A Machine Learning-Based Method for Lithology Identification of Outcrops Using TLS-Derived Spectral and Geometric Features by Yanlin Shao, Peijin Li, Ran Jing, Yaxiong Shao, Lang Liu, Kunpeng Zhao, Binqing Gan, Xiaolei Duan, Longfan Li

“…Results demonstrate that the integration of spectral and geometric features significantly improves classification performance, with the Macro F1-score increasing from 0.65 (with single-feature input) to 0.82. …”
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Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer by Weihua Tang, Huadong Chen, Peijun Liu, Yunxuan Zhang, Yunxuan Zhang

“…Logistic regression analysis was employed to identify independent risk factors for FOP. Radiomics features were extracted from CT images of FOP patients, and the Lasso method was used to select key radiomics features and calculate CT radiomics scores. …”
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Comparative Analysis of MVVM and MVP Patterns Performance on Android Dashboard System by Fajar Pradana, Raziqa Izza Langundi, Djoko Pramono, Nur Ida Iriani

“…Developing Android-based applications presents specific challenges, such as the need for responsive designs and optimization for devices with diverse specifications. Design patterns like model-view-controller (MVC), model-view-presenter (MVP), and model-view-viewmodel (MVVM) have become popular approaches to address these issues. …”
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Seismic performance of the replaceable steel links with different short length ratios by Liquan Xiong, Zhengchao Guo, Jun Cai, Kaiyu Jiang, Linyan Li

“…Finally, nonlinear finite element models (FEMs) of test specimens were implemented by the Abaqus software. …”
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Evaluation of machine learning algorithms in tunnel boring machine applications: a case study in Mashhad metro line 3 by Morteza Abbasi, Amir Hossein Namadchi, Mehdi Abbasi, Mohsen Abbasi

“…These findings underscore the practical applications of both simple and complex machine learning models in enhancing TBM performance prediction.…”
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Integrating molecular, biochemical, and immunohistochemical features as predictors of hepatocellular carcinoma drug response using machine-learning algorithms by Marwa Matboli, Marwa Matboli, Hiba S. Al-Amodi, Abdelrahman Khaled, Radwa Khaled, Marwa Ali, Hala F. M. Kamel, Hala F. M. Kamel, Manal S. Abd EL Hamid, Hind A. ELsawi, Eman K. Habib, Eman K. Habib, Ibrahim Youssef

“…A set of performance metrics for the complete and reduced models were reported including accuracy, precision, recall (sensitivity), specificity, and the Matthews Correlation Coefficient (MCC).Results and DiscussionNotably, (NN) achieved the best prediction accuracy where the combined model using molecular and biochemical features exhibited exceptional predictive power, achieving solid accuracy of 0.9693 ∓ 0.0105 and average area under the ROC curve (AUC) of 0.94 ∓ 0.06 coming from three cross-validation iterations. …”
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SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study by Abrar Yaqoob, Navneet Kumar Verma, Mushtaq Ahmad Mir, Ghanshyam G. Tejani, Nashwa Hassan Babiker Eisa, Hind Mamoun Hussien Osman, Mohd Asif Shah

“…Future work will explore the integration of other nature-inspired algorithms and deep learning models to further enhance performance and clinical applicability.…”
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Dual-Branch Seasonal Error Elimination Change Detection Framework Using Target Image Feature Fusion Generator by Hongming Zhu, Jipeng Zhang, Zeju Wang, Xinyu Liu, Qin Liu, Bowen Du

“…The experimental results demonstrate significant improvements in both quantitative and qualitative assessments of change detection tasks compared to directly performing change detection with various models, highlighting the effectiveness of the proposed DBSEE-CDF.…”
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The Quest for the Best Explanation: Comparing Models and XAI Methods in Air Quality Modeling Tasks by Thomas Tasioulis, Evangelos Bagkis, Theodosios Kassandros, Kostas Karatzas

“…In addition, the findings show that SHAP and LIME supported orthogonal insights: SHAP provided a view of the model performance at a high level, identifying interaction effects that are often overlooked using gain-based metrics such as feature importance; while LIME presented an enhanced overlook by justifying its local explanation, providing low-bias estimates of the environmental data values that affect predictions. …”
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Enhancing Real-Time Aerial Image Object Detection with High-Frequency Feature Learning and Context-Aware Fusion by Xin Ge, Liping Qi, Qingsen Yan, Jinqiu Sun, Yu Zhu, Yanning Zhang

“…Aerial image object detection faces significant challenges due to notable scale variations, numerous small objects, complex backgrounds, illumination variability, motion blur, and densely overlapping objects, placing stringent demands on both accuracy and real-time performance. Although Transformer-based real-time detection methods have achieved remarkable performance by effectively modeling global context, they typically emphasize non-local feature interactions while insufficiently utilizing high-frequency local details, which are crucial for detecting small objects in aerial images. …”
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Global–Local Feature Fusion of Swin Kansformer Novel Network for Complex Scene Classification in Remote Sensing Images by Shuangxian An, Leyi Zhang, Xia Li, Guozhuang Zhang, Peizhe Li, Ke Zhao, Hua Ma, Zhiyang Lian

“…While the combination of traditional convolutional neural networks (CNNs) and Transformers has proven effective in extracting features from both local and global perspectives, the multilayer perceptron (MLP) within Transformers struggles with nonlinear problems and insufficient feature representation, leading to suboptimal performance in fused models. …”
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Contextual Deep Semantic Feature Driven Multi-Types Network Intrusion Detection System for IoT-Edge Networks by Shaho Hassen, Ahmed Abdlrazaq

“…The proposed CDS-MNIDS model at first performs network traffic segmentation from the temporal network traces obtained from the network gateway. …”
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Multiclass leukemia cell classification using hybrid deep learning and machine learning with CNN-based feature extraction by Sazzli Kasim, Sorayya Malek, JunJie Tang, Xue Ning Kiew, Song Cheen, Bryan Liew, Norashikin Saidon, Raja Ezman, Raja Shariff

“…MLP-based models also achieved strong results, effectively capturing non-linear patterns in the data. …”
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Assessing above ground biomass of Wunbaik Mangrove Forest in Myanmar using machine learning and remote sensing data by Win Sithu Maung, Satoshi Tsuyuki, Takuya Hiroshima, San San Htay

“…We then set up different scenarios to improve the performance of the RF model for AGB estimation. Through different feature selection approaches, we identified features highly correlated with the field AGB, enhancing the RF model’s performance and resulting in the highest improvement in R2: 0.48 and RMSE: 28.12 Mg ha−1. …”
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Numerical Assessment of the Thermal Performance of Microchannels with Slip and Viscous Dissipation Effects by Pamela Vocale, Gian Luca Morini

“…In the present paper, a numerical analysis of the performance of microchannels featuring rectangular, trapezoidal and double-trapezoidal cross-sections in the slip flow regime is presented. …”
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A Hybrid Adaptive Particle Swarm Optimization Algorithm for Enhanced Performance by Zhengfeng Jiang, Daoheng Zhu, Xiao-Yu Li, Ling-Bo Han

“…To overcome these problems, this paper proposes an enhanced variant featuring adaptive selection. Initially, a composite chaotic mapping model integrating Logistic and Sine mappings is employed to initialize the population for diversity and exploration capability. …”
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GA-VAE: Enhancing Local Feature Representation in VQ-VAE Through Genetic Algorithm-Based Token Optimization by Jinghui Jiang, Dongjoon Kim, Bohyoung Kim, Yeong-Gil Shin

“…While VQ-VAE models have shown promise in learning discrete latent representations for complex data distributions, their performance is often limited by underutilized tokens in the codebook, particularly those representing local features, resulting in incomplete feature capture. …”
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Steel Wire Rope Damage Width Identification Method Based on Residual Networks and Multi-Channel Feature Fusion by Yan Peng, Junde Liu, Junjie He, Yongjun Qiu, Xie Liu, Le Chen, Fengfeng Yang, Bulong Chen, Bin Tang, Yuhan Wang

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Diagnosis of early nitrogen, phosphorus and potassium deficiency categories in rice based on multimodal integration and knowledge distillation by Xuanying Liao, Hongyun Yang

“…The teacher model then performs knowledge distillation on the custom neural network model, resulting in a lightweight model with high accuracy and low memory consumption, which serves as a feature extractor. …”
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Text mining approach for feature extraction and cartilage disease grade classification using knee MRI radiology reports by Antonio Saverio Valente, Teresa Angela Trunfio, Marco Aiello, Dario Baldi, Marilena Baldi, Silvio Imbò, Mario Alessandro Russo, Carlo Cavaliere, Monica Franzese

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