Volume 14 | Issue 5 |

 Abstract

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

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

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 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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 Abstract

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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 Abstract

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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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 Keywords

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

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 Abstract

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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 Keywords

Good governance, Healthcare, Socioeconomic Disparities, Central Luzon

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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

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

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With the exponential growth of social media platforms such as Twitter, Facebook, Instagram, and Reddit, vast amounts of user-generated content are produced every second. Sentiment analysis, also known as opinion mining, is the computational study of people's opinions, sentiments, attitudes, and emotions expressed in text. This paper presents a comprehensive review of sentiment analysis techniques applied to social media data, encompassing lexicon-based methods, machine learning algorithms, and state-of-the-art deep learning architectures. We examine the unique challenges posed by social media text -- including informal language, sarcasm, emojis, code-mixing, and data imbalance -- and survey benchmark datasets commonly used in the field. Furthermore, we explore real-world applications spanning business intelligence, political analysis, public health monitoring, and disaster management. Experimental comparisons of leading models are discussed, and open research directions are identified. Our study demonstrates that transformer-based models such as BERT and RoBERTa currently achieve the highest performance, while hybrid approaches combining linguistic knowledge with neural networks show promising potential.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sentiment Analysis, Opinion Mining, Social Media, Natural Language Processing, Machine Learning, Deep Learning, BERT, Twitter, Text Classification.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The lightning-induced overvoltage phenomenon poses a significant threat to insulation stress and failures in high voltage substations. Although much work has been done to understand the mechanisms of shielding failures (SF) and back flashover (BFO), the cumulative effect of both on overvoltage in substations, especially in the presence of lightning electromagnetic pulse (LEMP), has not been adequately explored in the past. This paper attempts to provide a comprehensive review on the subject by critically examining the phenomenon of lightning induced overvoltage in the context of lightning sources, transmission line behavior, and substation transients. A comparative evaluation of widely used lightning current models and attachment models (Electro geometric Model and Leader Progression Model) is conducted, highlighting their impact on predicted overvoltage levels. The analysis shows that conventional electromagnetic transient (EMT) approaches may significantly underestimate overvoltage due to neglect of LEMP effects, especially in BFO scenarios. Furthermore, the roles of multi-stroke lightning, grounding nonlinearity, and travelling wave interactions are critically examined. The review identifies key limitations in existing modeling approaches, including single-stroke assumptions and lack of integrated system-level analysis. Based on these findings, future research directions are proposed toward high-fidelity, multi-physics modeling frameworks for improved insulation coordination and lightning performance assessment in modern power systems.

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 Keywords

Lightning overvoltage shielding failure CIGRE Current model Heidler Current model back flashover substations insulation coordination Electro-geometric model Leader Progression Model LEMP.

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