Bioresource collections: algorithms for development and functioning; basic and applied significance by E. N. Kosobokova, N. A. Kalinina, M. A. Baryshnikova, V. S. Pokrovsky, O. N. Solopova, T. A. Bogush, V. S. Kosorukov

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Posture detection of athletes in sports based on posture solving algorithms by Huan Zhang

“…It can be seen that the detection error of the research constructed model is only 9.94%, and its three attitude angle errors are mainly concentrated between -0.5° and 0.5° The model constructed by the research can realize high-precision posture detection, which can provide more scientific and reliable training aids for gymnastics, which has very strict requirements for movements in sports. …”
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Comparative analysis of data-driven models for spatially resolved thermometry using emission spectroscopy. by Ruiyuan Kang, Dimitrios C Kyritsis, Panos Liatsis

“…The aim of this research is to explore the use of data-driven models in measuring temperature distributions in a spatially resolved manner using emission spectroscopy data. …”
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Spatial differences in predicted Phalaris arundinacea (reed canarygrass) occurrence in floodplain forest understories by John T. Delaney, M. Van Appledorn, N. R. De Jager, K. L. Bouska, J. J. Rohweder

“…We applied three approaches to better understand and incorporate the influence of spatial autocorrelation among our predictor variables, including random cross‐validation, spatial cross‐validation, and spatial cross‐validation with Euclidean distance fields. …”
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Multi-Fingerprints Indoor Localization for Variable Spatial Environments: A Naive Bayesian Approach by Chengjie Hou, Zhizhong Zhang

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Analysis of Brand Visual Design Based on Collaborative Filtering Algorithm by Gao Chaomeng, Wang Yonggang

“…Finally, the collaborative filtering algorithm is optimized to improve the consumer similarity based on the original algorithm. …”
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An algorithm for generation of DEMs from contour lines considering geomorphic features by Xiao-Ping Rui, Xue-Tao Yu, Jin Lu, Muhammad Aqeel Ashraf, Xian-Feng Song

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Abnormal link detection algorithm based on semi-local structure by Haoran SHI, Lixin JI, Shuxin LIU, Gengrun WANG

“…With the research in network science, real networks involved are becoming more and more extensive.Redundant error relationships in complex systems, or behaviors that occur deliberately for unusual purposes, such as wrong clicks on webpages, telecommunication network spying calls, have a significant impact on the analysis work based on network structure.As an important branch of graph anomaly detection, anomalous edge recognition in complex networks aims to identify abnormal edges in network structures caused by human fabrication or data collection errors.Existing methods mainly start from the perspective of structural similarity, and use the connected structure between nodes to evaluate the abnormal degree of edge connection, which easily leads to the decomposition of the network structure, and the detection accuracy is greatly affected by the network type.In response to this problem, a CNSCL algorithm was proposed, which calculated the node importance at the semi-local structure scale, analyzed different types of local structures, and quantified the contribution of edges to the overall network connectivity according to the semi-local centrality in different structures, and quantified the reliability of the edge connection by combining with the difference of node structure similarity.Since the connected edges need to be removed in the calculation process to measure the impact on the overall connectivity of the network, there was a problem that the importance of nodes needed to be repeatedly calculated.Therefore, in the calculation process, the proposed algorithm also designs a dynamic update method to reduce the computational complexity of the algorithm, so that it could be applied to large-scale networks.Compared with the existing methods on 7 real networks with different structural tightness, the experimental results show that the method has higher detection accuracy than the benchmark method under the AUC measure, and under the condition of network sparse or missing, It can still maintain a relatively stable recognition accuracy.…”
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Quantum approximate optimization algorithms for maximum cut on low-girth graphs by Tongyang Li, Yuexin Su, Ziyi Yang, Shengyu Zhang

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Identifying the Effective Factors on Neuropathic Diseases in Patients with Chronic pain Using Deep Neural Networks by Mobin Shaterian, Mohammad Teshnehlab

“…The main purpose of this research is finding major characteristics of clinical signs in the diagnosis of neuropathic disease in patients with chronic long-term pain. …”
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The spatial extent and the dispersal strategy of species shape the occupancy frequency distribution of stream insect assemblages by I. Szivák, Z. Csabai, D. Schmera, A. Móra

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Research on Big Data Application for Security by Deli Yang, Tao Zhang

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Rural Landscape Characters and Spatial Correlation Mechanism in the Tiaoxi River – Canal Basin in Zhejiang Province by Lin ZHANG, You ZUO, Binyi LIU

“…At the rural community scale, through spatial maximum expectation (EM) clustering, the types of rural landscape characters are classified and spatially mapped through simulation algorithms.ResultsIn terms of the spatial correlation of water network − canal channel − rural landscape within the Tiaoxi River − Canal Basin, the research identifies three major landscape character zones including the West Tiaoxi River − Ditang Canal Basin, East Tiaoxi River − Jiangnan Canal Basin, and Hangzhoutang River − Hangzhou − Jiaxing Canal Basin. …”
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Conceptual Framework for the Organization of Rural Areas: A Study Based on the Identification of Agglomeration Patterns by Aleksandr A. Tiutiunikov, Andrei V. Ulezko

“…The developed methodology can serve as a basis for further research on the economic space of agglomeration structures in rural and non-urban areas. …”
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Spatial analysis of air pollutant exposure and its association with metabolic diseases using machine learning by Jingjing Liu, Chang Liu, Zhangdaihong Liu, Yibin Zhou, Xiaoguang Li, Yang Yang

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Spectroscopic Ages for 4 Million Main-sequence Dwarf Stars from LAMOST DR10 Estimated with a Data-driven Approach by Jia-Hui Wang, Maosheng Xiang, Meng Zhang, Ji-Wei Xie, Jian Ge, Jinghua Zhang, Lanya Mou, Ji-Feng Liu

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Postoperative Respiratory Depression Associated with Pregabalin: A Case Series and a Preoperative Decision Algorithm by Naveen Eipe, John Penning

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Machine Learning Analysis to Identify Predictive Factors of Caudal Epidural Pulse Radiofrequency in the Treatment of Coccygodynia by Sir E, Aydogan S, Batur Sir GD, Celenlioglu AE

“…When a new patient is admitted, the ML-generated decision trees provide a quick and precise assessment of the possible success rate of CEPRF treatment.Keywords: machine learning, decision tree, pulsed radiofrequency treatment, chronic pain, pain management…”
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Evaluating treatments with topical anaesthetic and buccal meloxicam for pain and inflammation caused by amputation dehorning of calves. by Dominique Van der Saag, Sabrina Lomax, Peter Andrew Windsor, Casey Taylor, Peter John White

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A cellular automata coupled multi-objective optimization framework for blue-green infrastructure spatial allocation by Qinghe Hou, Hanwen Xu, Mingkun Xie, Pingjia Luo, Yuning Cheng

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