SORA: Energy-Efficient Resource Allocation in Open Radio Access Network With Online Learning by Aerman Tuerxun, Akihiro Nakao

“…By integrating variational inference with Thompson Sampling, the framework efficiently balances exploration and exploitation, allowing dynamic adjustment of MCS and PRB allocations in response to changing network states. The proposed algorithm achieves sub-linear regret, ensuring convergence toward an optimal policy over time while maintaining robust adaptability. …”
Get full text

A dual input dual spliced network with data augmentation for robust modulation recognition in communication countermeasures by Wang Guan

“…Feature extraction in the transform domain of the dataset can, to a certain extent, improve the modulation recognition accuracy. However, it significantly prolongs the algorithm’s running time. …”
Get full text

Balancing Predictive Performance and Interpretability in Machine Learning: A Scoring System and an Empirical Study in Traffic Prediction by Fabian Obster, Monica I. Ciolacu, Andreas Humpe

“…As Machine Learning algorithms become increasingly embedded in decision-making processes, particularly for traffic management and other high-level commitment applications, concerns regarding the transparency and trustworthiness of complex ‘black-box’ models have grown. …”
Get full text

Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting by Simge Özüağ, Ömer Ertuğrul

“…This AI-driven helmet detection model demonstrates significant potential in improving occupational safety by assisting safety officers, especially in confined environments, reducing human error, and enhancing efficiency.…”
Get full text

Day-Ahead Scheduling of IES Containing Solar Thermal Power Generation Based on CNN-MI-BILSTM Considering Source-Load Uncertainty by Kun Ding, Yalu Sun, Boyang Chen, Jing Chen, Lixia Sun, Yingjun Wu, Yusheng Xia

“…The validity of the proposed model is verified by algorithm prediction simulation and day-ahead scheduling experiments under different configurations.…”
Get full text

Adaptive variable channel heat dissipation control of ground control station under various work modes by Dexin Wang, Jiali Tao, Jin Lei, Xinyan Qin, Yanqi Wang, Jie Song, Tianming Feng, Yujie Zeng

“…This research introduces an Adaptive Variable Channel Control (AVCC) cooling approach using the Deep Reinforcement Learning Soft Actor-Critic (SAC) algorithm. The primary contributions of this paper include: (1) the design of a distributed cooling module featuring multiple cooling fans, which enables a variable channel cooling structure; (2) the development of a multi-module temperature control platform that simulates the heat generation conditions of each module under six work modes, providing a training environment for the cooling control algorithm; (3) the formulation of a model-free control method based on the SAC algorithm, AVCC, to optimize the cooling efficiency and endurance of the GCS. …”
Get full text

Maximum power point tracking control for mechanical rectification wave energy converter by Jianan Xu, Yanpeng Zhao, Yong Zhan, Yansong Yang

“…In order to improve the power generation efficiency, the maximum power point tracking control algorithm is designed based on the admittance differentiation method. …”
Get full text

Research on multi-attribute controller for virtual data domain based on software definition network by Jianmin Wang, Bo Zhang, Tongrang Fan, Zijian Fu, Wenbin Zhao

“…Based on software definition network, this article proposes a framework for building virtual data domain, which establishes a multi-attribute decision model by network nodes for optimizing the deployment of control layer, so as to realize large-scale deployment. …”
Get full text

Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography by Ruiting Jia, Baozhi Liu, Mohsin Ali

“…The algorithm effectively handled the CT images at the preprocessing stage, and the deep learning model performed well in detecting and classifying nodules. …”
Get full text

Evaluation of Liver Fibrosis through Noninvasive Tests in Steatotic Liver Disease by Yuri Cho

“…Further research is needed to refine these diagnostic tools and improve accessibility.…”
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

“…Our method introduces three key innovations: (1) A spatial perception module that combines the spatial rich model (SRM) with constrained convolution, enabling focused detection of tampering traces while suppressing interference from image content; (2) A hierarchical feature learning architecture that integrates Swin Transformer with UperNet for effective multi-scale tampering pattern recognition; and (3) A comprehensive optimization strategy including auxiliary supervision, self-supervised learning, and hard example mining, which significantly improves model convergence and detection accuracy. …”
Get full text

Fast Multimodal Trajectory Prediction for Vehicles Based on Multimodal Information Fusion by Likun Ge, Shuting Wang, Guangqi Wang

“…Finally, we propose a multi-stage decoder that generates more accurate and reasonable predicted trajectories by predicting trajectory reference points and performing spatial and posture optimization on the predicted trajectories. 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. …”
Get full text

A New Support Vector Machine Based on Convolution Product by Wei-Chang Yeh, Yunzhi Jiang, Shi-Yi Tan, Chih-Yen Yeh

“…., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. Nonetheless, smaller datasets may be very important, costly, and not easy to obtain in a short time. …”
Get full text

Enhancement Ear-based Biometric System Using a Modified AdaBoost Method by Abdulkareem Merhej Radhi, Subhi Aswad Mohammed

“…The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. …”
Get full text

MUFFNet: lightweight dynamic underwater image enhancement network based on multi-scale frequency by Dechuan Kong, Dechuan Kong, Yandi Zhang, Xiaohu Zhao, Yanqiang Wang, Lei Cai

“…A Multi-Scale Joint Loss framework facilitates dynamic network optimization.ResultsExperimental results demonstrate that MUFFNet outperforms existing state-of-the-art models while consuming fewer computational resources and aligning enhanced images more closely with human visual perception.DiscussionThe enhanced images generated by MUFFNet exhibit better alignment with human visual perception, making it a promising solution for improving underwater robotic vision systems.…”
Get full text

Normalised Diagnostic Contribution Index (NDCI) Integration to Multi Objective Sensor Optimisation Framework (MOSOF)—An Environmental Control System Case by Burak Suslu, Fakhre Ali, Ian K. Jennions

“…Building on previous work, the proposed approach leverages a multi-objective genetic algorithm to optimise key criteria, including performance, cost, reliability management, and compatibility. …”
Get full text

CoNfasTT: A Configurable, Scalable, and Fast Dual Mode Logic-Based NTT Design by Eldar Cohen, Leonid Yavits, Benjamin M. Zaidel, Alexander Fish, Itamar Levi

“…Our implementation offers several potential optimizations, including a unique, fully-combinational, and low-cost modular reduction technique within the K-RED algorithm. …”
Get full text

Explainable AI-Based Ensemble Clustering for Load Profiling and Demand Response by Elissaios Sarmas, Afroditi Fragkiadaki, Vangelis Marinakis

“…Notably, while ensemble clustering often ranked among the top performers, it did not consistently surpass all individual algorithms, indicating its potential for further optimization. …”
Get full text

Multi-Underwater Target Interception Strategy Based on Deep Reinforcement Learning by Wenhao GAN, Yunfei PENG, Lei QIAO

“…Next, the multi-agent proximal policy optimization algorithm was used to construct a scalable state and action space and design a compound reward function, enhancing interception efficiency and cooperation of AUVs. …”
Get full text

Default Risk Prediction of Enterprises Based on Convolutional Neural Network in the Age of Big Data: Analysis from the Viewpoint of Different Balance Ratios by Zhe Li, Zhenhao Jiang, Xianyou Pan

“…Second, we propose a comprehensive metric model based on multimachine learning algorithms (CMM-MLA) to select the best-derived dataset with the optimal balance ratio and feature combination. …”
Get full text