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Conference Site: I-COSTE 2024

A Reconfigurable and Efficient Architecture for Modular Polynomial Multiplier in Post-Quantum Cryptography

Quantum-resistant cryptographic algorithms have been proposed to prevent the security attacks from future Quantum Computers. The modular polynomial multiplication is the frequent and time-consuming arithmetic operation in Lattice Based Quantum-resistant Cryptography. In this paper, an efficient and reconfigurable architecture for modular polynomial multiplier is proposed in Lattice Based Post-Quantum Cryptography which can be implemented serially or parallelly depending on the application environments. The proposed modular polynomial multiplier is easily embedded in a crypto-processor to provide security services in the time of Quantum Computing.

An Interactive Learning Platform

This work helps learners engage in remote learning at their own pace whilst giving them the opportunity to also engage in in-depth assistance through the deployment of AI tools.

An Interactive Learning Platform

This work helps learners engage in remote learning at their own pace whilst giving them the opportunity to also engage in in-depth assistance through the deployment of AI tools.

An Interactive Learning Platform

This work helps learners engage in remote learning at their own pace whilst giving them the opportunity to also engage in in-depth assistance through the deployment of AI tools.

A Study on Object Detection Performance through Data Augmentation under Adverse Weather Conditions

This study compares the performance of object detection models through data augmentation with a severe weather dataset.

Advanced Grid Integration of EVs with V2G Capabilities: Power Management Across Diverse Distribution Networks

This paper studies the impact of V2G technology in diverse distribution networks.

Semiconductor Manufacturing Industry: Assessment, Challenges, and Future Trends

This is a review article on the state of the semiconductor industry, challenges, and future trends.

Thermal Performance of Microchannels Heat Sink with Fins on side walls

The main objective of this study is to investigate the thermal performance of straight microchannel heat sinks with fins on sidewalls. A mathematical model is developed and used to carry out the simulation-based study to examine the performance of the microchannel heat sink. From the CFD study, numerical results are obtained for different operational and geometrical conditions. The study shows that using a straight microchannel with pin fins on side walls is better at lower ranges of Reynolds number lower than 400; however, at Reynolds number higher than 400 the straight microchannel with smooth sidewalls shows better performance. Moreover, at a higher Reynolds number than 800, the pressure drop increases significantly. Furthermore, increasing the size of pin fins for both triangle and square fins enhances thermal resistance but also leads to higher pressure drop.

Modeling of the North Atlantic Gyre’s Meridional Overturning Circulation with Neural Nets

This paper analyzes CNNs and spatiotemporal transformers to predict future oceanic circulation patterns and examine meridional circulation in the North Atlantic Gyre, aiming to improve existing models and provide a new tool for analysis.

Proposal for a Genetic Algorithm-Based Approach to Optimize Light Spectrum in Vertical Farming

This study introduces a novel Genetic Algorithm (GA) designed to optimize artificial lighting in vertical farms to enhance Light Use Efficiency (LUE). The proposed GA seeks to identify the optimal spectral composition of Red, Green, and Blue (RGB) LEDs, aiming to maximize crop productivity by evaluating characteristics such as height, width, fresh weight, and leaf count. The algorithm operates through ten stages, including initialization of a population, actuation of RGB values, fitness evaluation, and iterative processes of selection, crossover, mutation, and validation. By comparing RGB treatments with a reference cold white light treatment, the algorithm refines lighting conditions to improve crop performance at different growth stages. Detailed methodologies for fitness evaluation, crossover, mutation, and validation are provided, highlighting the practical steps for implementing this approach in vertical farming environments. This research aims to contribute to more energy-efficient and productive vertical farming practices, supporting the broader goal of sustainable agricultural development.