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This paper aims to target tracking in the marine environment is typically obtained by considering the measurement parameters like frequency, elevation and bearing. Marine environmental surveillance provides critical information and assistance for the exploitation and maintenance of marine resources.

With the use of intelligent sensor techniques like Hull-mounted and towed array sensors, convenient, precise and dependable three-dimensional (3D) underwater target tracking is introduced.

This research investigates a method to develop a reliable Unscented Kalman Filter (UKF) algorithm for enhanced underwater target tracking in a 3D scenario by using bearing, frequency and elevation measurements. In applications for underwater target tracking, uncertainty and inaccuracies are typically described by using Gaussian additive noise.

The proposed UKF algorithm is tested and analyzed using 100 Monte Carlo simulations with the Gaussian generated noise.

Marine exploration is becoming an important element of pervasive computing underwater target tracking. Many pervasive techniques are found in current literature, but only scant research has been conducted on their effectiveness in target tracking.

This research paper, introduces a Shifted Rayleigh Filter (SHRF) for three-dimensional (3 D) underwater target tracking. A comparison is drawn between the SHRF and previously proven method Unscented Kalman Filter (UKF).

SHRF is especially suitable for long-range scenarios to track a target with less solution convergence compared to UKF. In this analysis, the problem of determining the target location and speed from noise corrupted measurements of bearing, elevation by a single moving target is considered. SHRF is generated and its performance is evaluated for the target motion analysis approach.

The proposed filter performs better than UKF, especially for long-range scenarios. Experimental results from Monte Carlo are provided using MATLAB and the enhancements achieved by the SHRF techniques are evident.

Nowadays advancement in acoustic technology can be explored with marine assets. The purpose of the paper is pervasive computing underwater target tracking has aroused military and civilian interest as a key component of ocean exploration. While many pervasive techniques are currently found in the literature, there is little published research on the effectiveness of these paradigms in the target tracking context.

The unscented Kalman filter (UKF) provides good results for bearing and elevation angles only tracking. Detailed methodology and mathematical modeling are carried out and used to analyze the performance of the filter based on the Monte Carlo simulation.

Due to the intricacy of maritime surroundings, tracking underwater targets using acoustic signals, without knowing the range parameter is difficult. The intention is to find out the solution in terms of standard deviation in a three-dimensional (3D) space.

A new method is found for the acceptance criteria for range, course, speed and pitch based on the standard deviation for bearing and elevation 3D target tracking using the unscented Kalman filter covariance matrix. In the Monte Carlo simulation, several scenarios are used and the results are shown.

This chapter explores how traditional femininity as a form of emphasized femininity influences single mothers’ decisions to be involved in romantic relationships. It explores how women negotiate the boundaries of emphasized femininity in making their choices related to involvement in romantic relationships.

The data for this study were collected by conducting in-depth interviews with 30 Malaysian Tamil women. They were selected using a purposive sampling method. The main criterion of selection was that participants were Malaysian Indian single mothers identifying Tamil as their mother tongue. Latent and manifest content analyses were used to scrutinize the interviews.

Single mothers identified their responsibilities qua mothers as the most important part of their life. Many have remained single because they were concerned about the well-being of their children. Other than that, many single mothers chose not to be involved in a romantic relationship because it may be stigmatized by their family or community. Involvement in a romantic relationship is seen as a transgression from the notion of traditional femininity, which is a form of emphasized femininity in Tamil society. Motherhood and karpu (chastity) are seen as central to the traditional notion of femininity in Tamil society.

This study contributes to the understanding of how emphasized femininity in a minority group in Malaysia influences single mothers’ decisions about romantic relationships. Furthermore, there are very few studies in Malaysia focusing on the experiences of single mothers from minority ethnic communities.

Presently gender inequality and women's nutrition are the most concerning area of any development policy. Recent empirical evidence emphasizes that gender inequality decreases over time and the on the other hand percentage of overweight (OW) and obesity for women, especially in developing countries, increases over time. However, the relationship between these two phenomena (gender inequality and obesity) has rarely been investigated. Using time series yearly data (1990–2016) from the Nutrition Landscape Information Systems (NLiS) database of World Health Organisation (WHO) for India, we apply standard time series analysis including break test, stationarity test, cointegration test, and vector error correction model (VECM) to estimate the relationship between gender inequalities and percentage of females OW and obese. Our results show that there is a long-run relationship between these variables. Moreover, we also find that a decrease in gender inequality influences the increase in the number of females under OW and obese. In conclusion, the findings of this study reveal that, while elevating the position of women in society may be an important step toward combating the epidemic of OW and obesity, strategies must also tackle unhealthy habits that promote obesity.

The purpose of this paper is to analyze the intensity of transmission of shocks from USA to BRICS countries in the long-run and short-run deviations and swiftness of recovery during US subprime mortgage crisis. This analysis enables the authors to explore the evolving patterns of relationships between these markets and examine whether their co-movements altered either in response to international shocks that originated in advanced markets like USA or due to their domestic fluctuations.

Employing data of daily stock market indices (open and close) of BRICS countries for the period January 2, 2001 to May 31, 2012, this paper examines the interactions and characteristics of price movements of BRICS with US market by applying co-integration tests, vector error correction model and Granger causality relationship. The daily stock market indices data are derived from respective stock exchange web sites.

The results exhibit that both long-run co-integration relationships and short-run Granger causality relationships exist between the stock markets of US-BRICS. Furthermore, this nexus is amplified in the short-run during 2007-2009, when the subprime mortgage financial crisis in the USA cropped up. This finding lends support to the prominence of developed (US) market links in the proliferation of persistent co-movements of BRICS stock markets.

The findings imply an increasing degree of global market integration due to quick dissemination of global shocks originating from developed market like USA, and swift recovery which can be attributed to the increased resilience, consistent with the moderated level of domestically driven risk in the BRICS markets. In spite of their similarities, long-run and short-run interdependences with the US stock market exhibit differences among the BRICS. This can be attributed to the regional heterogeneity in long-run risk and return co-movements with the USA.

Changes from the US index easily affect these stock markets in the short-run, which implies that the US index may act as a leading indicator for investing funds in BRICS markets.

This study would enable the authors to understand whether BRICS economies actually remain resilient to adverse developments in USA and could serve as alternative investment destinations for global portfolio diversification.

Bankruptcy is a financial failure of a business or an organization. Different kinds of bankruptcy prediction techniques are proposed to predict it. But, they are restricted as techniques in predicting the bankruptcy and not addressing the associated activities like acquiring the suitable data and delivering the results to the user after processing it. This situation demands to look for a comprehensive solution for predicting bankruptcy with intelligence. The paper aims to discuss these issues.

To model Business Intelligence (BI) solution for BP the concept of reference model is used. A Reference Model for Business Intelligence to Predict Bankruptcy (RMBIPB) is designed by applying unit operations as hierarchical structure with abstract components. The layers of RMBIPB are constructed from the hierarchical structure of the model and the components, which are part of the reference model. In this model, each layer is designed based on the functional requirements of the Business Intelligence System (BIS).

This reference model exhibits the non functional software qualities intended for the appropriate unit operations. It has flexible design in which techniques are selected with minimal effort to conduct the bankruptcy prediction. The same reference model for another domain can be implemented with different kinds of techniques for bankruptcy prediction.

This model is designed using unit operations and the software qualities exhibited by RMBIPB are limited by unit operations. The data set which is applied in RMBIPB is limited to Indian banks.

A comprehensive bankruptcy prediction model using BI with customized reporting.

Over the next decade, humanity is going to face big environmental problems, and considering these serious issues, businesses are adopting environmentally responsible practices. To put forward specific measures to achieve a more prosperous environmental future, this study aims to develop an environment-based perspective framework by integrating the Internet of Things (IoT) technology into a sustainable automotive supply chain (SASC).

The study presents a conceptual environmental framework – based on 29 factors constituting four stakeholders' rectifications – that holistically assess the SASC operations as part of the ReSOLVE model utilizing IoT. Then, experts from the SASC, IoT and sustainability areas participated in two rigorous rounds of a Delphi study to validate the framework.

The results indicate that the conceptual environmental framework proposed would help companies enhance the connectivity between major IoT tools in SASC, which would help develop congruent strategies for inducing sustainable growth.

This study adds value to existing knowledge on SASC sustainability and digitalization in the context where the SASC is under enormous pressure, competitiveness and increased variability.

The current study aims to analyze the linkage among bank competition, liquidity and loan price in an interconnected bank network system.

The study employs the Lerner index to estimate bank power; Granger non-causality for estimating competition, liquidity and loan price network structure; principal component for developing competition network index, liquidity network index and price network index; and panel VAR and LASSO-VAR for analyzing the dynamics of interactive network effect. Current work considers 33 Indian banks, and the duration of the study is from 2010 to 2020.

Network structures are concentrated during the economic upcycle and dispersed during the economic downcycle. A significant interaction among bank competition, liquidity and loan price networks exists in the Indian banking system.

The study meaningfully contributes to the existing literature by adding new insights concerning the interrelationship between bank competition, loan price and bank liquidity networks. While enhancing competition in the banking system, the regulator should also pay attention toward making liquidity provisions. The interactive network framework provides direction to the regulator to formulate appropriate policies for managing competition and liquidity while ensuring the solvency and stability of the banking system.

The study contributes to the limited literature concerning interactive relationship among bank competition, liquidity and loan price in the Indian banks.