Adaptive pilot design for OFDM based on deep reinforcement learning by Qiaoshou LIU, Xiong ZHOU, Shuang LIU, Yifeng DENG

“…For orthogonal frequency division multiplexing (OFDM) systems, an adaptive pilot design algorithm based on deep reinforcement learning was proposed.The pilot design problem was formulated as a Markov decision process, where the index of pilot positions was defined as actions.A reward function based on mean squared error (MSE) reduction strategy was formulated, and deep reinforcement learning was employed to update the pilot positions.The pilot was adaptively and dynamically allocated based on channel conditions, thereby utilizing channel characteristics to combat channel fading.The simulation results show that the proposed algorithm has significantly improved channel estimation performance compared with the traditional pilot uniform allocation scheme under three typical multipath channels of 3GPP.…”
Get full text

Coordinated beamforming for cognitive multi-cell networks with wiretap channels by Dong-hua CHEN, Xiu-xiu ZHANG, Wei-bo XIE

“…Owing to the coupling among the vectors to be optimized，the problem becomes non-convex and non-linear.Accordingly，a centralized coordinated beamforming design method was proposed by constraining the leakage interference and using the semi-definite relaxation，and on the base of it，a decentralized algorithm was also proposed by decomposing the centralized design problem into a group of sub-problems on each cell’s base by using dual decomposition.Simulation results show that the proposed schemes make effective reduction in power consumption while guarantee the legal users’ secrecy rate requirement and the cognitive interference constraint.Moreover，the proposed decentralized method not only reduces the computational complexity，but also has the same performance as the centralized algorithm.…”
Get full text

Enhanced Real-Time Onboard Orbit Determination of LEO Satellites Using GPS Navigation Solutions with Signal Transit Time Correction by Daero Lee, Soon Sik Hwang

“…The proposed method employs a reduced-dynamic orbit determination strategy to balance model fidelity and computational efficiency. A predictive correction model is also incorporated to compensate for GPS signal delays under dynamic motion, thereby enhancing positional accuracy. …”
Get full text

Application of photon-counting CT in cardiovascular diseases by WANG Mengzhen, BAO Shouyu, LIU Peng, YAN Fuhua, YANG Wenjie

“…PCCT shows great application potential in the diagnosis of cardiovascular diseases, especially in reducing beam-hardening artifacts and achieving ultra-high spatial resolution, which can further improve the specifi-city and positive predictive value in the assessment of coronary artery stenosis. …”
Get full text

Quantifying ruminal health: A statistical review and application of area and time under the curve in animal science by Luis O. Tedeschi

“…By combining these methods with advancements in data processing, such as machine learning and predictive modeling, the potential for broader applications becomes evident. …”
Get full text

In vivo efficacy of the boron-pleuromutilin AN11251 against Wolbachia of the rodent filarial nematode Litomosoides sigmodontis. by Alexandra Ehrens, Christopher S Lunde, Robert T Jacobs, Dominique Struever, Marianne Koschel, Stefan J Frohberger, Franziska Lenz, Martina Fendler, Joseph D Turner, Stephen A Ward, Mark J Taylor, Yvonne R Freund, Rianna Stefanakis, Eric Easom, Xianfeng Li, Jacob J Plattner, Achim Hoerauf, Marc P Hübner

Get full text

Federated Transfer Learning for IIoT Devices With Low Computing Power Based on Blockchain and Edge Computing by Peiying Zhang, Hao Sun, Jingyi Situ, Chunxiao Jiang, Dongliang Xie

“…With the development of artificial intelligence and Internet of Things (IoT), the era of industry 4.0 has come. According to the prediction of IBM, with the continuous popularization of 5G technology, the IoT technology will be more widely used in factories. …”
Get full text

Method for detecting cracks in retaining walls based on improved YOLOv5s by Yanhai Wang, Chenxin Guo, Guoyong Duan, Yuhao Zhang, Chao Yang, Huafeng Deng

“…The experimental results showed that the improved algorithm reduced the number of YOLOv5s parameters by 12% and increased the average precision by 1.5% compared to YOLOv5s using only the rotating prediction frames. …”
Get full text

Validation of CT perfusion-based vascular territory mapping: correlation to visual pial grading and outcome measures by Michael Valente, Henry Ma, Andrew Bivard, Bernard Yan, Mark Parsons, Chushuang Chen, Milanka Visser

“…VTM variables were not predictive of anterior collateral grade or stroke outcome measures. …”
Get full text

An integrated Artificial neural network technique to optimize the various parameters of Pineapple/SiO2/epoxy-based nanocomposites under NaOH treatment by Natrayan Lakshmaiya, Naga Dheeraj Kumar Reddy Chukka, Seeniappan Kaliappan, V. Balaji, Nimel Sworna Ross, Ramya Maranan

“…Quantitative optimisation using the Taguchi technique Depending on the S/N ratio of Taguchi refinement, the nanocomposite with the maximum mechanical performance contains 20 % pineapple fibre with a length of 10 mm, 5 % nano SiO2, and 6 h of NaOH treatment. The ANN predictive algorithm and the Taguchi L27 array show that the experiment and projected data for tensile, flexural, and impact are within 3 % and 4 %. …”
Get full text

Research on a Conflict Early Warning System Based on the Active Safety Concept by Bozhao Shen, Zhiqing Zhang, Hao Liu, Shiyun Li, Lei Zhao

“…Through a driving simulation experiment, the speed prediction model after implementation of the warning system was examined. …”
Get full text

DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…Most importantly, DS-AdaptNet achieves these results with only 1.57M parameters and 44.08 GFLOPs—a 94.9% reduction in parameters and 77.2% reduction in computational operations compared to standard U-Net. …”
Get full text

Quantitative analysis of deep learning-based denoising model efficacy on optical coherence tomography images with different noise levels by Furkan Kirik, Farid Iskandarov, Kamile Melis Erturk, Hakan Ozdemir

“…Background: To quantitatively evaluate the effectiveness of the Noise2Noise (N2N) model, a deep learning (DL)-based noise reduction algorithm, on enhanced depth imaging-optical coherence tomography (EDI-OCT) images with different noise levels. …”
Get full text

Abnormal sound detection method for coal mine belt conveyors based on convolutional autoencoder by SHEN Long, SHAN Haoran, PEI Wenliang, YANG Guixiang, WANG Yongli

“…Background noise in the signals was filtered using the WebRTC noise reduction algorithm, and Mel-Frequency Cepstral Coefficients (MFCC) were calculated from the denoised signals to obtain audio features of normal operation. …”
Get full text

Spot Position Extraction Based on High-resolution Parametric Subspace Method without Eigen decomposition by Azad Raheem Kareem

“…A simulated example is provided to evaluate the proposed method and the simulation results shows that the proposed algorithm has the advantages of reduction the computational load and superior estimation performance. …”
Get full text

Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…A DHKELM-based combined prediction model is developed for each component of the decomposition, tailored to different weather types. …”
Get full text

Optimization strategy of UAV‐ARIS assisted vehicular communication system by Haitao Zhao, Zhuoran Xu, Yiyang Ni, Wenxue Sun, Hongbo Zhu, Yaxuan Liu, Zhaoying Mo

“…The authors first provide a UAV‐ARIS based position prediction strategy for the vehicle. Then, a joint RIS phase shift, amplification and UAV trail optimization algorithm is proposed to pursue a high achievable rate. …”
Get full text

Identification and application of shale lithofacies based on conventional logging curves: A case study of the second member of Funing Formation in Qintong Sag, Subei Basin by WANG Xinqian, YU Wenduan, MA Xiaodong, ZHOU Tao, TAI Hao, CUI Qinyu, DENG Kong, LU Yongchao, LIU Zhanhong

“…Ultimately, the model was applied to predict lithology and identify lithofacies in the second member of Well-Qinye-1 and Well-Shaduo-1. …”
Get full text

Investigating the impact of fatty acid profiles on biodiesel lubricity using artificial intelligence techniques by Atthaphon Maneedaeng, Attasit Wiangkham, Atthaphon Ariyarit, Anupap Pumpuang, Ekarong Sukjit

“…To further analyze the impact of fatty acid composition on lubricity, an artificial intelligence (AI)-based approach using the Adaptive Boosting (AdaBoost) algorithm was implemented. The AI model effectively predicts wear scar diameter, friction coefficient, and film formation, providing insights into the complex interactions between fatty acid profiles and tribological performance. …”
Get full text

Validation of the 18-gene classifier as a prognostic biomarker of distant metastasis in breast cancer. by Skye Hung-Chun Cheng, Tzu-Ting Huang, Yu-Hao Cheng, Tee Benita Kiat Tan, Chen-Fang Horng, Yong Alison Wang, Nicholas Shannon Brian, Li-Sun Shih, Ben-Long Yu

“…We validated an 18-gene classifier (GC) initially developed to predict local/regional recurrence after mastectomy in estimating distant metastasis risk. …”
Get full text