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Analysis of Membership Probability in Nearby Young Moving Groups with Gaia DR2
We analyze the membership probability of young stars belonging to nearby moving groups with Gaia DR2 data. The sample of 1429 stars was identified from "The Catalog of Suspected Nearby Young Moving Group Stars." Good-quality parallax and proper motion values were retrieved for 890 stars from the Gaia DR2 database. The analysis for membership probability is performed in the framework of the LACEwING algorithm. From the analysis it is confirmed that 279 stars do not belong to any of the known moving groups. We estimated the U, V, W space velocity values for 250 moving group members, which were found to be more accurate than previous values listed in the literature. The velocity ellipses of all the moving groups are well constrained within the "good box," a widely used criterion to identify moving group members. The age of moving group members are uniformly estimated from the analysis of the Gaia color-magnitude diagram with MIST isochrones. We found a spread in the age distribution of stars belonging to some moving groups, which needs to be understood from further studies. 2020. The American Astronomical Society. All rights reserved.. -
Analysis of Mothers Willingness for Age 1 First Dental Visit of Their Child using Andersens Behavioral Model of Health Service Utilization
Background: Early childhood caries (ECC) is a preventable disease among children under 6 years of age.The first dental visit (FDV) is a preventive model endorsed by the American Academy of Pediatric Dentistry and the American Academy of Pediatrics. It is designed to improve oral health outcomes, yet the FDV attendance rate before the age of 1 is low globally, especially in India. Aims: To investigate maternal willingness to attend the FDV within 1 year of age and explore associations with predisposing, enabling, and need factors using Andersens behavioral model for health services utilization. Materials and methods: A cross-sectional survey was conducted among mothers of children aged 915 months. A validated questionnaire was administered to 640 mothers visiting vaccination centers in two hospitals. Statistical analysis involved descriptive statistics and logistic regression to evaluate factors influencing FDV willingness. Results: Willingness to attend FDV within 1 year of age was significantly influenced by predisposing factors, such as oral health knowledge, perceived barriers, and susceptibility to caries. Enabling factors, such as socioeconomic status and family support, showed minimal influence, while need factors, including the perceived oral health of the child, strongly correlated with FDV willingness. Findings revealed low awareness and attendance rates for FDV in the study population. Conclusion: First dental visit attendance among infants in the study population is critically low, highlighting the need for targeted awareness campaigns. Pediatric healthcare professionals should actively promote oral health and FDV as preventive measures during well-baby visits to enhance acceptance and utilization. Clinical significance: This studys focus on analyzing mothers willingness to pursue the FDV at age 1, using Andersens behavioral model of health service utilization, which provides actionable insights into the multifactorial drivers behind health-seeking behavior. Understanding how predisposing, enabling, and need-based factors influence maternal decision-making not only aids in identifying barriers to early dental care but also hi hli hts o ortunities to tailor ublic health interventions The Author(s). -
Analysis of MRI Images to Discover Brain Tumor Detection Using CNN and VGG-16
Brain tumor is a malignant illness where irregular cells, excess cells and uncontrollable cells are grown inside the brain. Now-a-days Image processing plays a main role in discovery of breast cancer, lung cancer and brain tumor in initial stage. In Image processing even the smallest part of tumor is sensed and can be cured in early stage for giving the suitable treatment. Bio-medical Image processing is a rising arena it consists of many types of imaging approaches like CT scans, X-Ray and MRI. Medical image processing may be the challenging and complex field which is rising nowadays. CNN is known as convolutional neural network it used for image recognition and that is exactly intended for progression pixel data. The performance of model is measured using two different datasets which is merged as one. In this paper two models are used CNN and VGG-16 and finding the best model using their accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analysis of multilayer convective flow of a hybrid nanofluid in porous medium sandwiched between the layers of nanofluid
AgBr acts as a good sensitizer for titanium oxide, hence TiO2AgBr nanoparticles exhibit high photocatalytic activity which helps decompose methyl orange under visible light irradiation. Methyl orange is a chemical compound that is hard to degrade and has high stability. It is photoreactive and can capture photons from the sun and is highly used as a light harvester in solar cells, hence, it is used in solar applications. In view of this, the present article deals with the analysis of heat transfer in a multilayer flow of two immiscible nanofluids in a vertical channel that finds application in the fields of solar reactors, electronic cooling, and so on. The mathematical model involving the effect of thermal radiation and the presence of heat source is in the form of a system of ordinary differential equations. This system of equations is simplified using the differential transform method-Padapproximant and the resulting equations are solved algebraically. It is observed that the temperature of the coolant does not reach its saturation point faster due to the presence of different base fluids that differ in their thermal conductivity. This helps in maintaining theoptimum temperature of the system. 2021 Wiley Periodicals LLC -
Analysis of multimode oscillations caused by subsynchronous resonance on generator shaft
Series capacitors are installed in high voltage alternating current transmission lines to counteract the inductive reactance of the line. The resonance caused by series capacitors between electric system and mechanical system at frequencies less than the synchronous speed, leads to torsional oscillations. Undamped oscillations ma y cause a severe fatigue in the turbine generator shaft system. Rotating component undergoes various modes of oscillations when it is subjected to resonance. Rotor oscillate in different modes such as swing mode, super synchronous mode, electromechanical mode and torsional mode. Rotor dynamics of rotating structure depends on several factors like Coriolis Effect, moment of inertia and stiffness coefficient. Modal analysis using finite element method gives the natural frequency and mode shapes of any rotating structures. In this paper, a two mass rotating system which is analogous to turbine generator is subjected to resonance by adding series capacitors and its dynamic behavior is studied using finite element method. 2018 Lavoisier. -
Analysis of Multinomial Classification for Legal Document Categorization
A major area of research today is the application of Machine Learning Techniques for Document or Text Classification. Document Classification is an important aspect of Electronic Discovery in the Legal domain. The need for the process to be automated has been realized over the past few years. Multinomial Classification is a well-known Supervised Machine Learning Technique that helps us classify if there are more than two classes used for the purpose of Classification. Evaluation metrics such as Precision, Recall, and F1 Score have been used to measure the efficiency of Classification. Logistic Regression and Gradient Boosting Algorithms have outperformed other Multiclass Classification techniques. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Analysis of Nifty 50 index stock market trends using hybrid machine learning model in quantum finance
Predicting equities market trends is one of the most challenging tasks for market participants. This study aims to apply machine learning algorithms to aid in accurate Nifty 50 index trend predictions. The paper compares and contrasts four forecasting methods: artificial neural networks (ANN), support vector machines (SVM), naive bayes (NB), and random forest (RF). In this study, the eight technical indicators are used, and then the deterministic trend layer is used to translate the indications into trend signals. The principal component analysis (PCA) method is then applied to this deterministic trend signal. This study's main influence is using the PCA technique to find the essential components from multiple technical indicators affecting stock prices to reduce data dimensionality and improve model performance. As a result, a PCA-machine learning (ML) hybrid forecasting model was proposed. The experimental findings suggest that the technical factors are signified as trend signals and that the PCA approach combined with ML models outperforms the comparative models in prediction performance. Utilizing the first three principal components (percentage of explained variance=80%), experiments on the Nifty 50 index show that support vector classifier (SVC) with radial basis function (RBF) kernel achieves good accuracy of (0.9968) and F1-score (0.9969), and the RF model achieves an accuracy of (0.9969) and F1-Score (0.9968). In area under the curve (AUC) performance, SVC (RBF and Linear kernels) and RF have AUC scores of 1. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Analysis of Nine Level Single-Phase Cascaded H-Bridge Inverters for EVs
This paper explores the design and operation of a Modular Nine-Level Inverter (MLI)-Electric Vehicle (EV) charging system, incorporating solar energy to power domestic loads and charge EVs. The system comprises a solar panel, DC-DC regulator, and MLI for efficient energy conversion. The MLI's modular design reduces complexity and enhances efficiency. Equivalent circuits illustrate voltage level generation, while PWM control regulates power device switching for precise output control. Performance metrics, including regulated DC supply voltage and staircase nine-level output voltage, demonstrate the system's capability for diverse applications. A nearly sinusoidal current waveform and harmonic analysis underscore the system's effectiveness in delivering stable power with reduced harmonic distortion. Comparisons between filtered and unfiltered output highlight the importance of filtering techniques in improving power quality. Overall, the MLI-EV charging system showcases advancements in renewable energy integration, offering a versatile solution for sustainable electricity generation and EV charging. 2024 IEEE. -
Analysis of nonlinear compartmental model using a reliable method
The goal of this work is to investigate nonlinear models and their complexity using techniques that are universal and have connections to historical and material aspects. Using the premise of a constant population that is uniformly mixed, a nonlinear compartmental model that depicts the movement between voter classes is taken into consideration. In the current work, we investigate the dynamical framework that supports the interactions between the three parties. It is discussed how rate change affects various metrics. The conditions for boundedness, stability, existence, and other dynamics are obtained. We derive the effects of generalizing the model in any order. The current study supports investigations into complex real-world issues and forecasts of necessary plans. 2023 The Author(s) -
Analysis of nonlinear convection and diffusion in viscoelastic fluid flow with variable thermal conductivity and thermal radiations
The study offers a thorough evaluation of the complex fluid dynamics and heat transfer phenomena in Williamson viscoelastic fluid flow, taking into account thermal radiations and variable thermal conductivity. The paper extends its analysis to include heat transfer effects, which are critical in several engineering and industrial applications, and digs into the complexity of non-Newtonian fluid behavior, with a special focus on thermal radiation, heat production, diffusion and viscous dissipation. The study makes use of mathematical models and numerical method RK4 to clarify the nonlinear interactions between convection and diffusion processes in this viscoelastic fluid. The energy and concentration equations are simulated in the presence of the modified Fourier and Fick laws. Moreover, the predicted heat flow is based on the Cattaneo-Christov theory. This research also sheds light on the interaction between rheological properties and thermal characteristics, providing important new knowledge to the broader field of fluid dynamics and heat transfer. 2024 World Scientific Publishing Company. -
Analysis of Online In-Destination Booking Service Processes in the Travel Industry: A Case Study
This article presents a comprehensive analysis of the online in-destination booking service processes within the dynamic landscape of the travel industry. Utilizing a case study approach, the research investigates the various stages involved in providing travel-related services, focusing on the key players. The study employs a quantitative method to assess the information quality, system quality, service quality, customer satisfaction, and purchase intention of online in-destination booking. The research highlights the investigation of the usability of online travel booking systems and identifies the purchase intention of customers towards online travel booking websites. To address the research objectives, the participants are selected using a nonprobability sampling method. The sample size of the study is 225 from in and around Coimbatore. The sampling procedure used is convenience sampling. The sampling is selected based on convenience and accessibility to the residents. The findings reveal that there exists a significant difference in respondents opinions on quality criteria: system quality and service quality. Additionally, the study finds that the loading time of online travel booking websites is positively correlated with quality criteria and features of travel apps. By examining a specific case within the travel sector, this study contributes valuable insights that can inform strategic decision-making for businesses operating in the online in-destination booking space. The results aim to guide industry players in enhancing their operational efficiency, leveraging technology advancements, and aligning their services with evolving customer expectations, ultimately fostering sustainable growth in the competitive travel market. 2024, Bentham Books imprint. -
Analysis of passive bloodstain morphology across surface textures and drop heights using deep learning
Bloodstain pattern analysis (BPA) is a critical forensic science tool for reconstructing crime scene events. In this study, the effect of substrate type and drop height on the morphology of passive bloodstains was examined under controlled laboratory conditions. Blood samples were dropped vertically at 90 angle from three different heights, and the drops were permitted to strike five different surfaces, including curved cups, crushed chart paper, jute cloth, jelly stone, and concrete. These substrates were chosen to represent a realistic range of porous, semi-porous, non-porous, textured, and curved materials that are commonly encountered in crime scenes. The features of the substrate affect stain morphology, including shape irregularity and satellite formation, but not the measured angle of impact. These findings validate the consistency of impact angle determination using BPA, wherein the nature of the substrate primarily affects stain morphology but not necessarily the accuracy of angles. The large image data sets were tested using deep learning approaches, which effectively differentiate bloodstain patterns generated from varying fall heights. MobileNet model, leveraging pretrained ImageNet features, achieved superior accuracy and generalisation, underscoring the value of transfer learning for small forensic datasets. Future extensions of this work will include multiple impact angles, motion-related effects and temperature-controlled conditions to represent the actual crime scene scenarios. Deep learningbased analysis of these data may improve the understanding of bloodstain morphology and strengthen the forensic applicability. 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Analysis of Perceptions and Attitudes of Scheduled Commercial Bank Personnel Toward Provision of Credit to Poor and Toward Financial Inclusion Process in India
Journal of Investment and Management, Vol-1 (1), pp. 1-11. -
Analysis of Rayleigh-type wave energy transmission in piezoelectric substrate following GreenNaghdi type III, MooreGibsonThompson and three-phase-lag theories
This study investigates the propagation of Rayleigh-type surface waves in a homogeneous, transversely isotropic piezoelectric half-space under various boundary conditionsspecifically, stress-free, electrically open- or short-circuited, and thermally insulated or isothermal surfaces. We analyze the problem within the framework of the GreenNaghdi type III (GN-III) and three-phase-lag thermoelastic models named as model I. Also, studies carry the comparative study with Rayleigh surface wave propagation in piezoelectric media influenced by thermal effects and the presence of voids where this has analytical solutions for Rayleigh wave propagation in a nonlocal piezo-thermoelastic medium with voids, employing the MooreGibsonThompson thermoelasticity theory that incorporates memory-dependent effects named as model II. Plane harmonic wave solutions are employed to determine mechanical displacements, electric potential and temperature variations. Using these results, expressions for stress, electric displacement and temperature gradient are derived. Four secular equations corresponding to different boundary conditions are formulated for the considered half-space. The trajectories of surface particles are shown to follow elliptical paths in a vertical plane parallel to the direction of wave propagation, with the eccentricity of these ellipses explicitly calculated. When there is no phase difference between the vertical and horizontal displacement components, the particle motion degenerates into a straight-line path. A previously established analysis is recovered as a special case of the present model. The effects of various wave characteristicsincluding phase velocity, attenuation coefficient and specific lossare illustrated graphically for both the GN-III and three-phase-lag models, using cadmium selenide (a 6-mm class, hexagonally symmetric material) as the representative medium. The findings of this study highlight several distinct scenarios that enhance the understanding of Rayleigh wave propagation in complex material systems, especially those containing voids. This research offers important insights into the interplay between piezoelectric components and surface wave behavior, paving the way for advancements in sensor design, improved energy harvesting techniques and innovative seismic monitoring applications. This mathematical framework can serve as a foundation for the design and development of temperature sensors and other piezoelectric surface acoustic wave devices. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025. -
Analysis of Reinforced Concrete Structure Subjected to Blast Loads Without and with Carbon Fibres
In the past few decades, the terrorist attack on buildings has significantly increased. Blast loads due to explosions cause severe damage to the buildings structural and non-structural elements which may also lead to progressive collapse of the building. Hence, there is a need for the structures to be analysed and designed for blast loads in addition to the conventional loads. An investigation is undertaken to minimize the damage of a G+3 storied building and by improving the mechanical properties such as compressive strength, nonlinear behaviour of M40 grade concrete by adding carbon fibres in different dosages. A finite element model of G+3 storied building has been created using Ansys/LS Dyna to analyse the structure subjected to a blast load with charge weights of 50 kg, 100 kg, 150 kg at 3000 mm standoff distance. The lateral deflections and strains of the structure are determined for different charge weights to study the behaviour of the structure when subjected to blast loads. The addition of carbon fibres has improved the behaviour of structure by reducing the strains and deflections and optimum dosage of fibres is also determined in this paper. 2023, Springer Science and Business Media Deutschland GmbH. All rights reserved. -
Analysis of Routing Protocols in MANET Networks
The scientific article is a review and comparative analysis of routing protocols for MANETs. The study examines the main protocols connected to mobile ad hoc networks such as B.A.T.M.A.N, BMX7, OLSRv1, Babel and provides a detailed analysis of their characteristics, advantages and disadvantages. To empirically evaluate performance, tests were carried out in a network simulator. The results of the study allow us to draw conclusions about the effectiveness and reliability of each of the monitoring protocols under various operating conditions of MANET. This article is a valuable contribution to the field of MANET research and can be used in the development of new technologies and solutions for mobile wireless networks. The work is relevant and practically significant because it helps researchers and engineers make informed decisions when choosing the optimal routing protocol in MANET networks. The results obtained can be useful in the design of mobile applications, emergency communication systems, transport management and other areas where the efficient operation of wireless networks is important. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Analysis of secure cloud storage provisioning for medical image management system
Medical images are considered to be the most sensitive images as it contains various health related sensitive information of an individual and it is necessary for the health care organization to maintain the sensitivity of these images without anybody misusing these data. When these images are transferred digitally through a network in order to store it in cloud for easy access for the authorities of the health care system, it is important to compress and encrypt these images to reduce the size and safeguard the information before storing and make sure that these images are transferred securely. In this paper, we use Huffman Coding technique in order to compress the image for easy transmission and to consume less storage space in cloud. To maintain the confidentiality of these images Blowfish encryption methodology is used. Once the image undergoes compression and encryption, the encrypted image is transferred and stored in a cloud storage. IAEME Publication. -
Analysis of SH and anti-plane SH wave signals for nanosensor applications using two distinct models of piezoelectric materials lead zirconate titanate
The primary goal of the current study is to examine the effects of wave propagation on the performance of surface acoustic wave (SAW) macro- and nano-sensors. Therefore, shear horizontal waves (SH) in an orthotropic piezoelectric layer laid on top of an elastic framework (Model I), a piezoelectric substrate, and an orthotropic piezoelectric substrate (Model II) are studied using the surface piezoelectricity theory. The study used a variable-separable methodology. Theoretical forms are developed and used to show the wavenumber of surface waves in any direction of the piezoelectric medium based on the differential equations and matrix formulation. A piezoelectric material half-space with a nano substrate and an orthotropic piezoelectric material layer over an elastic framework are the two configurations that are investigated. Frequency equations are expressed analytically for both symmetric and anti-symmetric waves. The study looks into how phase velocity is affected by surface density, anisotropic piezoelectric constant, surface elastic constants, and symmetric and antisymmetric modes. The study is limited to the propagation of linear waves. Furthermore, the analysis is predicated on the material's surface characteristics and idealized material qualities. Surface effect study is the novelty, which is conducted in the piezoelectric model and its applications in sensors. The findings of this research may be useful in designing SAW devices. 2025 Wiley-VCH GmbH. -
Analysis of SH-waves Propagating in Multiferroic Structure with Interfacial Imperfection
This article presents the study of wave mechanics in a multiferroic structure having imperfection in the structures interface. This article reflects the study of shear horizontal (SH) wave propagation in a layered cylindrical structure consisting of thin layers of different materials (reinforced material and piezomagnetic material) with an imperfect interface. The interface considered between both materials is mechanically imperfect. Dispersion relations are achieved analytically. Distinct graphs are drawn (numerically) to exhibit the influence of parameters like rotation, initial stress, and mechanically imperfect parameters on phase velocity. Numerical results are drawn analytically and explained for each affecting distinct parameters for materials and interface. Parametric results on the phase velocities yield a significant conclusion of which some are: (a) Performance of Piezo with reinforcement material have an influential impact on wave velocity. (b) The mechanical imperfection affects the significantly on wave velocity (c) The Reinforcement/PM stiffening can monotonically up the velocity of phase velocity. 2022 Published by Semnan University Press. -
Analysis of skip-lot sampling plan of Type 3 with multiple reference criteria
In the modern quality control segment, the skip-lot sampling plan is still significant among all others plans due to rising production volumes and the demand for cost-effective inspection methods that will yield high-quality outputs. Unlike other sampling plans, while inspecting a submitted lot, a skip-lot plan is economically advantageous and ensures high quality. The skip-lot sampling plan utilizes single sampling plan (SSP) or double sampling plan (DSP) as the reference plan during both normal and skipping inspections. However, using these plans as the reference can lead to bias, favouring either the producer or the consumer. In this paper, a novel approach is illustrated where the skip-lot sampling plan of type 3 is having the provision of two different reference plans in the normal and skipping phases. The proposed plan is termed as the Multi-Reference Skip-lot Sampling Plan of type 3 (MR-SkSP-3). The plan is then compared with the help of performance measures such as operational characteristic (OC) function and average sample number (ASN). The comparison is done between the proposed plan and existing skip-lot sampling plans which use single sampling plan or double sampling plan as reference plan in both inspection phases. The comparison is made based on performance measures with graphical and tabulated illustrations. The comparative analysis proves that the proposed plan successfully balances the satisfaction of both producers and consumers. By leveraging the strengths of conventional skip-lot sampling plans that use single reference plans, it achieves superior performance. 2026 The Korean Statistical Society, and Korean International Statistical Society. All rights reserved.