Volume 13 | Issue 1 |

 Abstract

Autism, also referred to as Autism Spectrum Disorder (ASD), is a developmental condition that affects how individuals perceive and interact with the world. It is characterized by challenges in social interaction, communication, and a tendency for repetitive behaviors or narrowly focused interests. However, it is a spectrum, meaning that the traits and abilities of individuals with autism can vary widely. Autism Spectrum Disorder (ASD) and speech delay often go hand in hand, though not all individuals with autism experience significant delays in language development. Speech delays can vary widely depending on the individual and their specific profile on the autism spectrum. Speech delay is a common challenge among children with Autism Spectrum Disorder (ASD). This delay can manifest as limited vocabulary, difficulty forming sentences, or an inability to use spoken language to communicate. Addressing speech delay is crucial, as it significantly impacts a child's ability to express needs, build relationships, and engage in educational activities. There are several effective AI tools and technologies that have been developed to assist individuals with Autism Spectrum Disorder (ASD) and speech delays. These tools use machine learning, speech recognition, and other AI techniques to support communication, learning, and social interaction

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 Keywords

Autism Spectrum Disorder (ASD) and speech delay

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Ameloblastoma is a group of odontogenic tumors of the jaws that arise from ectomesenchyme or epithelial remnants associated with tooth development. The majority of them speculate that the tumor's growth and development may be connected to the intricate process known as the epithelium-mesenchymal transition (EMT), which allows cells to dynamically change from having a mesodermal shape to a morphological one. The etiopathogenesis of these tumors is still incompletely understood. The most common site of the lesion is the mandibular premolar area, which accounts for 32.6% of cases. The lesion's histological subtype and the existence of mural invasion are two important variables to take into account when evaluating the histopathological features of atypical lesions. This article gives a complete review of ameloblastoma, pathophysiology, clinical features and its management.

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 Keywords

ameloblastoma, aggressive, odontogenic tumor

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Ramoji Film City (RFC) has emerged as a pivotal institution in shaping both Hyderabad's film and tourism industries. Established in 1996, RFC has grown into one of the largest integrated film studio complexes in the world, offering cutting-edge facilities for film production while simultaneously becoming a major tourist destination. This comprehensive study explores the dual impact of RFC on Hyderabad's economy, culture, and global positioning. By providing state-of-the-art infrastructure and attracting international filmmakers, RFC has contributed significantly to the growth of the local and national film industries, particularly in the Telugu film industry (Tollywood), while also facilitating Bollywood and international productions. Furthermore, RFC's integration of film production with tourism has played a crucial role in enhancing Hyderabad's status as a prominent global tourism hub. This study combines the secondary data, to assess RFC's influence on film tourism, local economic development, and community engagement. The findings highlight RFC's role in job creation, cultural preservation, and fostering a global identity for Hyderabad, while also identifying areas for improvement in sustainability practices and competition from emerging film cities. This research provides valuable insights into the symbiotic relationship between film production and tourism, offering a model for similar institutions globally.

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 Keywords

Ramoji Film City, Film, Tourism, Economic Impact, Social & Cultural Impact

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Customer churn prediction is crucial for e-commerce companies looking to improve retention and optimize business strategies. In this study, we aim to build a robust predictive model to identify customers at risk of churn, using a variety of customer features such as demographics, behavior metrics, order history, and satisfaction scores. The analysis begins with an exploratory data analysis (EDA), using Python libraries like pandas, numpy, matplotlib, and seaborn for data manipulation, visualization, and understanding patterns in the dataset. Missing values are visualized and addressed using missing no, ensuring data quality before model development. Several machine learning models are trained to predict customer churn, including Support Vector Classifier (SVC), Logistic Regression, Random Forest Classifier, and XGBoost, implemented with libraries such as scikit-learn and xgboost. Data preprocessing steps, such as scaling features with Standard Scaler and encoding categorical variables using LabelEncoder, are performed to prepare the dataset for model training. Model evaluation is conducted using performance metrics like accuracy, precision, recall, F1-score, ROC-AUC, and confusion matrix, offering detailed insights into the effectiveness of each model. In addition, hyperparameter tuning is achieved using GridSearchCV to optimize model performance. Cross-validation is applied with cross validate to ensure generalizability and robustness of the models. The study identifies key factors influencing churn, including marital status, order categories, and platform engagement, and provides actionable insights for the company to implement targeted retention strategies. By leveraging machine learning and data analytics, this research helps the e-commerce company proactively manage churn, enhance customer satisfaction, and optimize product offerings tailored to customer preferences.

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 Keywords

Customer Churn Prediction, Customer Segmentation, Exploratory Data Analysis (EDA), Predictive Modeling, Voting Classifier, Machine Learning, Feature Scaling.

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Creative Commons Attribution 4.0 and The Open Definition

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The increasing interest and adoption of cryptocurrency in India signal a transformative shift in the nation's financial ecosystem. Cryptocurrencies offer innovative solutions to challenges such as financial exclusion, currency inefficiencies, and limited access to global markets. This research paper explores the fundamental principles of cryptocurrency, its mechanisms, and its economic implications within the Indian context. Using case studies and data from India's burgeoning crypto market, the study investigates how cryptocurrencies can drive financial inclusion, support economic growth, and integrate the Indian economy into global financial systems. While acknowledging the potential advantages, the paper also examines challenges including regulatory uncertainties, technological barriers, and socio-economic risks, and proposes strategies for fostering sustainable growth of cryptocurrency in India.

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Cryptocurrency, Blockchain, Financial Inclusion, Economic Growth, India, Digital Economy, Regulation

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Creative Commons Attribution 4.0 and The Open Definition

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 Keywords

Direct Orange, Cotton Stalks,Adsorption Isotherms, Sorption mechanism.

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Creative Commons Attribution 4.0 and The Open Definition

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The widespread adoption of digital payment applications has transformed financial transactions, with Google Pay becoming one of the leading platforms in this domain. This study explores customer satisfaction with the usage of the Google Pay application, focusing on factors such as ease of use, transaction efficiency, security, rewards, and customer service. Using a survey-based approach, data was collected from a diverse group of users to understand their experiences and perceptions. The analysis highlights the key factors influencing customer satisfaction, including the intuitive interface, reliability of transactions, and the security measures offered by the platform. Positive experiences, such as seamless payment processes and attractive cashback offers, are significant contributors to user satisfaction, while challenges such as technical glitches and occasional delays in customer support were noted.

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 Keywords

Google Pay, Customer satisfaction, Security, Transactions

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This study explores the adoption of agile methods for the management of projects in collaborative research initiatives. The scrum framework, a specific set of agile principles and practices for self-organizing cross-functional teams in software development projects, is currently being expanded to other types of organizations and knowledge management processes. Qualitative research methodology was utilized in this study. The data for the current analysis was collected based on interview discussions, analysis of past sprint retrospectives, and sprint velocity data. The participants used for interviews and discussions were from various backgrounds and departments of the case company and included experts such as Scrum Master, Product Owner, Product Manager, Quality Assurance Team, Team Manager, Operation Manager and Software Developers. The study addresses the extent to which key principles and tools usually used in the scrum can contribute to the collaborative management and coordination of tasks in research processes due to their potentially positive influence on team dynamics and efficiency. The research started with the current state analysis of the agile scrum process within the case company's applications development team. Based on current state analysis and literature review, the researcher defined a new process model. The results and conclusions from the piloted iterations were further documented in this study.

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Agile Methodology, Scrum, Project Knowledge Areas, Project Management, Scrumban, Kanban and Scrum master

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This research paper consist of prompt based movie recommendation system that recommend the movies to users through using various technologies which interpret the user given prompt and give the movie suggestions to user.

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Content-based filtering- Natural Language Processing- Text input recommendation- Personalized movie suggestions- Recommendation algorithm-User prompt analysis-Movie genre classification.

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This study was conducted to determine the effectiveness of school-based management, stakeholders' engagement and school performance of Public Schools in Sta. Rosa City, Laguna. Specifically, it sought answers to the following statements (1) Determine the level of effectiveness of the school-based management dimensions in terms of: (1.1) leadership and governance, (1.2) curriculum and learning, (1.3) accountability and continuous improvement, and (1.4) managing of resources (2) Determine the stakeholders' engagement in terms of (2.1) school governance, (2.2) curriculum implementation, and (2.3) community involvement (3) Determine the school performance in terms of (3.1) school leadership, management and operations, (3.2) basic education services, (3.3) learning environment, (3.4) human resource management and development, and (3.5) parent's involvement and community partnership (4) Determine significant relationship between the level of effectiveness of school-based management dimensions and the level of stakeholders' engagement (5) Know significant relationship between the level of effectiveness of school-based management dimensions and the school performance (6) Know significant relationship between the level of stakeholders' engagement and the school performance (7) Determine if the level of effectiveness of school-based management and stakeholders' engagement, significantly predict the school performance. The descriptive-correlational design was used to analyze the data systematically. A standardized DepEd form and an adopted research questionnaire on a 5-point Likert scale were used in the study. Frequency, percentage distribution, and weighted mean were used for descriptive questions, while Pearson's R and Regression Analysis were used for inferential questions. Based on the gathered data, the implementation of school-based management is highly effective. The research further reveals that the stakeholders' were highly engaged and has excellent school performance. In addition, the results showed that there is a significant relationship between effectiveness of school management, stakeholders' engagement and school performance. Based on the findings and conclusion of the study, the following recommendations are hereby endorsed. (1) establish mechanisms for ongoing monitoring and evaluation of SBM and stakeholder engagement initiatives. (2) create formal structures for involving parents, teachers, students, and community members in the decision-making process. (3) develop effective communication channels to keep stakeholders informed and engaged. Use newsletters, social media, and school websites to share updates and gather input. (4) Foster partnerships with local businesses, non-profits, and community organizations to support school initiatives. These partnerships can provide additional resources, expertise, and opportunities for students. (5) Regularly recognize and celebrate the achievements of students, teachers, and other stakeholders. This can be in the form of a school program at the end of every academic year. This can boost morale and motivation, fostering a sense of pride and community. (6) Implement robust support services to address the diverse needs of students, including counseling, tutoring, and special education services. Ensure that all students have access to the resources they need to succeed. (7) Conduct longitudinal studies to understand the long-term impact of school-based management and stakeholder engagement on school performance. This can provide deeper insights into the sustainability of these practices. (8) Compare the effectiveness of SBM and stakeholder engagement across different regions, school types, and student populations to identify context-specific strategies that work best.

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 Keywords

Leadership and Governance, Curriculum and Planning, Accountability and Continuous Improvement, Management of Resources, Stakeholder Engagement, School Performance

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Creative Commons Attribution 4.0 and The Open Definition