Daily Archives: February 6, 2025

Abstract-Composite materials have emerged as a critical area of research and development, rapidly gaining importance as structural materials. Among polymer applications, composite materials are poised for significant advancements. Aluminum matrix composites (AMCs) are particularly favored in automotive and aerospace industries due to their exceptional mechanical properties, such as a high strength-to-weight ratio, superior wear resistance, increased stiffness, enhanced fatigue resistance, controlled thermal expansion, and stability at elevated temperatures. Stir casting is widely recognized as an efficient and cost-effective method for AMC fabrication. This study investigates the mechanical behavior of composites made from pure aluminum reinforced with copper, fabricated using the stir casting method. The composites were produced with reinforcement levels of 0%, 2%, 4%, and 6%. Results indicate that the inclusion of copper particles significantly enhanced the hardness, tensile strength, and wear resistance of the composites, though an increase in copper content resulted in decreased density. These findings highlight the potential of copper as a reinforcement material for aluminum-based metal matrix composites, offering valuable insights for diverse engineering applications.

Abstract-The per capita of power in India is insufficient compared to other developed countries in the world. Hence, the only way is the optimal utilization of available energy sources but the difference between production and consumption of electrical energy, during summer is very high, due to large utilization of cooling machines like Air conditioner, Air coolers in such case a software industry, like BPO call center or any office with large server and many systems need to have a 24 hours working Air conditioner. This leads to huge power consumption. Conservative measures need to be initiated and implement to decrease this gap to restrain this situation the concert of DSM has begun in power system planning and management. Therefore this paper included Fuzzy logic applied to Ac which results to calculate the actual hourly turn off period and reduction in energy consumption. By the optimal consumption of electrical power results increase saving by reducing the electricity bill and reduce the over load on live grid during peak hours and also calculate the cost of savings and playback period for the return of investment. In this paper, solar energy is used to run air conditioner. The cost of saving and playback period is calculated by considering only photo voltaic (PV) and photo voltaic with fuzzy controller, Results proved that usage of PV with fuzzy controller has better annual savings and lower pay back period compared with only considering PV.

Abstract-The rise of autonomous ships allows for great opportunities in the search for greater efficiency, cost-effectiveness, and environmental sustainability in maritime operations. Safety, though, has always been a major concern, particularly with the risks of collision within increasingly congested lanes. This paper reviews the literature on how artificial intelligence is being used to transform safety standards, including, in particular, autonomous shipping, for a collision avoidance system. We examined how AI-driven methodologies such as machine learning, path-planning algorithms, predictive analytics, and decision-support systems should be integrated to advance minimal human intervention in the development of navigational decision-making processes. Sensor technologies such as radar, LiDAR, sonar, and satellite imagery are analysed for situational awareness, real-time risk assessment, and dynamic adaptation to the maritime environment. The paper discusses the use of sensor technologies, for example, radar, LiDAR, sonar, and satellite imagery, in support of situational awareness, real-time risk assessment, and dynamic adaptation to the maritime environment. Further, it shows a number of regulatory challenges, ethical considerations, and urgent international standardization issues that the development and integration of AI technologies may have for maritime industries.

Abstract-This project presents a versatile antenna design suitable for various wireless communication platforms, including cognitive radio (CR) communication, 5G, and Wireless Local Area Network (WLAN) applications. A two-port Vivaldi antenna is designed using an FR4 substrate material with a dielectric constant of 4.4 and dimensions of 45.12 mm × 57.94 mm × 1.6 mm. This design is suitable for communication within a cognitive radio architecture. The antenna operates across multiple frequency bands, including the n79 band (4.4 GHz to 5 GHz) for 5G networks via port 1, and the 2.4 GHz band for Wi-Fi and Bluetooth communication via port 2. It achieves a return loss below -10 dB and a VSWR below 1.5 across the n79 band for 5G communication, and the 2.4 GHz band for WLAN applications.

Abstract-The Biomatrix Beat Sensor, developed by Siemens Healthineers, represents a significant leap forward in cardiac and respiratory MRI. By eliminating the need for traditional electrocardiogram (ECG) electrodes and respiratory belts, this contactless technology leverages electromagnetic navigation (EMN) and the Pilot Tone (PT) concept to provide real-time, artifact-free synchronization of cardiac and respiratory motion. This review explores the limitations of conventional methods, the working principles of the Biomatrix Beat Sensor, its clinical applications, and its potential to transform patient care in MRI.

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.