SkinSage XAI: An explainable deep learning solution for skin lesion diagnosis by Geetika Munjal, Paarth Bhardwaj, Vaibhav Bhargava, Shivendra Singh, Nimish Nagpal

“…While deep learning algorithms have greatly enhanced the categorization of skin lesions, the black‐box nature of many models limits interpretability, posing challenges for dermatologists. …”
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DANC-Net: Dual-Attention and Negative Constraint Network for Point Cloud Classification by Hang Sun, Yuanyue Zhang, Jinmei Shi, Shuifa Sun, Guanqun Sheng, Yirong Wu

“…Experiments demonstrate that the DANC-Net achieves better classification performance than the existing point cloud classification algorithms on synthetic datasets ModelNet10 and ModelNet40 and real-scene dataset ScanObjectNN. …”
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High‐Precision Prediction of Ionospheric TEC in the China Region Based on CMONOC High‐Resolution Data and an Auxiliary Attention Temporal Convolutional Network by Jianghe Chen, Pan Xiong, Haochen Wu, Xiaoran Zhang, Xuemin Zhang, Rongzi Chai, Ting Zhang, Kaixin Wang, Chaoyu Wang

“…At the data level, a non‐integrated spherical harmonic model and Differential Code Bias correction method are employed to significantly reduce interpolation errors and improve model accuracy. …”
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Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

“…IoT devices only contribute model updates, which are then combined to improve the global model. …”
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Multi-label classification for image tamper detection based on Swin-T segmentation network in the spatial domain by Li Li, Kejia Zhang, Jianfeng Lu, Shanqing Zhang

“…The experimental findings demonstrate that the proposed model enhances the IoU index by 13% compared to the leading algorithms. …”
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Modulating gene expression as a strategy to investigate thyroid cancer biology by Diego Claro de Mello, Joice Moraes Menezes, Antonio Tarelo Freitas de Oliveira, Marcella Maringolo Cristovão, Edna Teruko Kimura, Cesar Seigi Fuziwara

“…This strategy has evolved methodologically due to advances in cloning approaches, modeling/algorithms in short hairpin RNA (shRNA) design for knockdown efficiency, and biochemical modifications in RNA synthesis, among other developments. …”
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Application of state of health estimation and remaining useful life prediction for lithium-ion batteries based on AT-CNN-BiLSTM by Feng-Ming Zhao, De-Xin Gao, Yuan-Ming Cheng, Qing Yang

“…Comparative analysis with hybrid neural network algorithms such as LSTM, BiLSTM, and CNN-LSTM confirms the proposed model’s high accuracy and stability in SOH estimation and RUL prediction.…”
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Optimizing coverage in wireless sensor networks using deep reinforcement learning with graph neural networks by G. Pushpa, R. Anand Babu, S. Subashree, S. Senthilkumar

“…This integration significantly improves network adaptability and operational efficiency. …”
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Application and prospects of machine learning for rockfalls, landslides and debris flows by Jiazhu WANG, Yongbo TIE, Yongjian BAI, Yanchao GAO, Donghui WANG, Mingzhi ZHANG

“…Future research should prioritize enhancing data quality and quantity, optimizing model interpretability, improving model reliability and generalization, and establishing real-time monitoring and warning systems for automatic identification and rapid response to geological hazards. …”
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Systematic Review: Malware Detection and Classification in Cybersecurity by Sebastian Berrios, Dante Leiva, Bastian Olivares, Héctor Allende-Cid, Pamela Hermosilla

“…These studies cover a variety of detection techniques, including machine learning, deep learning and hybrid models, with a focus on feature extraction, malware behavior analysis and the application of advanced algorithms to improve detection accuracy. …”
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Fusing LiDAR and Photogrammetry for Accurate 3D Data: A Hybrid Approach by Rytis Maskeliūnas, Sarmad Maqsood, Mantas Vaškevičius, Julius Gelšvartas

“…The main contribution of this paper is the development of an innovative fusion system that combines classical algorithms, such as Structure from Motion (SfM), with advanced machine learning techniques, like Coherent Point Drift (CPD) and Feature-Metric Registration (FMR), to improve point cloud alignment and fusion. …”
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Fast Multimodal Trajectory Prediction for Vehicles Based on Multimodal Information Fusion by Likun Ge, Shuting Wang, Guangqi Wang

“…Comparative experiments with existing advanced algorithms demonstrate that our method improves the minimum Average Displacement Error (minADE), minimum Final Displacement Error (minFDE), and Miss Rate (MR) by 10.3%, 10.3%, and 14.5%, respectively, compared to the average performance. …”
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COVID-19 Detection from Computed Tomography Images Using Slice Processing Techniques and a Modified Xception Classifier by Kenan Morani, Esra Kaya Ayana, Dimitrios Kollias, Devrim Unay

“…This paper extends our previous method for COVID-19 diagnosis, proposing an enhanced solution for detecting COVID-19 from computed tomography (CT) images using a lean transfer learning-based model. To decrease model misclassifications, two key steps of image processing were employed. …”
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Automated Vertebral Bone Quality Determination from T1-Weighted Lumbar Spine MRI Data Using a Hybrid Convolutional Neural Network–Transformer Neural Network by Kristian Stojšić, Dina Miletić Rigo, Slaven Jurković

“…The trained model performed similarly to state-of-the-art lumbar spine segmentation models, with an average DSC value of 0.914 ± 0.007 for the vertebrae and 0.902 for the spinal canal. …”
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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

“…Additionally, SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) were employed to elucidate model predictions, improving transparency and trustworthiness. …”
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Optimization design of structural parameters of fan diaphragm coupling under the high torque by SUN Jiaxin, CAI Anwen, HU Weihui, DU Jing, SUN Weiwei, QIN Zhongzheng

“…Therefore, a parameterized model of fan couplings was established through finite element analysis software Abaqus to explore the mechanical performance of nonlinear structures of fan diaphragm couplings under high torque and large deformation conditions.MethodsThe reliability of the simulation results was verified by analyzing the finite element stress results of the global model of the fan coupling. …”
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Development of Robust CNN Architecture for Grading and Classification of Renal Cell Carcinoma Histology Images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

“…Compared to the best-performing state-of-the-art model the accuracy of RoCNN shows a significant improvement of about 4.22% and 3.01% for both datasets respectively.…”
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IRWT-YOLO: A Background Subtraction-Based Method for Anti-Drone Detection by Xueqi Cheng, Fan Wang, Xiaopeng Hu, Xinrong Wu, Min Nuo

“…To effectively separate low-contrast weak drone objects from complex backgrounds, the IRWT-YOLO model is proposed, in which image segmentation algorithms are leveraged to reduce background interference. …”
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A secure and efficient user selection scheme in vehicular crowdsensing by Min Zhang, Qing Ye, Zhimin Yuan, Kaihuan Deng

“…The model uses PCA for data dimensionality reduction to eliminate redundant information and then employs LSTM to process time series data, capture long-term dependencies for more accurate user credit prediction, screen high-quality users, and improve perceived data quality. …”
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Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis by Hanglin Cheng, Yihao Li, Ruiheng Zhang, Weiguang Zhang

“…Traditional Foreign Object Debris (FOD) detection methods face challenges such as difficulties in large-size data acquisition and the ineffective application of detection algorithms with high accuracy. In this paper, image data augmentation was performed using generative adversarial networks and diffusion models, generating images of monitoring areas under different environmental conditions and FOD images of varied types. …”
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