Editorial by Bulent Cavas

“…The ninth article, “Investigating the Effects of Socio-Scientific Issues-Based Learning Module in Enhancing Students’ Physics Knowledge,” by Badeo et al. …”
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Flat vs. Curved: Machine Learning Classification of Flexible PV Panel Geometries by Ahmad Manasrah, Yousef Jaradat, Mohammad Masoud, Mohammad Alia, Khaled Suwais, Piero Bevilacqua

“…A calibration analysis on the ML models showed that Random Forest and XGBoost were well calibrated for the flat-mounted module. However, they also showed overconfidence and underconfidence issues with the curved module geometries.…”
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Vehicle Flow Detection and Tracking Based on an Improved YOLOv8n and ByteTrack Framework by Jinjiang Liu, Yonghua Xie, Yu Zhang, Haoming Li

“…In the detection module, we introduce the innovative MSN-YOLO model, which combines the C2f_MLCA module, the Detect_SEAM module, and the NWD loss function to enhance feature fusion and improve cross-scale information processing. …”
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MULTIMODAL UKRAINIAN BRAND NARRATIVE: SEMIOTICS, STRUCTURE, ARCHETYPES by Nataliia K. Kravchenko, Liudmyla O. Shanaieva-Tsymbal

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Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

“…Combined with the spatial channel convolution (SCConv) to enhance the feature fusion module, the cross-modal interaction between texture and structural features is optimized through a dynamic gating mechanism. …”
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A Novel Trustworthy Toxic Text Detection Method with Entropy-Oriented Invariant Representation Learning for Portuguese Community by Wenting Fan, Haoyan Song, Jun Zhang

“…This module captures a more holistic representation of semantic information by learning both local and global features of texts. …”
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ECVNet: A Fusion Network of Efficient Convolutional Neural Networks and Visual Transformers for Tomato Leaf Disease Identification by Fendong Zou, Jing Hua, Yuanhao Zhu, Jize Deng, Ruimin He

“…Specifically, we first designed a Channel Attention Residual module (CAR module) to focus on channel features and enhance the model’s sensitivity to the importance of feature channels. …”
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Depth-Induced Intra-to-Inter Transformer network for stereoscopic image retargeting by Xiaoting Fan, Long Sun, Zhong Zhang

“…Due to the additional binocular information present between the left and right views in stereoscopic images, the CNN-based stereoscopic image retargeting methods have some obvious limitations in capturing long-range dependencies. To address these issues, we present a depth-induced intra-to-inter Transformer network (DITrans-Net) for stereoscopic image retargeting, which learns the long-range dependencies information between intra-view and inter-view by an intra-to-inter feature extraction module and aggregates the depth information of left view and right view by a depth-induced feature integration module. …”
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Dynamic Bidirectional Feature Enhancement Network for Thin Cloud Removal in Remote Sensing Images by Yu Wang, Hao Chen, Ye Zhang, Guozheng Li

“…First, we design a multidimensional attention module comprising skip-recursive dilated convolution-based spatial attention module and frequency-domain-driven channel attention module. …”
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HAF-YOLO: Dynamic Feature Aggregation Network for Object Detection in Remote-Sensing Images by Pengfei Zhang, Jian Liu, Jianqiang Zhang, Yiping Liu, Jiahao Shi

“…This study proposes a hierarchical adaptive feature aggregation network (HAF-YOLO) to improve detection precision in remote-sensing images. It addresses issues such as small object size, complex backgrounds, scale variation, and dense object distributions by incorporating three core modules: dynamic-cooperative multimodal fusion architecture (DyCoMF-Arch), multiscale wavelet-enhanced aggregation network (MWA-Net), and spatial-deformable dynamic enhancement module (SDDE-Module). …”
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Sparse Attention-Based Residual Joint Network for Aspect-Category-Based Sentiment Analysis by Jooan Kim, Hyunyoung Kil

“…In addition, it employs a residual joint learning framework that connects the aspect category detection (ACD) task module and the ACSA task module via residual connections, enabling the ACSA module to receive explicit guidance on relevant aspect categories from the ACD module. …”
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Road Obstacle Detection Method Based on Improved YOLOv5 by Pengliu Tan, Zhi Wang, Xin Chang

“…Second, the SPPF module is replaced with the C3SPPF module to improve the model’s understanding of contextual information and increase its multi-scale adaptability. …”
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Knowledge graph construction and talent competency prediction for human resource management by Bowen Yang, Zhixuan Shen

“…To address these challenges, we propose a hybrid model that integrates Graph Convolutional Networks (GCN), Reinforcement Learning (RL), and Deep Collaborative Filtering (DCF). The GCN module captures complex multi-relational structures between jobs and candidates, the RL module dynamically optimizes recommendation strategies based on feedback, and the DCF module enhances personalized recommendation capabilities. …”
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Selective transfer learning with adversarial training for stock movement prediction by Yang Li, Hong-Ning Dai, Zibin Zheng

“…Most existing approaches cannot jointly take the above two issues into account and thus cannot yield satisfactory prediction result. …”
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Multi-Head Attention Refiner for Multi-View 3D Reconstruction by Kyunghee Lee, Ihjoon Cho, Boseung Yang, Unsang Park

“…In this paper, we introduce a post-processing method, the Multi-Head Attention Refiner (MA-R), designed to address this issue by integrating a multi-head attention mechanism into the U-Net style refiner module. …”
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Exploiting high-order behaviour patterns for cross-domain sequential recommendation by Bingyuan Wang, Baisong Liu, Hao Ren, Xueyuan Zhang, Jiangcheng Qin, Qian Dong, Jiangbo Qian

“…Moreover, to simultaneously improve the recommendation performance in the two domains, a Cross-domain Feature Bidirectional Transfer module (CFBT) is proposed, transferring user's common sharing features in both domains and retaining user's domain-specific features in a specific domain. …”
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An Advanced Local Current-Only Protection for Microgrids: Deep-Learning-Based Approach by Amin Yazdaninejadi, Hossein Ebrahimi, Sajjad Golshannavaz

“…Notably, the operation of on-load tap-changers (OLTCs) can lead to the maloperation of overcurrent relays during both internal and external faults due to the altered fault current levels. This issue, combined with diverse operational conditions and other N-1 contingencies, further broadens the scope of undesirable operations. …”
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A small‐target traffic sign detection algorithm based on partial conv and atrous spatial pyramid by Yuqi Li, Zijian Wang, Han Zhang, Xinpeng Yao, Zhou Zhou, Xin Cheng

“…The deep learning‐based algorithm proposed in this paper aims to address the issue of low detection accuracy caused by the small size and high density of traffic signs in real‐world traffic scenarios. …”
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Vision-inertial collaborative localization of multi-agents with remote interaction by Chang Liu, Jin Zhao, Nianyi Sun

“…Additionally, we tackle the issue of scale ambiguity in visual-inertial collaborative localization. …”
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Preference-based expensive multi-objective optimization without using an ideal point by Peipei Zhao, Liping Wang, Qicang Qiu

“…This paper proposes a preference-based surrogate-assisted algorithm, PMEGO, to overcome this issue. In the preference management module, a set of new reference points derived from the user reference point is used to construct a series of subproblems, with the key merit of not using the ideal point. …”
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