Browse Items (16488 total)
Sort by:
-
Sigmoidal Particle Swarm Optimization for Twitter Sentiment Analysis
Social media, like Twitter, is a data repository, and people exchange views on global issues like the COVID-19 pandemic. Social media has been shown to influence the low acceptance of vaccines. This work aims to identify public sentiments concerning the COVID-19 vaccines and better understand the individuals sensitivities and feelings that lead to achievement. This work proposes a method to analyze the opinion of an individuals tweet about the COVID-19 vaccines. This paper introduces a sigmoidal particle swarm optimization (SPSO) algorithm. First, the performance of SPSO is measured on a set of 12 benchmark problems, and later it is deployed for selecting optimal text features and categorizing sentiment. The proposed method uses TextBlob and VADER for sentiment analysis, CountVectorizer, and term frequency-inverse document frequency (TF-IDF) vectorizer for feature extraction, followed by SPSO-based feature selection. The Covid-19 vaccination tweets dataset was created and used for training, validating, and testing. The proposed approach outperformed considered algorithms in terms of accuracy. Additionally, we augmented the newly created dataset to make it balanced to increase performance. A classical support vector machine (SVM) gives better accuracy for the augmented dataset without a feature selection algorithm. It shows that augmentation improves the overall accuracy of tweet analysis. After the augmentation performance of PSO and SPSO is improved by almost 7% and 5%, respectively, it is observed that simple SVM with 10-fold cross-validation significantly improved compared to the primary dataset. 2023 Tech Science Press. All rights reserved. -
Students Satisfaction with Remote Learning During the COVID-19 Pandemic: Insights for Policymakers
Purpose: This study aimed to learn more about the factors influencing student happiness and involvement in remote learning in Indian higher education institutions (HEIs). The study aims to assist administrators, strategists, and politicians in efficiently dealing with educations new normal. Methodology: The study used a quantitative research approach to fulfill the research aims. A sample of 546 students from various Indian HEIs was chosen, and data were gathered using standardized questionnaires. Structural equation modeling, confirmatory factor analysis, and importance-performance analysis (IPA) were used to calculate the student satisfaction index and examine the impact of various factors. Findings: The findings of this study revealed that institutional and faculty support emerged as the most influential factor impacting students satisfaction through remote learning. It also highlighted the need for HEIs to redesign the assessment process and evaluation techniques to adapt to the remote learning environment. Practical Implications: The findings of this study indicated the practical consequences for administrators, strategists, and policymakers at Indian HEIs. It was advised that improving institutional and teacher support should be a major concern in order to improve student happiness in remote learning situations. Furthermore, redesigning assessment procedures and evaluation processes may improve learning outcomes and student engagement. Originality: This study contributed to the existing body of knowledge by specifically investigating the factors influencing student satisfaction in remote learning within Indian HEIs. The findings shed light on the unique challenges and opportunities the shift to remote education presented. They offered valuable insights for managing and improving the quality of education during and beyond the pandemic. 2023, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Pre Packaged Insolvency - Exploring An Alternative Framework For Bankruptcy Resolution In India
This article is a review of literatures on the need for alternative bankruptcy resolution framework in India. The study explores the context & background to the recent initiation of limited Pre-Packaged Insolvency in India. The article makes a strong case for having a private & pre-negotiated mode of debt resolution along with the existing CIRP framework in India. The article provides a comparative perspective of CIRP and Pre-pack driven resolution model in India. The research paper also addresses some of the potential challenges & concerns related to initiation of pre-pack in India & accordingly discusses the relevant safeguards for the same. Lastly, the study also provide a brief view of pre-pack model currently practised in USA. The Electrochemical Society -
The mental health climate crisis: Unveiling the hidden consequences of global warming
Today, the issue of climate change is a matter of great urgency on a global scale, with vast-reaching implications. While the environmental and physical health effects of climate changes are well-documented, its impact on mental health is an emerging area of concern. The issue of climate change necessitates a rigorous and systematic approach to comprehending, evaluating, and addressing climatic anxiety. This approach must underscore the differentiation between adaptive and maladaptive forms of anxiety, and the importance of considering the societal-level response necessary to effectively combat climate change. Studies have documented the impact of natural calamities like Hurricane Katrina on low-income people residing in those areas. The present study rests on the objectives of examining the psychological impact of climate change on individuals, communities, and vulnerable populations with the help of literature. Further, investigation is continued on the role of climate-related stressors, such as natural disasters, heatwaves, and environmental degradation on mental health outcomes. The study also identified the potential interventions and strategies for mitigating the adverse impact on mental health due to climate change. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Message from IEEE InC4 2024 Publication Chair
[No abstract available] -
Recent Advances in Analytical Techniques for Antidepressants Determination in Complex Biological Matrices: A Review
Depression is one of the most prevalent but severe of mental disorders, affecting thousands of individuals across the globe. Depression, in its most extreme form, may result in self-harm and an increased likelihood of suicide. Antidepressant drugs are first-line medications to treat mental disorders. Unfortunately, these medications are also prescribed for other in- and off-label conditions, such as deficit/hyperactivity disorders, attention disorders, migraine, smoking cessation, eating disorders, fibromyalgia, pain, and insomnia. This results in an increase in the use of antidepressant medications, leading to clinical and forensic overdose cases that could be either accidental or deliberate. The findings revealed that people who used antidepressants had a 33% greater chance of dying sooner than expected, compared to those who did not take the medications. Analytical techniques for precisely identifying and detecting antidepressants and their metabolic products in a variety of biological matrices are greatly needed to be developed and made available. Hence, this study attempts to discuss various analytical techniques used to identify and determine antidepressants in various biological matrices, which include urine, blood, oral fluid (saliva), and tissues, which are commonly encountered in clinical and forensic science laboratories. The Author(s) 2023. -
Skin cancer classification using machine learning for dermoscopy image
Skin cancer is highly ambiguous and difficult to identify and cure in the last stage. To increase the survival rate, it is important to recognize the stages of skin cancer for effective treatment. The main aim of the paper is to classify the various stages of skin cancer using dermoscopy images from the data repository of ISIC and PH2. The data is pre -processed with the help of median filter and wiener filter for removing the noise. Segmentation is processed using Watershed and Morphological. After the segmentation, features were extracted using Grey Level Co-occurrence Matrix (GLCM), Color, Geometrical shapes in order to improve the accuracy of dermoscopy image. Finally, the dataset is classified with some popular methods like KNN with 89%, Ensemble with 84% and SVM works better than the other two methods by giving the highest accuracy of 92%. BEIESP. -
Effect of food insecurity on the cognitive problems among elderly in India
Background: Food Insecurity (FI) is a crucial social determinant of health, independent of other socioeconomic factors, as inadequate food resources create a threat to physical and mental health especially among older person. The present study explores the associations between FI and cognitive ability among the aged population in India. Methods: To measure the cognitive functioning we have used two proxies, word recall and computational problem. Descriptive analysis and multivariable logistic regression was used to understand the prevalence of word recall and computational problem by food security and some selected sociodemographic parameters. All the results were reported at 95% confidence interval. Results: We have used the data from the first wave of longitudinal ageing study of India (LASI), with a sample of 31,464 older persons 60 years and above. The study identified that 17 and 5% of the older population in India experiencing computational and word recall problem, respectively. It was found that respondents from food secure households were 14% less likely to have word recall problems [AOR:0.86, 95% CI:0.310.98], and 55% likely to have computational problems [AOR:0.45, 95% CI:0.290.70]. We also found poor cognitive functioning among those experiencing disability, severe ADL, and IADL. Further, factors such as age, education, marital status, working status, health related factors were the major contributors to the cognitive functioning in older adults. Conclusion: This study suggest that food insecurity is associated with a lower level of cognition among the elderly in India, which highlight the need of food policy and interventional strategies to address food insecurity, especially among the individuals belonging to lower wealth quintiles. Furthermore, increasing the coverage of food distribution may also help to decrease the burden of disease for the at most risk population. Also, there is a need for specific programs and policies that improve the availability of nutritious food among elderly. 2021, The Author(s). -
Forensic toxicological and analytical aspects of carbamate poisoning A review
Pesticides play a pivotal role in modern agricultural practices and effective domestic pest control. Despite their advantages, pesticides pose a great danger to humans and animals due to their toxicity. Pesticides, particularly carbamates, are extensively used all over the world in crop protection and domestic pest control, however, also causing morbidity and mortality on a larger scale, which is of great significance in both clinical and criminal justice management.Carbamates are derived from a carbamic acid (NH2COOH) that are commonly used as insecticides. Ethienocarb, Sevin, Carbaryl, Fenoxycarb, Furadan, Carbofuran, Aldicarb, and 2-(1-Methylpropyl) phenyl N-methylcarbamate are examples of insecticides that include the carbamate functional group. By reversibly inactivating the enzyme acetylcholinesterase, these insecticides can induce cholinesterase inhibition poisoning.Chromatographic methods, notably gas and liquid chromatography have traditionally been employed to analyse carbamate pesticides and their metabolites in various matrices. These approaches are employed due to their ability to separate the chemicals contained in a sample; as well as identify and quantify these compounds utilizing advanced detection systems. Aside from these GC and LC conventional methods, other detection and/or hyphenated techniques such as single-quadrupole, ion-trap, triple-quadrupole, or tandem mass spectrometry, have been used in carbamate analysis to provide quick results with excellent sensitivity, precision, and accuracy.The objective of this review is to describe various analytical techniques used to detect and determine carbamate pesticides in various matrices which include urine, blood, and tissues that are commonly encountered in emergency hospital laboratories and forensic science laboratories. 2022 Elsevier Ltd and Faculty of Forensic and Legal Medicine -
Strategic competency development in indian tourism: Harnessing digital transformation, sustainability, and human capital
The Indian tourism sector is experiencing a significant transformation influenced by technology, sustainability, and changing consumer expectations. This chapter examines how competency marketing can enhance the industry's competitiveness, particularly in digital transformation, sustainability, and human capital development. Drawing on global tourism leaders, it highlights the use of digital tools like big data, AI, and ML to offer personalized experiences. The chapter underscores sustainability as a marketing competency and the importance of continuous professional development. It advocates for industry-academia partnerships and regional training programs to support mid-career professionals. India is poised to lead in digital tourism marketing by aligning competencies with emerging technologies and sustainability goals. Key performance indicators such as digital literacy and sustainable tourism engagement are proposed to guide the sector's growth over the next decade. 2025, IGI Global Scientific Publishing. All rights reserved. -
Limelight in Dark Times: Jyoti Kumari's 'Cyclothon'
[No abstract available] -
Computational Intelligence for Solving Contemporary Problems
The special issue contains research papers elaborating advancements in computational intelligence. Computational intelligence mimics the extraordinary capacity of the human intellect to assert and understand in an environment of uncertainty and impre-cision. Computational intelligence is new-age multidisciplinary artificial intelligence. The main goal of computational intelligence is to develop intelligent systems to solve real-world problems that are not modelled or too hard to model mathematically. 2024, Bentham Science Publishers. All rights reserved. -
Consumer preference towards private label brands with reference to retail apparel in India
As majority of the present day consumers are considering brands as an important element in their choice of decision making while purchasing, it is pertinent that sellers should capitalize on the type of brands they are offering to consumers. Both private labels and global brands have their own advantages and disadvantages over each other mainly in terms of pricing and quality factors. However, the main motive the consumers are looking forward is to buy a product which would effectively satisfy their requirements. If they find a product which satisfies their needs effectively, they buy it irrespective of whether it is a private label or a global brand. Even the price of the product may not be a major factor in such a case. This study focused on the preference and intention among consumers towards buying of private label products, especially retail apparel products. This study examined the causal relationships between six antecedents of customer perceived preference identified in this study as fashion consciousness, attitude, store image, price, quality, and store loyalty with regard to the purchase intention of private label brand apparels. The model was evaluated using data collected from 292 customers from different malls in Bangalore in 2016-17. The findings revealed that customers attitude played a significant role in their purchase behaviour towards private label brand apparels. 2019, Associated Management Consultants Pvt. Ltd. All Rights Reserved. -
Elevating pyrrole derivative synthesis: a three-component revolution
Pyrrole is an essential chemical with considerable relevance as a pharmaceutical framework for many biologically necessary medications. The growing demand for biologically active compounds calls for a simple one-pot method for generating novel pyrrole derivatives. Nots surprisingly, several multicomponent reactions (MCRs) aim to synthesize pyrrole derivatives. However, this review presents the three-component synthesis of pyrrole derivatives, highlighting the significance of multicomponent reaction in synthesizing eclectic multi-functionalised pyrrole covering the selected literature on the three-component synthesis of substituted pyrrole from 2016 to late 2023. Furthermore, this article classifies the reactions based on the starting material with functional groups involved in the pyrrole ring formation. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
Catalytic potential of fluorescein under visible light irradiation: Enabling single-pot open flask synthesis of novel pyrazolyl methanesulfonamides
This groundbreaking study introduces a novel and efficient method for synthesizing a range of substituted pyrazolyl methanesulfonamides through a five-component cyclocondensation reaction. This reaction incorporates five different components, such as ethyl acetoacetate, hydrazine, dimedone, benzaldehydes, substituted phenyl acetonitriles, and methyl sulfonyl chloride was made to react under visible light irradiation, with fluorescein serving as an effective catalyst and ethanol as solvent for 30 mintues. This method offers significant advantages, including simplified handling, higher yields of target products with shorter reaction times, and easier purification processes. We successfully synthesized around 15 novel pyrazolyl methanesulfonamide derivatives with high efficiency. Comprehensive spectral characterization confirmed the structural integrity and purity of these derivatives, demonstrating the robustness and versatility of this approach. Facilitated by visible light and utilizing fluorescein as a bio-friendly catalyst, this methodology is both green and sustainable. This innovative approach not only streamlines the synthesis of pyrazolyl methanesulfonamides but also holds considerable promise for advancing research and applications in fields such as medicinal chemistry and materials science. 2024 The Author(s) -
A Mini Review on the Multicomponent Synthesis of Pyridine Derivatives
Multicomponent reactions (MCRs) have emerged as key green tool in organic synthesis for their methodological simplicity. MCRs have made heterocycle synthesis more versatile. The most crucial molecule among the most often used heterocycles is pyridine, which is widely used in biological, industrial, and pharmaceutical sectors. In light of this, our mini-review highlights the literature on substituted pyridine synthesis published from the year 2016 to early 2022 via multicomponent approach. 2022 Wiley-VCH GmbH.