Cross-Modal Object Detection Based on Content-Guided Feature Fusion and Self-Calibration by Liyang Ning, Xuxun Liu, Luoyu Zhou, Xueyu Zou

“…To address these issues, we propose a dual-backbone cross-modal object detection model based on YOLOv8n. First, we introduce a parallel network in the backbone to enable the model to process information from different modalities simultaneously. …”
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Tipping cascades between conflict and cooperation in climate change by J. Scheffran, W. Guo, F. Krampe, U. Okpara

“…System and agent models of conflict and cooperation are considered to analyse dynamic trajectories, equilibria, stability, and chaos, along with adaptive decision rules in multi-agent interaction and related tipping, cascading, networking, and transformation processes. …”
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PSO-optimised autoencoder for fault prediction in wind turbine planet carrier bearing by Samuel M. Gbashi, Obafemi O. Olatunji, Paul A. Adedeji, Nkosinathi Madushele

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Resilient Operation Strategies for Integrated Power-Gas Systems by Behdad Faridpak, Petr Musilek

“…The uncertainties of HILP events are modeled by different moment-based probability distributions. …”
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Interlayer Dzyaloshinskii-Moriya interaction in spintronics by Xupeng Zhao, Jianhua Zhao

“…Abstract The indirect interlayer exchange coupling (IEC) between two magnetic layers holds significant importance in development of spintronics. …”
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Surface Micro-Reflector Array for Augmented Reality Display by Zhanjun Yan, Chunlei Du, Lixin Zhang

“…The imaging process of optical system is modeled and simulated. …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…Further the model goes through two level optimization process where optimal hyperparameters identified through experimentation is given as parameters to genetic algorithm for optimization of VCNet during training. …”
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The effect of microflocculant MBFA9 and the mechanism of Pb(II) and Zn(II) removal from an aqueous solution by Jiaqi Zhang, Binhui Jiang, Bo Zhang, Yu Li, Ping Fang and, Xiaomin Hu

“…Both the adsorption kinetics and adsorption equilibrium, usually described as adsorption isotherms, showed that this process of Pb(II) or Zn(II) capture by MBFA9 involved simple adsorption of a single molecular layer. …”
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Aging-Friendly Design Research: Knowledge Graph Construction for Elderly Advantage Applications by Xiaoying Li, Xingda Wang, Guangran Li

“…Next, the elderly advantages knowledge graph was constructed by following these steps: (1) The KJ-AHP method was used to process raw data, making them structured and quantitative. (2) The ontology of the knowledge graph was reverse-engineered based on the functional requirements of the graph, allowing the construction of the knowledge graph model layer. (3) The processed data were applied to the knowledge graph ontology through AHP-ontology mapping rules, allowing the knowledge content construction. (4) The programming language Cypher was used for the functional verification of the elderly advantages knowledge graph, and a satisfaction survey was conducted through questionnaires to assess the verification process. …”
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A Malware Detection Method Based on Genetic Algorithm Optimized CNN-SENet Network by Zheng Yang, Hua Zhu, Zhao Li, Gang Wang, Meng Su

“…To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. …”
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Low frequency oscillations – neural correlates of stability and flexibility in cognition by Julia Ericson, Nieves Ruiz Ibáñez, Mikael Lundqvist, Torkel Klingberg

“…The model, featuring spiking and oscillatory cortical layers interacting via phase-amplitude coupling, demonstrated how frequency and spatial region could modulate information flow. …”
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Multi-scale conv-attention U-Net for medical image segmentation by Peng Pan, Chengxue Zhang, Jingbo Sun, Lina Guo

“…The AC module dynamically adjusts the convolutional kernel through an adaptive convolutional layer. This enables the model to extract features of different shapes and scales adaptively, further improving its performance in complex scenarios. …”
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A novel deep reinforcement learning‐based algorithm for multi‐objective energy‐efficient flow‐shop scheduling by Peng Liang, Pengfei Xiao, Zeya Li, Min Luo, Chaoyong Zhang

“…Furthermore, the state features of NFSP are extracted using a multi‐layer perceptron model based on BiRNNs. By utilising the TD(λ) algorithm to calculate the state value function, various policies are generated. …”
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Investigation of the dynamic charge transport behaviours under electron beam irradiation of advanced insulation materials for aerospace applications by Guangyu Sun, Xiong Yang, Wentong An, Kun Huang, Xiaogang Qin, Baipeng Song, Guanjun Zhang

“…The model‐predicted sample current, SEY and surface potential, in a surface layer of 1 μm and with incident electron energy range of 10–30 keV, are compared with the experiments, showing qualitative agreement. …”
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Using the diel cycle of ocean microbes to better understand their biogeochemical functions by Philip W. Boyd, Benjamin A. S. Van Mooy

“…A better understanding of the diel cycle provides a holistic framework with which to align patterns and causal sequences across multi‐omic layers, yielding consequent connections with metabolic processes to develop more robust mechanistic models. …”
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Theoretical explanation and regulation method for the edge effect in the sintered joints of metal nanoparticles by Guannan Yang, Zebo Li, Zhihao Zhang, Junyi Lu, Yu Zhang, Guanghan Huang, Tianshuo Zhao, Chengqiang Cui

“…With this understanding, a geometrically constrained sintering process is further proposed to mitigate the edge effect by using a pre-cured resin sealing layer around the chip edges to suppress the lateral flow of the metal nanoparticle slurry. …”
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Enhancing tool condition monitoring in friction stir welding with probabilistic neural network algorithm by Balachandar Krishnamurthy, Jegadeeshwaran Rakkiyannan

“…A feature importance study is conducted using a decision tree algorithm, which selects only the most significant features to reduce computational complexity.ResultFeature classification is then performed using various machine learning and deep learning algorithms, including Support Vector Machines (SVM), Multi-Layer Perceptron (MLP), Cascade Correlation, GMDH Polynomial Neural Networks, and Linear Discriminant Analysis Among these classifiers, Probabilistic Neural Networks (PNN) consistently deliver the best results as 91.25% under 1,400 rpm.DiscussionBased on these findings, the Probabilistic Neural Network algorithm is identified as a robust and reliable prediction model for monitoring FSW tool conditions.…”
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Features of solving the problem of condensation of vapor containing solid particles on the edge by N. D. Yakimov, A. V. Dmitriev, G. R. Badretdinova, S. D. Borisova

“…To evaluate the effect on the condensation process of contaminants contained in the steam and deposited on the surface of the cooled fins, for which to formulate a mathematical model of the process, to investigate its properties and to obtain quantitative estimates of the characteristics.METHODS. …”
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Multiple Feature Vectors Based Fault Classification for WSN Integrated Bearing of Rolling Mill by Bo Qin, Luyang Zhang, Heng Yin, Yan Qin

“…From the above analysis, the energy index and the singular value matrix are used for fault classification modeling based on the enhanced extreme learning machine (ELM), which is optimized by the bat algorithm to adjust the input weights and threshold of hidden layer node. …”
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Performance Evaluation of Stone Columns in Fine Soil Conditions: A Fem-Based Case Study by Bahman Zarazvand, Jana Frankovska

“…A staged construction approach is implemented to realistically simulate the sequential embankment construction process and its impact over time. To ensure model reliability, validation is performed by comparing numerical results with field measurements obtained from horizontal inclinometers installed beneath the embankment. …”
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