Volume 12 | Issue 4

 Abstract

Rabindranath Tagore's Gitanjali is a masterpiece of devotional poetry that delves into themes of spirituality, love, and human emotions. Central to the aesthetic experience of Gitanjali is the concept of Rasa-Siddhanta, derived from Indian aesthetic theories, which emphasizes the evocation of different emotional states or rasas in the audience. This research paper provides a comprehensive analysis of Rasa-Siddhanta in Tagore's Gitanjali, offering specific comparative examples from the text to illustrate the manifestation of various rasas or Sthayibhavas. By examining the interplay of language, imagery, and poetic devices, this paper elucidates how Tagore masterfully invokes different emotional aesthetics to evoke a transformative experience for the reader.

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Key Terms: Rasa-Siddhanta, Rasas, Sthayibhava, Symbolism, Allegory, Metaphor, Imagery

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In today's urban landscapes, parking congestion has become a pervasive challenge, leading to wasted time, increased emissions, and driver frustration. The evergrowing urban population, coupled with the increasing number of vehicles, has led to a severe shortage of parking spaces in metropolitan areas. This scarcity has not only made finding a parking spot a time-consuming and frustrating experience but has also contributed to traffic congestion and environmental pollution. Traditional parking management systems, which often rely on manual ticketing or physical barriers, are becoming inadequate in addressing these challenges. To address this issue, innovative solutions that combine technology and automation are on the rise. Traditional parking management systems often rely on physical infrastructure and human intervention, resulting in inefficiencies and limited scalability. In contrast, the integration of deep learning techniques and advanced computer vision technology into parking management opens up new possibilities for a smarter, more efficient, and user-friendly experience. This system leverages two key components: facial recognition technology to identify vehicle occupants and automatic recognition of license plate numbers for vehicle identification. By seamlessly integrating these technologies, the system not only facilitates effortless parking but also enhances security and optimizes parking space utilization. In this survey, we will explore the fundamental components, benefits, and potential impact of the Face and Number Plate Based Smart Parking System. Experimental results shows that improved efficiency in smart parking system using face and number plate verification system

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IOT enabled Powered Smart Parking System based on Facial Recognition and License Plate Analysis could include Smart Parking Systems, Deep Learning, Facial Recognition

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Introduction: This study explores the complex relationships between educational attainment and gender, examining how these relationships affect the motivational and pleasurable aspects of gaming. Our goal in looking at these variables is to learn more about the subtle factors influencing people's engagement and enjoyment of gaming. Aim: This study aims to investigate how personality traits affect college students' motivation to play games and level of enjoyment from them. It specifically attempts to look into the ways in which specific personality traits and demographic factors affect students' gaming motivation and overall enjoyment. Materials and Method: For this study, a total of 321 data points were first gathered at Plakad District Degree College. 277 data points were kept after outliers were removed, guaranteeing a dataset with greater reliability. The statistical analysis was carried out utilising SPSS version 22. The Mini-IPIP 20-item scale developed by Donnellan et al. (2006) was used for the personality assessment; Demetrovics et al. (2011) developed the motivating online game scale with 27 items; and Davidson (2018) developed the enjoyment scale with 25 items. Result: Most notably, the research reveals a significant gender disparity in motivating game, giving more weight to the underlying causes than just enjoyment. It also explores educational backgrounds, demonstrating that accomplishing educational goals is a stronger incentive for gaming than mere enjoyment. Correlation analysis results indicate negative relationships between relatedness and pleasure with particular personality traits, and somewhat positive relationships between coping strategies and competition. It's interesting to note that while certain personality traits may not have a direct impact on game motivation, the total model--which includes the identified predictors--significantly affects the enjoyment prediction. Conclusion: In conclusion up, the research explores the complex connections among personality qualities, reasons for gaming, and the enjoyment one gets from playing video games online. Through an examination of factors such as social interaction, escapism, and competition, the research offers significant insights into the creation of pleasurable gaming experiences, illuminating the complex interactions present in the digital entertainment space.

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Personality, Motivating game, Enjoyment, Gender, Educational background

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Our proposal, MEDICOBOT, is an AI-powered solution that aims to offer individualized support for mental well-being in response to the major global difficulties faced by mental health disorders. With its easy-to-use chat interface, MEDICOBOT provides a secure environment for people to voice their worries and ask for help. Personalized assessments, compassionate dialogue flows, and evidence-based solutions catered to the specific requirements of each user are important components. MEDICOBOT uses machine learning and natural language processing to dynamically modify its responses over time. It easily combines with the current mental health resources, making it easier to connect and send those seeking professional help. With the help of our initiative, we hope to empower people and foster positive outcomes in mental health care by providing them with easily accessible, efficient, and compassionate support. MEDICOBOT is a tool that has considerable potential to enhance current resources and encourage more accessibility

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MEDICOBOT, AI-powered solution, Individualized support, Mental well-being, Chat interface, Machine learning

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Abstract This kind of monitor exploration is common. The purpose of the study was to estimate and monitor the physico-chemical properties of drain water at the input and output of the stps as well as the stps themselves the average concentrations of the parameters at the intake are pH 6.8, TSS 149.6 DO 0.50, COD 185, BOD 82.6 , Temperature 24.2 ,NH4N 18.25,TN 7.3 and phosphorus 0.52 .The following outlet values were determined based on the wastewaters acceptability Temperature 19.0,NH4N 0.416, TN 0.48, pH 7.6, TSS 5.60, DO 0.208, COD 34.3, BOD 5.64 and Phosphorus 19.0. Lastly agglomerative hierarchical clustering techniques were used to examine the similarities among the sewage treatment plants the results show that after treatment at koshi river ramnagar effluent quality has considerably improved.

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Key words - Tumaria reservoir, Physical -chemical parameters, Water quality

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This paper addresses the study of bermed structures which act as an excellent passive adaptation strategy to reduce the adverse climatic effects and improve thermal performance of the bermed house in both HVAC and natural ventilation case in composite climate. Thus, the goal of this study is to simulate and compare the thermal performance of bermed and contemporary structures in composite climate and to study parametric optimization for the same. For that, a base scenario, a combination south facing facade with 10% WWR has been chosen by referring standards like NBC, reviewing literature and case study. Further the variation in WWR, orientation and stack effect has been performed to frame various design case and finding the optimum case for the construction of bermed structure in composite climate. The methodologies adopted are (i) the computational simulation of the EPI (ii) the quantification of the discomfort hours and PMV with the subsequent comparative analysis. The results shows that for adequate amount of natural ventilation and thermal performance, the most optimum composition for bermed structure that can be used is "vertically oriented windows with 10% WWR, facing towards south direction in natural ventilation case and north in HVAC case and bermed with minimum 0.9 m of earth mass". Also using stack effect can help in inviting cross ventilation. Nonetheless, it is shown that this passive strategy of making bermed structure works as an excellent adaptation measure to improve thermal performance and overall EPI of the building in composite climate.

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thermal performance, building simulation, global warming, EPI, discomfort hours, bermed.

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This research presents a groundbreaking agricultural effort that seeks to transform the sector using an integrated platform driven by data. The platform creates a strong base by including vital statistics from government ministries to tackle significant issues related to ineffective distribution of resources, wastage of food, and the need for up-to-date information. The main focus is utilizing machine learning models to forecast various agricultural products' demand and supply levels accurately. Essentially, the platform prioritizes farmers and promotes their involvement by offering tailored information and live data displays and enabling direct communication with vendors. Presenting data, past patterns, and future predictions visually enables stakeholders to make timely and well-informed decisions. "To tackle the problem of food waste" To tackle the problem of food waste," the platform guides farmers on locating storage facilities nearby. This helps maintain the products' quality and prolong their shelf life. An optimized cultivation cycle tool enables farmers to diversify their crop selection and broaden their market reach, providing valuable insights into potential export opportunities. This encourages farmers to consider selling their products in international markets rather than solely relying on domestic sales. Timely weather forecasts and notifications empower farmers to use proactive strategies, enhancing crop management's efficacy. The platform offers significant market information to farmers, enabling them to make well-informed decisions by providing multilingual accessibility and cloud-based machine-learning models for crop planning, production scheduling, and data analysis. Crucially, the platform serves as a strategic resource for governments, aiding in projecting crop requirements, managing surpluses during crises, and building a more sustainable and resilient agricultural industry. To summarize, this comprehensive agricultural platform offers a comprehensive and revolutionary method for modernizing agriculture, with the potential for increased efficiency, improved livelihoods, and the adoption of sustainable farming techniques.

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Integrated agriculture platform, Data-driven agriculture, Machine learning in agriculture, Agricultural supply chain optimization, Food waste reduction, Sustainable farming practices, Eco-friendly agriculture, Crop yield forecasting, Resource allocation efficiency. Real-time agricultural information

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paper uploaded

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Demographic Dividend, Inclusive Growth, Smart Cities, Skill India

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In the realm of biometrics and surveillance, the accuracy and efficiency of facial recognition systems play a pivotal role. One fascinating yet challenging facet within this domain is the detection of twins, where traditional methods often falter due to the striking resemblance between siblings. However, the fusion of Convolutional Neural Networks (CNN) and Swarm Optimization techniques has emerged as a groundbreaking solution, supplanting conventional decision tree algorithms and revolutionizing twin detection.

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Identical twins, CNN & Swarm Optimization, facial recognition.

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Abstract: Crop yield prediction is crucial for agricultural decision-making, impacting import-export dynamics, pricing strategies, and crop management practices. Soil quality, determined by nutrients and pH levels, significantly influences crop productivity. Despite advancements, farmers often rely on traditional soil analysis methods. Emerging technologies like Data Mining, AI, Machine Learning, Deep Learning, and Predictive Analytics offer promising avenues for agricultural improvement. Predictive analytics, leveraging historical data, aids in predicting soil nutrient levels for crops like Paddy, Raagi, and Cumbu, enabling proactive measures to optimize yields and mitigate losses. This study proposes a method employing Machine Learning with LSTM to predict crop yields based on geographical and climatic data, capturing temporal dependencies and operating on diverse datasets. Additionally, the system facilitates real-time monitoring of soil nutrient evolution, integrating key chemical elements, rainfall, and temperature data.

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Keywords: Support Vector Machines (SVM), Long Short-Term Memory (LSTM)

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Due to their network accessibility and frequent weaknesses, web applications are common targets for cyber-attacks. When a hacking attempt is discovered, a system for intrusion detection monitors online applications and sends out alerts. Intrusion detection systems that are now in use often take features from input strings or network packets that are carefully chosen to be pertinent to attack analysis. However, picking characteristics manually takes a lot of time and requires in-depth understanding of the security area. Furthermore, in order for supervised learning algorithms to differentiate between normal and aberrant behaviours, they require a significant amount of labelled legitimate or attack request data, which is frequently prohibitively expensive for use in production web services. This work adds three new insights to the field on autonomic intrusion detection systems research. Using the Robust Software Modelling Tool (RSMT), which autonomously monitors and characterises the runtime behaviour of web applications, as a basis, we first assess the viability of an unsupervised/semi-supervised strategy for web attack detection. In the second section, we walk through how RSMT trains a stacked blurring auto encoder to encode as well as reconstruct a call graph for end-to-end deep learning. The reconstruction error of the request data is computed to identify anomalies using a low-dimensional representation of the feature set with unlabelled sample data. The findings of our empirical testing of RSMT on purposefully vulnerable production applications as well as artificial datasets are examined in our third section. According to our findings, the suggested method requires little domain expertise and a little amount of labelled training data in order to effectively and accurately detect attacks such as SQL injection, cross-site scripting, and deserialization.

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Deep Learning, RSTM , SQL

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Machine learning, Opinion Mining, Text Mining

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Information and Technology has grown up to apex level in the 21st Century especially after 2010. Thus, learning has become easier and interesting for the students. Learners are exploring learning materials through various mediums such as: internet, social media, learning platforms and many more. As per the changing needs of the learners, the teachers are to be trained and well-acquainted with the use of new technologies. TPACK stands for Technological Pedagogical Content Knowledge. It is a framework for the integration of Technological knowledge with the Pedagogical and Content knowledge of a teacher in order to impart effective knowledge to the students. This study is basically a descriptive survey conducted to find the level of Techno-Pedagogical Competence among the Teacher-Educators with reference to their streams of education. This study was delimited to the Teacher-Educators of Teacher-education institutions of Odisha only. The objective was to study the Techno-Pedagogical Competency of Teacher-Educators with reference to their stream. The Null Hypothesis formulated for the study stated that, there was no significant difference of mean scores of Techno-pedagogical competency of Teacher Educators with references to their stream. The investigator had selected Disproportionate Stratified Random Sampling Technique to acquire the samples out of the total population. The investigator had selected 50 Teacher-Educators particularly 28 from Arts and 22 from Science of different Teacher Education Institutes as sample. The data were collected through a self-made Techno-Pedagogical Competency Scale and sent to the Teacher-Educators of Teacher-Education Institutes of Odisha through Google form. The data were analyzed using t-test for comparing two sample mean scores between science and arts stream. The finding of the study revealed that, the calculated t value was 1.36 and the table t value was 2.01 where df was 48 and level of significance was 0.05. The finding of the study states, there was no significant difference between science and arts Teacher-Educators with reference to their Techno-Pedagogical competencies.

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Technology, Pedagogy, Techno-Pedagogy, Competence, Techno-Pedagogical Competency, Teacher Educator

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The microscopic inspection of blood smears provides diagnostic information concerning patients' health status. They use a microscope and count the percentage of the occurrence of each type of cell counted within an area of interest in smears. Obviously, this manual counting process is very tedious and slow. In addition, the cell classification and counting accuracy may depend on the capabilities and experiences of the operators. Therefore, the necessity of an automated differential counting system becomes inevitable. In this project, CNN models are used. In order to achieve good performance from deep learning methods, the network needs to be trained with large amounts of data during the training phase. We take the images of the white blood cells for the training phase and train our model on them. With this method we achieved good accuracy than traditional methods. And we can generate the results with in the seconds also. white blood cells account for only about 1% of your blood, but their impact is big. White blood cells are also called leukocytes. They protect you against illness and disease .Think of white blood cells as your immunity cells. In a sense, they are always at war. They flow through your bloodstream to fight viruses, bacteria, and other foreign invaders that threaten your health When your body is in distress and a particular area is under attack.

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To demonstrate about this project, CNN models are used. In order to achieve good performance from deep learning methods, the network needs to be trained with large amounts of data during the training phase. We take the images of the white blood cells for the training phase and train our model on them. With this method we achieved good accuracy than traditional methods. And we can generate the results with in the seconds also.

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This is a study of Ride sharing applications. Ride-sharing platforms have changed urban transportation by offering a convenient and eco-friendly alternative to taxis and public transits. These platforms use mobile apps and algorithms to connect riders with drivers, reducing traffic congestion. Ride-sharing also fosters social interaction and improves accessibility for people with disabilities. However, there are safety concerns and potential negative impacts on traditional public transits which is a challenge. Overall, ride-sharing platforms offer a promising solution for urban mobility, with continuous innovation addressing current limitations.

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Urban Transit, Ride-Sharing, Mobile App, Ride-Sharing Safety, Urban Traffic Congestion

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paper uploaded

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small scale industries, economic development, employment, production and export

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An automatic fish aquarium is a system that utilizes technology to control and maintain the environment within a fish tank without the need for constant manual intervention. This system typically includes features such as automated feeding, water filtration and circulation, temperature regulation, and lighting control. By automating these essential tasks, the aquarium owner can ensure that their fish are provided with optimal living conditions and reduce the time and effort required for maintenance.

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Automatic Fish Aquarium

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``In the beginning, cyber shopping was really about getting commodity products online as cheaply as possible.Now,we're moving into the more exciting phase of e-commerce, where it's about emotional products the things people really cherish''. -Jason Goldber, Founder and CEO of Fab.com This study highlights on the consumers opinion towards cyber shopping with special reference to Theni town. The total number of Respondents is 150. The shift to cyber shopping is a result of some specific advantages that cyber shopping offers over traditional shopping from a customer's perspective. Today multichannel brand presence is a basic necessity and marketing efforts need to be optimized for breaking the clutter and grabbing the customer's attention. The homogenous amount of user generated content available digital channels and social media has made it easy for consumers to access reviews, ratings and recommendations before buying products. Consumers are empowered to research about the products, brands and companies.

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Cyber shopping, Products, Consumer's opinion.

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Artificial Intelligence (AI) in education is like having a helpful digital friend that makes learning more fun and personalized. It's about using smart technology to make studying easier. AI in education helps computers understand how you learn and what you need help with. It's like a clever assistant that adapts to your unique style of learning. To Evaluate the Student's utilization of AI tools used for Education purpose among Students. The sample size taken for this study is 270 respondents. This study aims to examining how the students gets benefited in the usage of the new AI tools, and explore the ways to enhance its accessibility and relevance to the student's academic journey. The main objective of the study is to examine how the students gets benefited by using the AI tools, in Coimbatore city has been taken for the current research work. For this study we have adopted the Convenience sampling. The analysis involved simple percentage analysis, rank analysis, chi-square test, and one-way ANOVA. Therefore, it can be concluded that the majority of the students are not updated with the knowledge of new technologies in AI tools for educational sector. So, they have to know about the tools which is available for education and the students can improve their skills and they can achieve their future goals.

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Artificial intelligence, AI tools, Education, Students

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Enhancing drug solubility is critical for effective medication delivery. Techniques like particle size reduction, nanonization, cosolvency, hydrotropy, pH adjustment, supercritical fluid processing, solid dispersion, and liquisolid methods are used to overcome poor solubility issues. These methods improve drug dissolution and bioavailability,addressing a common challenge in pharmaceutical development.

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Solubility, Dissolution, Oral absorption, Solubility enhancement, Drug formulation, Solid dispersion, Solubility equilibrium, USP and BP expressions for solubility

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