Volume 12 | Issue 4

 Abstract

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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Since several years, India being exposed to many Epidemics. Zoonotic diseases are the infection transmitted from animal to human. These diseases can be transmitted by direct or indirect way. Direct transfer of disease is due to the close contact with animal and indirect transfer is by water, air, soil and vehicle used for transport of animals. The cause of the disease may be a virus, bacteria, fungi or other agents. Anthrax, Rabies, Bovine tuberculosis, Japanese encephalitis, Rickettsia, Brucellosis, Plague, Swine-flu and the latest epidemic -Covid-19 etc are some deadly diseases. Zoonosis affects the livestock by killing lot of population throughout the world, hence leading to destroy the economy of the country. Ayurveda being in the fore front of eradicating the root cause of the disease, has recorded its valuable experience in epidemics and termed them as Janapadodhwansa. This article has discussed about the aetiology of zoonotic disease, their impact on human health, Janapadodhwansa and their control measures. We also highlighted Covid-19, a newly emerged zoonotic disease of bat origin, that has devastating effect on human health all over the world.

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Zoonotic diseases, Janapadodhwansa, Covid-19.

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This study aims to explore the definition and properties of big data as well as analyze consumer behavior features in the context of big data research. The findings indicate that while big data influences customer perception through external factors, external factors and internal perception are the main determinants of consumer decision making. Because of the sheer volume of data, standard database management system techniques are unable to handle and analyze it(Latvia_ESRD_43_2016, n.d.) .this article examines the features of the big data phenomena and how analytics may be used as a tool to help marketers understand consumer behavior and provide their companies a competitive edge. When service users receive technical and business training in a controlled context, data is collected from them. In addition to discussing technical details such environment building, theory, logic, framework, infrastructure, and architecture, this study will address consumer behavior modeling(Big Data Analytics, 2016) The first section of the literature review looks at ideas of consumer behavior that are connected to trust. It explores the psychological underpinnings of consumer trust and how perceptions of risk, confidence, and trust impact the process of making decisions. Moreover, it contradicts the notion of empowered firms by emphasizing the effect of legitimacy on consumer trust, trust, and brand integrity. On the other hand, it examines customer mistrust of unlicensed services and talks about issues and causes for that mistrust.(Anshari et al., 2019) In essence, the recommendation engine makes many product recommendations depending on a range of variables, such as age and past purchases made by the user. It is a type of data filtering technology that suggests the most pertinent products to a specific client based on machine learning algorithms. This study aims to develop a product recommendation system by analyzing user sentiment and segmentation related product reviews.(Ertemel, 2015).

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Consumer behavior, Big Data, Business analytics, Technology, data analytics, Sentiment Analysis.

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Abstract Chitra Banerjee's novels are intricately crafted tales of girls with hidden abilities negotiating challenging societal and familial settings. This essay examines the transformations of characters like Nayan Tara (Tilottma), highlighting her pursuit of independence, acceptance, and self-awareness. Through a detailed analysis of The Mistress of Spices, this study elucidates the ways in which Banerjee portrays gender disparity and the enduring effects of early trauma on family relationships. Furthermore, it delves into Tilottma's realization of her exceptional capacity to control fate and the subsequent strife in her family, illuminating wider societal themes including prejudice against women and dowry worries. In addition, the work explores topics of cultural identification and alienation as Tilottma travels from India to America, profoundly changing from Nayan Tara to Tilottma. This study aims to shed light on the perseverance and achievements of women navigating varied environments by analyzing Banerjee's tales. It also provides insights into the intricacies of female empowerment and self-discovery in the face of personal hardships and cultural expectations.

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Keywords: The Mistress of Spices, cultural identity, gender inequality, self-respect, and women's independence

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This present paper aims for research on bibliometric analysis (performance analysis) and science mapping or network visualization. With the data taken from the SCOPUS database, the researcher examines various performance analysis indicators, like document & source type, year-wise publication, subject area, geographical distribution of the publication, and most prominent authors. Scientific mapping is performed with the support of VOSviewer and MS-Excel software using the co-authorship and co-occurrence indicators. The most common type of network visualization is used to view images of the links that have been analyzed. This study result shows 296 papers and aids in accepting the facts and associations among the chosen indicators.

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Bibliometric study, IJSW, Scopus, VOSviewer, Network Visualization

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The Internet of Things (IoT) has transformed the way we interact with our environment and has opened up new opportunities for enhancing safety and security. This abstract presents an overview of an IoT project centered on gas leak detection, which leverages IoT technologies to provide a smarter, more connected approach to safety. The IoT Gas Leak Detection System discussed in this abstract is a cutting-edge project that integrates various IoT devices and sensors to monitor gas leaks in real-time across a wide range of environments, including industrial facilities, residential spaces, and commercial establishments. These sensors are strategically deployed to ensure comprehensive coverage and are capable of detecting multiple gas types, including methane, propane, and carbon dioxide. At the core of this project is the seamless integration of IoT devices, which collect and transmit data to a centralized platform. Leveraging wireless connectivity and the system offers real-time monitoring, allowing for instant alerts and notifications in case of a gas leak. This real-time data flow enables prompt response, reducing potential hazards and preventing extensive damage.

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AIRSHIELD

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Abstract Here is a thorough synopsis of curcumin's function as an antiviral agent for this review. Turmeric's primary component, curcumin, has anti-inflammatory, antiviral, antioxidant, anticancer, and antifungal properties and is used as a food additive and medicinal agent. The pharmacological and biological characteristics of curcumin are diverse. Antiviral action against dengue virus, norovirus, HIV, HSV, HPV, and other viruses is produced by curcumin. Curcumin is recommended because norovirus requires phytochemical activity to be treated. Natural products with anti-infective properties, such as curcumin, are well-known for their use in illness prevention, diagnosis, and treatment. Because natural materials are non-toxic and have no adverse effects, they are employed as treatments in alternative medicine. The main usage of curcumin is it is utilized in alleviating abdominal pain. Curcumin works to prevent disease by altering biological processes. Curcumin is a powerful scavenger of ROS and nitrogen species. Utilizing plant extract makes virus prevention safer and more affordable. Usages of pharmaceuticals include ulcers, diabetes, rheumatoid arthritis, atherosclerosis, and more. In the medical field, more medication combinations including curcumin are being produced. Curcumin's bioavailability is its primary disadvantage. As a result, curcumin is crucial for preserving the antiviral characteristic against viruses; it blocks certain viruses at specific locations via specific processes. Curcumin's bioavailability is altered to make it a more potent antiviral agent.

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Keywords: Curcuma longa; health benefits; antiviral; pharmacology; chemistry; curcumin nano-formulations

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ABSTRACT: The herbal cosmetics are those when natural herbs and their products used for their aromatic value in cosmetic preparation among consumers for herbal products triggered the demand for natural products and natural extracts in cosmetics preparations. The Herbal preparation is research by many more researcher and from new herbs obtained new herbal formulation. Herbal lotions have gained popularity in recent years due to their perceived natural and safe properties compared to synthetic skincare products. This abstract explores the formulation, benefits, and efficacy of herbal lotions in skincare routines. It discusses the key ingredients commonly found in herbal lotions, such as aloevera, coconut milk,honey, and lavender, known for their soothing and nourishing properties. Furthermore, it examines the potential benefits of herbal lotions, including hydration, inflammation reduction, and antioxidant protection.

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Herbal drugs, Herbal drug extract, alovera, Honey, coconut milk, Herbal formulation and Evaluation

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????? ???? : ?? ????, ???? ????? ???????? , ??????

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Sodium alginate beads are widely utilized in pharmaceutical and biomedical fields for their versatility in controlled drug delivery systems. This review provides an in-depth exploration of recent advancements in formulation techniques and evaluation methods for sodium alginate beads. Various formulation strategies, including traditional methods like ionotropic gelation and novel techniques like 3D printing and microfluidics, are discussed. Additionally, advanced evaluation methods encompassing physical, chemical, and biological characterization are comprehensively reviewed. The integration of innovative formulation approaches and precise evaluation techniques has significantly enhanced the performance and functionality of sodium alginate beads, paving the way for their diverse applications in drug delivery and tissue engineering.

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Sodium alginate beads, Formulation techniques, Evaluation methods, Controlled drug delivery systems, Biomedical applications

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The production of rice is significant worldwide; the husk produced is generally used as a combustible material for the preparation of paddies, delivering energy through direct combustion as well as by gasifying. Annually, 7.4 million tons of Rice Husk Ash (RHA) is produced and poses an incredible danger to the environment, harming the land and the encompassing zone where it is unloaded. In the transformation of rice husk to ash, the ignition cycle eliminates the natural products, leaving silica-rich remains. These silica-rich remains have proven to have potential to be utilized in concrete as a limited substitution of cement to enhance the concrete compressive strength. RHA is an environmentally friendly and cost-effective alternative cementitious material. In this experimental study Strength tests such as compressive strength,splitting tensile strength,and flexural strength with 5, 10, 15, and 20% percentages of RHA replacing the cement have been targeted.Based on the experimental results it was noted that RHA 10%-PPC 90% mix combination is having enhanced mechanical properties compared to conventional concrete.

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RHA fresh concrete properties; concrete mechanical properties; green concrete

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This paper investigates the integration of Machine Learning (ML) for anomaly detection within an Intrusion Detection and Prevention System (IDPS). We propose a two-pronged approach utilizing Golang and Python. Golang handles real-time network traffic analysis and signature-based detection, while Python tackles data pre-processing, training ML models, and potentially generating synthetic attack data using a Generative Adversarial Network (GAN). This synthetic data, focusing on anomaly patterns, will be evaluated in a simulated environment to assess its effectiveness in detecting real-world attacks. If successful, the generated data, along with real-world data emphasizing attack severity, will be used to enhance the training dataset, targeting the most relevant threats. This research aims to achieve a balance between real-time performance, improved detection accuracy and reduced false positives while acknowledging the challenges and ethical considerations of implementing ML in IDPS. The project leverages Golang's strengths for a less complex and scalable application, while Python provides the environment for ML development. Trained models will be saved in a format like ONNX for seamless integration with Golang for signature and anomaly-based detection, enabling the system to make informed decisions and generate alarms. Ultimately, this approach aims to simplify the system while enhancing its ability to identify zero-day attacks.

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Intrusion Detection and Prevention System (IDPS), Machine Learning (ML), Generative Adversarial Network (GAN), Real-Time Network Traffic Analysis, Zero-Day Attacks

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