YOLO-OHFD: A YOLO-Based Oriented Hair Follicle Detection Method for Robotic Hair Transplantation by Hui Wang, Xin Liu

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A prediction method for anti-cancer drug combinations synergy based on graph attention network by QIN Weiqi;BAO Xin;CHEN Xiao;QIU Jianlong;WANG Donglin

“…Evaluated on a public dataset, MFGSynergy outperforms Deep DDS, DeepSynergy, and six machine learning methods, achieving receiver operating characteri-stic area under the curve(ROC AUC), area under the precision-recall curve(PR AUC), accuracy(ACC), precision(PREC), true positive rate(TPR), and F1scores of 0.94, 0.94, 0.86, 0.87, 0.86, and 0.86, respectively, in five-fold cross-validation. …”
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Indoor Positioning System based on SSA-ELM Neural Network for Visible Light by JIA Kejun, NIU Zhen, YU Kai, ZHANG Zhicong, PENG Duo, CAO Minghua

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Exploring non-zero position constraints: algorithm-hardware co-designed DNN sparse training method by WANG Miao, ZHANG Shengbing, ZHANG Meng

“…And based on these rules, this paper proposed a parev hardware-friendly sparse training algorithm to reduce the computation and storage pressure of the three phases, and an energy-efficient sparse training accelerator that can be executed in parallel with the forward propagation computation to estimate the non-zero positions so that the runtime processing cost is masked. …”
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An online escape room as an icebreaker in interdisciplinary and international health care professions education: A pilot mixed-methods study of “UKA Escape” by Lemos, Martin, Kouchev, Veronique, Bell, Laura

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Monocular vision based on the YOLOv7 and coordinate transformation for vehicles precise positioning by Jingzhao Li, Huashun Li, Xiaobo Zhang, Qing Shi

“…The coordinate position of the beacon on the image is obtained through the YOLOv7 model based on transfer learning. …”
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Designing, Implementation, and Evaluation of Game-based Education in Pediatric Nursing Care Course by Fatemeh Ebrahimpour, Manijeh Nourian, Maryam Varzeshnejad

“…Introduction: Game-based education is a new method of teaching and learning in nursing education that can effectively enable teacher and learner to achieve educational goals. …”
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An Application Programming Interface (API) Sensitive Data Identification Method Based on the Federated Large Language Model by Jianping Wu, Lifeng Chen, Siyuan Fang, Chunming Wu

“…The traditional methods for identifying sensitive data in APIs mainly encompass rule-based and machine learning-based approaches. …”
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Passivity-Based Control for Rocket Launcher Position Servo System Based on ADRC Optimized by IPSO-BP Algorithm by Rong-lin Wang, Bao-chun Lu, Yuan-long Hou, Qiang Gao

“…In order to achieve better motion accuracy and higher robustness of the shipborne rocket launcher position servo system driven by a permanent magnet synchronous motor (PMSM), a passivity-based controller based on active disturbance rejection control (ADRC) optimized by improved particle swarm optimization-back propagation (IPSO-BP) algorithm is proposed in this paper. …”
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The dynamic case-based learning model: conducive to enhancing the practical learning effectiveness of dermatology for medical students by Yidan Li, Li Lei, Ling Jiang, Ping Mao, Chuhan Fu, Jing Chen, Qinghai Zeng

“…Methods This study proposes the dynamic case-based learning (DCBL) model, which was presented through typical dynamic cases. …”
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Research on a Panoramic Image Stitching Method for Images of Corn Ears, Based on Video Streaming by Yi Huangfu, Hongming Chen, Zhonghao Huang, Wenfeng Li, Jie Shi, Linlin Yang

“…<b>Methods:</b> A summary of corn ear panoramic stitching methods under complex backgrounds is presented as follows: 1. a perceptual hash algorithm and histogram equalization were used to extract video frames; 2. the U-Net image segmentation model based on transfer learning was used to predict corn labels; 3. a mask preprocessing algorithm was designed; 4. a corn ear splicing positioning algorithm was designed; 5. an algorithm for irregular surface expansion was designed; 6. an image stitching method based on template matching was adopted to assemble the video frames. …”
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Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors by Nazanin Mola, Hrafn Weishaupt, Valentin Krasontovitsch, Erlend Hodneland, Sabine Leh

“…Our findings highlight the enhanced accuracy of ML-based image analysis in detecting the correct tumor cells, outperforming traditional methods.…”
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Prognostic correlation analysis of colorectal cancer patients based on monocyte to lymphocyte ratio and folate receptor-positive circulating tumor cells and construction of a machi... by Siying Pan, Chi Lu, Chi Lu, Hongda Lu, Hongda Lu, Hongfeng Zhang

“…PurposeTo evaluate the prognostic value of the monocyte to lymphocyte ratio (MLR) and folate receptor-positive circulating tumor cells (FR+CTCs) in patients with colorectal cancer (CRC) and to develop predictive model for post-treatment survival using machine learning (ML) algorithms.MethodsWe retrospectively analyzed 67 CRC patients treated with radical surgery or chemoradiotherapy at The Central Hospital of Wuhan from January 2020 to December 2022. …”
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Explainable machine learning prediction of internet addiction among Chinese primary and middle school children and adolescents: a longitudinal study based on positive youth develop... by Jiahe Liu, Lang Chen, Yuxin Chen, Jingsong Luo, Kexin Yu, Linlin Fan, Chan Yong, Huiyu He, Simei Liao, Zongyuan Ge, Lihua Jiang, Lihua Jiang

“…Our study aimed to examine the risk factors associated with IA among Chinese children and adolescents and leverage explainable machine learning (ML) algorithms to predict IA status at the time of assessment, based on Young’s Internet Addiction Test.MethodsThe longitudinal data consisting of 8,824 schoolchildren from the Chengdu Positive Child Development (CPCD) survey were analyzed, where 33.3% of participants were identified with IA (Age: 10.97 ± 2.31, Male: 51.73%). …”
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Game-Based Learning: Alternative Approaches to Teaching and Learning Strategies in Health Sciences Education by Zijing Hu

“…The findings of this study revealed that game-based learning positively promoted students’ learning experiences and their curriculum outcomes. …”
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Electroencephalogram-Based Emotion Classification Using Machine Learning and Deep Learning Techniques by Gst Ayu Vida Mastrika Giri, Made Leo Radhitya

“…SVM, K-NN, and MLP have accuracy scores of 0.98, 0.95, and 0.97. Deep learning methods CNN, LSTM, and GRU had 0.98, 0.82, and 0.97 accuracy. …”
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Investigation of students' academic participation in combined learning based on learning management system. by Daryadokht Masroor Roudsar, Haghani Hamid, Dehnad Afsaneh, Mojtaba Ghanbari Ghalesari, Shoub Ghasemi Maryam, Rokni Akbarian Mostafa

“…The present study aimed to investigating the relationship between academic participation of nursing students who use combination education based on learning management system (LMS) and studied their degree of academic participation. …”
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Implementation of Technology-Based Interactive Learning Media in Supporting Students’ Learning Motivation by Ummu Salma, Haris Habibul Fattah, Eko Setiawan, Ika Ratih Sulistiani

“…This study specifically aims to explore the implementation of technology-based interactive learning media, reveal the effect of technology-based interactive learning media on students’ learning motivation, and identify supporting and inhibiting factors in the implementation of technology-based learning in PAI subjects at SMPI Salafiyah Singosari. …”
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PODCAST-BASED LEARNING: EVALUATING THE SUCCESS OF LEARNING MEDIA DEVELOPMENT IN VOCATIONAL EDUCATION by R Eka Murtinugraha, Shilmi Arifah, Rosmawita Saleh, Riyan Arthur, Nindya Reza Ostiyani

“…Purpose – This study evaluates the success of developing podcast-based learning media in Vocational Education Management courses in higher education. …”
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Adaptive Federated Learning With Reinforcement Learning-Based Client Selection for Heterogeneous Environments by Shamim Ahmed, M. Shamim Kaiser, Sudipto Chaki, A. B. M. Shawkat Ali

“…The framework integrates reinforcement learning (RL) based client selection using both Tabular Q-Learning and Deep Q-Network (DQN) strategies to dynamically identify clients that most positively impact global model performance. …”
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