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STUDY ON THE PHYTOCHEMICAL ANALYSIS OF APIUM GRAVEOLEN L. SEEDS
Introduction:The world is blessed with an abundance of healing herbs. Since ancient times, India has relied primarily on herbal remedies to treat illness, and this practise is gaining popularity across the developed world as people seek ways to maintain their health in the face of increasing exposure to environmental hazards like pollution and stress. Aim of the study: the main aim of the study is Study on The Phytochemical Analysis Of Apium Graveolen L. Seeds Material and method: There are four parts to the study. Phase 1 involves testing the hypoglycemic effects of extracts in type 1 and type 2 diabetes animals. In phase 3, researchers investigate how exactly the medicine is working to prevent diabetes complications. In Phase 4 of the study, the extract is analysed for its phytochemical composition using a battery of established assays and procedures. Conclusion:Results from the study demonstrate the anti-diabetic impact of Apium graveolans L. seed extracts on diabetic animal models.
DEVELOPMENT AND VALIDATION OF THE UV-SPECTROPHOTOMETRIC METHOD FOR DETERMINATION OF TETRAHYDROCURCUMIN
The main objective is to develop and validate the UV-spectrophotometric method for the estimation of Tetrahydrocurcumin as per ICH guidelines. Materials and Methods: A simple, rapid, accurate, and economical UV-spectrophotometric method has been developed for the estimation of tetrahydrocurcumin. Results: Theλ max of tetrahydrocurcumin was found to be 280nm. The drug follows linearity in the concentration range 2-12 µg mL-1 with a correlation coefficient value of 0.9975. The accuracy of the method was checked by recovery experiment performed at three different levels, i.e., 50%,100% and 120%. The % recovery was found to be in the ranged between 97.81-101.39 with < 1 %RSD, thereby indicating the low variability and a strong agreement between experimental and true values. Ruggedness of the proposed method was studied with the help of two analysts. Conclusion: The above method was a rapid tool for routine analysis of tetrahydrocurcumin.
Failure Analysis and Design Modification of Mandrel in Chassis Tube Bending Machine
Tube/pipe bending is crucial in the automotive industry, especially for rectangular chassis tubes that serve as vital structural components. However, the fatigue life of these tubes can be compromised by surface defects, loads, and vibrations, leading to hazardous failures. Wrinkles and shrinkage often occur during bending due to compressive stress. Mandrels are used for internal support, but they are susceptible to fatigue failure. This research analyzes three fractured mandrel specimens to guide design modifications. CAE analysis simulates real-world conditions, validating the design and predicting durability. The optimal mandrel design based on CAE simulation results will be manufactured for rotary tube bending machines, improving performance and reliability. This research aims to build confidence in finite element simulation, saving time and cost. It also highlights the significant impact of the heat treatment process on component fatigue life, enabling them to withstand rough service conditions.
Performance Analysis of Prepaid Nano Fluid for Cooling-Vehicle Motor
With the growing demand for electric vehicles (EVs), the importance of efficient thermal management systems has significantly increased. These systems play a crucial role in maintaining optimal performance and prolonging the lifespan of critical components, particularly electric motors. However, traditional cooling methods often struggle to meet the high heat dissipation requirements of EV motors, resulting in reduced overall efficiency and reliability. To address this issue, the integration of nano fluids as a cooling medium has emerged as a promising solution. Nano fluids, which are engineered colloidal suspensions, consist of a base fluid (such as water or oil) and nanoparticles with sizes ranging from 1 to 100 nanometers. Through the dispersion of nanoparticles within the base fluid, nano fluids possess unique thermal properties that significantly enhance heat transfer efficiency compared to conventional fluids. This abstract provides an overview of the application of nano fluids in E-vehicle motor cooling, emphasizing their potential benefits, challenges, and future prospects.
Design Optimization and Analysis of Robust and Reliable Battery Tray for Electric Vehicle against Collision
The safety and durability of battery brackets in electric vehicles (EVs) are of utmost importance to ensure the reliable performance and protection of battery packs. Impact testing plays a critical role in evaluating the structural integrity and crashworthiness of battery brackets subjected to various impact scenarios. This abstract presents an overview of the research conducted on impact testing for battery brackets in EVs. Studies have focused on experimental tests, numerical simulations, and finite element analysis to assess the impact performance of battery brackets, which is affected by maximum load (5000N), applied on bracket. Different impact scenarios, including frontal collisions, side impacts, and high-speed loading, have been considered to understand the response of battery brackets the von mises stress, deformation, Equivalent stress. The research highlights the need for rigorous impact testing to ensure the safety and reliability of battery brackets in EVs. By combining experimental tests with numerical simulations, researchers have gained valuable insights into the failure modes, deformation characteristics, and energy absorption capacity and stress formations in battery brackets. These findings have led to recommendations for optimized designs, improved material selection, and enhanced crashworthiness of battery brackets. During a crash, the battery and its bracket are subjected to significant forces and accelerations. The objective of crash testing is to ensure that these components can withstand these forces and protect the battery from damage or the risk of thermal runaway. The battery bracket's role is to secure the battery in place and prevent excessive movement during an impact, thereby safeguarding both the battery and the vehicle's occupants.
Design Optimization and Analysis of Tubing Head Spool for Surface Wellheads are used in the Oil and Gas Industry
The Tubing Head serves as the uppermost spool in a surface wellhead and is typically positioned above the production casing, which is the final string of pipe suspended within the well. It plays a vital role in various functions from well drilling to initial oil production. Tubing head spools have been employed in conventional surface wellheads for many years. However, the current design of the spool is characterized by its significant weight and bulkiness. While this design has proven its effectiveness in the field, there is a need for improvements in terms of size and shape. The primary objective of this study is to reduce the weight and modify the size and shape of the tubing head spool, specifically the 13-5/8”-10K Bottom X 7-1/16”-10K Top variant, utilizing Solidworks modelling and simulation techniques. By leveraging these tools, we aim to optimize the design, achieve weight reduction, and enhance the overall performance of the tubing head spool. The optimization process begins with a comprehensive analysis of the existing tubing head spool design to identify potential areas for improvement. This analysis includes evaluating the stress distribution, pressure containment capabilities, and material utilization of the spool. Various optimization techniques, such as finite element analysis (FEA) are employed to simulate and analyse different design scenarios. We successfully, achieved weight reduction of 5.16% in raw forging and 14.45% in finish part.
Experimental Investigation and Analyze the Effect of Varying L/D on Thermal Performance of Vortex Tube
Traditional vapour compression systems are known to be costly and require regular maintenance due to their numerous moving parts. However, a promising alternative is the vortex tube refrigeration system, which operates without any moving components. This system functions as a miniature refrigerator by effectively dividing the compressed gas into two separate streams: one hot and one cold. In order to maximize the temperature reduction achieved by this system, a study was conducted to assess its thermal performance based on various geometric parameters. Specifically, the investigation focused on the influence of the length-to-diameter (L/D) ratio of the vortex chamber under different inlet pressure conditions. Experimental trials were conducted with different L/D ratios, and the analysis primarily focused on the extent of low temperature fraction attained. The results highlighted the significance of the L/D ratio in determining the overall performance of the vortex tube cooling system
Smart Wearable Device for Women Safety Using IoT
The crimes against women have been rising significantly and often hear about molestation, eve teasing and rape cases in the public places of the society. The security of women is the most important concern these days and to build a safety device to act as a rescue and to prevent from harm at the time of hazard is highly necessary especially for women. In this paper, a smart device for women’s safety which automates the emergency alert system by using pressure sensor, pulse-rate sensor and temperature sensor to detect a possible atrocity automatically using outlier detection is proposed. This system detects and sends the alerts for the dear ones with the location coordinates of the women without the requirement other interaction in critical times. It sends an emergency message automatically to the relatives and nearby police station.
Leveraging Artificial Intelligence in Education: Transforming the Learning Landscape
This article explores the transformative potential of Artificial Intelligence (AI) in the field of education, with a focus on personalized learning. AI technologies can analyze vast amounts of data, adapt to individual needs, and provide tailored learning experiences for students. By leveraging AI in education, we can unlock the power of personalized learning, leading to improved student outcomes, increased engagement, and enhanced educational experiences. This article discusses the benefits, challenges, and future implications of AI in education, highlighting the importance of ethical considerations and responsible implementation to ensure equitable access to quality education for all learners.
Student Monitoring system using Face Recognition with Artificial Intelligence
Due to its potential use in numerous fields, face recognition technology has attracted a lot of attention lately. The monitoring of kids using face recognition technology is one such area of focus. The purpose of this abstract is to give a general understanding of the idea and its ramifications. Face recognition is a technique for monitoring students that uses sophisticated algorithms to recognize and track people based on their facial traits. It is possible to use this technology in educational settings to improve security precautions, simplify attendance monitoring, and keep track of student behavior. The face recognition technology works by taking pictures of students' faces with cameras positioned at key areas throughout the school. These photos are then analyzed and compared to a database of students who have registered. The system can reliably identify people, ensuring that only those with permission can access particular locations and services. Face recognition can automate attendance tracking, improving security while doing away with human procedures. The device may instantly record a student's attendance by merely scanning their face, hence minimizing administrative work and inaccuracies. Additionally, face recognition can be utilized to keep an eye on student behavior. The technology is capable of identifying unauthorized access or suspicious activity and immediately notifying the proper personnel. This could lessen instances of violence, theft, or damage within the institution. Using facial recognition technology to keep an eye on students has many advantages, including increased security, easier attendance tracking, and behavior monitoring. Although the use of such systems necessitates careful consideration of ethical and privacy issues, when used properly, they can help create a more secure and effective.
Smart Home Intelligent System for Elder People Using Raspberry Pi
Nowadays, the care of elderly peoples is a significant problem and needs more time and attention from the caregivers.In order to provide home intelligent control function for the elderly more efficiently and conveniently, this paper designed a smart home system controller based on raspberry PI with simple hardware structure and low development cost. The design is implemented by raspberry PI development board and python language, and the fatigue detection algorithm is implemented by OpenCV visual library, Dlib library and EAR algorithm. Through temperature and humidity sensor, infrared extended version, LCD display screen and other hardware intelligent control indoor environment. The test results show that the fatigue state can be accurately detected and the electrical control function can be realized. This design enhanced the intelligence of household control, and met the life demand of energy-saving convenience.
Sign Language Translator
The deaf community in India relies heavily on the Sign Language (SL) as a means of communication. But because so few people are fluent in SL, there is a communication gap between the hearing and deaf communities. The Sign Language Translator (SLT) in this paper employs MediaPipe and LSTM to convert Sign Language (SL) to text and back again. The suggested approach first uses MediaPipe to extract hand movements and facial emotions from movies of SL signals. The LSTM model, which is trained using a sizable dataset of SL signs and their related text labels, is then fed these characteristics. The input feature sequence is processed by the LSTM model, which also creates the matching text labels. A dataset of SL signs and the text labels that go with them was gathered in order to train and test the proposed system. The outcomes demonstrate that the suggested approach performs extremely well when converting SL signs to text and vice versa. The system is useful for usage in real-life scenarios since it can recognise and translate many indications in succession. Overall, a bridge between the hearing and deaf communities in India can be created by the proposed Sign Language Translator system, enabling seamless inclusion and communication. By allowing them to interact with the hearing world more effectively, it has the potential to greatly raise the quality of life for the deaf people in India.
Facial Emotion Recognition System for Isolated Patient Monitoring using ResNet-50 based Convolutional Neural Network Model
Facial emotion recognition is a promising technology that has the potential to improve the quality of care for isolated patients by enabling healthcare professionals to assess the emotional state of these patients more accurately. Isolated patient monitoring is the practice of closely observing patients who have been isolated due to the risk of infection or other health concerns, and it is essential to ensure the well-being of these patients. The Facial Expression Recognition system is the process of identifying the emotional state of a person. In this system, captured image is compared with the trained dataset available in database and then emotional state of the image will be displayed. This will also integrate the system into existing patient monitoring systems and collect data on its effectiveness in improving the care and well-being of isolated patients. The ultimate goal is to demonstrate the value of facial emotion recognition in isolated patient monitoring, and to identify any potential ethical or privacy concerns that may need to be addressed. This is for facial emotion recognition (FER) in isolated patient monitoring. FER is achieved using computer vision techniques and voice recognition techniques to analyze and interpret facial expressions, which can be useful for identifying and tracking changes in patient’s emotional states. The proposed FER system utilizes deep learning algorithms for real-time detection and classification of emotions with high accuracy. Two popular methods utilized mostly in the literature for the automatic FER systems are based on geometry and appearance. Facial Expression Recognition usually performed in three-stages consisting of pre-processing, face detection & feature extraction, and expression classification. The paper analyses various deep learning image classification models (convolutional neural networks) to identify the certain human emotions: depressed, despair, fear, irritated, uneasy, shocked and neutrality.
AR and VR on Real Estate Mapping
Augmented Reality (AR) and Virtual Reality (VR) technologies are currently prominent areas of research within the information technology field. These technologies have found extensive applications across various domains, including education, healthcare, construction, military operations, and entertainment. As research progresses on the technical aspects of AR and VR, it becomes crucial to simultaneously explore evaluation methods and optimization strategies based on user experience. The primary emphasis of this research centers on the domain of real estate exhibitions, serving as a foundation for conducting comparative experiments between augmented reality (AR) and virtual reality (VR) technologies in the context of real estate displays. The study meticulously selects suitable evaluation indices and employs quantitative methods to perform a comparative analysis of the evaluation results obtained from AR and VR experiments. The ultimate objective is to construct a user experience evaluation model specific to AR and VR technologies.
Blockchain and its Applications NFT’s: Use of Blockchain Security in the NFT Marketplace
In the current time’s, Blockchain or most commonly known as blockchain technology which is a distributed software network and a secure network that allows the secure transfer of assets without any intermediate and has made a huge hype in the digital market or in the internet market place and is taking over like a breeze with its secure and easier transactions, mostly transactions done with the cryptocurrencies like bitcoin ,etherum, etc , with the help of these methods the transactions can be kept out of the books or the papers , where NFT(Non fungible token) is a unique token with its unique characteristics, it is a unique digital art with which is traded on the blockchain network and etherum network including the etherum environment as the front end with the help of this front end system they can trade within the network using etherum coins on platform such as open sea where digital assests are listed , auctioned and traded for the secure transaction of these NFT it uses blockchain network to do the transactions more efficiently. Throughout this research all the required information about the Blockchain and its applications, NFT’s: Use of blockchain Security in the NFT marketplace is listed out.
Smart Table Food Ordering in Restaurant
This project report presents the development of a smart table food ordering system for restaurants. The system aims to enhance the customer experience by providing an intuitive interface for customers to view the menu, place orders, and make payments directly from their table using a touch screen interface. One potential solution is to incorporate technology to enhance customer service and streamline operations. One such innovation is the use of tables fixed with one LED display to enable customers to order directly from their tables. By incorporating this technology, restaurants can reduce their labor costs while improving customer experience. With this system, customers simply input their table number into the LED display, and they can browse the menu and place their order directly. The order is then sent directly to the kitchen or bar, reducing the need for servers to take orders manually. The use of this technology also allows for more efficient tracking of orders and can help reduce errors. When customers place their orders through the LED display, the information is sent directly to the kitchen, reducing the chance of miscommunication between the server and kitchen staff. Additionally, the system can track the time it takes to prepare each order, helping to identify any bottlenecks in the kitchen and improve overall efficiency. This technology can also improve the overall dining experience for customers. With the ability to place orders directly from their tables, customers can take their time browsing the menu and selecting items without feeling rushed. The system can also make recommendations based on previous orders, allowing customers to discover new dishes they may enjoy. In addition to the benefits for customers, this technology can also benefit hotels by reducing labor costs. With the ability to place orders directly from the table, the need for servers to take orders manually is reduced. This can free up staff to focus on other aspects of customer service, such as ensuring guests have a pleasant dining experience. Another benefit of this technology is its potential for integration with other hotel systems.
Smart Aquarium for Fresh Water Fishes
In the modern world, a monitoring system for an automated aquarium is not a novel concept. The device enables automatic pH, temperature, and turbidity level, water level, andfish nutrition management for the user. Manually examining an aquarium's conditions, however, would be inconvenient. It takestime, and dedication is needed. Here, a system connected to the Internet of Things (IoT) is presented to monitor and control the entire aquarium up keep utilizing electronics and sensors that continuously communicate and report real-time status to usersmartphones. The created system will keep track of any physical alterations to the water and maintain it at its perfect state, deciding on any necessary adjustments automatically. The aquarium will carry out all tasks automatically, including controlling the water level, feeding, pH, turbidity, and temperature. It will lessen the amount of manual work needed to manage aquariums.
Spam Detection Using Machine Learning
Deep learning has emerged as a powerful technique for spam detection due to its ability to automatically learn relevant features from raw data. This abstract presents an overview of deep learning approaches for spam detection and highlights their effectiveness in combating the ever-evolving landscape of spam. The challenges of spam detection, includes the use of sophisticated techniques by spammers to evade traditional rule-based filters. Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), have shown promise in addressing these challenges by automatically extracting high-level features from spam messages. The Spam Detection Using Machine Learning in this paper employs the Deep Learning model Bi-GRU to detect the spam messages. The advantages of this approach, is that it has the ability to handle large-scale datasets and their potential for transfer learning across different spam detection tasks. It highlights the role of deep learning in enhancing feature representation, model generalization, and the overall accuracy of spam detection systems
Humanoid Robotics in Artificial Intelligence
The humanoid robotics is the emerging and the fascinating field of research as it combines the advancements in artificial intelligence, machine learning and robotics to design socio- intelligent and human-like robots and robots resembling the human body in the structure .Art of humanoid robotics which include integration of artificial intelligent techniques to enhance their cognitive abilities, interactive behavior and perceptual capabilities like perception and sensing, natural language processing ,human robot interaction, autonomy and control, personalization and adaptability, collaborative capabilities. Overall artificial intelligence plays a crucial role in enhancing the capabilities of humanoid robotics. Machine learning is the one of the ways of implementing the social intelligence in humanoid robots. Humanoid robot is defined as robot resembling the human body and can interact with external world and exhibit basic locomotion like gestures and response to real time scenarios. Domestic robots like poppy developed and designed by poppy project and NAO developed by Softbank. Humanoid robots are used in healthcare, public-relations, education ,rescue operations, research ,human -robot interactions, personal assistance, and education sectors . Robots have proved to be good human companion by doing basic human chores and by robot human interactions. The presented research focuses on the development of 2D,3D indoor humanoid robots in a cost-effective manner which are capable of doing basic human household chores, understanding the human emotions, care giving, personal assistance and in education sector as social robot as an assistive tool in classrooms by accepting the voice commands and responding through the hand gestures and by biped or wheeled locomotion .
Applications of Machine Learning in Medicine
As medical data and information technologies advance, an increasing number of practitioners are recognizing or planning to use artificial intelligence. Radically alter medical practice through the use of cutting-edge machine learning techniques. Research is now being done to determine how machine learning and predictive analysis might be used to tailor individual therapies. In order to create a medical model that can rapidly and reliably forecast new data, machine learning must first learn a large quantity of medical data and investigate the dependencies in data concentration. This allows for the early detection of diseases and the support of therapeutic decisions. Clinical medicine must continue to identify and treat severely ill emergency patients quickly while dealing with a relative paucity of medical resources. The age of big data has made clinical demands and thoughtful medical treatment generate demand. The solution to the fore mentioned challenges lies in the assistance supplied by machines.