Hierarchical Mixed-Precision Post-Training Quantization for SAR Ship Detection Networks by Hang Wei, Zulin Wang, Yuanhan Ni

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Calculating Percentiles of <i>T</i>-Distribution Using Gaussian Integration Method by Tzu-Li Tien

“…Statistical inference is used to estimate population parameters based on sample information and to quantify the sampling error based on the probability narrative. …”
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INNSE: Invertible neural network-based DNA image storage with self-correction encoding by Yanfen Zheng, Xiaokang Zhang, Lijun Sun, Ben Cao, Bin Wang, Qiang Zhang, Pan Zheng

“…Finally, a self-correction method was constructed to achieve DNA sequence error correction at the base level without adding any redundant information. …”
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Quantum memory at nonzero temperature in a thermodynamically trivial system by Yifan Hong, Jinkang Guo, Andrew Lucas

“…Abstract Passive error correction protects logical information forever (in the thermodynamic limit) by updating the system based only on local information and few-body interactions. …”
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A Variational Bayesian Truncated Adaptive Filter for Uncertain Systems with Inequality Constraints by Tianli Ma, Rong Zhang, Song Gao, Hong Li, Yang Zhang

“…By choosing the skew-t and inverse Wishart distributions as the prior information of the measurement noise and predicted error covariance matrix, the state vector, the predicted error covariance matrix, and noise parameters are inferred and approximated by using the VB method. …”
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DASNet a dual branch multi level attention sheep counting network by Yini Chen, Ronghua Gao, Qifeng Li, Hongtao Zhao, Rong Wang, Luyu Ding, Xuwen Li

“…The LCPM leverages the advantages of attention mechanisms to more effectively extract multi-scale global features of the sheep regions, thereby helping the network to reduce the loss of deep feature information. Experiments conducted on our Sheep1500 UAV Dataset have demonstrated that DASNet significantly outperforms the baseline MAN network, with a Mean Absolute Error (MAE) of 3.95 and a Mean Squared Error (MSE) of 4.87, compared to the baseline’s MAE of 5.39 and MSE of 6.50. …”
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The Role of Landscape Metrics and Spatial Processes in Performance Evaluation of GEOMOD (Case Study: Neka River Basin) by Shrif Joorabian Shooshtari, Kamran Shayesteh, Mehdi Gholamalifard, Mahmood Azari, Juan Ignacio López-Moreno

“…The relative error obtained by comparison of observed map versus simulated map for patch density, related circumscribing circle, and for effective mesh size metrics was the highest. …”
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Long-distance target localization optimization algorithm based on single robot moving path planning by Yourong Chen, Ke Wu, Yidan Guo, Kehua Zhao, Liyuan Liu

“…Based on image parallelism, we propose a method for calculating the relative position of the target using sensing information from two positions. Additionally, an improved hierarchical density-Based spatial clustering of applications with noise (HDBSCAN) algorithm is developed to fuse the relative coordinates of multiple targets. …”
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Point‐convolution‐based human skeletal pose estimation on millimetre wave frequency modulated continuous wave multiple‐input multiple‐output radar by Jinxiao Zhong, Liangnian Jin, Ran Wang

“…Current methods of human skeletal pose estimation can reconstruct targets, but they lose the spatial information or don't take the density of point cloud into consideration. …”
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Use of Machine Learning to Predict California Bearing Ratio of Soils by Semachew Molla Kassa, Betelhem Zewdu Wubineh

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Yoked surface codes by Craig Gidney, Michael Newman, Peter Brooks, Cody Jones

“…Abstract One of the biggest obstacles to building a large scale quantum computer is the high qubit cost of protecting quantum information. For two-dimensional architectures, the surface code has long been the leading candidate quantum memory, but can require upwards of a thousand physical qubits per logical qubit to reach algorithmically-relevant logical error rates. …”
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A study on applying GA for performance improvement of SP decoder in SMR by Madoka Nishikawa, Yasuaki Nakamura, Yasushi Kanai, Yoshihiro Okamoto

“…In this study, to prevent error propagation in SP decoding, we evaluate the LLR for the check node using the parity check information and multiply the LLR for the priori information by the weight to reflect the evaluation result. …”
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Alfalfa stem count estimation using remote sensing imagery and machine learning on Google Earth Engine by Hazhir Bahrami, Karem Chokmani, Saeid Homayouni, Viacheslav I. Adamchuk, Md Saifuzzaman, Rami Albasha, Maxime Leduc

“…RF outperformed XGB and SVM in classification and regression tasks, showing superior accuracy in classifying density and lower root mean square error (RMSE) in estimating stem density. …”
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Next-Gen Decoding: Non-Binary LDPC Algorithms for Emerging Power Line and Visible Light Communications by Waheed Ullah, Fengfan Yang, Kwonhue Choi, Dushantha Nalin K. Jayakody

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Exploring demographic, healthcare, and socio-economic factors as predictors of COVID-19 incidence rate: A spatial regression analysis. by Kittipong Sornlorm, Ei Sandar U, Wongsa Laohasiriwong, Wor Mi Thi

“…OLS models were initially used with significant variables: household, hospital, and industry density, nighttime light index (NTLI). Spatial dependency led to spatial error (SEM) and spatial lag models (SLM), performing better with similar significant variables being applied. …”
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ECONOMIC EFFICIENCY OF SUNFLOWER PRODUCTION DEPENDING ON TECHNOLOGY by Adalbert OKROS, Casiana MIHUȚ, Alexandru RINOVETZ

“…Based on the values obtained, descriptive statistical indices related to the different technological factors were calculated, namely: arithmetic mean, error of the mean and coefficient of variation. The results showed that the profit had a variation between 849 RON/ha in the case of plants grown at a density of 49,26 g.g.…”
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Generalized Additive Model for Predicting ECBR of Stabilized Subgrades for Pavement by Alka Shah, Tejaskumar Thaker, Vipin Shukla

“…Further interpretability analysis through mutual information and partial dependence plots identified resilient modulus (<inline-formula> <tex-math notation="LaTeX">$\text{M}_{\mathrm {r}}$ </tex-math></inline-formula>), optimum moisture content (OMC), maximum dry density (MDD) and content of plastic waste (CP) as key predictors influencing ECBR. …”
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LDPC-Coded Modulation Performance Analysis and System Design by Cornelius Tomas Healy, Anas Al Rawi, Charalampos C. Tsimenidis

“…Finally, through the relationship between mutual information and error rate performance for error control codes, the derived analytical expressions are used to produce a semi-analytical finite-length performance predictor, whereby error rate results for a given code on the binary input additive white Gaussian noise (AWGN) channel can be mapped to the coded modulation scheme under consideration for any coded system parameters.…”
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A Hyperchaotic Lorenz and DNA-Encoded Image Encryption Algorithm by Shuangyuan Li, Mengfan Li

“…Meanwhile, the mean square error (MSE) of pepper and salt noise density is analyzed by the peak signal-to-noise ratio (PSNR). …”
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Estimating NOx Emissions in China via Multisource Satellite Data and Deep Learning Model by Kun Cai, Yanfang Shao, Yinghao Lin, Shenshen Li, Minghu Fan

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