Metallurgical and Materials Engineering (E-Journal)
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Design and Development of Quantum and ML-Based Cryptography System for SoC Applications
Get PDFIn recent decades, quantum computing-based cryptography has become the latest and more secure for sending of data through different protocols that could be wired or wireless in communications. To optimize power dynamic and static utilization in digital circuits, Machine Learning (ML) and Quantum computing are playing a major role in designing and implementing cryptography systems. The combination of these two techniques will increase the security level and be used for key authentications and integrity. Quantum Key Distribution (QKD) along with ML enables the communicating parties to detect the side channel effects and protection of keys from noisy channels. To guarantee two parties have access to significant sections of the key, the QKD creates random keys for private and public data transmission. The SHA-256 generates 256-bit hash values that are used for authenticating the signatures and data on the fly so that encryption and decryption can process their operation without waiting for hash values as private and public keys. The proposed design has been validated using benchmarking the overhead and measured performance degradation and shown their suitability for SoC and FPGA systems
Performance Study of a NH3/LiNO3 Absorption Chiller Under South Algerian Climate
Get PDFThis study investigates the feasibility of implementing an NH3/LiNO3 absorption chiller under the climatic conditions of Bechar, Algeria. Using energy and exergy analysis techniques, the research evaluates the system's performance under various operating conditions. The absorption cycle is modeled using Engineering Equation Solver (EES) to assess the impact of key parameters on the coefficient of performance (COP). Results indicate that the COP is significantly influenced by generator, condenser, and absorber temperatures. The COP increases from 0.10 to 0.524 as the generator inlet heating water temperature rises, and from 0.10 to 0.628 with increasing absorber temperature. However, the COP decreases from 0.58 to 0.31 as the evaporator temperature increases, and from 0.627 to 0.202 with increasing condenser temperature. The study contributes to ongoing efforts to develop sustainable cooling solutions tailored to regions with extreme climates, highlighting the potential of NH3/LiNO3 absorption chillers for solar-driven cooling applications in hot and arid environments like southern Algeria
Advancing Hybrid Vehicle Energy Systems: Integration of Supercapacitors for Enhanced Performance and Efficiency
Get PDFAs countries around the world look for ways to transition away from carbon-based energy and carbon vehicles, the global automotive industry responds with new developments and trends that are changing the face of transportation as we know it. One new approach being explored to reduce carbon footprint and fossil fuel reliance is the hybrid, which integrates traditional internal combustion engine systems with electric propulsion. Nevertheless, these machines can no longer escape the issues of energy management under fast acceleration and regenerative brake actions. However, hybrid vehicle systems will need assistive dealing with these constraints techniques, the way to address the questions is to perform an extensive review associated with the main body of knowledge in line with the application of these components. The “Hybrid Vehicle Supercapacitor” system uses the complementary characteristics of a conventional battery and a supercapacitor to arrive at a balanced energy storage solution. By utilizing supercapacitors' high-power density and rapid charge-discharge capabilities alongside the energy storage capacity of conventional batteries, the system optimizes energy capture during braking and energy delivery during acceleration. This integration is facilitated through an intelligent control system based on Arduino Nano microcontroller technology, enabling real-time monitoring and adaptive management of energy flow between components. The paper discusses the system architecture, component selection, implementation methodology, performance evaluation, and future development prospects. The findings demonstrate that this hybridized energy storage approach significantly improves vehicle performance, extends battery lifespan, reduces energy losses, and contributes to greater environmental sustainability in the automotive sector
A Study on Green Marketing Practices of Retailers in Coimbatore
Get PDFIn recent years, concern about the environment has been highlighted in many areas of life. Our limited resources are damaged, the future of human life disturbs this planet, thus leaders and thinkers have to create a solution. Green marketing can be considered to be contributing towards enhancing the environmental performance of industry. Due to the challenges of global warming, nations and people have high concerns for environment protection at the time demand by consumer groups for environmentally friendly products has also increased which led to the emergence of a ‘new marketing philosophy’, known as ‘green marketing’. An important element of the evolution of the Indian automobile industry as it responds to challenges of environmental regulations, increasing customer expectations and economic pressures. This research paper is an attempt to understand the green marketing practices of retailers in COIMBATORE. It contains the details of re tailers awareness about green marketing practices
Enhancing Aes And Ecc Cryptographic Protocols For Real-Time Data Security
Get PDFThe security of data is the highest relevance in the area of digital communication, with its emphasis on digital communication. Two cryptographic methods that have acquired extensive usage and are applied to secure the integrity and confidentiality of electronic data are Elliptic Curve Cryptography (ECC) and Advanced Encryption Standard (AES). This study analyses potential improvements to both of those protocols in order to improve their efficiency and effectiveness in real-time applications. A hybrid approach that achieves a balance between security, computing speed, and resource efficiency is what we propose as a solution. For determining of real-time data protection, the changes required shows the decrease in the time-phase which are essential for encryption and maintain a high degree of cryptographic security
Analysis On Mathematical Inventory Control Policy Models For Deteriorating Products With Various Costs By Using Exponential Function
Get PDFIn this paper, we estimate the control policies for deteriorating products with various costs by using exponential function. Deteriorating inventory models with exponential function of various costs with shortage are developed. Shortages are acceptable in a production process that is operating well. The fully backlogged portion balances this. Due to varying exponential costs, deterioration rate is also changeable with time function. Demand items are considered as a constant, which can be obeyed in the exponential function of various costs. We develop the stock keeping cost function as exponential with varying time. Based on these deductions, a mathematical model has been developed and solved numerically. Using the help of numerical analysis we obtain optimum order quantity for each cycle
A Study On Glass Ceiling Effect In Banking: Perceptions Of Women Employees Across Job Levels In Hyderabad
Get PDFDespite the implementation of gender equity policies in the banking sector, a persistent glass ceiling continues to affect women bank employees. This study investigates the attitudes of women working in public and private banks in Hyderabad District toward the glass ceiling and explores how these attitudes impact their career development. A structured questionnaire using a 5-point Likert scale was distributed among 120 women bank employees. The study employed quantitative analysis, including descriptive statistics and chi-square tests, to understand the relationship between job level and the perception of the glass ceiling. Results indicated significant associations between job level and the perceived existence of the glass ceiling. The findings highlight the importance of addressing systemic barriers to foster a more equitable workplace environment for women in banking
AI-Powered Drug Discovery: Integrating Chemistry, Biology, And Data Science
Get PDF“The integration of chemistry, biology and data science into Artificial Intelligence (AI) is rapidly re-defining the drug discovery landscape, to enable accelerated and improved identification of potential therapeutics. In this research we learn to apply four machine learning and two deep learning algorithms namely: Random Forest (RF), Support Vector Machine (SVM), Convolutional Neural Network (CNN), and Graph Neural Network (GNN) for molecular property prediction and virtual screening. These models were trained and evaluated on a comprehensive bioactive compounds dataset. Compound-target interactions are predicted with better performance of CNN and GNN models achieving accuracy of 91.4% and 93.2% respectively. On contrast, RF and SVM results for accuracy was 87.6 \% and 85.1 \%, respectively. Precisen, recall and F1 scores are used for comparing and GNN achieves an F1 score of 0.92. The second, the study also touts AI’s efficiency in cutting down drug discovery timelines and computational costs. The proposed AI driven solution is effective and novel, and is enhanced with the results of comparative analysis with existing literature. These findings highlight the enormous opportunities of AI in reshaping contemporary pharmacology and delivering high quality, low cost, and rapid scale-up in early stages drug development.
Intelligent Interactive Dietary Recommendation Systems Using Nlp
Get PDFDiet also plays a role in overall health and well- being, particularly in patients with conditions like diabetes. With the increase in nutritional health concerns, there is an increasing demand for individualized nutrition guidance depending on an individual's health, lifestyle and nutritional needs. Current nutrition recommendation systems are primarily concerned with food categorization with convolutional neural networks (CNNS), but they propose personalization, real- time user engagement or flexibility to local food culture. Our feeding planning system supports individualized food planning according to user-specific parameters like age, weight, medical history, eating behavior and activity level, based on the integration of artificial neuronal networks (ANN) and natural language processing (NLP). The system predicts the risk of diabetes by employing ML-based predictive models for maximizing food planning and dynamic nutrition planning. NLP facilitates an interactive interface whereby users can choose and get recommended meals, nutritional facts and recipes, and macronutrients. The nutrition tracking feature also tracks the user's food consumption, with real-time feedback and progress tracking.This work illustrates the capability of ML and NLP to be used in digital health interventions and demonstrates how data-driven nutrition recommendations can lead to healthy diets. By continuously adapting to the user's behavior and physiological changes, the system proposed here in provides users with the freedom to select healthier foods for improved health and disease prevention
Bead Optimization And Metallurgical Analysis Of Claddings Produced With Recycled Slag In Submerged Arc Welding
Get PDFThe waste slag which is by-product of steel plant has been recycled as a cladding flux for submerged arc welding (SAW). The recycled slag is applied as a flux in SAW for stainless steel cladding. The bead profile in terms of penetration, width of bead and reinforcement have been investigated and compared with that of original fresh flux. The experiments were performed using central composite design of experiments technique and optimization was achieved with RSM, to improve the performance of claddings. It observed that recycled slag has produced weld profile at par with that of virgin flux. The weld penetration, width of bead and reinforcement obtained using recycled slag is 5.25, 15.11 and 3.98 mm, respectively, which is comparable to that of equivalent virgin flux (5.35, 15.22 and 3.87 mm). The width of bead decreased from 11.0 to 8.2 mm as travel speed is increased from 8 to 34 m/hr. The penetration decreased from 7.4 to 5.9 mm, by increasing travel speed from 18 to 34 m/hr. The optimized parameters obtained are: welding current 427 amperes, travel speed 34 m/hr, voltage 34 volts. It is further observed that recycled slag has yielded desirable microstructure having skeletal delta ferrite embedded within austenitic matrix. The compounds formed within microstructure are also compables. This research is a step forward towards ‘waste to wealth’ technology for circular economy