Research News

The upcoming international conference, India & Southeast Asia in a Changing World: Convergences and Divergences, will examine India’s Act East policy, investigating its prospects and challenges in the Southeast Asian region. Assistant Professor Dr Vineeth Thomas from the Department of Liberal Arts has been selected for presenting a paper at this Conference organised by Christ University, Delhi NCR. He will present the paper titled The centrality of ASEAN in India’s Act East policy at the conference.

The international conference will be held In-Person from 14 to 15 October 2022 at the CHRIST (Deemed to be University) Delhi-NCR campus. The Hanns Seidel Foundation funds this conference. The major focus area of the conference is India’s foreign policy towards ASEAN countries like Myanmar, Thailand, Malaysia, Vietnam, Indonesia, and Singapore

Abstract

Against the backdrop of multi-dimensional developments and interventions in the Indo-Pacific region, India’s overseas policy and national security apprehensions have undergone substantial changes in the past few decades. Starting with the Look East Policy in the 1990s, India advanced its policy in 2014 as Act East Policy. The potential benefits of bilateral and multilateral relations in the Indo-pacific region made India take up its partnership with the Association of Southeast Asian Nations (ASEAN) seriously, which provided an opening and strip for India to explore Southeast Asia. This paper evaluates the significance of keeping ASEAN at the heart of India’s Act East Policy by illustrating the prospects and challenges in India-ASEAN relations.

The Department of Physics is glad to announce that Assistant Professor Dr Soumyajyoti Biswas and his PhD scholar Ms Diksha have published their article “Prediction of imminent failure using supervised learning in a fiber bundle model” in the Q1 journal, Physical Review E. Prediction of breakdown in disordered solids under external loading is a question of paramount importance to the stability of buildings and bridges to earthquakes. The researchers used numerical simulations of a model of disordered solids and recorded the time series of the avalanche sizes and energy bursts. They propose that a systematic analysis of these time series using supervised machine learning can predict the time of failure. Interestingly, the most important feature for such predictions turns out to be the measures of how unequal the avalanche sizes are.

Applying external stress on disordered materials beyond their mechanical limits results in their fracture. Hence it is important to know the limit or how the material behaves as it approaches the limit and the factors that influence it. The failure properties of materials are very distinct from other properties such as elasticity, in the sense that their predictions are not always straightforward. Predicting the failure in driven disordered systems is a long-standing problem in physics, engineering, and earth sciences. So, for understanding the fracture process and predicting the failure properties of the materials, a mathematical model (fibre bundle model) has been used.

They introduced the disorder to the system and generated the time series of avalanche size and energy bursts. Some inequality indices i.e., Hirsch index (h), Gini index (g) and recently introduced Kolkata index (k) were measured for the response statistics of the driven systems. These social inequalities are usually represented by the Lorenz function L(p), where p fraction of the population (events) possesses L(p) fraction of total wealth (avalanche mass) when the population (avalanche events) are arranged in the ascending order of their wealth (size). Based on these time series, the machine learning algorithm can predict the prior failure time of the system. So, they have used a supervised machine learning algorithm (with the above-mentioned indices as some of the features) to predict the failure time of the model. They observed that these inequality measures play an important role in making predictions.

Prediction of imminent fracture has its implications in a wide range of disciplines, including stability of mechanical structures (buildings, aircraft, bridges etc.), extraction of oil (fracking) to the largest scale of mechanical failure i.e., earthquakes. Here a supervised machine learning approach is used to make such predictions in numerical models. However, with the important features identified here for such predictions, such research can carry out similar predictions for experimental data. A follow-up of this work is being carried out by Ms Diksha with a group in Spain regarding the experimental verification. Their future research plans include applications of the methods developed here to be applied to real-life physical structures for their stability analysis and predictions of impending catastrophes.

Illustration 1: A schematic diagram of the Lorenz function L(p)is shown, where L(p) denotes the cumulative fraction of the avalanche mass contained in the smallest p fraction of avalanches. If all avalanches were equal in size, this would be a diagonal straight line, called the equality line. The area between the equality line and the Lorenz curve (shaded area),therefore, is a measure of the inequality in the avalanche sizes. Two quantitative measures of such inequality are extracted from here, the ratio of the shaded area and that under the equality line (Gini index, g) and the crossing point of the opposite diagonal – from (0,1) to (1,0), shown in dashed line,and the Lorenz curve, giving the Kolkata index, k. 1 − k fraction of avalanches contain k fraction of the cumulative avalanche mass.

The Department of Electronics and Communication Engineering is glad to announce that Assistant Professor Dr Sunil Chinnadurai and his research scholar Mr Shaik Rajak have published a paper titled “Energy Efficient MIMO-NOMA aided IoT Network in B5G Communications” in the Q1 journal Computer Networks having an Impact Factor of 5.5. With an intent to accelerate the development of future intelligence wireless systems, the paper proposes an energy-efficient massive multiple-input-multiple-output (MIMO)- non-orthogonal multiple access (NOMA) aided internet of things (IoT) network to support the massive number of distributed users and IoT devices with seamless data transfer and connectivity.

Abstract of the research

Massive MIMO has been identified as a suitable technology to implement the energy efficient IoT network beyond 5G (B5G) communications due to its distinct characteristics with a large number of antennas. However, providing fast data transfer and maintaining hyperconnectivity between the IoT devices in B5G communications will bring the challenge of energy deficiency. Hence, they considered a massive MIMO-NOMA aided IoT network considering imperfect channel state information and practical power consumption at the transmitter. The far users of the base stations are selected to investigate the power consumption and quality of service. Then, they calculated the power consumption which is a non-convex function and non-deterministic polynomial problem. To solve the above problem, fractional programming properties are applied which converted the polynomial problem into the difference of convex function. And then they employed the successive convex approximation technique to represent the non-convex to convex function. Effective iterative-based branches and the reduced bound process are utilized to solve the problem. Numerical results observed that their implemented approach surpasses previous standard algorithms on the basis of convergence, energy efficiency, and user fairness.

Explanation of the research in layman’s terms

• A cost-effective (i.e., energy efficient) maximization problem for the multiple cells NOMA heterogeneous network scheme is explored when meeting the transmission power and data necessity of far users. The singular value uncertainty model (SVUM) is deliberated to add the errors with the transmitted signal. Since it’s a non-convex problem and challenging to solve, they used the properties of fractional programming to convert it into its corresponding mathematical terms. ITS needs higher data rate and seamless connectivity to operate with maximum speed and safety.
• SCA methods are then applied to change the optimisation problem. After that, an effective iterative scheme is employed based on Branch and Reduced Bound (BRB) that resolves the energy-efficient SVUM problem and satisfies the convergence criteria.
• The proposed iterative BRB method enhances user fairness and decreases inter-tier interference (ITI). IRS has been recognised as the key enabling technology to provide the data required by the ITS with less power consumption.
• Energy efficiency achieved by the proposed BRB method is examined with the help of numerical results and found that the proposed algorithm provides better efficacy than the majorisation minimisation (MM) method and the well-known OMA scheme.

Practical implementations of the research

• To provide high data rates to wireless sensors and the internet of things (IoT), future communication systems can ultimately be advanced by implementing NOMA, small cell, and heterogeneous networks (HetNets) along with MIMO.
• An energy-efficient massive MIMO-NOMA aided IoT network to support the massive number of distributed users and IoT devices with seamless data transfer and connectivity between them in B5G communications.

Future research plans

• To explore the energy efficiency of AI-driven IoT networks for applications such as intelligent health care and intelligent vehicular communications.
• MIMO-NOMA with IRS elements to reduce power consumption and improve the connectivity between the users.

The Department of Chemistry is glad to announce that Assistant Professor Dr Nimai Mishra and his research group Manoj Palabathuni, Syed Akhil, and Rahul Singh have published an article titled “Charge Transfer in Photoexcited Cesium Lead Halide Perovskite Nanocrystals: Review of Materials and Applications” in the Q1 journal “ACS Applied Nano Materials ” published by The American Chemical Society. The journal has an Impact Factor of 6.14.

Cesium Lead Halide (CsPbX3) perovskite nanocrystals (PNCs) have attracted significant views from researchers due to their essential optoelectronic properties, especially long charge carrier transfer, high efficiency in visible light absorption, and long excited states lifetime, etc. Because of these properties, these materials exhibit outstanding charge transfer and charge separation, which enables them for solar cell applications. Recently, cesium lead halide perovskites have emerged as photocatalysts. In photovoltaics or photocatalysis, upon photoexcitation, the exciton dissociates, and the electron/hole is transmitted from the conduction/valance bands to the electron/hole acceptors. Therefore, it is essential to understand how the charge transfer occurs at the PNCs interface, which can help the researcher maximize the output in solar cells and photocatalytic efficiency.

In this article, Dr Mishra’s research group has outlined different charge transfer dynamics based on critical factors and discussed their optoelectronic properties. Electron/hole transfer dynamics are the most concerning characteristic; thus, they reviewed the relevant literature that reported efficient electron/hole transfer performance. In the end, they highlighted the recent development of the use of perovskite nanocrystal as photocatalyst in organic synthesis.

Read the full paper here

Dr Pankaj Pathak from the Department of Environmental Science has been keenly involved in research studies involving solid waste management and the effective conversion of wastes to energy. Her latest research publication Sustainable approach for valorization of solid wastes as a secondary resource through urban mining proposes an enhanced solution for the sustainable management of different types of solid wastes. It was published in the Journal of Environmental Management with an impact factor 8.98.

In this paper, sustainable alternative valorisation techniques that aid in maximum recovery from waste materials, and associated challenges and limitations have been highlighted. These solid wastes mainly include construction and demolition wastes, organic food wastes, plastic, and WEEE (Waste electrical and electronic equipment) from various sources. In order to overcome these challenges, a sustainable circular model is recommended in this paper that will help minimise the negative environmental impacts, maximise the life cycle of material, reduce the consumption of fossil fuels, and thereby sustainably manage waste. Implementation of this recommendation can help in achieving the target of sustainable development goals (SDGs).

The article was published in collaboration with her PhD Scholar MSSR Tejaswini, and D.K. Gupta, Member Secretary in the Hazardous Substance Management Division in the Ministry of Environment, Forest and Climate Change, New Delhi.

Abstract

The incessant population has increased the production and consumption of plastics, paper, metals, and organic materials, which are discarded as solid waste after their end of life. The accumulation of these wastes has created growing concerns all over the world. However, conventional methods of solid waste management i.e., direct combustion and landfilling have caused several negative impacts on the environment (releasing toxic chemicals and greenhouse gases, huge land use) besides affecting human health. Therefore, it is requisite to determine sustainable alternative technologies that not only help in mitigating environmental issues but also increase the economic value of the discarded solid wastes. This process is known as urban mining where waste is converted into secondary resources and thereby conserves the natural primary resources. Thus, this review highlights the technological advancements in the valorisation process of discarded wastes and their sustainable utilization. We also discussed several limitations of the existing urban mining processes and further the feasibility of valorisation techniques was critically analysed from a techno-economical perspective. This paper recommends a novel sustainable model based on the circular economy concept, where waste is urban mined and recovered as a secondary resource to support the united nations sustainable development goals (SDGs). The implementation of this model will ultimately help the developing countries to achieve the target of SDGs 11, 12, and 14.

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Merging the calibre of two well-fledged technologies will massively impact the momentum of social life. Decoding the possible links between promising technologies would employ solutions to various societal issues. Dr Ashok Kumar Pradhan, Associate Professor of the Department of Computer Science and Engineering, gave life to this thought by publishing a book titled Intelligent Systems for Social Good Theory and Practice. He published this work as an editor in a book series named Advanced Technologies and Social Change by Springer Nature.

The book highlights the connection between the two technologies: Artificial intelligence (AI) and the Internet of Things (IoT). It shows the better impact of the relation between these technologies in society, using real-world examples. Each chapter in the book proposes novel solutions to societal problems along with the challenges in the application of AI and IoT to solve them. The adverse attacks on Machine Learning models and how to protect sensitive data over the IoT network are discussed in the book.

The book is significant to Dr Ashok Kumar Pradhan as applying the two technologies mentioned helps resolve various social problems related to healthcare, agriculture, green environment, renewable energies, smart cities, etc.

Shyamapada Mukherjee and Naresh Babu Muppalaneni from NIT Silchar and Sukriti Bhattacharya from Luxembourg Institute of Science and Technology, Belvaux, have worked together with Dr Ashok for this work. The book’s target audience is undergraduate, master’s, and doctoral students from Science and Engineering backgrounds.

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The latest research at the Department of Physics is investigating the charge transport across protein-based molecular junctions. Researchers envision fabricating bio- FETs which is useful in electronic devices as an alternative to Si- technology. Assistant Professor Dr Sabyasachi Mukhopadhyay and his PhD scholar Kunchanapalli Ramya published their paper Modulation of optoelectronic and mechanical properties across (bio) molecular junctions under external stimuli in the journal of Electronic Materials with an impact factor 2.04.

Abstract

Molecular junctions are formed by wedging molecules between two metal electrodes. Besides the conventional parameters of the metal-molecule-metal junction, such as the work function of electrodes and the molecules’ energy gap, molecule-electrode electronic coupling strength also plays a vital role in modulating the electronic properties of the molecular junction under external stimuli. We have also calculated several transport parameters which play a crucial role in finding the origin of conductance modulation under the external stimuli. We could find that before particular humidity conditions, the modulation in the conductance is due to the variation in coupling strength, which is due to the modulation in the electrostatic environment of retinal chromophores of protein by changing the structure of protein under various external stimuli.

Researchers have explored the external stimuli (illumination, force, and humidity conditions) effect on charge transport across bacteriorhodopsin-based molecular junctions. Their future research plans include bio- FET fabrication with the protein reported and studying the transistor characteristics across it.

Integrated short-range wireless technologies are becoming the most sought-after machinery in recent years. The possibilities of its applications are expanding with the emergence of new health conditions and concerns. Assistant Professor of the Department of Electronics and Communication Engineering, Dr Sunil Chinnadurai’s recent research focuses on the future of this technology. His paper titled Priority Based Resource Allocation and Energy Harvesting for WBAN Smart Health got published in the journal Wireless Communications and Mobile Computing with Impact Factor 2.34. He worked with Dr Poongundran Selvaprabhu, Assistant Professor, Vellore Institute of Technology, for this project.

Abstract

With the emergence of new viral infections and the rapid spread of chronic diseases in recent years, the demand for integrated short-range wireless technologies is becoming a major bottleneck. Implementation of advanced medical telemonitoring and telecare systems for on-body sensors needs frequent recharging or battery replacement. This paper discusses a priority-based resource allocation scheme and smart channel assignment in a wireless body area network capable of energy harvesting. The project investigates the researcher’s transmission scheme in regular communication, where the access point transmits energy and command while the sensor simultaneously sends the information to the access point. A priority schedule non-pre-emptive algorithm to keep the process running for all the users to achieve the maximum reliability of access by the decision-maker or hub during critical situations for users has been proposed. During an emergency or critical situation, the process does not stop until the decisionmaker, or the hub takes a final decision. The objective of the proposed scheme is to get all the user processes executed with minimum average waiting time and no starvation. By allocating a higher priority to emergencies and on data traffic signals such as critical and high-level signals, the proposed transmission scheme avoids inconsistent collisions. The results demonstrate that the proposed scheme significantly improves the quality of the network service in terms of data transmission for higher priority users.

Explanation of the research

A priority scheduling non-pre-emptive algorithm with SCA for WBAN smart health is proposed. The potential advantage of this algorithm is to keep on running the process for all users to attain maximum reliability until all the processes are executed. The data traffic associated with the priority scheduling non-pre-emptive algorithm is categorised into four major sub classes, namely, emergency, on-demand, normal, and non-medical data signals in order to assist the different QoS requirements. The results indicate that the priority scheduling non-pre-emptive algorithm performs during emergency and on-demand signals compared to the novel priority-based channel access algorithm for contention-based MAC (NPCA-MAC), low-rate wireless personal area networks (LR- WPAN), and priority-based adaptive schemes.

WBAN is a precise technology requiring frequent recharging or battery replacement. During the emergency or critical rescue situation, the highest priority user information is processed with minimum service delay without compromising the QoS. In addition, the proposed method prioritises the sensor nodes and classifies data traffic into emergency- (highest priority-), on-demand- (minimum priority-), normal (lowest priority-), and nonmedical- (normal-) based applications.

The future directions of WBAN are dealing with smart WBAN healthcare, trust management, trust negotiation, data security, uninterrupted lifetime, and intelligent decision-making (enhance the predictions from prior information) processes.

Rampant exploitation of resources has indisputably contributed to an enormous rise in solid waste generation. It has been estimated that solid waste generation will shoot up from 1.3 billion tons to 2.2 billion tons in 2025. While 16% of the high-income countries’ population corresponds to 34% of waste being generated, only 5% of the waste generated is attributed to the low-income countries. However, it is a meagre volume of 39% that is collected leaving the rest to rot. This open dumping affects the environment and creates pollution. In addition, improper waste disposal techniques have resulted in emissions of 1.6 billion tons of CO2eq in 2016. Effective waste management is thus a matter of concern in third-world countries.

Assistant Professor Dr Karthik Rajendran and his post-doctoral scholar Dr V S Vigneswaran from the Department of Environmental Science in collaboration with Dr Mukesh Kumar Awasthi from the College of Natural Resources and Environment, Northwest A&F University, PR China, have published their research papers on solid waste management in the journal Bioresource Technology having an Impact Factor of 11.8. This is the second-best journal in the Environmental Engineering category according to SCImago Journal Rank (SJR). The journal aims to disseminate knowledge in the areas of biomass, biological waste treatment, bioresource systems analysis, and technologies associated with conversion or production.

The paper titled “Recovery of value-added products from biowaste: A review” introduces microbial biotechnology for the valorisation of solid wastes. Microbial biotechnology offers several solutions for the utilisation of waste resources. The carbon present in solid and gaseous wastes can be utilised by the microbes as carbon feedstock for their growth. During the growth of microbes on wastes, it produces primary and secondary metabolites, which are of significant use to humankind. The microbes can also be engineered biotechnologically to use waste resources and produce new compounds. Microbial biotechnology, with the use of various genetic engineering tools, can be efficiently explored for the microbes’ modification to utilise different wastes thereby making the environment clean by reducing GHG emissions.

Abstract of the Research

This review provides an update on the state-of-the art technologies for the valorization of solid wastes and its mechanism to generate various bio-products. The organic content of these wastes can be easily utilized by the microbes and produce value-added compounds. Microbial fermentation techniques can be utilized for developing waste biorefinery processes. The utilization of lignocellulosic and plastic wastes for the generation of carbon sources for microbial utilization after pre-processing steps will make the process a multi-product biorefinery. The C1 and C2 gases generated from different industries could also be utilized by various microbes, and this will help to control global warming. The review seeks to expand expertise about the potential application through several perspectives, factors influencing remediation, issues, and prospects.

Read the full article here

Food waste in solid forms has been generated throughout the entire food life cycle, from the agricultural production process to the distribution of processed foods and even to their consumption in the market. Considering that approximately 1.3 billion tons of edible food waste is leftover annually, recycling it in the biorefinery will contribute both economically and socially. Another of their publication “Myco-biorefinery approaches for food waste valorization: Present status and future prospects” discusses various types of food waste sources and their evaluation targets. Food waste can be evaluated in fungi-based bioproduction processes for this purpose. In addition, potential biorefinery systems, circular bioeconomy processes, techno-economic studies, and social/ethical aspects of food wastes in the evaluation of valuable products are discussed.

Abstract of the Research

The increase in population and urbanization leads to the generation of a large amount of food waste (FW) and its effective waste management is a major concern. Its putrescible nature and high moisture content are the major limiting factors for cost-effective FW valorization. Bioconversion of FW for the production of value-added products is an eco-friendly and economically viable strategy for addressing these issues. Targeting the production of multiple products will solve these issues to a greater extent. The article provides an overview of the bioconversion of FW to different value-added products.

Read the full article here

Presenting papers at international research conferences helps hone the research questions. Students from the Department of Computer Science and Engineering have attended two international research conferences and presented their papers drafted under the supervision of Assistant Professor V M Manikandan.

The International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET- 2022), organised by NIT Patna, India, was held from June 24 to 25. At the conference, BTech students Nitesh Bharti and Mohit Kumar presented the paper A Hybrid System with Number Plate Recognition and Vehicle Type Identification for Vehicle Authentication at the Restricted Premises. The work was composed under the guidance of Assistant Professor Dr V M Manikandan. The paper will soon be published in IEEE Xplore Digital Library (Scopus indexed). In the future, they plan to integrate the proposed algorithms with proper hardware units to completely automate the authentication of vehicles in restricted areas. The proposed computer vision-based systems can be used in restricted areas to ensure the entry of authenticated vehicles.

Explanation of the research

Vehicle detection and number plate recognition approaches have been widely studied in recent years due to their wide applications. The research paper proposes a framework to ensure the entry of authorised vehicles in restricted areas such as University campuses, townships, etc., where the researchers are expecting the entry of a set of authorized vehicles. Certainly, unauthorised vehicles might be allowed to enter those areas after proper verification by the concerned people responsible for ensuring security. In the proposed approach, the admin should register all the authorised vehicles in a system with the essential attributes such as vehicle number, type, etc. A surveillance camera placed at the entrance will capture live videos. When a vehicle is in the camera view, the image frames will be passed to an automatic number plate recognition module. The number plate recognition module will identify the same and be matched with the details in the database to authorise the vehicle. This manuscript proposes a real-time and reliable approach for detecting and recognising license plates based on morphology and template matching. To ensure the system’s reliability, a frame selection module will select the image frames with high quality, and even to improve the number plate recognition accuracy, the image will be enhanced using image enhancement techniques such as histogram equalisation. The image enhancement techniques will help to provide better results even though the videos are taken in low lighting conditions. Further, we ensure that the vehicle type matches the number present in the database to prevent unauthorised access using fake number plates. The experimental study is conducted using videos taken under various environmental conditions such as lighting, slope, distance, and angle.

Jahnavi Kolli presented her research paper, An Efficient Face Recognition System for Person Authentication with Blur Detection and Image Enhancement, at the International Conference on Sustainable Technology for Power and Energy Systems (STPES). The conference was organised by NIT Srinagar and IIT Jammu, India, and was held from July 4 to 8, 2022. The research work was monitored by Assistant Professor V M Manikandan and done in collaboration with Professor Yu-Chen Hu, Providence University, Taiwan. The proposed computer face recognition systems can be used to record the attendance of students in class or employees in the office in an easy way. In the future, the researchers plan to improve the face recognition systems, which will perform better when the images are captured using low-resolution cameras or the face regions occluded for some reasons.

Explanation of the research

The recent advancements in technology widely help to substitute manpower with machines in a better way. Even though machines are increasingly replacing humans in various ways, there are still a few areas where the use of machines still needs to be explored much more efficiently. Facial recognition systems are one such field. Facial recognition systems are used with various motives, such as identification of suspects in public places, authentication of users on restricted premises, etc. In this work, we propose a facial recognition system to facilitate the authentication of students at the university entrance. The same scheme can also be utilised to authenticate the students before entering examination halls. As the strength of the students at universities increases in a more significant way, it becomes strenuous for the security people to record their attendance manually, which frequently results in erroneous data. This paper proposes a facial recognition system that will help to capture the live videos from an area of interest and identify the faces. Further, a face recognition scheme will detect whether the person is authorised or not. Several facial recognition systems are already available in the literature, and this scheme differs from them in many ways. The proposed method selects the frames with less blur for face detection and further face recognition. A blur detection scheme is used in the proposed system to analyse the amount of blur in the image. To overcome the challenges such as low accuracy during face recognition when the images are taken in low lighting conditions, we use a histogram equalization method to enhance the quality. The experimental study shows that the proposed approach works well in real-time.