscles.

The congestion problems with processor vacations have confronted with increasing intricacy, and their explicit transient solutions are exceptionally hard to compute. The transient solution is more significant for studying the dynamical behavior of computing systems over a finite period and predominantly utilizes within the state-of-the-art design architect for a real-time I/O system. Motivated from this, we adopt the mathematical concepts, namely continued fractions and generating function, to derive explicit expressions for transient-state probabilities. Transient-state probabilities of the processing delay problem with a single processor which adopts the multiple vacations policy to save power consumption and thermal trip error with discouragement and feedback are obtained in terms of modified Bessel functions using the properties of the confluent hypergeometric function. Due to the inaccessibility of processor, discouragement behaviors balking and reneging of the job requests are prone to exhibit. Routing back for the service feedback for the processed job request is also critical to maintaining the quality of service $(QoS)$. For the glance of the I/O system performance, the expected value of the state of the computing system using stationary queue-size distribution is also derived.

Each and every human have unique fingernails. In the early days, the psychological conditions of the human body were reflected with the help of the growth situation of the surface of nails.  It is possible to diagnose human nails and predict the disease. Predicting the disease at the early stage helps in preventing the disease. In this proposed work, the image of the nail is taken from a microscopic image. The lunula and nail plate are segmented effectively using the image pre-processing techniques. Histograms of oriented gradients and local binary patterns are used to capture the characteristic value. Once after pre-processing various features of the nails are extracted using various machine learning algorithms such as Support Vector Machines, Multiclass Support Vector Machine, Convolution Neural Network along with an Optimization algorithm named Ant Colony Optimization to improve the efficiency of classification.

In the present study we have investigated the dielectric properties such as dielectric constant (ε'), dielectric loss (ε"), real part of electrical modulus (M'), imaginary part of electric modulus (M") and AC electrical conductivity, (σac) in wide range of applied voltage, temperature and frequency for Ni/n-TiO2/p-Si/Al heterojunction. A nanocrystalline TiO2 layer was grown on p-type boron doped silicon in oxygen-controlled environment using optimized KrF excimer laser. Ohmic contact of pure nickel and aluminum metals was made on TiO2 and silicon respectively, with thermal coating system. The characteristics obtained with the help of conductance-voltage and capacitance-voltage measurements also known as impedance/admittance spectroscopy. The studied parameters are found to be very sensitive to frequency, temperature and voltage. The restructuring and reordering of interface state density due to temperature variations and interfacial polarizations due to frequency variations collectively result the observed changes in the and . With an increase in frequency AC conductivity and electrical modulus also increases. The relaxation mechanism can be observed in the complex electrical modulus analysis. The thermally activated conduction process was indicated by the frequency dependent AC conductivity at different temperatures. Using power law, the AC conductivity was analyzed and found to increase with temperature, applied voltage.

Canine leptospirosis is a serious public health concern.

This study aims to investigate the feasibility of conserved first to fifth domains of recombinant Leptospira immunoglobulin like protein B antigen (rLigBCon1-5) as a serodiagnostic marker for detecting canine leptospirosis.

A total of 340 unvaccinated canine serum samples were screened using microscopic agglutination test (MAT) and rLigBCon1-5 based immunoglobulin G (IgG) indirect-enzyme-linked immunosorbent assay (I-ELISA). Further, 60 vaccinated canine sera were screened using MAT and rLigBCon1-5 based latex agglutination test (LAT).

Microscopic agglutination test results revealed seropositivity of 28.6%. The relative sensitivity, specificity, and accuracy of IgG I-ELISA in comparison to MAT were 100%, 96.0%, and 97.2%, respectively. Out of 60 vaccinated sera, 46 sera reacted with MAT alone, and eight sera reacted by both tests, while six sera were non-reactive with both tests. Anti-LigB antibodies were detected in eight canine sera by rLigBCon1-5 based LAT. In five LAT reactive sera, agglutinins of locally circulating Leptospira serovars Grippotyphosa (n=4) and Australis (n=1) were detected. In three LAT reactive sera, agglutinins against Icterohaemorrhagiae (n=3) produced due to natural infection were present.

Immunoglobulin G based indirect ELISA assay (IgG I-ELISA) can be employed as an alternative test instead of MAT. rLigBCon1-5 based LAT detected anti-LigB antibodies in eight vaccinated sera where the vaccine failure occurred partially or totally due to the limited efficacy spectrum of Nobivac® RL and cold chain breakage. This vaccine could not provide cross-protection against locally circulating Leptospira serovars. The recombinant LigBCon1-5 antigen based LAT possesses capability of differentiating infected from vaccinated individuals (DIVA capability) when employed as a pen-side test for detecting canine leptospirosis.

We introduce the notion of uniform number of a graph. The  uniform number of a connected graph $G$ is the least cardinality of a nonempty subset $M$ of the vertex set of $G$ for which the function $f_M: M^crightarrow mathcal{P}(X) - {emptyset}$ defined as $f_M(x) = {D(x, y): y in M}$ is a constant function, where $D(x, y)$ is the detour distance between $x$ and $y$ in $G$ and $mathcal{P}(X)$ is power set of $X = {D(x_i, x_j): x_i neq x_j}.$ We obtain some basic results and compute the newly introduced graph parameter for some specific graphs.

Exergy analysis of a 250 MW power plant is done in this study. Thermal performance analysis using MATLAB calculation tool has been done. Exergy destruction phenomenon and Exergetic efficiency is calculated for various components of 250 MW coal fired subcritical power plant. The calculated overall plant exergy efficiency is evaluated 34.75%. Besides, results also concluded that exergy destruction takes place in the steam generator 490.76 MW (93.07%) followed by the other components. The comparative study of heat loss ratio with respect to varying plant load is performed out of which condenser contribute to have major heat loss ratio. The outcomes of this research study will be beneficial for future researchers.

A high velocity ratio synthetic jet on an arched surface is of great interest for its potential applications in navy, including torpedo. However, in spite of detailed research on synthetic jets over a flat surface in cross-flow, very few observations have been made on synthetic jets over a surface which is shaped like a torpedo. This study experimentally explores a synthetic jet mounted on a torpedo shaped model in quiescent and cross-flow conditions. Initially, the synthetic jet is characterized for two different diaphragm displacements and at four distinct actuation frequencies in the range of 1 Hz – 6 Hz in a quiescent flow environment. Subsequently, in cross flow, similar study is conducted for three cross-flow velocities ranging from 7.2 – 32 cm/s, at a fixed amplitude of diaphragm oscillations. The measurements are carried out using Laser Induced Fluorescence (LIF) and Laser Doppler Velocimetry (LDV) and the qualitative LIF visualizations are corroborated by the quantitative LDV data. These results indicate that the synthetic jet vortex rings can be grouped as stretched vortex rings and distorted tilted vortex rings. The flow structures primarily depend on the velocity ratio, which is function of cross-flow velocity and frequency of actuation. The flow physics in case of a curved torpedo surface is slightly different as compared to the synthetic jet on a flat surface.

Electron beam welding has shown a remarkable job in the space industry for welding of components. It is performed under a vacuum environment that eliminates foreign matter such as hydrogen, oxygen, and other gases. Joining of similar and dissimilar materials is the main advantage of electron beam welding with high depth to width ratio as well as sharp focus at the point where parts are to be welded. EBW reduces the HAZ (heat affected zone), making it one of the most acceptable welding processes. In this study, evaluation of the effect of joining parameters on the mechanical strength and hardness is conducted using Minitab software. The strength of the electron beam weld varies with welding parameters. Therefore, correct and optimized parameter selection imparted the highest welding strength. Some welding parameters directly affect weld strength; those were judiciously selected for our experiments. Therefore, 3x3 arrays were selected for investigation on the microhardness and ultimate tensile strength of Fe49Co2V. Three levels and four factors are chosen for analysis. The input parameters are selected as Accelerating Voltage (KV), Welding Speed (mm/min), Beam Current (mA), and Focus Current (mA). This study reveals the maximum welding strength obtained at High Voltage (55 KV), High Beam current (7 mA), Moderate Speed (20 mm/min), and moderate focus current (2365 mA). Similarly, the microhardness obtained at a High Voltage (55 KV), High beam current (7 mA), high welding speed (30 mm/min) and minimum focus current (2210 mA). This study reveals the maximum welding strength obtained at High Voltage (55KV), High beam current (7mA), moderate speed (20 mm/min) & moderate focus current (2365mA). Similarly, the micro-hardness obtained at a High Voltage (55KV), High beam current (7mA), and the high welding speed (30 mm/min) & minimum focus current (2210mA).

The current experimental study is to investigate the effects of process parameters (cutting speed, feed rate and depth of cut) on performance characteristics (surface roughness, machining force and flank wear) in hard turning of AISI 4340 steel with multilayer CVD (TiN/TiCN/Al2O3) coated carbide insert. Combined effects of cutting parameter (v, f, d) on performance outputs (Ra, Fm and VB) are explored employing the analysis of variance (ANOVA). An L9 Taguchi standard design of experiments procedure was used to develop the regression models for machining responses, within the range of parameters selected. Results show that, feed rate has statistical significance on surface roughness and the machining force is influenced principally by the feed rate and depth of cut whereas , cutting speed is the most significant factor for flank wear followed by cutting speed. The desirability function approach has been used for multi-response optimization. Based on the surface roughness, machining force and flank wear, optimized machining conditions were observed in the region 147 m/min cutting speed and 0.10 mm/rev feed rate and 0.6 mm depth of cut.

Turning of hardened steels using a single point cutting tool has replaced the cylindrical grinding now as itoffers attractive benefits in terms of lower equipment costs, shorter set up time, fewer process setups,higher material removal rate, better surface quality and elimination of cutting fluids compared to cylindricalgrinding. In order to obtain desired surface quality by machining, proper machining parameters selection isessential. This can be achieved by improving quality and productivity in metal cutting industries. Thepresent study is to investigate the effect of machining parameters such as cutting speed, feed and depth ofcut on surface roughness during dry turning of hardened AISI 4340 steel with CVD(TiN+TiCN+Al2O3+ZrCN) multilayer coated carbide inserts. A full factorial design of experiment isselected for experimental planning and the analysis of variance (ANOVA) has been employed to analyzethe significant machining parameters on surface roughness during turning. The results showed that feed(60.85%) is the most influencing parameter followed by cutting speed (24.6%) at 95% confidence level.And the two-level interactions of feed-cutting speed (F*V), depth of cut-feed (D*F) and depth of cutcuttingspeed (D*V) are found the significant effects on surface roughness in this turning process.Moreover, the relationship between the machining parameters and performance measure i.e. surfaceroughness has been modeled using multiple regression analysis.