Integrating spatial-temporal risk maps with candidate trajectory trees for explainable autonomous driving planning by Qiyuan Liu, Jiawei Zhang, Jingwei Ge, Cheng Chang, Zhiheng Li, Shen Li, Li Li

“…We then design an explainable trajectory planning framework that integrates risk maps with the candidate trajectory tree generated by trajectory prediction models. We further filter safe candidate trajectories from the tree on the basis of their cumulative risks in the risk maps and then select the optimal trajectory to execute by balancing other driving objectives. …”
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High-Temperature Rutting Resistance of Inverted Asphalt Pavement Structure by Yingjun Jiang, Yu Zhang, Changqing Deng, Yong Yi, Tian Tian, Kejia Yuan

“…To improve the high-temperature rutting resistance of asphalt pavements, an inverted asphalt pavement structure (IAPS), 4 cm AC-13 mixture + 8 cm AC-25 mixture + 6 cm AC-20 mixture + 54 cm cement-stabilized macadam, was proposed herein by considering engineering practice, theoretical calculation, and analysis. A rutting prediction equation of asphalt pavements was then proposed via rut-development trends found by laboratory 18 cm thick rutting test. …”
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Merger of Higher Education Institutions and Educational Competitiveness: Interrelationship Issues by E. S. Anichkin

“…As a methodical basis for the study, we used generalization, comparison, abstraction, prediction; methods of empirical research: interviewing focus groups, content analysis of universities’ Web sites, expert evaluation, case-method.The paper considers the theoretical and methodological grounds of university competitiveness in the conditions of higher education modernization, measurement indicators and factors influencing the competitiveness of university’s educational activity. …”
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An Incremental Learning Ensemble Strategy for Industrial Process Soft Sensors by Huixin Tian, Minwei Shuai, Kun Li, Xiao Peng

“…The weight updating rules are designed by considering the prediction accuracy of submachines with new arrived data. …”
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Target Threat Assessment in Air Combat Based on Improved Glowworm Swarm Optimization and ELM Neural Network by Yuan Cao, Ying-Xin Kou, An Xu, Zhi-Fei Xi

“…Firstly, the linear discriminant analysis method is used to classify the threat assessment indicators, eliminate the correlation between the assessment indicators, and achieve dimensionality reduction of the assessment indicators. Secondly, a prediction model with multiple parallel extreme learning machines as the core is constructed, and the input weights and thresholds of extreme learning machines are optimized by the improved glowworm swarm optimization algorithm, and the weighted integration is carried out according to the training level of the kernel. …”
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Species distribution modelling using MaxEnt: overview and prospects by Yuliia Novoseltseva

“…Niche modeling of species has become increasingly important in the context of accelerating climate change and anthropogenic impacts on the biosphere. One such tool for predicting the potential distribution of species is the maximum entropy method (MaxEnt). …”
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Complexity in Individual Trajectories toward Online Extremism by Z. Cao, M. Zheng, Y. Vorobyeva, C. Song, N. F. Johnson

“…A generalization of diagrammatic expansion theory helps quantify these characteristics, including the impact of changes in geographical location, and can facilitate prediction of future risks. By quantifying the trajectories that individuals follow on their journey toward expressing high levels of pro-ISIS support—irrespective of whether they then carry out a real-world attack or not—our findings can help move safety debates beyond reliance on static watch-list identifiers such as ethnic background or immigration status and/or postfact interviews with already convicted individuals. …”
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Scenario Analyses of Land Use Conversion in the North China Plain: An Econometric Approach by Jinyan Zhan, Feng Wu, Chenchen Shi, Fan Zhang, Zhihui Li

“…Scenario analysis and dynamic prediction of land use structure which involve many driving factors are helpful to investigate the mechanism of land use changes and even to optimize land use allocation for sustainable development. …”
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Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition by Sota Nemoto, Shunsuke Kitada, Hitoshi Iyatomi

“…Evaluation experiments on four NER datasets (Japanese and English) showed that MoM learning improves the prediction performance of the minority classes without sacrificing the performance of the majority class and is more effective than widely known and state-of-the-art methods. …”
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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. …”
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Hybrid learning in post-pandemic higher education systems: an analysis using SEM and DNN by Alvin Muhammad ‘Ainul Yaqin, Ahmad Kamil Muqoffi, Sigit Rahmat Rizalmi, Faishal Arham Pratikno, Remba Yanuar Efranto

“…Meanwhile, DNN achieved a high prediction accuracy of 82.40%, significantly outperforming logistic regression (baseline) models. …”
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Antioxidants and Cognitive-Behavioral Therapy in Patients with Functional Dyspepsia by T. V. Sapozhnikova, S. A. Parfenov, T. E. Yesina, K. V. Sapozhnikov, A. N. Smirnov, A. A. Paulov, D. M. Rizakhanov, O. A. Rizakhanova

“…After comparing it with a threshold, the probability of a positive response to a combination of antioxidant and cognitive-behavioral therapy is estimated. The developed prediction algorithm is valid (sensitivity — 91 %, specificity — 73 %, accuracy — 84.8 %) and allows to optimize the definition of treatment tactics for a patient with functional dyspepsia.…”
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Mini meta-analysis of anticholinesterase actions of atorvastatin, simvastatin and rosuvastatin, and in silico identification of their protein targets in Mus musculus by Fouad Kasim Mohammad, Rawnaq Faris Al-Shalchi

“…The study aims at conducting a mini meta-analysis on in vivo and in vitro adverse anti-ChE effects of atorvastatin, simvastatin and rosuvastatin in mice, and using the SwissPrediction to identify in silico body target proteins. …”
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Experimental Research of the Influence of Microfracture Morphology on Permeability of Shale Rock by Xiaohe Huang, Yunqian Long, Yuyi Wang, Ming Yue

“…This research can provide some new insights for the production prediction of shale gas reservoir after fracturing.…”
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Immediate and short-term effects of neurodynamic techniques on hamstring flexibility: A systematic review with meta-analysis. by Sergio Núñez de Arenas-Arroyo, Vicente Martínez-Vizcaíno, Ana Torres-Costoso, Sara Reina-Gutiérrez, Bruno Bizzozero-Peroni, Iván Cavero-Redondo

“…Furthermore, to reflect the variation in genuine therapy effects in different scenarios, including future patients, we calculated a 95% prediction interval(prI).<h4>Results</h4>Thirteen trials were included, involving 624 participants. …”
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Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence by Tarun Kumar Kotteda, Rama Bhadri Raju Chekuri, B. Naga Raju, Prasada Raju Kantheti, S. Balakumar

“…It has been identified that ANN showed an average accuracy of prediction superior than regression analysis.…”
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Quantitative Analysis of Multicomponents in Qufeng Zhitong Capsule and Application of Network Pharmacology to Explore the Anti-Inflammatory Activity of Focused Compounds by Mengjie Xue, Yuting Zhao, Ying Cui, Jing Yang, Yuefei Wang, Xin Chai

“…Based on the brief prediction results of network pharmacological analysis, ultra-performance liquid chromatography coupled with photodiode array detector method was validated in terms of linearity, limit of detection, limit of quantification, precision, repeatability, stability, and recovery test and was successfully employed to determine 16 compounds in 28 batches of QZCs, which confirmed the feasibility and reliability of the established method for the quantitative analysis of 16 compounds in QZC. …”
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Mechanism of Permeability Evolution for Reservoir Sandstone with Different Physical Properties by Xianshan Liu, Ming Xu, Ke Wang

“…The results also show that the variation patterns of permeability are similar for two reservoir sandstones under combination of confining pressure and water pressure; however, the strength and permeability are smaller for the sandstone with mud than that without mud, deeply indicating that mud-like materials have a relatively great impact on the mechanical properties and permeability, so mud components cannot be ignored for prediction of reservoir permeability. Furthermore, a statistical damage constitutive model considering hydraulic-mechanical coupling process is presented to calculate the damage variable D, illustrating that larger water pressure will result in a relatively smaller damage variables D and corresponding maximum, which explains that the permeability increases more rapidly and is larger for the sandstone without mud than that with mud, and sandstone damage related to corresponding circumferential crack strain and permeability has been investigated, also implying the evolution mechanism of permeability for two sandstones with different physical properties. …”
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Robust Optimization of Alginate-Carbopol 940 Bead Formulations by J. M. López-Cacho, Pedro L. González-R, B. Talero, A. M. Rabasco, M. L. González-Rodríguez

“…Confirmation tests to verify the prediction model were carried out and the obtained results were very similar to those predicted in every profile. …”
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A Feature-Extraction-Based Lightweight Convolutional and Recurrent Neural Networks Adaptive Computing Model for Container Terminal Liner Handling Volume Forecasting by Bin Li, Yuqing He

“…Subsequently, a feature-extraction-based lightweight convolutional and recurrent neural network adaptive computing model (FEB-LCR-ACM) is presented initially to predict the LHV by the fusion of multiple deep learning algorithms and mechanisms, especially for the specific feature extraction package of tsfresh. …”
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