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Is Bitcoin a Safe Haven for Indian Investors? A GARCH Volatility Analysis
This paper attempts to understand the dynamic interrelationships and financial asset capabilities of Bitcoin by analysing several aspects of its volatility vis-a-vis other asset classes. This study aims to analyse the volatility dynamics of the returns of Bitcoin. An asymmetric GARCH model (EGARCH) is used to investigate whether Bitcoin may be useful in risk management and ideal for risk-averse investors in anticipation of negative shocks to the market (leverage effect). This paper also examines Bitcoin as an investment and hedge alternative to gold as well as NSE NIFTY using a multivariate DCC GARCH model. DCC GARCH models are also used to check whether correlation (co-movement) between the markets is time-varying, examine returns and volatility spillovers between markets and the effect of the outbreak of COVID-19 in India on the investigated markets. The results show that given the supply of Bitcoin is fixed, low returns realisation is equivalent to excess supply over demand wherein investors are selling off Bitcoin during bad times. The positive co-movement between Bitcoin and gold during the COVID-19 outbreak shows that investors perceived Bitcoin as a relatively safe investment. However, overall analysis shows that Bitcoin was not considered a safe hedge and an investment option by Indian investors during the study period. 2022 by the authors. -
Is asteroid 33 Polyhymnia a dark matter (DM) degenerate object?
Polyhymnia (33 Polyhymnia) is a main belt asteroid in our solar system with a diameter around 54km. The density of asteroid 33 Polyhymnia, located in the main asteroid belt, is calculated to be 75g/cc. Researchers have speculated the possibility that Polyhymnia could be composed of high-density superheavy elements near atomic number 164. Here, we propose that Polyhymnia could be an asteroid composed of degenerate dark matter (DM) and there could be many such asteroids in our solar system. (This is following our earlier work suggesting that Planet Nine could be such an object.) The Author(s), under exclusive licence to SocietItaliana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Irrigation water policies for sustainable groundwater management in irrigated northwestern plains of India
Increasing global water shortage emphasizes the need for demand-side water management policies, especially in the agriculture sector, being the largest consumer of freshwater. Such policies are relevant in India, where groundwater depletion may have severe implications at various socio-economic levels. In this study, using mathe-matical modelling, we assess the feasibility of two alter-native irrigation water pricing policies (i) uniform wa-ter pricing policy and (ii) differentiated water pricing policy, wherein farmers growing less water-requiring crops (<4488 m3/ha) get an incentive for saving water, while those growing water-intensive crops pay for it. Us-ing a case study of Punjab, the breadbasket and one of the fastest groundwater-depleting states in India, alter-native cropping patterns are also suggested. The findings reveal that the current rate of groundwater withdrawal could not sustain agricultural intensification in the state. Although optimization of resource allocation has the pote-ntial to save water by 8%, this alone is unlikely to break the ricewheat mono-cropping pattern in Punjab. The analysis of two different volumetric irrigation water pricing policies shows that differentiated water pricing would be more effective in halting groundwater deple-tion in the state. However, adequate investment in irri-gation water supply infrastructure, mainly for installing water meters, is required to implement the policy. 2022, Current Science. All Rights Reserved. -
Irreversibility analysis of the MHD Williamson fluid flow through a microchannel with thermal radiation
The heat transport and non-Newtonian fluid (Williamson fluid) flow through a micro-channel are considered to analyze the entropy generation minimization using the thermodynamic second law. The energy equations have been modeled with the addition of joule heating, heat source, and thermal radiation. The use of suitable dimensionless transformation helps to convert the modeled flow equations into non-dimensional coupled ODEs. The numerical simulations are done via the Finite Element Method. The current outcomes are constructed to examine the behavior of various flow parameters and presented via graphs. It is found that the rise of heat source and Reynolds number Re decays/boosts the entropy rate Ns and the Bejan number Be profile near the left/right plate, and reverse behavior is noticed for the thermal radiation parameter. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Irreversibility analysis of radiative heat transport of Williamson material over a lubricated surface with viscous heating and internal heat source
Thecurrent research explores the importance of surface lubrication and convective boundary conditions in the flow of non-Newtonian Williamson material. Rosseland radiative heat flux and viscous heating are also considered. The phenomenon of the generation or absorption of internal heat is studied. The conservation laws of momentum, mass, and energy are used to model the problem with suitable boundary conditions. With the help of appropriate transformations and the finite difference method, highly nonlinear equations of governance are solved. The influence of key parameters on Bejan number, velocity, entropy production, temperature profiles are analyzed by parametric analysis. It was found that the entropy generation rate improves due to the presence of the Rosseland radiative heat flux and the convective boundary on the lubricated surface. The sliding condition on the lubricated surface has lengthened the structure of the velocity boundary layer, while this trend is opposite to the thermal field. The dissipation due to the viscous forces of the Williamson material improves the production of entropy. 2021 Wiley Periodicals LLC -
IRRELEVANCE OF ITEM NUMBERS IN BOLLYWOOD MOVIES TODAY- AFFECTING THE PORTRAYAL OF ITEM GIRLS
The research paper was aimed to look into the portrayal of women in media especially those who do item numbers. The paper also looked into the matter that how due to the lack of relevance of item numbers in movies today, the portrayal is negative. Whether this in turn has led to a negative stereotypical representation of women in general was also a concern of the study. The researcher focussed on this matter as she is strongly against any kind of stereotypical representations. As a media student she wanted to inform people about the rights and wrongs in the society and how this leads to framing of stereotypes which is often regarded derogatory. The research was done using both primary and secondary sources. Primary data collection included questionnaire method to general audience of sample size of 100 and a comparative analysis will be done. An extensive study was done of secondary sources too including books, journals, movies, short videos, internet and newspapers. The study revealed that item numbers have definietely lost its relevance in the movies and that has led to the negative portrayal of item girls. There were other reasons also found have an impact on the audiences?? mind which in turn influences his thinking towards the item girls, this was found by comprehending the study with Cultivation theory by Gerbner. -
Irreducible tensor approach to study ? + d ? d + ? 0
The study of photoproduction of mesons plays an important role in understanding the properties of strong interactions. Pion photoproduction on deuterons has been studied theoretically for several decades. At the VEPP - 3 storage rings, tensor analysing powers in ? + d ? d + ?0 have recently been measured. In light of these advances, we suggest adopting an irreducible tensor technique to explore the reaction ? + d ? d + ?0 at close to threshold energies. Our method, which is model-independent, works well for predictions regarding spin observables. By describing the differential cross section in terms of multipole amplitudes, the angular dependence of the cross section will be studied. 2023 Author(s). -
Iron-pulsing, a novel seed invigoration technique to enhance crop yield in rice: A journey from lab to field aiming towards sustainable agriculture
Bulk fertilizer application is one of the easiest means of improving yield of crops however it comes with several environmental impediments and consumer health menace. In the wake of this situation, sustainable agricultural practices stand as pertinent agronomic tool to increase yield and ensure sufficient food supply from farm to fork. In the present study, efficacy of iron-pulsing in improving the rice yield has been elucidated. This technique involves seed treatment with different concentrations (2.5, 5 and 10 mM) of iron salts (FeCl3 and FeSO4) during germination. FeCl3 or FeSO4 was used to treat the sets and depending on the concentration of the salts, the sets were named as C2.5, C5, C10 and S2.5, S5, S10 (where C and S stands for FeCl3 and FeSO4 respectively and the numbers succeeding them denotes the concentration of salt in mM). Our investigation identified 72 h of treatment as ideal duration for iron-pulsing. At this time point, the seedling emergence attributes and activities of ?-amylase and protease increased. The relative water uptake of the seeds also increased through upregulation of aquaporin expression. The treatment efficiently maintained the ROS balance with the aid of antioxidant enzymes and increased the iron content within the treated seeds. After transplantation in field, photosynthetic rate and chlorophyll content enhanced in the treated plants. Finally, the post-harvest agro-morphological traits (represented through panicle morphology, 1000 seed weight, harvest index) and yield showed significant improvement with treatment. Sets C5 and S5 showed optimum efficiency in terms of yield improvement. To our best knowledge, this study is the first report deciphering the efficacy of iron-pulsing as a safe, cost effective and promising technique to escalate the yield of rice crops without incurring an environmental cost. Thus, iron-pulsing is expected to serve as a potential tool to address global food security in years to come. 2021 Elsevier B.V. -
Iron pulsing, a cost effective and affordable seed invigoration technique for iron bio-fortification and nutritional enrichment of rice grains
Rice being a major staple food for millions of people, it has been one of the major targets for bio-fortification and iron bio-fortification in rice has been in prime focus to address global micronutrient malnutrition. Commonly practiced methods for obtaining Fe biofortified rice includes soil amendments and foliar spray with iron salts, breeding and development of transgenic rice varieties with Fe-enriched grain are associated with impediments like high cost, labor intensiveness, sub-optimal outcome and approval for commercialization respectively. Iron pulsing technique has reportedly enhanced the carbon and nitrogen assimilation in rice seedlings, which has been translated in yield. Based on the previous findings, in the present study, we have undermined the efficacy of iron pulsing, in improving the iron content and nutritional status of rice kernel obtained from pulsed plants. The present study documents that kernel of seeds obtained from iron pulsed plants have a higher amounts of iron, carbohydrate, protein, lipid, vitamins, nutrient and anti-oxidants than that of non-treated ones. The iron localization studies revealed that iron was mostly present in the endosperm and embryo. Besides, the ferritin expression levels also validated the fact that, the treated grains have accumulated more iron. Thus, iron-pulsing can serve as a novel and propitious sustainable agricultural innovation for iron bio-fortification and improvisation of the overall nutritional value of the rice grains that is affordable, user and consumer friendly in years to come. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
IRIS Data Classification using Genetic Algorithm Tuned Random Forest Classification
Optimising hyper-parameters in Random Forest is a time-consuming undertaking for several academics as well as professionals. To acquire greater performance hyper-parameters, specialists should explicitly customize a series of hyper-parameter settings. The best outcomes from this manual setting are then modelled and implemented in a random forest algorithm. Several datasets, on the other side, need various prototypes or hyper-parameter combinations, which may be time-consuming. To solve this, we offered various machine learning models and classifiers for correctly optimising hyper-parameters. Both genetic algorithm-based random forest and randomised CV random forest were assessed on performance measures such as sensitivity, accuracy, specificity, and F1-score. Finally, when compared to randomised CV random forest, our suggested model genetic algorithm-based random forest delivers more incredible accuracy. 2022 IEEE. -
IPWM Based IBMSC DC-AC Converter Using Solar Power for Wide Voltage Conversion System; [Convertisseur DC-AC IBMSC bassur l'IPWM et utilisant l'ergie solaire pour un syste de conversion large tension]
This article proposes isolated bidirectional micro dc-ac single phase controlled (IBMSC) converter based on in-phase-voltage pulsewidth modulation (IPWM). This resonant IPWM converter, ratio of voltage conversion can be controlled from 0 to ?. So, this converter is highly referred for huge range voltage conversion. However, voltage conversion ratio determines power transfer direction and duty ratio. Power flow direction and duty cycle value can be varying smoothly, so it is suitable for dc-ac bidirectional power conversion application. Inverter mode and also rectifier mode are possible from bidirectional operation, which is controlled by a unified current controller. The proposed solution can achieve smooth switching grid operation with high efficiency. Working principle, design procedure, control strategy, and characteristics of the proposed converter are implemented with a prototype model of power rating 500 W with a voltage range of 20-50 V to test the ability of withstanding. Performance, feasibility, and effectiveness of the proposed converter are tested with this hardware test-bench model. 2022 IEEE. -
IPR in Stem Cell Research, Therapy, and Regenerative Medicine
According to the World Trade Organization, intellectual property rights are rights given to persons over the creations of their minds. They usually give the creator an exclusive right over the use of his or her creation for a certain period. There is a critical need for fresh developments in the existing medical diagnostic techniques, therapy, pharmaceutical medications, and research, in a world where such a sizable number of people are afflicted with various ailments, some of which are fatal and still incurable. Pharmaceutical companies are developing novel and cutting-edge ways to treat diseases at an increasing rate. The major pharmaceutical corporations in the world, including Pfizer, Miltenyi, Biotec, AstraZeneca, and Mesoblast Limited are pursuing research in the area of stem cell and regenerative medicine. Regenerative medicine, stem cell research, and therapy are currently regarded as groundbreaking developments in the medical sciences. Understanding their intellectual property rights and the legal means through which these businesses can safeguard their discoveries becomes crucial. This paper will analyze the meaning of stem cell and regenerative medicines, the eligibility of IPR in Stem cell research under the Indian Patents Act, of 1970 and the morality and public issues related to the same. 2024 Taylor & Francis. -
IoVST: Internet of vehicles and smart traffic - Architecture, applications, and challenges
The internet of things (IoT) is the network of sensors, devices, processors, and software, enabling connection, communication, and data transfer between devices. IoT is able to collect and analyze large amounts of data which can then be used to automate daily tasks in various fields. IoT holds the potential to revolutionise and create many opportunities in multiple industries like smart cities, smart transport, etc. Autonomous vehicles are smart vehicles that are able to navigate and move around on their own on a well-planned road. 2023, IGI Global. -
IoT-Powered Innovations in Renewable Energy Generation and Electric Drive
This review explores the growing impact of the Internet of Things (IoT) on the energy sector, particularly in the context of renewable energy generation and electric drive systems. IoT technology has rapidly expanded into various sectors, including energy, smart cities, and industrial automation, revolutionizing monitoring, control, and management processes. In this paper, we examine the existing literature on IoT applications in energy systems, with a focus on smart grids. We also delve into the core IoT technologies, such as cloud computing and data analysis platforms, that underpin these innovations. Additionally, we address challenges associated with IoT implementation in the energy sector, notably privacy and security concerns, and suggest potential solutions, such as blockchain technology. Our findings provide valuable insights for energy policy-makers, economists, and managers, offering a comprehensive overview of how IoT can optimize energy systems. Furthermore, we highlight IoT's expanding role in renewable energy and electric drive applications, enhancing performance monitoring, management, and energy savings while also advancing research and education in engineering. The Authors, published by EDP Sciences, 2024. -
IOT-Enabled Supply Chain Management for Increased Efficiency
Deep learning methods have demonstrated potential Supply chain is a set or group of people as well as companies responsible for producing goods and getting it to their consumers. The producers of the raw materials are the first links in the chain, and the vehicle that delivers the finished goods to the client is the last. Lower costs and higher productivity are the benefits of an efficient supply network, which emphasizes the importance of management of supply chain. The internet of things, or IoT, is a network of mechanical and digital technology that can communicate with one another and send data without the need for human contact. Smart items were included into the conventional supply chain system to increase intelligence, automation potential, and intelligent decision-making. The existing supply chain system is offering previously unforeseen chances to increase efficiency and reduce cost. The aim and motive of our research is to analyze the methods of supply chain management where the main elements of IoT in management of supply chain will be highlighted. 2024 IEEE. -
IoT-Enabled Analysis of COVID Data: Unveiling Insights from Temperature, Pulse Rate, and Oxygen Measurements
The COVID-19 pandemic has forced unparalleled transformation on healthcare systems around the world, demanding new and improved approaches for effective monitoring and diagnosis. In this context, we present a study titled IoT-Enabled Analysis of COVID Data: Unveiling Insights from Temperature, Pulse Rate, and Oxygen Measurements. The global impact of COVID-19, with millions of confirmed cases and fatalities, underscores the urgency of finding efficient monitoring solutions. To address this crisis, IoT-Enabled Health Monitoring Systems have emerged as a promising tool for remote patient monitoring and infection risk reduction. These systems leverage sensors to collect real-time data on the temperature, pulse rate, and oxygen saturation levels of the subject. The integration of a mobile application enables immediate access to this critical health information. In this study, we explore the use of IoT systems, which have demonstrated accuracy comparable to other devices on the market. By leveraging these technologies, we aim to provide healthcare professionals with valuable insights into patients health status, aiding in early detection, monitoring, and timely intervention. Our research contributes to the efforts to battle the COVID-19 pandemic by highlighting the potential of IoT-enabled monitoring systems in enhancing healthcare delivery, reducing infection risks, and ultimately saving lives. 2024 Scrivener Publishing LLC. -
IoT-Driven Credit Scoring Models: Improving Loan Decision Making in Banking
By the game-changing possibilities of credit scoring models driven by the Internet of Things, this hopes to shed light on how the banking sector may enhance its loan decision-making procedures. Financial organisations are putting more and more faith in Internet of Things technologies to improve their risk assessment and lending processes. These IoT-driven models provide a more accurate and thorough assessment of creditworthiness by including real-time and detailed data on borrowers' activities, spending habits, and asset utilisation. This research examines the practicality and accuracy of Internet of Things (IoT) credit scoring by comparing it to conventional methods, looking closely at case researches, and analysing empirical data. The findings shed light on potential ways to enhance the loan approval and risk prediction procedures while also addressing concerns and considerations related to data privacy, security, and regulatory compliance. It is possible that decision-making frameworks could be altered by IoT-driven credit scoring algorithms, which could lead to a more inclusive and informed lending atmosphere. The contributes to the growing area of banking credit evaluation by showing that these models have promise. 2024 IEEE. -
IoT-based traffic prediction and traffic signal control system for smart city
Because of the population increasing so high, and traffic density remaining the same, traffic prediction has become a great challenge today. Creating a higher degree of communication in automobiles results in the time wastage, fuel wastage, environmental damage, and even death caused by citizens being trapped in the middle of traffic. Only a few researchers work in traffic congestion prediction and control systems, but it may provide less accuracy. So, this paper proposed an efficient IoT-based traffic prediction using OWENN algorithm and traffic signal control system using Intel 80,286 microprocessor for a smart city. The proposed system consists of 5 phases, namely IoT data collection, feature extraction, classification, optimized traffic IoT values, and traffic signal control system. Initially, the IoT traffic data are collected from the dataset. After that, traffic, weather, and direction information are extracted, and these extracted features are given as input to the OWENN classifier, which classifies which place has more traffic. Suppose one direction of the place has more traffic, it optimizes the IoT values by using IBSO, and finally, the traffic is controlled by using Intel 80,286 microprocessor. An efficient OWENN algorithm for traffic prediction and traffic signal control using a Intel 80,286 microprocessor for a smart city. After extracting the features, the classification is performed in this step. Hereabout, the classification is done by using the optimized weight Elman neural network (OWENN) algorithm that classifies which places have more traffic. OWENN attains 98.23% accuracy than existing model also its achieved 96.69% F-score than existing model. The experimental results show that the proposed system outperforms state-of-the-art methods. 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
IoT-Based Smart Indoor Navigation System with Voice Assistance for Museums
In the current era of smart heterogenous devices, the surrounding environment too needs to be smarter to match the gravity of such devices. Such advanced environment can be built with the technology called Internet of Things (IoT). Due to the presence of such vivid thing devices in the Internet of Things (IoT) environment, the task of automatically predicting the end users desires can play an important role when it comes to match the pace of modern society with too much diverse aspects. Since last decade, people have deviated their attention towards Indian ancient culture and Museums are eye catching attraction where our ancient cultural heritage exist. To improvise the slow pace growth of the tourism sector, there is the crucial requirement of technological improvement especially due to the restrictions on installations of external hardware within the close proximity. One prominent way of improving tourists experience at museums is to renovate existing museums with IoT-based smart devices which is programmed such a way to automatically navigate the user indoor and briefs the associated information about artwork without any user intervention. In this paper, we propose an IoT-based smart indoor navigation system along with voice assistance which can enhance the tourists experience in a museum. In addition, the proposed design also delivers the very personalized cultural contents related to the visited artworks. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
IoT-based smart healthcare video surveillance system using edge computing
Managing distributed smart surveillance system is identified as a major challenging issue due to its comprehensive aggregation and analysis of video information on the cloud. In smart healthcare applications, remote patient and elderly people monitoring require a robust response and alarm alerts from surveillance systems within the available bandwidth. In order to make a robust video surveillance system, there is a need for fast response and fast data analytics among connected devices deployed in a real-time cloud environment. Therefore, the proposed research work introduces the Cloud-based Object Tracking and Behavior Identification System (COTBIS) that can incorporate the edge computing capability framework in the gateway level. It is an emerging research area of the Internet of Things (IoT) that can bring robustness and intelligence in distributed video surveillance systems by minimizing network bandwidth and response time between wireless cameras and cloud servers. Further improvements are made by incorporating background subtraction and deep convolution neural network algorithms on moving objects to detect and classify abnormal falling activity monitoring using rank polling. Therefore, the proposed IoT-based smart healthcare video surveillance system using edge computing reduces the network bandwidth and response time and maximizes the fall behavior prediction accuracy significantly comparing to existing cloud-based video surveillance systems. 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.