Development of G–Ag and C–Ag Nanoparticle‐Based Biosensor for Benzoic Acid Detection by Mehmet Selcuk Erdogan, Muhammed Bekmezci, Nihal Yigit Ertas, Ramazan Bayat, Fatih Sen

“…In this study, an efficient electrochemical sensor for the highly sensitive detection of benzoic acid (BA) is developed using silver nanoparticles (Ag NPs) obtained by two different methods: the green synthesis method (G–Ag) and the chemical synthesis method (C–Ag). …”
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Advancing sustainable mobility: Dynamic predictive modeling of charging cycles in electric vehicles using machine learning techniques and predictive application development by Biplov Paneru, Durga Prasad Mainali, Bishwash Paneru, Sanjog Chhetri Sapkota

“…The considered models are gradient boosting, random forests, decision trees, and linear regression. Each of these was assessed based on its R-squared score, which is an important statistical measure in indicating the variance proportion yielded by the model. …”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

“…These improvements are achieved within a tolerable training time, making our method both efficient and effective for real-world NSS prediction tasks.…”
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Quick-Response Model for Pre- and Post-Disaster Evacuation and Aid Distribution: The Case of the Tula River Flood Event by Francisca Santana-Robles, Eva Selene Hernández-Gress, Ricardo Martínez-López, Isidro Jesús González-Hernández

“…<i>Background</i>: In the context of humanitarian logistics, efficiently evacuating people from disaster-stricken areas is a complex challenge. …”
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Experimental analysis of genetic algorithm-enhanced PI controller for power optimization in multi-rotor variable-speed wind turbine systems by Habib Benbouhenni, Nicu Bizon, Mourad Yessef, Z. M. S. Elbarbary, Ilhami Colak, Badre Bossoufi, Abdulrahmane Al Ayidh

“…Abstract The direct power control (DPC) algorithm is one of the most popular linear techniques used to implement notable controllers, known for their simplicity and fast dynamic response. …”
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Volatility characteristics and hyperspectral-based detection models of diesel in soils by Jihye Shin, Jaehyung Yu, Jihee Seo, Lei Wang, Hyun-Cheol Kim

“…This study developed an efficient method using hyperspectral camera for detecting diesel content in soils with spectral indices. …”
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Study on flow characteristics of pneumatic conveying of stiff shotcrete materials by CFD-DEM by Hui Ma, Guanguo Ma, Zhenjiao Sun, Kang Gao, Lianjun Chen

“…Key results reveal a linear correlation between feeding rate and minimum conveying velocity, while elbow spacing >1.5 m prevents flow instability. …”
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Large-Scale Hyperspectral Image-Projected Clustering via Doubly Stochastic Graph Learning by Nian Wang, Zhigao Cui, Yunwei Lan, Cong Zhang, Yuanliang Xue, Yanzhao Su, Aihua Li

“…Meanwhile, when using label propagation, pixel-level clustering results are obtained. An efficient optimization strategy is proposed to solve our HPCDL model, requiring monomial linear complexity concerning the number of pixels. …”
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High voltage direct current system-based generation and transmission expansion planning considering reactive power management of AC and DC stations by Ehsan Akbari, Ahad Faraji Naghibi, Mehdi Veisi, Sasan Pirouzi, Sheila Safaee

“…The scheme incorporates a non-linear model. The Red Panda Optimization (RPO) is utilized to solve the provided model in order to attain a dependable and optimal solution. …”
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Multi-factor optimization for electric bus charging stations: Integrating electrical, social, and environmental perspectives by Mustafa Nurmuhammed, Ozan Akdağ, Teoman Karadağ, Maged Kafafy˘

“…The energy consumption of the EBs is calculated by linear modeling method using ten parameters. To test the applicability and effectiveness of the proposed method, IEEE-33 and IEEE-69 bus systems are modified in accordance with EBs, and the distances between the stops are set as routes. …”
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Malaria Disease Prediction Based on Convolutional Neural Networks by Dhrgam AL Kafaf, Noor N. Thamir, Samara S. AL-Hadithy

“…The architectonics of the CNN model is meticulously devised, comprising of six blocks and three interconnected blocks, thereby rendering an efficient extraction of features and subsequent classification of the cells. …”
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Humans self-organise balance control strategies on a dynamic platform by Naser Taleshi, Amid Kheirandish, James M. W. Brownjohn, Sarah E. Lamb, Genevieve K. R. Williams

“…The emergent behaviour involves non-linear transitions from ankle to knee strategy, followed by transition in the relative motion between the centre of pressure and centre of mass as platform frequency increases. …”
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Second-Order Cone Programming for Linepack in Multistage Stochastic Co-Expansion Planning Power and Natural Gas Systems with Natural Gas Storage by Arash Gholami, Hamed Nafisi, Hossein Askarian-Abyaneh, Ali Jahanbani Ardakani, Zahra Shad

“…Therefore, co-expansion planning is imperative for having efficient systems with minimum cost. In this paper, multistage stochastic co-expansion planning power and natural gas systems is presented. …”
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Wind speed prediction for trains on bridges using enhanced variational mode decomposition assisted feature extraction and physical auxiliary mechanism by Zhilan Zhu, Yuan Jiang, Haicui Wang, Shuoyu Liu

“…However, given the intricate nature of its characteristics, which encompass linearity, nonlinearity, nonstationarity etc., accurately predicting the short-term wind speed presents a notable obstacle. …”
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Time-Frame Integrate-and-Fire Neuron Circuit for Low Energy Inference Hardware Spiking Neural Networks by Yeonwoo Kim, Bosung Jeon, Jonghyuk Park, Woo Young Choi

“…Hardware spiking neural networks (SNNs) are gaining increasing attention as promising next-generation computing approaches owing to their parallel computing and energy-efficient nature. Recent SNNs have achieved excellent performance by introducing artificial neural networks (ANN) to the SNN conversion training method. …”
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Genome-Wide Association Study of Seed Quality and Yield Traits in a Soybean Collection from Southeast Kazakhstan by Botakoz Doszhanova, Alibek Zatybekov, Svetlana Didorenko, Chao Fang, Saule Abugalieva, Yerlan Turuspekov

“…The multiple-locus mixed linear model (MLMM) facilitated the identification of 38 stable MTAs: nine for protein content, nine for oil content, seven for the number of fertile nodes, six for the number of seeds per plant, four for thousand seeds weight, and three for yield per plant. …”
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AI-driven kinematics and experimental control of 3-SRR mechanism for UAV stabilization by Mohamad Haidar Chamas, Semaan Amine, Eddie Gazo-Hanna, Mohamed El-Gohary

“…Using extensive data gathered from Simscape simulations, an ANN predicts the desired joint angles, successfully solving the non-linear equations associated with inverse kinematics. …”
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An Adaptive Prediction Framework of Ship Fuel Consumption for Dynamic Maritime Energy Management by Ya Gao, Yanghui Tan, Dingyu Jiang, Peisheng Sang, Yunzhou Zhang, Jie Zhang

“…Accurate prediction of fuel consumption is critical for achieving efficient and low-carbon ship operations. However, the variability of the marine environment introduces significant challenges, as it leads to dynamic changes in monitoring data, complicating real-time and precise fuel consumption prediction. …”
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A statistically predictive heat transfer rate model in a radiative magnetized hybrid nanofluid flow with dissipation over a sheet elongating exponentially: Combined RSM &amp; ANOVA by Rupa Baithalu, S.R. Mishra, Subhajit Panda

“…The predictive model demonstrates several applications in various in industrial processes, including efficient thermal regulating systems utilizing magnetic and porosity. …”
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Measurement and Decoupling of Hygrothermal-Mechanical Effects with Optical Fibers: Development of a New Fiber Bragg Grating Sensor by Pietro Aceti, Lorenzo Calervo, Paolo Bettini, Giuseppe Sala

“…A theoretical framework based on linear strain superposition and constitutive laws was developed to isolate the individual contributions of each factor. …”
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