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Analysis of determinants of voter turnout in Indian states for election years 19912019
Elections, considered the flagship to the emergence of a new government and a new era is a platform replete with exuberance and vibrancy in all forms. No election is complete without its voters who form the backbone behind the success of democracy. Democracy means elections and free and fair elections mean democracy. The present study is a focus on economic determinants of voter turnout in India since 1991 till date (2019 elections). Economics of voting is a study that encompasses analysis of both economists and political scientists in an attempt to study the economic forces influencing political outcome of the country. In this study, relevant forces determining voter turnout and their impact on political outcomes have been emphasized upon. The data are collected across regions and is characterized using panel regression. Economic factors influencing voter turnout are explored using pooled regression and fixed effect model. Results suggest that as India goes to vote, factors such as income employment influence turnout. Literacy (GER) and urban voter turnout do not influence voter turnout. Lack of efficient governance, bureaucratic loopholes, corruption, large-scale migration and others are some of the potent causes of low turnout. 2022, The Author(s), under exclusive licence to Institute for Social and Economic Change. -
Analysis of dystopian films 'Book of Eli' and 'V for Vendetta' using Randal Marlin's theory of propaganda /
Visual media, namely films, is one of the greatest mediums for the conveyance of propaganda. Dystopian films contain strong persuasive content in them and are used by filmmakers to spread propaganda. Unlike the filmmakers of the past, dystopian filmmakers focus on the future and their films are usually set in a futuristic environment. The environement is usually shown as being completely destryed by neglect or the overtake by technology. -
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Analysis of Elliptic Curve Cryptography & RSA
In todays digital world, the Internet is an essential component of communication networks. It provides a platform for quickly exchanging information among communicating parties. There is a risk of unauthorized persons gaining access to our sensitive information while it is being transmitted. Cryptography is one of the most effective and efficient strategies for protecting our data and it are utilized all around the world. The efficiency of a cryptography algorithm is determined by a number of parameters, one of which is the length of the key. For cryptography, key (public/private) is an essential part. To provide robust security, RSA takes larger key size. If we use larger key size, the processing performance will be slowed. As a result, processing speed will decrease and memory consumption will increase. Due to this, cryptographic algorithms with smaller key size and higher security are becoming more popular. Out of the cryptographic algorithms, Elliptic Curve Cryptography (ECC) provides equivalent level of safety which RSA provides, but it takes smaller key size. On the basis of key size, our work focused on, studied, and compared the efficacy in terms of security among the well-known public key cryptography algorithms, namely ECC (Elliptic Curve Cryptography) and RSA (Rivets Shamir Adelman). 2023 River Publishers. -
Analysis of error rate for various attributes to obtain the optimal decision tree
The competitiveness and computational intelligence are required to increase the gross profit of the product in a market. The classification algorithm rpart is applied on retail market dataset. The regression rpart decision tree algorithm is implemented with principal component analysis to impute data in the missing part of the dataset. The objective is to obtain an optimal tree by analysing cross validation error, standard deviation error, and number of splits and relative error of various attributes. The results of various attributes by ANOVA method are compared to choose the best optimal tree. The tree with minimum error rate is considered for the optimal tree. Copyright 2022 Inderscience Enterprises Ltd. -
Analysis of factors impacting firm performance of MSMEs: lessons learnt from COVID-19
Purpose: The micro, small and medium scale enterprises (MSMEs) faced various challenges in the ongoing COVID-19 pandemic, making it challenging to remain competitive and survive in the market. This research develops a model for MSMEs to cope with the current pandemic's operational and supply chain disruptions and similar circumstances. Design/methodology/approach: The exhaustive literature review helped in identifying the constructs, their items and five hypotheses are developed. The responses were collected from the experts working in MSMEs. Total 311 valid responses were received, and the structural equation modeling (SEM) approach was used for testing and validating the proposed model. Findings: Critical constructs identified for the study are-flexibility (FLE), collaboration (COL), risk management culture (RMC) and digitalization (DIG). The statistical analysis indicated that the four latent variables, flexibility, digitalization, risk management culture and collaboration, contribute significantly to the firm performance of MSMEs. Organizational resilience (ORS) mediates the effects of all the four latent variables on firm performance (FP) of MSMEs. Practical implications: The current study's findings will be fruitful for the manufacturing MSMEs and other firms in developing countries. It will enable them to identify the practices that significantly help in achieving the firm performance. Originality/value: The previous researches have not considered the effect of organizational resilience on the firm performance of MSMEs. This study attempts to fill this gap. 2022, Emerald Publishing Limited. -
Analysis of Fine Needle Aspiration Images by Using Hybrid Feature Selection and Various Machine Learning Classifiers
Women die of breast cancer most often worldwide. Breast tissue samples can be examined by radiologists, surgeons, and pathologists for evidence of this cancer. Fine needle aspiration cytology (FNAC) can be used to detect this cancer through a visual microscopic examination of breast tissue samples. This sample must be examined by a cytopathologist in order to determine the patient's risk of breast cancer. To determine if a tumor is malignant, the nuclei of the cells must be characterized by their chromatin texture patterns. A machine learning method is used in order to categorize FNA images into two classes, respectively Malignant and Benign. For detecting abnormalities, numerous feature collection methods and machine learning means are applied here. Using features extracted from the FNA image set, UCI machine learning datasets are used to validate the proposed approach. This paper compares three classification methodologies, namely random forests, Naive Bayes, and artificial neural networks, by examining their accuracy, specificity, precision, and sensitivity, respectively. With the ANN and PCA along with the Chi-square selection method, 99.1% of the classifiers are correctly classified. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analysis of Flexoelectricity with Deformed Junction in Two Distinct Piezoelectric Materials Using Wave Transmission Study
Analysis of flexoelectricity in distinct piezoelectric (PE) materials bars (PZT-7A, PZT-6B) with deformed interface in stick over Silicon oxide layer is studied analytically with the help of Love-type wave vibrations. Using the numerical data for PE material, then research achieves the noteworthy fallouts of flexoelectric effect (FE) and PE. The effect of flexoelectricity is compared first between biomaterials of piezoelectric ceramics. Dispersion expressions are procured logically for together electrically unlocked/locked conditions under the influence of deformed interface in the complex form which is transcendental. Fallouts of the research identify that contexture consisting of FE has a noteworthy impact on the acquired dispersion expressions. Existence of FE displays that the unreal section of the phase velocity rises monotonically. Competitive consequences are displayed diagrammatically and ratified with published outcomes. The outcomes of the present research done on both the real and imaginary section of the wave velocity. The comparative study between the two piezo-ceramics bars helps us to understand the properties of one piezo-material over the another and as an outcomes the significance of the present study helps in structural health monitoring, bioengineering for optimizing the detection sensitivity in the smart sensors. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Analysis of food consumption expenditure patterns for developing sustainable business practices
Food consumption patterns are said to be near ideal variable since it is one of the most important commodities that ensure human survival. The patterns within the consumption as well as between different types of food items to different levels of consumption varies with respect to the macroeconomic conditions. The consumption expenditure for cereals, pulses and pulse products, edible oil, milk and milk products, meat, fish and egg, vegetables and fruits, shows an increasing trend in India and in Karnataka. The income elasticity for all food categories are lesser in urban sectors of Karnataka than the rural sector which indicates that the income of the rural households is lesser and the increase in income is also lesser compared to that of the Urban-Karnataka. The business enterprises can aim at sustainable consumption practices through the pricing strategies, product design and distribution channels. 2021 Ecological Society of India. All rights reserved. -
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. -
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 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 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 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 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 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 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 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 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 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..