Context and Scope of Social Work Interventions in Perinatal Mental Health Settings in India

The perinatal period may not be a happy time for all mothers. During this period, some may develop psychiatric complications, which have both biological and psychosocial etiology, and such illness may affect the whole family. Psychosocial aspects may trigger the illness and act as risk and maintaining factors. Social workers need to intervene in this context for optimal functioning of women with perinatal mental health issues and her family. A biopsychosocial framework may be adopted for social work assessment and intervention. Individual, familial, group, and community level intervention is required to address this complex issue, along with other mental health clinicians.     

Particle swarm optimization based Liu-type estimator

In this study, a new method for the estimation of the shrinkage and biasing parameters of Liu-type estimator is proposed. Because k is kept constant and d is optimized in Liu’s method, a (k, d) pair is not guaranteed to be the optimal point in terms of the mean square error of the parameters. The optimum (k, d) pair that minimizes the mean square error, which is a function of the parameters k and d, should be estimated through a simultaneous optimization process rather than through a two-stage process. In this study, by utilizing a different objective function, the parameters k and d are optimized simultaneously with the particle swarm optimization technique.     

A new per-field classification method using mixture discriminant analysis

In this study, a new per-field classification method is proposed for supervised classification of remotely sensed multispectral image data of an agricultural area using Gaussian mixture discriminant analysis (MDA). For the proposed per-field classification method, multivariate Gaussian mixture models constructed for control and test fields can have fixed or different number of components and each component can have different or common covariance matrix structure. The discrimination function and the decision rule of this method are established according to the average Bhattacharyya distance and the minimum values of the average Bhattacharyya distances, respectively. The proposed per-field classification method is analyzed for different structures of a covariance matrix with fixed and different number of components. Also, we classify the remotely sensed multispectral image data using the per-pixel classification method based on Gaussian MDA.     

The effect of large controlling shareholders on equity prices in France: monitoring or entrenchment?

Journal of Management and Governance - The corporate governance literature has shown that firms with better governance exhibit higher abnormal returns. In this paper, we examine the effect of cash...     

Multilevel estimation of normalization constants using ensemble Kalman–Bucy filters

Statistics and Computing - This paper presents tests to formally choose between regression models using different derivatives of a functional covariate in scalar-on-function regression. We...     

Time-series forecasting with a novel fuzzy time-series approach: an example for Istanbul stock market

Artificial intelligence procedures such as artificial neural networks (ANNs), genetic algorithms and particle swarm optimization and other procedures such as fuzzy clustering have been successfully used in the various stages of different fuzzy time-series forecasting approaches. Fuzzy clustering, genetic algorithm and particle swarm optimization are generally used in the fuzzification stage, and this simplifies the applicability of this stage and makes the fuzzy time-series approach more systematic. ANNs have also been applied successfully in the fuzzy relationship determination stage. In this study, we propose a new hybrid fuzzy time-series approach in which fuzzy c-means clustering procedure is employed in the fuzzification stage and feed-forward neural networks are used in the fuzzy relationship determination stage. This study also includes an empirical analysis pertaining to the forecasting of Index 100 for the stocks and bonds exchange market of Istanbul.     

Preventing Religious Radicalization in Bosnia and Herzegovina: The Role of the BiH Islamic Community

The goal of the paper is to identify the Islamic Community’s methods of preventing religious radicalization in Bosnia and Herzegovina (BiH). The roots of radicalism and extremism are explained by examining “Islamic revival” and studied within the Bosnian context. Although BiH appears in many international reports as a potential “cradle of terrorism”, the situation on the ground is quite different and there are many instances of combined efforts by the government and religious institutions in preventing religious radicalization in BiH. The analysis focuses on the Islamic community’s efforts to contend the spread of illegal mosques that sometimes promote radical Islam in BiH. Although there are radical individuals with different and sometimes radical understanding of Islam, the majority of Bosnian Muslims oppose any form of religious radicalization. The Islamic Community plays the most important role in preventing the spread of radical Islam in BiH, and this paper analyzes its efforts to homogenize Bosnian Muslims and prevent radicalization.     

An integrated hybrid approach to the examination timetabling problem

This paper is derived from an interest in the development of automated approaches to tackle examination timetabling problems effectively. We propose a hybrid approach that incorporates effective heuristic operators within the great deluge algorithm. The latter was chosen because of consistently good performances being reported within the examination timetabling research domain. The additional heuristic procedures further enhance the overall effectiveness of this integrated hybrid approach. These procedures are drawn from methodologies that have appeared in the literature under term the “electromagnetic-like mechanism”. The aim is to move sample points towards a high quality solution while avoiding local optima by utilising a calculated force value. This value, which is calculated dynamically, is treated as a decay rate in determining the level within the great deluge algorithm. To evaluate the proposed algorithm, we carry out experimental work on two types of examination timetabling datasets. All the related results and analysis obtained illustrate that this hybrid approach is effective when compared with existing approaches in the literature.