Machine learning, clinical-radiomics approach with HIM for hemorrhagic transformation prediction after thrombectomy and treatment by Sheng Hu, Junyu Liu, Jiayi Hong, Yuting Chen, Ziwen Wang, Jibo Hu, Shiying Gai, Xiaochao Yu, Jingjing Fu

“…The support vector machine (SVM) was the optimal ML algorithm for constructing the models. …”
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Preliminary Study on Sensor-Based Detection of an Adherent Cell’s Pre-Detachment Moment in a MPWM Microfluidic Extraction System by Marius-Alexandru Dinca, Mihaita Nicolae Ardeleanu, Dan Constantin Puchianu, Gabriel Predusca

“…This optimizes detachment while minimizing liquid absorption and reflux volume, ensuring efficient extraction. …”
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Operators of potential type in problems of applied analysis by Igor Eduardovich Naats, Victoria Igorevna Naats, Roman Andreevich Riskalenko, Elena Pavlovna Yartseva

“…In the present work, the investigated function is in the form of the integral, Riemann-Stieltjes, on this view, formulate the corresponding optimization problem and defines its solution. Consider examples of integrals of performance of the studied functions and the corresponding computational scheme. …”
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Low-threshold dual-polarization electro-optic nonlinear activation functions by Tao Jin, Jian Lin, Pengjun Wang, Qiang Fu, Yuhan Sun, Yi Zou, Shixun Dai, Weiwei Chen, Jun Li, Tingge Dai, Jianyi Yang

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A DSP–FPGA Heterogeneous Accelerator for On-Board Pose Estimation of Non-Cooperative Targets by Qiuyu Song, Kai Liu, Shangrong Li, Mengyuan Wang, Junyi Wang

“…YOLOv5s is modified with a Focus module to enhance feature extraction, and URSONet adopts global average pooling to reduce the computational burden. Optimization techniques, including batch normalization fusion, ReLU integration, and linear quantization, are applied to improve inference efficiency. …”
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Chest Soft Tissue Schwannoma: a Difficult Case of Diagnosis by M. V. Perevedentsev, E. A. Podolskaya, N. S. Vorotyntseva, E. N. Kretova

“…The publication can help radiologists, ultrasound diagnosticians, morphologists, oncologists, surgeons to accumulate clinical experience for choosing optimal diagnostic methods and developing an algorithm for patient management.…”
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Knowledge Acquisition for the Stunting Prevention Expert System (SIPENTING) using Decision Tree and Grid Search by Azhar Basir, Fitri Ayuning Tyas

“…Decision Tree is one of the data mining algorithms used to generate rule bases. In this study, the Decision Tree algorithm is optimized using Grid Search as a knowledge acquisition technique to determine the rule base applied in the Stunting Prevention Expert System (SIPENTING). …”
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Innovation in Manufacturing Within the Digital Intelligence Context: Examining Faultlines Through Information Processing by Kangli Zhang, Jinwei Zhu

“…Using panel data from A-Share manufacturing listed companies between 2015 and 2023, we conducted programming in the R language employing hierarchical clustering and k-means algorithms for faultline grouping calculations. The empirical analysis portion utilized STATA software, where the Hausman test was implemented to determine the use of a fixed-effects model for computation. …”
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Interference Mitigation in Coexisting Satellites and Cloud-Assisted Ground Networks in the mmWave Band by Sirine Ben Ati, Hayssam Dahrouj, Mohamed-Slim Alouini

“…The paper assumes that a fraction of the ground base-stations connects to a centralized computing processor (i.e., cloud) using fronthaul links with limited capacity. …”
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Research review on intelligent object detection technology for coal mines based on deep learning by Fan ZHANG, Jiarong ZHANG, Haixing CHENG

“…However, deep learning object detection has a strong dependence on annotated datasets, and there are problems such as poor model interpretability and computational complexity. How to improve the accuracy, model adaptability, and computational efficiency of mine object detection is an urgent research topic in the field of mining artificial intelligence. …”
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Bio-Magneto Sensing and Unsupervised Deep Multiresolution Analysis for Labor Predictions in Term and Preterm Pregnancies by Ejay Nsugbe, Oluwarotimi Williams Samuel, Jose Javier Reyes-Lagos, Dawn Adams, Olusayo Obajemu

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Cloud Survivability Scenarios Under Attacks With and Without Countermeasures by Rachid Beghdad, Faiza Benmenzer, Alaa Eddine Khalfoune

“…Background: Despite its increasing importance, cloud computing is vulnerable to Distributed Denial of Service (DDoS) attacks, affecting data centre availability and functionality. …”
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Resource Management Based on Security Satisfaction Ratio with Fairness-Aware in Two-Way Relay Networks by Jun Zhao, Zhaoming Lu, Xiangming Wen, Haijun Zhang, Shenghua He, Wenpeng Jing

“…Moreover, a suboptimal subchannel pairing algorithm is proposed to reduce the computational complexity compared with the CHA. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…By integrating the predictive power of computational models and the data‐driven insights of AI, the synergy between these approaches has the potential to accelerate drug discovery, optimize treatment strategies, and usher in a new era of personalized medicine, benefiting patients, researchers, and the pharmaceutical industry as a whole.…”
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Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent. by Alejandra de-la-Rica-Escudero, Eduardo C Garrido-Merchán, María Coronado-Vaca

“…In this work, driven by the motivation of making DRL explainable, we developed a novel Explainable DRL (XDRL) approach for PM, integrating the Proximal Policy Optimization (PPO) DRL algorithm with the model agnostic explainable machine learning techniques of feature importance, SHAP and LIME to enhance transparency in prediction time. …”
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Adaptive User Pairing With Non-Orthogonal Medium Access Choices for Balanced Coexistence of Mission-Critical and eMBB Services in Cellular IoT by Farnaz Khodakhah, Aamir Mahmood, Patrik Osterberg, Mikael Gidlund

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Automated analysis and textual summarization of time-varying references in advanced greenhouse climate control by Ramesh Arvind Naagarajan, Kiran Kumar Sathyanarayanan, Nadja Bauer, Stefan Streif, Stefan Streif

“…This technique generates time-varying climate reference trajectories, which are sent to the local process computer to control the corresponding climate parameter or equipment. …”
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A model-based Decision Support System for multiple container terminals hub management by Francesco Facchini, Francesco Boenzi, Salvatore Digiesi, Giovanni Mummolo

“…Research method The model is based on a heuristic computational algorithm for non-linear programming. …”
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Time-Dependent Vehicle Routing of Free Pickup and Delivery Service in Flight Ticket Sales Companies Based on Carbon Emissions by Jingmei Guo, Chao Liu

“…The heuristic algorithm is embedded into a set-partitioning model to produce high-quality routing plans. …”
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Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors. by Montaser Abdelsattar, Mohamed A Ismeil, Karim Menoufi, Ahmed AbdelMoety, Ahmed Emad-Eldeen

“…This study's novelty lies in directly comparing a diverse range of ML and DL algorithms while highlighting the potential of advanced computational approaches for renewable energy optimization.…”
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