A benchmarking framework for the accurate and cost-effective detection of clinically-relevant structural variants for cancer target identification and diagnosis by Guiwu Zhuang, Xiaotao Zhang, Wenjing Du, Libin Xu, Jiyong Ma, Haitao Luo, Hongzhen Tang, Wei Wang, Peng Wang, Miao Li, Xu Yang, Dongfang Wu, Shencun Fang

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Regional blue and green water-saving potential and regulation paths for crop production: A case study in the Yellow River Basin by Yiduo Duan, Wei Wang, La Zhuo, Yilin Liu, Pute Wu

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Application-Aware Resource Allocation Based on Benefit–Cost Ratio in Computing Power Network with Heterogeneous Computing Resources by Yahui Wang, Yajie Li, Jiaxing Guo, Yingbo Fan, Ling Chen, Boxin Zhang, Wei Wang, Yongli Zhao, Jie Zhang

“…With massive simulations, we compare the performance of the AARA algorithm with a benchmark. In terms of blocking probability, resource utilization, and BCR, AARA achieves better performance than the benchmark. …”
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Learning adversarial policy in multiple scenes environment via multi-agent reinforcement learning by Yang Li, Xinzhi Wang, Wei Wang, Zhenyu Zhang, Jianshu Wang, Xiangfeng Luo, Shaorong Xie

“…Experiments demonstrate that MPO converges more stable and faster than benchmark methods in model training, and demonstrates excellent adversarial policy compared with benchmark models.…”
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Ensemble of ERDTs for Spectral–Spatial Classification of Hyperspectral Images Using MRS Object-Guided Morphological Profiles by Alim Samat, Erzhu Li, Sicong Liu, Zelang Miao, Wei Wang

“…Additionally, the ExtraTrees, bagging, adaptive boosting (AdaBoost), and MultiBoost ensemble versions of the extremely randomized decision trees (ERDTs) are introduced and comparatively investigated for spectral-spatial classification of hyperspectral images. Two hyperspectral benchmark images are used to validate the proposed approaches in terms of classification accuracy. …”
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A Lightweight CNN Architecture for Automatic Modulation Classification by Zhongyong Wang, Dongzhe Sun, Kexian Gong, Wei Wang, Peng Sun

“…Compared to recent works, the experimental results show that the proposed network can save approximately 70~98% model parameters and 30~99% inference time on two well-known benchmarks.…”
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A Joint Symbol-Detection, Channel-Estimation and Decoding Scheme under Few-Bit ADCs in mmWave Communications by Peng Sun, Fei Liu, Jianhua Cui, Wei Wang, Yangdong Ye, Zhongyong Wang

“…Since this joint scheme can be implemented via fast Fourier transformation (FFT), the complexity grows only logarithmically. Compared to the benchmark algorithms, numerical results show that the proposed joint scheme can achieve significant performance gain, and demonstrate the effectiveness in dealing with the nonlinear distortion from few-bit ADC.…”
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Binary‐Stochasticity‐Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better‐than‐Software Accuracy by Yang Li, Wei Wang, Ming Wang, Chunmeng Dou, Zhengyu Ma, Huihui Zhou, Peng Zhang, Nicola Lepri, Xumeng Zhang, Qing Luo, Xiaoxin Xu, Guanhua Yang, Feng Zhang, Ling Li, Daniele Ielmini, Ming Liu

“…It also provides better accuracy in pattern recognition tasks than the HP learning algorithm benchmarks.…”
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A Review on Lithium-Ion Battery Separators towards Enhanced Safety Performances and Modelling Approaches by Ao Li, Anthony Chun Yin Yuen, Wei Wang, Ivan Miguel De Cachinho Cordeiro, Cheng Wang, Timothy Bo Yuan Chen, Jin Zhang, Qing Nian Chan, Guan Heng Yeoh

“…Moreover, we summarize the physical properties of separators and benchmark selective key performance indicators. A broad picture of recent simulation studies on separators is given and a brief outlook for the future directions is also proposed.…”
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An Experimental Investigation of Viscoelastic Flow in a Contraction Channel by Wei Wang, Linlin Wang

“…In order to assess the predictive capability of the S–MDCPP model, which may describe the viscoelastic behavior of the low-density polyethylene melts, a planar contraction flow benchmark problem is calculated in this investigation. …”
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Margin‐based reliability reinforcement method for stateful logic by Qingjiang Li, Xingzhi Fu, Wei Wang, Yinan Wang, Weihe Wang, Jietao Diao, Hui Xu, Hongqi Yu

“…Simulations demonstrate that the proposed method can improve the allowed threshold variability range by 42% and 92% for 2‐input NAND gate and 2‐input OR gate, respectively. Benchmark with other methods shows that the proposed margin‐based reinforcement method achieves almost the same reliability reinforcement effect, but the overhead in area and peripheral circuit is greatly reduced.…”
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Basin-scale exposure risk of psychiatric pharmaceuticals and illicit drugs in tap water in Eastern China by Wei Wang, Zeyuan Wang, Feng Chen, Fangxing Yang

“…Exposure assessment indicated the median exposure doses of diazepam and temazepam were from 85 to 99 and 3.5–4.1 pg kg-1 bw d-1 in the basins, respectively. Benchmark quotient for the nine detected substances was calculated in each basin with the range from 0.0001 to 0.0389, indicating low risk in the tap water for human health under current concentrations.…”
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Joint trajectory design and spectrum allocation for unmanned aerial vehicle task efficiency by Wei Wang, Yong Chen, Xianyu Zhang, Panfeng He, Yu Zhang

“…Simulation results show that the proposed algorithm can effectively reduce the task time of UAV compared to other benchmark algorithms.…”
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A Novel Approach for Apple Freshness Prediction Based on Gas Sensor Array and Optimized Neural Network by Wei Wang, Weizhen Yang, Maozhen Li, Zipeng Zhang, Wenbin Du

“…Furthermore, by fitting the relationship between the prediction coefficient and the input vector, the accuracy benchmark of the prediction model is set, which further improves the prediction accuracy of apple odor information. …”
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Multi illumination color constancy based on multi-scale supervision and single-scale estimation cascade convolution neural network by Fei Wang, Fei Wang, Wei Wang, Dan Wu, Guowang Gao, Zetian Wang

“…Extensive experiments are conducted on single and multi-illumination benchmark datasets. In comparison with previous multi-illumination estimation methods, our proposed method displays a partial improvement in terms of quantitative data and visual effect, which provides the future research direction in end-to-end multi-illumination estimation.…”
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HOLP-DF: HOLP Based Screening Ultrahigh Dimensional Subfeatures in Deep Forest for Remote Sensing Image Classification by Alim Samat, Erzhu Li, Wei Wang, Sicong Liu, Ximing Liu

“…Experimental results on three widely acknowledged hyperspectral and PolSAR image classification benchmarks showed that: 1) HOLP is an optimal choice for FS in contrast with other screeners in terms of high classification accuracy and execution efficiency; 2) HOLP-DF is capable of obtaining better results than the original DF, DF with confidence screening and feature screening; 3) optimum sets of model depth, propaganda ratio and screening ratio parameters are 30, 40%, and 40%, respectively; 4) performance of HOLP-DF can be further boosted by extra usage of patch-based pooling and morphological profiling techniques.…”
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Mechanical properties and microscopic characterization of mortar with recycled aggregate from waste road by Chulei Fang, Jichao Feng, Shuaishuai Huang, Jun Hu, Wei Wang, Na Li

“…To sum up, the compressive strength, flexural strength and consistency of RAM are better than those of the benchmark group. When RSA = 40 %, the mechanical properties of RAM reach the optimal value and has high practicability.…”
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A hybrid RBF neural network based model for day-ahead prediction of photovoltaic plant power output by Qipei Zhang, Ningkai Tang, Jixiang Lu, Wei Wang, Lin Wu, Wenteng Kuang

“…In the proposed method, the linear as well as non-linear variables in the RBFNN scheme are efficiently trained using the whale optimization algorithm to speed the convergence of prediction results. A nonlinear benchmark function has also been used to validate the suggested scheme, which was also used in predicting the power output of solar energy for a well-designed experiment. …”
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Assessment of Ab Initio and Density Functional Theory Methods for the Excitations of Donor-Acceptor Complexes: The Case of the Benzene-Tetracyanoethylene Model by Peng Xu, Cai-Rong Zhang, Wei Wang, Ji-Jun Gong, Zi-Jiang Liu, Hong-Shan Chen

“…In order to obtain a balanced description of the different excitation types for electron-donor-acceptor systems, including the singlet charge transfer (CT), local excitations, and triplet excited states, several ab initio and density functional theory (DFT) methods for excited-state calculations were evaluated based upon the selected model system of benzene-tetracyanoethylene (B-TCNE) complexes. On the basis of benchmark calculations of the equation-of-motion coupled-cluster with single and double excitations method, the arithmetic mean of the absolute errors and standard errors of the electronic excitation energies for the different computational methods suggest that the M11 functional in DFT is superior to the other tested DFT functionals, and time-dependent DFT (TDDFT) with the Tamm–Dancoff approximation improves the accuracy of the calculated excitation energies relative to that of the full TDDFT. …”
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Point-Plane SLAM Using Supposed Planes for Indoor Environments by Xiaoyu Zhang, Wei Wang, Xianyu Qi, Ziwei Liao, Ran Wei

“…We test our proposed system on public RGB-D benchmarks, demonstrating its robust and accurate pose estimation results, compared with other state-of-the-art SLAM systems.…”
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