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Teacher-Trainess Attitude Towards ICT
Journal of Education and Practice, Vol-4 (19), pp. 18-21. ISSN-2222-1735 -
Investigating the Dynamic Interlinkages between Exchange Rates and the NSE NIFTY Index
This study aims at examining the short-run and long-run dynamic linkages among exchange rates and stock market index in India through a structured cointegration and Granger causality tests. Daily exchange rates of USD, EUR, CNY, JPY, and GBP to INR along with the daily movement of NSE NIFTY for a period spanning 13 years from 6 September 2005 to 31 December 2018 were used for the analysis. The results reveal that there is no evidence for a stable long-run relationship between NSE NIFTY and the exchange rates under study. However, the VAR-based Granger causality test shows that USD, JPY, and CNY have short-run causal relationship with NSE NIFTY. The NSE NIFTY also seemed to have an influence on USD expressed in terms of Indian rupee. The impulse response analysis further supports the results of the Granger causality test and provides information on the time required for the NSE NIFTY index to recover from a shock caused by the fluctuation in exchange rates. 2021 by the authors. -
From a recession to the COVID-19 pandemic: Inflation-unemployment comparison between the UK and India
The recession in India and the UK peaked in 2017 due to the implications of new policy initiatives. The outbreak of the COVID-19 pandemic at the beginning of 2020 intensified the crisis, causing a drastic decline in aggregate demand and output. India and the UK have resorted to monetary and fiscal stimulus packages to face the economic crisis. This study investigated the inflation-unemployment dynamics during the recession and COVID-19 times in India and the UK. Using a generalized additive model (GAM), the results of this study revealed that the recession had given way to stagflation in India. In contrast, in the UK, it has led to a more severe recession in the short-run. During the downturn, policy initiatives aggravate the recession and eventually turn to stagflation in India due to inflation caused by the weak supply side. However, in the UK, the policy initiatives during this downturn pushed the economy into a deeper recession due to reduced demand. The outbreak of the COVID-19 pandemic has had a similar recessionary impact on both economies. A time horizon based recovery plan is suggested to help the economies recover from stagflation and even deeper recession. This framework could enable policymakers to choose the right path of recovery within the shortest possible time. 2021 by the author. Licensee MDPI, Basel, Switzerland. -
Nudges and choice architecture in public policy: A bibliometric analysis
In recent years, nudges and choice architecture have gained significant attention amongst researchers, particularly in the domain of public policymaking. This study contributes to the existing literature on the application of nudges and choice architecture in public policy through a bibliometric analysis. A total of 419 documents from the Web of Science database from 2010 to 2021 were analysed, identifying the most prolific authors, foundational works, and sources, along with primary research themes. The study identifies keywords and themes that shape the current research trends and visualizes the intellectual structure of empirical works. The findings show an increasing focus on this subject area over the past decade, with a growing interest in themes such as dietary habits, healthcare, effectiveness of behavioral interventions, and sustainable choices. The application of nudges and choice architecture in policies related to health, food consumption, and diet management has also become increasingly prevalent as evidenced by the exponential growth in publications on these topics. 2023 Elsevier Inc. -
Consumer response towards personalised pricing strategies in online marketing
E-tailers are now capable of customising prices for an individual buyer or a group of buyers who exhibit similar behavioural traits and perceived ability to pay. Tailoring prices based on personal information may evoke unanticipated reactions as it could infringe users privacy and hurt fair price perceptions. To investigate the potential impact of positive and negative online personalised pricing situations, this study conducted a controlled experiment to observe the changes in consumer behaviour in a personalised pricing context. Seven hundred and twenty responses were collected from thriving online-active communities in India and Malaysia, both countries with high growth of e-commerce activities. Consumers reaction towards fair price, customer loyalty, privacy concern, purchase satisfaction; and the influence of these constructs on post purchase behaviours such as repurchase intentions, revenge intentions and strategic purchase intentions were analysed using PLS SEM modelling. Results indicate online consumers in both countries have high privacy concerns, and as it increased, their repurchase intentions decreased correspondingly. Strategic purchase intentions and revenge intentions increased regardless of positive and negative purchase situations, while purchase satisfaction mediates fair price perceptions and repurchase intentions. Copyright 2021 Inderscience Enterprises Ltd. -
An approach to develop content based video modules /
Researchers World Journal Of Arts Science And Commerce, Vol.7, Issue 1, pp.101-104, ISSN: 2231-4172. -
Financial Freedom, social Capital, and the Development of Rural Women Entrepreneurship in India; [?????????? ???????, ?????????? ??????? ? ???????? ??????????????????? ????? ???????? ?????? ? ?????]
Human resource development can only be achieved by promoting female entrepreneurship. There is a very low level of female entrepreneurship in India, especially in rural areas, which has recently been a cause for concern. Women are now aware of their existence, privileges, and employment circumstances.The subject of this research is female entrepreneurs in rural India, their contribution towards society, problems faced by women entrepreneurs in India, and initial steps taken by the administration for their development in Indias rural region. The research is explanatory. The primary data is used in the paper. The self-structured questionnaire was circulated to the women entrepreneurs in rural India. The data collected was analysed using a targeted sampling method in the Statistical Package for Social Sciences programme, followed by a study of the statistical results. During the survey, 44 respondents were interviewed. The results showed that among the most significant challenges were womens family responsibilities, gender inequality, financial difficulties, low risk inclination and competition between men and women. It was concluded that the challenges faced by women entrepreneurs could be addressed through appropriate incentives, training, encouragement, social recognition of their entrepreneurial capabilities and appropriate family support. Victor M., Elangovan N., Halaswamy D., Sonia M., 2024. -
Behavioural nudges and maternal diet: Results from a cluster-randomised pilot trial among pregnant women in India
Micronutrient shortfalls pose a significant threat to maternal health across India. We evaluate whether brief, low-intensity informational nudges can improve short-run maternal diet quality during pregnancy. We conducted a pilot cluster-randomised controlled trial across 22 primary health centre (PHC) catchments in Karnataka, assigning catchments to one of three behavioural interventions (printed pamphlets, Accredited Social Health Activist (ASHA) home visits, or research-team phone calls) or to routine-care control. A panel of 440 pregnant women was surveyed at baseline and again four weeks later. Primary outcomes were small meal frequency and two 24-hour dietary diversity measures: a continuous score and the binary Minimum Dietary Diversity for Women. Using multi-arm difference-in-differences models with pooled specifications, we find modest improvements over time across all arms. However, the interventions did not improve meal frequency or dietary diversity relative to the control group. These inferences were robust to 100 control-group subsampling iterations. Over this four week pilot period, low intensity, information only nudges did not improve meal frequency or dietary diversity beyond standard care by policy relevant amounts, helping bound the short run impacts of brief informational messaging in this setting. 2026 Elsevier Inc. -
From Text to Ticker: A Comprehensive Survey and Methodological Guide to Named Entity Recognition in Finance
The financial industry generates vast volumes of unstructured textual data from sources such as regulatory filings, news articles, social media, and earnings call transcripts. Extracting structured and actionable intelligence from this data remains a significant challenge. Named Entity Recognition (NER) is a fundamental task in natural language processing that supports this process by identifying and categorizing key information within text. However, the linguistic complexity, contextual ambiguity, and domain-specific terminology of financial text require specialized approaches that extend beyond general-purpose NER models. This paper presents a comprehensive survey and methodological guide to Financial Named Entity Recognition (Fin-NER). It begins by introducing the core concepts of NER while highlighting the unique challenges posed by financial text. The paper then reviews the evolution of Fin-NER approaches, ranging from rule-based systems and classical machine learning techniques to modern deep learning architectures. Furthermore, it analyzes the distinction between fine-tuned transformer-based models and general-purpose large language models in the current research. The study also examines commonly used datasets and evaluation metrics for benchmarking Fin-NER systems. Finally, it discusses key findings, existing methodological limitations, and future research directions, including hybrid modeling strategies, cross-lingual datasets, and the development of more reliable and explainable systems. Overall, this work serves both as a scholarly review of the Fin-NER field and as a practical guide for researchers and practitioners seeking to transform unstructured financial text into structured and informative representations. 2026 IEEE. -
Combining Text Information and Sentiment Dictionary for Sentiment Analysis on Twitter During Covid
Presence of heterogenous huge data leads towards the 'big data' era. Technique's proliferation is rapidly increasing data and making dynamic changes that results in 'big data' world. Progressive transition in technologies and adoption of social media in the society also stepped into the 'big data' epoch. Social media popularity is uprising attention in the community. This platform reduces the communication gap among people. Recently, tweeter use increased with unprecedented rate. Presence of social media like tweeter has broken the boundaries and touches the mountain in generating the unstructured data. It opened research gate with great opportunities for analyzing data and mining 'valuable information'. Sentiment analysis is the most demanding, versatile research to know user viewpoint. Society current trend can be easily observed through social network websites. These opportunities bring challenges that leads to proliferation of tools. This research works to analyze sentiments using tweeter data using Hadoop technology. This study explores the big data arduous tool called Hadoop. Further, it explains the need of Hadoop in present scenario and role of Hadoop in storing ample of data and analyzing it. Hadoop cluster, HDFS, and Hive are also discussed in detail. Researchers enthusiastic work is deeply studied and presented here. Dataset used in performing the experiment is explained briefly. Moreover, this research explains thoroughly the implementation work and provide workflow. Next session provides the experimental results and analyzes of result. Finally, last session concludes the paper, its purpose, and how it can be used in upcoming research. 2024 IEEE. -
Pioneering Security in Healthcare: Reversible Data Hiding for ECG Signals and Patient Information
A population in large across worldwide grieve from cardiac illnesses, leading towards an increase in the popularity of telecardiology. Consequently, a significant quantity of electrocardiogram (ECG) signals and sensitive patient information are communicated over the Internet. Using electrocardiogram (ECG) signals as the host medium, this system safeguards the patient's personal information. Nevertheless, it was not possible to replicate the original electrocardiogram (ECG) signal entirely. Therefore, any alterations that occur on EKG have the potential to lead physicians to make an inaccurate diagnosis, which is something that the patient cannot accept. According to the fundamental viewpoint presented in this study, reversible hidden data must completely hide the patient information and ECG signals when they are present. Discreet patient data leading to their personal attributes should be incorporated into the electrocardiogram which is ECG signal while preserving a high level of visibility. On the other hand, in order to safeguard the confidentiality of the patient and the ECG signal, we employ a single built-in encryption mechanism. The ECG instance which is watermarked is recreated in detail. The findings presented herein provide evidence that the proposed method can be reversed. 2026 IEEE. -
Exploring the effect of Covid-19 on herding in Asian financial markets
We examine herding behavior before, during, and after the Covid-19 pandemic in eight prominent Asian stock markets. Daily stock returns for the period Jan- 2018 to July- 2022 in the markets were investigated using the models prescribed by Chang et al., (2000) and Chiang and Zheng (2010). The empirical results provide strong support to earlier studies by providing robust evidence of herding in Vietnam, Indonesia, India, South Korea, and Singapore when the market is bullish and Indonesia and Vietnam also exhibit herding when the market is bearish. Herding tendency is dominant for Vietnam, India, and Indonesia during the pandemic with the post-pandemic time being more potent for China and Vietnam. Notably, an anti-herding tendency is found in China, Hong Kong, and Singapore. As a policy measure, efficient information dissemination, deterrence of insider trading, and regulation of mispricing can be undertaken. 2022 -
An Empirical Analysis of Factors and Variables Influencing Internet Banking among Bangalore Customers
International Journal of Research in Computer Application & Management, Vol. 2, Issue 10, pp. 143-148, ISSN No. 2231-1009 -
N-rGO/NiCo2O4 nanocomposite for high performance supercapacitor applications
Spinel structured transition metals oxide GO/NiCo2O4 nanocomposites and nitrogen doped N-rGO/NiCo2O4 nanocomposites were developed. Powder X-ray diffraction investigations confirmed the structure. The bonding vibrations of the produced nanocomposites were confirmed using infrared and Raman spectroscopy. EDX analysis was used to determine the composition and element weights of the nanocomposites. The electrochemical properties of the nanomaterials were measured using 1M KOH electrolyte. At 5mVs?1 scan rates, cyclic voltammetry revealed a specific capacitance (Csp) of 1078.2 Fg?1 for N-rGO/NiCo2O4. The bare and nanocomposites of NiCo2O4, GO/NiCo2O4, and N-rGO/NiCo2O4 specific capacitance, charge-discharge capability, and cyclic stability were investigated. Energy density and power density of the N-rGO/NiCo2O4 nanocomposite were estimated to be 20.4 Wh kg?1 and 1300W kg?1, respectively. N-rGO//N-rGO/NiCo2O4 asymmetric supercapacitor device with Ed of 14.9 Wh kg?1 and Pd of 3500W kg?1 was fabricated. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Effects of nitrogen, sulphur, and temperature treatments on the spectral, structural, and electrochemical characteristics of graphene oxide for energy storage applications
The structural and surface modifications have been studied on the hydrothermally Nitrogen (N) and Sulphur (S) doped and thermally reduced at 350 C nitrogen-doped, nitrogen-sulfur-doped graphene oxides. Raman spectra confirmed the reduction of graphene oxides by shifts in position and intensity variations of the D and G bands. EDX and mapping images revealed the carbon-oxygen ratio as well as the doping of nitrogen and sulphur into two-dimensional graphene oxide. The electrochemical properties of undoped and doped graphene oxides were investigated using a three-electrode system using a 1 M KOH electrolyte. It shows how doping, and reduction improve current conduction in graphene oxides. The specific capacitance of N,S-rGO after being synthesized and reduced at 350C was 930 Fg?1 and 1059 Fg?1, respectively, according to cyclic voltammetry results. The N-rGO specific capacitance was found to be similar, with 850 Fg?1 and 891 Fg?1, respectively, for the as prepared and reduced at 350C. The charge-discharge analysis, cycle stability, and impedances for the applied frequency ranges of undoped and doped graphene oxides for energy storage applications have all been estimated and discussed. 2023 -
Influence of annealing on the morphological, structural and electrochemical properties of Co3O4 spinel electrodes
Effectual use of energy requires the conversion and storage device with great ability. In this research, Co3O4 nanoparticles are achieved via facile and low-cost reflux method. The consequence of annealing treatment on morphological, structural, and electrochemical behaviors of produced Co3O4 (350, 550, 750 and 950 C) nanoparticles are investigated. XRD analysis exposes the formation of cubic Co3O4 spinel above 300 C annealing temperature. SEM and EDX study demonstrate that the morphology of Co3O4 nanoparticles changes with different annealing temperatures. The electrochemical performance of prepared Co3O4 (350950 C) nanoparticles was determined via charge-discharge experiment, and electrochemical impedance, cyclic voltammetry studies. It exposes that the annealing treatments have an important effect on the specific capacitances. Among them, the optimized Co3O4 (950 C) electrode demonstrates the best capacitive behaviors in the three-electrode cell, which exhibitions the best capacitance value of 1388 Fg?1 at 5 mVs?1 and outstanding cycling capability of 97.2 % capacitance even after 5000 cycles. The asymmetric supercapacitor device assembled by Co3O4 (950 C) displays a capacitance value of 519.3 Fg?1 for 5 mVs?1 and long reversible capacity (92.7 % capacitance retains after 5000 cycles) and a high-power density (26.7 W h Kg?1). These outcomes exposed that the Co3O4 (950 C) nanoparticles could be a perfect candidate for eminent electrochemical application as electrode materials. These results state that Co3O4 nanoparticles are a multipurpose material and thus can be applied in numerous applications namely gas sensors, fuel cells, solar cells, electrochemical sensors, and photocatalysis. 2023 Elsevier Ltd -
A Comprehensive Survey on Deep Learning Techniques for Digital Video Forensics
With the help of advancements in connected technologies, social media and networking have made a wide open platform to share information via audio, video, text, etc. Due to the invention of smartphones, video contents are being manipulated day-by-day. Videos contain sensitive or personal information which are forged for one's own self pleasures or threatening for money. Video falsification identification plays a most prominent role in case of digital forensics. This paper aims to provide a comprehensive survey on various problems in video falsification, deep learning models utilised for detecting the forgery. This survey provides a deep understanding of various algorithms implemented by various authors and their advantages, limitations thereby providing an insight for future researchers. 2024 World Scientific Publishing Co. -
Real-Time Fire Detection Through the Analysis of Surveillance Videos
The Forest Fire Detection System is an intelligent system that can detect forest fires and alert authorities in real-time. It uses a YOLOv5 deep learning algorithm to process live video feeds captured by a web camera which is trained with the sizable dataset of inputs to locate the fire accurately, making it an ideal choice for real-time fire detection in the forest. Upon detecting a fire, the system sends an email alert to a designated email address, containing a picture of the fire and location information. The email alert system is built using the standard SMTP protocol, which ensures that the message is delivered to the recipient in a timely and reliable manner. The system is also equipped with a speaker that triggers an alarm upon detecting a fire. The alarm is designed to alert people in the vicinity of the fire so that they can take the necessary action. It is activated using the Pygame library, a collection of Python modules specifically crafted for game development across multiple platforms. Overall, the Forest Fire Detection System is a fast, efficient, and accurate system that can help prevent the spread of forest fires. It is an intelligent system that can detect fires quickly and send alerts to authorities, giving them the information they need to take the necessary action to control the fire. The system is built using a web camera, a computer, and a speaker, making it easy to install and maintain. 2024 IEEE.