The smartphone industry is advancing rapidly, emphasizing the development of smaller, energy-efficient devices with enhanced features. However, this progress often overlooks the significant environmental impacts of th...
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ISBN:
(纸本)9798331507879;9798331507862
The smartphone industry is advancing rapidly, emphasizing the development of smaller, energy-efficient devices with enhanced features. However, this progress often overlooks the significant environmental impacts of these ubiquitous devices. While corporate sustainability reports from mobile product companies aim to address these concerns, they typically provide high-level overviews that obscure critical details, particularly regarding the carbon footprints (CFP) of individual components such as processors and memories. This paper investigates the discrepancy between the overall CFP trends reported and the actual increasing CFP contributions of processors over the years. Through a detailed analysis, the inadequacies in current reporting practices are highlighted, underscoring the necessity for more granular data and metrics in corporate sustainability reports. Specific, detailed metrics are proposed for inclusion in these reports to enhance transparency and help align the chip architecture, design, and manufacturing communities toward addressing relevant sustainability-related challenges.
This paper introduces a pioneering approach integrating Advanced Encryption Standard (AES) security algorithms with multi-objective drug design, aimed at personalized medicine and optimized drug discovery. By leveragi...
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The current generation of 5G technology has reached its limitations in terms of both frequency and wavelength. There is no room for further increasing the frequency, nor can we decrease the wavelength any further. In ...
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Computer science skills have become very important in the careers of STEM fields in today’s digital economy. However, many students often struggle in grasping programming concepts, leading to high dropout rates in co...
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Integrating game-based learning application in engineering education provides a dynamic approach to increase student engagement and understanding. The goal of this initiative is not only to boost interest in engineeri...
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Premature birth (PB) presents a significant global health challenge, often leading to enduring developmental issues and neonatal mortality. Approximately 4-16% of new-born worldwide is born prematurely. Leveraging mac...
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This study uses a deep learning technique to output the slope failure warning areas from numerical elevation data. This is treated as a semantic segmentation task, with U-Net as the network model. The experiment resul...
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The proceedings contain 290 papers. The topics discussed include: Augmented Reality Experience Application- Area;Enhancing Autonomous Vehicle Navigation with Real-Time Object Detection Using Convolutional Neural Netwo...
ISBN:
(纸本)9798350350067
The proceedings contain 290 papers. The topics discussed include: Augmented Reality Experience Application- Area;Enhancing Autonomous Vehicle Navigation with Real-Time Object Detection Using Convolutional Neural Networks;Advanced Hybrid Intelligence Framework for Scalable and Robust Big Data Analytics;Optimizing Real-Time Medical Diagnostics with Adaptive AI algorithm;an efficient algorithm for black hole attacks detection in VANET;leveraging deep learning architectures for accurate wind speed and power prediction in renewable energy systems;revolutionizing Internet of Things with blockchain for enhanced security and data management;heart disease detection system using machine learning;and evaluating machine learning techniques for stock loss forecasting: hypothesis testing and model selection.
The proceedings contain 192 papers. The topics discussed include: reducing gender and ethnicity bias in personality trait prediction;MDLGO: integrated multimodal deep learning framework for enhanced precision in glauc...
ISBN:
(纸本)9798350306613
The proceedings contain 192 papers. The topics discussed include: reducing gender and ethnicity bias in personality trait prediction;MDLGO: integrated multimodal deep learning framework for enhanced precision in glaucoma diagnosis using OCT A-scans;advancing manufacturing energy efficiency: the role of AI and web-based tools;integrated healthcare system for saline monitoring, patient communication, and heart disease prediction using IoT and machine learning algorithms;IoT based real time drainage monitoring system;software defect prediction by logistic regression with gradient descent cost computation;ONU: A reinforcement load balancing approach for resource-aware task allocation in distributed systems;a novel approach using feature fusion for android malware detection and classification;and graph based analysis technique for identification of key functionalities in malicious IoT binaries.
The rapid proliferation of mobile devices has dramatically increased energy consumption, presenting significant challenges for sustainability. Traditional energy-saving techniques often lack adaptability and fail to a...
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