Accurate Method for Solar Power Generation Estimation for Different PV (Photovoltaic Panels) Technologies by Aissa Meflah, Fathia Chekired, Nadia Drir, Laurent Canale

“…Therefore, accurate estimation of maximum power generation is then crucial for optimizing photovoltaic (PV) system performances and selecting suitable PV modules for specific climates. …”
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Re-Evaluating Deep Learning Attacks and Defenses in Cybersecurity Systems by Meaad Ahmed, Qutaiba Alasad, Jiann-Shiun Yuan, Mohammed Alawad

“…To address these concerns, it is important to explore new defense methods and understand the nature of different types of attacks. In this paper, we investigate four serious attacks, GAN, Zeroth-Order Optimization (ZOO), kernel density estimation (KDE), and DeepFool attacks, on cybersecurity. …”
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Causal Diagnosability Optimization Design for UAVs Based on Maximum Mean Covariance Difference and the Gray Wolf Optimization Algorithm by Xuping Gu, Xianjun Shi

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Generation and evaluation of an IPTG-regulated version of Vav-gene promoter for mouse transgenesis. by Francesca Grespi, Eleonora Ottina, Nikolaos Yannoutsos, Stephan Geley, Andreas Villunger

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Optimizing Distributed Generation and Energy Storage in Microgrids through Intelligent Energy Administration Strategies by Raj Vijilius Helena, Reddy R. Akhilesh, Singh Navdeep, Gupta Navya, Al-Rubaye Taqi Mohammed Khattab, Agrawal Priyanka

“…Finally, to get a workable approach of load management, an efficiency component for VE-GA is presented. This module generates control diagram of the dispersed generators and ESS, and give three different operation strategies.…”
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IMPACT OF SEASONALITY OF GENERATION AND LOAD ON THE OPTIMAL CAPACITY OF THE ENERGY STORAGE SYSTEM OF THE PROSUMER’S MICROGRID by O.В. Кулапін, A.В. Івахнов, С.O. Федорчук, К.В. Махотіло, Д.О. Данильченко, О.В. Булгаков

“…Two radically different controller algorithms of microgrid operation are considered: the first is focused on the maximum use of solar generation, and the second is on the balanced use of all elements of the prosumer’s microgrid system, including storage and energy consumption. …”
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Structural optimization of different truss designs using two archive multi objective crystal structure optimization algorithm by Pranav Mehta, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…Four recognized standard evaluators—Hypervolume (HV), Generational-Inverted Generational Distance (GD, IGD), Spacing to Extent Metrics (STE), convergence, and diversity plots—were utilized to compare the results with those of nine sophisticated optimization techniques, including MOCRY and NSGA-II. …”
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Evaluation of Natural Image Generation and Reconstruction Capabilities Based on the β-VAE Model by Zhang Honghao

“…This article evaluates the performance of β-VAE in natural image generation and reconstruction tasks, comparing it with Conditional VAE and Information VAE. …”
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Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system performance enhancement and protection adaptation by Nasreddine Bouchikhi, Fethi Boussadia, Riyadh Bouddou, Ayodeji Olalekan Salau, Saad Mekhilef, Chaima Gouder, Sarra Adiche, Abdallah Belabbes

“…The effectiveness of the proposed approach is evaluated by simulations performed on the IEEE 33-bus test system and a large scale 114-bus distribution network to determine its reliability for different network sizes. …”
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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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Design and implementation of a cost-effective, safe, and precise lean-rich generating system for the evaluation of NOX storage reduction catalysts: performance analysis, statistica... by Javad Sajedifar, Seyyed Bagher Mortazavi, Hasan Asilian Mahabadi, Ali Khavanin, Mohammad Sharif Hosseini

“…This research presents a simple, safe, and cost-effective gas generation system for laboratory applications, including evaluating adsorbents and catalysts, particularly NOx storage reduction catalysts, and for toxicological studies using precise dynamic methods like gas stream mixing and evaporation. …”
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From Topology Optimization to Complex Digital Architecture: A New Methodology for Architectural Morphology Generation by Kangqiang Lin, Yongpeng He, Yang Yang, Lei Xiong

“…Owing to the capacities of generating structural configuration with both reasonable mechanical properties and high material utilization, topology optimization has been widely adopted in engineering design. …”
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Sensitivity Analysis of Distribution Network Reconfiguration Optimization for Electric Vehicle and Renewable Distributed Generator Integration by Mahmoud Ghofrani

“…A sensitivity analysis is conducted to evaluate the effectiveness of our proposed reconfiguration strategy across different levels of EV and DG penetration.…”
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Differential Evolution Optimized a Second-Order Divided Difference Particle Filter by Ting Cao, Huo-tao Gao, Chun-feng Sun, Guo-bao Ru

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Evaluation of MODIS and VIIRS BRDF Parameter Differences and Their Impacts on the Derived Indices by Chenxia Wang, Ziti Jiao, Yaowei Feng, Jing Guo, Zhilong Li, Ge Gao, Zheyou Tan, Fangwen Yang, Sizhe Chen, Xin Dong

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Evaluation of Model and Process Optimization for the Treatment of Drilling Wastewater Using Electrocoagulation by Muhammed Kamil Öden

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Construction and Demolition Waste Generation Prediction by Using Artificial Neural Networks and Metaheuristic Algorithms by Ruba Awad, Cenk Budayan, Asli Pelin Gurgun

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Cost-based optimal distributed generation planning with considering voltage depended loads and power factor of DG by Babak Yousefi-Khangah, Saeed Abapour, Shahram Yousefi-khangah

“…To confirm the results, impact of loads which are dependent on voltage and variation of the power factor of the DG units is applied and then Effect of power factor on optimal location and size of DG is shown. A method is proposed for convergence of different results which is caused by different power factors. …”
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Scalable evaluation framework for retrieval augmented generation in tobacco research using large Language models by Sherif Elmitwalli, John Mehegan, Sophie Braznell, Allen Gallagher

“…Abstract Retrieval-augmented generation (RAG) systems show promise in specialized knowledge domains, but the tobacco research field lacks standardized assessment frameworks for comparing different large language models (LLMs). …”
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Sensitivity analysis of activity scheduling parameters with a parameter optimization framework by Matheus Moro Zamprogno, Domokos Esztergár-Kiss

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