Prognostication of Learning Curve on Surgical Management of Vasculobiliary Injuries after Cholecystectomy by Abu Bakar Hafeez Bhatti, Faisal Saud Dar, Haseeb Zia, Muhammad Salman Rafique, Nusrat Yar Khan, Mohammad Salih, Najmul Hassan Shah

“…Whether a new HPB center should embark upon repair of complex biliary injuries with associated vascular injuries during learning curve is unknown. The objective of this study was to determine outcome of surgical management of IBDI with and without vascular injuries in a new HPB center during its learning curve. …”
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A Study On The Usage Of M-Learning Applications Within Bulgarian Schools by Bonimir Penchev

Subjects: “…M-learning applications…”
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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

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Machine learning of swimming data via wisdom of crowd and regression analysis by Jiang Xie, Junfu Xu, Celine Nie, Qing Nie

“…For the first time, statistical analysis and machine learning methods are systematically applied to 4,022,631 swim records. …”
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Anomaly Detection in IoMT Environment Based on Machine Learning: An Overview by Peyman Vafadoost Sabzevar, Hamidreza Rokhsati, Alireza Chamansara, Ahmad Hajipour

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Multi-Agent Hierarchical Graph Attention Actor–Critic Reinforcement Learning by Tongyue Li, Dianxi Shi, Songchang Jin, Zhen Wang, Huanhuan Yang, Yang Chen

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Living, Caring, Learning - Changing mindsets and enabling goals for people with haemophilia by Cruickshank Anne-Louise

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Research on Typhoon Prediction by Integrating Numerical Simulation and Deep Learning Methods by Tianyi Lv, Huaming Yu, Liangshi Lin, Yijun Tao, Xin Qi

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p-Norm Broad Learning for Negative Emotion Classification in Social Networks by Guanghao Chen, Sancheng Peng, Rong Zeng, Zhongwang Hu, Lihong Cao, Yongmei Zhou, Zhouhao Ouyang, Xiangyu Nie

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The Learning Continuum: A Model for Sustained Participation with Hard-to-Serve Clients by Elizabeth B. Bolton

“… This report, The Learning Continuum: A Model for Sustained Participation with Hard-to-Serve Clients, is part of the UF/IFAS Welfare-to-Work Initiative (Grant #A6218) funded by the Florida Agency for Workforce Innovation (formerly Florida Department of Labor and Employment Security). …”
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Ferrography Wear Particles Image Recognition Based on Extreme Learning Machine by Qiong Li, Tingting Zhao, Lingchao Zhang, Wenhui Sun, Xi Zhao

“…However, the feedforward neural network based on traditional gradient training algorithms for image segmentation creates many issues, such as needing multiple iterations to converge and easy fall into local minimum, which restrict its development heavily. Recently, extreme learning machine (ELM) for single-hidden-layer feedforward neural networks (SLFN) has been attracting attentions for its faster learning speed and better generalization performance than those of traditional gradient-based learning algorithms. …”
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PPPs Policy Entity Network Change and Policy Learning in Mainland China by Ying Jiang, Qian Wang

“…Taking 201 policy documents promulgated from 1995 till 2019 as a research sample, this paper explores PPPs policy entity network change and policy learning behind it in China. Research results show the following: (1) China’s PPPs policy entity network has mainly gone through three stages: partial-focus network with bad stability, loose-multiactor network with general stability, and balanced-multiactor network with good stability; (2) the key players are NPC in the first stage, MOF and NDRC in the second stage, and MOF and 8 other government entities in the third stage; (3) policy learning behind PPPs policy entity network change is government learning in the first stage and lesson-drawing in the second and third stages.…”
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Monitoring Population Phenology of Asian Citrus Psyllid Using Deep Learning by Maria Bibi, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Muhammad Irfan Khan, Shouket Zaman Khan, Casper Shikali Shivachi, Asad Anees

“…In the current study, several prediction models were developed based on regression algorithms of machine learning to monitor different phenological stages of Asian citrus psyllid to predict its population about different abiotic variables (average maximum temperature, average minimum temperature, average weekly temperature, average weekly relative humidity, and average weekly rainfall) and biotic variable (host plant phenological patterns) in citrus-growing regions of Pakistan. …”
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Direction-of-Arrival Estimation for Coherent Sources via Sparse Bayesian Learning by Zhang-Meng Liu, Zheng Liu, Dao-Wang Feng, Zhi-Tao Huang

“…A spatial filtering-based relevance vector machine (RVM) is proposed in this paper to separate coherent sources and estimate their directions-of-arrival (DOA), with the filter parameters and DOA estimates initialized and refined via sparse Bayesian learning. The RVM is used to exploit the spatial sparsity of the incident signals and gain improved adaptability to much demanding scenarios, such as low signal-to-noise ratio (SNR), limited snapshots, and spatially adjacent sources, and the spatial filters are introduced to enhance global convergence of the original RVM in the case of coherent sources. …”
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Machine Learning-Based Multiagent Control for a Bunch of Flexible Robots by Jun Wang, Jiali Zhang, Jafar Tavoosi, Mohammadamin Shirkhani

“…In this paper, two novel methodologies of employing machine learning (here, the type-2 fuzzy system) are presented to control a multiagent system in which the agents are flexible joint robots. …”
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Ensemble learning-based predictor for driver synonymous mutation with sequence representation. by Chuanmei Bi, Yong Shi, Junfeng Xia, Zhen Liang, Zhiqiang Wu, Kai Xu, Na Cheng

“…Subsequently, we propose EPEL, an effect predictor for synonymous mutations employing ensemble learning. EPEL combines five tree-based models and optimizes feature selection to enhance predictive accuracy. …”
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Examining the Use of Machine Learning Algorithms to Enhance the Pediatric Triaging Approach by Aljubran HJ, Aljubran MJ, AlAwami AM, Aljubran MJ, Alkhalifah MA, Alkhalifah MM, Alkhalifah AS, Alabdullah TS

Subjects: “…machine learning…”
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Integrating IoT data and reinforcement learning for adaptive macroeconomic policy optimization by Cong Peng, Yongshan Zhang, Liheng Jiang

“…To address this, we propose MLD-Net, a framework that combines IoT high-frequency data with economic data through MIDAS regression, LSTM networks for temporal dynamics, and Deep Q-Networks (DQN) for reinforcement learning-based policy optimization. MLD-Net effectively aligns multi-frequency data, captures complex temporal patterns, and adjusts policies in real-time. …”
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Visual Semantic Navigation Based on Deep Learning for Indoor Mobile Robots by Li Wang, Lijun Zhao, Guanglei Huo, Ruifeng Li, Zhenghua Hou, Pan Luo, Zhenye Sun, Ke Wang, Chenguang Yang

“…In order to improve the environmental perception ability of mobile robots during semantic navigation, a three-layer perception framework based on transfer learning is proposed, including a place recognition model, a rotation region recognition model, and a “side” recognition model. …”
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Transmission Lines Insulator State Detection Method Based on Deep Learning by Xu Tan, Shiying Hou, Fan Yang, Zhimin Li

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