A regression based approach to phylogenetic reconstruction from multi-sample bulk DNA sequencing of tumors. by Henri Schmidt, Benjamin J Raphael

“…This algorithm has both asymptotic and empirical improvements over linear programming (LP) approaches to the problem. …”
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Advancing thyroid diagnosis: integrating AI-driven CAD framework with numerical data and ultrasound images by Saleh Ateeq Almutairi

“…The proposed CAD framework employs the sparse search algorithm (SSA) for optimized feature selection from numerical data and the tree-structured Parzen estimator for tuning the hyperparameters. …”
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Research on the integrated "cloud-edge-end" intelligent and precise management and control technology system for coal mine disasters by LIU Yubing, LI Yiteng, LI Zhonghui, YIN Shan, JING Chao, LI Kai, LI Zhenxing, ZHAO Shenglei, LIU Chengfei

“…Existing research mainly focuses on monitoring and early warning technologies or algorithm optimization for individual disasters, lacking a coordinated mechanism for multi-disaster monitoring and early warning, as well as disaster avoidance path planning under emergency response. …”
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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…DNN demonstrates strong capabilities in handling complex nonlinear relationships, and XGBoost further improves classification accuracy by optimizing decision tree models through gradient boosting. …”
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Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning by Johan Helleberg, Anna Sundelin, Johan Mårtensson, Olav Rooyackers, Ragnar Thobaben

“…The best performing algorithm was extreme gradient boosting (XGboost) using 9 features, with an AUCPR of 0.9974 (95% CI 0.9961–0.9984), significantly better than the LR model (AUCPR = 0.9791, 95% CI 0.9651–0.9904). …”
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Target Detection in Low Grazing Angle with Adaptive OFDM Radar by Yang Xia, Zhiyong Song, Zaiqi Lu, Hao Wu, Qiang Fu

“…Then, we propose an algorithm to optimally design the transmitted subcarrier weights to improve the detection performance. …”
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Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis by Ping Li, Hua Zhang, Sang-Bing Tsai

“…With the application of an automatic scoring system to all kinds of oral English tests at all levels, the efficiency of test implementation has been greatly improved. The traditional speech signal processing method only focuses on the extraction of scoring features, which could not ensure the accuracy of the scoring algorithm. …”
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Advanced GPU Techniques for Dynamic Remeshing and Self-Collision Handling in Real-Time Cloth Tearing by Jong-Hyun Kim, Jung Lee

“…We also present a method to optimize kernels based on a complete binary tree in arbitrary triangular meshes, improving performance. …”
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Research on Near-Infrared Non-Invasive Blood Glucose Detection Technology by Wang Jinshuo

“…In response to the complex and easily interfered characteristics of near-infrared spectral signals, an innovative BP neural network algorithm is introduced to construct a prediction model. …”
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An Integrated Approach to Scheduling B-CAVs in Container Terminals considering Battery Management by Shuo Wang, Jiliang Luo, Weimin Wu, Dahai Zhang, Tao Zhang

“…Furthermore, a congestion-free path plan-based improved genetic algorithm is presented to obtain a near-optimal plan for dispatching B-CAVs to perform transporting and charging operations. …”
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Susceptibility assessment of freeze-thaw erosion induced debris flow using random forest, Eastern Tibetan Plateau by Yongjie Yang, Yongjie Yang, Yongjie Yang, Yuqi Zhang, Yuqi Zhang, Yuqi Zhang, Hai Huang, Hai Huang, Jinsong Zhu, Jinsong Zhu, Jinsong Zhu, Qiwei Lv, Qiwei Lv, Qiwei Lv, Jiang Peng, Jiang Peng

“…Control factors with high frequency and performance were selected from the perspectives of material sources, dynamic conditions, and hydrological factors, leading to an optimized selection strategy, and the Random Forest Algorithm was employed for susceptibility assessment (No Freeze-thaw erosion model, NFEM). …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…The neural network was trained on a highly imbalanced dataset, using oversampling and Bayesian hyperparameter optimization. The final classification algorithm achieved classification metrics with high accuracy (99%). …”
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Load-dependent vehicle routing problem with route time constraint: a heuristic approach by Nguyen Thuy Trang, Parthana Parthanadee, Jirachai Buddhakulsomsiri, Pham Duc Tai

“…The results show that for instances with known optimal solutions, the heuristic algorithm can reach solutions with small gaps to the optimal. …”
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Industrial-scale prediction of cement clinker phases using machine learning by Sheikh Junaid Fayaz, Néstor Montiel-Bohórquez, Shashank Bishnoi, Matteo Romano, Manuele Gatti, N. M. Anoop Krishnan

“…Abstract Cement production exceeds 4.1 billion tonnes annually, emitting 2.4 billion tonnes of CO2 annually, necessitating improved process control. Traditional models, limited to steady-state conditions, lack predictive accuracy for clinker mineralogical phases. …”
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Vehicle Reidentification via Multifeature Hypergraph Fusion by Wang Li, Zhang Yong, Yuan Wei, Shi Hongxing

“…To merge multiple feature descriptors, an efficient and appropriate representation is particularly necessary, and a hypergraph is naturally suitable for modeling high-order relationships. In addition, the spatiotemporal correlation of traffic status between cameras is the constraint beyond the image, which can greatly improve the re-ID accuracy of different vehicles with similar appearances. …”
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Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks by Shakil Ahmed, Mostafa Zaman Chowdhury, Saifur Rahman Sabuj, Md Imtiajul Alam, Yeong Min Jang

“…We compare our algorithm with existing algorithms and demonstrate the improved EE UAV relaying communication for our model.…”
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Un Algoritmo de Estimación de Distribuciones copulado con la Distribución Generalizada de Mallows para el Problema de Ruteo de Autobuses Escolares con Selección de Paradas by Ricardo Pérez-Rodríguez, Arturo Hernández-Aguirre

“…Different and diverse instances served as input and test parameters in order to show that permutation-based optimization problems such as the school bus routing problem with bus stop selection can be solved by means of a probability model, and improving the estimation of the central permutation helps the performance of the algorithm. …”
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Artificial intelligence based classification and prediction of medical imaging using a novel framework of inverted and self-attention deep neural network architecture by Junaid Aftab, Muhammad Attique Khan, Sobia Arshad, Shams ur Rehman, Dina Abdulaziz AlHammadi, Yunyoung Nam

“…The extracted features are fused using a modified serial fusion with a strong correlation approach. An optimization algorithm- slap swarm controlled standard Error mean (SScSEM) has been employed, and the best features that passed to the shallow wide neural network (SWNN) classifier for the final classification have been selected. …”
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High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics by Nauman Ahmed, Huigang Wang, Shanshan Tu, Norah A.M. Alsaif, Muhammad Asif Zahoor Raja, Muhammad Kashif, Ammar Armghan, Yasser S. Abdalla, Wasiq Ali, Farman Ali

“…For this purpose, particle swarm optimization (PSO), minimum variance distortion-less response (MVDR), multiple signal classification (MUSIC), and estimation of signal parameter via rotational invariance technique (ESPRIT) standard counterparts are employed along with Crammer–Rao bound (CRB) to improve the worth of the proposed setup further. …”
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Collision-Free Path Planning for Multiple Drones Based on Safe Reinforcement Learning by Hong Chen, Dan Huang, Chenggang Wang, Lu Ding, Lei Song, Hongtao Liu

“…To this end, this paper proposes an end-to-end planning method based model-free RL framework with optimization, which can achieve better learning performance with a safety guarantee. …”
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