Volume 12 | Issue 7

 Abstract

This paper is an attempt to understand the concept of innovation and the integration of new technology within the Indian education sector, as well as how to effectively measure its impact. The COVID-19 pandemic has significantly affected the education system in India at all levels. The Digital India initiative by the Indian government places a strong emphasis on improving teacher development to enhance the quality of education nationwide. The incorporation of technology has greatly enhanced the educational landscape, becoming essential for the advancement of education. Technology is playing an increasingly crucial role in the field of education, offering numerous benefits to students across all levels of learning. As India strives to become a global leader, its education system must undergo significant changes to align with the digital education standards of developed nations. Educational technology has the potential to revolutionize education, making it more accessible and affordable. The rising costs of education in a country with one of the largest populations in the world can be mitigated through the use of technology, providing opportunities for those who have been previously unable to access quality education. The study also explores the implications of online teaching and learning practices, as well as suggests avenues for further research.

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Education technology, COVID-19 Pandemic, Digital India, E-learning, Software technology, Educational apps.

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: The expanding consumer interest in natural products has led to a recent increase in demand for herbal mixtures. Nowadays, herbal cosmeceuticals are more common because they don't cause harmful side effects. A common hyperpigmentation condition called melasma is characterized by sporadic brown patches on skin exposed to the sun. While hydrocortisone is a corticosteroid with anti-inflammatory characteristics, Withania somnifera, often known as ashwagandha, is a well-known herb having antioxidant and anti-inflammatory activities. This study intended to formulate and evaluate an emulgel that would treat melasma by combining hydrocortisone with Withania somnifera extract.

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Box Behnken Design; Emulgel; Hydrocortisone; Withania somnifera.

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Now a days, people face various diseases due to environmental condition and their living habits. So the prediction of disease at an earlier stage becomes an important task. The correct prediction of disease is the most challenging task. To overcome this problem Machine Learning plays an important role to predict the disease. Medical science has a large amount of data growth per year. Due to the increasing amount of data growth in the medical and healthcare field the accurate analysis of medical data has been benefits from early patient care. With the help of disease data, machine learning finds hidden pattern information in a huge amount of medical data. With the help of disease symptoms data set disease prediction is done by using Machine learning algorithms like Random forest and Support Vector Machine.

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Machine Learning, Disease, Symptoms, Efficiency, Supervised, Accuracy

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The development of the smart drug delivery system (SDDS) is a revolution of nanotechnology in the pharmaceutical and medical fields. Nanomaterials through their enhanced target specificity, biodistribution, and plasma retention have overcome the therapeutic adverse effects of the conventional drug delivery system. The response-based intelligence of the system helps to release drug payloads released under specific pathological conditions. The development of an intelligent drug delivery system combines multiple approaches and multiple signal responses to improve their applicability in diagnosis as well as therapy. This chapter provides a brief overview of the SDDSs with respect to various stimuli-responsive systems.

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SMART DRUG DELIVERY

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"Composite and Multilingual culture of Palakkad District" is a study to explore study on the phenomenon of Palakkad migration movement of different communities from other states to Palakkad throughout the period. The composite culture of the Palakkad district known for its multilingual communities reflects the diverse heritage of the region. The history of Migration is a complex phenomenon, that has fascinated different scholars across disciplines. Many scholars have explored the historicity of migration process from different states of India particularly, Palakkad. Especially those people who have migrated from the neighbouring states of Kerala to Palakkad. From its vibrant festivals to its traditional art forms, Palakkad 's composite culture is evidence to the harmonious coexistence of different ethnic groups and their shared history. Basically, the society of Palakkad depended on agriculture which is their basic occupation and at the same time many migrated groups are contributing economic and cultural prosperity to this region. This study is an attempt to analyse the multi lingual culture Palakkad, that resulted in the formation of the Composite culture in the region.

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Migration, Palakkad Gap, Tamil Brahmins, Agraharam, Theru, Moothan, Chetties, Rawthers, Andi, Pandarams, Vadugas, etc.

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Ahara, Nidra, Bramhcharya are Traya Upstambha (like pillar which supports building) in Ayurveda. Ahara has been enumerated first, which shows its importance. Acharya Charaka has mentioned in Agrya prakrana that Anna is the best sustainer of life. Ghrita is one such Snigdha Ahara Dravya which is viewed as a necessary piece of the human eating regimen in India for a long time. Ghrita is one among the best Ajasrika Rasayana. It is Ayu Vardhaka, Balavardhaka, Ojovardhaka, Vayasthapaka, Dhatuposhaka and is supreme in Snehana Dravya. By virtue of its Yogavahitva, as per its ingredients the medicated Ghrita will be attaining properties of the ingredients without forfieting its own properties. Goghrita is the best among all the Ghrita. Goghrita is having Madhura Rasa; Guru, Snigdha, Mridu Guna; Madhura Vipaka and Sheeta Veerya. It is having Chakshusya, Balya, V?isya, Jeevaneeya, Medhya, Vishaghna and Vatapitta shamaka properties which is indicated in Jeerna jvara, Kshaya, Visha, Daha, Shotha, Shoola, Unmada, Apasmara and many other diseases.

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Ahara, Ghrita, Goghrita, Sneha.

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Morality can be considered as a test upon an individual or society's behaviour to interpret that behaviour or the actions as right or wrong. In a sense morality promotes cooperation amongst the people living in the society and the things they do wrong or right. Morality is a set of rules or values that helps the people living in the society to know as to what is wrong or right/ good or bad/ moral or immoral. Morals can also be considered as customs that are followed since a long time and these morals are usually passed from generation to generation and these values are made for maintaining the peace of the society. When the morality is linked with constitutionality and society it gives birth to terms "social morality" and "constitutional morality". There are many cases and judgements in which both of these types of morality are used, so it cannot be said that Indian judiciary while delivering judgments sticks to only one type or morality, it considers both types of morality considering the facts of each case.

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SOCIAL MORALITY VERSUS CONSTITUTIONAL MORALITY

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This study explores the impact of mineral admixtures, such as fly ash, silica fume, and metakaolin, on the strength and durability of concrete. The primary focus is on M40 grade concrete, with fly ash replacing a portion of the cement according to IS10262:2009 standards. The replacement levels considered are 0%, 5%, 10%, 15%, and 20% for both silica fume and metakaolin. The investigation involves a comprehensive analysis of compressive strength, split tensile strength, and flexural strength at 7, 14, and 28 days, along with various durability tests. According to the test results, the incorporation of both silica fume and metakaolin has demonstrated an enhancement in the concrete's strength at specific replacement percentages.

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Comprehensive, flexural strength and atmosphere.

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Abstract: Biogas is one of the promising renewable technologies which can have ability to convert animal, agriculture, municipal and industrial waste into a non-polluting form of energy. Biogas is a mixture of gases (mainly methane, CO2, traces of H2S, moisture, etc.) produced through the anaerobic digestion of biodegradable organic matter. The digested slurry produces in biogas plants as a byproduct is a better source of of nutrient enriched organic matter for use in agriculture. In India, the biogas development programme was started in 1981 and was one of the approaches to reduce the energy crisis in rural areas. At the national level the estimated potential of biogas power generation up to 2020 by off-grid project was only 7.34 MWe (Megawatt electrical). The highest potential of biogas generation is done by Tamil Nadu i.e., 1.97 MWe followed by Karnataka i.e., 1.57 MWe. Under the National Biogas and Manure Management Programme (NBMMP) total 50,56139 number of biogas plants were installed from 1981-82 to 2020-21 out of which Maharashtra state has the highest no. of biogas plants i.e., 9,24111 followed by Andhra Pradesh (5,58962), Karnataka (5,10916), Uttar Pradesh (4,40930) and Gujrat (4,35272). Recently, the government has emphasized several initiatives, including GOBAR-DHAN, New National Biogas and Organic Manure, Sustainable Alternative towards Affordable Transportation, and the waste-to-energy program. These initiatives aim to enhance the utilization of waste, promote cleanliness in villages and towns, and support the Swachh Bharat Mission and Atmanirbhar Bharat campaign.

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Keywords: Biogas, anaerobic digestion, Manure, Compressed biogas, GOARDHAN,

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The most essential and significant task in computer vision is object detection whose objective is to identify all the pertinent items in the image, along with their category and position. In recent times computer vision technologies have given precise and interesting results using convolution neural network (CNN) model to identify objects. This study has investigated the application of auditory perception in comprehending visual objects, highlighting the notable parallels between the senses of sight and hearing. In this work, real-time object detection assisted with a voice based an alert system has been created with the goal of conveying the user 18 what all is in the surroundings. This type of system can support the visually challenged persons for detecting objects at a particular distance in their vicinity which will help them move around safely, without crashing into any object. Another innovative aspect of this work is that it converts into Bengali regional language after translation for aid of those people who do not understand English. Performance of the suggested model for object detection was evaluated against contemporary techniques and the outcomes of the trial demonstrated its capacity to achieve a significant accuracy level.

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real-time object detection; convolution neural network; text-to-speech; voice feedback; visually impaired; deep learning.

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The World Economic Forum's 2024 Global Risk survey,highlighted concern towards increasing rates of dissemination of false news around the world as a significant concern in the digital age. In 2019, statistics report on fake news in India revealed that 51% of respondents are concerned about the twisting of facts and 32% worried about the impact of the manipulation of facts and the use of parody to spread the fake news.The present study focuses on the reasons for the spread of misleading propaganda in India and proposes mechanisms to combat such falsity using a non-doctrinal research methodology. The paper emphasized that significant challenges faced by individuals, society, economy, and the judiciary due to the widespread distribution of disinformation and misinformation by the intense media. It suggests that strengthening freedom of speech and expression may help to protect interest in society against dissemination of fake news in India.

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Fake News, Social-media, Misleading information, Misreport, False propaganda

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This study analyzes the monthly sunshine hours across five locations in Chhattisgarh, India, to determine if there are significant differences between them. The analysis is conducted using an ANOVA F-test in Microsoft Excel. The findings indicate no statically significant differences in sunshine hours among the locations.

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ANOVA, Excel, Renewable, Sunshine, Sun hours

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Lung cancer remains one of the leading causes of cancer-related deaths worldwide, necessitating the development of advanced diagnostic tools to improve early detection and treatment outcomes. This study introduces "DeepLungCareNet", a novel deep learning-based framework specifically designed for the prediction and classification of lung cancer from medical imaging data. Leveraging the power of convolutional neural networks (CNNs) and advanced image processing techniques, "DeepLungCareNet" aims to enhance the accuracy and reliability of lung cancer diagnosis. In this research, we utilized the IQ-OTH/NCCD Lung Cancer Dataset available from Kaggle, comprising thousands of labeled medical images, including computed tomography (CT) scans and X-rays. The dataset was preprocessed through a series of steps, including normalization, augmentation, and segmentation, to ensure optimal input quality for the neural network. Our model architecture was meticulously designed to capture intricate patterns and anomalies within the imaging data, utilizing multiple convolutional layers, pooling layers, and fully connected layers to extract and learn meaningful features. The performance of "DeepLungCareNet" was evaluated using various metrics, such as accuracy, precision, recall, F1-score, and support. Comparative analysis with existing state-of-the-art models demonstrated that "DeepLungCareNet" outperformed traditional methods, achieving superior results in both sensitivity and specificity. Additionally, we employed explainability techniques, such as Grad-CAM, to visualize and interpret the regions of interest that significantly contributed to the model's predictions, thus providing valuable insights for medical practitioners. Our findings underscore the potential of "DeepLungCareNet" as a robust tool for early lung cancer detection, offering promising implications for clinical practice and patient care. The proposed framework not only enhances diagnostic accuracy but also aids in reducing false positives and false negatives, ultimately contributing to better prognosis and treatment planning. Future work will focus on expanding the dataset, incorporating multi-modal data, and exploring transfer learning to further refine and validate the model's capabilities.

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DeepLungCareNet, lung cancer, machine learning, deep learning, medical imaging, convolutional neural networks (CNN), ResNet50, computed tomography (CT) scans, early cancer detection, Grad-CAM, diagnostic accuracy, privacy in AI, IQ-OTH/NCCD lung cancer dataset, Adam optimizer

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In today's medical landscape, understanding blood thinners is crucial for cardiac and neurological patients to mitigate the risk of life threatening complications like strokes or heart attacks. Knowledge of mechanisms, dosages, and potential side effects empowers patients, fostering better adherence and outcomes while minimizing adverse events. A study aimed to assess an individualized education program on blood thinners among 60 cardiac and neurological patients at a selected hospital. The objectives of the study were to assess the pretest knowledge regarding blood thinners among patients in a selected hospital, to determine the effectiveness of individualized education program on blood thinners among patients in a selected hospital and to determine the association between pretest knowledge score on blood thinners with their demographic variables in a selected hospital. Using a pre-experimental approach with non-probability purposive sampling, researchers evaluated patients' pre-test knowledge and demographic variables through structured questionnaires. And the data were collected and analyzed by using descriptive and inferential statistics. Results indicated varying levels of knowledge: 1.67% had average, 31.67% good, and 66.67% very good knowledge. Significant associations between pre-test knowledge and demographic variables were identified, highlighting the program's effectiveness in enhancing patient understanding of blood thinners.

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blood thinners, effectiveness

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Crystal structure, dioxole, methyl, single crystal X-ray diffraction and phosphinate; T = 295 K; R factor = 0.0523; wR factor = 0.1154; data-to-parameter ratio = 9.08.

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BHARATIYA PARAMPARAYAM VIVAHA SAMSKARANAM TULANATMAKA SAMIKSANAM

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BHARATIYA PARAMPARAYAM VIVAHA SAMSKARANAM TULANATMAKA SAMIKSANAM

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The rising demand for organic products online underscores the necessity for transparency and personalization. This project aims to develop an Android app featuring advanced rating and recommendation capabilities for organic items. Utilizing complex algorithms and machine learning, the app will analyze extensive data from trusted vendors and certification bodies, offering objective product scores based on purity, environmental impact, and ethical manufacturing. The app will provide personalized recommendations through user-friendly interfaces, enabling consumers to make informed choices aligned with their values. Users can rate, discuss, and evaluate products, enhancing the community-driven platform's knowledge and credibility. This innovative approach, integrating advanced analytics, user-centered design, and robust security, aims to revolutionize e-commerce by promoting sustainable purchasing practices and ensuring transparency in the supply chain. The app is expected to boost user engagement, simplify purchasing, and encourage eco-friendly behavior.

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Organic Products, Machine Learning, Personalization, Transparency, Sustainability, Recommendation System, User Engagement, Supply Chain

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???????? ????????, ???????????, ???? ??????, ???????????? ?????? ??????

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Abstract: Introduction: Artificial intelligence (AI) has emerged as a transformative tool in healthcare, particularly in enhancing patient safety measures. By leveraging AI algorithms and data analytics, healthcare systems can proactively detect, prevent, and mitigate clinical-level patient safety concerns. This introduction outlines the significance of AI in revolutionizing patient safety practices, promising improved outcomes and reduced adverse events. Aim and Objectives: To utilize artificial intelligence (AI) to advance patient safety within healthcare systems by implementing innovative solutions and practices.This systematic literature review had the objective to find and evaluate quantitative research that addressed and reported clinical-level patient safety issues by integrating or using AI. Summary: Artificial intelligence revolutionizes patient safety by leveraging advanced algorithms for early detection of adverse events, personalized medication management, and clinical decision support, though challenges such as data privacy and algorithm bias require ongoing attention for effective implementation. Conclusion: According to this systematic review, if utilized appropriately, AI-enabled decision support systems can help to improve patient safety by facilitating better medication management, error detection, and patient stratification. To learn further about how effectively AI can predict safety outcomes in healthcare settings, further work is still required for these systems' strong validation in hypothetical and actual clinical scenarios.

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Artificial intelligence, Patient safety, Clinical-level, Quantitative studies, Systematic literature review

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The fear of persecution, physical harm or death from the warring parties, combined with insecurity owning to conflict forced Sri Lankan Tamil to leave their homes from 1970s to 2000s to India, a closet neighbour. Principally, the civil war between Sri Lankan security forces and the Liberation Tigers of Tamil Eelam (LTTE) impelled the Sri Lankan Tamil to seek refuge in the southern Indian state of Tamil Nadu. From around three lakhs refugees at one point of time, currently more than 52,000 Tamil refugees live in camps spread all over Tamil Nadu. Although Sri Lankan Tamil refugees are entitled to liberal welfare schemes of Tamil Nadu government and work permits, prolonged life in the camps does not lead to resilience and empowerment, and these refugees consider themselves in limbo, belonging neither to Sri Lanka nor to India and unable to get on with their lives. Elder Tamil refugees eager to return - wish to be disassociated with the label of 'refugee', while younger generation feel desire to settle in India or move to abroad as it would improve quality of life for them. On the whole, there are two sustainable options available to Sri Lankan Tamil refugees in India: repatriation or local integration. Resettlement option is the preferred one but the existing divisions and resentment between the two main ethnic communities and perceived anti-Tamil prejudice of Sinhalese leaders are obstacle in repatriation or return to their home. Other options is get citizenship and settle down in India, which some refugees wish to take it up but given the absence of official mechanism will force them to live further in appalling and subhuman condition as refugees. This paper examines issues related to Sri Lankan Tamils refugees in India and the humanitarian dilemma faced by them. The aim is to contribute to the understanding of how Sri Lankan Tamil refugees coping with post-war Sri Lanka and options available before them.

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Refugees, Sri Lanka, Tamil, India, Tamil Nadu

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