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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 native advertising on buzzfeed and its impact on the brand image of 7 companies /
In today's world, the social web space has become a competitive platform for companies engaged in a plethora of activities to promote and sell their products and, more importantly, create a brand image. In tandem with the rapid development that has been observed in social media, the advertising industry has also evolved to accommodate the needs of the internet. Native advertising has emerged as a viable and lucrative alternative for companies to communicate with their audiences. -
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 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 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 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 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 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 MARKETING AND ADVERTISING STRATEGIES OF DECCAN HERALD, BANGALORE
For years newspapers have sold papers through racks on the streets. With change in consumer behaviour, the sales and purchases of newspapers have also transformed. Technological advancement brought in a demand to be innovative and to suit the changing behaviour of the consumer. Newspaper like any other commodity has to fight for its survival and make an impact on the consumer??s mind. The days of ??Plan Buy?? have taken a backseat because of availability of many options for the product of the same kind. There comes a need to draw all the attention of the consumer to the devices of innovation in order to make a purchase. Newspapers therefore, have adopted different elements of the marketing communication mix of the integrated marketing communications to smartly market themselves at every level to reach and appeal to ever changing readers. The research will aim at studying the changes by the newspaper organization in order to market their newspaper through ??An Analysis of Marketing and Advertising Strategies of Deccan Herald, Bangalore.?? The research is aimed at studying the steps and procedures that are taken by the newspaper organization to position their newspaper to the target readers to get the desired market share. The research will also try and gauge the impact of the marketing and advertising strategies adopted. If there is an impact what might be the possible reasons and till what extent. The research will make a detailed analysis by interviewing people from Deccan Herald, Bangalore to get in-depth knowledge about the steps and procedures taken by the newspaper organization. Also, in addition a sample survey was conducted with a total sample size of 85 to gauge the impact. -
Analysis of Market Communication and Informatization Services: A Data-Driven Study Based on SDMX Statistics
The market communication and informatization services sector plays a crucial role in modern economic development, facilitating digital transformation and connectivity. This study leverages official statistical data to analyze trends, growth patterns, and the economic impact of communication services in Uzbekistan. Using the SDMX dataset, we evaluate sectoral contributions, regional disparities, and the role of technological advancements. The findings provide insights into investment efficiency and policy recommendations for sustainable sectoral growth. 2025 IEEE. -
Analysis of Market Behavior Using Popular Digital Design Technical Indicators and Neural Network
Forecasting the future price movements and the market trend with combinations of technical indicators and machine learning techniques has been a broad area of study and it is important to identify those models which produce results with accuracy. Technical analysis of stock movements considers the price and volume of stocks for prediction. Technical indicators such as Relative Strength Index (RSI), Stochastic Oscillator, Bollinger bands, and Moving Averages are used to find out the buy and sell signals along with the chart patterns which determine the price movements and trend of the market. In this article, the various technical indicator signals are considered as inputs and they are trained and tested through machine learning techniques to develop a model that predicts the movements accurately. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analysis of magnetohydrodynamic casson fluid flow with chemical reaction in a vertical channel: thermal and mass transfer effects
This study investigates Casson fluid flow in a vertical channel within a magnetohydrodynamic (MHD) region, incorporating chemical reaction effects. The channel consists of two regions: one filled with an electrically conducting fluid and the other with a Casson fluid. The nonlinear coupled governing equations are solved using the perturbation method with a small perturbation parameter. The results are presented graphically to analyze the flow characteristics. This systematic analysis yields the velocity and temperature distributions, governed by key parameters such as the Grashof number (Gr), Hartmann number (M), Casson parameter (?), and chemical reaction rate, all of which critically influence the hydrodynamic and thermal behavior of the system. It is observed that the larger the values of the viscosity ratio, width ratio, and the conductivity ratio, the larger the flow field. The findings reveal that the presence of Casson fluid enhances the thermal and mass Grashof numbers, attributed to buoyancy forces. Conversely, the chemical reaction parameter and Hartmann number exhibit a suppressive effect on the flow. The Author(s) under exclusive license to Universitdegli Studi di Ferrara 2026. -
Analysis of machining parameters for face milling of inconel 718 using response surface methodology
The machining of Inconel 718 which is a nickel based super alloy has become a material of great importance mainly in the aerospace industry. Reason being the materials possesses properties of increase in strength at elevated temperature, high resilience to chemical reaction and high wear resistance. Gaining optimum machining parameters have become a great concern in the manufacturing industry, where economy of machining plays a very important key role in the market. This paper gives an overview of the experimentation conducted on the basis of Response Surface Methodology (RSM). Regression equations have been developed for surface roughness, by taking into consideration the machining parameters like cutting speed, feed rate and depth of cut for face milling operation performed in CNC machine. RSM analysis was carried out with the help of Mini Tab 18 software. The Mathematical equation developed after regression analysis shows to be very efficient. BEIESP. -
Analysis of Kidney Ultrasound Images Using Deep Learning and Machine Learning Techniques: A Review
Ultrasonography is the most accepted and widely used imaging technique due to its non-invasive and radiation-free nature. The heterogeneous structure of kidney makes the disease detection a difficult task. Hence, more efficient models and methods are required to assist radiologists in making precise decisions. Since ultrasound imaging is considered to be the initial step in the diagnosis, more efficient processing techniques are needed in the interpretation of images. The presence of speckle noise is a challenge task in image processing. It diminishes the clarity of the images. In this article, an in-depth review has been performed on various machine learning and deep learning techniques, which are helping to improve the quality of images. The pre-processing, segmentation, feature extraction, and classification are described in detail using kidney cyst, stone, tumor, and normal kidney images. Deep learning techniques are enhancing the quality of the images with better accuracy. The remaining challenges and directions for future research are also explored. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analysis of indias trade patterns and trade possibilities with the european union
Trade has played a crucial role in the emergence of developing econo-mies. The global emergence of India is also linked to its role in global trade. In this context, the European Union and India initiated talks for a free trade agreement known as the Bilateral Trade and Investment Agreement (BTIA). However, this agreement has failed to materialise due to various challenges and disputes. Against this backdrop, the present study attempts to trace the existing pattern of trade relations between India and the EU and provide a preliminary analysis of the nature of trade in this proposed region. A modified gravity equation and indicators of regional trade interdependence have been estimat-ed. The results indicate that trade within this region is in line with cer-tain predictions of the gravity model. Additionally, it also indicates that such an agreement has little potential for expanding trade and might even result in unnatural trade. Thus, it provides evidence for the argu-ment that India can benefit from developing ties with similar emerging economies in the Asia-Pacific neighbourhood. 2020, WSB University. All rights reserved. -
Analysis of imperfect interfaces in cobalt ferrite plates using a linear spring model: a comparative study with terfenol-D
Purpose: This research aims to explore the transmission of seismic surface waves through a two magneto-strictive materials i.e. cobalt ferrite and Terfenol-D when embedded in a plate-substrate configuration with non-ideal interface. The study focuses on understanding the impact of width of the plates, imperfect parameter, heterogeneity parameter on both the materials cobalt ferrite and Terfenol-D under magnetically open and short conditions. Methodology: To achieve this, the study employs a variable-separable technique following Direct Sturm-Liouville method and appropriate boundary conditions to derive frequency relations for both magnetically open and short circuit scenarios. Numerical simulations are conducted to investigate the effects of width of the plates, imperfect parameter, heterogeneity parameter on both the materials cobalt ferrite and Terfenol-D under magnetically open and short conditions. Findings: The research findings indicate that the phase velocity is increasing more in Terfenol-D as compared to Cobalt ferrite, either the case magnetically open or closed. Graphical comparisons highlight the impact of width plates, imperfect parameter, heterogeneity parameter on the characteristics on wave propagation clearly. Research limitations: The study is confined to linear wave propagation and does not consider nonlinear effects. Additionally, the analysis is based on idealized material properties and interface conditions. Practical implications: The results of this research can contribute to the design and optimization of sensors, energy harvesters, and wave manipulation devices utilizing piezomagnetic materials. Understanding the behaviour of surface waves in these structures is crucial for their effective application. Originality: This study offers a comprehensive analysis of surface wave propagation in two different types of piezomagnetic composite structure by considering heterogeneity and interface conditions. The comparative study of different piezomagnetic models and the incorporation of heterogeneity and interface conditions contribute to the originality of the research. The Author(s) 2024. -
Analysis of impact investment for sustainable development in India
Impact investment is a form of investing the purpose of which is to generate not just financial returns, but positive social or environmental impacts also. The objective of this research is to observe the trends that are being followed in the Indian impact investing landscape and draw the comparisons and/or similarities with the data published by the Global Impact Investing Network (GIIN), a nonprofit organisation committed to expanding the scope of impact investing globally. For the objective of gauging the Indian impact investment movement, primary data was collected through a survey of 238 Indian impact investors, and the data collected was analysed descriptively and compared with secondary data available on the GIIN's website. The insights that are provided by this study shall aid investors as they are encouraged to review the implications for their own strategies and patterns of investing and investigate these actionable measures so as to facilitate a sustained responsible industry growth, improve market transparency, and reinforce the patterns of investment decision-making. 2024, IGI Global. All rights reserved. -
Analysis of Human Physiological Parameters Using Real-Time HRV Estimation from Acquired ECG Signals
The overall healthiness of the heart can be computed from Electrocardiogram. The healthiness of the heart depends on several lifestyle parameters, like as- stress, sleeping pattern, smoking habit etc. In this paper, an algorithm to determine Heart Rate Variability from the acquired ECG signal on a real-time basis is presented. Impacts of above-stated lifestyle parameters on cardiac health using Heart Rate Variability analysis are also computed. ECG signal gets contaminated with different sources of noises while acquisition. Multi-rate FIR Impulse Filter is used for de-noising of the acquired signal. Heart Rate Variability analysis and real-time plotting are done on de-noised output for accurate feature extraction. A simple robust hardware realizable algorithm was developed for analyzing obtained HRV to state different health conditions of the heart. 2019 IEEE. -
ANALYSIS OF GOVERNMENT ADVERTISEMENT ON THE AGRICULTURE OF MANIPUR
The term development, advancement and technology may not be the right set of words to describe rural areas of a country, as generally we associate rural parts of a country as backward, dirty, uncivilized and poverty. Today, Media is one of the most important and powerful medium that plays a very significant role in the lives of millions of people in the country because from centuries before media has helped and made people aware of the available options and the new technologies which make the lives of millions of people easy especially for the development of backward or the rural areas of a country catering to the needs of different people. Advertising is an indirect way of bringing or turning the masses or peoples towards the advertised services by providing plenty of information that is premeditated in order to bring effectiveness with a complimentary thought, now advertising is one such aspect of media that plays a vital role. Hence, the researcher in this research tries to find out the role of IASF and its effectiveness through advertisement by analysis its creative tactics. -
Analysis of Fraud Prediction and Detection Through Machine Learning
In today's world the rate of fraudulent activities has significantly elevated, because of which a need for a competent system is required. Among all the fraudulent activities insurance fraud has the most dominating rate of growth. Fraud studies have suggested, that upon identifying the similar characteristics of a fraudulent claim with the claimants, a system of forensic and data-mining technologies for fraud detection can be set up. In this, seek to define fraud and fraudster, and look at the types of fraud and followed by the consequences of fraud to financial systems. As fraud is getting widespread these days epically in the health care insurance system, dealing with this problem has become a necessity. Unsupervised machine learning algorithms such as K-Means clustering along with supervised algorithms used in machine learning, like support vector machines, logistic regression, design trees etc. can play a very vital role in binary class classifications, which would ultimately help in identifying and outreaching the desired goal of fraudulent detection. In the end, this paper specifies the best or the most appropriate model that could be used in the given dataset to produce the most accurate results, based on certain parameters of confusion metrics like accuracy, precision, and specificity. 2023 IEEE.