Integrating IoT sensors and machine learning for sustainable precision agroecology: enhancing crop resilience and resource efficiency through data-driven strategies, challenges, an... by Val Hyginus Udoka Eze, Esther Chidinma Eze, George Uwadiegwu Alaneme, Pius Erheyovwe BUBU, Ezekiel Oluwaseun Ejiofor Nnadi, Michael Ben Okon

“…Coupled with advanced ML algorithms, this data facilitates predictive analytics and real-time decision-making, optimizing resource utilization for irrigation, pest control, and yield prediction. …”
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Investigating Internet of Things and Artificial Intelligence-Based Approaches to Smart Irrigation System Optimisation for Agricultural Water Resource Management by Balassem Zaid Ajzan, Alkhafaij Mahdi Abdulkhudur, Raju Nadimpalli Venkata Ganapathi

“…This system leverages IoT sensors to monitor environmental variables and uses AI algorithms to analyze this data and make real-time irrigation decisions. …”
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Systematic Security Analysis of Sensors and Controls in PV Inverters: Threat Validation and Countermeasures by Fengchen Yang, Kaikai Pan, Chen Yan, Xiaoyu Ji, Wenyuan Xu

“…These vulnerabilities can lead to incorrect sensor readings, disrupting control algorithms. We propose an IEMI attack that results in three potential outcomes: Denial of Service (DoS), physical damage to the inverter, and power output reduction. …”
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Toward reliable fluorescence imaging: Optical prior-guided probabilistic reconstruction for structured illumination microscopy by Kun Lin, Junkang Dai, Huaian Chen, Yi Jin

“…Furthermore, by leveraging the strong cognition ability of GRL to precisely learn the hierarchical representations of the SIM imaging process, PG-SIM itself also achieves a significant uncertainty reduction compared to current methods, overcoming the constraints of unreliability on the practical application of SIM. …”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Many existing methods for crack detection rely on deep learning algorithms or traditional approaches that typically use image data. …”
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Optimization Design Method of a 6-DOF Micromanipulation Mechanism for Extreme Ultraviolet Projection Lithography Objective Lens by Shiyu Li, Junbo Liu, Ji Zhou, Haifeng Sun, Chuan Jin, Xia Kang, Song Hu

“…The results demonstrate a 15.1% reduction in maximum driving force, significantly enhancing outrigger driving smoothness.…”
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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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Hybrid Electric Propulsion Design and Analysis Based on Regional Aircraft Mission by Wenjuan Shan, Shengze Bao, Shixuan Lin, Le Kang

“…Hybrid propulsion systems have become a focal point of low-carbon aviation research due to their advantages in energy savings, emissions reduction, and noise abatement. This study develops an integrated design methodology for hybrid propulsion systems for aircraft, incorporating multidisciplinary algorithms to establish an overall performance model. …”
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Performance of 2D Compressive Sensing on Wide-Beam Through-the-Wall Imaging by Edison Cristofani, Mathias Becquaert, Marijke Vandewal

“…Hardware simplicity, data, and measurement time reduction and simplified imagery are some of its most attractive strengths. …”
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Solving differential‐algebraic equations in power system dynamic analysis with quantum computing by Huynh T. T. Tran, Hieu T. Nguyen, Long T. Vu, Samuel T. Ojetola

“…This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. …”
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An adaptive processing model for large superalloy pipeline components by LUO Ziyan, QIN Xiansheng, WANG Zhanxi, LIU Weiwei, LI Shulu

“…Precision machining of superalloy curved surface components is an important way to achieve the weight reduction of the aerospace engine’s gas pipeline system. …”
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Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising by Rudy Gunawan, Yvonne Tran, Jinchuan Zheng, Hung Nguyen, Rifai Chai

“…Evaluating the results of image denoising algorithms in Computed Tomography (CT) scans typically involves several key metrics to assess noise reduction while preserving essential details. …”
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Laparoscopic Surgeries in Pediatric Abdominal Surgical Emergencies by Elena Yu. D’yakonova, Aleksandr Yu. Razumovskii, Abdumanap B. Alkhasov, Alexander A. Baranov, Leyla S. Namazova-Baranova, Aleksandr S. Bekin, Aleksei А. Gusev, Ekaterina A. Romanova

“…The possible risks of laparoscopic access and methods for their reduction were analyzed. The advantages of this technique were specified in comparison with open surgical interventions. …”
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Improved Remote Photoplethysmography Using Machine Learning-Based Filter Bank by Jukyung Lee, Hyosung Joo, Jihwan Woo

“…In this study, we propose a machine learning-based filter bank (MLFB) noise reduction algorithm to improve the quality of rPPG signals. …”
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Design of a Lifting Robot for Repetitive Inter-Floor Material Transport with Adjustable Gravity Compensation by Byungseo Kwak, Seungbum Lim, Jungwook Suh

“…Manipulator-based robotic systems have been explored as alternatives; however, they require complex control algorithms and struggle with confined construction environments. …”
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An Improved NSGA‐III With Hybrid Crossover Operator for Multi‐Objective Optimization of Complex Combined Cooling, Heating, and Power Systems by Lejie Ma, Dexuan Zou

“…NSGAIII‐AC‐GM delivers a 20% reduction in operational costs and a 10% decrease in CO2 emissions, outperforming seven other algorithms in optimization efficiency on DTLZ and IMOP problems. …”
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Natural gas bi-level demand response strategies considering incentives and complexities under dynamic pricing by Huibin Zeng, Jie Zhou, Hongbin Dai

“…Abstract As global energy demand rises and carbon reduction targets intensify, natural gas is gaining prominence as a clean energy source. …”
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Multi energy dynamic soaring trajectory optimization method based on reinforcement learning by ZHANG Yunfei, WANG Honglun, ZHANG Menghua, GONG Yinan

“…On the foundation of the trained policies, the method utilizes the twin delayed deep deterministic policy gradient algorithm for policy enhancement. This significantly boosts the real-time inference capabilities while addressing the challenges traditional optimal control algorithms face in dynamic soaring due to varying wind fields. …”
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Asymptotic Approximation of the Stationary Solution with Internal Layer for FitzHugh–Nagumo System by A. A. Melnikova, R. L. Argun

“…Blood clotting, nerve impulse propagation, reduction of the heart muscle, the pattern-formation in nature are auto-wave processes. …”
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Dynamic Skin: A Systematic Review of Energy-Saving Design for Building Facades by Jian Wang, Shengcai Li, Peng Ye

“…Parametric modeling, computer simulation, and multi-objective algorithms are commonly used to optimize the performance of dynamic skin. …”
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