Volume 12 | Issue 4 |

 Abstract

It is an innovative chat bot designed to revolutionize the agriculture sector by providing farmers with accessible, personalized and multilingual assistance.

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 Keywords

Chat bot, AI, Machine learning, Deep learning, Agriculture.

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The hotel booking industry has experienced a notable transition in recent times, with a greater emphasis on online platforms due to technological improvements and evolving consumer tastes. Students constitute a distinct group within several demographic groupings, and their online hotel booking behaviours and intentions warrant special consideration. Students' desire to book hotels online not only demonstrates their connection with online channels for booking hotels but also represents their behavioural intention. It is essential to comprehend the elements affecting students' intents in this respect. (UTAUT) the model has grown as a very effective test in considering the factors that stand in the way of using or disusing technology-proven services to the UTAUT model developed by Venkatesh et al. (2003), the users' intentions towards technology are determined by the combination of excellent characteristics, for example, the performance expectancy, effort expectancy and the social effect and conditions such as facilitating conditions. This study investigate the students' intentions to book online hotels, which is one of the dimensions of a broader research field. Through a systematic review and synthesis of existing literature, this research endeavours to contribute to both theoretical and practical knowledge. The findings of this study will not only advance our understanding of the factors driving students' intentions toward online hotel booking but also offer valuable insights and services to meet the needs and preferences of this important demographic segment. In summary, this study addresses a significant gap in the literature by applying the UTAUT model to explore students' intentions to book online Hotels. By leveraging insights from similar research papers, this research aims to shed light on the complex interplay of factors influencing students' adoption of online Hotel booking.

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Students intention for online hotel booking: An application of the unified theory of acceptance and use of technology.

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Shatavari, or asparagus racemosus, is revered as the "Queen of Herbs" and used extensively in traditional Ayurvedic therapy.This perennial climber plant, which is native to India and the Himalayas, has been used for a very long time due to its numerous medicinal benefits.Its moniker, which translates to "she who possesses a hundred husbands," highlights the belief that it promotes energy and fecundity, particularly in women.Indian Ayurveda has been using shatavari, commonly known as asparagus (Asparagus racemosus Wild; family Asparagaceae1), for thousands of years.Another name for shatavari is Asparagus racemosus. It belongs to the family Asparagaceae.Shatavari is a frequent element in ayurveda medicine and is given as an analeptic to support one's health and energyIt has been discovered that.shatavari extracts, which are made from a variety of parts such roots, flowers, leaves, and are effective in treating female reproductive systems.Shatavari, also known as Asparagus racemosus This article involvesthe traditional and morden uses of shatavari supplements in order to provide guidance on their administration.Asparagus racemosus methodically as a therapeutic product with commercial possibilities

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Asparagus racemosus, shatavari, Queen of herbs

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Sharenting, the act of parents disseminating their children's images and personal details on social media has emerged as a widespread phenomenon in the era of digital technology. This article examines the psychological effects of sharenting specially exploring the reasons for it, the different sorts of material shared and the resulting influence on children's privacy, self-esteem and the connection between parents and children. The text examines ethical concerns and provide suggestion for appropriate sharenting behaviours with a focus on safeguarding children's privacy. The study used a literature based review to emphasise the key components of sharenting and its influence on children. The motives include social affiliation, parental satisfaction, online exhibition and assistance from virtual groups. Sharenting may have adverse effects on children's emotional well-being and make them vulnerable to privacy hazards. The research findings indicate that parental awareness and appropriate internet sharing are of utmost importance. Furthermore, the study highlights the significance of digital literacy for parents and what the consequences of the relationship parents have with their children can be.

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Sharenting, children, privacy, sharing, parenting

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In India, where agriculture is pivotal to the economy and employs a significant portion of the workforce, there's a pressing need to enhance farming practices to meet rising food demands. Leveraging advanced technologies like machine learning (ML) and deep learning (DL) can revolutionize agricultural productivity by enabling early detection of crop diseases and optimizing resource usage. Our project harnesses ML techniques such as KNN, SVM, and DL methods like CNN to swiftly and accurately detect plant diseases. By training these models on extensive datasets, they learn to identify patterns and predict diseases effectively. Specifically, our DL system automates the process of scanning leaf images and discerning diseases based on visual symptoms. Moreover, it assesses the severity of the disease and recommends appropriate fertilizer quantities to mitigate its impact on crop health. To facilitate ease of use for farmers and agricultural workers, we've developed a user-friendly interface. With a simple leaf image capture, users can obtain insightful suggestions tailored to their crop's condition. This not only aids in boosting crop production but also ensures the maintenance of crop quality, thereby empowering farmers to make informed decisions and optimize their yields.

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AgriSmartHub, nlp, ml, convolutional neural network, artificial intelligence, crop, disease, fertilizers, machine learning, natural language processing , crop recommendation, Agriculture, farming

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Quality of care is the degree to which health services for individuals and populations increase the likelihood of desired health outcome. It is based on evidence based professional knowledge and is critical for achieving universal health coverage. Nurses play an important role in the health care system for providing high quality care which helps to monitor and evaluate what health care services are available and what else needed to improve their quality which in turn helps the health care organizations to effectively use their quality assurance resources to focus on quality care. Child safety refers to the safeguarding of children from violence, exploitation, abuse and neglect. It involves identifying signs of potential harm. In addition, the physical, psychosocial, developmental, communication and cultural needs of children differ from those of adults. Therefore, standards of care are required to ensure that the care given to all children in health facilities is evidence based, safe, effective, timely, efficient, equitable and appropriate for their age and stage of development, and that care provided is child and family centred.

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EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING QUALITY CARE AND CHILD SAFETY AMONG STAFF NURSES WORKING IN PAEDIATRIC WARD /PICU/NICU IN SELECTED HOSPITALS KAMRUP, ASSAM: AN EVALUATIVE STUDY

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Introduction: The emotional maturity of teachers plays a crucial role in educational settings, influencing teaching effectiveness and student success. This study focuses on female mathematics teachers in secondary schools across West Bengal, particularly exploring the implications of emotional maturity on teaching and learning outcomes in mathematics. Objectives: The primary goals are to assess the emotional maturity levels of women mathematics teachers using a standardized Emotional Maturity Scale, explore the impact of this maturity on teaching effectiveness, and investigate the correlation between emotional maturity and beliefs about mathematical ability, with an emphasis on gender-specific outcomes. Methodology: The study employed a quantitative survey approach, involving 60 female mathematics teachers from 20 secondary schools in Nadia, West Bengal, categorized into urban and rural settings. An Emotional Maturity Scale and various statistical tools like ANOVA and Pearson correlation were used to analyze the data. Findings: The results revealed significant variations in emotional maturity levels among the teachers, which correlated with their teaching effectiveness and classroom management. A key finding is that emotional maturity significantly affects how teachers manage their classrooms and interact with students, particularly in challenging subjects like mathematics. Moreover, teachers' beliefs about mathematical ability were found to significantly influence student academic self-concept and achievement, with notable differences based on gender. The study highlights the critical need for professional development programmes that enhance emotional maturity and address gender biases to improve educational outcomes. Conclusion: Enhancing emotional maturity among teachers can lead to more effective teaching strategies, better classroom environments, and improved student outcomes, particularly in reducing gender disparities in mathematics education. The findings support educational reforms that include emotional maturity development as a component of teacher training and professional development programs.

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Emotional Maturity, Mathematics Education, Teaching Effectiveness, Gender Bias in Education, Teacher Professional Development.

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UV spectrophotometry, Regression, Recovery, Precision, Linearity.

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Virtual Machines (VMs) in Cloud systems are scheduled to hosts based on their instant resource consumption (e.g., hosts with the greatest accessible RAM), rather than their overall and long-term utilisation. Furthermore, the scheduling and placement operations are often computationally intensive and have an impact on the performance of deployed VMs. In this paper, we provide a Cloud VM scheduling method that considers existing VM resource consumption over time by assessing previous VM utilisation levels in order to schedule VMs while maximising performance using the PSO technique. Because Cloud management activities such as VM placement have an impact on previously deployed systems, the goal is to minimise such performance deterioration. Furthermore, because overcrowded VMs tend to grab resources from neighbouring VMs, the task enhances the VMs' true CPU consumption. The results reveal that our method refines traditional Instant-based physical machine selection as it learns and adapts to system behaviour over time. The idea of VM scheduling based on resource monitoring data taken from previous resource utilisations (VMs). The PSO classifier reduces the physical machine count by four.

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Cloud Data Centre, Virtual Machine, Energy Consumption, Resource Management

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The study involves quantitative analysis of 3 different brands (samples) of Pregabalin (75mg) Capsules used in Vadodara (India), using and High-Performance liquid Chromatographic method, The mobile phase was prepared by mixing Phosphate Buffer pH 3.0 adjusted with OPA: Methanol: Acetonitrile (30:35:35, v/v/v). The prepared mobile phase was sonicated and filtered through 0.45?m membrane filter. There is official method available so as per IP criteria this method is validated as well as performed. Instrument- SHIMADZU HPLC - LC-2030, Software-Lab Solutions used for performing the analysis.at flow rate of 1mL/min and detection wavelength of 215nm.in the analysis for sample- 1 RT found 2.758 for 2nd sample RT time found-2.757, 3rd RT on 2.758 found all three samples found suitable for market as well as complies the %label claim.

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Pregabalin, Method Validation, Api, Capsules, marketed Study, Hplc

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