Volume 4 | Issue 4 |

 Abstract

With the ecological imbalance in the nature due to exploitation of natural sand from rivers, there is much need to utilize the industrial wastes in concrete as a part to replace the natural sand deficiency and also as to develop sustainable environment in construction industry. High strength and durability properties being the key components of High-performance concrete can be produced by using some admixtures like fly ash and silica fume. In the present study, fly ash and silica fume are taken as steady replacement of 15% and 10% respectively for cement. Bottom ash is introduced in place of sand at the variations of 0%, 10%, 20%, 30%, 40% and 50%. Glass fibers of 1% are added as extra ingredient as to improve some properties. The properties of strength, drying shrinkage and water absorption are studied for the M60 grade concrete designation. The results showed that the concrete with 40% bottom ash had the optimum strength.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bottom ash, drying shrinkage, fly ash, silica fume, strength

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the upcoming years, cloud computing, a new and developing technology, is anticipated to drastically alter the IT industry. Leading enterprise companies like Amazon, Microsoft, and Google now offer a wide range of cloud services in the form of specialised, dependable, and reasonably priced web applications. Numerous people and organisations from a variety of fields, including business, education, and health, are drawn to these services. Our goal in this paper is to familiarise cloud users with the most well-known Cloud Service Providers (CSPs). We additionally present a comparative analysis of these CSPs based on various service-related criteria. Before moving their business, people and organisations can use the study presented in this paper to make important decisions about the costs and advantages of cloud technology.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cloud computing, Cloud Service Providers, SaaS, PaaS, IaaS

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The last few years have seen artificial intelligence systems transform education at an unprecedented rate. Such systems have far-reaching implications-they bring opportunities and challenges-and their development must adhere to ethical principles that make learning contexts inclusive, equitable, and effective. This conceptual review offers a discussion on the possibility of Bayesian networks as a framework for modelling and addressing complex interconnectivity between ethical considerations, societal impacts, and technical feasibility within AI-driven educational systems. Bayesian networks allow stakeholders to see dependencies and trade-offs that lie underneath informed decision-making and responsible design of AI. It therefore focuses on empowering diverse groups, including women, fully to take an active role in lobbying for ethical development of AI, discussing salient topics in attention to issues like bias, privacy, accountability, and accessibility. This paper gives a theoretical footing from which it is possible to integrate ethical decision-making into AI system design and underlines the need for multidisciplinary education. The study is going to be a roadmap for researchers, educators, and policymakers interested in the development of ethical AI for education.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bayesian, Ethics, AI, Education, Empowerment, Equity, Feasibility, Framework, Inclusion, Policy.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nymithikinaam kaamyaanaam cha saamidheninaam Vidhana Vivaranam

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Nymithikinaam kaamyaanaam cha saamidheninaam Vidhana Vivaranam

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Open Government Data initiatives look to promote transparency and accountability of public sectors besides enhancing citizen engagement through free availability public sector data. However, through the integration of cloud computing technologies, the effective use and scalability of OGD initiatives have been very much enhanced. This review paper examines trends and patterns in the adoption of cloud computing for open government data platforms, cognizant of international case studies, technological and policy frameworks that support these efforts, and challenges related to security of data, privacy, interoperability, and governance. The review highlights the advantages of cloud infrastructure, which include scalability, real-time access, cost efficiency, and seamless data sharing, as reasons that have made OGD more accessible to developers, researchers, and citizens. Other emerging trends of OGD include hybrid cloud models, the role of artificial intelligence in processing OGD, and the open data platforms of smart cities. The future discussion will cover research aspects in overcoming technical and policy challenges to make cloud-based OGD solutions more effective

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Open Government Data, Cloud Computing, Transparency, Accountability, Data Security, Hybrid Cloud, Smart Cities, Policy Frameworks, Scalability, Data Governance

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the role of mass media in the success of the Biogas Programme in Karnataka, which focuses on sustainable energy adoption and rural development. The paper explores how various forms of media, such as television, radio, newspapers, and online platforms, have contributed to promoting and educating people about biogas technology. By sharing knowledge, raising awareness, and educating rural communities, mass media have encouraged participation and adoption. The research combines qualitative media content analysis and quantitative surveys of Biogas Programme beneficiaries, revealing that mass media have positively influenced perceptions and attitudes towards biogas, leading to increased acceptance and implementation. Challenges, such as language barriers and access limitations, are also identified. The study's implications extend globally to other sustainable development initiatives, highlighting the vital role of mass media in their success. Ultimately, the Biogas Programme's achievement is linked to effective communication through mass media, emphasizing collaboration between governments, media, and local communities for successful sustainable development.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Biogas Programme. Karnataka. Mass media. Success. Sustainable energy. Rural development. Communication. Awareness dissemination. Information sharing. Energy adoption. Waste management. Environmental conservation. Television. Radio. Newspapers. Online platforms.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Content marketing has become an increasingly crucial strategy for businesses across the board in a bid to engage their customers and foster brand loyalty. However, this exponential increase in online content has reached a point of saturation, whereby consumers are overwhelmed by the deluge of information at their disposal. This paper reviews challenges and opportunities in connection with content marketing in this age of content saturation. It highlights the role of big data in coming up with efficient content strategies that help block out the noise and get through to target audiences. Big data analytics can be utilized in analyzing consumer behavior, preferences, and trends to generate highly personalized and relevant content. The paper further reviews some big data tools and techniques for use in optimizing content creation, distribution, and performance measurement. Furthermore, it identifies and points out the successful case studies of firms that did an exemplary job in harnessing big data to improve their content marketing efforts. Indeed, the research concludes that infusing big data in content strategy formulation is not just useful; it is a requirement to maintain competitive advantage within the jammed digital marketplace.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Content marketing, content saturation, big data, consumer behavior, personalized content, big data analytics, content strategy, digital marketing, content creation, data-driven marketing.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

AI and robotics have had good integration into disaster response and recovery over the past two years. The research paper focuses on the advancements of AI-powered robots in handling a wide array of disaster scenarios, from natural disasters like earthquakes, floods, and hurricanes to artificial crises involving industrial accidents and terrorist attacks. It reviews state-of-the-art technologies that allow robots to move through treacherous landscapes, perform search and rescue, transport medicine, and participate in restoring infrastructure. They include machine learning algorithms for real-time data processing, autonomous navigation, human-robot interaction, and multi-robot coordination. The paper also explains some challenges and limitations of AI-robotics systems, including ethics issues, logistics, and standardized protocols for deployment. We discuss how case studies and experimental results may point to the potential for AI-powered robots in transforming disaster response and recovery into life-saving and economically remedial activities.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI-powered robots, disaster response, disaster recovery, search and rescue, autonomous navigation, machine learning, human-robot interaction, multi-robot coordination, ethical considerations, deployment logistics.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the intricate historical fabric of medieval Assam and the crucial influence Persian sources had in influencing the history of medieval period. The article centers on how Persian documents offer distinctive perspectives on the political, cultural, and social aspects of Assam in the Middle Ages, as historical strands intertwine throughout history. Through meticulous analysis, this study aims to shed light on lesser-known facets of Assamese history, revealing the nuanced ways in which Persian influence intersected with and enriched indigenous developments in the region. By exploring Persian sources, the study uncovers how Persian literary, administrative, and historical texts offer unique insights that complement and enhance the indigenous records, leading to a more comprehensive understanding of the medieval Assam. By bringing these obscured aspects to light, the research not only enriches our understanding of Assam's past but also highlights the broader implications of cross-cultural exchanges in the shaping of historical narratives.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Assam, Persian Documents, Medieval Period, Political Dynamics

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Stock market prediction is one of the toughest tasks in finance and attracts much attention from academia and industry due to huge economic potential. Traditional econometric models dominated the field until recent developments in machine learning introduced new methodologies that capture complex market dynamics. Of these, the RF algorithm has excelled in large data volumes, the ability to model nonlinear relations, and ranking feature variable importance. The paper presents a review on the application of Random Forests in stock market prediction, covering the theoretical foundations of Random Forest, advantages over traditional methods, reviews of empirical studies proving their effectiveness, and challenges and future research directions. It synthesizes how recent literature can help researchers and practitioners use random forests to guide and improve the accuracy of predictions and robustness associated with stock market analysis.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Stock market prediction, random forest algorithm, machine learning, finance, predictive modeling

  License

Creative Commons Attribution 4.0 and The Open Definition