Volume 13 | Issue 6 |

 Abstract

Urban flooding was considered a concern of municipal and local governance only till the 1990s,but currently it draws the attention of disaster and environmental scientists. Urban floods have attained the status of disaster due to high vulnerability and risks. It leads to extreme fatalities and enormous economical losses in every country. Especially in developing countries like India, where population density is high and has enormous population growth during the last few decades due to high migration in urban areas and have a lot of issues about uncontrolled and inappropriate development .Flood is a phenomenon occurring from time to time in all rivers. An attempt has been made in this project to study the rainfall in urban areas & the effects area and solution of flash floods.

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 Keywords

Frequency, Extreme rainfall depth, Depth area duration, Probable maximum temperature, Rate of infiltration, Infiltration Capacity, initial infiltration capacity, limiting constant value of infiltration

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Creative Commons Attribution 4.0 and The Open Definition

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Deep learning is one of the most prominent areas of machine learning that relies entirely on artificial neural networks. Since neural networks are designed to replicate the functioning of the human brain, deep learning may also be thought of as a form of brain mimicking. Owing to its capacity for data-driven learning, deep learning (DL) technology--which has its roots in artificial neural networks (ANNs)--has gained significant traction in the computer community and finds extensive use across a wide range of industries, including the field of cybersecurity, health care, visual identification, and text analytics. However, it is not easy to develop a suitable deep learning model because of its dynamic nature of data. In many different fields, deep learning approaches have become successful tools for resolving challenging issues.This paper offers a systematic and thorough analysis of deep learning approaches, which includes a nomenclature that takes into account different kinds of real-world challenges, such as supervised and unsupervised ones. Moreover, this article also includes a deep study of the core deep learning approaches, with particular emphasis on generative adversarial networks (GANs), long short-term memory networks (LSTMs), recurrent neural networks (RNNs), and convolutional neural networks (CNNs). Deep learning methods still have difficulties with interpretability, resilience to adversarial attacks, and scalability to big datasets, despite their amazing success. More explainable models, adversarial training for increased robustness, and effective training methods on large-scale datasets are some of the areas of future research. To gain a competitive edge in the future, organisations aiming to utilise artificial intelligence must comprehend and effectively utilise deep learning methodologies.

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 Keywords

Machine Learning, Deep learning, SVM, KNN

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Creative Commons Attribution 4.0 and The Open Definition

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The exponential growth of Online Social Media (OSM) platforms has provided users with dynamic means of communication, content sharing, and interaction. However, this growth has also attracted malicious entities that exploit these platforms for spamming, spreading misinformation, and executing fraudulent activities. Traditional content-based and user-behavioral spam detection techniques often fall short in detecting sophisticated spam patterns. In response, network-based approaches have gained significant traction by leveraging the structural and relational properties of social networks. This comprehensive review explores the spectrum of network-centric methodologies used in spam detection, including graph-based models, community detection algorithms, propagation patterns, and trust networks. The paper categorizes and analyzes the state-of-the-art techniques, evaluates their strengths and limitations, and highlights emerging trends in network science applied to OSM spam detection. Furthermore, it discusses real-world datasets, performance metrics, and the integration of hybrid frameworks combining machine learning with network-based insights. This review serves as a valuable resource for researchers and practitioners aiming to develop robust and scalable spam detection systems in the dynamic landscape of online social platforms.

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 Keywords

Online Social Media (OSM), Spam Detection, Network-Based Approaches, Graph Theory, Community Detection, Propagation Modeling, Trust Networks, Hybrid Frameworks, Machine Learning, Social Network Analysis

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Abstract: Makoto Shinkai is a Japanese writer, animator and director who has produced several renowned work of animation. Shinkai's films are known for its blend between reality and fantasy elements. He often incorporates fictional elements with reality to add layers of intrigue and complexity to the narrative. The adaptations produced by Shinkai have often left the audience speechless and star gazed. The objective of this paper is to study the works of Makoto Shinkai through the lens of post modernism, analyze the technique of adaptation to compare how it has evolved over the years and how his works blends with the era of post modernism. This work was analyzed from the perspective of use of history, intertextuality, pastiche, subversion of facts of information and open endedness. This study will also compare the works of Makoto Shinkai to other contemporaries to see how his style of modern adaptation sets him apart from other animators and directors. Lastly the study will follow a qualitative approach to scrutinize Shinkai's work based on post modern elements.

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 Keywords

Keywords: Post Modern, Fragmentation, Magic Realism, Hybridity, Pastiche.

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The construction industry plays a vital role globally, with rapid development leading to an accelerated consumption of naturally available construction materials. Simultaneously, vast quantities of waste are generated each year, much of which is non-recyclable. Even when recycling is possible, the process often demands substantial energy and contributes to environmental pollution. Additionally, the accumulation and disposal of such waste, particularly in suburban areas, pose significant ecological threats. Incorporating waste materials into concrete production offers a sustainable solution--reducing waste and potentially enhancing the properties of concrete. This project involves an experimental investigation aimed at evaluating the compressive strength, flexural strength, and split tensile strength of M20 grade concrete when cement, fine aggregates, and coarse aggregates are individually replaced with fly ash, steel slag, and recycled aggregates at varying proportions (10%, 20%, and 30%). The results indicate that such replacements can be made up to the mentioned percentages without compromising the compressive strength of the concrete. Furthermore, after identifying the optimal replacement percentage for each material individually, a combined replacement is carried out to assess the overall performance and compressive strength of concrete incorporating all three materials simultaneously.

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Compressive Strength, Flexural Strength, Split Strength, fly ash, steel slag, recycled aggregates.

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Pumpkin (Cucurbita spp.) is an important vegetable crop cultivated across diverse agro-climatic regions for its nutritional, economic, and cultural value. This review outlines the current production and management practices along with emerging trends shaping the future of pumpkin farming. Conventional practices include careful site selection, land preparation, use of high-yielding and disease-resistant varieties, and balanced nutrient application guided by soil testing. Efficient irrigation management, integrated pest and disease control strategies, and effective pollination methods also play key roles in ensuring optimum yield and fruit quality. Post-harvest handling, including proper curing and storage, further contributes to marketability and shelf life. In recent years, innovative and sustainable approaches have begun to influence pumpkin cultivation. The adoption of organic farming, use of bio-fertilizers and bio-pesticides, and the development of improved hybrid varieties are enhancing crop performance while reducing environmental impact. Precision farming tools, such as soil sensors and GPS-guided irrigation systems, are improving input efficiency. Additionally, climate-resilient practices and smart irrigation technologies are becoming essential in adapting to unpredictable weather patterns. Together, these emerging trends present new opportunities to improve productivity, sustainability, and profitability in pumpkin production. This paper highlights both existing methods and future directions to support informed decision-making in the cultivation of pumpkins.

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Pumpkin production and management: current practices and emerging trends.

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Creative Commons Attribution 4.0 and The Open Definition

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India's digital revolution has transformed WhatsApp into a potent medium for political communication, particularly in its linguistically diverse southern states. This paper investigates the nature, spread, and impact of political misinformation disseminated via WhatsApp during the 2019 Lok Sabha and 2023 Karnataka Assembly elections. Using qualitative content analysis on a curated dataset of 250 fake or misleading messages in Tamil, Telugu, and Kannada, this study unpacks how misinformation campaigns are linguistically localized, emotionally charged, and designed to polarize. We also explore voter perception and the psychological architecture of misinformation acceptance in rural South Indian contexts. The study concludes with implications for media literacy, regulatory frameworks, and the future of democratic engagement in a digital age.

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 Keywords

misinformation, WhatsApp, elections, South India, digital democracy, fake news, political polarization

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT Cancer is a global problem. It is becoming more a more challenging problem in both developed and developing countries .Cancer is the second leading cause of death. This may be due to increasing number of carcinogens, lack of skilled diagnosis and more people seeking medical care .As the cancer is a malignant disease, it attracted ten public fear and concerns. Childhood cancer is a physically and cognitively debilitating disease, leading to short-term fatal consequences or long-term adverse effects of prolonged illness and treatment. According to the recent NCRP report based on data from hospital-based cancer registries (HBCRs'), Childhood cancers (0-14 years of age) comprise 4% of all reported cancers in India. The proportion of children affected may be higher owing to "missed cases" due to low coverage, lack of awareness, delayed diagnosis and a fledgling electronic referral system. Statement of the problem "Effectiveness of planned teaching programme on knowledge regarding selected childhood malignancy among mothers of children under 10 years in a rural area of Palakkad District." Objectives of the study ? To assess the pre test knowledge regarding selected childhood malignancy among mothers of children under 10 years. ? To assess the post test knowledge regarding selected childhood malignancy among mothers of children under 10 years. ? To evaluate the effectiveness of planned teaching programme regarding selected childhood malignancy among mothers of children under 10 years. ? To determine the association between pretest knowledge with their selected demographic variables. Method The design used in this study is Pre-experimental one group pretest posttest design .Descriptive study conducted by administration of structured knowledge questionnaire to assess the knowledge level of mothers of children under 10 years regarding selected childhood malignancy.Total 30 mothers were selected by non probabilityconvenient sampling. Study conducted among mothers of children under 10 years in Vaniyamkulam, Ottapalam, Palakkad District. The collected data was analyzed by using descriptive and inferential statistics. Result The knowledge score of mothers regarding childhood malignancy was low. The mean pretest knowledge score was 8.9 out of 20. The mean knowledge score percentage was only 44.9%. Data shows that highest percentage (40%) of the mothers had satisfactory knowledge regarding Childhood malignancy. 16.7% of mothers had good knowledge and 36.7% had poor knowledge. Only 6.6% had excellent knowledge about Childhood malignancy.The mean posttest knowledge score obtained is 15 The mean knowledge score percentage was 75%. The data shows that the highest percentage 60% of mothers have good knowledge, 33.3% having excellent knowledge and 6.7% having satisfactory knowledge regarding childhood malignancy. The paired 't' test was done to find out the difference between the mean pretest and post-test knowledge score. Thecalculated't' value(5.99) was found to be significant This reveals that on the whole the knowledge level of Mothersregardingchildhood malignancy was low. All chi-square values were lesser than that of the tabulated values. The findings indicated that there is no significant association between the knowledge score and selected demographic variables Interpretation and Conclusion The knowledge score of Mothers regarding childhood malignancy score was low. The findings of the study would help the nurses to develop an insight into the importance of health education regarding Childhood malignancy and its various aspects. .

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 Keywords

Effectiveness, Planned teaching programme, Knowledge, Mothers, Malignancy

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Creative Commons Attribution 4.0 and The Open Definition

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The Edisinge art form, also known as Ideesung or Tongseng, is a traditional wall mural practice of the Savara tribe, primarily residing in the Eastern Ghats of Andhra Pradesh and Odisha, India. This intricate art, characterized by its vivid depiction of nature, wildlife, and tribal life, holds profound cultural and spiritual significance for the Savara community. However, modernization, changes in religious practices, and the replacement of traditional mud houses with concrete structures threaten its survival. This paper explores the historical roots, artistic techniques, cultural importance, and contemporary challenges of Edisinge art, drawing on ethnographic accounts and recent initiatives to revive this endangered tradition. It argues for the urgent need to preserve Edisinge as a vital expression of Savara identity and heritage.

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Edisinge, Savara, Tribe,Art, Mural.

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This study examines the disparities in access to housing amenities among Scheduled Tribes in Kerala, focusing on six tribal communities with differing socio-economic backgrounds. While Kanikkar, Malayaraya, and Kurichiya exhibit better infrastructure and living conditions, Paniya, Irular, and Muthuvan face significant challenges in housing, sanitation, drinking water, and healthcare. The findings reveal that socio-economic status influences access to essential services, with tribes that have better socio-economic conditions benefiting from improved facilities, while disadvantaged groups struggle with inadequate infrastructure. The study underscores the urgent need for targeted interventions, enhanced welfare programs, and effective implementation of policies to bridge these inequalities. Ensuring equitable access to sanitation, clean water, and safe housing is essential for the holistic development of Scheduled Tribe communities, fostering inclusive growth and social well-being. Government initiatives must prioritise infrastructure development to address these disparities effectively.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Scheduled Tribe, Housing Amenities, disparity, inclusive growth

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Creative Commons Attribution 4.0 and The Open Definition