A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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Research on Discrete Dynamic System Modeling of Vocal Performance Teaching Platform Based on Big Data Environment by Xiaohui Gong

“…The results show that the optimization model based on the deep recurrent neural network algorithm has the advantages of high feasibility, high intelligence, and wide range of applications. …”
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EDT-MCFEF: a multi-channel feature fusion model for emergency department triage of medical texts by Tao Lin, Shiming Yi

“…The model employs a hybrid masking approach and RoBERTa (Robustly Optimized BERT Approach) to facilitate feature enhancement and word vector processing of text. …”
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Connected Transit Bus Dynamic Priority Weight Modeling and Conflicting Request Resolution Control at the Signalized Intersection by Shuxian He, Haihang Han, Huan Zhang, Shanzhi Sun, Tony Z. Qiu

“…Moreover, for the transit signal priority system, how to establish a model to measure traffic demand for conflicting priority request resolution and improve system response time has been widely researched for the last few decades. …”
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Transmission and Generation Expansion Planning Considering Virtual Power Lines/Plants, Distributed Energy Injection and Demand Response Flexibility from TSO-DSO Interface by Flávio Arthur Leal Ferreira, Clodomiro Unsihuay-Vila, Rafael A. Núñez-Rodríguez

“…The flexibility from the TSO-DSO interconnection is also modeled, analyzing its impact on system expansion investments. …”
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Mortality prediction of heart transplantation using machine learning models: a systematic review and meta-analysis by Ida Mohammadi, Setayesh Farahani, Asal Karimi, Saina Jahanian, Shahryar Rajai Firouzabadi, Mohammadreza Alinejadfard, Alireza Fatemi, Bardia Hajikarimloo, Mohammadhosein Akhlaghpasand

“…IntroductionMachine learning (ML) models have been increasingly applied to predict post-heart transplantation (HT) mortality, aiming to improve decision-making and optimize outcomes. …”
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NeuroAdaptiveNet: A Reconfigurable FPGA-Based Neural Network System with Dynamic Model Selection by Achraf El Bouazzaoui, Omar Mouhib, Abdelkader Hadjoudja

“…By adaptively selecting the most suitable model configuration, NeuroAdaptiveNet achieves significantly improved classification accuracy and optimized resource usage compared to conventional, statically configured neural networks. …”
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Developing an Interpretable Machine Learning Model for Early Prediction of Cardiovascular Involvement in Systemic Lupus Erythematosus by Deng Z, Liu H, Chen F, Liu Q, Wang X, Wang C, Lyu C, Li J, Li T

“…Notably, the GBM model showed optimal performance, and its interpretability allowed clinicians to visualize decision-making processes, facilitating early identification of high-risk patients.Keywords: systemic lupus erythematosus, cardiovascular involvement, machine learning, prediction model, interpretability…”
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Enhancing Flexibility of Virtual Power Plants Considering Reconfiguration of District Heating Network by Peinan Fan, Yixun Xue, Haotian Zhao, Xinyue Chang, Jia Su, Ke Wang, Hongbin Sun

“…Case studies based on an actual CHP-VPP certify the validity of the proposed model and algorithm.…”
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Cooperative sensing method considering malicious nodes in cognitive radio networks by Xiao-gang QI, Sheng-yu ZHENG, Li-fang LIU, Hui-fang WANG

“…Based on a more practical cognitive radio network with malicious users,the spectrum sharing network model based on the cooperative spectrum sensing was studied that the secondary user can dynamically adjust its transmit power based on cooperative sensing results.To avoid significant reduction in performance of spectrum sensing system caused by malicious nodes,it is aimed to study how to improve the performance of cooperative sensing.By introducing the convex optimization problem,the secondary network throughput is maximized under the certain detection probability conditions and the corresponding power constraints.Simulation results show that whether or not there are malicious nodes,the algorithm is efficient in calculating optimal sensing time and the optimal transmit powers,and the secondary network throughput is increased when the maximum interference power limits and the maximum transmit power restrictions are decreased.…”
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Extended State Observer-Based Robust Model Predictive Velocity Control for Permanent Magnet Synchronous Motor by Eunji Lee, Yonghao Gui, Sesun You, Jun Moon, Wonhee Kim

“…Thus, the proposed method is robust against external disturbances and parameter uncertainties owing to feedback linearization, state feedback, and ESO-based MPC using the acceleration PMSM model. The proposed control algorithm was experimentally verified and it showed improved velocity tracking performance compared with ESO-based MPC using the conventional PMSM model.…”
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Prediction of Urban Rail Transit Train Door Faults Based on FOA-BP Neural Network Model by WEN Kaiyue, QIU Weibin, DING Xianze, OU Hongxiang

“…[Method] Taking the abnormal current signal of URT train door before failure as the research object, a FIR (finite impulse response) filter is designed to filter and dimensionally normalize the collected URT train door current signal data; the FOA (fruit fly optimization algorithm)-BP (back propagation) neural network model is used to train the closed state learning sample data of different doors after dimensional normalization, and output test results; FOA-BP results and output results after BP neural network models training are compared and analyzed. …”
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Automatic Synthesis of Recurrent Neurons for Imitation Learning From CNC Machine Operators by Hoa Thi Nguyen, Roland Olsson, Oystein Haugen

“…This article applies an evolutionary algorithm to synthesize recurrent neurons optimized for specific datasets. …”
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NLP for computational insights into nutritional impacts on colorectal cancer care by Shengnan Gong, Xiaohong Jin, Yujie Guo, Jie Yu

“…Colorectal cancer (CRC) is one of the most prominent cancers globally, with its incidence rising among younger adults due to improved screening practices. …”
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Research on Channel Modeling and Communication Coverage of Wireless Sensor Networks in Barrier Area of Nuclear Power Plants by Zhi-Guang Deng, Qian Wu, Xin Lv, Bi-Wei Zhu, Mei-Qiong Xiang, Xue-Mei Wang, Jia-Liang Zhu

“…Based on the channel modeling, this paper optimizes the coverage of the network in the obstacle area by using the improved teaching and learning group intelligent algorithm. …”
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A model study of teaching method reform of computer laboratory course integrating internet of things technology. by Xiao Zhou, Ledan Qian, Haider Aziz, Marvin White

“…In particular, face capture services improve student concentration to create an efficient classroom atmosphere by using face recognition algorithms that support end devices. …”
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Machine learning driven digital twin model of Li-ion batteries in electric vehicles: a review by Muaaz Bin Kaleem, Wei He, Heng Li

“…Recently, researchers are working on the development of digital twin models to automate and optimize the BMS state estimation process by utilizing machine learning (ML) algorithms and cloud computing. …”
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Enhancing Three-Dimensional Reconstruction Through Intelligent Colormap Selection by Alexandros Vrochidis, Dimitrios Tzovaras, Stelios Krinidis

“…This approach saves valuable time by recommending the most effective colormaps, eliminating the need to test each individually. …”
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Improving Vehicle Dynamics: A Fractional-Order PI<i>^λ</i>D<i>^μ</i> Control Approach to Active Suspension Systems by Zongjun Yin, Chenyang Cui, Ru Wang, Rong Su, Xuegang Ma

“…A fractional-order PI<i>^λ</i>D<i>^μ</i> (FOPID) controller was proposed, and its structural parameters were optimized using a gray wolf optimization algorithm. …”
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Development of a multidimensional data model for efficient content-based image retrieval in big data storage by Stanislav Danylenko, Serhii Smelyakov

“…The following results were obtained: Multi-Dimensional Cube (MDC) model with optimizations and search algorithms was developed. …”
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