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The open access movement has become the center of discussion during the last decade. Open access publishing facilitates researchers' and scientists' access to research literature through the internet free of cost. The purpose of this paper is to analyze the awareness of open access publishing among researchers and faculty members of Indian institutions, and to evaluate the development of open access initiatives in India.

This study is based on both primary and secondary sources of data. For studying awareness of open access publishing, a survey was conducted among the researchers of IITs and IIMs in July‐August 2012 by using a closed ended questionnaire. The growth of open access initiatives in India is analyzed through data collected from secondary sources, i.e. the websites of Ulrich's, DOAJ, ROAR, and OpenDOAR.

The results showed that India's contribution has increased in the last few years. It was found that the awareness about such open access information sources and initiatives among the research community is increasing.

This study will assist in understanding the practices of open access publishing in India.

Dynamic economic and emission dispatch (DEED) aims to optimally set the active power generation with constraints in a power system, which should target minimum operation cost and at the same time minimize the pollution in terms of emission when the load dynamically changes hour to hour. The purpose of this study is to achieve optimal economic and emission dispatch of an electrical system with a renewable generation mix, consisting of 3-unit thermal, 2-unit wind and 2-unit solar generators for dynamic load variation in a day. An improved version of a simple, easy to understand and popular optimization algorithm particle swarm optimization (PSO) referred to as a constriction factor-based particle swarm optimization (CFBPSO) algorithm is deployed to get optimal solution as compared to PSO, modified PSO and red deer algorithm (RDA).

Different model with and without wind and solar power generating systems; with valve point effect is analyzed. The thermal generating system (TGs) are the major green house gaseous emission producers on earth. To take up this ecological issue in addition to economic operation cost, the wind and solar energy sources are integrated with the thermal system in a phased manner for electrical power generation and optimized for dynamic load variation. This DEED being a multi-objective optimization (MO) has contradictory objectives of fuel cost and emission. To get the finest combination of the two objectives and to get a non-dominated solution the fuzzy decision-making (FDM) method is used herein, the MO problem is solved by a single objective function, including min-max price penalty factor on emission in the total cost to treat as cost. Further, the weight factor accumulation (WFA) technique normalizes the pair of objectives into a single objective by giving each objective a weightage. The weightage is decided by the FDM approach in a systematic manner from a set of non-dominated solutions. Here, the CFBPSO algorithm is applied to lessen the total generation cost and emission of the thermal power meeting the load dynamically.

The efficacy of the contribution of stochastic wind and solar power generation with the TGs in the dropping of net fuel cost and emission in a day for dynamic load vis-à-vis the case with TGs is established.

Cost and emission are conflicting objectives and can be handled carefully by weight factors and penalty factors to find out the best solution.

The proposed methodology and its strategy are very useful for thermal power plants incorporating diverse sources of generations. As the execution time is very less, practical implementation can be possible.

As the cheaper generation schedule is obtained with respect to time, cost and emission are minimized, a huge revenue can be saved over the passage of time, and therefore it has a societal impact.

In this work, the WFA with the FDM method is used to facilitate CFBPSO to decipher this DEED multi-objective problem. The results reveal the competence of the projected proposal to satisfy the dynamic load demand and to diminish the combined cost in contrast to the PSO algorithm, modified PSO algorithm and a newly developed meta-heuristic algorithm RDA in a similar system.

The current work explores the relationship between workplace ostracism, emotional intelligence (EI) and organizational change cynicism. This paper also aims to examine how dimensions of EI moderate the relationship between workplace ostracism and organizational change cynicism.

This study intends to examine the contribution of independent variable as well as moderating variable towards the outcome. Therefore, Pearson product–moment correlation and moderated regression analyses have been carried out to verify the hypotheses. To validate the tools upon the employees of India, authors have carried out measurement model analyses through AMOS and checked their composite reliability, convergent validity (average variance extraction [AVE]) and discriminant validity (square root of AVE). This study followed a simple random sampling technique with 276 employees (Male: N = 150, Mage = 34.34, female: N = 126, Mage = 31.57) from three manufacturing units of Odisha, an Eastern part of India.

Results showed that workplace ostracism was positively related to organizational change cynicism. However, only two dimensions of EI, namely, appraisal and regulation of self-emotion (ARSE) and other’s emotional appraisal were negatively related to organizational change cynicism. Moderated regression analysis indicates that positive relationship between workplace ostracism and organizational change cynicism is stronger for employees with low ARSE and other emotional appraisals than those with higher scores.

The researchers conclude this paper with inputs for developing a suitable training module on EI, specifically focusing on various emotional management skills.

To the best of the authors’ knowledge, this study is first of its kind on workplace ostracism and organizational change cynicism among Indian employees in the manufacturing sector. This study also examines the moderating role of EI on workplace ostracism and organizational change cynicism, which has been somehow inadequate in the present epoch.

The paper has proposed to implement gray wolf optimization (GWO)-based filter-type proportional derivative with (FPD) plus (1+ proportional integral) multistage controller in a three-area integrated source-type interlinked power network for achieving automatic generation control.

For analysis, a three area interconnected power system of which each area comprises three different generating units where thermal and hydro system as common. Micro sources like wind generator, diesel generator and gas unit are integrated with area1, area2 and area3 respectively. For realization of system nonlinearity some physical constraints like generation rate constraint, governor dead band and boiler dynamics are effected in the system.

The supremacy of multistage controller structure over simple proportional integral (PI), proportional integral, derivative (PID) and GWO technique over genetic algorithm, differential evolution techniques has been demonstrated. A comparison is made on performances of different controllers and sensitivity analysis on settling times, overshoots and undershoots of different dynamic responses of system as well as integral based error criteria subsequent a step load perturbation (SLP). Finally, sensitive analysis has been analyzed by varying size of SLP and network parameters in range ±50 per cent from its nominal value.

Design and implementation of a robust FPD plus (1 + PI) controller for AGC of nonlinear power system. The gains of the proposed controller are optimized by the application of GWO algorithm. An investigation has been done on the dynamic performances of the suggested system by conducting a comparative analysis with conventional PID controller tuned by various optimization techniques to verify its supremacy. Establishment of the robustness and sensitiveness of the controller by varying the size and position of the SLP, varying the loading of the system randomly and varying the time constants of the system.

Now days, various techniques are used for controlling the plants. New ideas are evolving day by day to get better-quality control for various industrial processes to produce high-quality products. Currently, the focus of this research is being emphasized on application of nature-inspired algorithms in control systems. The purpose of this paper is to apply a nature-inspired algorithm called Ant Lion Optimizer (ALO) for the design of proportional-integrator-derivative (PID) controller for an automatic voltage regulator (AVR) system.

For the design of the PID controller, the ALO algorithm is considered as a designing tool for obtaining the optimal values of the controller parameter. All the simulations are carried out in Simulink/MATLAB environment. A comparative study is carried out with some modern nature-inspired algorithm to describe the advantages of this tuning method.

The proposed method has superiority value in transient and frequency domain analysis than the other published heuristic optimization algorithms. The presented approach has almost no variation in transient response when varying time constants of the system parameter, such as exciter, generator, amplifier and sensor from −50 per cent to +50 per cent. In addition, the close loop system is robust against any disturbances such as input–output disturbances and parametric uncertainty, as the sensitivity values are nearly equal to one.

The proposed method presents the design and performance analysis of proportional integral derivate (PID) controller for an AVR system using the recently proposed ALO.