The Military Aleatory: Weaponizing Winds by Ryan Bishop

“…From signal interpretation with remote sensing systems to telecommunciations to algorithms, media and information theory, and the weather, the unintended consequences of both dynamic systems in nature and technological attempts to control them led to innovations and accidents, developments and prediction advances that furnish large swaths of our current global sensorial domain. …”
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Research for SARIMA and PatchTSMixer Models on the IEA Monthly Statistics Dataset by Hu Yuwei

“…The rapid evolution of intelligent algorithms has led to their extensive application in time-series forecasting, particularly in predicting electricity consumption. …”
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A Traffic Information Detection Method at Single Intersection Based on Wi-Fi Data by Qingmiao Wang, Jinghe Feng, Shuguang Li

“…K-means clustering algorithms and the LSTM neural network prediction model are used to obtain the space mean speed and vehicle steering ratio of the intersection sections. …”
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Enhancing Sports Team Management Through Machine Learning by Ling Zhang, Yifan An

“…The 34 performance characteristics identified achieved a prediction accuracy of 63.4% for match outcomes.…”
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Theoretical study of the influence of a variable ground resistance by position tracked chassis in motion by Goncharov K.A.

“…The examples show procedures for mathematical prediction of the physical and geometric characteristics of the movement of a tracked vehicle, the use of which in software algorithms of posi-tion control systems can help improve the accuracy of their operation.…”
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Application of Data Mining Technology on Surveillance Report Data of HIV/AIDS High-Risk Group in Urumqi from 2009 to 2015 by Dandan Tang, Man Zhang, Jiabo Xu, Xueliang Zhang, Fang Yang, Huling Li, Li Feng, Kai Wang, Yujian Zheng

“…The goal of this study was to use four data mining algorithms to establish the identification model of HIV infection and compare their predictive performance. …”
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Advancement of artificial intelligence based treatment strategy in type 2 diabetes: A critical update by Aniruddha Sen, Palani Selvam Mohanraj, Vijaya Laxmi, Sumel Ashique, Rajalakshimi Vasudevan, Afaf Aldahish, Anupriya Velu, Arani Das, Iman Ehsan, Anas Islam, Sabina Yasmin, Mohammad Yousuf Ansari

“…At the same time, the rapidly increasing role of AI in diabetes care is woven into the story, mainly targeting how insulin therapy can be modified and personalized through algorithms and predictive modelling. It leaves a deep review of their pre-existing synergies, which helps understand how collaborative opportunities will unlock the future of T2DM care. …”
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Trends, outcomes and knowledge gaps in mobile apps for reproductive endocrinology and infertility: a scoping review protocol by Alba Regina de Abreu Lima, Emerson Roberto dos Santos, Aline Russomano de Gouvêa, Natália Almeida de Arnaldo Silva Rodriguez Castro, João Daniel de Souza Menezes, Matheus Querino da Silva, Helena Landin Gonçalves Cristóvão, Cíntia Canato Martins, Jéssica Gisleine de Oliveira, Patrícia da Silva Fucuta, Alexandre Lins Werneck, Gerardo Maria de Araújo Filho, Heloisa Cristina Caldas, Vânia Maria Sabadoto Brienze, Júlio César André, Antônio Hélio Oliani

“…Despite promising advancements such as the development of apps with sophisticated algorithms for ovulation prediction and comprehensive platforms offering integrated fertility education and emotional support, there remain gaps in the literature regarding the comprehensive evaluation of mobile apps for reproductive endocrinology and infertility. …”
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Track Classification and Characteristics Analysis of Northeast China Cold Vortex During the Warm Season by Jin Tong, Yueming Yu, Qiuping Wang, Xulin Ma, Zhaorong Zhuang

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Study on Rapid Inversion Method for Chlorophyll Content in Ginseng Leaves Based on Reflectance Spectroscopy by Jinyu Wang, Jin Yang, Jiaqi Chen, Shulong Feng, Zitong Zhao, Mingjia Wang, Nan Song, Wei Zhang, Ci Sun

“…To address the problem that the existing means of detecting chlorophyll in ginseng leaves are time-consuming and disruptive and cannot meet the demand for rapid detection of chlorophyll in ginseng leaves, this study firstly establishes a variety of prediction models for chlorophyll in ginseng leaves based on the hyperspectral reflectance data and the vegetation index, respectively, and determines the strengths and weaknesses of the models by comparing the RMSE and the MAE of the test sets; Secondly, the analytical model construction process used for ginseng leaf chlorophyll content prediction was obtained through comparison and summary, and a fast and non-destructive ginseng leaf chlorophyll prediction method based on hyperspectral imaging technology and combining vegetation indices with machine learning algorithms was proposed; The experimental results showed that the final VI-SPA-RFR ginseng leaf chlorophyll prediction model had the best prediction performance, which had an RMSE of 1.1568 and an MAE of 0.9936 in the test set. …”
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Bias Mitigation in Primary Health Care Artificial Intelligence Models: Scoping Review by Maxime Sasseville, Steven Ouellet, Caroline Rhéaume, Malek Sahlia, Vincent Couture, Philippe Després, Jean-Sébastien Paquette, David Darmon, Frédéric Bergeron, Marie-Pierre Gagnon

“… BackgroundArtificial intelligence (AI) predictive models in primary health care have the potential to enhance population health by rapidly and accurately identifying individuals who should receive care and health services. …”
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An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates by J. Hu, C. Miao, J. Su, Q. Zhang, J. Gou, J. Gou, Q. Sun, Q. Sun

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Development of standard fuel models in boreal forests of Northeast China through calibration and validation. by Longyan Cai, Hong S He, Zhiwei Wu, Benard L Lewis, Yu Liang

“…Understanding the fire prediction capabilities of fuel models is vital to forest fire management. …”
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A machine learning approach for the diagnosis of obstructive sleep apnoea using oximetry, demographic and anthropometric data by Zhou Hao Leong, Shaun Ray Han Loh, Leong Chai Leow, Thun How Ong, Song Tar Toh

“…Seven commonly used supervised learning algorithms were trained with the data. Sensitivity (recall), specificity, positive predictive value (PPV) (precision), negative predictive value, area under the receiver operating characteristic curve (AUC) and F1 measure were reported for each model. …”
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Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent. by Alejandra de-la-Rica-Escudero, Eduardo C Garrido-Merchán, María Coronado-Vaca

“…In this work, driven by the motivation of making DRL explainable, we developed a novel Explainable DRL (XDRL) approach for PM, integrating the Proximal Policy Optimization (PPO) DRL algorithm with the model agnostic explainable machine learning techniques of feature importance, SHAP and LIME to enhance transparency in prediction time. …”
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Clinical interpretation of variants identified in RNU4ATAC, a non-coding spliceosomal gene. by Clara Benoit-Pilven, Alicia Besson, Audrey Putoux, Claire Benetollo, Clément Saccaro, Justine Guguin, Gabriel Sala, Audric Cologne, Marion Delous, Gaetan Lesca, Richard A Padgett, Anne-Louise Leutenegger, Vincent Lacroix, Patrick Edery, Sylvie Mazoyer

“…As RNU4ATAC has a single non-coding exon, the bioinformatic prediction algorithms assessing the effect of sequence variants on splicing or protein function are irrelevant, which makes variant interpretation challenging to molecular diagnostic laboratories. …”
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Development of Automatic Balancing Application forFashion Company Using Artificial Intelligence by May Alrasheed, Mohamed Jmali, Thouraya Hamdi

“…Therefore, ant colony algorithms are perfect for manufacturers pursuing cost reduction, improved product quality and facilitated production processes. …”
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On Simplifying Expressions with Mixed Boolean-Arithmetic by Yury V. Kosolapov

“…Based on the length reduction algorithm, an algorithm is constructed that allows to estimate the resistance of an MBA-expression to simplification. …”
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A Self-Adaptive Regression-Based Multivariate Data Compression Scheme with Error Bound in Wireless Sensor Networks by Jianming Zhang, Kun Yang, Lingyun Xiang, Yuansheng Luo, Bing Xiong, Qiang Tang

“…Theoretically and experimentally, it is concluded that the proposed algorithms can effectively exploit the correlations on the same sensor node and achieve significant reduction in data transmission. …”
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Indoor Localization Using Visible Light Via Fusion of Multiple Classifiers by Xiansheng Guo, Sihua Shao, Nirwan Ansari, Abdallah Khreishah

“…Unlike the existing RSSs-based algorithms, several representative machine learning algorithms are adopted to train multiple classifiers based on these RSSs fingerprints. …”
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