A Lightweight Model for Small-Target Pig Eye Detection in Automated Estrus Recognition by Min Zhao, Yongpeng Duan, Tian Gao, Xue Gao, Guangying Hu, Riliang Cao, Zhenyu Liu

Get full text

Extracting Meso- and Microscale Patterns of Urban Morphology Evolution: Evidence from Binhai New Area of Tianjin, China by Xiaojin Huang, Ran Cheng, Jun Wu, Wenjian Yang, Longhao Zhang, Pengbo Li, Wenzhe Zhu

“…The results indicate that in the stock development phase, high-density urban areas exhibit multidimensional development characteristics by region, period, and function. Our work demonstrates the potential of using deep learning and grid classification indicators to study meso-/microscale urban morphology evolution, providing a scalable, cost-effective, quantitative, and portable approach for historical urban morphology understanding.…”
Get full text

Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease by Tiantian Bai, Mengru Xu, Taotao Zhang, Xianjie Jia, Fuzhi Wang, Xiuling Jiang, Xing Wei

“…This study systematically evaluated the performance of each feature selection algorithm under different population sizes, specifically by comparing their average running time and objective function values to identify the optimal feature subset. …”
Get full text

Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Autoencoder consists of two functions: an encoder function that encodes the input data into a lower-dimensional hidden layer and a decoder function that reconstructs the encoded input data. …”
Get full text

Transformer-based travel time estimation method for plateau and mountainous environments by Guangjun Qu, Kefa Zhou, Rui Wang, Dong Li, Yingpeng Lu, Zhihong Lv, Dequan Zhao, Aijun Zhang, Qing Zhang

“…Abstract Travel time estimation (TTE) is a critical function in intelligent driving systems. Current research and applications related to TTE primarily focus on urban environments. …”
Get full text

Automatic detection and counting of wheat spike based on DMseg-Count by Hecang Zang, Yilong Peng, Meng Zhou, Guoqiang Li, Guoqing Zheng, Hualei Shen

“…Compared with other deep learning models, the proposed DMseg-Count model can detect wheat spike image in challenging situations, and has better computer vision processing capabilities and performance evaluation detection effect. …”
Get full text

Development and validation of a risk prediction model for acute kidney injury in coronary artery disease by Ming Ye, Chang Liu, Duo Yang, Hai Gao

Get full text

Different methods of estimating riverbed sediment grain size diverge at the basin scale by Peter Regier, Yunxiang Chen, Kyongho Son, Jie Bao, Brieanne Forbes, Amy Goldman, Matt Kaufman, Matt Kaufman, Kenton A. Rod, James Stegen, James Stegen

“…IntroductionThe distribution of sediment grain size in streams and rivers is often quantified by the median grain size (D50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual D50 measurements are time-consuming and ignore larger grains, while approaches to model D50 based on catchment characteristics may over-generalize and miss site-scale heterogeneity. …”
Get full text

Sinh-Cosh Optimization-Based Efficient Clustering for Big Data Applications by Lahbib Khrissi, Mohammed Es-Sabry, Nabil El Akkad, Hassan Satori, Saad Aldosary, Walid El-Shafai

“…However, challenges arise in the application of optimization-based techniques, stemming from the non-linear nature of the objective function and the complexities inherent in the search space. …”
Get full text

Seeing Beyond Noise: Improving Cryptocurrency Forecasting with Linear Bias Correction by Sibtain Syed, Syed Muhammad Talha, Arshad Iqbal, Naveed Ahmad, Mohammed Ali Alshara

“…Hyperparameter tuning was performed by trial-and-error technique, and an early stopping function was applied to minimize time and space complexity. …”
Get full text

PAMFPN: Position-Aware Multi-Kernel Feature Pyramid Network with Adaptive Sparse Attention for Robust Object Detection in Remote Sensing Imagery by Xiaofei Yang, Suihua Xue, Lin Li, Sihuan Li, Yudong Fang, Xiaofeng Zhang, Xiaohui Huang

“…Deep learning methods have achieved remarkable success in remote sensing object detection. …”
Get full text

Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…Bayesian optimisation (BO) protocols grounded in active learning (AL) principles have gained significant recognition for their ability to efficiently optimize black-box objective functions. …”
Get full text

Adaptive Cut Selection in Mixed-Integer Linear Programming by Turner, Mark, Koch, Thorsten, Serrano, Felipe, Winkler, Michael

“…We propose a variation on the design of existing graph convolutional neural networks, adapting them to learn cut selection rule parameters. We present a reinforcement learning framework for selecting cuts, and train our design using said framework over MIPLIB 2017 and a neural network verification data set. …”
Get full text

Assessing chronic obstructive pulmonary disease risk based on exhalation and cough sounds by Geyi Wen, Chenshuo Wang, Wei Zhao, Jinliang Meng, Yanyan Xu, Ruiqi Wang, Zijing Zeng

“…Following this, each individual completed pulmonary function tests and participated in questionnaire surveys. …”
Get full text

CNN-Based Object Recognition and Tracking System to Assist Visually Impaired People by Fahad Ashiq, Muhammad Asif, Maaz Bin Ahmad, Sadia Zafar, Khalid Masood, Toqeer Mahmood, Muhammad Tariq Mahmood, Ik Hyun Lee

Get full text

Detection of Electric Network Frequency in Audio Using Multi-HCNet by Yujin Li, Tianliang Lu, Shufan Peng, Chunhao He, Kai Zhao, Gang Yang, Yan Chen

“…Furthermore, a sine activation function (SAF) is utilized to better align with the periodic nature of ENF signals, enhancing the model’s capacity to capture periodic oscillations. …”
Get full text

Enhanced dry SO₂ capture estimation using Python-driven computational frameworks with hyperparameter tuning and data augmentation by Robert Makomere, Hilary Rutto, Alfayo Alugongo, Lawrence Koech, Evans Suter, Itumeleng Kohitlhetse

“…The limited experimental samples were magnified to 342 datasets using the random interpolation and random scaling augmentation procedures and analyzed using the empirical cumulative distribution function and box plots. Model training incorporated grid search with cross-validation to identify the optimal hyperparameter sets. …”
Get full text

Integration of AI with artificial sensory systems for multidimensional intelligent augmentation by Changyu Tian, Youngwook Cho, Youngho Song, Seongcheol Park, Inho Kim, Soo-Yeon Cho

“…However, no studies have systematically categorized the output functions of these systems or analyzed the associated AI algorithms and data processing methods. …”
Get full text

Classification Based on the Support Vector Machine for Determining Operational Targets for Controlling Electricity Usage With Conventional Meters: A Case Study of Industrial and Bu... by Galih Arisona, Alief Pascal Taruna, Dwi Irwanto, Arif Bijak Bestari, Wildan Juniawan

“…Various SVM kernels were tested, including Radial Basis Function (RBF), Linear, Polynomial (Poly), and Sigmoid, alongside classifiers such as SVM, Logistic Regression, Decision Tree, and Naïve Bayes. …”
Get full text

RAU-Net for precise lung cancer GTV segmentation in radiation therapy planning by Huai-wen Zhang, Bo Hu, Jun Yang, Liang-li Xiong, Huan-huan Shi, Qi-liang Xiong, Chen Yi, Shao-feng Jiang

Get full text