Abstract-Online payment fraud detection is a critical area of research and development in the realm of financial security. With the rise of e-commerce and digital transactions, ensuring the integrity and safety of online payments has become paramount, This abstract explores various methodologies and techniques employed in the detection and prevention of fraud in online payment systems. The detection of online payment fraud involves the use of advanced machine learning algorithms, anomaly detection techniques, and behavioral analytics. These methods analyze transactional data in real-time to identify suspicious patterns or anomalies that deviate from normal user behavior or transaction patterns. Additionally, the integration of artificial intelligence (Al) and deep learning models has enhanced the accuracy and efficiency of fraud detection systems by enabling them to adapt and learn from new fraud patterns continuously. Moreover, the abstract discusses the challenges associated with online payment fraud detection, including the balance between security and user experience, the need for real-time decision-making, and the evolving nature of fraudulent tactics employed by cybercriminals. Furthermore, it highlights the importance of collaboration between financial institutions, payment service providers, and cybersecurity experts in combating fraud effectively. In conclusion, effective online payment fraud detection is crucial for maintaining consumer trust, safeguarding financial transactions, and mitigating potential financial losses for businesses. Continued advancements in technology and methodologies will play a pivotal role in strengthening fraud prevention strategies and adapting to emerging threats in the digital payment landscape.

Abstract-This project aims to develop a prototype that could potentially assist dog owners in managing feeding schedules more efficiently and inclusively. The functionality of the prototype was assessed based on the aptness of the object detection using an ultrasonic sensor, the accuracy of its real-time clock, the precision of its servo motor for kibble dispensing, the audibility of its voice recorder, the visibility of the neon signage for aging dogs, the braille integration for visually impaired owners, and its overall system reliability. The automated dog feeder was built using an Arduino Uno R3, an HC-SR04 ultrasonic sensor, RTC Module DS3231, PCB matrix, jumper wires, SG90 servo motor, LCD I2C screen, 12V AC adapter, MP3 player, speaker, acrylic, PVC elbow, and some recycled materials such as wood and PVC pipe. The data analysis was based on user feedback and system performance parameters. The results indicated that the prototype accurately dispensed kibble upon detection of the dog’s presence, tracked and scheduled feeding times, and got favorable feedback on its overall functionality, usability, and inclusivity. The given results imply that the automated dog feeder has strong potential to assist diverse dog owners in maintaining regular feeding schedules, making it a more practical solution for busy homes.

Abstract-Population growth is a multifaceted and evolving issue that has captivated the attention of demographers, ecologists, and policymakers for many years. The swift increase in the global population carries significant consequences for resource management, environmental sustainability, and socioeconomic development. This study seeks to enhance the current body of knowledge on population growth by creating and comparing mathematical models that reflect the fundamental dynamics of this phenomenon. In particular, this research examines the exponential and logistic models of population growth, which are commonly utilized in the fields of demography and ecology. The exponential model posits that population growth is influenced by a constant birth rate and death rate, whereas the logistic model considers the environmental carrying capacity and the effects of resource constraints on population growth. Employing a mix of analytical and numerical techniques, this study evaluates the advantages and drawbacks of each model in forecasting population growth across various scenarios. The findings underscore the necessity of accounting for environmental carrying capacity and resource limitations when modeling population growth, and illustrate how mathematical models can guide policy and decision making in areas such as demography, ecology, and resource management. The implications of this study are significant for our comprehension of population growth and its effects on both the environment and society. The outcomes can be leveraged to create more precise and realistic population models, which can aid in policy and decision-making at local, national, and global scales. Additionally, this research showcases the potential of mathematical modeling to deepen our understanding of intricate social and environmental issues, emphasizing the need for further exploration in this area.

Abstract-The Smart rides is robotic car. The rise of smart transportation solutions is revolutionizing urban mobility, and the concept of “Smart Rides” is at the forefront of this transformation. Smart Rides integrate emerging technologies such as the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) with transportation systems to provide efficient, safe, and sustainable travel experiences. This review paper explores the development, implementation, and challenges of Smart Rides, focusing on key components like real-time data processing, autonomous vehicles, ride-sharing services, and predictive analytics. We analyse various smart transportation initiatives across global cities, highlighting their impact on reducing congestion, enhancing energy efficiency, and improving accessibility for diverse populations. The paper also examines the role of smart infrastructure, including sensors and communication networks, in enabling seamless mobility. Additionally, the environmental and social implications of Smart Rides are discussed, with an emphasis on sustainability and equity. Challenges related to data privacy, cybersecurity, and regulatory frameworks are also addressed, proposing solutions for overcoming these barriers. By providing a comprehensive overview of the current state of Smart Rides and future trends, this review aims to guide policymakers, engineers, and researchers in shaping the next generation of intelligent transportation systems.

Abstract-Plasma Physics, the study of charged particles and fluids interacting with electromagnetic fields, is increasingly gaining interest in the field of space propulsion. Traditional chemical rockets have limitations that restrict long-distance space travel, whereas plasma-based propulsion system promise higher efficiency and greater fuel academy. This paper explores the principles behind the plasma propulsion and examines the most recent advancement that bring this futuristic technology closer to practical applications. Additionally, it investigates the ongoing challenges, such as power requirements, fuel sources, and magnetic confinement, and how overcoming these challenges could open new frontiers for deep-space explorations.

Abstract-The aim of this study is to Identification of hazards in various machineries in the steel industry and solution based on the hierarchy of controls. This will minimize the occupational health hazards of the workers. Hazard Identification and Risk Assessment (HIRA) is a process that involves examining what could cause harm to people in black bar to bright bar process workplace and evaluating whether the necessary precautions are in place. The goal is to ensure that no one becomes ill or gets hurt. Based on the risk assessment tool will Identify hazards, assess exposure, evaluate potential risks, and take precautions and to ensure that your workplace is safe and then decide what type of control measures shall be taken to control the employees are protected from harm by using the risk matrix to assist with the process.

Abstract-A serious environmental issue that has an impact on ecosystems, wildlife, and human health is plastic pollution. Since plastic production has increased to almost 368 million tons per year, plastics are found in both terrestrial and marine habitats. Although plastic materials are useful for many purposes, their durability also adds to their persistence in nature, which frequently harms the environment. Millions of marine species consume or become entangled in plastic waste, which can cause harm or even death, making marine life especially vulnerable. Microplastics, which are tiny plastic particles smaller than five millimeters, have also gotten into food chains, affected biodiversity, and endangered human health by contaminating water and shellfish. Plastic pollution has major socioeconomic repercussions since it impacts public health, tourism, and fisheries. Animal health and biodiversity are severely harmed by plastic pollution, which also poses a serious threat to ecosystems and animals. Ingestion, entanglement, or accumulation in food chains are all possible outcomes of the millions of tons of plastic waste that enter rivers, oceans, and terrestrial habitats every year. Fish, marine mammals, seabirds, and other marine species are especially at risk. Malnutrition, internal damage, and obstructions can result from consuming plastic waste, which significantly lowers survival rates. Several governmental efforts are being implemented to reduce plastic production and consumption, encourage recycling and biodegradable alternatives, and increase public knowledge of sustainable practices to reduce plastic pollution. To properly solve this complex issue, however, a comprehensive strategy including individuals, businesses, and governments is required.

Abstract-Automated traffic monitoring solutions have become necessary due to the difficulties of manual monitoring systems and the exponential growth in vehicular traffic. The new Advanced Vehicle Detection System described in this work uses sophisticated computer vision algorithms to identify, recognize, and log vehicle data in real time. Utilizing OpenCV, CNN (Convolutional Neural Network), YOLO (You Only Look Once), and OCR (Optical Character Recognition) technologies, the suggested system detects automobiles and records license plate information. In addition, the system gives law enforcement, traffic management, and institutional surveillance a reliable and scalable approach by automating the entry and exit timestamp logging process. Mostly we are developed for the college buses which has been include arrival and Departure time with an owner details and also the vehicle claim the insurance or not, These also updated the count of vehicle that are recognized by the entry and the exit time. Experimental results demonstrate the system’s high precision and efficiency, ensuring its practical applicability in real- world scenarios. This practical and efficient system is an excellent example of how technology can address real- world challenges in monitoring and managing vehicles.

Abstract-This work is concerned with the machining of Glass Fiber Reinforced Plastics (GFRP), with a primary interest in how surface roughness is affected by cutting tool materials. GFRP has found a niche in aerospace, automotive, and marine applications, and has obtained recognition for its ratio of strength to weight, resistance to corrosion, and thermal stability. Because of the peculiar structure of E-glass fibers in epoxy resin matrix systems, specific problems concerning the use of this material arise, such as delamination, fiber pull out, and wear of tools, thus requiring tailored machining techniques. The experiment compared performance between cut rods using high-speed steel (HSS) and high-carbon steel (HCS) while machining a GFRP rod (30 mm diameter, 240 mm length) using a lathe. Surface roughness parameters are Ra, Rz, Rt, Rpk, all measured by a Talysurf device. The results showed that HSS tools led to smoother surfaces and greater accuracy but that HCS tools were more economically viable for less rigorous jobs. These results touch upon the need for tool selection based on application and give some insight into further pros in terms of coatings, monitoring systems, and further sustainable machining approaches.