Assessment and Modeling of Green Roof System Hydrological Effectiveness in Runoff Control: A Case Study in Dublin by Mehdi Gholamnia, Payam Sajadi, Salman Khan, Srikanta Sannigrahi, Saman Ghaffarian, Himan Shahabi, Francesco Pilla

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Experiment on Shock Wave Control of a Hypersonic Vehicle Standard Model Based on Plasma Synthetic Jet by Wei XIE, Guotun HU, Wei SHI, Yan ZHOU, Hongbo LU, Zhenbing LUO

“…The control effect of single-pulsed PSJ on head bow shock and wing shock of a hypersonic vehicle model and the drag reduction effect were experimentally studied in a hypersonic wind tunnel. …”
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Control System of an SVC Based on ARMA Model to Improve the Displacement Power Factor of an Electric Arc Furnace by J. Marulanda-Durango, A. Escobar-Mejía, E. Giraldo

“…This paper proposes a multivariable coupled control technique based on an autoregressive moving average (ARMA) model. …”
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Assessing the impact of a potential canine vaccine for the control of Chagas disease: a mathematical modeling study by Edem Fiatsonu, Aniruddha Deka, Martial L. Ndeffo-Mbah, Martial L. Ndeffo-Mbah

“…As dogs are important reservoirs in the disease’s spread, developing a canine vaccine could be transformative for controlling disease transmission to dogs and humans.MethodsWe developed a compartmental Susceptible-Infected model to simulate the transmission dynamics of Trypanosoma cruzi, considering interactions among dogs, humans, cats, rodents, and triatomine vectors. …”
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Modelling epidemiological dynamics with pseudo-recovery via fractional-order derivative operator and optimal control measures. by Samson Olaniyi, Furaha M Chuma, Ramoshweu S Lebelo, Richard C Ogbonna, Sulaimon F Abimbade

“…Consequently, the analysis is extended to the fractional optimal control model where time-dependent preventive strategy and treatment measure are characterized by Pontryagin's maximum principle. …”
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Dynamic Dual-Phase Forecasting Model for New Product Demand Using Machine Learning and Statistical Control by Chien-Chih Wang

“…This research proposes the Dynamic Dual-Phase Forecasting Framework (DDPFF) that amalgamates machine learning-based classification, similarity-driven analogous forecasting, ARMA-based residual compensation, and statistical process control for adaptive model refinement. The framework underwent evaluation through five real-world case studies conducted by a Taiwanese semiconductor tray manufacturer, encompassing a variety of scenarios characterized by high volatility, seasonality, and structural drift. …”
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A novel analysis of two parallel connected inverters for isolated DC microgrid system by using droop controller technology by J. Venumadhav, Durgam Rajababu, CH Hussain Bhasha

“…This model integrates an LCL filter, a droop controller, a voltage controller, and a current controller. …”
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Adapted Speed Control of Two-Stroke Engine with Propeller for Small UAVs Based on Scavenging Measurement and Modeling by Yifang Feng, Tao Chen, Qinwang Liu, Heng Zhao

“…The feed-forward control strategy was built by a simplified crankcase–scavenging–cylinder model with CFD results under different air pressures, demonstrating a 1% error compared with CFD simulation. …”
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High-Precision Image Editing via Dual Attention Control in Diffusion Models Without Fine-Tuning by Zhiqiang Pan, Yingchun Kuang, Jianmei Lan, Lizhuo Zhang

“…Specifically, compared to the editing outcomes under no control conditions, the introduction of dual visual attention control has led to an increase of 6.19% in CLIP scores, a reduction of 29.3% in LPIPS, and a decrease of 24.7% in FID. …”
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Large language model-driven natural language interaction control framework for single-operator bimanual teleoperation by Haolin Fei, Tao Xue, Yiyang He, Sheng Lin, Guanglong Du, Yao Guo, Ziwei Wang

“…To overcome these challenges, we propose a novel bimanual teleoperation large language model assistant (BTLA) framework, an intelligent co-pilot that augments a single operator’s motor control capabilities. …”
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Investing in non-communicable disease risk factor control among adolescents worldwide: a modelling study by David Watkins, Jessica Hale, Brian Hutchinson, Ishu Kataria, Vasilis Kontis, Rachel Nugent

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Dynamics and optimal control of fractional-order monkeypox epidemic model with social distancing habits and public awareness by Raqqasyi Rahmatullah Musafir, Agus Suryanto, Isnani Darti, Trisilowati

“…Meanwhile, public awareness can substantially modify the basic reproduction number, shifting the endemic condition towards a disease-free state, although its impact on case reduction in the early period is not significant. We also implemented optimal control strategies for vector culling and vaccination in the proposed model. …”
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Real-Time Model Predictive Control for Two-Level Voltage Source Inverters with Optimized Switching Frequency by Ariel Villalón, Claudio Burgos-Mellado, Marco Rivera, Rodrigo Zuloaga, Héctor Levis, Patrick Wheeler, Leidy Y. García

“…This paper presents a Finite-Control-Set Model Predictive Control (FCS-MPC) strategy for three-phase, two-level voltage source inverters (VSIs), incorporating a secondary objective for switching frequency minimization. …”
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Frequency Limited & Weighted Model Reduction Algorithm With Error Bound: Application to Discrete-Time Doubly Fed Induction Generator Based Wind Turbines for Power System by Sajid Bashir, Sammana Batool, Muhammad Imran, Mian Ilyas Ahmad, Fahad Mumtaz Malik, Muhammad Salman, Abdul Wakeel, Usman Ali

“…., induction and synchronous generator-based wind turbines, with facts readily available for stability, controllability, and observability analysis. In this article, the model order reduction of a stable doubly fed induction generator based variable-speed wind turbines model is performed with the aid of the proposed stability preserving balanced realization algorithm based on discrete frequency weights and limited frequency-interval. …”
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Data-driven model predictive control for irrigation management in agricultural greenhouses under CO2 enrichment by Ikhlas Ghiat, Rajesh Govindan, Tareq Al-Ansari

“…In this study, a data-driven model predictive control (MPC) is employed within a greenhouse environment to optimise irrigation scheduling. …”
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Evaluation of Machine Learning Models for Stress Symptom Classification of Cucumber Seedlings Grown in a Controlled Environment by Kyu-Ho Lee, Samsuzzaman, Md Nasim Reza, Sumaiya Islam, Shahriar Ahmed, Yeon Jin Cho, Dong Hee Noh, Sun-Ok Chung

“…This study highlights the potential of ML-driven stress symptom detection models for controlled seedling production, enabling real-time decision-making to optimize crop health and productivity.…”
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Nonlinear Model Predictive Yaw Moment Control Through Electric Axle and Friction Brake Torque Distribution by Carmine Caponio, Gaetano Tavolo, Davide Tavernini, Ahu Ece Hartavi Karci, Javad Ahmadi, Basilio Lenzo, Giulio Reina, Giacomo Mantriota, Pietro Perlo, Aldo Sorniotti

“…To address the gap, this paper presents real-time capable nonlinear model predictive controllers (NMPCs) for ATV and ESC, targeting: i) energy consumption reduction in normal driving, through powertrain and tire slip power loss limitation; and ii) yaw rate, sideslip angle and wheel slip control at the limit of handling, by considering the trade-off between powertrain and friction brake actuation. …”
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Original Error Analysis of the Second Reduction Part of RV Reducer by Zheng Yuxin, Xi Ying, Li Mengru, Hua Binbin, Liu Xianhui

“…Through establishing a transmission four bar mechanism model,the relationship between the three components is expressed,and the direct relationship between input angle and output angle of the second reduction part is established. …”
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Identifying Suitability for Data Reduction in Imbalanced Time-Series Datasets by Dominic Sanderson, Tatiana Kalganova

“…This paper demonstrates methods to identify if data may be removed from the imbalanced time-series training datasets to optimise the training process and model performance. It also describes how the calculation of the class density of a dataset may be used to identify if a dataset is applicable for data reduction, and how dataset fusion may be used to combine occupancy datasets. …”
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Advancements in Wind Farm Control: Modelling and Multi-Objective Optimization Through Yaw-Based Wake Steering by Tiago R. Lucas Frutuoso, Rui Castro, Ricardo B. Santos Pereira, Alexandra Moutinho

“…The findings underscore the need for integrated approaches that combine physics-based models, AI techniques, and instrumentation to fully leverage the potential of wind farm control.…”
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