Evaluation and optimization of carbon emission for federal edge intelligence network by Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI

“…In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.…”
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Batch Evaluation Metrics in Information Retrieval: Measures, Scales, and Meaning by Alistair Moffat

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Multi-factor evaluation of clustering methods for e-commerce application by Adam Wasilewski, Krzysztof Juszczyszyn, Vera Suryani

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Machine learning classification meets migraine: recommendations for study evaluation by Igor Petrušić, Andrej Savić, Katarina Mitrović, Nebojša Bačanin, Gabriele Sebastianelli, Daniele Secci, Gianluca Coppola

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Fibre-based organic electrochemical transistors: principle, evaluation, and application by Yingying Huang, Zhijun Hu, Shouwen Zhu, Bo Fang

“…Abstract Organic electrochemical transistors (OECTs) are emerging organic semiconducting devices intensively used in biological detection, environmental monitoring, biomimetic electronics, and computing circuits, due to the high transconductance, low working voltage, and exceptional biocompatibility. …”
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Evaluation and Optimization of Prediction Models for Crop Yield in Plant Factory by Yaoqi Peng, Yudong Zheng, Zengwei Zheng, Yong He

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Panoramic Assessment Method of Substation Equipment Health Status Based on Multisource Monitoring and Deep Convolution Neural Network under Edge Computing Architecture by Zhu-xing Ma, Li-shuo Zhang, Hao Gu, Zi-zhong Xin, Zhe Kang, Zhao-lei Wang

“…In view of the low efficiency of the traditional manual evaluation method of substation equipment status under the background of complex environment, a panoramic evaluation method of substation equipment health status based on multisource monitoring and deep convolution neural network under edge computing architecture is proposed. …”
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Applying usability recommendations when developing mobile instant messaging applications by Sergio Caro‐Álvaro, Eva García‐López, Antonio García‐Cabot, Luis de‐Marcos, Adrián Domínguez‐Díaz

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Evaluation framework for the generation of continental bare surface reflectance composites by Paul Karlshoefer, Pablo d’Angelo, Jonas Eberle, Uta Heiden

“…This study presents a novel approach to evaluate the process of computing bare SRCs across large geographical areas. …”
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Expert evaluation of large language models for clinical dialogue summarization by David Fraile Navarro, Enrico Coiera, Thomas W. Hambly, Zoe Triplett, Nahyan Asif, Anindya Susanto, Anamika Chowdhury, Amaya Azcoaga Lorenzo, Mark Dras, Shlomo Berkovsky

“…Abstract We assessed the performance of large language models’ summarizing clinical dialogues using computational metrics and human evaluations. The comparison was done between automatically generated and human-produced summaries. …”
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An Investigation into the Validity of Some Metrics for Automatically Evaluating Natural Language Generation Systems by Ehud Reiter, Anja Belz

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RELPRON: A Relative Clause Evaluation Data Set for Compositional Distributional Semantics by Laura Rimell, Jean Maillard, Tamara Polajnar, Stephen Clark

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The essential AI skills and knowledge that business accounting students should acquire by Wilfredo Moran

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A Comprehensive Study on Lightweight Convolution Techniques for Malicious Traffic Synthesis in Diffusion Models by Fuhao Li, Ifiok Udoidiok, Jielun Zhang

“…Two popular datasets, USTC-TFC2016 and N-BaIoT, are utilized to train our generative models, with the generated data being employed to train various classifiers for a thorough performance evaluation. The experimental results demonstrate that the investigated lightweight approaches can efficiently generate high-quality and diverse malicious traffic data for enhancing the performance of intrusion detection systems while the computational complexity is reduced to around 19.69% of the baseline.…”
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Defining and Analyzing Nervousness Using AI-Based Facial Expression Recognition by Hyunsoo Seo, Seunghyun Kim, Eui Chul Lee

“…This study presents a mathematical and computational framework for defining and classifying nervousness using facial expression data projected onto a valence–arousal (V–A) space. …”
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A A Comprehensive Review of Energy Optimization Techniques in the Internet of Things by Bassey Isong, Kedibone Moeti

“…However, challenges like scalability, computational overhead and real-world deployment issues persist. …”
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Fast autoscaling algorithm for cost optimization of container clusters by José María López, Joaquín Entrialgo, Manuel García, Javier García, José Luis Díaz, Rubén Usamentiaga

“…An essential characteristic implemented by these clusters is autoscaling, which is the ability to automatically adapt the computing resources of a cluster to support variable workloads. …”
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Sustainable Material Selection in New Constructions: A Brute-Force Optimization Framework Using Parallel Computing, Cost Benefits, and Thermal Performance Analysis by Ehsan Arab Anvari, Sajad Sadi, Javad Gholami, Rima Fayaz

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Balancing Radiation Dose Reduction and Image Quality in Chest Computed Tomography using Silicon Rubber-barium Sulfate Composite Shield by Mohammad Keshtkar, Saeedeh Yazdanifar

“…The objective of this study is to develop and evaluate a novel silicon rubber-barium sulfate (BaSO4) composite breast shield for reducing radiation dose in chest computed tomography (CT) examinations while minimizing impact on image quality. …”
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Role of 256 and 128 Slice Multidetector Computed Tomography Scan (MDCT) in the Staging of Urinary Bladder Cancer with its Histopathological Correlation by Udayan Bhattacharya, Suresh K. Toppo, Anima R. Xalxo, Rajeev K. Ranjan, Nisha Rai, Saumik Pal, Harish S. Gupta

“…Imaging modalities, especially multidetector computed tomography (MDCT), play a critical role in preoperative staging. …”
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