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Impact of Artificial Intelligence on the Social Media Marketing Strategies
The use of social media is increasing as the use of smartphones is increasing, various applications on smartphones are now becoming good platform for market. As the use of smartphones is increasing the use of different artificial intelligence (AI) technologies making the phones smarter. The social media is now one of the most globally crowded platforms with millions of users. Most of the businesses are now turning their marketing strategies by highlighting the digital marketing from various platforms. Thus, the focus of study is to find the increasing impact of AI on the social media related marketing strategies. Different studies highlight the different impacts of social media and marketing using different AI tools and platforms which makes customer to find the best product as per their choice. So, social media marketing has become simpler and more adaptable thanks to the development of artificial intelligence. 2024 IEEE. -
Impact of blended education system on outcome-based learning and sector skills development
An effective education system transforms the teaching and learning process into innovative idea generation and independent working ability. A blended education system is the representation of effective education that connects the teachers, students, and educational institutions for content development, delivery of effective teaching methods, and choice-based learning. The motive for initiating the research work was to address the demand for outcome-based learning in society that can fulfill the sector-wise human resource requirements and sector skill development. A blended education system helps to design effective courses and degrees with the capacity of choosing subjects, lectures, and teachers either in online or offline mode of education. The system may also assist in preparing the learning pattern like classroom-based learning, internship-based learning, or learning through project works. The researchers identified the dependent and independent variables with the help of expert opinion. The questionnaire was designed with all relevant questions based on the variables and refined through a pilot study. The research outcomes are described by understanding the nature of quantitative data using statistical tools like frequency distribution, t-test, and ANOVA test with the connectivity of qualitative data and the reality of social issues. 2023 IEEE. -
Impact of Childhood Trauma on Psychological Distress and Personality Pathology in Young Adults
Adulthood is a time of change, thus stressful. A predetermining factor to this is a provision for a safe environment during the crucial years of life (childhood). Children make meanings of everything and are more dynamic in the early developmental years. It is a basis for their overall development and defines their coping mechanisms during adulthood. Therefore, if they develop faulty meanings of themselves, others, and the world at large, it can alter their abilities to function during adulthood. It is fundamental to understand the psychological well-being and personality traits in adulthood by this very nature of traumatic experiences in childhood. This paper is a conceptual framework discussing a three-tier model to retrospectively understand the impact of childhood trauma on psychological distress and personality pathology in adulthood. This paper suggests future research to focus on developing intervention and prevention models for young adults (childhood trauma survivors) on positive parenting practices. The Electrochemical Society -
Impact of Corporate Announcement of Green Innovation on Automaker's Market Value -An Event Study Methodology
The aim of this paper is to analyse the effects of the Green Innovation event and corporate announcements regarding green innovation on the stock price of the Automobile Industry and the performance of firms. The authors also aim to assess the impact of these events on business performance and identify the effective innovation strategy influenced by the type of corporate announcement. The study focuses on the corporate announcements made by the automobile industry and their impact on company performance, specifically in relation to the application of green innovation methods. Furthermore, there is no universally agreed upon standard for defining and categorising corporate announcements. The writers also exclude the impact of media and other events that occur during the event window when categorising these announcements. The findings of this study have important practical consequences. They suggest that the release of green innovations, which aim to protect the environment, can have an impact on an organization's stock market success. Specifically, the type of innovation and the trade segment in which the organisation operates can influence its stock market performance. Grenze Scientific Society, 2024. -
Impact of demand response contracts on short-term load forecasting in smart grid using SVR optimized by GA
In a Smart Grid environment the performance measure of the grid is calculated by considering the fact that how accurately and precisely a load forecasting (LF) is done. A true Load Forecasting is vital to make a current grid smarter and more reliable when it comes to its performance. Demand Response (DR) contracts is a type of program in smart grid where the customer is free to select a type of contract which is given by the utility and is one of the growing factor which affects the load forecasting results in the Smart Grid, therefore in order to do a complete evaluation of smart grid performance and to accomplish an accurate load forecasting results the different types of contracts should also be studied. The purpose of this study is to accomplish two goals. The first one is to develop a suitable model which can incorporate various factors that can affect the load forecasting results. The subsequent goal is to identify the impact of the demand response contracts on the load forecasting results. In the proposed study, Support Vector Machine-Regression (SVR) is selected as the base methodology to perform a Short - Term Load Forecasting (STLF) under smart grid environment. 2017 IEEE. -
Impact of Demographicson Green Behavior
The need to preserve the environment, lower pollution levels, expand the amount of green space, and encourage environmentally responsible behavior has grown in recent years, all of which will contribute to a more sustainable society. This study seeks to determine the probability that demographic variables of students in higher education in Delhi NCR will influence their desire to participate in environmental education. Binary Logistics Regression has been used on the data gathered from 302 respondents and the model has been found to have been a good one as shown by Omnibus Test. It is found that 'Gender' and 'Field of Study' are the two most significant variables, which have a higher probability impact on students' willingness to join environmental education. Specifically, female students vis-vis male students and students with engineering & and science background vis-vis other students have more chance of joining environmental education courses. 2024 IEEE. -
Impact of Digital Media Marketing on Consumer Buying Decisions
Digital Marketing has become one of the most discussed topics in the field of management in the recent past. With the advent of social media, digital marketing has even garnered more attention. It has directly or indirectly influenced the buying behaviour of the customers also. This paper has tried to understand the impact of digital marketing in influencing the impulsive buying behaviour of the customers. 2024 IEEE. -
Impact of e-commerce on India's exports and investment
E-commerce has become an important mode of trade, both domestically and internationally. E-commerce provides a platform for exchange of goods and services and thus directly alters the cost of trade and profits of firms, while simultaneously, generates a demand for a different set of skilled managers and creates opportunities for increasing investment and thereby affects the volume of domestic and international trade and in-turn affects the overall level of output and employment in an economy. There are empirical evidences on how certain developed countries like UK, USA, earlier, and lately developing countries like China, have leveraged e-commerce to enhance international trade. This paper attempts to contribute to the literature by studying the impact of e-commerce on India's international trade, especially exports, and investment which in-turn impact the level of output/gross domestic product (GDP) and employment in the country. Copyright 2021 Inderscience Enterprises Ltd. -
Impact of ESG Practices on the Firm's Performance: A Longitudinal Study on Emerging Markets
This study investigated the relationship between business performance in emerging markets (BICS countries) and ESG disclosure scores. Overall, it did not find any correlation between different performance indicators and ESG scores. It's interesting to see that higher overall ESG scores were linked to greater share prices and earnings per share (EPS). This implies that businesses with robust ESG policies may ultimately perform better than others. The study emphasises how ESG may help create value and support sustainable corporate success in emerging markets. It highlights how crucial ESG is to investors, companies, and legislators. 2024 IEEE. -
Impact of Expert Academic Teaching Quality and its Performance Based on BiLSTM-Deep CNN Network
Undergraduate and postgraduate students from eight different departments at a UK institution participated in organized conversations about the impact of teachers' research activities on their education. In both samples, positive responses greatly outnumbered negative ones. There was an increase in positive feedback on professors' research when the overall quantity and quality of research in a specific field (as measured by Research Assessment Exercise [RAE] ratings) improved. Undergraduate samples with higher RAE scores were more likely to have negative feedback on research than graduate student samples. Both graduate and undergraduate students agreed that lecturers' research increased the instructor's credibility, relevance, and knowledge, as well as piqued and maintained their own interest, engagement, and drive. Data processing, feature selection, and model training are the first steps in the proposed approach. The data are changed from their raw form into a form suitable for academic use during the data pre-processing phase. They are employing Information Gain and Symmetric Uncertainty for feature selection. Following the feature selection process, the models are trained using BiLSTM-CNN. Both the BiLSTM and the CNN methods are inferior to the proposed method. 2023 IEEE. -
Impact of green bonds issuance on stock prices - Evidence from India
Today, with the increasing global warming, many companies are trying to adopt sustainable ways of producing the product and preserve the atmosphere. A green bond is one such financial tool that helps companies to raise the funds for social and eco-friendly projects. Keeping this in view and the Indian market emerging as the second-largest bond market in terms of green bond issuance; this paper aims to identify the impact on stock prices due to the issuance of green bonds by the companies. We conduct an event study to understand how the stock prices are subject to volatility due to green bond issuance during the period 2018-2021. The data is collected from secondary sources like Economic Times, Business Standard, Climate Bond Initiative, and the BSE website. The event window is assumed to be [-30,30], [-15, 15] and [-7, 7] days. Using Cumulative Average Abnormal returns and t-tests we understand the volatility of stock prices due to green bond issuance. The empirical results show that green bonds have a short-term impact on stock prices. Overall, the study can be a great input for the investors to understand the behavior of stocks due to the issuance of green bonds. 2023 Author(s). -
Impact of Homophily on Patient Empowerment: A Study of Online Patient Support Groups
Internet facility has led to emergence of patient support groups. These have gained prominence as these fulfils important benefits to patients. One such benefit is patient empowerment. These online groups provide opportunity to patients to interact with similar ailments and predicaments and who can understand the pain and discomfort felt by the patient. This provides validation for the patient and patients experiences. How does this homophily impacts patient empowerment? This question has been explored in this study. The methodology is based on an online survey of patients visiting such online platforms. In all 701 patients provided the data. Independent variable (homophily) and dependent variable (patient empowerment) have been measured using a 7-point Likert scale. Findings provide that both are weakly correlated, but this correlation is significant. Regression analysis led to a regression model that is fit statistically. This provides basis to encourage patients to visit online support groups. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Impact of Learning Functions on Prediction of Stock Data in Neural Network
Digitization has made a vast impact on the modern society. Financial sector is one field where a huge revolution has been experienced because of digitization. Financial data especially time series data is being stored in the digital repositories where it can be used for prediction and analysis. One such data is a stock market data which is a time series data and is generated in a huge amount every second. The stock market data is of great importance as the proper analysis and prediction of data can transform the fate of the global market. Thus the companies and the individuals are looking forward for the development of the automated techniques that can predict stock market data accurately in a real time. In this regard, many researchers developed machine learning techniques such as use of neural network for prediction of stock data. The most common learning function used in neural network is sigmoid function. However, we found that there are many learning functions are available for building neural network. In this paper we are studying the impact of four different learning functions in estimating/predicting the stock value. From the experimental study we found that unipolar sigmoid learning function produced an accuracy of 95.65%, bipolar sigmoid produced an accuracy of 91.34%, tan hyperbolic equation produced an accuracy of 91.02%, and radial base equation produced an accuracy of 87.53%. Clearly, unipolar sigmoid function emerged as the best learning function to build stock data prediction model. The main reason behind its out-performance of unipolar sigmoid is its less complex structure and the 0 to 1 range. 2018 IEEE. -
Impact of Machine Intelligence on Clinical Disease Outbreak Prediction
This research paper examines the utilization of Artificial Intelligence (AI) in disease outbreak prediction and its importance in public health. It explores the hurdles associated with predicting disease outbreaks, including data quality and accessibility, ethical considerations, algorithmic bias, and integration and interpretability challenges. The paper presents an overview of AI techniques applied in healthcare and their relevance to forecasting disease outbreaks. Case studies demonstrate the efficacy of AI -based models in predicting infectious diseases, vector-borne diseases, and epidemics/pandemics, employing diverse data sources. The limitations and future prospects of AI in disease outbreak prediction are addressed, accompanied by recommendations for enhancement. In conclusion, the paper highlights AI's potential to revolutionize disease outbreak prediction, leading to proactive public health interventions and improved response strategies. 2023 IEEE. -
Impact of Machine Learning Algorithms in Intrusion Detection Systems for Internet of Things
The importance of security aspects is increased recently due to the enormous usage of IoT devices. Securing the system from all sorts of vulnerabilities is inevitable to use IoT applications. Intrusion detection systems are power mechanism which provides this service. The introduction of artificial intelligence into intrusion detection systems can further enhance its power. This paper is an attempt to understand the impact of machine learning algorithms in attack detection. Using the UNSW-NB 15 dataset, the impact of different machine learning algorithms is assessed. 2021 IEEE. -
Impact of Meltdown and Spectre Threats in Parallel Processing
[No abstract available] -
Impact of Perceived Social Support on Patient Empowerment: A Study of Online Patient Support Groups
Disease-specific online patient support groups have emerged predominantly in last 30years, and these are being visited by a large number of patents. These platforms obviously bring important benefits to the patients visiting them. An important variable is the perceived social support that patients feel they derive while interacting with healthcare providers and fellow patients over there. Patient empowerment is another variable, and which has been found to be a critical factor in overall well-being of patients. How does the perceived social support felt by patients visiting an online patient support group impact their perceived empowerment? This paper explores this question. Research design is associative, and for which the data has been procured online from the patients visiting online patient support groups. The questionnaire comprises of an independent variable (perceived social support) and a dependent variable (patient empowerment). Validated scales have been used. For analysis, a factor analysis was undertaken to reconfirm the validity of the scales. Thereafter, regression equation has been developed to measure the impact. Results show that the model obtained passes the fitness and the independent variable has a significant positive association with patient empowerment. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Impact of Prolonged Screen Time on the Mental Health of Students During COVID-19
The COVID-19 pandemic has struck every sector around the world, including the education sector. The pandemic has forced educational institutions around the world to close, putting academic calendars in jeopardy. To keep academic activities going, most educational institutes have switched to online learning platforms. However, the lack of e-learning readiness and the current crisis has taken a toll on students mental health significantly. In this study, we hope to understand better students impressions of online education and the impact of prolonged screen time on students mental health. From the responses of 438 students, our study aims to identify the causes of stress in students due to the online mode of education. From eye stress to limited social interaction, all factors leading to poor mental health are considered. Suggestions for addressing the challenges of online education and approaches to create a more successful online learning environment are also provided. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Impact of Risk Perception on Use and Satisfaction with Online Pharmacies and Proposed Use of IoT to Minimize Risks
This study investigates consumer risk perceptions regarding online pharmacies and their impact on usage frequency and satisfaction. The growing popularity of online pharmacies offers benefits such as accessibility, cost savings, and privacy. However, significant risks, including the potential for counterfeit drugs and insufficient medical oversight, raise concerns. This study has measured consumer perceptions of risk, satisfaction, and usage frequency through a survey conducted in Northeast India, excluding Sikkim (online) and Sikkim (offline). The findings reveal that the fear of receiving counterfeit medications is a significant risk factor, negatively influencing both the frequency of use and consumer satisfaction. Despite this, the impact is relatively weak, suggesting that while risk perception is a concern, it does not significantly deter online pharmacy usage. The study suggests that integrating advanced technologies such as IoT, RFID, and blockchain can mitigate these risks by ensuring the authenticity of medications in the supply chain. 2024 IEEE. -
Impact of Urban Environmental Quality, Residential Satisfaction, and Personality on Quality of Life among Residents of Delhi/NCR
Environmental quality and Sustainability seek to preserve, enhance and protect our environmental resources that directly aim at providing an amicable quality of life and sustainable development for the upcoming generations. Considering the hazardous environmental urban quality in Delhi NCR, air pollution is the topmost factor deteriorating health of the population in general. The urban air database by WHO reports Delhi exceeding the maximum PM10 limit by almost 10-times at 292 ?g/m3. Noticing that an individual's surroundings have an enormous value in human lives, the study aimed at understanding the impact of urban environmental quality, residential satisfaction, and personality on the quality of life among residents of Delhi NCR. In addition, we also track the environmental worldviews to attitudes on pro-environmental behavior in understanding sustainability. The results from the SEM model indicated that one index rise in RESS lead to a fall in quality of life by 0.029-point value whereas one index rise in personality could enhance the quality of life by 0.15-point value. Pro-Environmental Behaviors and Urban Environmental factors did not showcase any significant impact on the quality of life. The Electrochemical Society.