Volume 12 | Issue 5

 Abstract

Traffic accidents pose significant threats to public safety and infrastructure. Predicting accident risk is crucial for implementing preventive measures and enhancing road safety. This study proposes a machine learning approach to predict traffic accident risk.The methodology involves the collection of extensive historical accident data, including factors such as weather conditions, road types, time of day, and traffic volume. Various machine learning algorithms are employed, including decision trees, random forests, and neural networks, to analyze and model the complex relationships between these factors and accident occurrence. Feature engineering techniques are applied to extract meaningful patterns and improve model performance. The performance of the models is evaluated using metrics.

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Traffic Accident Prediction Using Machine Learning.

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Integrating Generative adversarial Networks (GANs) with Twitter sentiment analysis for stock market prediction. GANs are hired to generate sensible market situations, while sentiment analysis of Twitter information provides actual-time insights into public sentiment. by combining those strategies, the version ambitions to beautify prediction accuracy and seize market dynamics prompted via social media sentiment. The experiment evaluates the effectiveness of this method the use of ancient market data and Twitter sentiment analysis. consequences exhibit the capability of GAN-primarily based models in improving stock marketplace prediction by way of incorporating real-time sentiment analysis from social media structures like Twitter

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Stock Market Prediction, Generative Adversarial Networks (GANs)

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Climate warming is making wildfires a greater menace. This project handles smoke and fire detection using a deep learning model built with Mobile-Net, a robust yet efficient architecture perfect for real-time applications. The model is trained using a vast library of images and videos that depict fire, smoke, and commonplace situations. Its great degree of precision in consistently differentiating between these groups makes it appropriate for a wide range of applications. Through the analysis of images and even live webcam feeds, the technology offers real-time fire and smoke detection. It can be utilized with surveillance systems, fire alarms, and emergency response systems due to its versatility. All things considered, by offering a precise and intuitive deep learning solution for smoke and fire detection, our research advances safety and security in a variety of scenarios

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Wildfire, Machine Learning, Fire Detection, Mobile-Net, Smoke, Video.

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Diabetes, a widespread chronic condition globally, has spurred interest in using machine learning for prognosis and management. This effort aims to develop a predictive framework using machine learning tools, analyzing various data sources to identify at-risk individuals. By employing XGBoost and other machine learning algorithms, it processes large datasets efficiently. Additionally, it integrates a diabetes forecasting chatbot, offering personalized guidance based on individual risk factors. This system shows promise in enhancing diabetes management and health outcomes by accurately identifying high-risk individuals and providing tailored support. Overall, it underscores the potential of machine learning and chatbot technologies in improving chronic disease management.

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Diabetes, Prediction, Machine Learning, Chat Bot.

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A deals on accident detection, wherein we identify the characteristic attributes of objects in addition to detecting them as belonging to a class. More precisely, our goal is concurrently identifying the status of item class bounding boxes--safe, harmful, or crashed--and their detection on roadways. In order to accomplish this, we create a brand-new dataset and suggest a baseline technique for comparing accident detection tasks. Our Attention R-CNN accident detection network is designed with two streams: one for computing characteristic properties and the other for object detection with classes. We incorporate global contexts that are taken advantage of from the scene into the stream for object detection as an attention mechanism that gathers contextual information in the scene.

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Bounding Boxes, image processing, Attention RCNN, Object Detection

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The advent of Artificial Intelligence (AI) has revolutionized various industries, with the computer science sector being at the forefront of this transformation. This research paper explores the potential impact of AI on job automation within the computer science industry, examining both the opportunities and challenges that arise. AI technologies such as machine learning, natural language processing, and robotics are rapidly advancing, leading to increased automation of tasks traditionally performed by human professionals. This shift has significant implications for job roles, skill requirements, and employment patterns. Through a comprehensive literature review and analysis of current trends, the paper identifies key areas where AI-driven automation is most prevalent, including software development, data analysis, cybersecurity, and IT support. The study also delves into the economic and social consequences of job automation, highlighting potential job displacement, the need for reskilling and upskilling, and the creation of new job categories. Additionally, it addresses ethical considerations and the role of policy in managing the transition towards an AI-integrated workforce. The findings suggest that while AI has the potential to enhance productivity and innovation within the computer science industry, it also necessitates proactive measures to mitigate adverse effects on the workforce. By fostering a collaborative approach between industry stakeholders, policymakers, and educational institutions, it is possible to harness the benefits of AI while ensuring a sustainable and inclusive future for all professionals in the field.

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Artificial Intelligence, Job Automation, Computer Science Industry, Machine Learning, Natural Language Processing, Robotics, Employment Patterns, Skill Requirements, Job Displacement, Reskilling, Upskilling, Ethical Considerations, Policy Management.

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Starting a business is inherently fraught with challenges, ranging from financial constraints to market competition. Effective business management approaches are crucial in navigating these hurdles and setting a strong foundation for success. This paper explores various strategies that can mitigate common problems encountered during the early stages of business development. Key areas of focus include financial management, market analysis, risk management, and human resource optimization. Financial management is paramount, as inadequate funding and poor cash flow management are leading causes of start-up failure. This paper examines budgeting techniques, funding options, and the importance of maintaining financial records. Market analysis is another critical component, helping entrepreneurs understand their target audience, competitors, and market trends. Tools such as SWOT analysis, customer segmentation, and market research are discussed in detail. Risk management strategies are essential in preempting potential setbacks. This involves identifying risks, assessing their impact, and developing mitigation plans. The paper highlights methods such as scenario planning, insurance, and diversification. Additionally, human resource optimization is vital for building a competent and motivated team. This section covers recruitment strategies, employee training, and the creation of a positive organizational culture.The paper also emphasizes the importance of strategic planning and adaptability. A well-defined business plan provides a roadmap for the start-up, outlining goals, strategies, and action plans. However, the ability to adapt to changing market conditions and feedback is equally important. Case studies of successful start-ups are presented to illustrate the practical application of these management approaches.By integrating these business management strategies, start-ups can significantly reduce the risks associated with their ventures, enhance operational efficiency, and improve their chances of long-term success. This research provides a comprehensive guide for entrepreneurs looking to establish and sustain a successful business.

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Management, Start-Ups, Financial Management, Market Analysis, Risk Management, Human Resource Optimization, Strategic Planning, Adaptability, Entrepreneurship, Operational Efficiency

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Women entrepreneurs in Rajasthan face unique challenges and opportunities that influence their entrepreneurial journeys. This research paper explores the multifaceted problems and prospects that women entrepreneurs encounter in this region. Despite the progressive strides in entrepreneurship globally, women in Rajasthan still grapple with socio-cultural barriers, limited access to finance, inadequate support systems, and a lack of education and training. These challenges are often exacerbated by the traditional patriarchal mindset prevalent in many parts of the state.The study employs a mixed-method approach, combining quantitative surveys with qualitative interviews to gain a comprehensive understanding of the issues. The findings indicate that financial constraints are a significant hurdle, with many women unable to secure loans or venture capital due to a lack of collateral and gender biases in lending practices. Additionally, the societal expectation for women to prioritize household responsibilities over professional ambitions further limits their entrepreneurial potential.However, the research also highlights several prospects for women entrepreneurs in Rajasthan. Government initiatives, such as the Start-up Rajasthan program and various women-centric schemes, are providing much-needed support. The rise of digital platforms and e-commerce is opening new avenues for women to market their products and services. Success stories of women entrepreneurs in sectors like handicrafts, textiles, and food processing serve as inspiration and proof of the potential for growth.The paper concludes with recommendations to enhance the entrepreneurial ecosystem for women in Rajasthan. These include the need for targeted financial products, mentorship programs, and community support networks. Furthermore, there is a call for policy-makers to address the socio-cultural barriers through awareness campaigns and educational reforms. By fostering a more inclusive and supportive environment, Rajasthan can unlock the full potential of its women entrepreneurs, contributing to the state's economic development and gender equality.

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Women Entrepreneurs, Government Policies, Rajasthan, Entrepreneurship, Prime Minister's Employment Generation Programme, Mudra Yojana, Rajasthan Startup Policy, Rajasthan Investment Promotion Scheme, Socio-Cultural Constraints, Financial Access, Entrepreneurial Ecosystem

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Bharatanatyam, a classical dance form originating from South India, has undergone significant transformations in recent years. This research paper explores the latest trends in Bharatanatyam, focusing on innovations in technique, choreography, music, costumes, and themes. Through an analysis of recent performances, scholarly articles, expert interviews, and case studies, the paper examines how traditional elements are being reinterpreted and integrated with contemporary influences. It also discusses the socio-cultural dynamics and global perspectives shaping the evolution of Bharatanatyam in the modern era.

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Bharatanatyam, Adavus, Margam, Natya Shastra.

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Rural tourism, village traditions, State economy, Himachal Pradesh, Ecology, Culture and environment.

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Dr. PRASADA RAO MUSUGU Faculty Dept. of Philosophy Andhra University Visakhapatnam ABSTRACT The world is beset with numerous social problems including maltreatment, inequity, subordination, carnage and slavery etc. The scenarios of Indian social problems are relatively different from other lands or societies. The most vulnerable practices adopted by Hindus social system and discriminated people basing on their social conditions and social status. The Indian society strongly stratified and controlled under the four fold caste system. The out caste people called as chandalas or panchama caste and treated them as untouchables. Since the ancient times it was prevalent in every part of the Indian sub-continent. The untouchability defined as the discrimination of certain caste people and their inhuman treatment based on their caste system. According to my understanding the untouchability was not a problem if anyone belongs to upper caste happed to be touch or share eatables or using water with the untouchables, and then the upper caste fellow was supposed to purify themselves by taking a holy bath and perform some ceremony. It was somehow better, but there were some other susceptible and intolerable acts prevailing in caste system i.e. panchamas were unseekable, unshadowble and untalkble etc, so where is the life to survive them. Mahatma Gandhi stated that the practice of untouchability is a leper wound in the whole body of Hindu politic. Gandhi was named Dalits as Harijans which means children of God and in 1933, he agitated movement against social discrimination and aimed at gaining socio-economic, political upliftment and social justice for downtrodden people in the society. In 1932 September, Gandhi went on a fasting to protest against segregation of untouchables and started a journal Harijan in Yeravda Jail. Then many Hindu leaders get together and discussed the alternative electoral arrangement agreed for approval of British Government. In 1933 November, Gandhi was dedicated himself to campaign against untouchability and conducted country wide tour to educated the orthodox Hindu community. After the intense great effort of the national leaders especially the Indian Constitution supported the abolishment of untouchability. Now it is formulating laws against practice of any discrimination and it considered to be one of the most dreadful social crimes.

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Key words: Discrimination; Dalits; Untouchability; Orthodox; Harijan; Constitution; Upliftment, Vulnerable, Discrimination, Abolishment.

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ABSTRACT The notion of Corporate Social Responsibility (CSR) encapsulates a comprehensive array of concerns, encompassing sustainable social and environmental interests and welfare, in addition to the financial gains for its shareholders. In the seminal work by Dr. Muhammad Tariq Khan, Dr. Naseer Ahmed Khan, Sheraz Ahmed, and Mehfooz Ali, the authors delve into a comprehensive examination of their chosen subject matter. The enumeration of Indian corporations that have diligently strived to enhance the standard of living within their operational domains and have actively pursued their social obligations encompasses esteemed entities such as HPCL, NTPC, STEEL PLANT, Shell, Price, Water House Cooper, SAIL, TATA Steel Ltd., Coca-Cola India, Arcelor Mittal, and BHEL etc. Corporate Social Responsibility, in contrast, embodies a meticulously orchestrated, strategically devised, and meticulously executed framework that endeavors to foster a more standardized and dedicated socio-economic well-being. The term Corporate Social Responsibility, encompasses the amalgamation of the term 'Corporate', which denotes business entities or organized companies, 'Social', which encompasses all aspects pertaining to the broader society, and 'Responsibility', signifying the reciprocal obligation between these two entities, namely the companies and the society. Corporate Social Responsibility encompasses a set of open and transparent business practices that are grounded in principles of accountability and reverence for employees, communities, and the environment.

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Key Words: Corporate Social Responsibility; Shareholders; Comprehensive; Meticulously; Amalgamation; Pertaining; Reciprocal; Transparent; Accountability; Environment.

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Diathesis Stress Model by Rosenthal and Bleuler gives explanation that abnormal behaviour or any mental illness is the result of biological and genetic Vulnerability. The present study and its findings clearly demonstrates that the medical condition of the child is one of the major psychosocial stressor that can affect the mental well being of the mother thereby activating high levels of stress precipaying future mental illness in the mother .The findings of the study is in agreement eith the Diathesis Stress Model of Psychopathology ranging from mild to chronic

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Diathesis Stress Model,Psychopathology

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Here we consider the female artistes in Calcutta during the life time of Tagore only not belonging to Tagore family who practiced Rabindra-sangeet but were never trained in music at Sangit Bhavana, Santiniketan. The contributions of these female artistes are not only pioneering but also a step further to the 'gender equality' and 'female empowerment'. Many of these female artistes are forgotten now and some others never published any records, whereas some published records are not available in the market except in some personal collections.

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Rabindra-sangeet, Female artistes, Calcutta, Lifetime of Tagore

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A condition referred to as rectal prolapse, involves the rectum moving out of its normal position and may either be partial or full. The specific objectives of this study were therefore to find a para surgical economical and conducive procedure of rectal prolapse also known as Gudabhramsha. Worthy of note at this juncture is the fact that Kshara karma is not usually linked to Gudabhramsha but the result from this case study is promising. The medications and remedies prescribed after the operation incorporated Pitta-shamak medicines, diet and Prakriti conduct changes. Kshara karma also burning with chemical gives inflammation and fibrosis, and fix the rectal mucosa to the muscle layer. Yashtimadhu ghrita matra basti served as post-operative pain-relieving agent and had anti-inflammatory property. The surgery done was an outpatient surgery and after the surgery she has reduced the size of the prolapsed mass without feelings of pain or burning this was true as indicated above. Other side effects were negligible; the patient had a single episode of slight bleed and slight mucousy discharge, but no faecal incontinence. There were no complications of prolapse noted in the later follow up visits and the patient continued to be in stable condition.

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Partial rectal prolapse, Kshara karma, para surgical management, Gudabramsha

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This review discusses the significant role of Dihydropyrimidine dehydrogenase (DPD) in cancer drug metabolism, causing severe toxicity. It highlights that 71% of severe 5-Fluorouracil (5-FU) toxicity patients have reduced DPYD activity, contributing to adverse effects. The four variant genes DPYD*2A, DPYD*13, SNP c.2846A>T, and HapB3 are significant contributors to adverse events, accounting for at least 20% of severe toxicities associated with 5-FU. The review suggests pre-emptive screening for DPYD variants and genotype-guided dose adjustments to improve patient safety.

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Dihydropyrimidine Dehydrogenase (DPYD), Gene Mutation, 5-Fluorouracil, Genotype-guided dose

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Fingerprint identification is one of the most popular and reliable personal biometric identification methods. By using this biometric authentication, we can prevent non-licensees from driving and therefore causing accidents. The proposed system consists of a smart card capable of storing the fingerprint of particular person. While issuing the license, the specific person's fingerprint is to be stored in the card. Vehicles such as bike should have a card reader capable of reading the particular license. The same automobile should have the facility of fingerprint reader device .A person, who wishes to drive the vehicle, should insert the smartcard in the vehicle and then swipe his/her finger. If the fingerprint matches with the fingerprint stored in the smart card then it goes for alcohol detection and helmet checking. After passing all authentications, the vehicle will be ignited. The vehicle will not be ignited, if any one of the authentications fails and will not proceed the next step. This increases the security of vehicles and also ensures safe driving by preventing accidents. The prototype of the ignition system is used by the Master controller is implemented along with the vehicle prototype is developed and the results are attached.

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Keywords: Smart card reader, Fingerprint module, Alcohol sensor, Helmet detector

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Automation of Cattle Livestock is a groundbreaking initiative transforming cattle care and management, crucial for rural economies in India. The absence of accessible veterinary care, delayed vaccinations, and disease outbreaks significantly threaten cattle health and the livelihoods of dependent communities. This project offers a comprehensive solution using cutting-edge technology, including a robust cattle information management system with speech recognition for data input to accommodate diverse literacy levels.

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Lumpy Disease , CNN Algorithm, Cattle Identification, Vaccination Remainder, Insumin, RFID Tags.

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In this article Emotional development refers to the ability to understand and manage one's emotions. Academic performance refers to the grades obtained by the students. Emotions play a key role in behavior and influence the Academic Achievements . The aim of the study is to find the relationship between Emotional Development , Cognitive Development and Academic performance of adolescents. Null hypothesis was adopted. Sample consists of seven districts urban and rural colleges. college students belonging to the age group of 13 to 18years, purposive sampling method was adopted. The results are analysed by computing Pearson correlation and the results indicate that there is no significant relationship between emotional development and academic performance. Independent sample t-test is computed to study the gender difference in emotional maturity and academic performance and the result indicates that there is a significant gender difference in emotional development and academic performance Reasoning ability directly affects academic performance, while selective attention and short-term temporal memory indirectly affect academic performance through reasoning ability. Rohde and Thompson (2007) found that cognitive ability directly predicts academic performance, and the correlation is as high as.

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Emotional development, cognitive development, Academic Achievement.

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Federated learning is an innovative approach used in medical field to resolve the issues like centralization, privacy and confidentiality. It gathers diverse data from several local models and aggregates it in a global model where only results are shared instead of data. Its a collaborative model training method to achieve best performance. We build a frame work for diabetics prediction, which consists of local models like Artificial Neural Networks (ANN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM) networks. These models are trained independently on local data distributed across multiple hospitals, ensuring privacy and data security. To improve the dataset and address class imbalance, both Exploratory Data Analysis (EDA) techniques and Synthetic Minority Over-sampling Technique (SMOTE) are used. EDA helps in understanding the underlying patterns and characteristics of the data, while SMOTE generates synthetic data points to balance the classes. And at the global model we aggregate all local models weights and check for the best model among the existing local models based on their predictive accuracy. In our frame work ANN performs with 89% accuracy. Hence those values are considered for prediction. After training different models , we achieved 89.00% accuracy with an RNN,89.99% accuracy with an ANN, and 89.08% accuracy. With an LSTM model .therefore, we proceed with the ANN model to predict diabetes .After successfully submitting all the weights, we obtained these accuracy levels through the best performer strategy in the global model. This approach ensures that the highest-performing model is utilized for predications,enhancing the overall effectiveness and realiability of the diabetics predication system in a collaborative healthcare environment.

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 Keywords

Federated Learning , Artifical Neural Network , LSTM

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