Oscillations in power system aggravations day by day with uncertainty in load variations and disturbances such as renewable penetrations. The present study proposes deployment of steam governors to supper oscillations in power system. The steam governor is equipped with fractional compensated lead lag action, where the gains are set by improved salp swarm algorithm (ISSA). The ITAE based objective function being considered with the remote signal speed deviation of generator taken as input for controller action. Sudden and discrete variations in reference voltage to generator, load and plug in electric vehicles (PEV) have been the source of low frequency oscillations and proposed steam governor being employed to suppress these oscillations. The tunning efficacy of ISSA has been contrasted with PSO and SSA techniques. The variations in speed have been analyzed for different disturbances with system eigen distributions and justification of proposed action has been established. Low frequency modelling of power system along with steam governor has been taken at an initial operating state. Time domain simulations have been carried out to analyses system behavior and it has been observed that proposed approach is much effective to oscillation suppression in power system.
The mechanism towards generation of query evaluation plans particularly in distributed database system can be referred to as optimization of distributed queries. In fact the schema and queries can be linked to logical portions of data. The performance of the system especially in distributed database environment, are dependent on query evaluation plans and cost of queries. Usually, in the distributed database systems, as the queries linked to datasets may be accumulated in several heterogeneous locations, it can enhance the accessibility of inter query plans prioritizing the query execution strategies. In fact, the enhancement of size of clusters also depends on the voluminous data linked with the databases. Accordingly, to make better performance on query execution, suitable optimization criteria can be adopted so that the dependability of query plans can be preserved as well as searching abilities of local and global optimal query plans can be observed. In this work, the heuristic algorithm is implemented to manage the size of the databases in distinct locations with stored voluminous data. The main aim of the proposed algorithm implemented in this work is to focus on search capabilities both locally and globally to minimize the difficulties of linking the criteria while obtaining optimality. As a result, the query plans can be generated with minimal execution cost with better efficiency.
Human resource development requires more than ethical intent to be sustainable; it depends on institutional architecture that supports long-term capability formation. Although value-based leadership research often assumes that morally grounded leaders directly create sustainable organisational systems, the mechanisms through which leadership philosophy translates into structured HR sustainability remain underexplored. At the same time, entrepreneurship research highlights that sustainable venture performance, innovation, and firm growth depend on the development of underlying organisational capabilities rather than leadership intent alone, yet the integration between leadership capability and entrepreneurial outcomes remains underexplored. Drawing on the Resource-Based View and Knowledge-Based View, this study conceptualises Indian Knowledge System-inspired Leadership Practices (IKSLP) as a higher-order leadership capability encompassing ethical stewardship, service orientation, spiritual purpose, and reflective self-regulation. Using survey data from 250 managers and Partial Least Squares Structural Equation Modelling, the study examines whether IKSLP influences Sustainable Human Resource Development (SHRD) directly or through Leadership Development Effectiveness (LDE). The model is further conceptually extended to link sustainable HR capability with entrepreneurial outcomes such as innovation, firm performance, and long-term venture sustainability. The findings reveal full mediation: IKSLP significantly influences LDE, LDE significantly influences SHRD, and the direct effect of IKSLP on SHRD is not significant. From an entrepreneurship perspective, the findings suggest that entrepreneurial success emerges through institutionalised capability-building systems supporting innovation, adaptability, and scalable growth, particularly in SME and emerging economy contexts.
Integrating insights from political ecology and intersectionality, this study analyzes the Hindi-language Bollywood film Kaun Kitney Paani Mein to explore the political ecology of water crises and related issues of power, control, inequity, and struggles. The 2015 Indian film examines water scarcity and its socio-economic and cultural implications in rural India, focusing on two fictional villages—Upri, a formerly prosperous high-caste community now facing acute water scarcity, and Bairi, an initially marginalized low-caste village that has flourished through sustainable water management. While the film underscores the transformative role of water as a vital resource, it also enacts the complex dynamics of how class, caste, and resource inequality subvert the social equity of water. Employing satire, the film highlights the interdependence between water resources and community well-being, illustrating how effective leadership and water management can bridge socio-economic divides, and foregrounds water-related challenges embedded within broader questions of development and governance. However, the film’s underdeveloped political-ecological framework, marked by its limited engagement with state power, governance, feminine agency, and its reliance on romantic interpersonal resolution, dilutes its potential as a robust intersectional climate critique.
Urban growth and demographic changes have significantly influenced land use and land cover (LULC) patterns, highlighting the importance of monitoring these changes for sustainable urban planning. This study investigates and predicts LULC changes in Alipurduar, India, over three decades, focusing on 2001–2021 and forecasting 2031 changes using the Cellular Automata Markov (CA-Markov) Chain approach in QGIS. Artificial Neural Network (ANN) classifications were performed on Landsat 7 and 8 imagery using the Google Earth Engine (GEE) platform to analyze historical LULC patterns. Spatial variables, including elevation, slope, distance from roads, and distance from water bodies, were incorporated into the ANN transition submodel to assess their influence on LULC changes. The findings reveal a substantial increase in urban land use, growing from 40 % of the total area in 2001 to 55 % in 2021, primarily at the expense of vegetation cover and water bodies. The CA-ANN model demonstrated robust predictive capability, with a kappa coefficient of 0.79 and an overall accuracy of 0.81, outperforming alternative models in predicting LULC distribution for 2021. Using this validated model, future simulations indicate that urban expansion will continue and that natural resources, including vegetation and water bodies, will further decline by 2031. This analysis provides valuable insights into the dynamics of urbanization in Alipurduar and underscores the need for proactive measures to balance development and ecological conservation. The results serve as a foundation for comparative studies and offer critical data to guide sustainable urban planning and resource management in the region.
