Volume 12 | Issue 4 |

 Abstract

It is a species of double stranded DNA contagion that causes in humans and other mammals.

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 Keywords

Monkey Pox, mammals

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The "Leaf Disease Detection using Image Processing " project aims to tackle the critical challenge of timely and accurate detection of plant diseases through the integration of advanced image processing techniques and Convolutional Neural Networks (CNNs). Plant diseases can significantly impact agricultural productivity, making early detection a crucial aspect of modern farming practices. This project seeks to develop an efficient and automated system for identifying leaf diseases using the MATLAB environment. The project begins by assembling a comprehensive dataset of leaf images, encompassing both healthy and diseased samples. These images undergo preprocessing to enhance their quality, including noise reduction, resizing, and normalization .

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 Keywords

Convolutional Neural Networks , MATLAB ,Noise Reduction, Resizing and Normalization

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This study endeavors to create a reliable anomaly detection system for heart disease using the Bisecting Min-Max DBSCAN algorithm. Given the global impact of heart disease on mortality rates, timely detection is crucial for effective treatment. Conventional methods often struggle to discern subtle patterns within complex heart health data. By harnessing the Bisecting Min-Max DBSCAN algorithm, which integrates the strengths of DBSCAN with adaptability, the study addresses this challenge. Data preprocessing involves comprehensive cleaning, integration, transformation, and reduction to enhance model performance. The model employs bisecting K-means clustering followed by DBSCAN to pinpoint abnormal patterns and outliers. Encouraging results exhibit high precision, recall, F-measure, and accuracy, showcasing the algorithm's effectiveness in anomaly detection. Interpretations suggest that this method can facilitate early diagnosis and intervention, thereby improving patient outcomes in cardiovascular health. This research underscores the importance of advanced anomaly detection techniques in healthcare and lays the groundwork for further refinement and expansion of such methodologies for heart disease diagnosis and beyond.

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 Keywords

Support Vector Machine, Random Forest, DBSCAN (Density-Based Spatial Clustering of Applications with Noise), Machine Learning.

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Small cell lung cancer (SCLC) is a type of malignant tumor that is characterized by rapid growth and early metastasis spread. Early and accurate SCLC diagnosis is critical for improved survival. Accurate cancer segmentation assists doctors in better understanding the location and size of cancer and making better diagnostic decisions. In this project, we are using the YOLO framework to pinpoint the exact location of a lung tumor that is attached to the border of blood veins, as well as to classify the tumour. The R-CNN techniques demonstrated in Part 1 primarily use regions to localize objects within an image. The network does not examine the entire image, but only the portions of the image that are more likely to contain an object. The main advantage of using YOLO is that it is extremely fast and accurate

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YOLO, Deep Learning, Lung cancer, CNN.

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Madrasa community as a marginalised group within the minority communities of India face extreme socio-economic and low literacy challenges. Madrasa teachers and students, because of being vulnerable on accounts of their low socio-economic status, lack exposure to mainstreaming and training and development opportunities for seeking gainful employment despite Govt. of India's policy of modernisation and universalisation of education. Yet, they continue to function in relative isolation. Against this backdrop of Covid-19 pandemic issues, this paper reports the inequalities stemming from social-security and welfare issues, in addition to digital remote learning challenges and disparities faced by the madrasa community.Madrasa community as a marginalised group within the minority communities of India face extreme socio-economic and low literacy challenges. Madrasa teachers and students, because of being vulnerable on accounts of their low socio-economic status, lack exposure to mainstreaming and training and development opportunities for seeking gainful employment despite Govt. of India's policy of modernisation and universalisation of education. Yet, they continue to function in relative isolation. Against this backdrop of Covid-19 pandemic issues, this paper reports the inequalities stemming from social-security and welfare issues, in addition to digital remote learning challenges and disparities faced by the madrasa community.

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 Keywords

Marginalised Institutions, Mainstreaming, Employment, Covid-19, Madrasa Education.

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This project proposes a food recognition system that uses a convolution neural network as a base model for image prediction and then returns nutrition facts such as calories in the given single food image. Knowing the nutrition content of the food that we are consuming helps in maintaining a balanced diet. Our work is organized in two parts. First, we trained and optimized a CNN, state-of-art model using Tensorflow 2.0, we are using CNN as the convolution layers are tweakable and easy to implement. Second, we adapt our model with GUI features as well as nutrition analysis. We also created an extension of FOOD-101 dataset by adding typical Indian food categories. Our model performed extremely well with a mean accuracy of 95% in both normal FOOD-101 dataset and in the extended version.

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Deep Learning,CNN,Food Classification

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The Rockwell hardness test is a widely used method for evaluating the hardness of materials, particularly metals. This research paper explores the principles, applications, and significance of the Rockwell hardness test in material science and engineering. The paper delves into the testing procedure, including the selection of scales, test loads, and indenters, as well as the interpretation of hardness values. It discusses the advantages of the Rockwell test, such as its simplicity, speed, and ability to provide reliable hardness measurements. Additionally, the paper examines factors that can influence Rockwell hardness results, such as material composition, surface finish, and testing conditions. Understanding the Rockwell hardness test's fundamentals and considerations is crucial for accurate material characterization and quality control in various industries, from manufacturing to aerospace engineering.

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Rockwell hardness test, Material science engineering, Hardness, Evaluation, Quality.

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The PCMC Divyang KYC Project aims to streamline and enhance the Know Your Customer (KYC) process for persons with disabilities (Divyang) within the Pimpri-Chinchwad Municipal Corporation (PCMC) region. Recognizing the unique challenges faced by individuals with disabilities in accessing and completing traditional KYC procedures, this project seeks to leverage technology to create an inclusive and efficient system.

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Government Initiatives, welfare Programs, Social Impact Technology

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This paper discusses the dynamic connection between oral tradition, performance poetry, and cultural identity, focusing on Native American poetry and poet Joy Harjo's influential contributions. Drawing from interdisciplinary fields like literature, cultural studies, and performance studies, the paper explores how oral tradition plays a crucial role in preserving cultural heritage and passing down wisdom within Native American communities. By analyzing thematic elements, styles, and cultural motifs in Native American poetry, the paper emphasizes the impact of factors like land, spirituality, and oral traditions on shaping Indigenous poems. It further investigates Joy Harjo's innovative approach to performance poetry, blending spoken word, music, and storytelling to create performances with wide-reaching appeal. Through discussions on themes like resilience and connection, the paper evaluates how performance poetry fosters cross-cultural understanding. Examining Harjo's artistic techniques, such as expressive vocal delivery and collaboration, the study reveals how performance poetry can authentically engage with cultural heritage across borders. Ultimately, the research highlights the enduring importance of oral tradition and performance poetry in shaping cultural identity and encouraging dialogue among diverse communities, stressing the significance of preserving and celebrating cultural heritage in modern society.

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Oral tradition, Performance poetry, Native American poetry, Cultural identity, Joy Harjo, Cross-cultural understanding, Cultural heritage.

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Culture refers to the complex total which includes knowledge, belief, art, morals, laws, customs and other capabilities and habits acquired by an individual as a member of a society. Culture trains people along particular lines, tending to put a personality stamp on them. It's also not necessary that all people are likewise in a particular culture. There are sub-cultures within a culture. For, people have their own quiddities and are told by heredity, artistic gests ,sub-cultural gests , family gests and unique particular gests . Cross-culture refers to the commerce of people from different artistic backgrounds, generally within a plant, community, or society. This commerce can lead to a blending or exchange of artistic morals, values, actions, and practices. It's frequently associated with globalization and increased interconnectivity between people from different backgrounds. Cross-cultural issues in transnational surrounds arise due to differences in artistic morals, values, communication styles, and actions between individualities or groups from different countries or regions. These issues can manifest in colorful aspects of transnational relations, including business, tactfulness, education, and social relations.

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1436

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