Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…Finally, the CADHDD-SFLNHM model implements the pelican optimization algorithm (POA) method to fine-tune the hyperparameters involved in the CNN-BiGRU-A method. …”
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Quantum Feasibility Labeling for NP-Complete Vertex Coloring Problem by Junpeng Zhan

“…Currently, neither existing classical nor quantum algorithms can solve these problems in polynomial time. …”
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Clinical significance of human epididymis protein 4 (HE4), cancer antigen 125 (CA125), the risk of ovarian malignancy algorithm (ROMA), and Copenhagen index (CPH-I) for the diagnos... by Vesselina Koleva, Sevim Shefket, Snezhana Stoencheva

“…The subgroup analysis based on the histological type of EC revealed that the highest markers and algorithms were recorded in type II EC group. …”
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Explainable machine learning algorithms to identify predictors of intention to use family planning among women of reproductive-age in Ethiopia: Evidence from the Performance Monito... by Agmasie Damtew Walle, Shimels Derso Kebede, Jibril Bashir Adem, Tewodros Desalegn Nebi, Daniel Niguse Mamo, Sudi Jemal Wado, Ermias Bekele Enyew

“…It is widely believed that intentions are a strong predictor of behaviours, and many interventions that aim to change behaviour, including those targeting FP use, rely on evaluating programme effectiveness through analysis of behavioural intentions. …”
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Preventing Spurious Interactions: A New Inductive Bias for Accurate Treatment Effect Estimation by Roger Pros, Jordi Vitria

“…In recent years, the use of non-linear machine learning techniques to estimate treatment effects from observational data has gained significant attention. Many of the most effective methods incorporate specific algorithmic inductive biases that encode causal information, thereby enhancing the precision of treatment effect estimates. …”
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APPROACH TO BUILDING A GLOBAL MOBILE AGENT WAY BASED ON Q-LEARNING by Vitalii Martovytskyi, Oleksandr Ivaniuk

“…At the moment, there are many algorithms that allow you to solve such problems in accordance with the specified criteria for building a route. …”
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Research on Abstraction-Based Search Space Partitioning and Solving Satisfiability Problems by Yuexin Huang, Qinzhou Niu, Yanfang Song

“…Solving satisfiability problems is central to many areas of computer science, including artificial intelligence and optimization. …”
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Efficient Structural Damage Detection with Minimal Input Data: Leveraging Fewer Sensors and Addressing Model Uncertainties by Fredi Alegría, Eladio Martínez, Claudia Cortés-García, Quirino Estrada, Andrés Blanco-Ortega, Mario Ponce-Silva

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Analysis of physical properties in white and whole wheat sliced bread using digital image processing by Neiry-Dayán Martínez-Lara, Claudia L. Garzón-Castro, Annamaria Filomena-Ambrosio

“…Abstract Many studies have addressed the reformulation and preservation of sliced bread, yet the evaluation of its physical properties often demands standardized procedures and extensive manual labor. …”
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Quantum distance approximation for persistence diagrams by Bernardo Ameneyro, Rebekah Herrman, George Siopsis, Vasileios Maroulas

“…In particular we propose variational quantum algorithms for the Wasserstein distance as well as the $d^{c}_{p}$ distance. …”
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Food Sales Prediction Using MLP, RANSAC, and Bagging by Hussam Mezher Merdas, Ayad Hameed Mousa

“… Many datasets about food sales, these datasets contain different features depending on the data present. …”
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Bit-Level Construction for Multiplicative-Repetition-Based Non-Binary Polar Codes by Rongchi Xu, Peiyao Chen, Ling Liu, Min Zhu, Baoming Bai

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Solving a Global-Mixed Integer Signomial Geometric Fractional Programming Problem by J. Shirin Nejad, M. Saraj

“…Therefore, we apply a spatial branch and bound algorithm to decrease that distance to an acceptable extent and maintain the global solution. …”
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Suggesting a Novel Hybrid Approach for Predicting Solar Irradiance in the Qinghai Province of China by Baran Yılmaz, Rachel Samra

“…In this work, long short-term memory has been optimized using Particle swarm optimization, Grasshopper optimization algorithm, and Slime mold algorithm. SMA-LSTM, which has the best performance result compared to other developed models, is presented as the main method for this work. …”
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Football sports video tracking and detection technology based on YOLOv5 and DeepSORT by Bin Wang

“…Abstract Enhancing the analysis of football sports video is of great practical significance and commercial value for tactical analysis, player performance evaluation, tournament broadcasting, and many other aspects. Considering that the current target detection and tracking is characterized by complex scene changes, target occlusion, and obvious external motion interference, the study proposes to improve the YOLOv5 and DeepSORT algorithms for improving the tracking and detection accuracy of sports video to enhance its application performance. …”
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A Hybrid Optimization Approach for Improving Sensor Configuration to Enhance Nasogastric Tube (NGT) Localization During Insertion and Withdrawal by M. Souganttika, Shaohui Foong

“…However, achieving great precision usually necessitates many sensors, increasing computational burden and system complexity. …”
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A traction load modeling method of metro trains based on the regenerative braking energy effective utilization and its application by SHI Dan, GAO Dongsheng, YANG Rui

“…Currently, many metro lines use ground energy storage facilities to gather regenerative braking energy of trains. …”
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Predicting Student Performance through Machine Learning Methods: Naive Bayesian Classifier by Chenyang Li, Qianzhi Zhou, Luming Du, Sihan Zhang

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Exploiting Extrinsic Information for Serial MAP Detection by Utilizing Estimator in Holographic Data Storage Systems by Thien An Nguyen, Jaejin Lee

“…This leads to the development of storage devices. Many technologies are proposed for the next generation of storage fields. …”
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Automated Pruning Framework for Large Language Models Using Combinatorial Optimization by Patcharapol Ratsapa, Kundjanasith Thonglek, Chantana Chantrapornchai, Kohei Ichikawa

“…Currently, large language models (LLMs) have been utilized in many aspects of natural language processing. However, due to their significant size and high computational demands, large computational resources are required for deployment. …”
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