Small-sample-data augmentation and transfer strategies for forest cover change monitoring by Kun Feng, Shaoxiu Ma, Haiyang Xi, Linhao Liang, Weiqi Liu, Atsushi Tsunekawa

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Access and benefit sharing biological materials for machines: Artificial intelligence, machine learning and deep learning by Charles Lawson, Elizabeth Englezos, Michelle Rourke

“…Societal Impact Statement Future research and development of biological materials for foods, feeds, fibres, materials and medicines will increasingly rely on information and knowledge using Artificial Intelligence (AI) applications for detecting patterns to make useful decisions. …”
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Prediction method of gas content in deep coal seams based on logging parameters: A case study of the Baijiahai region in the Junggar Basin by Yijie Wen, Shu Tao, Fan Yang, Yi Cui, Qinghe Jing, Jie Guo, Shida Chen, Bin Zhang, Jincheng Ye

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A machine learning approach to identifying key predictors of Peruvian school principals' job satisfaction by Luis Alberto Holgado-Apaza, Dany Dorian Isuiza-Perez, Nelly Jacqueline Ulloa-Gallardo, Yban Vilchez-Navarro, Ruth Nataly Aragon-Navarrete, Wilian Quispe Layme, Marleny Quispe-Layme, Danger David Castellon-Apaza, Remo Choquejahua-Acero, Jaime Cesar Prieto-Luna

“…Despite the significance of this issue, there is limited research on satisfaction predictors for these professionals, particularly using machine learning approaches. …”
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GeneSetCluster 2.0: a comprehensive toolset for summarizing and integrating gene-sets analysis by Asier Ortega-Legarreta, Alberto Maillo, Daniel Mouzo, Ana Rosa López-Pérez, Lara Kular, Majid Pahlevan Kakhki, Maja Jagodic, Jesper Tegner, Vincenzo Lagani, Ewoud Ewing, David Gomez-Cabrero

“…Methodologically, GeneSetCluster 2.0 introduces a novel approach to address duplicated gene-sets and implements a seriation-based clustering algorithm that reorders results, aiding pattern identification. …”
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Correction of TRMM 3B43 Monthly Precipitation Data Using Quantile Regression Model in the Urmia Lake Basin by Sima Kazempour Choursi, Mahdi Erfanian, Hirad Abghari, Mirhassan Miryaghoobzadeh, khadijeh Javan

“…The studies conducted confirmed this overestimation pattern across different time scales. Linear Regression was not enough to correct the TRMM data, as the corrected data still showed both underestimation and overestimation. …”
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Potential Accuracy of Joint Parameter Estimate by Space-Based Radar Altimeter by D. S. Borovitsky, A. E. Zhesterev, V. P. Ipatov, R. M. Mamchur

“…The subject of research is a space-based radar altimeter. Modern satellite altimeters along with the instant distance to an earth surface are to measure the sea wave height and scattering cross section per unit of a probed spot. …”
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Electroencephalographic monitoring in detection and prediction of delayed cerebral ischemia due to non-traumatic subarachnoid hemorrhage by I. V. Okuneva, M. V. Sinkin, A. I. Evdokimov, A. V. Prirodov

“…During the continuous videoEEG monitoring 2 days before clinical deterioration and appearance of ischemic changes in the right cerebral hemisphere on computed tomography scans, an ictal-interictal continuum pattern was noted to emerge. Future studies should be aimed at clarifying and validating the most informative DCI biomarkers including while recording EEG with intracranial electrodes that may contribute to development of automated algorithms for DCI detection.…”
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Inflammatory markers mediate the association between alternative adiposity indices and mortality in patients with rheumatoid arthritis: data from NHANES 1999–2018 by Feng Luo, Jia-jie Guo, Xue-mei Yuan, Heng Zhou, Qiu-yi Wang, Chang-ming Chen, Xue-ming Yao, Wu-kai Ma

“…Survival patterns were assessed with restricted cubic splines (RCS) and Kaplan–Meier curves. …”
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EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia by Shihai Ling, Lingyan Du, Xi Tan, Guozhi Tang, Yue Che, Shirui Song

“…Electroencephalography (EEG) microstate is a voltage topographical representation of temporary brain network activations. Most research on EEG microstates in SCZ has focused on differences between patients and healthy controls (HC). …”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

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Efficient Real-Time Pathfinding for Visually Impaired Individuals by Tadeh Ghahremanians, Hossein Mahvash Mohammadi

“…Traditional methods usually focus on the detection of specific patterns or objects, requiring custom algorithms for each object of interest. …”
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Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM by Xiaofeng Huang, Xuan Zhou, Junwei Yan, Xiaofei Huang

“…Due to the influence of multiple factors, the cooling load in manufacturing plants exhibits complex characteristics, including multi-peak patterns, periodic fluctuations, and short-term disturbances during meal periods. …”
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A study of Mandelbrot and Julia Sets via Picard-Thakur iteration with s-convexity. by Bashir Nawaz, Krzysztof Gdawiec, Kifayat Ullah, Maggie Aphane

“…Nowadays, many researchers are employing various iterative techniques to analyse the dynamics of fractal patterns. …”
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Sleep Spindles as an Electrographic Element: Description and Automatic Detection Methods by Dorothée Coppieters ’t Wallant, Pierre Maquet, Christophe Phillips

“…To analyze spindle activity in a more robust way, automatic sleep spindle detection methods are essential. Various algorithms were developed, depending on individual research interest, which hampers direct comparisons and meta-analyses. …”
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Modeling growth curve parameters in Peruvian llamas using a Bayesian approach by Ali William Canaza-Cayo, Rubén Herberht Mamani-Cato, Roxana Churata-Huacani, Francisco Halley Rodríguez-Huanca, Maribel Calsin-Cari, Ferdynand Marcos Huacani-Pacori, Oscar Efrain Cardenas Minaya, Júlio Sílvio de Sousa Bueno Filho

“…However, limitations include the use of historical data, which may not fully represent current growth patterns, and the reliance on non-informative priors, which could be improved with prior knowledge. …”
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Three Decades of Land Cover Dynamics in a Boreal Coastal Basin: A Multisensor Spectral Index and Machine Learning Approach Using Landsat Data and GB-SAR Data by Jinsong Zhang, Bochi Zou, Yifei Yuan, Asad Khan, Muhammad Bilawal Junaid, Qaiser Abbas, Rana Muhammad Zulqarnain, Nazih Y. Rebouh, Olga D. Kucher, Hassan Alzahrani

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Causal estimation of the relationship between reproductive performance and the fecal bacteriome in cattle by Yutaka Taguchi, Haruki Yamano, Yudai Inabu, Hirokuni Miyamoto, Koki Hayasaki, Noriyuki Maeda, Yoshiro Kanmera, Seiji Yamasaki, Noboru Ota, Kenji Mukawa, Atsushi Kurotani, Shigeharu Moriya, Teruno Nakaguma, Chitose Ishii, Makiko Matsuura, Tetsuji Etoh, Yuji Shiotsuka, Ryoichi Fujino, Motoaki Udagawa, Satoshi Wada, Jun Kikuchi, Hiroshi Ohno, Hideyuki Takahashi

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Intelligent Technologies and Robotic Machines for Garden Crops Cultivation by I. G. Smirnov, D. O. Khort, A. I. Kutyrev

“…It is noted that there is a need for developing special actuators, grippers and new control algorithms for harvesting horticulture products. (Research purpose) The research aimed to develop an intelligent control system for horticulture industrial technologies and robotic techniques for yield monitoring and fruit harvesting. …”
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Appraisal and analysis on various web service composition approaches based on QoS factors by M. Rajeswari, G. Sambasivam, N. Balaji, M.S. Saleem Basha, T. Vengattaraman, P. Dhavachelvan

“…We have illustrated the related technology by analyzing QoS parameters based on existing algorithms with composition patterns and compared the results.…”
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