Volume 12 | Issue 7 |

 Abstract

Cloud computing has revolutionized commercial operations by enhancing technology and blending a hybrid workstyle. After COVID-19, businesses may integrate AI and IoT, cloud and blockchain, manage cloud services effectively, and streamline competition without traditional IT infrastructure constraints. The former section of the article analyses the economic influence of cloud computing in business. It also enables the author to select the appropriate cloud solution depending on the size and specific needs of the business. By understanding the features and suitability of each cloud service model, businesses can make informed decisions that align with their operational goals, technical capabilities, and growth strategies. Cloud computing has transformed commercial operations by upgrading technology and incorporating a hybrid mode of work style. After COVID, organizations may combine AI and IoT, cloud and blockchain, effectively manage cloud services, and simplify competition without relying on traditional IT infrastructure. This examines the economic impact of cloud computing on business. It also enables the author to select the appropriate cloud solution based on the size and special needs of the business. Understanding the benefits and applicability of each cloud service model allows businesses to make sound choices regarding the characteristics and viability of each cloud service model based on their operational objectives, technical capabilities, and growth plans.

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 Keywords

Software as a Service (SaaS) solutions, ABCD technology, Platform as a Service (PaaS) solutions, pay-as-you-use model,Infrastructure as a Service (IaaS) solutions, cloud-based CRM, Continuous Integration and Continuous Deployment (CI/CD)

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This review synthesizes existing research on the tolerance of various lemon grass (Cymbopogon citratus) varieties to saline and sodic conditions, key environmental stresses that impact agricultural productivity. Through a comprehensive analysis, this paper examines the physiological and biochemical mechanisms that confer tolerance, the differential responses among common varieties, and the impact of saline and sodic stress on plant growth, yield, and essential oil quality. Methodologies ranging from traditional soil testing to advanced remote sensing are evaluated for their effectiveness in assessing stress responses. Additionally, adaptive strategies including genetic breeding, agronomic practices, and technological innovations are discussed, providing insights into mitigating the adverse effects of these soil conditions. The review highlights the importance of selecting appropriate varieties and implementing integrated management practices to enhance the sustainability of lemon grass cultivation in affected regions. Future research directions are proposed to further understand genetic tolerance mechanisms and develop resilient lemon grass varieties. This work contributes to the ongoing efforts to sustain agricultural productivity in saline and sodic environments, ensuring economic viability and supporting global food security.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Lemon grass, saline tolerance, sodic tolerance, Cymbopogon citratus, stress response, essential oil, agronomic practices, genetic breeding, remote sensing, soil management.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Insider threats present a significant cybersecurity challenge due to the legitimate access insiders have to an organization's systems and data, making detection and mitigation particularly complex. Traditional security measures often fail to identify these threats, resulting in considerable damage such as data breaches, intellectual property theft, financial losses, and reputational harm. This paper investigates the use of graph theory for detecting insider threat attacks by analysing the relationships and interactions among various organizational entities. By representing users, devices, and files as nodes, and interactions like access events and communications as edges, we utilize advanced graph-theoretical algorithms to identify anomalous patterns that indicate insider threats. Graph-based approaches offer several benefits, including the visualization of intricate interactions, detection of subtle anomalies, and integration of diverse data sources for a comprehensive organizational overview. We propose a comprehensive system leveraging graph-based analysis, encompassing data collection, graph construction, anomaly detection, and response mechanisms. The system's effectiveness is assessed using a dataset of simulated insider threat scenarios, showcasing its potential to enhance insider threat detection capabilities.

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 Keywords

Insider security

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The paper displays the formulation and evaluation of anti-acne patches made with chitosan, gelatin, tea tree oil, and salicylic acid as active ingredients. Chitosan is dissolved in 1% acetic acid. Glutaraldehyde acts as a crosslinking agent. Both tea tree oil and salicylic acid have antibacterial and anti-acne properties. Evaluation tests such as moisture content, uniformity weight, pH, skin irritancy, etc. are tested. The antibacterial assay was measured using the spread plate method. A zone of inhibition of 26mm was observed, which shows great inhibition activity. PH was found to be 5.3, which is safe to use in the skin. The trials F1, F2, F3 has performed. From this, F2 is found to be more specific.

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 Keywords

acne vulgaris, anti-acne patches, topical application

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Creative Commons Attribution 4.0 and The Open Definition

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Tomato plants are a vital crop worldwide, yet they are susceptible to various leaf diseases that can significantly impact yield and quality. Early and accurate identification of these diseases is crucial for effective management and prevention. This study presents a novel approach to enhanced tomato leaf disease identification utilizing Convolutional Neural Networks (CNN) and advanced image analysis techniques. By employing CNNs, the approach leverages deep learning to analyze and classify images of tomato leaves, distinguishing between healthy and diseased conditions with high precision. Advanced image processing methods are integrated to improve the accuracy of the detection system, addressing the challenges posed by varying leaf textures, disease symptoms, and environmental factors. The proposed method is evaluated against existing techniques, demonstrating superior performance in terms of accuracy, robustness, and efficiency. This approach not only enhances the ability to diagnose tomato leaf diseases but also contributes to more effective crop management practices, ultimately supporting agricultural productivity and sustainability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Tomato leaf diseases, Convolutional Neural Networks, image analysis, deep learning, disease identification, agricultural technology.

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract Child labour in domestic work represents a significant barrier to achieving the Sustainable Development Goals (SDGs), particularly those focused on poverty reduction (Goal 1) and promoting decent work (Goal 8). This paper analyzes the connection between poverty and child labour in domestic work, exploring its implications for sustainable development. Using a mixed-methods approach, the study integrates quantitative data from global organizations with qualitative insights from case studies in high-incidence regions. Findings reveal a strong correlation between low household income and child labour, with economically disadvantaged families often relying on their children's earnings for survival. The data indicates that children in domestic work face severe exploitation, including long hours and hazardous conditions, which impede their educational attainment and well-being. Approximately 60% of households earning less than 5000 per month reported child labour in domestic settings. The implications of these findings underscore the challenge of breaking the cycle of poverty that perpetuates child labour. Policy recommendations include enhancing social protection systems, improving educational access, and enforcing child labour laws more effectively. Addressing these issues is crucial for promoting equitable growth and achieving the SDGs. This research highlights the need for comprehensive strategies that integrate economic support with robust protections for children, aiming to eradicate child labour and foster sustainable development. Keywords: Child labour, domestic work, poverty, Sustainable Development Goals, social protection, education, policy intervention

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Keywords: Child labour, domestic work, poverty, Sustainable Development Goals, social protection, education, policy intervention

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Creative Commons Attribution 4.0 and The Open Definition

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This research paper aims to identify the key challenges faced by rural women in securing and maintaining land rights and to explore the impact of insecure land rights on their livelihoods, economic empowerment, and overall well-being. The paper begins by providing an overview of the significance of women's land rights in rural areas, emphasizing the importance of land ownership for rural women's economic stability, social status, and agency. Through a comprehensive literature review and qualitative research methods, the study examines the multifaceted challenges that rural women encounter in their pursuit of land rights. These challenges include gender-based discrimination, limited awareness of legal provisions, cultural norms and biases, lack of access to resources and information, and weak implementation of existing laws and policies. Furthermore, the paper investigates the repercussions of insecure land rights on rural women's livelihoods, economic empowerment, and overall well-being. It explores the impact on their ability to access credit and financial services, engage in productive agricultural activities, make long-term investments, and exercise decision-making power within their households and communities. The study also examines the interplay between land rights and other dimensions of well-being, such as education, health, and social inclusion. Drawing from the findings, the paper highlights the need for targeted interventions and policy reforms to address the identified challenges and secure women's land rights in rural areas. It emphasizes the importance of raising awareness, strengthening legal frameworks, ensuring women's participation in decision-making processes, and providing support services and resources to enhance rural women's capacity to assert their land rights. In conclusion, this research paper sheds light on the challenges faced by rural women in securing and maintaining land rights and underscores the significance of addressing these challenges to promote gender equality, empower rural women, and foster sustainable development in rural communities.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Women's Land Rights, Rural, Challenges, Insecure Land Rights, Livelihoods, Economic Empowerment

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Creative Commons Attribution 4.0 and The Open Definition

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Ice cream is a nutritious food because it contains ingredients responsible for supplying energy to the body. Soy has a high nutritional value and functional properties which make it to be an alternative ingredient to replace cow's milk. The purpose of this paper was to formulate an ice cream with soy milk and cow milk & banana powder ,is also used and submitted to a sensory evaluation. Three formulations of ice cream were prepared: one soy-based (containg soy milk 70% , cow milk 30%) and this is control sample, the other with soy-based probiotic ice cream (containg soy milk 70% , cow milk 30%) and last one is sugar free (containing 100 % cows milk only) & for the sugar replacement here we added dextrose,fructo-oligosaccharide & oligofructose) & for all the three types of ice creams here we used ripened banana powder as it is a good source of dietary fibre,which promotes the healthy digestion, supports weight management. All these ice creams were submitted to a sensory evaluation in order to evaluate the appearance, flavor and texture attributes, mouthfeel, sweetness and overall acceptance ,for this examination it was used the hedonic scale of five points. With regard to colour & appearance control ice cream obtained rating of 3.8 remaining between the terms "Good" & "Very good" , while the probiotic with sugar ice cream got 3.71 remaining between the terms "Good" & "Very good" and where as the probiotic sugar free ice cream obtained 4.0 remaining between the terms "Good" & "Very good". For the attribute flavour & taste control ice cream obtained rating of 4.1 remaining between the terms "Excellent" & "Very good" ,while the probiotic with sugar ice cream also got the result of 4.01 whose term is as same the control sample and where as the probiotic sugar free ice cream obtained 3.2 remaining between the terms "Good" & "Very good". For the attribute mouthfeel , control ice cream obtained rating of 4.16 which corresponds between the terms "Excellent" & "Very good" , while the probiotic with sugar ice cream got 3.6 remaining between the terms "Good" & "Very good" and where as the probiotic sugar free ice cream obtained 3.4 remaining between the terms "Good" & "Very good". For the attribute sweetness control ice cream obtained rating of 4.0 which corresponds to the terms between "Very good" & "Excellent" , while the probiotic with sugar ice cream got 3.93 remaining between the terms "Good" & "Very good" , where as the probiotic sugar free ice cream obtained 3.0 which corresponds to the "good". The sensory parameters evaluated showed that the control ice cream i,e soy-based dietary ice cream had a good acceptance compared to that of the probiotic with sugar soy based dietary ice cream & probiotic sugar free ice cream.

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 Keywords

Ice cream, soy milk, probiotic, sugar free sensory acceptance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The purpose of this exploration paper is to examine the effect of AI on cybersecurity strategies by assaying told designs, current approaches, and over- and- coming conceivable issues, driving progressive viability and versatility against cyber troubles. Indian enterprises defy multitudinous hurdles when using AI- AI-grounded cybersecurity results. The fast proliferation of cyber pitfalls, similar to ransomware, phishing, and malware attacks, has made cyber security a crucial issue in India, which ranks 11th encyclopedically in terms of original cyberattacks. still, a lack of specialized capability, moxie, and collaboration among other countries' authorities is a significant hedge to effectively suppressing these pitfalls. likewise, resolvable AI(XAI) is critical in cybersecurity since standard AI models constantly warrant translucency in decision-making processes, making it delicate to trace the logic behind specific acts. likewise, carrying a sufficient library of approved images for training AI models to sludge unequivocal content online highlights the difficulties in using AI interfaces for cybersecurity purposes. Addressing these challenges through enhanced specialized capabilities, skill development, and XAI perpetration is essential for Indian associations to bolster their cybersecurity defenses effectively.

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 Keywords

Artificial Intelligence, Threat Detection, Cybersecurity, Machine Learning, Automated Systems

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition