Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks by Kun Mei, Zikang Feng, Hui Liu, Min Wang, Chao Ce, Shi Yin, Xiaoying Zhang, Bin Wang

“…Feature selection was performed using the Lasso algorithm to identify the most predictive variables, which were subsequently incorporated into the radiomics-based neural network model. …”
Get full text

FPA-based weighted average ensemble of deep learning models for classification of lung cancer using CT scan images by Liang Zhou, Achin Jain, Arun Kumar Dubey, Sunil K. Singh, Neha Gupta, Arvind Panwar, Sudhakar Kumar, Turki A. Althaqafi, Varsha Arya, Wadee Alhalabi, Brij B. Gupta

“…Unlike traditional ensemble approaches that assign static or equal weights, the FPA adaptively optimizes the contribution of each CNN based on validation performance. …”
Get full text

Improving neural network training using dynamic learning rate schedule for PINNs and image classification by Veerababu Dharanalakota, Ashwin Arvind Raikar, Prasanta Kumar Ghosh

Get full text

Machine Learning-Based Cost Estimation Models for Office Buildings by Guolong Chen, Simin Zheng, Xiaorui He, Xian Liang, Xiaohui Liao

“…This paper explores the application of algorithm-optimized back propagation neural networks and support vector machines in predicting the costs of office buildings. …”
Get full text

Minimum-Cost Design of Auto-Scaling Server Farms Providing Reliability Guarantees by Jesus Perez-Valero, Pablo Serrano, Jaime Garcia-Reinoso, Albert Banchs, Xavier Costa-Perez

“…To this end, we develop an optimization algorithm that combines (i) a queueing-theoretic model to estimate the resources needed to meet reliability constraints, and (ii) a general cost model that captures both capital and operational expenditures. …”
Get full text

A Review of High-Sensitivity Tracking Techniques for Satellite Navigation Signals by Zhiqiang Gong, Honglei Lin, Zhe Liu, Zengjun Liu, Long Huang, Gang Ou

“…Key strategies—such as coherent integration time extension, discriminator and loop filter optimization, vector tracking (VT), and Direct Position Estimation (DPE) are evaluated in the context of weak signal scenarios. …”
Get full text

Tomato Leaf Disease Identification Framework FCMNet Based on Multimodal Fusion by Siming Deng, Jiale Zhu, Yang Hu, Mingfang He, Yonglin Xia

Get full text

Research on temperature and humidity compensation method of vehicle gas sensor based on SCA-PSO support vector regression by Lv Yingming, Yuan Wenping

Get full text

Distributed Dynamic Traffic Modeling and Implementation Oriented Different Levels of Induced Travelers by Yan Liu, Yao Yu

Get full text

Lightweight deep learning system for automated bone age assessment in Chinese children: enhancing clinical efficiency and diagnostic accuracy by Pang Hai, Zhang Bin, Liu Kesheng, Li Cong, Xu Fei

“…This lightweight design reduces computational complexity, enabling faster inference while maintaining diagnostic precision. …”
Get full text

SwinFishNet: A Swin Transformer-based approach for automatic fish species classification using transfer learning. by Ebru Ergün

“…Transfer learning was applied using the ST, which was fine-tuned on these datasets and optimized with the AdamW algorithm. The model's performance was evaluated using classification accuracy (CA), F1-score, recall, precision, Matthews correlation coefficient, Cohen's kappa and confusion matrix metrics. …”
Get full text

Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background by Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che

Get full text

GIS partial discharge fault diagnosis method based on SGMD-LSTM by Zhang Yun, Zhang Chao, Zhang Shiyong, Ma Pengchi, Yang Guang, Ding Hao

Get full text

Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…The particle swarm optimization (PSO) algorithm is refined with enhanced termination criteria and integrated with the 3D Bishop method to search for the minimum factor of safety (F). …”
Get full text

A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY by Lev Raskin, Yurii Parfeniuk, Larysa Sukhomlyn, Mykhailo Kravtsov, Leonid Surkov

“…Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. …”
Get full text

Deep learning-based energy efficient LSFD weights prediction for user centric cell free massive MIMO system by Moustafa Mohamed, Salwa El-Ramly, Bassant Abdelhamid

“…These models are trained using dataset generated from heuristic sparse LSFD optimization algorithm, this allows the models to learn the sparsity nature of the system and apply AP-UE association based on the values of the predicted LSFD weights at the receiver side while using the large scale fading coefficients as the models’ input. …”
Get full text

Unsupervised Learning for Distributed Downlink Power Allocation in Cell-Free mMIMO Networks by Mattia Fabiani, Asmaa Abdallah, Abdulkadir Celik, Omer Haliloglu, Ahmed M. Eltawil

“…The proposed unsupervised learning approach circumvents the arduous task of training data computations, typically required in supervised learning methods, bypassing the use of conventional complex optimization methods and heuristic methodologies. …”
Get full text

Building construction crack detection with BCCD YOLO enhanced feature fusion and attention mechanisms by Wenhao Ren, Zuowei Zhong

“…Abstract An effective algorithm for detecting cracks in bare concrete structures in building construction, capable of identifying small targets, is essential for safeguarding buildings. …”
Get full text

SECURE VERTEX-EDGE DOMINATION IN HYPERCUBE AND GRID GRAPHS: APPLICATIONS OF CYBERSECURITY IN BANKING FOR SECURE TRANSACTIONS by C. Ruby Sharmila, S. Meenakshi

“…Moreover, develop a Hidden Markov Model (HMM) framework to enhance the detection of anomalous activities within these graph structures. This algorithm efficiently computes the minimum number of security agents required to monitor transaction flows, thus reducing vulnerabilities. …”
Get full text

Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. To optimize computational efficiency, window parameters are determined through an energy concentration maximization criterion, enabling rapid extraction of discriminative features from diverse PQ disturbances (e.g., voltage sags and transient interruptions). …”
Get full text