AI-assisted Pattern Generator for Garment Design by Michael Danner, Elena Brake, Gabriela Kosel, Yordan Kyosev, Katharina Rose, Matthias Rätsch, Holger Cebulla

“…The process uses advanced AI algorithms to facilitate the conversion of 3D scans into usable patterns. …”
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Comparison of the Performance of the C.45 Algorithm with Naive Bayes in Analyzing Book Borrowing at the Library Pringsewu Muhammadiyah University by Dani Wilian, Sriyanto Sriyanto

“…This study examines the effectiveness of the Naïve Bayes and C4.5 algorithms in analyzing book borrowing patterns at the Pringsewu Muhammadiyah University Library. …”
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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

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Application of smart technologies for predicting soil erosion patterns by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid, Shiva Gharibi, Jing-Cheng Han

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Method for recognizing abnormal operation patterns in hydraulic support machine-following and shifting control by MA Zhitao, FU Xiang, LI Haojie, NIU Penghao, JIA Yifan

“…To address this issue, a method was proposed for identifying abnormal condition patterns in machine-following and shifting control of hydraulic supports. …”
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Leveraging diverse cell-death patterns in diagnosis of sepsis by integrating bioinformatics and machine learning by Mi Liu, Xingxing Gao, Hongfa Wang, Yiping Zhang, Xiaojun Li, Renlai Zhu, Yunru Sheng

“…Results A total of 289 PCD-related differentially expressed genes were identified between sepsis patients and healthy individuals. The machine learning algorithm screened three PCD-related genes, NLRC4, TXN and S100A9, as potential biomarkers for sepsis. …”
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Myoelectric signal and machine learning computing in gait pattern recognition for flat fall prediction by Shuo Zhang, Biao Chen, Chaoyang Chen, Maximillian Hovorka, Jin Qi, Jie Hu, Gui Yin, Marie Acosta, Ruby Bautista, Hussein F. Darwiche, Bryan E. Little, Carlos Palacio, John Hovorka

“…This study aimed to determine the feasibility of using lower limb myoelectrical signals (electromyographic signals, EMG) for gait pattern recognition and to identify the optimal machine learning (ML) algorithms for EMG signal processing. …”
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Application of artificial neural network in determining the fabric weave pattern by Subrata Das, Keerthana Shanmugaraja

“…The approaches based on early machine learning algorithms directly depend on handcrafted features, which are time-consuming and occurs more errors. …”
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Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma by Fanyan Ou, Yi Pan, Qiuli Chen, Lixiong Zeng, Kanglai Wei, Delin Liu, Qian Guo, Liquan Zhou, Jie Yang

“…We utilized a combination of 101 machine learning algorithms to analyze the TCGA-KIRC cohort and the GSE22541 KIRC patients, screening for cell death patterns closely associated with prognosis from 18 potential modes. …”
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APPLYING SOME MATCHING ALGORITHMS FOR SEQUENCE IGNATURE TO ANALYZE AND DETECT ENTRIES INTO SYSTEM NETWORKS by Pham Nguyen Huy Phuong, Dang Le Nam

“…Additionally, tools for network monitoring such as open source munintools,are also used to analyze and evaluate the performance of network-attack. Next, the time of pattern identification in the Snort's machine, and the performance of Snort as well as the number of packets passing through Snort, the amount of alerts per second, connection speed in real time, the percentage of received data in pattern matching process, etc. are also measured based on intelligent algorithms built in Snort. …”
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Integrating Remote Sensing, Landscape Metrics, and Random Forest Algorithm to Analyze Crop Patterns, Factors, Diversity, and Fragmentation in a Kharif Agricultural Landscape by Surajit Banerjee, Tuhina Nandi, Vishwambhar Prasad Sati, Wiem Mezlini, Wafa Saleh Alkhuraiji, Djamil Al-Halbouni, Mohamed Zhran

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Modification of the WaldBoost algorithm to improve the efficiency of solving pattern recognition problems in real-time by A. N. Chesalin, S. Ya. Grodzenskiy, M. Yu. Nilov, A. N. Agafonov

“…The aim of the study is to improve the known machine learning algorithms for pattern recognition using a minimum amount of time (the minimum number of used classifiers) and with a given accuracy of the results. …”
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Machine learning-based pattern recognition of Bender element signals for predicting sand particle-size by Yong-Hoon Byun, Juik Son, Jungmin Yun, Hyunwook Choo, Jongmuk Won

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Discovering User Sentiment Patterns in Libraries with a Hybrid Machine Learning and Lexicon-Based Approach by Dini Nurmalasari, Dini Hidayatul Qudsi, Nessa Chairani, Heri R Yuliantoro

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The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns by Lianne Grin, Sieglinde Bogaert, Saskia Wijnands, Arnold Besselaar, Marieke van der Steen, Jesse Davis, Benedicte Vanwanseele

“…Machine learning algorithms have the capacity to analyse such complex nonlinear relationships, offering the potential to train a model that assesses whether a child has relapsed clubfoot based on their movement pattern. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Modern multi-tiered data storage systems optimize file access by managing data across a hybrid composition of caches and storage tiers while using policies whose decisions can severely impact the storage system’s performance. Recently, different Machine-Learning (ML) algorithms have been used to model access patterns from complex workloads. …”
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Improvement of classification accuracy of functional near-infrared spectroscopy signals for hand motion and motor imagery using a common spatial pattern algorithm by Omid Asadi, Mahsan Hajihosseini, Sima Shirzadi, Zahra Einalou, Mehrdad Dadgostar

“…This study aimed to address this challenge by employing the common spatial pattern (CSP) algorithm to reduce input dimensions for support vector machine (SVM) and linear discriminant analysis (LDA) classifiers. …”
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Modulation pattern recognition method of wireless communication automatic system based on IABLN algorithm in intelligent system. by Ting Xie, Xing Han

“…The Kappa coefficient in the Communication Signal Processing Benchmark for Machine Learning (CSPB.ML2018) 2018 dataset was 0.62, representing an average increase of 10.32% over other algorithms. …”
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Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy by Jing Zhang, Lulu Cheng, Shan Jiang, Duosheng Zhu

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Pattern and semantic analysis to improve unsupervised techniques for opinion target identification by Khairullah khan, Ashraf Ullah, Baharum Baharudin

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