Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…These improvements highlight the model’s ability to assimilate diverse climatic and topographical inputs for more accurate rainfall prediction, particularly in areas where conventional methods fall short due to sparse or irregular precipitation. …”
Get full text

Research on Method for Intelligent Recognition of Deep-Sea Biological Images Based on PSVG-YOLOv8n by Dali Chen, Xianpeng Shi, Jichao Yang, Xiang Gao, Yugang Ren

“…These performance metrics represent improvements of 1.2%, 2.3%, and 1.1%, respectively, over the baseline YOLOv8n model. …”
Get full text

A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…Furthermore, as the extrapolation time increases, the smoothing effect inherent to convolution operations leads to increasingly blurred predictions. To address the algorithmic limitations of deep learning-based echo extrapolation models, this study introduces three major improvements: (1) A Deep Convolutional Generative Adversarial Network (DCGAN) is integrated into the ConvLSTM-based extrapolation model to construct a DCGAN-enhanced architecture, significantly improving the quality of radar echo extrapolation; (2) Considering that the evolution of radar echoes is closely related to the surrounding meteorological environment, the study incorporates specific physical variable products from the initial zero-hour field of RMAPS-NOW (the Rapid-update Multiscale Analysis and Prediction System—NOWcasting subsystem), developed by the Institute of Urban Meteorology, China. …”
Get full text

Advancing Sika deer detection and distance estimation through comprehensive camera calibration and distortion analysis by Sandhya Sharma, Stefan Baar, Bishnu P. Gautam, Shinya Watanabe, Satoshi Kondo, Kazuhiko Sato

“…The calculated coefficients successfully corrected these distortions, improving image accuracy. The derived coefficients effectively corrected these distortions, improving image accuracy. …”
Get full text

Automatic construction of global cloud sample database based on Landsat imagery by Tao He, Guihua Huang, Lei Zhang, Daiqiang Wu, Yichuan Ma

“…The results showed that the overall accuracies of models trained on UAC-CSD sample database were basically higher than models trained on Fmask4.0, and computational efficiencies were also greatly improved. …”
Get full text

Radiomic Analysis of Contrast‐Enhanced CT Predicts Recompensation in Hepatitis B‐Related Decompensated Cirrhosis by Qiaofeng Chen, Yuanping Fan, Kaini Wu, Tianpan Cai, Chunyu Lan, Mingju Yu, Yunfeng Fu, Qi Zhu, Jianhao Qiu, Xiaodong Zhou

“…ABSTRACT Aims Accurately predicting recompensation in patients with decompensated hepatitis B‐related cirrhosis is crucial for guiding treatment strategies. As a reliable model for accurately predicting recompensation is currently lacking, this study aimed to develop a contrast‐enhanced computed tomography (CECT) radiomics model specifically for assessing recompensation outcomes in this patient population. …”
Get full text

MSF-GhostNet: Computationally Efficient YOLO for Detecting Drones in Low-Light Conditions by Maham Misbah, Misha Urooj Khan, Zeeshan Kaleem, Ali Muqaibel, Muhamad Zeshan Alam, Ran Liu, Chau Yuen

“…We also integrated autoanchor and batch size mechanisms to ensure efficient model training and avoid overfitting. Our proposed model showed 1.25% fewer false positives than the state-of-the-art GhostNet-YOLOv5 model. …”
Get full text

Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
Get full text

A survey of sand-dust image visual enhancement techniques by SI Yazhong, ZHANG Xulong, YANG Fan, WANG Jianzong, CHENG Ning, XIAO Jing

“…The visual enhancement technology of sandstorm images aims to improve the visual perception clarity of the captured data by imaging equipment under sandstorm weather, assisting high-level vision algorithms to enhance the ability to obtain key features from the data. …”
Get full text

Innovative Sandia Frequency Shift Islanding Detection for Microgrids Using Interval Type-II Fuzzy Logic and VP-PSO Optimization by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Yeonwoo Lee, Sun-Kyoung Kang, Ilhami Colak, El Manaa Barhoumi, Kei Eguchi

“…The proposed approach further integrates a variable-parameter PSO (VP-PSO) algorithm to optimize both fuzzy membership functions and controller parameters. …”
Get full text

Adaptive sliding mode control based on maximum power point tracking for boost converter of photovoltaic system under reference voltage optimizer by Borhen Torchani, Ahmad Taher Azar, Ahmad Taher Azar, Ahmad Taher Azar, Anis Sellami, Saim Ahmed, Saim Ahmed, Ibrahim A. Hameed, Ibraheem Kasim Ibraheem, Moamin Ibrahim Jameel Al-Obaidi

“…Simulations conducted demonstrate superior performance in terms of stability, speed, and control of the converter compared to traditional MPPT algorithms. The main contributions of this article include an improvement in system robustness against irradiance variations, thanks to the integration of an adaptive algorithm and a PI controller within the SMC. …”
Get full text

Design Optimization of Compliant Mechanisms for Vibration- Assisted Machining Applications Using a Hybrid Six Sigma, RSM-FEM, and NSGA-II Approach by Huy-Tuan Pham, Van-Khien Nguyen, Quang-Khoa Dang, Thi Van Anh Duong, Duc-Thong Nguyen, Thanh-Vu Phan

“…Vibration-assisted machining, a hybrid processing method, has been gaining considerable interest recently due to its advantages, such as increasing material removal rate, enhancing surface quality, reducing cutting forces and tool wear, improving tool life, or minimizing burr formation. …”
Get full text

Charting γ-secretase substrates by explainable AI by Stephan Breimann, Frits Kamp, Gabriele Basset, Claudia Abou-Ajram, Gökhan Güner, Kanta Yanagida, Masayasu Okochi, Stephan A. Müller, Stefan F. Lichtenthaler, Dieter Langosch, Dmitrij Frishman, Harald Steiner

“…Our approach outperforms state-of-the-art protein language models, improving prediction accuracy from 60% to 90%, and achieves an 88% success rate in experimental validation. …”
Get full text

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. …”
Get full text

Analysis of disease severity and mortality prediction using machine learning during COVID-19 by Hodjat (Hojatollah) Hamidi, Mostafa Moradi

“…This paper focuses on how machine learning (ML) algorithms and applications have been used to analyze disease severity and mortality prediction in COVID-19 research. …”
Get full text

Using machine learning methods to investigate the role of volatile organic compounds in non-alcoholic fatty liver disease by Chih-Hao Shen, Ruei-Hao Huang, Yaw-Kuen Li, Ta-Wei Chu, Ta-Wei Chu, Dee Pei, Dee Pei

“…The addition of VOCs to Model 1 improved the AUC from 0.722 ± 0.149 to 0.770 ± 0.264 (p < 0.001). …”
Get full text

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. …”
Get full text

The Impact of Snow Cover on River Discharge Simulation: Insights from the Barandozchay River Basin by Haleh Hashemi, Hossein Rezaie, Keivan Khalili, Amin Amini

“…Conversely, the RF model experienced an increase in error for the test data, but the correlation coefficient R2 improved from 0.85 to 0.88. …”
Get full text

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.…”
Get full text

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. …”
Get full text