Research News

The Department of Electrical and Electronics Engineering is glad to announce that Dr Ramanjaneya Reddy, Assistant Professor; his students, Mr Rahul Kotana and Ms SK Hima Bindu have published a paper titled “High Gain Boost Converter Fed Single-Phase Sine Pulse Width Modulated Inverter” in the journal ‘International Journal of Renewable Energy Research’ having a Scopus site score of 4.2.

Abstract of the Research

A high gain boost converter fed single-phase voltage source inverter with its control for DC to AC power conversion in uninterrupted power supply and renewable energy applications is presented in this paper. The conventional DC-DC boost converter with a coupled inductor and switched capacitor is utilised to obtain high gain. Further, the output voltage of the inverter is controlled by the sinusoidal pulse width modulation technique. The detailed design and analysis of a high gain boost converter fed single-phase voltage source inverter is presented. The sine pulse width modulation control scheme for the voltage source inverter is also developed and presented. To validate the high gain boost converter fed single-phase voltage source inverter, the simulation model is developed in the LTspice software environment, and the results are validated. The results show high gain boost converter achieves a gain of about 10 and the single-phase voltage source inverter can provide an rms voltage of 228 V without using the step-up transformer. The total harmonic distortion of output current is found to be below 4.

About the Research

Energy is an essential factor for the functioning and economic development of the industrialized world. It plays a key role in our day-to-day life. On the other hand, energy management has become a critical factor for our successive economic prosperity. The energy consumption process frequently needs either DC-AC conversion or AC-DC conversion. The DC-AC conversion finds its major application in uninterrupted power supply (UPS) and renewable energy (RE). To supply during power outages, most UPS systems use batteries, usually lead-acid, as the storage mechanism. The battery is supposed to provide the backup in the absence of the grid supply. However, the voltage provided by the battery alone may not be enough to provide the backup. At first, the battery output power which is DC needs to be converted to AC with the help of an inverter. Apparently, the output of the inverter needs to be stepped up with the help of a step-up transformer to achieve an output of 220V 50Hz. An alternative approach to the same process is by using a power electronic converter called the DC-DC boost converter. The boosting of battery/PV voltage can be achieved with the help of a standard boost converter as shown in Fig. 1(b), or by using a battery capable of supplying higher voltage and a step-up transformer as shown in Fig. 1(a). High power batteries and step-up transformers can be eliminated if a high gain boost (HGB) converter is used instead of a standard boost converter. The HGB converter fed DC-AC conversion system is presented in this paper which eliminates the step-up transformer. The circuit configuration of the proposed work is depicted in Fig. 2.

Practical Implementations of the Research

The DC-AC conversion method proposed is based on the HGB converter fed single-phase SPWM inverter. The proposed model is best suited when a low voltage DC supply is available, and a standard 230V AC output is needed to deliver the load. The detailed design and analysis of the HGB converter are carried out, and the gain of the converter is achieved at around 10, which is very high compared with conventional boost converter topologies. A unipolar SPWM control scheme is developed in LTspice to control the single-phase VSI. The simulation results of the complete DC-AC conversion system are in close agreement with the design parameters. Further, the total harmonic distortion of the output current waveform is around 4% which is well below the international standards. In addition, the complete model consisting of both HGB converter and single-phase VSI are successfully simulated for an input of 36 V DC and produced an rms output voltage of 228 V.

In future, the DC-AC conversion method based on a high gain boost converter can be extended with the three-phase voltage source inverter with electric drive applications.

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“The correct analogy for the mind is not a vessel that needs filling, but wood that needs igniting” – Plutarch

Where would you go to get the most appropriate feedback to improve your learning? Whom would you approach? An active learner requires continuous assessment. Exposure to relevant remarks can make a significant impact in the learning output. Choosing the right source of feedback is important to locate your position in the learning ecosystem. This is where C-SMILE enters the frame.

The Department of Computer Science and Engineering is delighted to inform you that the patent application (202241010415) entitled ‘Classification of Student’s Misconceptions in Individualized Learning Environments (C-SMILE)’ got published. The patent application was submitted by Associate professor Dr Sobin C C and BTech final year student Meka Varsha as part of the Capstone Project.

C-SMILE is an innovative platform which allows students to take assessment and receive feedback based on their performance and misconceptions. This targets to refine their conceptual and individualised learning. The platform offers the benefits of automated identification of misconceptions and classification of their level of conceptual clarity. This eventually leads to pertinent feedbacks and ensures quality learning. It also helps engineering educators to classify their students into different categories based on their level of conceptual clarity. Short quizzes and multi-level assessments can utilise the objective of this platform.

Dr Sobin C C and Meka Varsha have collaborated with Mr Subheesh N P from IIT Madras and Mr Jahfar Ali from IIT Hyderabad as part of this work. The team has already published 2 conference papers. One of them is in the prestigious IEEE Global Engineering Education Conference (EDUCON 2022), which is the flagship conference of IEEE Education Society.

The researchers are now working on to extend this concept to incorporate Bloom’s taxonomy to formulate more specific questions based on their level in the cognitive domain.

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Publishing a paper in the second-best journal in the discipline of Environmental Engineering and having an impact factor of 9.7 is obviously a significant achievement. The Department of Environmental Science is elated to inform you that the paper, “Dynamic Simulation and Optimization of Anaerobic Digestion Processes using MATLAB” has been published by Dr Karthik Rajendran, Assistant Professor of Environmental Science, and his PhD student, Mr Prabhakaran G in ‘Bioresource Technology’ journal.

Abstract of the research

Time series-based modelling provides a fundamental understanding of process fluctuations in an anaerobic digestion process. However, such models are scarce in literature. In this work, a dynamic model was developed based on modified Hill’s model using MATLAB, which can predict biomethane production with time series. This model can predict the biomethane production for both batch and continuous processes, across substrates and at diverse conditions such as total solids, loading rate, and days of operation. The deviation between the literature and the developed model was less than ±7.6%, which shows the accuracy and robustness of this model. Moreover, statistical analysis showed there was no significant difference between literature and simulation, verifying the null hypothesis. Finding a steady and optimized loading rate was necessary from an industrial perspective, which usually requires extensive experimental data. With the developed model, a stable and optimal methane yield generating loading rate could be identified at minimal input.

About the research

Anaerobic Digestion (AD) is a natural process that converts organic waste into biogas, in the absence of oxygen, which can be used as cooking fuel or for electricity generation. Biogas generation depends on various operational parameters of the AD processes like temperature, organic loading rate, and pH. For example, the speed of a car depends on various parameters like mileage per litre, type of fuel (petrol or diesel), engine power, type of gear, and road type. The optimum speed of a car can be defined by the manufacturer. Likewise, the optimum biogas/ biomethane can be calculated by computer simulations. If the loading rate is increased, the biogas yield increases up to a particular time and then decreases due to overloading like human bodies (eating a large amount of food may strain or cause failure of the digestive system), then the biogas plant will be a failure.

Optimising the loading rate through experiment was not easy, as multiple trials were necessary and it will take a longer time and high cost. In this work, the researchers did the optimisation based on the loading rate over the time period. The loading rate was optimised to maximum methane production, which also showed the region of stability from an operational perspective.

Practical implementations of the research

The practical implications of this work are, to use it in real-time operations of an AD plant and in research laboratories to estimate the best region of operation in terms of loading rate and yield. This work shows that longer days of operation could optimise better loading rates or could help in reaching a steady-state condition in real-time biogas plants.

Future research plans

Real-time biogas plants are deficient in the availability of data to do the computer simulation by using the mathematical model. To overcome this problem, researchers are planning to do Artificial Intelligence (Machine learning)- based biogas prediction by data-driven techniques. It will reduce the complexity with higher accuracy. In future, the machine learning model will integrate with real-time bioreactor for self-diagnosis and better decision making.

 

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The Department of Physics is happy to announce that Prof Ranjit Thapa and his PhD Scholar Mr Samadhan Kapse have published a paper titled “Supercapacitor electrodes based on quasi-one-dimensional van der Waals TiS3 nanosheets: experimental findings and theoretical validation” in the Nature indexed journal ‘Applied Physics Letters’ having an impact factor of 3.79. The Paper is published in collaboration with Abhinandan Patra and Chandra Sekhar Rout from Jain University and Dattatray J Late from Amity University.

Abstract of the Research

To cease the ever-increasing energy demand, additional enthusiastic focus has been given to generate more sustainable energy from alternative renewable sources. The storage of these energies for future usage solely depends on the energy storage devices. A diversity of electrode materials based on two-dimensional (2D) transition metals and their derivatives have enticed the whole world owing to their tunable properties. Transition metal trichalcogenides (TMTCs- MX3 type) is the emergent class of 2D materials that gathered a lot of interest because of their quasi-one-dimensional anisotropic properties with the van der Waals force of attraction in between the layers. Herein, TiS3 being an MX3-type of material is preferred as the electrode for supercapacitor application with detailed experimental investigations and theoretical validation. The highest capacitance attained for TiS3 is found to be 235 F/g (105 C/g) at 5 mV/s with a battery type of charge storage mechanism. The asymmetric device is fabricated using Ti3C2Tx MXene nanosheets as negative electrode and a brilliant 91 % of capacitance retention is accomplished with an extensive potential window of 1.5 V. The investigational discoveries are substantiated by theoretical simulation in terms of the quantum capacitance assessment and charge storage mechanisms.

About the Research

In this work, a battery type TMTC material i.e., TiS3 has been synthesized and characterized by different analytical techniques such as Raman spectroscopy, FESEM and TEM to gain information on its structural and morphological aspects. The electrochemical performance was found to be promising by considering its good energy storage performance. High capacitance of 235 F/g (105 C/g) at 5 mV/s was achieved and the asymmetric supercapacitor devices disclosed outstanding cycling stability of 91 % over 6000 GCD cycles. In addition, the theoretical simulations also validated the experimental findings through the evaluation of the quantum capacitance. The higher conductivity, abundant electrochemical active sites, swift faradic redox kinetics and well-connected pathway for ion transfer characteristics pave the way for TiS3 to emerge as an eminent material for energy storage application in the long run.

Social Implications

Energy storage devices come into picture whenever there is a prerequisite of storing renewable energy. Among the numerous energy storage devices, batteries and ultracapacitors have acquired more popularity in nanotechnology and optoelectronics field. The high stability, accuracy, swift functionality, power density and reversibility are the key factors that have positioned ultracapacitors at the forefront of all energy storage devices. On the contrary, the low energy density and high cost of supercapacitor electrodes try to put them in the back seat of the wheels of the energy industry. Henceforth, in recent times the development of supercapattery (abbreviated for supercapacitor and battery) types of materials has become a way out which tie the aces like high specific power of supercapacitors with the high energy density of batteries. These materials exhibit capacitive or battery type behaviour on the basis of materials properties, electrolytic ions, design of the electrochemical cell. Due to these advantages and superior energy storage performance, the demand for this kind of material is growing.

Theoretical quantum capacitance is an important parameter to investigate the supercapacitor performance of low dimensional materials such as electrodes. This approach is highly cost-effective for the rapid screening of various materials for supercapacitor applications.

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The Department of Electronics and Communication Engineering is glad to announce that our PhD scholar, Mr Vasudeva Bevara and BTech students, Mr Shakamuri Narendra Chowdary and Mr Bolem Venkata Surendra Babu, published a paper titled ‘High performance 2n: 1: 2n Reversible MUX/DEMUX Architecture for Quantum-dot Cellular Automata’ in the international journal ‘Numerical Modelling: Electronic Networks, Devices and Fields (SCI Index)’ under the supervision of Dr Pradyut Kumar Sanki.

Abstract of the Research

Quantum-dot Cellular Automata (QCA) lead to fundamental changes in nanoscale technology. It promises small area, low power & high-speed structures for digital circuit design. This paper presents efficient low power structures of Reversible Multiplexer & Demultiplexer (RMD) modules based on the QCA technology. The simulation result shows that the proposed RMD modules have utilised less area & low power consumption. The simulation, layout & energy dissipation analysis of the proposed RMD module has been carried out using the QCA Designer-E simulation tool.

Essentially, CMOS is used as a well-known traditional technology in the design of the Very Large-Scale Integration (VLSI) circuits, which leads to the introduction of QCA as new nanotechnology to overcome the limitations of CMOS technology, such as material, physical, power, heat & economic challenges.

In reversible computation, the power dissipation occurs only when the computation is started or when the output is permanently stored. The reversible logic circuits are being investigated to prevent data loss in irreversible logic circuits. The reversible logic circuits provide zero loss of energy/information making the logic circuits the most suitable for QCA nanotechnologies. This has resulted in widespread interest in the design of reversible logic circuits based on QCA over the last few years.

In this paper, a modular 2n: 1 reversible multiplexer & 1: 2n reversible demultiplexer design in a single circuit is proposed. The 2:1 multiplexer & 1: 2 demultiplexer is realised in a single module i.e., 3 × 3 RMD. The 3 × 3 RMD is formed fundamental building block of the modular 2n: 1 reversible multiplexer & 1: 2n reversible demultiplexer design is extended to large RMD design.

Practical Implementations of the Research

This work can push forward research in the QCA domain and overcome the limitations of Complementary Metal Oxide Semiconductor (CMOS) technology. Soon the era of Beyond CMOS will start as the scaling of the current CMOS technology will reach the fundamental limit. QCA (Quantum-dot Cellular Automata) is the transistor less computation paradigm and viable candidate for Beyond CMOS device technology.

So, they have implemented the High Performance 2n: 1: 2n Reversible MUX/DEMUX Architecture for Quantum-dot Cellular Automata compared to other researcher works. In future, the research team would like to explore deeper into QCA technology and design efficient circuits which are small sized, with less cell count and less power consumption.

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Microbial fuel cells (MFCs) are biochemical systems producing green energy through the microbial degradation of organic contaminants in wastewater. The Oxygen Reduction Reaction (ORR) that takes place at MFC cathode decides the overall output of energy generation. Hence, the selection of ORR catalyst becomes pivotal in MFC fabrication for its efficiency and cost effectiveness. Gopa Nandikes P, PhD Scholar, Department of Environmental Science, proposes perovskite-based nanocatalyst as an excellent replacement to Platinum in his paper “Perovskite-Based Nanocomposite Electrocatalysts: An alternative to Platinum ORR Catalyst in Microbial Fuel Cell Cathodes”. The paper is published in ‘Energies Journal’ having an Impact Factor of 3.04.

The paper comprehensively summarises all the studies conducted with perovskite-based ORR catalyst in MFC, its unique reaction mechanism and the synergistic effect with carbon. The paper also throws light into various challenges and prospects to further improve the ORR activity of perovskite-based catalysts.

Abstract of the Research

Microbial fuel cells (MFCs) are biochemical systems having the benefit of producing green energy through the microbial degradation of organic contaminants in wastewater. The efficiency of MFCs largely depends on the cathode oxygen reduction reaction (ORR). A preferable ORR catalyst must have good oxygen reduction kinetics, high conductivity, and durability, together with cost-effectiveness. Platinum-based electrodes are considered a state-of-the-art ORR catalyst. However, the scarcity and higher cost of Pt are the main challenges for the commercialization of MFCs; therefore, in search of an alternative, cost- effective catalysts, those such as doped carbons and transition-metal based electrocatalysts have been researched for more than a decade. Recently, perovskite-oxide based nanocomposites have emerged as a potential ORR catalyst due to their versatile elemental composition, molecular mechanism, and the scope of nanoengineering for further developments. In this article, we discuss various studies conducted and opportunities associated with perovskite-based catalysts for ORR in MFCs. Special focus is given to a basic understanding of the ORR reaction mechanism through oxygen vacancy, modification of its microstructure by introducing alkaline earth metals, electron transfer pathways and the synergistic effect of perovskite and carbon. At the end, we also propose various challenges and prospects to further improve the ORR activity of perovskite-based catalysts.

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The Department of Commerce is glad to announce that Dr Shailender Singh, Associate Professor, published a paper titled ‘Pro-Environmental Purchase Intention Towards Eco-friendly Apparel: Extension of the theory of planned behavior model’ in the Journal of Global Fashion Marketing published by Taylor and Francis. The research is conducted in collaboration with Dr Nishant Kumar, Amity University, Noida.

Abstract of the Research

In this study, the theory of planned behaviour (TPB) model is employed with environmental concern, personal moral norms, and perceived consumer effectiveness to better predict the eco-friendly apparel purchase intention of educated Indian youths. Variance-based partial least square-structural equation modelling (PLS-SEM) is applied to evaluate the hypothesized model. Findings indicated that perceived behavioural control has a strong significant positive influence on purchase intention, followed by personal moral norms, attitude, and perceived consumer effectiveness. Environmental concern is found to indirectly affect purchase intention through three primary TPB variables and personal moral norms. Multi-group analysis (MGA) examines the moderating effect of perceived consumer effectiveness on an attitude–intention relationship. The highly perceived consumer effectiveness group is shown to have a more consistent attitude-purchase intention relationship as compared to the low-perceived consumer effectiveness group. The study promulgates insights to professionals and policymakers to formulate sustainable marketing strategies and policies to cope with the indigenous market conditions.

The textile industry has emerged as a significant pollution source owing to a rise in carbon footprint, the spike in greenhouse gas emissions, and increasing landfill waste. Sustainable fashion has become a new style statement, and industries are shifting their orientation towards environment-friendly manufacturing. A plethora of research studies have been conducted to explore consumer behaviour intention towards visiting green hotels, green products, organic food, and electric vehicles. Studies have also been done to understand consumer behavioural intention toward sustainability in apparel, sustainability, social media communication, ethical fashion consumption behaviour, and eco-friendly apparel in developed countries. However, the paucity of research studies examining the influential factors affecting purchase intention of eco-friendly apparel in a developing economy makes this study more imperative.

This study furnishes the problem by examining the eco-friendly apparel purchase intention of the educated Indian youth in the sustainable apparel framework by investigating the potential of three core predictors of purchase intention in the theory of the planned behaviour model. Furthermore, the study extends the model by adding three more variables: environmental concern (EC), personal moral norm (PMN), and perceived consumer effectiveness (PCE). Moreover, this study also examines the PCE as a moderator between consumer attitude and eco-friendly apparel purchase intention (PI), which adds to the existing body of knowledge. The study promulgates insights to professionals and policymakers to formulate sustainable marketing strategies and policies to cope with the indigenous market conditions.

Based on the proposed extended framework, the study disseminates several practical implications to attain sustainability in fashion:

(i) The strong PBC influence on apparel purchase intention would facilitate marketing professionals to support consumers with sustainable apparel choices through clear visibility, long-term benefits, and striking design with a vast form of offerings, sustainability certification, and ease of access.
(ii) It has also been observed that youth’s moral obligation to behave ethically no longer depends on social pressure. Consumers may feel that the discussion on pro-environmental intention is not having social acceptance. Policymakers must bring opinion leaders to pitch the benefit of using organic clothing so that it can be discussed socially and develop suitable sustainable purchase intent.
(iii) Marketers should use vivid marketing communication tools to educate customers about the attribute-based benefits of organic apparel and the technological difference which makes it different from fast fashion.
(iv) Policymakers should sensitize people about the deteriorating environment and try to teach pro-environmental intent through green info-commercials, organic apparel labels, socio-environmental themes in products, and affordable pricing strategies.
(v) Marketers may adopt various media platforms to showcase how individual-specific green behaviour is self-sufficient in combating environmental problems. This would increase the PCE level among people, further leading to an attitudinal shift.

The Indian government can launch an awareness campaign based on the theme of environment protection through individual contributions and urge citizens to accept green as a socially accepted norm.

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Studies that open new possibilities into some of the gripping issues in the scientific domain have transformed SRM University-AP into the epicentre of cutting-edge research and investigations. We are proud to announce that Dr B Lokeshgupta, Assistant Professor of the Department of Electrical and Electronics Engineering has won the Best Paper Award at IEEE Second International Conference on Power, Control and Computing Technologies ICPC²T 2022 held at NIT Raipur, Chhattisgarh. The paper titled “Reliability Improvement of a Radial Distribution System Considering Load Modeling and Energy Management” was co-authored by Dr S Sivasubramani and Mr. Ram Prakash from IIT, Patna. The research gives new insight into energy management and power consumption patterns.

Abstract of the Research

Increasing energy demand and recent advancements in electrical and distributed generation (DG) technology have made power systems complex. Therefore, the reliability assessment is important for efficient planning and operation of distribution networks. The system reliability can be improved with optimal DG integration and energy management schemes. This work mainly studies the impact of optimal DG planning with an energy management scheme on the reliability of radial distribution network. Usually, the reliability of a power system is evaluated using the distribution system reliability indices which are based on load point and customers. The voltage-dependent load model and time-varying load profile for different load classes are included in this work for pragmatic planning. Particle swarm optimization (PSO) algorithm is used to find the optimal site and size of DG units and optimal scheduling of the shiftable loads. The proposed model of optimal DG allocation with energy management is evaluated with a case-based analysis. The modified IEEE 33-bus distribution system is considered in this model to demonstrate the improvement of reliability and operational parameters. Simulation results verify the efficacy of the model.

About the Research

In recent decades, a high load growth rate and frequently changing power consumption patterns are observed due to urbanization and industrialization. Also, the increasing penetration of renewable-based DG has caused a significant mismatch between power generation and electricity demand pattern. This mismatch introduces reliability and power quality issues with loss of energy and revenue to the utilities in power systems. Thus, various energy management programs are carried out by utilities to encourage consumers to change their load patterns. This paper proposes a reliability improvement technique in a radial distribution system by optimal planning of disperse generation and energy management programme.

Social Implication

The research proposes an offline algorithm for the efficient planning and operation of radial distribution networks. Simultaneous deployment of distribution generation (DG) and energy management system (EMS) makes the network more reliable compared to just DG allocation. Application of DG and EMS also improves other operational parameters of the network like power loss and voltage profile.

In future, the energy management concept can be extended with the inclusion of neighbourhood power-sharing model in the environment of multiple smart home consumers and prosumers.

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The healthcare system across the globe has been under colossal pressure since the emergence of novel coronavirus pandemic. The pandemic has also unveiled some of the greatest gaps in the existing healthcare systems. The research paper authored by Dr Ashok Kumar Pradhan and his PhD student E Bhaskara Santhosh, Department of Computer Science and Engineering, proposing a blockchain-based pandemic detection model was recognised by WHO and the paper was listed in COVID-19 Global literature on coronavirus disease. The paper titled “iBlock: An Intelligent Decentralised Blockchain-based Pandemic Detection and Assisting System” was published in collaboration with Saraju Mohanty, University of North Texas and Dr Venkata Ramana Badarla, Associate Professor, IIT Tirupati. The authors have expressed their deepest gratitude to Science and Engineering Research Board (SERB) for Grant number TAR/2019/000286 and SRM University-AP for supporting this work.

Abstract of the Research

The recent COVID-19 outbreak highlighted the requirement for a more sophisticated healthcare system and real-time data analytics in the pandemic mitigation process. Moreover, real-time data plays a crucial role in detection and alerting process. Combining smart healthcare systems with accurate real-time information about medical service availability, vaccination, and how the pandemic is spreading can directly affect the quality of life and economy. The existing architecture models become inadequate in handling the pandemic mitigation process in a real-time dataset. This is because, the present models are server-centric and controlled by a single party, hence to manage confidentiality, integrity, and availability (CIA) of dataset is a challenging task. Therefore, a decentralised user-centric model is essential, where the CIA of user data can be assured. In this paper, we have suggested a decentralized blockchain-based pandemic detection and assistance system named as (iBlock) that uses robust technologies like hybrid computing and IPFS to support system functionality. Moreover, a pseudo-anonymous personal identity is suggested using H-PCS and cryptography for anonymous data sharing. The distributed data management module guarantees data CIA, security, and privacy using cryptography mechanisms. Furthermore, it delivers useful intelligent information in the form of suggestions and alerts to assist the users. Finally, the iBlock reduces stress on healthcare infrastructure and workers by providing accurate predictions and early warnings using AI/ML technology.

Contributions of the Research

i) Proposes a novel architecture model for pandemic detection and alertness using a blockchain called as “iBlock”. It supports sharing of real-time data utilization.
ii) The proposed system introduces suitable privacy and security mechanisms to cover system-level data privacy and security.
iii) It also suggests a logical combination of blockchain and AI/ML on hybrid computing to support global level requirements during pandemic mitigation and alerting the systems.

Social Implications

The proposed system helps in the early detection of Covid-19 and encourages people to use their health data anonymously in pandemic detection and mitigation process. Moreover, iBlock maintains all crucial data on blockchain for future sustainable healthcare solutions. The majority of pandemic detection and alerting systems are limited to prediction, however iBlock further simplifies the area-labelling to cover area wise mitigation mechanisms. The classification of areas helps the government and healthcare organizations to plan sustainable preventive measures in a real-time scenario. It also helps in prediction of new cases and death rates with the aid of a dedicated AI/ML detection engine module. To motivate the people to share legitimate data, the proposed model even suggests a reward mechanism to influence the participants.

The research investigates the advanced possibilities in smart healthcare architecture to bring down the time and effort for pandemic mitigation activities. Read to know more.

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Health expenditure assumed enormous importance with the outset of coronavirus pandemic. The disparity between public and private health expenditure will often reflect in the health outcome of any nation. Through the research paper titled ‘The dynamics of public and private health expenditure on health outcome in Southeast Asia’ published in the journal Health and Social Care in the Community, Dr Shailender Singh, Associate Professor, Department of Commerce, attempts to argue that public expenditure on health has a substantial impact over private spending across the countries of ASEA.

Abstract of the Research

This study examines the dynamics of public and private health expenditure on health outcomes in Southeast Asia, vis-a-vis two of the Sustainable Development Goals (SDGs). The techniques of fixed effect, random effect, and feasible generalized least square methods are employed to obtain robust estimates. Further, the analysis dives deep into the country-specific impact of public and private health expenditure on health outcomes using the technique of seemingly unrelated regression. Estimates show that, across Southeast Asia, public health expenditure alone contributes to improving life expectancy at birth, lower levels of under-five, and non-communicable disease mortality rates. Unlike public health expenditure, private health expenditure contributes to better health outcomes only in Brunei and Singapore but not across the countries of Southeast Asia.

The paper asserts that, despite the statistical significance of private health spending with respect to the health outcomes, it does not contribute to lower mortality rate (MR) and higher life expectancy at birth. The results strongly support several prior pieces of evidence in the literature regarding health expenditure and health outcomes. The country-specific estimates show that public health spending contributes greatly to lower mortality rate, particularly in Brunei and Singapore. By contrast, private health spending does not contribute to lower levels of U5MR and NCD mortality rate across the countries of ASEA except in Cambodia, Indonesia, and Philippines.

The differences in economic development and the settings of health systems in these countries could be a plausible reason for the inability of private health expenditure to contribute to lower levels of NCD mortality rate in most of these countries. The result implies that more funding to the public health system has the potential to lower U5MR and NCD MR close to the SDGs target across the countries of ASEA. Also, strengthening the health system through providing greater access to preventive services for diabetes, hypertension, respiratory diseases, and cancers at primary care units may help in better diagnosis and management of these chronic conditions in Indonesia, Laos, and Myanmar where NCD MR is relatively high. However, an increase in funding alone may not be sufficient at improving health outcomes. For emerging conditions, diet modification, active physical exercise, little tobacco and alcohol consumption are also imperative.

The research is reported to be the first of its kind that examines the dynamics of public and private health expenditure on health outcomes in line with the SDGs targets. Apart from the traditional indicators commonly used as health outcomes in the literature (life expectancy and U5MR), the study further extends the literature by introducing NCD MR as an additional health outcome which could play a pivotal role in providing empirical evidence to the health policymakers and researchers.

Health plays an important role in promoting human capital and the economic growth of a country. The available stock of human capital in a country determines the rate of growth in its per capita income. A healthy individual contributes more to their economy by allocating more hours to work, earning more disposable income, in turn investing more in human development.

As the individual stock of health tends to diminish over time, there is a need to augment it by making more investment in time, income, and regular medical care. Thus, this research work has a societal benefit for the population of Southeast Asia to identify the threats in the field of health and focus more on their well-being for improving the state of health. Dr Singh conducted this research in collaboration with Dr Nishant Kumar, Amity University, Noida.

In future, he also intends to analyse the impact of socioeconomic and behavioural health determinants on the health system efficiency of the Middle East region, and to predict the key drivers for health care expenditure growth in the Middle East region through Grossman-PLS Modeling Approach.

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