Volume 12 | Issue 5

 Abstract

The agriculture sector plays a crucial role in the economic development of a nation, and technological advancements have the potential to enhance its productivity and sustainability. This project focuses on leveraging machine learning techniques to provide intelligent and data-driven recommendations for crop selection, aiming to optimize agricultural output. The proposed system utilizes historical and real-time data related to soil characteristics, climate conditions, and crop performance to make informed decisions.

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 Keywords

Random Forest, machine learning model, Nitrogen and pH level, temperature, and recommendation system, Naive bayes, factors.

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The Indian Premier League (IPL) is one of the most popular and widely watched cricket tournaments in the world. With the increasing popularity of live sports streaming and the demand for real-time updates, there is a need for innovative solutions that enhance the viewing experience. This research paper presents the development of a Chrome extension called "IPL Live Tracker," designed to provide an immersive and comprehensive experience for IPL fans. The extension leverages web technologies, including HTML, CSS, and JavaScript, to deliver real-time match scores, live commentary, player statistics, and match highlights directly within the user's browser. By integrating with third-party APIs and employing efficient data fetching techniques, the extension ensures seamless and up-to-date delivery of cricket data. Additionally, the paper discusses the user interface design considerations, data visualization techniques, and performance optimization strategies employed to create a responsive and engaging user experience

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 Keywords

Chrome extension, Indian Premier League (IPL), live sports tracking, real-time data delivery, web development, data visualization, user experience, performance optimization, APIs, JSON.

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This study investigates the impact of social sector expenditure on health outcomes in Chhattisgarh, India. Using secondary data sources, including government reports and statistical databases, the research examines the intricate relationship between social sector spending and the health status of the population. The analysis identifies trends and correlations between social sector investments and key health indicators such as infant mortality rate (IMR), maternal mortality rate (MMR), life expectancy, and disease prevalence. Preliminary findings suggest a positive correlation between increased social sector funding and improved health outcomes, albeit with varying degrees of influence across different health parameters. Moreover, distinctive spending patterns emerge in sub-sectors like education, sanitation, and public health, each contributing uniquely to overall health improvement. These insights highlight the critical role of strategic social sector investment in fostering holistic health development in Chhattisgarh. Policy recommendations are provided to optimize resource allocation, maximize health benefits, and reduce disparities within the region.

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 Keywords

Social Sector Expenditure, Health Outcomes, Public Health, Social Expenditure Patterns, Health Indicators, Infant Mortality Rate (IMR), Maternal Mortality Rate (MMR), Life Expectancy, Resource Allocation.

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Diabetes is a chronic illness that develops when the body either cannot use the insulin that the pancreas makes properly or does not create enough of it. One hormone that controls blood sugar is insulin. elevated blood sugar, is a frequent consequence of uncontrolled diabetes mellitus that eventually causes major harm to numerous bodily systems, particularly the blood vessels and neurons. 8.5% of persons who were 18 years of age or older had diabetes in 2014. 2019 had 1.5 million deaths directly related to diabetes, with 48% of these deaths happening before the age of 70. Diabetes contributed to an additional 460000 deaths from kidney disease, and elevated blood glucose accounts for 20% of fatalities from cardiovascular disease. One of the most important aspects of managing diabetes is nutrition therapy. In order to manage type 2 diabetes mellitus (T2DM), it is important to encourage a healthy lifestyle. Nutritional therapy (NT) can assist patients in reaching their blood pressure and glycemic control goals. The treatment of diabetes has advanced recently with an emphasis on developing artificial pancreas systems for automated insulin delivery, optimising insulin therapy, and investigating new oral drugs. Furthermore, SGLT-2 inhibitors and sophisticated GLP-1 receptor agonists are still being studied. Similarly, the recommended nutrition therapy for diabetes may change in near future. Such changes in nutrition therapy must be dynamic and based on not only scientific evidence but also each patient's narrative. The project's goal is to treat diabetes with a diet that is balanced in nutrients.

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 Keywords

Diabetes, Insulin, Nutrition, Nutrition Therapy, Type 2 diabetes mellitus (T2DM)

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Farming is a major input sector for economic development of any country. Livelihood of majority of population of the country like India depends on agriculture. In this project, it is proposed to develop a Smart Farming System that uses advantages of cutting an edge technology such as IoT, Wireless Sensor Network and Cloud computing to help farmers enhance the way farming is done. Four IR sensors is placed in Four direction such as north, south, west and east in order to prevent animal entry. If any animal is detected then it alerts by buzzer and alert through IoT app. Using sensors like temperature, humidity, IR sensors are used to get information about the field and help farmers to take precise decisions on insights and recommendations based on the collected data. The device is IoT enabled by connecting to Wi-Fi using NodeMCU.

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Real time detection, IoT devices, Animal detection, NodeMCU

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: In present world where there is an increasing number of vehicles, it has become more apparent that manual record-keeping is insufficient to manage the vast influx of vehicles. Having a continuous human presence to record license plate numbers is not only labour-intensive but also challenging. Additionally, there are concerns about the legibility of manually stored data. Instances of theft within residential societies are often linked to insufficient authentication procedures during exit, especially during nighttime hours. Authorization for exit is granted only if the information associated with the vehicle and the individual aligns with the database records. To enhance authentication, QR codes are employed. During the time of entry, the number plate recognition serves to be an exceptional solution. The user enters without any obstruction if found to be a resident, and if not, registers himself as one and moves ahead for his own business. At the time of exit, a protected QR code scanner is accomplished by the number plate recognition. This QR code scanner works in a protected manner where the individual consents to their identity. It will be used to match the encrypted key using the designated software or application and when found to be illicit, is denied the exit from the premises. Hence, a protected QR code scanner prioritizes user safety by inspecting content and employing encrypted measures to avoid risks and misleads that may occur. The combination of Python for development, Yolo V8 for real-time object detection, Easy OCR for precise character recognition, and a protected QR Code scanner for authentication reasons, propel this system to an unprecedented level of performance and reliability. This system has the potential to revolutionize security and management at various entry points, ensuring smoother operations and heightened security measures at all times.

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 Keywords

: License Plate Detection, License plate Extraction, Character Segmentation, Character Recognition, Protected QR Code Scanner.

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This study aims to explore the clinical presentation, treatment efficacy, and management challenges of Obsessive-Compulsive Disorder (OCD) in a patient with predominant compulsions related to washing clothes and hands due to fear of contamination.One of the most widely recognized impulses saw in OCD is unnecessary hand washing, frequently determined by an extraordinary apprehension about pollution. This survey looks at the predominance, clinical highlights, hidden components, and treatment moves toward explicitly connected with impulsive hand washing in OCD.The pattern of fixations and impulses sustains tension and misery, prompting critical impedance in personal satisfaction.The case involves a 40-year-old lady diagnosed with OCD, focusing on her compulsive washing behaviours.Treatment approaches for impulsive hand washing in OCD commonly include a blend of pharmacotherapy and psychotherapy. Specific serotonin reuptake inhibitors (SSRIs), like fluoxetine and sertraline, are the first-line pharmacological treatment choices. Mental social treatment (CBT), especially openness and reaction counteraction (ERP), is viewed as the highest quality level psychotherapeutic medication for OCD and has exhibited viability in diminishing habitual hand washing ways of behaving.

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Obsessive Compulsive Disorder, Washing hands and clothes, Recurring thoughts, Cognitive Behaviour Therapy,Exposure Response Prevention, Repetitive behaviours , Medication , Pharmacotherapy, specific serotonin reuptake inhibitors (SSRIs) .

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Locating large picture collections requires the use of content-based image retrieval systems. Convolutional Neural Networks (CNNs) are deep learning algorithms which have upgrade the CBIR with their immense picture feature extraction capabilities. The efficiency of CNNs, ResNet-50, and VGG16 three prominent CNN architectures--for image retrieval is studied in this work. This is investigating a transfer learning-based deep learning framework for CBIR. In this study pre trained models such as CNN, ResNet-50 and visual geometry group (VGG-16) are used to obtain properties from image. These models were trained using large Cifar-10 image datasets. These attributes allow for efficient retrieval based on similarity by capturing the visual properties and semantic content of the images. The study evaluates how effectively these CNN architectures perform in terms of retrieval accuracy. A versatile framework for modifying feature extraction layers is provided by standard CNNs. With its residual connections, ResNet-50 enables deeper structures and better learning. VGG-16's depth can cause overfitting on smaller datasets. The results of this study can help in the development of reliable and effective Content based image retrieval systems. For researchers and practitioners looking to use deep learning for image retrieval applications, the comparison offers valuable insight.

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CBIR, CNN, Pretrained RESNET-50 model, Pretrained VGG16 model, Cifar-10 dataset.

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 Abstract

The nationalist movement that gave the freedom of the country through the leadership of Gandhi. With the participation of many people from different places irrespective of the caste, class, gender etc. Gandhi roles in the organising of national movement from 1919 to 1947. Gandhi weapon of Satyagraha, as a form of struggle, was based on the active participation of the people and on the sympathy and support of the non- participating millions. This paper focused on the various Movements during the Gandhian era and also the participation of women during that period. Additionally it also focuses little on the media influences or the participation of media that give a changes or give a way of communicating tools in the movement to the people's of the country.

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Satyagraha, Nationalism, National Movement,

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This research work introduces a new system for cars that can understand how the driver feels using facial recognition technology. It combines this with picking music from Spotify to match the driver's mood. The system watches the driver's face with a camera and uses a smart program to figure out if they're happy, sad, or other emotions. It then picks songs that match how they feel. Additionally, the system can suggest things like rest stops or calming exercises based on the driver's emotions. This new way of using technology in cars aims to make driving safer and more enjoyable. A camera in the car watches the driver's face as they drive. A computer program quickly looks at the video and figures out the driver's emotions by recognizing facial expressions like smiles or frowns. It can tell if the driver feels happy, sad, angry, surprised, or just neutral. Once it knows how the driver feels, it talks to Spotify or a similar music service to choose songs that fit the mood. This makes sure the music matches the driver's emotions, making driving more personal and enjoyable.

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 Keywords

Recognition System, Intelligent Systems, Smart Vehicle, Road Safety, Emotion Identification, Music

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Its farmers selling application

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work

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To keep pace with the updates in obliging informatics, thriving recuperating data is being amassed unendingly. Regardless, inferable from the not too appalling gathering of its classes and sources, therapeutic data has ended up being particularly jumbled in various specialist's work environments that it now needs Clinical Decision Support (CDS) system for its affiliation. To sensibly utilize the party flourishing data, we propose a CDS structure that can interweave mixed thriving data from different sources, for instance, take a gander at office test works out as planned, critical information of patients, and achievement records into a joined depiction of features everything considered. Using the electronic prospering healing data so made, multi-name delineation was used to endorse a layout of afflictions and thusly help experts in diagnosing or treating their patients' therapeutic issues more capably. Once the ace sees the contamination of a patient, the running with organize is to consider the conceivable complexities of that perplexity, which can impel more infections.

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Clinical Decision Support, analysing and file.

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 Abstract

Dihydropyridine derivatives were synthesized via a unique, environment friendly, and highly effective one-pot multicomponent process, which produced a good to wonderful yield. An important class of low molecular weight heterocyclic scaffolds is represented by 1, 4-dihydropyridines and their derivatives. The Hantzsch pyridine synthesis was completed quickly at room temperature in solvent-free condition using various 1,3-diones and the same starting ingredient aldehyde derivatives such as 5-bromothiophene-2-carboxaldehyde and ammonium acetate in the presence of the catalyst ceric ammonium nitrate (CAN). Interestingly, we discovered that just one of the compounds had excellent antifungal activity against Candida albicans when compared to griseofulvin, while all the compounds were assessed for their in vitro antibacterial and antifungal activities. Every chemical has had its cytotoxicity evaluated using cell lines from breast tumours.

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one-pot multicomponent, Heterocyclic scaffolds, 1, 4-dihydropyridines, ceric ammonium nitrate, Hantzsch reaction.

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Creative Commons Attribution 4.0 and The Open Definition

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Techniques for Preventing Crime Numerous factors, including social, political, and economic ones in addition to environmental ones, have an impact on crime. Humans have a basic need for security and safety. The rate of crime in India's cities has been steadily rising, and efforts to lower it are working. People are drawn to dwell in this neighborhood by its cosmopolitan lifestyle, spacious roadways, cutting-edge amenities, and serene surroundings, yet these same attributes also make it susceptible to criminal activity. Because the police do not respond to crimes in a timely manner, many of them go unreported and ignored. Criminologist C. Ray Jeffery developed the idea of crime prevention through environmental design (CPTED) in 1971. Other notable criminologists who supported the idea included Timothy D. Crow, C. Ray Jeffery, architect Oscar Newman, Jane Jacobs, and Schlomo Angel. First proposed by criminologist C. Ray Jeffery in 1971, the idea of crime prevention through environmental design (CPTED) was further developed by renowned criminologists Timothy D. Crow, C. Ray Jeffery, architect Oscar Newman, Jane Jacobs, and Schlomo Angel. The main factors that determine safety and security in an urban setting are (i) surveillance will someone committing a crime be seen by anyone? (ii) access how easy is it to enter and exit a place? and (iii) territoriality does anyone care about what goes on around them, or is there a sense of belonging to the space among the users? Building layouts, street designs, public spaces, and public facilities can all be addressed at the urban design level to influence both the likelihood of crime and the fear of it. The authors do, however, recognize several commendable initiatives in Indian places such as Ahmedabad, Bangalore, and Surat, where improved surveillance techniques combined with community involvement have transformed the urban landscape and significantly increased public safety. In order to address security concerns in Indian cities, this paper aims to identify the factors that lead to criminal activity within an urban area. It also emphasizes the importance of crime prevention strategies and the applicability of environmental criminology to Pandesara city planning and management practices.

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 Keywords

Environmental Criminology, Crime Prevention Strategies, Urban Design, Pandesara

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The efficient operation of three-phase induction motors is crucial for various industrial applications. However, the occurrence of faults can lead to unexpected downtime and costly repairs. This project proposes a novel approach for fault diagnosis in three-phase induction motors by integrating wavelet analysis and artificial neural networks (ANN). Wavelet analysis is employed for feature extraction from motor current signals, allowing for the detection of subtle changes indicative of different fault types. The extracted features are then fed into an ANN model, trained to classify various fault conditions accurately. The effectiveness of the proposed methodology is demonstrated through simulation data of three phase induction motor under different fault scenarios. Results indicate that the combined approach of wavelet analysis and ANN yields high accuracy in fault detection and classification, enabling proactive maintenance and minimizing downtime in industrial systems. This project contributes to advancing the field of condition monitoring and predictive maintenance for three-phase induction motors, offering a robust solution for early fault detection and diagnosis, thereby enhancing reliability and efficiency in industrial operations.

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 Keywords

ANN, Three phase Induction Motor, Quality Disturbances, Wavelet Transform ,Faults etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the contemporary landscape of education and technology, the demand for innovative learning solutions has paved the way for the development of cutting-edge projects. One such endeavor is the creation of a Data-Powered VoiceMatic Chatbot Conversation designed to enhance the learning experience. This project converges advancements in chatbot technology, machine learning, and Android application development to offer a dynamic and personalized learning platform. The primary objective of this project is to revolutionize traditional learning paradigms by introducing an intelligent and conversational interface. Users can engage in interactive conversations with the VoiceMatic Chatbot, receiving personalized guidance, educational content, and real-time feedback. Through the utilization of machine learning, the chatbot continuously refines its understanding of user preferences, thereby optimizing the learning journey for each individual.

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VoiceMatic Chatbot, Machine Learning , Android Application,Real-time Feedback.

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Creative Commons Attribution 4.0 and The Open Definition

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This study aims to improve the quality of life and promote a culture of health and well-being for people around the world by arguing for a comprehensive approach to health promotion that considers the interconnection between physical and cognitive health. A survey instrument was developed to evaluate participants' attitudes and behaviours about physical fitness and cognitive ability. The survey responses were analysed using relevant software packages to perform descriptive and inferential statistical analysis on the quantitative data. The analysis of the survey data reveals several key findings regarding the perceptions and beliefs of participants regarding the interrelationship between physical activity and cognitive abilities: (1) A vast majority (94.4%) of respondents report noticing positive changes in their cognitive abilities following engagement in regular physical exercise, affirming the beneficial effects of exercise on cognitive function; (2) regular exercise contributes significantly to intellectual development, particularly in enhancing concentration, reducing age-related cognitive decline, and improving sleep quality, underscoring the holistic benefits of exercise for cognitive health; (3) regular exercise is perceived to be associated with improved cognitive development, with a focus on memory, attention, and executive function; and (4) the significance of elements such as diet, sleep, and preparedness for learning. The findings of the study highlight the intricate and diverse connection between physical exercise and cognitive capacities, offering significant knowledge for boosting overall health and guiding interventions to improve cognitive health and performance in various populations.

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OUR FITNESS HAS SOME LINK TO OUR INTELLIGENCE

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The present study explores the viewpoints of school heads and teachers in higher education for guidance and counselling programs functional in secondary Schools of Jajpur District of State of Odisha. The investigators collected data from five different Schools of both state and CBSE board. It was found that the counsellor's contribution has improved the overall participation of students in Co-Curricular activities and career choices based on aptitude of secondary students in a few schools. Some schools have appointed regular counsellors to nurture the young minds to stay motivated and make smart career decisions. Some other teachers and heads opined that the institute should be provided with a regular counsellor to help students make good career decisions based on aptitude, and getting involved in cocurricular activities, which would make the school environment more inclusive and goal oriented.

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 Keywords

Guidance, Counselling, Higher Secondary Institutions, Career Choices, Decision Making

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Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This project provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms. FER approaches using neural networks enabling "end-to-end" learning are then presented. This work also focuses on an up-to-date hybrid learning approach combining a neural network (NN) for the spatial features of an individual frame and long short-term memory (LSTM) for temporal features of consecutive frames. In the later part of this paper, a brief review of publicly available evaluation metrics is given, and a comparison with benchmark results, which are a standard for a quantitative comparison of FER researches, is described. This review can serve as a brief guidebook to newcomers in the field of FER, providing basic knowledge and a general understanding of the latest state-of-the-art studies, as well as to experienced researchers looking for productive directions for future work.

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Facial Emotion Recognition, Conventional FER, Convolutional Neural Networks, Deep Learning- based FER, Principal component Analysis (PCA).

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 Abstract

OBJECTIVE - To evaluate the effect of body weight support treadmill training on balance in stroke individuals. METHOD - A scoping review of observational, experimental, randomized control trials were performed. Google Scholar, EBSCO host and PubMed were searched using terms balance and body support treadmill training and stroke. The PRISMA-Scoping review checklist and preferred reporting items used to analyze each report's section. RESULT - A total of 67 studies were selected, of which 14 were published between 2010-2023 were included in the study. CONCLUSION- This review suggests that body weight support treadmill training is effective on balance in stroke individuals.

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Creative Commons Attribution 4.0 and The Open Definition

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Stroke, body weight support treadmill, balance

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