Spatial Identification and Distribution Pattern of the Complexity of Rural Poverty in China Using Multisource Spatial Data by Zhenyu Qi, Jinghu Pan, Yaya Feng

“…In the process of poverty alleviation and development, targeted poverty alleviation and economic development should be carried out based on the poverty-dominant type and self-development ability of the county, in order to improve efficiency. …”
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Dynamic changes and prediction of land-use patterns in a typical area for rocky desertification control by Xu Sang, Caili Sun, Zongzheng Chai

“…Consequently, it causes substantial changes in land-use patterns, hindering regional sustainable development.MethodsThis research focuses on Bijie City, Guizhou Province, China, a region severely affected by rocky desertification. …”
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Evolution and Motivation of the Value-Added Trade Pattern of Producer Services Based on a Complex Network by Yan Li, Xuehan Liang, Sizhe Guan, Qingbo Huang

“…The value chain of producer services shows a pattern of being led by developed countries and extending to developing countries. (3) The broader tendency of modularity is decreasing, indicating that the development process of the DVA and FVA networks is becoming globalized. …”
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Recognition Number of The Vehicle Plate Using Otsu Method and K-Nearest Neighbour Classification by Maulidia Rahmah Hidayah, Isa Akhlis, Endang Sugiharti

“…The method of this research was Otsu method to extract the characteristics and image of the plate into binary image and KNN as recognition classification method of each character. The development of the license plate recognition program by using Otsu method and classification of KNN is following the steps of pattern recognition, such as input and sensing, pre-processing, extraction feature Otsu method binary, segmentation, KNN classification method and post-processing by calculating the level of accuracy. …”
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A Machine Learning Framework for Classroom EEG Recording Classification: Unveiling Learning-Style Patterns by Rajamanickam Yuvaraj, Shivam Chadha, A. Amalin Prince, M. Murugappan, Md. Sakib Bin Islam, Md. Shaheenur Islam Sumon, Muhammad E. H. Chowdhury

“…<i>Results:</i> The findings revealed that statistical features are the most sensitive feature metric in distinguishing learning patterns from EEG. …”
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Identification of Papua Cenderawasih Batik Motifs using Local Binary Pattern and K-Nearest Neighbor by Dian Dwi Ariani, Sitti Zuhriyah, Eva Yulia Puspaningrum, Mahabintang Pallawabonang

“…This research aims to develop a texture recognition system using the Local Binary Pattern (LBP) feature extraction method and K-Nearest Neighbor (KNN) classification. …”
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Morphological characterization of Mycobacterium tuberculosis in a MODS culture for an automatic diagnostics through pattern recognition. by Alicia Alva, Fredy Aquino, Robert H Gilman, Carlos Olivares, David Requena, Andrés H Gutiérrez, Luz Caviedes, Jorge Coronel, Sandra Larson, Patricia Sheen, David A J Moore, Mirko Zimic

“…We developed a pattern recognition algorithm to automatically interpret MODS results from digital images. …”
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Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis. by Jörn Diedrichsen, Nikolaus Kriegeskorte

“…Here we develop a common mathematical framework for understanding the relationship of these three methods, which share one core commonality: all three evaluate the second moment of the distribution of activity profiles, which determines the representational geometry, and thus how well any feature can be decoded from population activity. …”
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SLEEP-SAFE: Self-Supervised Learning for Estimating Electroencephalogram Patterns With Structural Analysis of Fatigue Evidence by Wonjun Ko, Jeongwon Choe, Jonggu Kang

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Classification of SD-OCT Volumes Using Local Binary Patterns: Experimental Validation for DME Detection by Guillaume Lemaître, Mojdeh Rastgoo, Joan Massich, Carol Y. Cheung, Tien Y. Wong, Ecosse Lamoureux, Dan Milea, Fabrice Mériaudeau, Désiré Sidibé

“…Our method considers combination of various preprocessing steps in conjunction with Local Binary Patterns (LBP) features and different mapping strategies. …”
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Evaluating the feasibility of using crystalline patterns induced by PBF-LB to predict strength enhancing orientations by José David Pérez-Ruiz, Luis Norberto López de Lacalle, Wilmer Velilla-Díaz, Jaime A. Mesa, Gaizka Gómez, Heriberto Maury, Gorka Urbikain, Haizea Gonzalez

“…The continuous advancement of Laser Powder Bed Fusion (PBF-LB) has expanded the possibilities of additive manufacturing, particularly in producing complex geometries. A distinctive feature of the PBF-LB process is its capacity to develop crystalline patterns, which can be utilized to predict strength-enhancing orientations of the produced components. …”
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Controlled random tests with limited Hamming distance by V. N. Yarmolik, V. V. Petrovskaya, D. V. Demenkovets, V. A. Levantsevich

“…The main feature of the proposed approach is the use of the difference measure proposed by the authors based on determining the Hamming distance for test patterns consisting of symbols of different alphabets. …”
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Temporal and Spatial Patterns of Blue Carbon Storage in Mangrove and Salt Marsh Ecosystems in Guangdong, China by Di Dong, Huamei Huang, Qing Gao, Kang Li, Shengpeng Zhang, Ran Yan

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A Delphi study to identify key gait patterns and their potential causes in people with multiple sclerosis by Sjoerd T. Timmermans, Marjolein M. van der Krogt, Marc B. Rietberg, Heleen Beckerman, Vincent de Groot

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The impact of social features on the financial sustainability of pension systems in Central and Eastern Europe and Baltic States by Florin Cornel Dumiter, Klaus Bruno Schebesch, Ștefania Amalia Nicoară, Cristian Bențe

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Noncoding variants and sulcal patterns in congenital heart disease: Machine learning to predict functional impact by Enrique Mondragon-Estrada, Jane W. Newburger, Steven R. DePalma, Martina Brueckner, John Cleveland, Wendy K. Chung, Bruce D. Gelb, Elizabeth Goldmuntz, Donald J. Hagler, Jr., Hao Huang, Patrick McQuillen, Thomas A. Miller, Ashok Panigrahy, George A. Porter, Jr., Amy E. Roberts, Caitlin K. Rollins, Mark W. Russell, Martin Tristani-Firouzi, P. Ellen Grant, Kiho Im, Sarah U. Morton

“…While genetic factors contribute to sulcal features, the association of noncoding de novo variants (ncDNVs) with sulcal patterns in people with CHD remains poorly understood. …”
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Persistent homology based topological analysis on the gestalt patterns during human brain cognition process by Zaisheng LIU, Fei NI, Rongpeng LI, Honggang ZHANG, Chang LIU, Jiefang ZHANG, Songyun XIE

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Exploring engagement patterns within a mobile health intervention for women at risk of gestational diabetes by Signe B Bendsen, Timothy C Skinner, Sharleen L O’Reilly, Elena Rey Velasco, Mathias S Heltberg, Ditte H Laursen

“…Understanding these differences is essential to provide personalised support during pregnancy and has implications for tailored medicine, digital health, and intervention development. Further research is needed to validate these findings across diverse healthcare settings, exploring engagement patterns throughout different pregnancy phases and their impact on health outcomes.…”
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Vision-based approach to knee osteoarthritis and Parkinson’s disease detection utilizing human gait patterns by Zeeshan Ali, Jihoon Moon, Saira Gillani, Sitara Afzal, Muazzam Maqsood, Seungmin Rho

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UGS-M3F: unified gated swin transformer with multi-feature fully fusion for retinal blood vessel segmentation by Ibtissam Bakkouri, Siham Bakkouri

“…However, accurately segmenting blood vessels in fundus images is challenging due to factors such as significant variability in vessel scale and appearance, occlusions, complex backgrounds, variations in image quality, and the intricate branching patterns of retinal vessels. To overcome these challenges, the Unified Gated Swin Transformer with Multi-Feature Full Fusion (UGS-M3F) model has been developed as a powerful deep learning framework tailored for retinal vessel segmentation. …”
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