Occlusion-Robust Multi-Target Tracking and Segmentation Framework with Mask Enhancement by Hao Sheng, Defa Zhang, Dazhi Yang, Da Yang, Xi Liu, Wei Ke

“…Our framework achieves the best performance on the MOTSA (84.4%), MT, and FN metrics, with a 6.1% reduction in FN compared to the state-of-the-art method. …”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…The samples were divided into two major categories of felsic rocks and mafic rocks using the kNN algorithm, and then six categories were formed by the SVM algorithm. …”
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Estimating Energy Consumption During Soil Cultivation Using Geophysical Scanning and Machine Learning Methods by Jasper Tembeck Mbah, Katarzyna Pentoś, Krzysztof S. Pieczarka, Tomasz Wojciechowski

“…These data, along with soil texture, served as inputs for predicting fuel consumption and field productivity. …”
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Identification of immune and major depressive disorder-related diagnostic markers for early nonalcoholic fatty liver disease by WGCNA and machine learning by Yuyun Jia, Yanping Cao, Qin Yin, Xueqian Li, Xiu Wen

“…Immune cell infiltration levels were quantified using single-sample gene set enrichment analysis (ssGSEA). A predictive model for SS/NASH was developed by evaluating nine machine-learning algorithms with 10-fold cross-validation on the datasets.ResultsFourteen genes strongly linked to both the immune system and the two conditions were identified. …”
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Carbonate Seismic Facies Analysis in Reservoir Characterization: A Machine Learning Approach with Integration of Reservoir Mineralogy and Porosity by Papa Owusu, Abdelmoneam Raef, Essam Sharaf

“…To this end, this study utilizes an unsupervised comparative hierarchical and K-means ML classification of the whole 3D seismic data spectrum and a suite of spectral bands to overcome the cluster “facies” number uncertainty in ML data partition algorithms. This comparative ML, which was leveraged with seismic resolution data preconditioning, predicted geologically plausible seismic facies, i.e., seismic facies with spatial continuity, consistent morphology across seismic bands, and two ML algorithms. …”
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Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads by Keyong Hu, Qingqing Yang, Lei Lu, Yu Zhang, Shuifa Sun, Ben Wang

“…In modeling uncertainties, this article utilizes historical data on PV, WT, and loads, combined with the adjustability of decision variables, to generate a large set of initial scenarios through the Monte Carlo (MC) sampling algorithm. These scenarios are subsequently reduced using a combination of the K-means clustering algorithm and the Simultaneous Backward Reduction (SBR) technique to obtain representative scenarios. …”
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Research on operation optimization of heavy-haul combined trains in long and steep downhill sections based on reinforcement learning by WANG Jianhua, WANG Chunyi, ZENG Zhou, WANG Cong, WANG Qingyuan, YANG Hang

“…To mitigate longitudinal impulse and address challenge posed by continuous air braking operations in long and steep downhill sections for 20 000-ton heavy haul combined trains, this paper proposes an approach for operation optimization of such trains featuring a long formation in such sections based on a data-driven algorithm. An air braking force prediction model was developed based on neural network learning focusing on the variation rules of air braking performance across different operating states, to incorporate differences in air braking characteristics across different trains and varied braking system states on same trains. …”
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A recurrent neural network‐based rotor displacement estimation method for eight‐pole active magnetic bearing by Longyuan Fan, Zicheng Liu, Haijiao Wang, Dong Jiang, Yu Chen

“…The input dimensions and the architecture of the neural network are optimised to improve both prediction accuracy and computational complexity. Experimental results validate the effectiveness of the algorithm and demonstrate that the proposed method has high accuracy, robustness and generalisation ability.…”
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Architecture of the discrete sosine transformation processor for image compression systems on the losless-to-lossy circuit by V. V. Kliuchenia

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ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

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Using Time Clusters for Following Users’ Shifts in Rating Practices by Dionisis Margaris, Costas Vassilakis

“…In that sense, the practice of using a single mean value for adjusting users’ ratings is inadequate, since it fails to follow such shifts in users’ rating practices, leading to decreased rating prediction accuracy. In this work, we address this issue by using the concept of dynamic averages introduced earlier and we extend earlier work by (1) introducing the concept of rating time clusters and (2) presenting a novel algorithm for calculating dynamic user averages and exploiting them in user-user collaborative, filtering implementations. …”
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A modern view on the management of patients with ulcerative colitis of mild and moderate severity in outpatient practice by A. M. Kharitidis, O. B. Shchukina

“…It is indicated that for the choice of tactics and treatment algorithm, the extent of the lesion, as well as the severity of the current exacerbation, classified as mild, moderate and severe, are important. …”
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Delivering Dual Polarization-Division-Multiplexing Millimeter-Wave Signals at W-Band by One Pair of Antennas by Yifan Chen, Jiangnan Xiao, Ze Dong

“…The bit error ratio (BER) is less than the new-generation forward-error-correction (eFEC) threshold of 2 × 10^−2 with CMA algorithm for equalization.…”
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Public and mental health professionals’ perspectives on social media and suicide exposure by Jo Bell, Christopher Westoby

“…Results Four key themes emerged: (1) The communicative ecology of social media (where the public act as content purveyors, rapidly disseminating varied and often unregulated narratives); (2) Harmful effects (including the copycat effect and toxic discourse); (3) Positive effects (where protective discourse and moderation offer harm reduction opportunities); and (4) Challenges in intervention (including content moderation difficulties and algorithmic biases that amplify harmful narratives). …”
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Identification breeds equity: the regulation effect of group decision-making on beauty premium by Lu Cheng, Qingguo Ma, Yijin He, Yulin Tan, Linanzi Zhang, Wenwei Qiu

“…For exploring the underlying mechanism, this study employed a genetic-algorithm-based modelling method to analyse participants’ trial-by-trial dynamic adjustment in group environment. …”
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Detecting Botrytis Cinerea Control Efficacy via Deep Learning by Wenlong Yi, Xunsheng Zhang, Shiming Dai, Sergey Kuzmin, Igor Gerasimov, Xiangping Cheng

“…The innovations include (1) combining channel attention mechanism, multi-head self-attention mechanism, and multi-scale feature extractor to improve prediction accuracy and (2) introducing the Shapley value algorithm to achieve a precise quantitative analysis of environmental variables’ contribution to colony growth. …”
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Learning atomic forces from uncertainty-calibrated adversarial attacks by Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson, Morten Ledum, Simen Reine, Sigbjørn Løland Bore

“…We propose the Calibrated Adversarial Geometry Optimization (CAGO) algorithm to discover adversarial structures with user-assigned errors. …”
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Real‐Time Coseismic Slip Estimation via the GNSS Carrier Phase to Fault Slip Approach: A Case Study of the 2016 Kumamoto Earthquake by Yusuke Tanaka, Yusaku Ohta, Shin'ichi Miyazaki

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Risk Limiting Based Resilient Operation Method for Power Grid by Xiyue WANG, Hao ZHANG, Chaoyi PENG

“…Finally, based on the IEEE 6-node system and an actual 25981-node regional grid examples, we analyze the relationship between system flexibility, prediction accuracy, and system resilience, and it is concluded that improving the operational resilience of the new power system is premised on sufficient system flexibility and prediction accuracy.…”
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Digital Twin-Based Technical Research on Comprehensive Gear Fault Diagnosis and Structural Performance Evaluation by Qiang Zhang, Zhe Wu, Boshuo An, Ruitian Sun, Yanping Cui

“…In terms of technical implementation, combined with HyperMesh 2023 refinement mesh generation, ABAQUS 2023 simulates the stress distribution of gear under thermal fluid solid coupling conditions, the Gaussian process regression (GPR) stress prediction model, and a fault diagnosis algorithm based on wavelet transform and the depth residual shrinkage network (DRSN), and analyzes the vibration signal and stress distribution of gear under normal, broken tooth, wear and pitting fault types. …”
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