Search results

Green supply chain (GSC) modelling is still evolving, yet according to the literature, there is no standard and comprehensive approach for modelling GSCs. This chapter attempts to examine this remarkable gap in research by proposing a standard approach for industrial supply chain (SC) modelling, which allows integrating all relevant environmental constraints. This new approach is inspired from other methodologies proposed earlier regardless of their area of study and implemented via a case study in fish canning industry. The steps of the proposed approach are based on Artificial Intelligence (AI), which has become a mainstream trend nowadays. The proposed approach may help managers and researchers and could provide a guideline for GSC modelling.

The national health policy should strive towards achieving the concept of “healthcare for all” conceptualized by the World Health Organization (WHO) through health insurance scheme. The purpose of this paper is to identify and discuss the various gaps affecting the health care systems and to evolve strategic issues in health care in India through an exploratory survey.

The main thrust is to analyze the problems of India's health care system and review of related literature, to identify the areas in the field of healthcare and health insurance which are unexplored or need to be tapped. This evaluation would give ample data to reinforce these areas and would lead us ultimately to the pre‐set target of WHO.

India's march to prosperity faces a serious risk of slowing down due to the main reason – lack of proper access to health care due to the absence of a well laid out public policy. Therefore, the key stakeholders of the health insurance industry jointly need to build a robust health insurance system and help to bridge the gap that exists in reaching quality healthcare in India. A review of the health policy for modifications and to implement it successfully through health insurance without road blocks is called for.

The results of this study, it is hoped, will outline equity in health care, which matters to every Indian citizen and how it can be achieved in India.

This paper suggests the adoption of an approach of management science called the gaps model of service quality in dealing with India's healthcare system problems, a new indicator aimed at assessment of the deficit in access to health services through a structured integrated way. The strategy takes account of the significant gaps identified to suggest new pragmatic methods to close the gaps.

The exponential growth of artificial intelligence (AI) technologies, coupled with advanced algorithms and increased computational capacity, has facilitated their widespread adoption in various industries. Among these, the financial technology (FinTech) sector has been significantly impacted by AI-based decision-making systems. Nevertheless, a knowledge gap remains regarding the intricate mechanisms behind the micro-decision-making process employed by AI algorithms. This paper aims to discuss the aforementioned issue.

This research utilized a sequential mixed-methods research approach and obtained data through 18 interviews conducted with a single FinTech firm in France, as well as 148 e-surveys administered to participants employed at different FinTechs located throughout Europe.

Three main themes (ambidexterity, data sovereignty and model explainability) emerge as underpinnings for effective AI micro decision-making in FinTechs.

This research aims to minimize ambiguity by putting forth a proposition for a model that functions as an “infrastructural” layer, providing a more comprehensive illumination of the micro-decisions made by AI.

This research pioneers as the very first empirical exploration delving into the essential factors that underpin effective AI micro-decisions in FinTechs.

Traditionally, industrial power supplies have been exclusively controlled through analog control to sustain high reliability with low cost. However, with the perpetual decrement in cost of digital controllers, the feasibility of a digitally controlled switch mode power supply has elevated significantly. This paper aims to outline the challenges related to the design of digital proportional-integral (PI) controlled synchronous rectifier (SR) buck converter by comparing controller performance in continuous and discrete time. The trapezoidal approximation-based digital PI control is designed for low voltage and high-frequency SR buck converter operating under continuous conduction mode.

The analog and digital controller are designed using a SISO tool of MATLAB. Here, zero-order hold transform is used to convert the transfer function from continuous to discrete time. Frequency and time domain analysis of continuous plant, discrete plant and close loop system is performed. The designed digital PI control is simulated in MATLAB Simulink. The simulated results is also verified on hardware designed around digital signal processing control.

The continuous and discrete control loops are validated with multiple tests in the time and frequency domain. The detailed steady state theoretical analysis and performance of the SR buck converter is presented and verified by simulation. It is found that the delay in digital control loop results in a low phase margin. This phase margin decreases with higher bandwidth. The hardware experiments with the digital control loop are carried out on a 10 W prototype. The chosen parameters for the SR buck converter are found to be optimum for steady and transient state response.

This paper compares the digital and analog control approach of compensator design. It focuses on the implications created at the time of transforming the control design from continuous to discrete time. Further, it also focuses on the selection of parameters such as phase margin, bandwidth and low pass filter.

Adaptive equalization plays an important role in digital communication to reduce the distortions due to inter-symbol interference. An adaptive filter is used as an equalizer model in channel equalization. An adaptive algorithm is the heart of the adaptive filter which finds the optimum coefficients of the filter. The choice of the adaptive algorithm improves the convergence rate and minimizes the mean square error (MSE). This paper aims to propose a cat swarm optimization (CSO)-based adaptive algorithm and its modification to improve the performance of a channel equalizer.

The input digital training data are transmitted through different channel conditions. A linear transversal filter is used as a channel and equalizer model. The equalizer coefficients are trained by the proposed simplified cat swarm optimization (SCSO) algorithm to find the estimated digital training data.

The performance of the proposed SCSO algorithm is compared with particle swarm optimization (PSO)-based channel equalization. The improvement in convergence rate and MSE is verified under linear and nonlinear channel conditions with different delay spreads. The optimum parameters of the SCSO are found using simulation-based sensitivity analysis.

This paper analyzes a CSO algorithm for adaptive channel equalization and proposes a SCSO algorithm to identify the optimum coefficients of a transversal equalizer. The seeking mode process is simplified in the proposed SCSO to achieve better performance in channel equalization. The proposed SCSO algorithm guarantees minimum MSE in all independent runs, whereas in PSO, few misses are possible.

The purpose of this paper is to minimize corrosion-related pollution in the environment. From the lemongrass extract (LGE), the authors selected one of the best green inhibitors.

The corrosion and inhibition of mild steel in traditional acidification solutions were estimated by electrochemical measurements. The corrosion appearance was observed with scanning electron microscopy, atomic force microscopy micrographs and attenuated total reflectance infrared spectroscopy spectrum. The correlation was formed between the gained inhibition efficiency (IE)% from electrochemical measurements and certain quantum chemical parameters.

The results displayed that the IE was up to 90% when the LGE concentration was 300 ppm. The results confirmed that the theoretical experiments are very similar to the experimental observations.

For the first time, LGE was used as a cheap and safe corrosion inhibitor for mild steel corrosion in the acidification process. The mechanism of mild steel corrosion and anti-corrosion in acid solution has been suggested.

Static VAR compensators (SVC) have been recognized to be one of the most important flexible AC transmission systems devices used for mitigating the low-frequency electrochemical oscillations occurring in the system and for reactive power compensation, thereby improving the overall dynamic stability and efficiency of the system. The purpose of this paper is to optimize and dynamically tune the control parameters of the classical proportional integral and derivative (PID) controller of the SVC for a two-machine system by designing a new robust optimization technique.

The angular speed deviation between the two machines is used as an auxiliary signal to SVC for generation of the required damping output. To justify the efficacy of the system undertaken, a light load fault at time t =1 s is projected to the system. The simulation is carried out in MATLAB/Simulink architecture.

The proposed technique helps in the enhancement of system efficiency, reliability and controllability and by effectively responding to the non-linearities taking place in a power grid network. The results obtained are indicative of the fact that the proposed modified brain storming optimization (MBSO) technique reduces system disturbances very quickly, increases the system response in terms of better rise time, settling time and peak overshoot and improves the efficiency of the system.

A detailed comparison of the MBSO technique is compared with the conventional brain storming optimization (BSO) and PID technique. Total harmonic distortion through fast Fourier transform is also compiled to prove that the values of the proposed MBSO method found out to be confined well within the prescribed IEEE-514 boundaries.

This study looked at the impact of a community-based public health campaign on hypertension and diabetes mellitus awareness and prevention, as well as student experiential learning in a campaign conducted by pharmacy students.

A convenience sampling cross-sectional pre–post survey was done to assess disease awareness and knowledge among those who attended the health campaign. The data analysis includes a total of 230 participants with complete data. After the campaign, the pharmacy students used self-assessment to reflect their learning experience.

Most participants were unaware of their blood pressure and blood glucose readings, but they reported improved awareness of diseases and prevention of hypertension and diabetes after the health campaign. Although most participants correctly identified the common signs and symptoms of hypertension, few could associate it with overweight. Most participants were unaware of the 5 g per day salt intake limit for controlling hypertension before the campaign. Most participants were less aware that diabetes is associated with impaired vision, peripheral neuropathy, renal and heart diseases. Students expressed increased confidence in leadership, teamwork and communication abilities after the campaign based on self-assessment.

A health campaign enhances the disease knowledge of the general public. It has been suggested that experiential learning be encouraged in the pharmacy curriculum.

This study adds to the knowledge on the roles of community-based health campaigns and the value of pharmacy students’ involvement in experiential learning.

The purpose of this paper is to explore illness beliefs among adults with type 2 diabetes (T2DM), studied in a clinical setting in the Indian context. Diabetes management lies primarily in the hands of the patient, which signifies the need for understanding the various dimensions of individuals’ illness beliefs. While past research from abroad has stressed the need for understanding the patient’s perspective in effective illness management, the lack of studies in the Indian context calls for further research in this area.

Drawing on the Self-Regulation Model (Leventhal et al., 1980), semi-structured interviews were carried out to understand the beliefs about diabetes among individuals diagnosed to have T2DM. In total, 70 individuals with T2DM were included, taking into account the disease duration, urban-rural, age and gender distinctions. The data were analyzed using content analysis method.

The results of the analysis revealed numerous sub-themes related to the perceived consequences of diabetes, control or cure issues, timeline and emotional issues as experienced by the subjects.

Carrying out a triangulated research with the various stakeholders, namely, diabetologists, general practitioners and other support staff like dieticians could add more value to this exploratory study.

There is a dearth of research work that explores the illness beliefs that patients’ hold about diabetes, as discussed in the Indian context. It is expected that the insight provided by the study can help the government bodies, healthcare organizations and practitioners design and develop interventions from a patient-centric view. Additionally, such a patient-centric approach will enable individuals to achieve their treatment goals.

This study aims to design a facility network for the weavers to do direct business in the Indian handloom industry by using tourists as potential customers.

Data from 4,001 weavers of the handloom industry and 82 tourist locations of Varanasi city were collected. This data was analysed using the k-mean and elbow methods to determine the locations and the optimal number of collection centres, selling stores and warehouses to provide opportunities for the weavers to do direct business.

The study's findings showed that a greater opportunity could be provided with four optimal collection centres and selling stores, along with two warehouses in the handloom industry of Varanasi city. These results provide valuable guidance for policymakers to plan the Varanasi handloom network of facilities efficiently and effectively to improve the conditions of weavers.

Determining the optimal locations is crucial for designing a facility network. The proposed network will aid the government and policymakers in comprehending and pinpointing potential sites to establish new facilities in the handloom industry in Varanasi, a city with tourism potential.