Volume 13 | Issue 6 |

 Abstract

As we know, the machine learning field has been continuously evolving and Kolmogorov-Arnold Networks (KANs) have caught the attention of many researchers recently due to their performance and profound applications in mathematical and physics problems. These networks have been originated from the theorem of Kolmogorov Arnold and dominated traditional machine learning models. These networks have been equipped with dynamic adaptable and learnable univariate parameters and replacing traditional networks having fixed learnable weights. A lot of variants of KAN are already in use such as Graph KAN, Temporal KAN, Convolutional KAN, Rational KAN, etc. With the objective of assisting the keen researchers to navigate this complex field of KAN, this article aims to provide an in-depth study of various KAN architectures and discusses future potential applications of KAN in computer vision and other domains.

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 Keywords

KAN, Kolmogorov Arnold Network, Deep Learning, Computer Vision

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Land-cover classification is one of the core applications in the field of remote sensing. It is a valuable resource for city planners to achieve sustainable development. Many metropolitan cities are experiencing disorganized growth with a high intensity of urban sprawl due to the economic pull and better standards of living offered in metropolitan cities when compared to the surrounding rural areas. If this pattern of growth continues, it will lead to unsustainable development. This leads to an increase in pressure on urban infrastructure and the ecosystem. The traditional methods which are used for urban mapping are time consuming. Land Cover Semantic Segmentation is a process of developing an automated system for land cover classification. This system takes a multiband satellite image of an area as input and outputs the land cover map of the area at the same resolution as the input. For this purpose UNET models were trained in the task of predicting the land cover semantic segmentation of satellite images.

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 Keywords

deep learning semantic segmentation; LoopNet; Landsat 8; land use dataset; land use extraction; multispectral bands; Thailand;

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This study investigates the impact of macroeconomic and market-specific variables on stock returns, in addition to the effect of investment styles, i.e., value and growth investing. It focuses on the region, stock market and examines the risk and uncertainty in future markets through sensitivity analysis. The results provide valuable insights for investors, policymakers, and scholars. By analysing the influence of macroeconomic variables, including GDP, inflation, and interest rates, on stock returns and assessing the efficacy of various investment strategies, the research adds to the literature base on stock market behaviour and investment choice.

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 Keywords

Sensitivity analysis, robustness, stock market behaviour

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Creative Commons Attribution 4.0 and The Open Definition

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Coronary Artery Disease also called as Ischemic Heart Disease. It results from narrowing of the coronary arteries due to atherosclerosis. This is due to buildup of cholesterol and other materials, called plaque, on their inner walls. This buildup is called atherosclerosis. As it grows, less blood can flow through the arteries. As a result, the heart muscle can't get the blood or oxygen it needs. This can lead to chest pain (angina) or a heart attack. Over a time, CAD can also weaken the heart muscle and contribute to heart failure and arrhythmias. As of 2010, CAD was the leading cause of death globally resulting in over 7 million deaths. Males are affected more than females. 65 years male reported at a multispeciality hospital in southern part of kerala with the complaints of chest pain, nausea, light headache, fast heart rate for last 1 week. He had a past medical history of type 2 diabetes mellitus with hypertension. He was diagnosed with Coronary Artery Disease based on a blood tests and ECG. He was continuously monitored for 3 days and prescribed with medications. The patient was found stable, and he was discharged from the hospital with some discharge medications and patient advised to return for OPD follow up in 7 days.

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Coronary Artery Disease, Aspirin, Patient Counselling

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This research presents a comprehensive study of the geological and hydrogeological framework of the Bhopal region in central Madhya Pradesh. Bhopal's subsurface conditions are shaped by a complex geological history encompassing the Vindhyan Supergroup of sedimentary formations, Deccan Trap basaltic flows, and Quaternary alluvium. This paper delineates the lithostratigraphy, structural controls, and aquifer systems that define the region's groundwater regime. It investigates how topography, sedimentology, and tectonics influence aquifer characteristics and groundwater availability. Given the growing urban pressure and climate variability, the study emphasizes the need for sustainable groundwater management strategies informed by geological understanding. The findings can support integrated water resource planning, urban development, and climate adaptation in the region.

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 Keywords

Vindhyan Supergroup, Deccan Trap, Aquifer System, Hydrogeology, Urbanization, Groundwater Management

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Empowering students through targeted educational initiatives remains a cornerstone of inclusive socio-economic development. The Tamil Pudhalvan Scheme, launched by the Government of Tamil Nadu, is a strategic intervention aimed at bridging the financial gap faced by Tamil medium male students in pursuing higher education. This study explores the level of awareness, accessibility, and perceived effectiveness of the scheme among students in Coimbatore city. Employing a mixed-methods research approach, the study collected quantitative data through structured questionnaires from 120 respondents and qualitative insights via interviews with key stakeholders. The findings reveal that while a moderate awareness of the scheme exists, detailed understanding regarding eligibility, application procedures, and long-term benefits is limited. The study highlights that students from urban and better-educated families tend to benefit more, whereas rural and economically disadvantaged students face barriers due to limited awareness, infrastructure challenges, and poor institutional implementation. Overall, the Tamil Pudhalvan Scheme is seen as a promising initiative with considerable potential to enhance employability, reduce dropout rates, and promote skill development--provided its outreach and implementation mechanisms are further strengthened.

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 Keywords

Education Policy, Awareness, Tamil Pudhalvan Scheme, Higher Education, Financial Assistance, Skill Development

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India's transition to electric mobility is propelled by rising fuel prices, supportive government policies, and growing environmental awareness. A study conducted in Coimbatore city examined consumer behavior towards electric two - wheelers, focusing on factors such as Brand perception, Affordability, Eco - friendliness, Technological advancements, Awareness levels, and the availability of charging infrastructure. The results showed that while consumers are becoming more aware of the benefits of electric vehicles, challenges like inadequate charging facilities, high upfront costs, and concerns about batteries continue to hinder widespread adoption. The study provides valuable insights for manufactures, policymakers, and marketers who aim to promote sustainable transportation in urban areas.

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 Keywords

Government policies, Charging infrastructure, Sustainable transportation.

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Introduction: Early ambulation is a powerful catalyst for enhanced postoperative recovery, particularly for post-Caesarean mothers. According to National Family Health Survey 2019-2020, there has been an increase in the number of Caesarean section deliveries in a majority of states. This proactive approach significantly reduces pain, shortens hospital stays, and lowers the risk of complications. Aim: To determine the effectiveness of early ambulation among post caesarean mothers in experimental group. Methodology: A quasi-experimental study was conducted in the Maternity Ward of SLBSGMC&H, Nerchowk, Mandi (H.P), using a post-test-only design. 40 post-natal mothers (20 in the experimental group and 20 in the control group) who underwent LSCS were selected through purposive sampling technique. Data were collected using a socio-demographic data sheet (9 items), a postoperative recovery assessment scale (9items), and a subjective checklist (15 items) to evaluate the effectiveness of early ambulation. Ethical approval was obtained from the ethical committee and the Medical Superintendent of SLBSGMC&H. Data were analyzed using descriptive and inferential statistics. Results: Majority of the participants in both groups were aged 19-24 years (50% experimental, 45% control) and had education levels above graduation (60% in both groups). The majority were homemakers (70% experimental, 60% control). The experimental group had a mean score was 36.25 with SD 2.807, while the control group had a mean score was 12.25 with SD = 2.633 and the p value is <0.001 at p<0.05. Conclusion: Findings of the study revealed that the early ambulation group experienced significantly improved bowel and bladder function, shorter hospital stays, and fewer postoperative complications compared to the control group. An informational booklet was developed to promote the benefits and best practices of early ambulation for mothers undergoing LSCS, highlighting its role in improving postoperative maternal health outcomes.

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 Keywords

Early Ambulation, post-operative mothers, LSCS, post-operative recovery.

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With the rise of deepfake content on social media, distinguishing between genuine and AI generated tweets has become a major challenge. This project proposes an advanced detection framework that utilizes Fast-Text embeddings and deep learning models to identify manipulated text. Fast-Text is chosen for its ability to capture semantic meaning, sub word information, and contextual nuances in social media text, including slang and misspellings. The system integrates LSTM, GRU, and Transformer models to enhance classification accuracy, following a structured workflow of data collection, text preprocessing, Fast Text-based feature extraction, and model training. To ensure reliable detection, the system is evaluated using key metrics like accuracy, precision, recall, and F1 score, demonstrating superior performance over traditional methods. By effectively handling out-of-vocabulary (OOV) words and noisy tweet data, the proposed framework provides a scalable and robust solution for detecting machine-generated tweets. Future enhancements may include real-time detection, integration with BERT, RoBERT, or GPT

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 Keywords

DEEPFAKE DETECTION ON SOCIAL MEDIA: LEVERAGING DEEP LEARNING AND FASTTEXT EMBEDDINGS FOR IDENTIFYING MACHINE-GENERATED TWEETS

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Conflicting narratives are frequently presented by various media, such as social media, news sources, and the entertainments sector, which leads to misunderstandings and divisions in the general public's perception. While some perceive feminism as an extremist philosophy. Others see it as an essential movement for equality. These disparate portrayals have a big influence on how young people understand and interact with feminist ideas. This study aims to evaluate how young people view and engage with feminist narratives, as well as examine how the media shapes misunderstandings about feminism. Through a survey-based approach, this research determines how much different media platforms influence youth attitudes toward feminism, whether social media promotes awareness and engagement or contributes to misinformation, how news coverage and entertainment media reinforce or challenge feminist stereotypes, and whether these portrayals discourage active participation in feminist discussions or influence shifts in perception over time. The study's objectives are to analyze the role of media in shaping misconceptions about feminism and to evaluate how the youth perceive and interact with feminist narratives. In order to determine whether the youth perceives feminism differently from older generations, this study also looks at how various generations perceive it. The youth now mostly encounters feminist discourse through internet channels, whereas earlier generations may have been exposed to feminism through historical movements and direct participation. This change in exposure may lead to changing viewpoints, either making the youngsters more progressive or encouraging skepticism because of media misrepresentations. In order to contribute to the larger conversation on media responsibility in accurately portraying feminist values, this study attempts to comprehend how the media shapes the image of feminism and how it affects youth engagement. The results will promote critical thinking in the consumption of media narratives regarding gender equality and feminism.

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 Keywords

Media representation, feminism, misconceptions, youth perception, 21st century, social media influence, gender equality, media influence, feminist engagement, generational differences.

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