Volume 14 | Issue 5 |

 Abstract

Rice is a cereal grain that is dominantly consumed by more than half of worlds population and is very significant in Indian agricultural economy. Rice is number one, most eat in food globally followed closely by other staples like wheat(in bread ) and maize(corn). Agriculture and allied sectors contribute about 16 to 18% of India's GDP, despite its lower GDP share, the sector employees over more than 40% of the total population. And hence, India is among leading producers and exporters of rice. However, the crop yield as significantly threatened by diseases such as bacterial Blight, brown spots, leaf blasts etc, which can cause potential yield and quality loss if not identified properly. Farmers majorly rely on manual field assessment, which is labour intensive ,time consuming and often could lead to Miss identification and significant economic loss. Recent advancement in fields like machine, learning, deep learning, and hyperspectral imaging has automated data driven approaches that are capable of improving detection, accuracy and efficiency. This study critically examine is more than 10 research works published between 2019 - 2025 covering traditional tools, techniques, frameworks, and algorithms for object detection and imaging techniques. And after a thorough systematic research and evaluation, a detection system was developed to identify rise, disease and help reduce yield loss. After comparatively evaluating the researches, it has indicated that deep learning models consistently demonstrate a superior performance frequently achieving a higher accuracy level more than 95% while hyperspectral and UAV base system offer potential for early stage disease identification despite practical cost constraints. This review identifies existing research gaps and focuses on need for scalable, lightweight and farmer friendly disease detection system to support sustainable farming in India and contribute to global agricultural application.

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 Keywords

Machine Learning, Deep Learning, Rice Disease Detection, YOLO, Hyperspectral Imaging, UAV, Smart Agriculture, Automation.

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 Abstract

Globally, more than 135 million people die annually as a result of road traffic accidents. Of those fatalities, India experiences more than 155,000 each year.These staggering statistics indicate that the current strategies in place to increase road safety are less in preventing road collisions. The system has been created with one purpose in mind -- to prevent road collisions/accidents before they happen rather than after they occur. This project has brought together experts in two different areas of science: computer science (specifically through machine learning and still-image preprocessing) and electronics & communications engineering (specifically through sensor design, wireless communication, and signal processing). We are engaging in a collaborative effort among these two groups of experts within an entirely new paradigm called transdisciplinary research. The proposed system consists of five layers in its design. At the bottom layer are three sensors, an ultrasonic proximity detection array and a LiDAR, which facilitate non-contact detection of a vehicle's approximate location. The next layer above the sensors is an AI-powered collision prediction engine that can predict possible collisions with vehicles or objects up to several seconds before they would otherwise occur. A vehicle-to-vehicle (V2V) communications module allows for real-time sharing of hazard information between two vehicles; and an automated emergency response interface completes the loop by acting on the information provided by the V2V communications system without waiting for human input. To substantiate the design with empirical evidence, we conducted four case studies of deployed smart safety systems: the Euro NCAP AEB program in Europe, the ITS Connect V2V system in Japan, the IHMCL smart highway pilot in India, and Tesla Autopilot's collision avoidance functions. The collective lessons learned from these four studies were used to inform the technical architecture and policy recommendations of the proposed system. The key outputs of this project include a conceptual system prototype, a multi-dimensional feasibility analysis, and a specific set of recommendations regarding India's road infrastructure and automotive laws/regulations necessary for the successful implementation of smart vehicle safety technologies.

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 Keywords

1. Smart Collision Safety System 2. Advanced Driver Assistance Systems (ADAS) 3. Vehicle-to-Vehicle Communication (V2V) 4. Collision Avoidance System 5. Artificial Intelligence (AI) 6. LiDAR Technology 7. Convolutional Neural Network (CNN) 8. Autonomous Emergency Braking (AEB) 9. Sensor Fusion 10. Intelligent Transportation System (ITS)

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Abstract-- Fake emails, fake sites and harmful links are now one of the top internet risks to both individuals and businesses. Many users are caught off guard and give away private details like login codes, financing facts or personal records, without realizing it. Firewalls can be big and strong, but they can't stop someone from clicking on something they shouldn't. Introducing PhishScale: not just alerting, but changing the way teams alert from within. It runs quiet drills behind locked digital doors, simulating real attack techniques without real-world risk. Leaders begin practice rounds based on what the team is used to, instead of waiting for the mistakes. Messages come as usual, but these have lessons within them, not harm. Learning occurs quietly after every exchange, shaped by the conduct rather than lectures. No panic, no blame - just a slow improving of gut instincts over time. Building awareness from setup to follow-up, each step is without much attention. Someone clicks on a fake link? The system absorbs this immediately. Then training is delivered afterwards, built just for those caught out. Reports seem automatically, showing exactly where safety efforts work and where they fail. Behind it web tools stay current, Work smoothly when loads get heavy. Testing hazards, lessons, and simple data views--all in one place.

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Keywords-- Phishing Threats, Basic Cybersecurity Awareness, Phishing Simulation, Security Training, Typical Email Security

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Digital health technologies have greatly strengthened modern healthcare by supporting continuous monitoring, early detection of illnesses, and timely interventions. Despite these advancements, many individuals still find it difficult to manage their health on a daily basis due to demanding routines, the rise of lifestyle-related diseases, and limited access to medical services--particularly in rural communities. Consequently, issues such as overlooked symptoms, missed medications, and slow emergency responses continue to persist. To address these challenges, this project introduces a browser-based Smart Health Assistant capable of delivering symptom-based guidance, medication reminders, doctor recommendations, and emergency alerts--without the need for users to install additional applications or devices. The primary aim is to offer a fast, accessible, and user-friendly digital solution that supports individuals in maintaining better everyday health.

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Smart Health Assistant, Symptom Analysis Medication Reminders, Emergency Alerts, Browser-Based Application.

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The utilization of composite materials has been exponential over the years and especially the demand for carbon fibre reinforced polymer composite is increasing rapidly because of their high performance. However, the recycling aspects of these materials proves to be challenging. The aim of our project is to recycle the fibre reinforced polymer composite in a cost-efficient method and to effectively use the recovered fibre in other applications. The project plan is to recover the fibres from two recycling processes - Pyrolysis and Solvolysis, and to pulverize the recovered fibres into fine powder. This powder is to be used as a microfiller in glass fibre reinforced polymer composite to enhance the mechanical properties. The final conclusion is to identify the best recycling method based on the analysis of the mechanical properties. Based on Tensile and Flexural tests, it was found that both the composite laminates with carbon fibre powder microfiller showed better structural properties than GFRP with plain epoxy. However, the carbon powder recovered from solvolysis process showed the best mechanical properties.

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Composite Recycling, Fibre Recovery, Microfiller, Composite Waste Management and Material Reuse.

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Among the canonical works of metaphysical poetry, Andrew Marvell's To His Coy Mistress has largely been read through the lens of its rhetorical brilliance and carpe diem urgency -- yet its dynamics of desire, silence, and emotional coercion remain critically underexplored. The seventeenth century witnessed the rise of metaphysical poetry, a literary movement characterized by intellectual wit, conceits, philosophical reflection, and emotional intensity, and it is within this cultural and literary context that Marvell's poem must be re-examined. This paper argues that To His Coy Mistress employs the language of romance to disguise and legitimize masculine authority and emotional coercion. Drawing on Kate Millett's theorization of patriarchal power in literature, Simone de Beauvoir's concept of woman as "the Other", and Laura Muvley's notion of the male gaze, this study demonstrates that the speaker systematically deploys fear, urgency, and seductive rhetoric as instruments of control over female sexuality consent, functions as a site of suppression within the poem's persuasive structure. This feminist analysis ultimately reveals that To His Coy Mistress reflects not only the literary culture of seventeenth-century England, but also the broader patriarchal attitudes toward women, desire, and bodily autonomy that defined the period. By re-reading this celebrated poem through a feminist lens, this paper challenges conventional admiration of its wit and invites a more critically engaged understanding of its gender politics.

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Feminism, Metaphysical Poetry, Andrew Marvell, Carpe Diem, Male Gaze, Gender, Coercion

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Paracetamol, Cyclobenzaprine, UV spectrophotometry, simultaneous estimation, method validation, pharmaceutical analysis

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Selective Laser Melting (SLM) has emerged as a key metal additive manufacturing process for producing complex, near-net-shape components with tailored properties for advanced manufacturing applications. Among aluminium alloys, AlSi10Mg is extensively used in SLM due to its excellent process ability, good castability, and favourable combination of strength, lightweight characteristics, and corrosion resistance, making it attractive for aerospace, automotive, and tooling industries. This review critically examines the influence of SLM processing from a manufacturing perspective, with emphasis on the interrelationships between process parameters, microstructure evolution, and resulting mechanical and tribological properties of additively manufactured AlSi10Mg alloy. The effects of laser power, scan speed, hatch spacing, layer thickness, and scan strategy on densification, defect formation, and microstructural features such as grain morphology and silicon distribution are discussed. Corresponding impacts on tensile strength, hardness, fatigue behavior, wear resistance, and friction characteristics are systematically reviewed. The role of post-processing routes, including heat treatment, hot isostatic pressing and surface finishing, in enhancing functional performance is also addressed. Key conclusions highlight that optimized SLM parameter windows and appropriate post-processing are essential to achieve balanced mechanical and tribological performance suitable for industrial deployment. Despite significant progress, gaps remain in standardized tribological testing, long-term fatigue behaviour, and scalable process optimization strategies. Addressing these challenges is crucial for the reliable and widespread manufacturing adoption of SLM-processed AlSi10Mg components.

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Selective Laser Melting; AlSi10Mg Alloy; Additive Manufacturing; Microstructure Evolution; Mechanical Properties; Tribological Performance; Process Optimization

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This study examines the public administration's contributions to combat socioeconomic disparities in Central Luzon. Using a Quantitative Descriptive Correlational Research Design, the study gathered data from respondents, composing of patients admitted in various provincial hospitals in Central Luzon. Findings revealed that age, sex, and health insurance are not significantly linked to the socioeconomic profile or health indicators contributing to healthcare disparities. In contrast, factors such as monthly income, education, occupation, housing type, and the number of household members are significantly associated with socioeconomic status and health indicators, leading to disparities in healthcare. The data showed that 100% of respondents identified high medical costs as the main barrier to healthcare access. Additionally, 81% reported a lack of transparency in healthcare programs, while 77% cited insufficient healthcare facilities. Shortages of doctors and nurses and a lack of accountability in programs were each noted by 64.3% of respondents. Furthermore, 58.7% mentioned the absence of health awareness programs, 55% pointed to unequal distribution of resources among barangays, and 53.3% reported poor quality of services. These figures highlight the multifaceted and widespread nature of healthcare challenges faced by the respondents. Lastly, healthcare in Central Luzon faces multiple interconnected challenges, including high medical costs, lack of transparency and accountability, inadequate and outdated facilities, shortages of doctors and nurses, insufficient health awareness programs, unequal distribution of resources, and poor service quality. These issues create major barriers to healthcare access and perpetuate socioeconomic disparities in the region. Addressing these problems requires not just more resources, but also strong, effective governance rooted in transparency, accountability, equity, and participation. By focusing on the needs of the most disadvantaged, encouraging cross-sector collaboration, and embracing innovation, public administration can help build a health system that provides quality, affordable care for all. Achieving health equity in Central Luzon ultimately depends on visionary and robust governance.

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Good governance, Healthcare, Socioeconomic Disparities, Central Luzon

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 Abstract

1857 ki kranti mein uttar Bihar ka yogdan karan prasar prabhav ek vivechan

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Creative Commons Attribution 4.0 and The Open Definition

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1857 ki kranti mein uttar Bihar ka yogdan karan prasar prabhav ek vivechan

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Creative Commons Attribution 4.0 and The Open Definition