Research News

Research at the Department of Physics envisions future studies on the anisotropic properties across various planes of their reported MAPbBr3 crystals and identifying the better plane for efficient electrical contact in device applications. Assistant Professor Dr Sabyasachi Mukhopadhyay and his research scholar Kunchanapalli Ramya recently published the paper Room-Temperature Cost-effective In-situ grown MAPbBr3 Crystals and their Characterization towards Optoelectronic Devices in the journal Material Science and Engineering: B. The paper has an impact factor of 3.407. They have done this work in collaboration with Sr Satyajit, IIT- Bhilai. This is the first article published under the Indo- Israel bilateral project A Halide Perovskite-Based Photoanode for Oxygen Evolution Reaction Using a Molecular Diode in a Hybrid Nanometer Scale.

Abstract

The paper reports the in-situ, room-temperature synthesis of methylammonium lead bromide CH3NH3PbBr3 crystals using N-methyl formamide as a source of methylammonium (MA+) ions during the crystallization process to explore the structural, dielectric, and electronic properties of CH3NH3PbBr3 crystals for optoelectronic applications. Optical absorption and radio-luminescence measurements affirm the direct bandgap nature of the crystals. Impedance spectroscopy measurements with various applied AC voltages within the 20 Hz – 10 MHz frequency range depict the influence of ionic motions on electrical transport across crystal planes. Researchers have extracted electrical transport parameters in CH3NH3PbBr3 crystals from the Nyquist plots, which we found to be distinctly varied wherein two different AC voltage amplitude regimes, broadly for 10 – 50 mV and 100 – 500 mV AC voltage range.

Explanation of the research

The wide approachability of our synthesis method lies in avoiding expensive precursor salts and eliminating the use of toxic solvents. We have obtained the MAPbBr3 crystals with improved thermal, optical, and dielectric properties that are used in optoelectronic devices, mainly in the applications of solar cells and photodetectors.

The value of certain looks or appearances is constructed intentionally, and it directly takes part in social stratification. The explanation for this practice can be found in the concept of aesthetic labour. Aesthetic labour implies the practice of screening, managing, and controlling workers on the basis of their physical appearance. When read together with femininity and body, the concept discloses several crucial dimensions. Assistant Professor Dr Ipsita Pradhan, Department of Liberal Arts, published an article titled Aesthetic labour, Body, and Femininity: Insights from a Retail Shop-floor in the journal Sanghaditha. The paper is translated from English to Malayalam by Dr Anu Kuriakose.

Abstract

The essay discusses the importance of the body in interactive service work. By focusing on women retail shop floor workers, employed in the apparel and cosmetic sections of multi-national brands argues that employment in this sector requires working on one’s body to produce a “presentable” body by grooming so as to fit the larger image that the mall presents. The presence of the mannequin and its dressing is also analysed to understand how it perpetuates stereotypes of the ‘ideal’ body through the apparent function of attracting customers or giving the customers an idea of the products on display, simultaneously perpetuating the male gaze on ‘acceptable’ feminine bodies.

The Department of Computer Science and Engineering is proud to announce that Dr Priyanka, Assistant Professor, and her research Scholar, Ms Kilari Jyothsna Devi have published their patent (application no: 202241033779 A), “A System and a Method for Watermarking Medical Images for the Secure Transmission of Images”. The patent was published on June 17, 2022, by the Indian Patent Office.

In the present technology, medical images and patient information are widely transmitted through a public transmission channel in e-healthcare applications. While sharing medical images or electronic patient records (EPR) through a public network, they can get tampered with or manipulated, leading to wrong diagnosis by the medical consultants. Similarly, one can easily claim false ownership of the medical images. This makes the confidentiality of the patient record at low cost a major concern.

The proposed novel MIW scheme ensures most of the watermarking characteristics such as high imperceptibility, robustness, security with low computational cost, temper detection and recovery in medical image transmission in real-time healthcare applications. In the future, they intend to design digital image watermarking schemes for the secure transmission of images over blockchain and cloud-based applications.

Post-truth represents the replacement of facts with personal beliefs and emotional appeals in order to shape public opinion. The distinction between fake and real news is not about reliable and unreliable sources. It’s about honesty and deception. The media can both inform and deceive people. What makes the news fake is the intention of its author. Discourses are produced by the effects of power within a social order. This power prescribes certain rules and categories that define the criteria for legitimating knowledge and truth within the discursive order. Assistant Professor Dr Ugen Bhutia of the Department of Liberal Arts published an article titled Beyond the discourse of Post-Truth: Some Reflection on the Idea of Fake News based on Corpus Linguistics in the Online Journal of Educational Policy and Management.

Abstract

The article illustrates how we deceive ourselves by attempting to understand fake news through the notion of a post-truth society. The paper argues that the concepts of fake news and post-truth are not an aberration in the history of media practices and neither of contemporary origins. They are an intricate part of the discursive practices in which media as an institution engages. The article builds on Foucault’s approach to discursive practices and applies a meta-discursive framework to trace the genealogy of post-truth and fake news in an Indian context. The article also critically reflects on some key strategies to contain and counter fake news. For instance, media literacy and linguistic approaches such as corpus linguistics to detect fake news.

Economic institutions, technological developments, cultural norms, religious and intellectual currents, and popular beliefs have always played a huge role in asserting clear boundaries between men’s and women’s work. The recent research paper of Assistant Professor Dr Ipsita Pradhan, Department of Liberal Arts, focuses on the transformation of gendered work in contemporary India. The paper is titled Women and the Changing Nature of Work in Hyderabad’s Hitec City and was published in the journal Sociological Bulletin.

Abstract

This article looks at the ways in which gendered work is being transformed in contemporary India by focussing on Hyderabad, the capital of Telangana. Since the mid-1990s, after India opened its doors to multinational agencies, new forms of gendered labour have manifested. One of the ramifications of this gendered process is the feminisation of labour that enabled the participation of more women in the workforce, engaging in activities that were low-paid. The basis of feminisation is that certain jobs require fewer skills or particular kinds of skills, for which women are thought to be suitable. This also has implications for the low bargaining power of women workers. The feminisation of the labour force in HITEC city, Hyderabad is a consequence of the changing labour markets with globalisation, offshore factories, migration, and other changes in the workplace.

Dr Divya Chaturvedi, Assistant Professor, from the Department of Electronics and Communication Engineering has been keenly pursuing research on wearable antennas that are used within the context of Wireless Body Area Networks. These antennas are commonly used in wearable wireless communication and bio-medical RF systems. Her latest publication “Design and Investigation of Dual-Band 2×2 Elements MIMO Antenna-Diplexer Based on Half-mode SIW” was featured in the Q1 journal, IEEE Access, having an Impact Factor of 3.37. The research was done in collaboration with Assistant Professor Dr Goutam Rana and Research Scholar Ms Buela Pramodini from the Department of Electronics and Communication Engineering.

This antenna is designed to enhance data rate twice as much as a single antenna. The antenna can be used to operate in two frequency bands simultaneously, without causing any interference. One frequency band can be used for the transmission of data while the other frequency band can be utilised for the reception of data. The radiating elements are configured in such a way that it occupies a compact size. Thus, the designed antenna can be easily mounted or integrated into a portable wireless electronic device. The field from one radiating element is not coupled to the other element due to their adequate isolation that mitigates the interference problem.

The dual-band self-diplexing 4-port MIMO antenna operates in the lower frequency band around 3.4 GHz (3.35-3.55 GHz, 160 MHz) for the TD-LTE system and in the higher frequency band around 4.2 GHz (4.14-4.34 GHz, 200 MHz) for FCC ID WLAN in 5G LTE communication. The electronic devices which operate in these frequency bands can enhance the data transmission and reception speed twice as much as a single element. In other words, the proposed design prototype also improves the reliability of communication by employing the spatial multiplexing technique. In future, they plan to work on the design and investigation of MIMO-based self-diplexing antenna using the polarization diversity technique.

Abstract of the Research

In this article, a compact dual-band, 2-elements antenna-diplexer is investigated and extended to a 2×2 multi-input and multi-output (MIMO) antenna. The proposed design employs half-mode Substrate Integrated Waveguide (HMSIW) technology, which reduces the antenna footprint by 50%. To enhance the bandwidth, a rectangular slot is engraved at the center of each HMSIW cavity. The slot splits the dominant mode of the HM cavity into two odd- and even-half TE110 modes in proximity, which leads to enhancement in the bandwidth by 50%. The antenna resonates around 3.4 GHz with a fractional bandwidth of 5% and around 4.3 GHz with a bandwidth of 4.7%, when corresponding ports are excited, respectively. Both the lower and upper frequency bands can be tuned individually, by simply altering the dimensions of each HMSIW cavity. This can be achieved in a common antenna, without employing filters, which satisfies the antenna-diplexer function. The isolation levels between any two radiating elements are obtained below -23 dB for the proposed MIMO antenna, and it occupies an overall size of 1.0λg × 0.8λg. The peak gain of the antenna is obtained at 5.35 dBi in the lower frequency band and at 6.75 dBi in the upper frequency band while radiation efficiency is better than 80% in both frequency bands.

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The Department of Computer Science and Engineering is delighted to announce that Dr Abinash Pujahari, Assistant Professor, has published his research article “Item Feature Refinement using Matrix Factorization and Boosted Learning based User Profile Generation for Content-Based Recommender Systems” in the journal Expert Systems with Applications having an Impact Factor of 8.665. The research was done in collaboration with Dr Dilip Singh Sisodia, Assistant Professor, National Institute of Technology Raipur.

This research focuses on improving the quality of information available about the features of various items so that it can be used for content-based recommendations. Content-based recommender systems are used in many e-commerce platforms (e.g., NetFlix, Amazon Prime, etc.). Here, the item (i.e., movies, TV shows) feature information is compared with the users’ past behaviour to recommend similar things. This research enables such systems to study the feature information for more accurate recommendations.

Most of the items’ feature information is sparse, redundant, and inconsistent. Matrix Factorization is used to avoid such inconsistencies. Further, iterative learning of user profiles is used using boosted learning approach for model building. The proposed research is compared with state-of-the-art related works using benchmark datasets and can be implemented in most e-commerce platforms and online streaming service providers. Dr Pujahari looks forwards to employing the same in group recommender systems where individuals have their preferences, in his future research endeavours.

Cultural and Post-colonial studies enclose various historical approaches. It ranges from cultural studies and comparative social history to analysis of the means of domination and resistance. Nevertheless, there are communities that didn’t get the space they deserve in the studies of settled communities. Assistant Professor Dr Bikku R from the Department of Liberal Arts published a paper titled Colonial Impact on Pastoral Nomads and Caravan Traders in India: The Raika and the Banjara to analyse the aftereffects of colonialism in the most unexplored communities. The article was published in the book Tribe, Space, and Mobilisation.

Abstract

The Raika of Rajasthan and the Banjara or Lambadi tribe of the Deccan region had been self-sustained as nomadic pastoralists and caravan traders, respectively, in pre-British India. Colonial policies imposed several restrictions on nomadic communities and their economic activities by branding them as ‘criminals’ under the Criminal Tribes Act of 1871. As a result, many of the nomadic communities lost their cultural economy and struggled to survive. Colonial and post-colonial studies have primarily focused on settled communities. However, little attention is paid to pastoral nomads and itinerary communities. The present paper focuses on the transformation of traditional nomadic livelihoods, culture, and economy of the two communities; the Raika pastoralist and the Banjara traditional caravan traders and livestock breeders’ as a consequence of colonial policies. It also emphasises current livelihood strategies. Empirical data resulting from ethnographic fieldwork and colonial and post-colonial literature have been examined. An ethnographic study among the Banjaras from the Deccan region during the year 2009- 2010 and the Raika of Rajasthan between 2013- 2015 and 2019 helped to understand their past and present situations. Colonial and post-colonial policies, governance, and their impact on pastoralists and other nomadic communities have been critically examined.

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The Department of Computer Science Engineering is glad to announce that Dr Kshira Sagar Sahoo, Assistant Professor, has published an article titled ‘Sustainable IoT Solution for Freshwater Aquaculture Management’ in the Q1 journal, IEEE Sensors, having an Impact Factor of 4.325. The research was published in collaboration with Munesh Singh, from the Department of Computer Science and Engineering, PDPM IIITDM Jabalpur Campus, Madhya Pradesh, and Anand Nayyar, Graduate School, Faculty of Information Technology, Duy Tan University, Vietnam.

Freshwater pearl farming has the potential to generate an alternative source of income for small farmers. Indian freshwater river bodies have 51 types of species that can produce pearls. Still, India imports 2.4 billion dollars’ worth of pearls from China and Japan. To reduce the import burden on the Indian economy, the government encouraged the farmers to do integrated freshwater pearl farming. Aquaculture-based farming needs a small investment for the initial setup. Although the Indian government promotes aquaculture-based farming through subsidies and free training programs, farmers find it difficult to get success in aquaculture-based farming.

The paper proposes a comprehensive IoT system for freshwater pearl farming which has an intelligent control system for maintaining the aquaculture environment. The proposed system monitors and supports the habitable underwater environments for aquaculture. To train the farmers and educate them in pearl farming business is a time taking and skill-oriented job. The comprehensive IoT system will encourage farmers for freshwater pearl farming and proper utilisation of the government subsidy granted for aqua farming. In future, the researchers will consider more relative water parameters for robust forecast and analyse the best model for predictive analysis.

Abstract of the Research

In recent years, we have seen the impact of global warming on changing weather patterns. The changing weather patterns have shown a significant effect on the annual rainfall. Due to the lack of annual rainfall, developing countries like India have seen a substantial loss in annual crop production. Indian economy largely depends on agro products. To compensate for the economic loss, the Indian government encouraged the farmers to do integrated aquaculture-based farming. Despite government subsidies and training programs, most farmers find it difficult to succeed in aquaculture-based farming. Aquaculture farming needs skills to maintain and monitor underwater environments. The lack of skills for monitoring and maintenance makes the aquaculture business more difficult for farmers. To simplify the pearl farming aquaculture, we have proposed an Internet of Things (IoT)-based intelligent monitoring and maintenance system. The proposed system monitors the water quality and maintains an adequate underwater environment for better production. To maintain an aquaculture environment, we have forecasted the change in water parameters using an ensemble learning method based on random forests (RF). The performance of the RF model was compared with the linear regression (LR), support vector regression (SVR), and gradient boosting machine (GBM). The obtained results show that the RF model outperformed the forecast of the DO with 1.428 mean absolute error (MAE) and pH with 0.141 MAE.

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Individuals with pre-existing medical conditions are more vulnerable to Covid-19 and its variants. Patients in countries like India require early testing to diagnose crucial disorders to reduce the risk. Research at the Department of Computer Science and Engineering has come up with a system that automatically identifies and categorises diseases based on the patient’s medical test results. Assistant Professor Dr Ravi Kant Kumar published a paper Improving Performance of Classifiers for Diagnosis of Critical Diseases to Prevent COVID Risk as a co-author in the Q1 journal Computers and Electrical Engineering and has an impact factor of 4.152. With an accurate diagnosis, the required actions can be planned and executed to stop the patients from serious health issues as well as covid risk.

Abstract

The risk of developing COVID-19 and its variants may be higher in those with pre-existing health conditions such as thyroid disease, hepatitis C virus (HCV), breast tissue disease, chronic dermatitis, and other severe infections. As a result, early and precise identification of these disorders is critical. A huge number of patients in nations like India require early and rapid testing as a preventative measure. Machine learning methods for automatically identifying and classifying diseases have been created, and they function effectively when the dataset is well specified and balanced at every class level, including “no disease”. The problem of imbalance arises from the skewed nature of data, in which a large number of cases belonging to one class (known as the majority class) are classified correct, while the other class (known as the minority class) has lesser instances; is unfortunately misclassified by many classifiers. When it comes to human life, this kind of misclassification is unacceptable. To solve the misclassification issue and improve accuracy in such datasets, we applied a variety of data balancing techniques to several machine learning algorithms. The outcomes are encouraging, with a considerable increase in accuracy. As an outcome of these proper diagnoses, we can make plans and take the required actions to stop patients from acquiring serious health issues or viral infections.

Explanation of the research

Lethal COVID-19 and its mutant forms may be more likely to arise in patients with pre-existing medical conditions such as thyroid illness, hepatitis C virus (HCV), breast tissue disease, chronic dermatitis, compromised immune systems, obesity, diabetes, heart disease, cancer, etc. For patients, an early and accurate diagnosis of these illnesses is crucial. Based on patient data, machine learning algorithms can assist in the early and quick detection of numerous diseases in a huge population like India. On the other side, machine learning algorithms perform poorly when a dataset has a class unbalanced problem. As a result, we used a variety of smote and its variants in this study to address the problems about the imbalanced class size. The experimental work showed that all six classifiers (DT, SVM, LDA, k-NN, GNB, and ANN) performed better overall on clinical datasets when class balancing strategies and classification techniques were combined. It recommends the use of the recommended classifications and class balancing technique with regard to specific data to identify the disease accurately and automatically

For this work, Dr Ravi Kant Kumar has collaborated with Mr Vinod Kumar, Koneru Lakshmaiah Education Foundation, Vaddeswaram,India, and Mr Gotam Singh Lalotra, University of Jammu, India. Their future research will investigate and design the most effective multi-class balancing method to address the multi-class imbalance problem in medical data.