Search results

This paper reports a new technique for achieving optimized design for power system stabilizers. In any large scale interconnected systems, disturbances of small magnitudes are very common and low frequency oscillations pose a major problem. Hence small signal stability analysis is very important for analyzing system stability and performance. Power System Stabilizers (PSS) are used in these large interconnected systems for damping out low-frequency oscillations by providing auxiliary control signals to the generator excitation input. In this paper, collective decision optimization (CDO) algorithm, a meta-heuristic approach based on the decision making approach of human beings, has been applied for the optimal design of PSS. PSS parameters are tuned for the objective function, involving eigenvalues and damping ratios of the lightly damped electromechanical modes over a wide range of operating conditions. Also, optimal locations for PSS placement have been derived. Comparative study of the results obtained using CDO with those of grey wolf optimizer (GWO), differential Evolution (DE), Whale Optimization Algorithm (WOA) and crow search algorithm (CSA) methods, established the robustness of the algorithm in designing PSS under different operating conditions.

This paper aims to examine the enforcement practices of the Investment Dealers Association of Canada (IDA) and argue that self-regulation simply does not work in the financial sector, as the sanctions available are neither applied with sufficient severity nor are the responsibilities for enforcement adequately divided between self-regulation, provincial securities commissions and the police.

The core compliance data for the study came from the IDA’s tribunal cases that were heard between 1984 and June 2008. The theoretical approach involves the invocation of classic articles by the likes of Stigler, Posner and Becker, the essence of whose conclusions is that institutions will act in their own best interests and cannot be expected to act in the public interest.

The findings show that over the period from 1984 to 2008, the severity of the sanctions increased consistently over the period. When penalty ceilings were increased, penalties increased. When in the latter phase of the period, public members (i.e. non-members of the industry) chaired the tribunals, penalties also increased.

Researchers can use the data to write a paper which asks “Why did the IDA tribunal penalties increase so consistently with time?” Future research could canvass various possible explanations, including the one presented in this paper, to focus sustained attention on the issue of self-regulation.

This study is the first to systematically examine the enforcement performance of the IDA.

The purpose of the paper is to evaluate print and electronic resources of TERI’s Library and Information Centre (LIC) with an aim to maximize the net marginal benefits and minimize net marginal costs, without compromising the quality of the library resources.

The parameters considered for analyzing the value of the library resources for this exercise were resource access costs, strategic value of the resource based on subject area coverage, frequency of use, citations, direct and indirect benefits to users. The data regarding these parameters were provided from wide range of sources (both tangible and intangible), to come out with the qualitative and quantitative assessment through an optimization and simulation based model.

Out of the total holdings in TERI LIC that were analyzed, 85 percent of book collections and 63.5 percent of journals were found to be useful for the researchers. The least-used books and journals were identified for weeding to optimize the value of library for users and make space for new and topical library collections.

A sample of data sources out of the total library collections was defined for the evaluation.

The paper demonstrates the value of library resources that is of critical importance to libraries for an effective and efficient delivery of services for generating future knowledge. Evaluating the value of libraries resources has implications both for librarians as well as library users.

The evaluation exercise established the efficacy of the TERI library holdings for research and academic purposes in the domain of sustainable development. The library collection was found to be cost effective and beneficial to meet the future demand from the user community.

The effect of throughflow and Coriolis force on convective instabilities in micropolar fluid layer heated from below for free‐free, isothermal and micro‐rotation free boundaries is investigated. Calculations are made using a lower order Galerkin approximation to solve the eigenvalue problem for stationary instability. It is observed that both stabilizing and destabilizing factors due to constant vertical throughflow can be enhanced by rotation.

This paper aims to study the anti-diabetes activity of the Kombucha prepared from different snake fruit cultivars.

The juices of snake fruits of Suwaru, Madura, Pondoh and Bali cultivars were fermented for 14 days. Anti-diabetes activity of the products was analyzed. Twenty-four male albino Wistar rats were used and randomly divided into six experimental groups, i.e. four groups of the diabetic rats treated with the Kombucha, plus the normal group and diabetic control group. The Kombucha were orally administered to the streptozotocin induced-diabetic rats at 5 mL/kg body weight per day during the 28-day experiment. The fasting plasma glucose (FPG), oxidative stress indices (superoxide dismutase [SOD] activity and Malondialdehyde [MDA] level) and lipid profile of the blood plasma were measured. The pancreas was used for immunohistochemical study and β-cells quantification. Data were analysed by ANOVA followed by Fisher test using Minitab version 16.0.

FPG of the diabetic rats treated with the Kombucha (110.3-189.3 mg/dL) was significantly lower (p = 0.000) than the diabetic control group (413.3 mg/dL). Those were in line with the number of pancreatic β-cells of 42.1 in diabetic rats that lower (p = 006) than those in treated the diabetic rats (61.2-73.5). The treated diabetic rats had lower oxidative stress (SOD activity: 20.9-44.6 unit/100 µL with p = 0.000; MDA level: 0.37-0.48 ng/100 µL with p = 0.000) than those in the diabetic rats (SOD activity: 18.7 unit/100µL; MDA level: 0.84 ng/100 µL). The treated diabetic rats also showed better lipid profile than those in the diabetic control rats. There were cultivar differences, and the Suwaru and Madura snake fruit Kombucha demonstrated the most potential for diabetes management.

This is the first study on in vivo anti-diabetes activity of snake fruit Kombucha prepared from different snake fruit cultivars.

The study aims to carry out predictive modeling based on publicly available COVID-19 data for the duration April 01, 2020 to June 20, 2020 pertaining to India and five of its most infected states: Maharashtra, Tamil Nadu, Delhi, Gujarat and Rajasthan.

The study leverages the susceptible, infected, recovered and dead (SIRD) epidemiological framework for predictive modeling. The basic reproduction number R0 is derived by an exponential growth method using RStudio package R0. The differential equations reflecting the SIRD model have been solved using Python 3.7.4 on the Jupyter Notebook platform. For visualization, Python Matplotlib 3.2.1 package is used.

The study offers insights on peak-date, peak number of COVID-19 infections and end-date pertaining to India and five of its states.

The results subtly indicate toward the amount of effort required to completely eliminate the infection. It could be leveraged by the political leadership and industry doyens for economic policy planning and execution.

The emergence of a clear picture about COVID-19 lifecycle is impossible without integrating data science algorithms and epidemiology theoretical framework. This study amalgamates these two disciplines to undertake predictive modeling based on COVID-19 data from India and five of its states. Population-specific granular and objective assessment of key parameters such as reproduction number (R0), susceptible population (S), effective contact rate (ß) and case-fatality rate (s) have been used to generate a visualization of COVID-19 lifecycle pattern for a critically affected population.

The prime objective of this paper is to design a green supply chain management (GSCM) framework to evaluate the performance of environmental-conscious suppliers using multi-criteria decision-making (MCDM) approach.

The literature survey reveals critical factors for implementing GSCM, adopted methodologies and the result obtained by several researchers. Data have been collected by conducting surveys and interviews with strategic-level personnel of five esteemed organizations in automobile manufacturing sectors. A GSCM framework is developed in which a mathematical tool entropy–the technique for order of preference by similarity to ideal solution (TOPSIS) has been used to analyze the six parameters of automobile manufacturing unit. Initially, entropy is used to find the weights of each of the parameters that influence the decision matrix of the TOPSIS method. Secondly, the proposed GSCM framework ranks the supplier. Finally, sensitivity analysis of the model satisfies the GSCM framework and benchmarked the supplier.

The result shows that “Total CO₂ emission” has an influential role for GSCM sustainability, and hence, firms should put more effort to reduce emissions to improve overall performance. Again, the parameters like investment in R&D and total waste generation may be ignored in the selection process. The result reveals the benchmarked supplier and its strategies for effective sourcing, which would have an indirect effect on organizations' overall sustainability.

This research entirely focuses on sustainability within supply chain considering economic, social and environmental paradigms. The mathematical modeling of the proposed work considers many influential parameters and provides an easy and comprehensive decision-making technique.

The methods may be adopted by the industries for sustainable supply chain management. This study benchmarks the supplier organizations and explores the adopted policies by benchmarked organizations. Other organizations should follow the policies followed by benchmarked organization for enhancing environmental, social and economic performance. Organizations striving for sustainable development can adopt this framework for evaluation of supplier performance and benchmark with better accuracy.

The design of the GSCM framework explores both the qualitative and quantitative data based on environmental, social and economic parameters simultaneously in the evaluation of environmentally conscious suppliers. The research also investigates the constraints of the system to implement the GSCM in automobile manufacturing unit. Additionally, the sensitivity analysis justifies the benchmarked supplier and the adopted strategies to be followed by other manufacturing unit.