Volume 12 | Issue 5 |

 Abstract

Nutritional anaemia is one major health issues among women in Manipur. Poor density and bioavailabity of dietary iron staple foods are the major etiological factors for wide spread prevalence of iron deficiency in India. The prime objective of the study is to understand the Nutritional Anemia among Tribal Women in Manipur. This review paper discusses the prevalence of anaemia among women of pregnant women, non-pregnant, non- lactating women among tribal women in Manipur (15-49years) comparing NFHS-4 and NFHS-5. This paper will explore the current state of anaemia among the top five ST dominant district of Manipur. As tribal community largely depend on a limited number of locally available food items and found missing valuable nutrients which later cause deficiency of iron in the blood which is responsible for the formation of red blood cell to protect from anaemia. Additionally it is difficult to meet ascorbic acid, iron and folic acid requirements unless a good source of these nutrients is added to improve the anaemia status among the tribal community. Some issues like their geographical location, low literacy rate, low socio economic backwardness, high terrain, low status occupation, more children, no family planning and addition to lack of awareness about foods and nutrition can be a major issue in rising the causes of anaemia. Recommended for locally available low-cost seasonal foods preferentially vitamin C, iron, folic acid rich food items etc. are guiding principles for better anemia management. In order to improve nutritional related disease and health issues, studies of different health problems, study on nutritional status, and program based like intervention programme on nutrition should be encourage to bring health solution among the rural tribal community.

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 Keywords

Keywords: Nutritional, Anaemia, Health, Tribal, Women, Manipur, Community

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In the present computerized time medical services is one among the significant center region of the clinical space. Individuals attempting to find reasonable wellbeing related data that they are worried about. The Web could be an incredible asset for such an information, but you want to take care to try not to get hurtful data. These days, an epic amount of clinical data scattered absolutely across various sites on the Web keeps clients from finding valuable data for their prosperity improvement. Blunders in drug are one of the first extreme clinical issues that would be a danger to patients' lives. These issues build the necessity to utilize proposal frameworks inside the space of medical care to help clients makes extra efficient and right wellbeing related choices. In this research, we construct a medication proposal framework that utilizes patient surveys to foresee the feeling utilizing different exploitation processes like Count Vectorizer, TF-IDF, BeautifulSoup4, and Manual Component Examination, which can assist with suggesting the top medication for a given infection by various order calculations. The anticipated opinions were assessed by accuracy, review, f1score, exactness, and AUC score. The outcomes show that classifier utilizing TF-IDF exploitation beats any remaining models with 98.3%accuracy.

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Sentiment Analysis, Patient Reviews, TF-IDF, Passive Aggressive Classifier, Matrix, Machine Learning.

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dept of political science S.K.UNIVERSITY ANANTAPUR PIN 515003

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Keywords: contemporary state politics, political landscape, governance and policy-making.

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Classifying brain tumours is a crucial and challenging task that is required to identify the most effective treatment plan based on the many types of brain tumours. An individual's health and quality of life can be profoundly impacted by brain tumours. More than 84,000 people had a primary brain tumour diagnosis in 2021, and more than 18,600 of them passed away from malignant brain tumours. It is imperative that these cancers be promptly and precisely identified. A highly preferred diagnostic technique, Magnetic Resonance Imaging (MRI) is characterised by its outstanding picture quality and non-ionizing radiation.

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Brain Tumor, CNN, Machine Learning, Relu, Python,

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 Abstract

Siksha me kala : siksha me kala prasikshan ka mahatva

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Siksha me kala : siksha me kala prasikshan ka mahatva

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The rapid boom of urbanization and transportation demands has considerably elevated complexity of coping with visitors gliding on highways. This mission introduces a progressive real-time machine that inte- grates car counting, classification, vehicle type, and emblem detection with the usage of deep getting-to-know methodologies. The motive of this mission is to decorate highway site visitors' control by imparting compre- hensive insights into vehicle motion patterns. Employing cutting-edge convolutional neural networks which include YOLO(You Only Look Once), the gadget achieves precise and adaptable automobile detection across various environmental situations. In addition to accurate vehicle detection and counting, this mission uniquely extends its competencies to perceive automobile kinds and brands. By leveraging the electricity of deep studying, the machine can distinguish between exceptional car categories or even understand unique brands, contributing to richer visitor insights. The real-time nature of the system guarantees timely records shipping for informed choice-making in visitor management and infrastructure planning. Extensive experimentation with real-international toll road video information validates the system's first-rate accuracy, processing veloc- ity, and effectiveness as compared to traditional techniques. This mission represents a full-size development in highway traffic control, offering a comprehensive, real-time, vision-primarily based answer that encompasses detection, counting, and type of vehicle kinds and brands.

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Vehicle dataset, Image segmentation, Vehicle detection, Vehicle counting, Highway management

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India's abortion laws have undergone a significant evolution over time, reflecting changing societal norms, medical advancements, and legal considerations. This abstract explores the historical trajectory and current status of abortion laws in India, highlighting key milestones, debates, and challenges. Historically, India's legal stance on abortion has been influenced by various factors, including religious beliefs, socio-cultural norms, and public health concerns. The Medical Termination of Pregnancy (MTP) Act of 1971 marked a watershed moment by legalizing abortion under specific circumstances, such as threats to the mother's life or health, fetal abnormalities, and contraceptive failure. However, the law was criticized for its restrictive nature, limited accessibility, and lack of clarity on gestational limits. In recent years, there has been a growing recognition of the need to reform India's abortion laws to ensure women's reproductive rights and address public health imperatives. The amendment of the MTP Act in 2020 was a significant step towards liberalization, extending the gestational limit for abortion and allowing women greater autonomy in decision-making. The amendment aimed to reduce maternal mortality, combat gender-based discrimination, and promote reproductive justice. Despite these advancements, challenges persist in the implementation and interpretation of abortion laws in India. Access to safe and legal abortion services remains uneven, particularly in rural areas and among marginalized communities. Stigma, misinformation, and socio-economic barriers continue to hinder women's ability to exercise their reproductive rights. Moreover, debates surrounding issues such as sex-selective abortion and conscientious objection by healthcare providers further complicate the landscape of abortion laws in India. Looking ahead, there is a need for concerted efforts to ensure the effective implementation of abortion laws, enhance access to comprehensive reproductive healthcare services, and address underlying socio-cultural barriers. Advocacy, education, and collaboration between stakeholders, including policymakers, healthcare professionals, and civil society organizations, are essential for advancing women's reproductive rights and promoting a more equitable and inclusive society. In conclusion, India's abortion laws have evolved significantly over the years, reflecting changing social realities and evolving medical practices. While progress has been made, continued efforts are required to realize the full potential of reproductive rights and ensure the well-being and autonomy of women across the country.

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Abortion, India, Reproductive Rights, Legal Framework, Public Health

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This system makes use of sensors and ESP 32 micrpocontroller to identify cracks and obstacles on railway track and send the location of cracks if any to the railway authority through the app.This can be used to avoid railway accidents .This becomes automated .

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ESP 32, sensors , railway app, crack and obstacle detection

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 Abstract

My present project concern itself how the term perception enplane by Advaita. According to the Advaita theory of Perception, it is the Chaitanya within us that makes perception possible,. The Chetana (intelligence) within us unites with the chenta in the object, and result is perception. The following well-know illustration from the Vedanta paribhasa gives an account of the nature of perception: "as water from a tank may flow through a channel into a plot of land and assume in shape, so the radiant mind (taijasa-Antahkarana) goes out through the eye or any Vedanta paribhasa cites instances, of perception experience where no sense contact is involved 5, such as pleasure pain, other internal perceptions where moder of mind are directly apprecheded, further, it clearly states that the fact of the sense organ is not the

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Chaitanga, Sannikarsa, Upadhis, Upadhi, Ghatakasa, Kala, Asasa, Kula, Nirupadhika, Paricayaka, Vritti, Janta, Jneya, Advaita, Pramata.

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The growing computation power has made the deep learning algorithms so powerful that creating a indistinguishable human synthesized video popularly called as deep fakes have became very simple. Scenarios where these realistic face swapped deep fakes are used to create political distress, fake terrorism events, revenge porn, blackmail peoples are easily envisioned. In this work, we describe a new deep learning-based method that can effectively distinguish AI-generated fake videos from real videos. Our method is capable of automatically detecting the replacement and reenactment deep fakes. We are trying to use Artificial Intelligence(AI) to fight Artificial Intelligence(AI). Our system uses a Res-Next Convolution neural network to extract the frame- level features and these features and further used to train the Long Short Term Memory(LSTM) based Recurrent Neural Network(RNN) to classify whether the video is subject to any kind of manipulation or not, i.e whether the video is deep fake or real video. To emulate the real time scenarios and make the model perform better on real time data, we evaluate our method on large amount of balanced and mixed data-set prepared by mixing the various available data-set like Face-Forensic++[1], Deepfake detection challenge[2], and Celeb-DF[3]. We also show how our system can achieve competitive result using very simple and robust approach.

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 Keywords

RESNEXT and LSTM Architecture

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