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In this modem age, the use of biometrics is an important aspect in the lives of people in all areas. Iris recognition is now a trustworthy method of personal recognition due to the outstanding requirements for security and reliable types of identification in biometric systems. It is a main and challenging field of study because of its advantages of high precision and non-contact recognition technology. In automatic identification, iris recognition technology plays a vital role. This paper introduces a new concept of optimal security where the proposed system is trained using Convolutional Neural Networks (CNN) incorporated with softmax classifier. The model is trained on a dataset for iris recognition where only a small number of images were trained for each set and showed an enhancement in the results over earlier methods. It focuses on a systematic approach for iris recognition, even when the images have noise, obstructions and various levels of illuminations. Experiments with standard datasets have shown that the put forward approach can attain high performance than competing with other deep learning-based methods. The efficiency gained from iris recognition based on performance evaluation is accurate, achieving a total of 99%. [ABSTRACT FROM AUTHOR]

Here, the efficiency, pollution attributes of a typical DI Diesel power train working on Diesel fuel, B20, and the combination of B20 with MgO and TiO2 in the aforementioned proportions(B20NA25, B20NA50, B20NA75, and B20NA100), were examined. The experiment was conducted with a Mono-cylinder Diesel engine runs at 1500 rpm speed at steady-state circumstances. Throughout the testing, the engine output, fuel consumption, and exhaust pollutants are noted. Methyl ester of Papaya and Diesel fuel was shown to create much less Smoke, HCand COpollution. However, when equated to diesel fuel, it exhibited a less BTE and a 3.2% higher BSFC. However, when the cylinder's internal temperature increased, so did the NOX emission. [ABSTRACT FROM AUTHOR]

The main ideal of this document is to Analyze and Design of a Multi storey structure applying a Software usually known as STAAD Pro and its cost prediction using a AI technique called Machine Learning. In this we are designing a multi storey building of G+12 which involves load calculations, sesmic load conditions and analysing of building by STAAD pro and also analyzing the building erect for chancing the bending moments, shear forces, deflections and also underpinning details for the structural members of structure(similar as shafts, columns & crossbeams) for developing the provident and sustainable design. For this design process we used Indian standard code books of IS 456-2000, IS 875 (Part 1,2,3,5). AUTOCAD software is used for development of plans and the plan is imported to staad pro and designed. The total height of the building is 39m and the area of the building is around 8000sq.ft consisting of 12 floors. This paper also introduces machine learning (ML) technology to optimize design costs. In our project we used linear regression algorithm. Linear regression relationships are modelled using a linear prediction function that estimates unknown model parameters from data. Data is given in form of datasets that comprises of attributes such as essential building materials and their cost according to the area, so that the future cost is predicted accordingly. The result obtained in trained model and the manual estimation is accurate. In this project we are calculating and comparing the cost of high rise, mid rise and dwarf buildings through machine learning as well as through manual estimation of the building. [ABSTRACT FROM AUTHOR]

Video Surveillance assumes a vital part in the present world. The innovations have been progressed an excessive amount of when man-made brainpower, AI and profound learning pitched into the framework. Utilizing above mixes, unique frameworks are set up which assists with separating different dubious practices in live following of recordings. The greatest unusual thing is human conduct and is undeniably challenging to discover whether it is dubious or ordinary. Profound learning approach is utilized to distinguish dubious or ordinary movement in a scholastic climate, and which sends an alarm message to the comparing authority, if there should arise an occurrence of anticipating a dubious movement. Observing is frequently performed through successive outlines are extricated in video. The whole system is partitioned into two sections. At initial segment, highlights are registered in video outlines and in other part, in view of the got highlights classifier foresee dubious or ordinary. [ABSTRACT FROM AUTHOR]

There are very few automobiles in developing countries because two wheelers have always been the uppermost mode of transport. Motorcycle crashes have been on the rise in the last few years. A number of people who are involved in traffic collisions include motorcyclists who do not wear reflective helmets, since they do not believe they provide sufficient protection. Once the traffic police spot those driving Motorcycles on a whole-or Motorcycles in junctions-without helmets, they also use video from CCTV to take control of the drivers of those vehicles and penal those who are riding without one. However, it can only be achieved through human action and commitment. Again they classifies moving vehicles as motorcycle or nonmotorcycle. for example, when referring to the head component, in the case of a motorcyclists, it is graded as either full face or non-full face. An excellent image analysis of the motorcycle number is then used to extract the characters that were missed by the identification software and/ Finally, the character count of the motorcycle is found, and from the motorcycle is examined using OCR software. The algorithm detects Objects to discover faces from still photos or videos. In their study "Rapid Object Detection using a Boosted Cascade of Simple Characteristics," Viola and Jones presented edge or line detection features, which are used by the technique. A deep learning algorithm called a convolutional neural network may analyse a picture as input and rank its significance. to separate elements/objects in the picture and be able to tell one from the other. Because of its great accuracy, CNNs are utilized for picture categorization and recognition. With the use of a hierarchical model, the CNN creates a network in the form of a funnel that eventually yields a fully connected layer in which all of the neurons are interconnected and the output is processed. [ABSTRACT FROM AUTHOR]

There is a plethora of tools available in the literature for analysis and prediction. Some of them are built on top of JAVA scripts for Matlab, Minitab, SPSS, R, Ky plot, etc., while others are based on C programming. The article makes use of the WEKA programme, which stands for Waikato Environment for Knowledge Analysis. We use atmospheric data such as visibility, wind speed, minimum and maximum temperatures, and local weighted learning (LWL) and regression by discretization (R2D) techniques based on M5P trees. After calculating the RMSE and SMAPE for each of the three trees, we can then pick the optimal one. [ABSTRACT FROM AUTHOR]

This paper aims at measurement of hydrodynamic parameters of cold model of Pressurized Fluidized Bed Gasifier (PFBG) and develops hydrodynamic similarity with the existing hot model PFBG of an IGCC Power plant. In the present experimental work, pilot scale hot model data of PFBG of 168 TPD had been verified by constructing hydrodynamically similar cold model of 2/3rd scale semi-circular. Also pressure measurements at four different heights have been taken for recording pressure fluctuations. Bed hydrodynamics are reflected in the amplitude of pressure variations, which is shown to be proportional to bubble size. Variable distributor setups with apex angles of 1500 and 1800 have been tested. Which were designed, fabricated and tested in a cold model and the optimised distributor configuration arrived. Various materials, including REFRACTORY (with mean particle sizes-0.8mm) and BOTTOM ASH (with mean particle sizes-0.8mm), were tested at varying static bed heights (D, 1.5D, 2D) using distributors with apex angles of 150° and 180°. We have shown the variation of distributor pressure drop (ΔPd) and Bed pressure drop (ΔPbe) over time as a function of surface velocity (Uo) have been recorded and formatted into a graph of ΔPbedVsUo. The Umfs for the aforementioned materials at the aforementioned static bed heights for the aforementioned distributors are then calculated. Minimum fluidization velocities (Umf) were found to be decreasing with the increase in static bed heights when air flow was raised from zero to its maximum (D, 1.5D, 2D). The Umf values are found to be increasing with increase in distributor apex angle (α) from 150° to 180°. [ABSTRACT FROM AUTHOR]

In this paper, our aim is to reduce sensors and measure pulse and temperature to monitor in rapid speed. A total of 25 samples are collected from one person by using Sensors. These samples are divided into training dataset (n=70%) and test dataset(n=30%). Time period values are calculated to quantify the performance of the Arduino based system. By using Arduino to monitor specific functions like pulse and temperature in 30 sec i.e quicker than previous conventional system which takes at least 1 minute. Arduino uno reduces measuring time by reducing more number of sensors when compared with conventional systems which have more sensors that take more time to monitor. [ABSTRACT FROM AUTHOR]

Rainfall plays an important role for cultivation and drinking purpose. If rains are high human beings face problems like floods and rains are low human beings again face another problems like droughts. In this paper, annual rainfall data from 1988 to 2017 is used for estimation of outliers using control limits and specification limits. After eliminating outliers for modified data of Rayalaseema, Coastal Andhra Pradesh and Telangana regions, we are fitting general linear model, Holt's linear exponential smoothing model and Brown's linear exponential smoothing model. Best among these three models is estimated using R2 criteria. [ABSTRACT FROM AUTHOR]

With the increase in the population density, portability and industrial pursuit maintain at a stimulating rate, in the recent years, air pollution has acquired the surveillance of policy makers in both the urban and metropolitan areas. There is a frequent review in highly polluted cities concerning the growing mortality correlated with acute diseases whose consequences may be incensed owing to exposure to air contaminants. Forecasting environmental pollution is contemplated as an indispensable lead for timely warning and control management of environmental pollution, specifically in emergency circumstances, where large proportions of pollutants are immediately liberated in the air, bringing about substantial destructions. Predicting environmental pollution in such circumstances is distinctly demanding owing to numerous spatial aspects influencing environmental pollution. In this study, we propose a method called Bivariate Gibbs and Spatial Correlated Deep Prediction (BG-SCDP). The proposed BG-SCDC based on Bivariate Gibbs Aggregated Feature Selection algorithm and Spatial Correlated Deep Prediction for highly dynamic environmental prediction mining. First, meteorological big data dataset is provided as input to the Bivariate Gibbs Aggregated Feature Selection model. Here, data points that include missing value are eliminated therefore obtaining computationally efficient features for further reference. Furthermore, if uncertain spatial big data analytic estimates of prediction make the forecasting more reliable, a Convoluted Long and Short-Term Memory for highly dynamic environment quality prediction is designed that allows in mining spatial data features in a precise and accurate manner. We conduct extensive experimental evaluations using meteorological dataset. The results demonstrate the efficiency of our proposed BG-SCDC method in comparison to state-of-the-art methods in terms of execution time, true positive rate and prediction accuracy. [ABSTRACT FROM AUTHOR]

MD simulation is used to study the interaction between the molecules at atomic as well as molecular level. In this simulation study, Carbon nanotube has been dispersed in water base solution to measure the interactions between the carbon-carbon, carbon-hydrogen, carbon-oxygen, hydrogen-oxygen molecules. Lennard-Jones (LJ) potential is used to determine the interfacial properties between the CNTs and water molecules. Study depicts that viscosity of the nanofluid increases as the concentration of particle increases at fixed temperature 308K and vice versa. Investigation concluded that at fixed temperature 308K, viscosity of nanofluid is 373.69mPa-ses. [ABSTRACT FROM AUTHOR]

Civil engineering has grown in numerous aspects as a result of technological advancements and evolution. Previously, the study and sustainability of civil structures were done using paper-based calculations, which resulted in insufficient precision and changeable elements causing the structure's demise through inevitable events. However, with the help of the integration of various engineering fields, this determination of various characteristic changes, deformation, or failure caused by hidden factors that are left out in real-time and manual calculations, i.e., paper-basedcalculations, has converted and led this system to a whole new level. Currently, Various software are being developedfor the analysis, computing, and management of a very precise RCC Entrance Arch. This study explains how to use and benefit from the software STAAD Proficient in the field of building and in the examination of concrete structures. [ABSTRACT FROM AUTHOR]

Outlier means points lie outside the normal data. Outlier plays an important role in model fitting. If outlier is involved in data, models may be over fitted or under fitted. Detection of outlier is important for fitting the best model to data. In data mining techniques for detection of outliers DBSCAN Clustering method, Isolation Forest etc. are used. In this paper for rainfall data for detection of outliers DBSCAN clustering method is used. After detecting outliers we removed that and we run regression models of data mining techniques such as Linear Regression(LR), k-Nearest Neighbors(k-NN), Decision Tree(DT), Support Vector Machines(SVM) and Multi-Layer Perceptron(MLP) using WEKA software. Using the accuracy measures such as Mean absolute error(MAE), Root mean square error(RMSE) criterion, we choose the best model among five regression algorithm of data mining techniques for rainfall data. [ABSTRACT FROM AUTHOR]

There are numerous regression models in literature and some of them are simple linear, multiple linear, polynomial, Cubic, Stepwise, Ridge, Lasso, Elastic Net, Negative Binomial, Poisson, Partial, Principal Component Regression etc. Generally regression gives single fit for total data. Splines or piecewise regression gives two or more regression lines for data using knots. In this paper we are fitting trigonometric piecewise regression, Polynomial piecewise regression and cubic piecewise regression for Atmospheric data. Best among these three piecewise models is estimated using R square criteria. [ABSTRACT FROM AUTHOR]

Aviation is a fast growing and challenging field where demand for a better and economical technology is always sought of. The current research looks at a flapping-based vertical locomotion mechanism. The flapping wings combine lift and thrust functions, reducing drag-inducing structures. As a result, a high level of lift and hovering efficiency is required. The computational investigation of the aerodynamic efficiency of two-dimensional flat plates is carried out. An inverted V structure prototype, consisting of vertical hinged at their leading edges, is being considered. The effect of 2D plates is examined by adjusting the hole at different locations on the flapper. It has been discovered that a hole at a specific location with a specific geometry is needed for improved aerodynamic characteristics. [ABSTRACT FROM AUTHOR]

In this paper Capacitor Clamped Multilevel Inverter (CCMLI) is simulated for the output voltage by Phase Disposition SPWM methods. They are Alternate Phase Opposition Disposition (APOD) SPWM, Carrier Over Lapping (COL) SPWM, Multicarrier Variable Frequency (MCVF) SPWM, Phase Disposition (PD) SPWM, and Phase Opposition Disposition (POD) SPWM. Modulation index is varied from 0.2 to 0.9 for each SPWM methods to get Total Harmonic Distortion (THD). It is found that MCMF SPWM method will give better THD results comparatively. This analysis will be useful for the researchers. [ABSTRACT FROM AUTHOR]

A Schmitt Trigger is a comparator that helps in improving the noise immunity of the circuits and is an inbuilt component of various applications. Earlier much study was done on how to increase the speed of the circuit. But over the last decades the focus has been shifted to power. Reducing Power Consumption has always been a major constraint in designing VLSI circuits which can be achieved by using adiabatic circuits. The Adiabatic process refers to a thermodynamically reversible process, which significantly reduces power by using the concept of switching activities where the energy stored is given back to supply. In this paper the power of the proposed diode free adiabatic logic Schmitt trigger is examined and differentiated with the conventional CMOS Schmitt trigger. This logic is implemented and simulated in VIRTUOSO SPECTRE of Cadence tool using standard 45nm technology within frequency range of 1MHz-25MHz [ABSTRACT FROM AUTHOR]

The studies on the structural and magnetic properties of YFe1-xMnxO3 (x =0, 0.1, 0.2, 0.3, 0.4 and 0.5) multiferroic samples, prepared by sol-gel method, are reported in this paper. The X-ray diffraction studies confirm the crystalline nature of the compounds which are formed in a pure single phase. From scanning electron micrographs, the average particle size is found to be increased with increasing Mn content and the sample is becoming porous. Magnetization versus magnetic field studies reveal that as Mn content increases, the saturation magnetization, remnant magnetization and coercive field values decreases which clearly indicates that the antiferromagnetic coupling gets strengthened. This increase in the antiferromagnetic nature is possibly due to the structural distortions in the compounds which give rise to the antiferromagnetic super exchange magnetic interactions between Fe+3 - Fe+3 and Fe+3 - Mn+3. [ABSTRACT FROM AUTHOR]

The design engineers are vigilant about weight reduction without compromising on the structural strength. The composite is a lightweight material that has good structural properties, and it is widely used as it can be tailored based on the requirements. Fabric-reinforced polymer composites have a wide applicationin engineering because of its high specific strength. The fabric serves as reinforcement, and it may be synthetic or natural. Synthetic fibers are not only strong but also lightweight. In the present work, fabrication and experimental investigation on synthetic fiber-based polymer composites are carried out. Initially, bidirectional carbon, Kevlar, and glass laminates are fabricated using hand lay-up and vacuum bagging methods. Then, hybrid laminate made up of carbon-Kevlar and carbon-glass laminates are fabricated, and experimental investigationis conducted to study their mechanical behavior. The comparative studies on the laminates are carried out and theobtained results are quite interesting. [ABSTRACT FROM AUTHOR]

A supersonic inlet plays a predominant role in obtaining the optimal thrust in a ramjet engine. Since there are no moving parts in a ramjet, the air gets compressed by the formation of a series of oblique and normal shock along the inlet to ensure that combustion occurs at subsonic flow. Generation thrust is depends on the inlet aerodynamic design, so there is a need for an optimal design for the maximum efficiency. In this work, design of optimal inlet design is carried out using the meta-heuristic optimization scheme. Initially, the Bezier curve parameterization method and QuickerSim flow analysis tool are coupled with genetic algorithms to parametrize the inlet design and to identify the total pressure recovery over an inlet respectively. The objective function of optimization scheme is to design the optimal inlet design by maximizing the total pressure recovery under a constraint. The complete cycle is coded in Matlab platform to reduce the computational cost. [ABSTRACT FROM AUTHOR]

An analysis has been carried out to study an unsteady MHD convective non-Newtonian fluid flow in the presence of heat source and radiation absorption. The governing partial differential equations along with the boundary conditions are first cast into a dimensionless form and then the equations are solved by closed analytical method. The effect of various physical parameters like porous permeability, Prandtl number, heat source, radiation absorption, diffusion-thermo, Schmidt number and chemical reaction parameter on velocity, temperature and concentration profiles are presented graphically. The effects of all these parameters on wall velocity gradient, wall temperature gradient and wall concentration gradient are also discussed with the help of tables. Temperature increases in the presence of heat source, radiation absorption parameter and Dufour number while decrease in the presence of Prandtl number and radiation parameter. [ABSTRACT FROM AUTHOR]

This analysis reveals an analytical study on heat and mass transfer effects on MHD visco-elastic fluid flow past an inclined vertical plate embedded in porous medium. The nature of the flow is examined with the influence of thermal radiation, heat source, chemical reaction, Prandtl number and Dufour number. A closed analytical solution is evaluated for the flow velocity, temperature and concentration from the equations that govern the flow. Graphical presentations are taken to discuss the impact of considered parameters. Further the variations in skin friction, Nusselt number and Sherwood number are examined under the impact of related parameters. [ABSTRACT FROM AUTHOR]

Structural and 57Fe MÖssbauer study of Sol-Gel prepared Indium substituted Cobalt ferrites with chemical formula CoFe2-xInxO4 (x= 0, 0.2, 0.4, 0.6 and 0.8) are reported in this paper. From the Rietveld refinement of X-Ray diffraction patterns, it is observed that x=0, 0.2 samples are formed in single phase without any detectable impurity and x=0.4, 0.6 and 0.8 samples consists of a relatively small fraction un-reacted Fe2O3 as an impurity phase. It is also found that lattice parameters increase with the increase of Indium concentration. The SEM images exhibit the increase of grain size from 100-205 nm with the increase of Indium doping concentration. Room temperature 57Fe Mossbauer spectroscopy confirms the magnetic ordering of Fe3+ spins in all the samples. [ABSTRACT FROM AUTHOR]

Structural and 57Fe MÖssbauer study of Sol-Gel prepared Indium substituted Cobalt ferrites with chemical formula CoFe2-xInxO4 (x= 0, 0.2, 0.4, 0.6 and 0.8) are reported in this paper. From the Rietveld refinement of X-Ray diffraction patterns, it is observed that x=0, 0.2 samples are formed in single phase without any detectable impurity and x=0.4, 0.6 and 0.8 samples consists of a relatively small fraction un-reacted Fe2O3 as an impurity phase. It is also found that lattice parameters increase with the increase of Indium concentration. The SEM images exhibit the increase of grain size from 100-205 nm with the increase of Indium doping concentration. Room temperature 57Fe Mossbauer spectroscopy confirms the magnetic ordering of Fe3+ spins in all the samples. [ABSTRACT FROM AUTHOR]

Gravitational waves from neutron-star mergers are expected to provide stringent constraints on the structure of neutron stars. At the same time, recent advances in nuclear theory have enabled reliable calculations of the low density equation of state using effective field theory based Hamiltonians and advanced techniques to solve the quantum many-body problem. In this paper, we address how the first observation of gravitational waves from GW170817 can be combined with modern calculations of the equation of state to extract useful insights about the equation of state of matter encountered inside neutron stars. We analyze the impact of various uncertainties and we show that the tidal deformability extracted from GW170817 is compatible, while less constraining, than modern nuclear physics knowledge. [ABSTRACT FROM AUTHOR]

The paper presents the effect of electron beam (e-beam) irradiation on potato starch. Starch powder was exposed to e-beam source of doses 30, 60 and 90 kGy and the effect of irradiation treatment on structural, thermal, morphological and viscosity properties of starch granules were studied. Signals were traced from electron spin resonance (ESR) spectroscopy indicating that free radicals are formed on irradiation. The results have showed that the viscosity of starch solution decreases whereas solubility increases on irradiation. Gelatinization temperature decreased following irradiation from differential scanning calorimetry studies. From fourier transform infrared (FTIR) studies, the intensity of absorption band 999 cm-1 increases on irradiation which indicates an increase in amorphous nature of starch. The X-ray diffraction results are in good agreement with the FTIR studies regarding crystallinity. The surface structure of the starch granules have changed significantly at high dose of irradiation from scanning electron microscopy. [ABSTRACT FROM AUTHOR]

Stable a-phase of Al2O3 is synthesized by combustion method usingtemperature controlled microwave oven. Crystalline phase is analyzed by X-ray diffraction (XRD)and average crystallite size is found to be 75 nm. Thermoluminescence (TL) glow curve of Al2O3 is studied in UV, blue and open (visible) windows after beta irradiation. A prominent TL glow with peak at 472 K along with shoulders at 416 and 513 K are observed in all three windows. These peaks may be ascribed to F, F2 and F+- centers. Highest TL intensity isobserved inopen window. Optically stimulated luminescence (OSL) studies in UV and blue windows shows highest intensityin UV window. TL/OSL of phosphor shows linearresponse with beta dose upto 6.16 Gy.TL/OSL properties viz fading, repeatability and MDD are studied. TL kinetic parameters are estimated by deconvolution with computerized glow curve deconvolution (CGCD) techniques. [ABSTRACT FROM AUTHOR]

Solid electrolytes with a matrix of Pb(NO3)2 as host and Al2O3 (0.3μm) as dispersoid is prepared by conventional milling mechanism. Structural and morphological studies were carried out through XRD and SEM respectively which confirm that these composites are two phase systems. AC conductivity studies were performed by employing impedance measurement technique between the temperatures 30 and 300°C and in the frequency range 100Hz to 5MHz. Non-overlapping small polaron tunneling mechanism (NSPT) model suggested for ion hopping in the conduction processes. [ABSTRACT FROM AUTHOR]