Volume 12 | Issue 7 |

 Abstract

The rapid growth of big data analytics has transformed various sectors such as healthcare, finance, and marketing by enhancing decision-making, operational efficiency, and service personalization. However, this rapid growth also raises significant ethical issues that need to be addressed to ensure responsible usage. This paper examines three primary ethical concerns: economic disparity, market manipulation, and privacy invasion. The paper explores how big data can exacerbate economic inequality by reinforcing existing biases and providing disproportionate advantages to those with access to extensive data resources. It examines the implications for marginalized communities and the potential for data-driven policies to widen the economic gap. The analysis highlights how big data facilitates manipulative market practices, such as personalized pricing and targeted advertising, which can exploit consumer behaviour and undermine fair market competition. It investigates the ethical ramifications of these practices and their impact on consumer trust and market integrity. The paper addresses the pervasive issue of privacy invasion, discussing how extensive data collection and analysis can lead to significant breaches of personal privacy. It considers the balance between data utility and individual rights, evaluating the effectiveness of current data protection measures. By applying ethical theories such as utilitarianism, deontology, and virtue ethics, the paper provides a nuanced understanding of these challenges and underscores the need for robust ethical frameworks. The paper also reviews current regulations like GDPR and CCPA, highlighting regulatory gaps and proposing best practices, and policy recommendations to mitigate these challenges. Ultimately, this paper aims to emphasize the ethical concerns in big data practices and suggest strategies for fostering a more equitable and transparent data-driven economy.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ethical, concerns, big data, artificial intelligence, machine learning, economic disparity, market manipulation, analytics, General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA)

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Mathematical models are used in applied mathematics in conjunction with engineering disciplines (computer science, electrical engineering) and natural sciences (physics, biology, earth science, and chemistry). Using mathematical modeling is a crucial for comprehending and resolving complex real-world issues. It entails utilizing mathematical terminology and ideas to theoretically model systems in order to study, forecast, and interpret their behavior. Mathematical modeling has many uses, ranging from managing pandemics to space exploration, which highlights its vital role in knowledge advancement and solving pressing global issues.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Modeling, Analytics, Real-world problems, Prediction of Behavior

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents an accessible overview of pattern searching algorithms, which are vital tools in computer science for finding specific patterns within data. It break down the complexities of these algorithms into understandable concepts suitable for readers unfamiliar with advanced technical jargon. By employing straightforward language and examples, this paper aim to provide a clear understanding of how pattern searching algorithms function and their significance in various applications.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Rabin karp,suffix trees,pattern mining,Deep learning

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

: Heart disease is a leading cause of mortality worldwide, necessitating effective and timely diagnosis. This study presents a novel approach to predicting heart disease using advanced machine learning techniques and data-driven insights. The system is designed for the identification of heart disease, leveraging the performance of various machine learning classifiers on selected features. Predictive models including Decision Tree (DT), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) are employed to identify heart disease. The effectiveness of these classifiers is evaluated to determine the most accurate method for heart disease detection. Additionally, the system provides patients with information about the nearest doctor, facilitating rapid access to medical diagnosis and treatment. This integrated approach aims to enhance early detection and intervention for heart disease, ultimately improving patient outcomes and reducing the burden on healthcare systems.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Heart disease, machine learning, prediction, identification, Decision Tree, Naive Bayes, Random Forest, Support Vector Machine, data-driven insights, early detection, medical diagnosis, healthcare systems.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The tremendous issues of handling the large flood of data have been brought about by the cloud computing field's fast development. By 2020, 247 EB will be achieved by data analytics and IoT-based applications, according to Cisco's Global Cloud Index. Load Managing strategies are critical in tackling cloud environments' data overflow. The study promotes Round Robin Load Managing and highlights how well it manages data overflow. Based on set policies, load managing techniques such IP hash, weighted round-robin, least connections, and round-robin allow the effective allocation of incoming traffic across active targets. One important remedy that is emphasized is cloud load management, which uses software-based techniques to keep an eye on the target's health inside a cluster. In order to avoid data loss and service outages, it foresees and manages unexpected increases in traffic, rerouting it to servers that aren't as busy. The book offers explanations on how the load distribution techniques are used, and a Pythonexample of the Round Robin algorithm.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cloud computing , Load Managing, Round-robin , Hardware-based load managing, Software-based Load Managing .

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Agenda 2030 for Sustainable Development, which was overwhelmingly adopted in 2015 by all UN Member States, presents fresh opportunities and entry points for closing the gap between human rights and development. It consists of 231 distinct indicators, 169 targets, and 17 Sustainable Development Goals (SDGs). Sustainable development acts as the general foundation for guiding both national and international development initiatives. To make the world a sustainable place to live, the United Nations launched the Sustainable Development Goals at the General Assembly in 2015. India was a key contributor to the creation of the 2030 Sustainable Development Agenda of the United Nations, and India's development is crucial to global progress toward the SDGs.In 2018, NITI Aayog took a step forward by releasing the SDG India Index. India has also embraced the SDGs as a means of advancing development objectives in several economic sectors. As part of the ongoing research, an attempt has been made to analyse all the 16 SDGs, National Indicators developed by NITI Aayog, and various initiatives the Indian government has launched to reform and improve the development paradigm, the research paper also focuses on Himachal Pradesh progress toward Agenda 2030 and compare the performance of Himachal Pradesh and India concerning various indicators of Sustainable Development Goals.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

SDGs, Agenda 2030, National Indicators, NITI Aayog.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key Words: Metacognition, Marital Adjustment, MCQ, DAS

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the perceptions of secondary school teachers towards the application of computers in the teaching-learning process. The objectives were to classify teachers' perceptions, analyze these perceptions in specific areas (Impact of IT, Usefulness for Students, Productivity for Teaching, Teacher's Interest and Acceptance, and Support and Resources for Implementation), and investigate the influence of variables such as gender, locality, and teaching experience on these perceptions. A random sample of 100 secondary school teachers from West Godavari District was selected, and data were collected using a self-constructed questionnaire with 40 items across five components. The findings revealed that 21% of teachers have high perceptions, 55% have average perceptions, and 24% have low perceptions regarding the use of computers in the teaching-learning process. The availability of support and resources was perceived as the most significant factor, followed by the usefulness for students, the impact of IT, teachers' interest and acceptance, and productivity for teaching. Significant differences were observed in perceptions based on gender, with male teachers showing more positive attitudes compared to female teachers. Urban teachers exhibited more favorable perceptions than rural teachers. Additionally, teachers with more than 20 years of experience had significantly higher perceptions compared to those with less experience, although no significant difference was found between teachers with below 10 years and those with 11 to 20 years of experience. This study highlights the need for targeted support and professional development to bridge the gaps in perceptions and enhance the integration of computers in education, with a particular focus on gender, locality, and experience-based disparities.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Perceptions, Secondary school teachers, Computers, gender, locality, and teaching experience

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract Food is a fundamental aspect of human life and culture. It provides nourishment, sustenance, and pleasure to people around the world. Food is deeply intertwined with culture. Different regions and communities have unique culinary traditions, ingredients, and preparation methods that reflect their history, values, and identity. Food is not only a vital aspect of human life but also a significant commercial item in a complex and multifaceted industry. The commercialisation of food involves a wide range of activities, from production and processing to distribution and marketing, and consumer preferences, regulatory standards, and global trade dynamics influence it. Urban food culture is a dynamic and ever-evolving aspect of city life, reflecting the diverse culinary traditions, social interactions, and economic activities of urban areas. In recent years, food wagon eateries have gained prominence in many cities worldwide, contributing significantly to the urban food landscape. This study comes under the interdisciplinary field of Urban Studies, and this paper investigates the role of food wagon eateries in Thiruvananthapuram, shaping urban food culture, focusing on their impact on culinary diversity, social dynamics, economic development, and preserving culinary traditions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Food wagon, urban food culture, nightlife, lifestyle.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Bharat mein mahilaon ki stithi aur mahila sanrakshan vidhiyon ka vikas

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bharat mein mahilaon ki stithi aur mahila sanrakshan vidhiyon ka vikas

  License

Creative Commons Attribution 4.0 and The Open Definition