Volume 13 | Issue 2

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Velvet Beans,Parkinsonism,

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This research delves into integrating AR into education using Unity, focusing on creating interactive and immersive learning experiences. The project comprises four modules: AR try-ons for accessories, 3D product models, AR furniture placement, and VR exploration. These modules enhance user engagement by enabling virtual try-ons, detailed 3D product exploration, real-world furniture visualization, and immersive VR experiences. By leveraging technologies such as image recognition, object tracking, and real-time data, the system fosters efficient, personalized, and interactive learning and shopping experiences.

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Augmented Reality

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Unmanned aerial vehicles (UAVs), also known as Drone Technology, have rapidly advanced and found new uses in a wide range of industries, including Disaster Relief, delivery services, agriculture, and Environmental monitoring. Drones' growing range of applications has resulted in more efficient and affordable solutions for both public and private sectors as their technolog- ical capabilities continue to advance. The present state of drone Applications is reviewed, and their potential to revolutionize several industries in the future is examined. Peer reviewed pa- pers, industry reports, and case studies released between 2015 and 2024 were the main focus of a thorough assessment of the literature that was carried out. Based on industry sectors, use cases, and geographical areas, the review categorized drone applications. To ascertain their effect on the adaptability and scalability of drone usage, significant technological developments including enhanced battery life, sensors, and AI-based Navigation were also examined. In the review, im- portant uses for drones are highlighted, including the improvement of Precision Farming through aerial imaging in the agricultural sector and the inspection and maintenance of infrastructure through drone use. Because drones can deliver medical supplies to remote locations, the Health- care Industry has also profited from drone technology. Drones also help with tracking pollutants and protecting wildlife, which makes them essential for Environmental Monitoring. According to the report, advances in AI and machine learning have greatly enhanced autonomous navigation, enabling drone missions to cover more ground in challenging-to-reach locations. Utilized across a wide range of businesses, drones have shown themselves to be a game-changing technology. Further realizing drones' promise will require breakthroughs in regulations and ongoing inno- vation in drone hardware and software. Yet, in order to properly incorporate drones into daily operations, obstacles including Security Concerns, privacy concerns, and airspace laws must be resolved. Improved safety procedures, more Drone Autonomy, and unexplored uses in industries like telecommunications and urban planning should be the main goals of future study.

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AI-based Navigation, Precision Farming, Healthcare Industry, Environmental Monitoring, Security Autonomy. Concerns, Drone

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The integration of blockchain technology into health management systems offers a secure, transparent, and efficient framework for managing healthcare data. Blockchain ensures the immutability and traceability of medical records, addressing issues of data tampering and unauthorized access. Its decentralized nature empowers patients with ownership and control over their medical information, enabling seamless and secure sharing across healthcare providers. Additionally, blockchain facilitates interoperability, reduces administrative overhead, and minimizes fraud through smart contracts and automated verification processes. This innovative approach not only enhances data security and privacy but also supports the implementation of personalized care of patient which ultimately leading to improved healthcare delivery and outcomes. The proposed system explores the potential of blockchain in addressing the challenges of existing health management systems while discussing its implications, challenges, and future directions.

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Blockchain, Interoperability, Automated, Security, Privacy.

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With the rapid growth of information on social media and news platforms, the spread of fake news has become a significant concern. Fake news can manipulate public opinion, disrupt social order, and negatively impact decision-making. This paper explores the application of Natural Language Processing (NLP) techniques for detecting fake news, focusing on the BERT (Bidirectional Encoder Representations from Transformers) algorithm. BERT, a state-of-the-art pre-trained language model, enables deep understanding of the context within text by processing words in relation to all other words in a sentence. We propose a framework that leverages BERT's powerful contextual embeddings for classifying news articles as either real or fake. The model is fine-tuned on a large dataset of labeled news articles, which enhances its ability to distinguish between truthful and deceptive content. Results show that BERT-based models outperform traditional machine learning methods in terms of accuracy, precision, and recall. This study highlights the potential of using BERT in fake news detection and offers insights into how NLP can be used to combat misinformation in the digital age.

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NLP, Fake News Detection, Social Media

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Employee welfare policies are crucial for enhancing productivity within organizations, particularly in demanding industries like coal mining, as exemplified by Singareni Collieries Company Limited (SCCL). This abstract explores the impact of employee welfare measures on productivity at SCCL, focusing on key areas like healthcare, housing, education, and recreation. It investigates how these initiatives influence employee morale, motivation, and overall well-being, ultimately affecting productivity. The abstract argues that comprehensive welfare programs contribute to a positive work environment, leading to increased efficiency, reduced absenteeism, and improved quality of work. It also examines the correlation between employee satisfaction and key productivity indicators within SCCL. Furthermore, the abstract acknowledges the challenges and opportunities in optimizing these policies to maximize their impact in the ever-evolving coal mining sector. By prioritizing employee welfare, SCCL can foster a motivated workforce, attract and retain skilled employees, and achieve sustainable productivity gains

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Employee welfare, productivity, SCCL, coal mining, Safety, Security, employee satisfaction, work environment

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Modern game design relies heavily on the development of intelligent and engaging enemy AI, especially in 2D games, where enemy behavior largely influences player experience. The traditional techniques used in AI scripted behavior and Finite State Machines are part of a top-down approach and result in a completely predictable, thus easily manageable, enemy action. However, there is usually no adaption to dynamic player behavior in these kinds of approaches, hence degrading gameplay depth and replay values greatly. On the other hand, adaptive AI techniques, such as genetic algorithms following the bottom-up approach, promise more responsive and challenging behaviors from enemies but can also be complicated and resource-intensive in their implementation. This research investigates the practical implications, performance differences, and impacts on player experience between top-down and bottom-up AI approaches. In this study, a 2D game prototype with enemies controlled by both AI techniques is developed in order to systematically evaluate and compare the effectiveness of these methods. The aim is to provide insights into the strengths and limitations of each AI approach, hence guiding game developers in the selection of the most appropriate method for different gaming contexts.

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Game AI, top-down AI, bottom-up AI, finite state machines (FSM), genetic algorithms.

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The present work is an attempt to understand the concept of mind and body from the standpoint of Indian Philosophy. All the Indian schools of philosophy tried to know the reality and to understand the secret of life through the inner knowlwdge of human being. According to Vedic literature, human body is composed of five elements, which are earth, water, fire, air, and ether. In the Upanishad, human body constituted energy body , physical body and soul, which link the human body with the life in the Universe. Human body divided into three categories, Gross body, Subtle body and Causal body. On the other hand, almost all the the Indian schools of philosophy accepted that mind is an inner sense organ of the body, which is master or controller of other sense organ. In Indian Philosophy, mind is considered an instrument of the soul. It is considered an inner sense organ or antahkaran.it is also related to the body, which is outer instrument or five sense organs and five action organs. It is also an instrument of knowlwdge and helps in knowing consciousness.

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mind, body, gross body, sublte body, causal body, antahkarana, citta, ahamkara.

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Abstract Yoga can be accepted as the foundation of 'Vasudhaiva Katumbakam', the idea of tying the whole world into a single thread of kinship, of living together peacefully as a global family, regardless of caste, religion, gender, culture etc, the root of which embeded in Indian culture and the theoretical as well as practical teaching of yoga that has been considered as a well-accepted holistic method in this regard. Derived from the Sanskrit root 'yuj', yoga means the union of the individual consciousness with the universal consciousness. It is not only some physical exercises for breathing procedures but also a scientific method of developing the infinite power and potential that already exist within the human mind and soul. Another meaning of the word 'yoga' is harmony, just as when all of the strings of a veena are property blended and coordinated, a heavenly tone emerges from that, so through the coordination of physical and mental actions, the overall self-realization of a person is emerged and that self-realization is gradually transmitted to all beings of this universe. This article has taken an attempt to sketch a brief outline of the concept of "Yama', the first limb of ast?nga yoga sadhana depicted by Maharsi Patanjali, as a vital Key concept, following or practicing which, the sense of morality be revealed in its fullest form in man and nurture a non-violent happy, peaceful togetherness in the society.

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Key words: Yoga, Yama, morality, peaceful coexistence.

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Abstract This study explores the rich tradition of literary adaptations in Indian cinema, tracing their historical progression and examining how filmmakers have transformed Indian narratives for the screen. From ancient epics to contemporary novels, Indian literature has been a vital source of inspiration for the country's film industry. This paper examines the film adaptation of Aravind Adiga's "The White Tiger" with a focus on its portrayal of social inequality, class struggle, and systemic corruption. This paper examines how the movie uses a unique visual language to vividly depict the ingrained socioeconomic divisions in contemporary India by contrasting lavish high-rises and dazzling cityscapes with the confined, dark innards of servant quarters and destitute rural area. Through a detailed analysis of cinematographic techniques such as contrasting settings, strategic use of colour, lighting, and composition, the research demonstrates how these visual elements not only underscore the external realities of a corrupt society but also mirror the internal transformation of the protagonist, Balram Halwai. This article highlights how cinematic storytelling may effectively convey difficult literary concepts into a captivating visual story, supporting and enhancing the novel's sharp social commentary. This study explores how filmmakers manage the balance between preserving the original text's integrity and creatively reinterpreting it to reflect changing audience expectations and cultural shifts. Key words: Film adaptation, cinematographic techniques, transformation, contemporary socio-economic divide, transformation.

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Key words: Film adaptation, cinematographic techniques, transformation, contemporary socio-economic divide, transformation.

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This case presents a 35-year-old man who ingested paraquat, a toxic herbicide, in a suicide attempt following the recent loss of a close family member. He presented with acute onset of nausea, vomiting, severe abdominal pain, shortness of breath, and worsening respiratory distress. Physical examination revealed signs of severe respiratory compromise, including cyanosis, labored breathing, and decreased breath sounds bilaterally. Laboratory results indicated kidney dysfunction, and imaging showed early signs of pulmonary edema. Paraquat poisoning was suspected based on these findings, and the patient is under close monitoring for respiratory failure, renal dysfunction, and multi-organ involvement. Management includes supportive care such as oxygen therapy, intravenous fluids, and consultation with a toxicologist for additional therapeutic guidance.

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Paraquat poisoning, suicide attempt, Acute respiratory distress, Pulmonary edema, Kidney dysfunction, toxicology, supportive care

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Abstract: Introduction: Salvia hispanica (commonly known as chia) is a flowering plant native to Central and South America. It is highly valued for its seeds, which are a rich source of essential nutrients such as omega-3 fatty acids, dietary fiber, antioxidants, and high-quality proteins. Medicinally, chia seeds are recognized for their potential in promoting cardiovascular health, regulating blood sugar levels, and aiding in weight management. Additionally, they possess anti-inflammatory and antioxidant properties, making them beneficial in preventing chronic diseases such as diabetes, hypertension, and obesity. These attributes underscore their role as a functional food with significant therapeutic applications. Objective: To evaluate the impact of different colored light treatments on growth parameters, polyphenolic content, and antioxidant activity in Salvia hispanica, with a focus on enhancing its medicinally significant properties. This study aims to optimize light conditions to maximize the production of bioactive compounds that contribute to its therapeutic potential, including its antioxidant, anti-inflammatory, and disease-preventive effects. Methodology: The research was conducted to investigate the effects of different colored light treatments on the growth, polyphenolic content, and antioxidant activity of Salvia hispanica, with a focus on enhancing its medicinal properties. The experiment was carried out at Pakistan, under controlled environmental conditions. Results: The study demonstrated that different colored light treatments significantly influenced the growth parameters, polyphenolic content, and antioxidant activity of Salvia hispanica. Red and blue light treatments showed the most pronounced effects, enhancing plant height, biomass, and chlorophyll content. Plants exposed to blue light exhibited the highest polyphenolic content and antioxidant activity, indicating an improvement in the plant's medicinal properties. These findings suggest that light quality plays a crucial role in optimizing the therapeutic potential of Salvia hispanica. Conclusion: This study concludes that light quality significantly affects the growth, polyphenolic content, and antioxidant activity of Salvia hispanica. Blue light was identified as the most effective in enhancing its medicinal properties, highlighting its potential for optimizing the production of bioactive compounds for therapeutic applications.

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Chia seeds, JASU, medicinal plant, antioxidant

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Reforms in Indian Education System: Teacher Training and New Education Policy 2020

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Reforms in Indian Education System: Teacher Training and New Education Policy 2020

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Traditional arrhythmia detection methods often focus solely on identifying irregular heart rhythms, frequently neglecting the quality of the input signal, which can lead to inaccuracies. This study proposes a novel approach that incorporates signal quality assessment as a preliminary step in arrhythmia detection, significantly enhancing reliability. By leveraging advanced deep learning models such as CNNs, RNNs, and FCNNs, combined with signal processing techniques, our method evaluates signal quality prior to detecting arrhythmic events, ensuring a more robust analysis. The proposed approach is tested on diverse datasets, demonstrating notable improvements in detection accuracy and signal quality evaluation. Comparative analyses, with and without signal quality assessment, further underscore the advantages of this technique over conventional methods. By integrating quality-aware detection into routine cardiac monitoring, this method holds the potential to reduce false alarms, improve detection precision, and advance arrhythmia management in clinical practice.

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Deep Learning, CNN, RNN, FCNN, Datasets, Arrhythmia Signals

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Pesticide residues in food crops have emerged as a significant concern due to their potential implications for food safety and human health. This comprehensive review evaluates the current state of knowledge regarding the presence of insecticide, herbicide, fungicide, and rodenticide residues in various crops, assessing their associated risks and mitigation strategies. The study highlights the widespread use of pesticides in agriculture, driven by the need to enhance crop yields and protect against pests. However, improper application, incorrect selection, and inadequate post-harvest intervals can accumulate harmful residues in produce. Through an extensive literature review, the study analyzes the levels of pesticide residues detected in diverse crops, scrutinizing the analytical methods employed for their determination. Furthermore, it delves into the potential adverse health effects associated with exposure to these residues, including neurotoxicity, endocrine disruption, reproductive issues, and increased cancer risk.

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pesticides, impact on health, occupational hazards, insecticides, poisoning

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This Manuscript explores the integration of nanotechnology with biomedical engineering in the development of advanced wearable devices. As wearable technology continues to gain traction in health monitoring and management, the unique properties of nanomaterials enable the creation of highly sensitive sensors, flexible electronics, and efficient drug delivery systems. By examining the principles of nanotechnology and biomedical engineering, we highlight their collaborative potential in enhancing the functionality, comfort, and efficacy of wearable devices. The paper discusses various applications, including smart health monitoring, personalized medicine, and the challenges of safety and regulatory compliance associated with nanomaterials. Additionally, it emphasizes the importance of interdisciplinary collaboration in driving innovations in this field. Ultimately, this review aims to provide a comprehensive understanding of how cross-disciplinary approaches can lead to transformative advancements in wearable technology, ultimately improving healthcare outcomes and empowering users to take charge of their health.

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Wearable Devices, Biosensors, Nanotechnology, Biocompatible materials

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This research examines the impact of digital transformation on the satisfaction levels of the young generation with banking services in Tamil Nadu, particularly focusing on Krishnagiri Town. By analyzing factors such as convenience, user experience, security, accessibility, and personalization, the study aims to provide valuable insights for financial institutions to enhance their digital offerings and improve customer satisfaction. Through descriptive studies, factor analysis, and regression analysis, the research identifies key determinants of satisfaction and recommends strategies for banks to enhance service quality, increase customer involvement, leverage endorsements, and ensure service availability. These findings contribute to the existing knowledge on digital transformation in banking and offer actionable insights for developing customer-centric digital solutions tailored to the needs of today's tech-savvy consumers.

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Digital transformation, Banking services, Service quality, Customer-centric

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This paper explores the application of AI-powered predictive maintenance in microservices-based financial systems, focusing on its potential to enhance system resilience, optimize performance, and reduce operational costs. With the increasing adoption of microservices architectures in the financial sector, ensuring system reliability and availability is paramount. The study employs machine learning models to predict system failures, enabling proactive maintenance and minimizing downtime. By analyzing key performance metrics such as system uptime, failure rates, recovery times, resource utilization, and response times, the research demonstrates the effectiveness of predictive maintenance in reducing failure rates, accelerating recovery, and improving resource efficiency. The results show significant improvements in system reliability, cost savings, and user satisfaction. This paper provides valuable insights into how AI-driven predictive maintenance can be integrated into financial systems to improve their performance, reduce maintenance costs, and increase operational resilience, offering both practical implications for industry practitioners and theoretical contributions to the field of AI and microservices architecture.

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AI-powered predictive maintenance, microservices architecture, financial systems, machine learning, system resilience

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Pandit Deendayal Upadhyay : Nishkaam Karmyogi

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Pandit Deendayal Upadhyay : Nishkaam Karmyogi

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Electro-mechanical switch reliability is a critical issue in the automobile industry. While physical tests are used to evaluate reliability, adequate sample size is a challenge. It is essential to design Reliability model using physical as well as digital simulation data. Such "Phygital Reliability Model" will be useful to improve the overall prediction accuracy and pave the path for fully digital reliability model. The paper presents an experimental study of switch reliability parameters and proposes a "Phygital Reliability model". A methodology used analyses electrical and mechanical parameters of a switch in physical domain and simulated data in digital environment. During this process, the design specifications for Roof lamp Switch are collected, the environmental parameters such as temperature, humidity and vibration are measured, and electrical load analysis is conducted. The switch contact geometry, one of the major parameters that affect contact resistance, has been elaborated holistically. The obtained results are used in statistical model to forecast the switch life. This methodology can be further extended to all electromechanical switches in automotive industry.

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Regression, Reliability, FEA

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