Volume 13 | Issue 4 |

 Abstract

Allergic rhinitis (AR) is a prevalent condition characterized by inflammation of the nasal mucosa due to allergic triggers, causing significant morbidity and impairment of quality of life. Accurate diagnosis is essential for effective management and treatment, but remains challenging due to the overlap of symptoms with other nasal disorders. This comprehensive review explores the diagnostic approach to allergic rhinitis, from patient history to advanced diagnostic testing. We begin by discussing the critical role of a thorough clinical history, including symptom onset, seasonal patterns, and potential allergen exposure, in differentiating AR from other causes of rhinitis. Physical examination findings, particularly the identification of allergic nasal mucosal changes, are also examined. The review then delves into diagnostic testing modalities, including skin prick tests (SPT), specific IgE blood tests, and emerging methods like nasal allergen provocation tests. By synthesizing current evidence, this review aims to provide a clear, updated framework for diagnosing allergic rhinitis, ensuring early and precise identification of the condition for optimal patient care.

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 Keywords

Allergic rhinitis, allergens, pruritis, nasal congestion, rhinorrhea, rhino conjunctivitis,IgE.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The growing application of artificial intelligence (AI) in medical imaging has significantly improved diagnostic capabilities. However, the high computational demands of deep learning models have raised concerns regarding energy consumption and environmental sustainability. This paper explores an innovative green computing approach to optimizing AI-based medical imaging systems. By leveraging model pruning, quantization, and edge computing, this paper propose an energy-efficient framework that minimizes carbon footprints while maintaining diagnostic accuracy. The study evaluates the energy savings and performance trade-offs in MRI, CT scans, and X-rays, comparing traditional AI-based models with optimized green AI systems. Experimental results indicate that sustainable AI models can significantly reduce energy consumption without compromising diagnostic efficiency. This research provides a foundation for further advancements in eco-friendly AI applications in healthcare.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Green computing, AI in medical imaging, energy-efficient deep learning, sustainable healthcare, edge computing

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Creative Commons Attribution 4.0 and The Open Definition

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Water assets are fundamental for supporting life, farming, businesses, and environments. Be that as it may, the developing weights of expanding populace, fast urbanization, and climate alter are straining the existing water framework. Precise determining of future water requests and a comprehensive evaluation of store capacity capacities are pivotal for successful water administration. Without these experiences, choice producers battle to arrange for maintainable advancement and relieve the dangers related with water shortage and extraordinary climate occasions. This venture centers on creating a prescient model that coordinating authentic information, climate projections, populace development patterns, and agrarian hones to figure future water necessities. It too assesses the supply capacity capacities and distinguishes potential holes and related dangers. By leveraging progressed information analytics and machine learning methods, this framework gives noteworthy experiences for policymakers, empowering proactive arranging and productive water asset administration. The Prescient Demonstrate for Water Emergency Administration particularly addresses challenges, such as extraordinary dry spells, wasteful supply administration, and eccentric climate designs. By combining vigorous data-driven strategies and user-friendly devices, the demonstrate points to guarantee feasible and strong water-management hones

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 Keywords

Water requirement, ARIMA Model, Machine Learning, water capacity, future water requirement.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Employee engagement, job satisfaction, and organizational development are interconnected constructs that are driven by effective communication, feedback, and relationship management. This study investigates the relationships between employee motivation, feedback, communication, and organizational development, employing a mixed-methods approach. The findings emphasize the significance of regular feedback, open communication channels, and positive employee relationships in promoting employee engagement, job satisfaction, and motivation. Furthermore, a multilevel approach to organizational development is essential for sustaining long-term employee engagement and job satisfaction. This study provides a comprehensive framework for enhancing employee engagement, job satisfaction, and organizational development. Keywords: employee engagement, employee feedback, communication, job satisfaction, employee relationship management, organizational development, employee motivation.

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The effect of motivation and employee relationship on employee well-being and life satisfaction

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 Abstract

Cyber-security, similar to statecraft, requires strategic foresight, intelligence gathering, and strong defensive measures. This study examines how Chanakya's strategic principles from the Arthashastra can be applied to modern cyber-security frameworks, illustrating how ancient wisdom can enhance contemporary digital defense strategies. Chanakya focused on governance, espionage, fortification, and crisis management to protect a kingdom principles that resonate with proactive risk assessment, defense-in-depth strategies, and governance policies in cyber-security. A crucial element of Chanakya's strategy was the use of intelligence and counterintelligence, which has modern equivalents in threat intelligence, deception tactics like honeypots, and insider threat management. His focus on alliances and diplomacy aligns with today's cyber-security collaborations, such as information sharing among organizations and collective threat mitigation efforts. Moreover, crisis preparedness and pre-emptive actions, central to Chanakya's governance, correspond with modern cyber-security strategies like Zero Trust Architecture and proactive defense measures. This paper posits that cyber-security can gain from Chanakya's comprehensive approach, integrating layered defense, proactive threat management, and strategic deception to bolster resilience against evolving cyber threats. By drawing connections between ancient state security and digital security, this research emphasizes the enduring relevance of Chanakya's insights. It also highlights the significance of education and awareness programs, reflecting Chanakya's belief in knowledge as a vital defense tool. Through this interdisciplinary approach, the study presents a comprehensive cyber-security framework inspired by Arthashastra, bridging historical strategic thought with modern technological advancements. By leveraging these principles, organizations can strengthen their Cyber-security posture, ensuring a more resilient and adaptive digital defense system in an era of increasingly sophisticated threat.

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 Keywords

Chanakya, Arthashastra, Strategic Defense, Threat Intelligence, Espionage, Counterintelligence, Zero Trust Architecture, Defense-in-Depth, Cyber Resilience.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The integration of Artificial Intelligence (AI) in agriculture, often termed "smart farming," is transforming traditional agricultural practices into data-driven, optimized systems that increase productivity and sustainability. With the global population projected to surpass 9 billion by 2050, conventional farming methods alone may not suffice to meet the escalating food demands. Smart farming, powered by AI technologies, addresses critical challenges in agriculture by enhancing crop monitoring, enabling precision irrigation, improving soil analysis, and optimizing pest and disease control. This research paper explores the deployment of AI-driven tools, such as machine learning algorithms, Internet of Things (IoT) devices, and drones, to revolutionize various agricultural tasks. Machine learning algorithms analyze environmental and crop-related data to predict ideal planting and harvesting periods, assess soil health, and optimize resource distribution. IoT sensors provide real-time data on factors such as soil moisture, temperature, and humidity, allowing for automated irrigation systems that significantly reduce water waste. Additionally, computer vision and deep learning enable precise monitoring and diagnosis of plant diseases, supporting timely interventions and reducing the need for chemical treatments. The adoption of AI in agriculture not only enhances efficiency and crop yields but also minimizes environmental impact by reducing resource consumption and improving land utilization. This paper further highlights the practical applications of AI in smart farming and discusses the challenges and future opportunities for AI integration in agriculture. Ultimately, the findings underscore AI's potential to make farming more resilient, sustainable, and capable of supporting global food security.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart Farming, Machine Learning, Crop Monitoring, Precision Irrigation, Agricultural Automation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents the development and implementation of a Domestic Waste Management System that integrates an Android mobile application and a web platform. The system is designed to improve waste collection efficiency by enabling users to schedule waste pickups, track waste collectors, and report missed pickups. The web platform provides an interface for waste management authorities to monitor and manage the waste collection process, view analytics, and respond to user feedback. Technologies such as GPS, real-time data analytics, and cloud computing have been leveraged to ensure system scalability and reliability. The system aims to optimize the waste collection process, reducing environmental impact and enhancing urban cleanliness.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Waste Management, Android Application, Web Platform, Smart City

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Mouth ulcers, also known as aphthous ulcers or canker sores, are a common oral mucosal disorder characterized by painful lesions in the mouth. They can be caused by various factors such as trauma, hormonal changes, stress, or certain underlying medical conditions. Traditional herbal remedies have been used for centuries to alleviate the discomfort associated with mouth ulcers and promote healing. This abstract review the efficacy of several herbal remedies commonly used for treating mouth ulcers, including turmeric, guava leave and coccinea grandis. These herbs possess anti-inflammatory, antimicrobial, and wound-healing properties, which may help to reduce pain, inflammation, and promote faster healing of mouth ulcers. Clinical studies evaluating the effectiveness of these herbal remedies have shown promising results in reducing the duration and severity of mouth ulcers. However, further research is needed to fully understand their mechanisms of action and establish standardized protocols for their use in clinical practice. Herbal remedies can be considered as alternative or adjunctive therapies for managing mouth ulcers, but patients should consult with healthcare professionals before using them, especially if they have underlying medical conditions or are taking medications that may interact with these herbal remedies. Mouth ulcer gel can help alleviate discomfort and promote healing for mouth ulcers. They create a protective barrier over the ulcer, reducing irritation from food and drink, and often contain ingredients to reduce inflammation and pain. If you're experiencing discomfort from mouth ulcers, using a gel could provide relief and support healing. However, for persistent or severe ulcers, it's advisable to consult a healthcare professional for further evaluation and treatment.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mouth ulcer, Polyherbal gel, Anti-inflammatory, Antimicrobial.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Task scheduling is the pillar of successful cloud computing systems. With increasing system complexity and the reliance on data, intelligent, adaptive task management becomes ever more in demand. This project proposes an error-level analysis-based, automated task rescheduling system incorporating a sequential model, and integrating it with cloud databases through MongoDB. The system seeks to effectively reallocate tasks due to delays in execution, failure, or abnormalities so that optimal use of resources and staff productivity is maintained. An intuitive interface based on Streamlit facilitates real-time task allocation, tracking, and handling. The solution solves static scheduling challenges by dynamically adjusting according to task condition variations and employee working hours. The project further incorporates a gamified experience point system that motivates timely task completion and monitors employee progress. The system's architecture, implementation, and implications are presented in this paper, which demonstrates its relevance to organizations pursuing operational resilience and efficiency.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Task Scheduling, Cloud Computing, MongoDB, Streamlit, Automation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Purusho ka Balatkar aur Utteepadan

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Purusho ka Balatkar aur Utteepadan

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Creative Commons Attribution 4.0 and The Open Definition