Volume 12 | Issue 11 |

 Abstract

Climate change is an area of science that has been studied for many years. The fossil record has taught humankind much about conditions on Earth long prior to our arrival. We now live in a unique time in that our scientific abilities have not only given us a precise age of the planet, but of the universe itself. Yet there are many things we do not understand, and some of the questions that remain before us may have a significant impact on the quality of our lives in the future. As our current civilization observes an unquestioned period of warming on Earth, the issue of the nature of this change remains a topic of discussion for both scientists and the public at large. It is important, therefore, for those of us in the educational community to help our students get the best information with which to guide their own thoughts and decisions in a changing world. This paper analyzes educational resources for climate change and applies concepts from these resources to research-focused curriculum for secondary school students.

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 Keywords

Climate Change

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The purpose of this work is to examine how AI in a cloud environment may help the banking sector alter for the better in terms of work performance, work quality, work security, and cost savings. Using industry reports data, bank performance figures and qualitative and quantitative surveys of banking employees and customers, the study find visibility of tangible changes along all the highlighted measures. Studies demonstrate measurable improvements in transaction cycle times and periods of time taken to resolve customer support issues, in addition, fraud detection, customer satisfaction, and retention. This translated to = The operational costs went down since many processes were automated, and since the cloud could be hybrid, costs were easily scalable As some tasks were automated, the employees' productivity went up. Based on the research, it is prudent to argue that the integration of AI and cloud technologies is the way forward for banks to deliver on their mandate of being innovative-serving customers across the digital economy. These results bear testimony to ongoing investments in AI-based cloud technologies for handling the changing needs of the banking world.

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 Keywords

AI-enhanced cloud technologies, banking transformation, operational efficiency, fraud detection, customer satisfaction, digital banking

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Deep fakes are highly realistic 'fake' videos and they are entirely the creation of advanced technologies of recent decades including machine learning, artificial intelligence, and deep learning. Such videos, very similar to real videos, are obtained by training deep computer models on the abundant face database and gradually mapping one person's facial movements onto the other. The following questions arise when Deepfakes are often used; Political instabilities, fake terrorism cases, losing confidence in digital platforms among others. Hence, there is a need for society and advance technology to develop new techniques for deep fake detection and prevention. This essay looks critically at the situation of today.

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 Keywords

Deepfakes, Haar Cascades, MTKNN (Multi-task Kascaded Convolutional Networks), Convolutional Neural Network (CNN), Sigmoid Activation, Real-time Detection, Prevention Model, Steganalysis.

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 Abstract

Agricultural productivity largely depends on the suitability of soil types and optimal crop selection. However, traditional methods of soil classification and crop recommendation often lack accuracy and are time-consuming. This research introduces "Smart AgroTech," a system integrating sensor technology and machine learning to classify soil and recommend crops efficiently. This system gathers real-time soil data (pH, temperature, moisture, nutrient levels) via sensors, applies Support Vector Machine (SVM) for classification, and offers crop recommendations aligned with soil properties. Results demonstrate a substantial improvement in classification accuracy and crop matching, thus highlighting Smart AgroTech potential as a practical solution for enhancing agricultural yield through data-driven precision.

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 Keywords

Soil Classification, Machine Learning, Smart Agriculture, SVM, Sensor Integration, Soil Analysis, Crop Prediction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research examines hypnotherapy as a therapeutic intervention for addressing childhood trauma in adults, focusing on its effectiveness in fostering resilience and emotional stability. Childhood trauma, including abuse and neglect, significantly affects adult psychological well-being, often leading to disorders such as PTSD, depression, and anxiety. Hypnotherapy, rooted in positive psychology, is explored here as a technique to reprocess traumatic memories and integrate them into a healthier self-concept. The study presents three case studies of adults with histories of childhood trauma, each receiving hypnotherapy for symptoms such as anxiety, insomnia, and social withdrawal. Over multiple sessions, each participant achieved a notable improvement in resilience, reduced anxiety, and greater social confidence. Hypnotic techniques, including visualization, relaxation, and age regression, were tailored to each individual, facilitating emotional release and fostering positive cognitive restructuring. Findings suggest that hypnotherapy, through its ability to access the subconscious mind, is a promising intervention for those suffering from the lingering effects of childhood trauma. Despite the study's limited sample size, results indicate hypnotherapy's potential as a meaningful approach to trauma healing, warranting further research with a larger, more diverse population.

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 Keywords

Hypnotherapy, Childhood trauma, Positive psychology, PTSD, Relaxation, Age regression, Cognitive restructuring

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Asset light strategy is a new trend of investing and earning revenue in the hospitality sector. In an asset-light strategy, hotels invest in intangible assets, despite tangible ones, to earn revenue. One notable example is the Mariott Hotel, which successfully implemented this strategy while entering the Indian market. In their reports, Mariott Hotel explicitly stated that they are employing an asset-light strategy. This strategy can help businesses increase their market share with less capital investment. It is beneficial both in terms of risk and profitability. This case study paper examines Marriott International's strategy of asset lighting and its success story in capturing the Indian hospitality industry. It helps improve the firm's value by increasing profits and lowering risks. This paper initially explains the asset light strategy and the various pros and cons of implementing it. Then it gives an overview of Mariott Corporation and how they used this strategy to capture and dominate the Indian hospitality industry. The paper concludes with a discussion on the implementation of the asset light strategy.

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Mariott Hotel and Resorts, Asset Light Strategy, Capital Structure, Franchising, Hospitality

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The purpose of the study was to investigate the effect of aerobics training and circuit training on selected physical fitness components and physiological variables among college women volleyball players. It was hypothesized that there was a significant difference on selected physical fitness components and physiological variables due to the effect of aerobics training and circuit training among college women volleyball players. For the present study the 30 female college volleyball players from volleyball players in Sri Ramakrishna College of Arts and Science for Women were selected at random and their age ranged from 18 to 25 years. For the present study pretest & posttest random group design, which consists of control group and experimental groups was used. The subjects at random assigned to three equal groups of fifteen each and named as Group 'A', Group 'B' and Group 'C'. Group 'A' underwent aerobics training, Group 'B' underwent circuit training, and Group 'C' have not undergone any training. The physical fitness component variables is cardio respiratory endurance and physiological variables is resting pulse rate were assessed by cooper '12' minutes run and walks test & digital pulse monitor respectively. The data were collected before and after six weeks of training. The data were analyzed by applying Analysis of Co-Variance (ANCOVA). The level of significance was set at 0.05. The experimental group showed better improvement on cardio respiratory endurance and resting pulse rate among college women volleyball players than the control group.

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 Keywords

Volleyball, Aerobics Training, Circuit Training, Physical Fitness Components, Physiological, Cardio Respiratory Endurance and Resting Pulse Rate.

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Creative Commons Attribution 4.0 and The Open Definition

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This paper introduces a blockchain-enabled Tender Management System (TMS) designed to enhance the security, transparency, and efficiency of the traditional tendering process. The proposed system consists of several integrated modules: Database Connection, Tender Management, Bid Management, and Blockchain Integration, each of which plays a crucial role in delivering a secure and user-friendly bidding environment. With bid encryption, time-sensitive bidding windows, and immutable blockchain records, the application addresses key challenges in tender processes, such as data tampering, lack of transparency, and bid confidentiality. Our findings suggest that the integration of these modules not only improves user trust but also sets a new standard for decentralized and transparent applications in tender management.

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blockchain

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Creative Commons Attribution 4.0 and The Open Definition

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The constitutional approach in homoeopathy is a distinctive and holistic method that aims to treat individuals based on their unique mental, emotional, and physical make-up rather than just the presenting symptoms. This article reviews the various constitutional types in homoeopathy, such as temperamental, diathesis, and miasmatic constitutions, exploring their characteristics and associated remedies. The study demonstrates how constitutional assessment can guide homoeopathic practitioners in selecting individualized treatments that address both predispositions and current health concerns.

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Constitution, Homoeopathy, Temperament, Diathesis, Remedy, Miasmatic

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As much as prompt engineering has become an important method of optimizing generative AI systems, it is only useful in making the output that it produces accurate, contextually relevant, and ethically sound across various applications. However, the field remains fraught with challenges, including the ambiguity of language, risk of bias, and lack of standardization in best practices. The process of prompt engineering by its nature is iterative, and it can take hours to complete, making large-scale deployment at the enterprise level challenging. Moreover, in applications where the latest data is required, the use of generative models having a fixed knowledge cutoff renders them less suitable. At the same time, vast opportunities are opened up when using prompt engineering: namely, it allows for specialization towards specific industry use cases, supports accessible human-AI collaboration, and provides innovation in creative industries. New tools and frameworks are making prompt design easier. In addition, growing career opportunities underpin how much more critical this emerging area of significance is for all. Lastly, prompt engineering may also make more responsible AI outputs that can further the generative models along ethical lines while bringing the role of AI closer to becoming a trusted partner in commercial as well as creative fields.

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 Keywords

Prompt Engineering ,Generative AI , Challenges in AI ,Opportunities in AI , AI Models , Natural Language Processing (NLP), Large Language Models (LLMs),Prompt Optimization , Human-AI Interaction, AI Ethics, Model Training, Contextual Relevance, AI Prompt Customization

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