Implementation and Performance Evaluation of Quantum Machine Learning Algorithms for Binary Classification by Surajudeen Shina Ajibosin, Deniz Cetinkaya

“…In this work, we studied the use of Quantum Machine Learning (QML) algorithms for binary classification and compared their performance with classical Machine Learning (ML) methods. …”
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A Novel Traffic Scheduling Algorithm for Multi-CQF Using Mixed Integer Programming and Variable Neighborhood Search Genetic Algorithm in Time-Sensitive Networking by Cheng Wang, Zhiquan Lin, Yuhao Zhao, Fen Hu, Zhan Huan

“…In its original form, Multi-CQF-based scheduling algorithms do not account for flow sorting, leading to increased transmission delays and reduced network efficiency as a network dynamically changes. …”
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Compression Index Regression of Fine-Grained Soils with Machine Learning Algorithms by Mintae Kim, Muharrem A. Senturk, Liang Li

“…This study employs machine learning algorithms—the random forest regressor (RFR), gradient boosting regressor (GBR), and AdaBoost regressor (ABR)—to predict the <i>C_c</i> values based on a dataset comprising 915 samples. …”
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Greedy Graph Coloring and Hungarian Algorithms for Resource Scheduling in TWDM-PON by Sandra Arnaout, Md Arifur Rahman, Md Munjure Mowla, Slawomir Hausman, Piotr Korbel

“…Numerical simulations show that the proposed GGCA and HA provide approximately 70- 80% delay reduction compared to a fixed baseline algorithm that schedules the timeslots and the wavelength in a fixed manner.…”
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Optimization of data allocation in hierarchical memory for blocked shortest paths algorithms by A. A. Prihozhy

“…This paper is devoted to the reduction of data transfer between the main memory and direct mapped cache for blocked shortest paths algorithms (BSPA), which represent data by a D[M×M] matrix of blocks. …”
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Computer-Aided Quantum Algorithms for Real-Time Energy Market Trading by Jinghui Wu, Wenjun Zhu, Yun Xu, Kangan Shu, Wei Yang

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Research on fusion prediction model of wind speed, gas and dust concentration under wind flow control in fully-mechanized heading face by Xiaoyan GONG, Hao ZOU, Zhuangzhuang LIU, Long CHEN, Haoran FU, Yuheng SUN, Hao LI, Xinyu WANG, Huming NIU

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Prediction and Impact Analysis of Soil Nitrogen and Salinity Under Reclaimed Water Irrigation: A Case Study by Zeyu Liu, Kai Fang, Xiaoqin Sun, Yandong Wang, Zhuo Tian, Jing Liu, Liying Bai, Qilin He

“…The models achieved high predictive accuracy, with NSE values of 0.918, 0.946, 0.936, 0.967, and 0.887 for NO₃⁻-N, NH₄⁺-N, TN, EC, and Cl⁻, respectively, demonstrating their robustness. …”
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Selection of methods and tools of voltage unbalance reduction within the Eastern part of Siberian integrated power system by V. V. Dikovich, E. M. Katz, O. S. Stremilova

“…The article includes the analysis of various technical tools for voltage unbalance reduction within the Eastern part of IPS of Siberia and describes control algorithms for them. …”
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Proactive spectrum handoff in distributed cognitive radio networks by Hua JIANG, Li-chuan MA, Ding-yu YAN, Nan PAN

Subjects: “…distributed cognitive radio network;spectrum handoff;spectrum prediction;task allocation algorithm of ant colony…”
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A Multi-Fusion Early Warning Method for Vehicle–Pedestrian Collision Risk at Unsignalized Intersections by Weijing Zhu, Junji Dai, Xiaoqin Zhou, Xu Gao, Rui Cheng, Bingheng Yang, Enchu Li, Qingmei Lü, Wenting Wang, Qiuyan Tan

Subjects: “…pedestrian trajectory prediction…”
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Novel load balancing mechanism for cloud networks using dilated and attention-based federated learning with Coati Optimization by Atul B. Kathole, Viomesh Kumar Singh, Ankur Goyal, Shiv Kant, Amit Sadanand Savyanavar, Swapnaja Amol Ubale, Prince Jain, Mohammad Tariqul Islam

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Development and Validation of an Interpretable Machine Learning Model for Prediction of the Risk of Clinically Ineffective Reperfusion in Patients Following Thrombectomy for Ischem... by Hu X, Qi D, Li S, Ye S, Chen Y, Cao W, Du M, Zheng T, Li P, Fang Y

“…Our CIR risk prediction platform enables early intervention and personalized treatment. …”
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Comparing variable neighbourhood search algorithms for the direct aperture optimisation in radiotherapy by Mauricio Moyano, Keiny Meza-Vasquez, Gonzalo Tello-Valenzuela, Nicolle Ojeda-Ortega, Carolina Lagos, Guillermo Cabrera-Guerrero

“…We apply our proposed algorithms to prostate cancer cases, achieving highly competitive results for both algorithms. …”
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Development and validation of multimodal deep learning algorithms for detecting pulmonary hypertension by Wei Zhao, Zhihua Huang, Xiaolin Diao, Zhan Yang, Zhihui Zhao, Yun Xia, Qing Zhao, Zhaohong Sun, Qunying Xi, Yanni Huo, Ou Xu, Jiahui Geng, Xin Li, Anqi Duan, Sicheng Zhang, Luyang Gao, Yijia Wang, Sicong Li, Qin Luo, Zhihong Liu

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SINGULAR VALUE VERSUS EIGENVALUE DECOMPOSITION EFFICIENCY IN COMPUTING PRINCIPAL COMPONENTS FOR DIMENSIONALITY REDUCTION OF LARGE DATASETS by Vadim Romanuke

“… Principal component analysis, being one of the best techniques for dimensionality reduction, is implemented by using one of the two high-accuracy algorithms: the singular value decomposition (SVD) and eigenvalue decomposition (EVD). …”
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Research on Hybrid Wind Speed Prediction System Based on Artificial Intelligence and Double Prediction Scheme by Ying Nie, He Bo, Weiqun Zhang, Haipeng Zhang

“…Regarding point prediction in the developed double prediction system, a novel nonlinear integration method based on a backpropagation network optimized using the multiobjective evolutionary algorithm based on decomposition was successfully implemented to derive the final prediction results, which enable further improvement of the accuracy of point prediction. …”
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Enhanced Multilinear PCA for Efficient Image Analysis and Dimensionality Reduction: Unlocking the Potential of Complex Image Data by Tianyu Sun, Lang He, Xi Fang, Liang Xie

“…Additionally, it innovatively combines the dimensionality reduction method with the Mask R-CNN algorithm, enhancing the accuracy of image segmentation. …”
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Improved feature reduction framework for sign language recognition using autoencoders and adaptive Grey Wolf Optimization by Rajeev Goel, Sandhya Bansal, Kavita Gupta

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A systematic review on search‐based test suite reduction: State‐of‐the‐art, taxonomy, and future directions by Amir Sohail Habib, Saif Ur Rehman Khan, Ebubeogu Amarachukwu Felix

“…To address this situation, the test suite reduction (TSR) technique is widely used that focusses on finding a representative test suite without compromising its effectiveness such as fault‐detection capability. …”
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