Reinforced Cost-Sensitive Graph Network for Detecting Fraud Leaders in Telecom Fraud by Peiwen Gao, Zhihua Li, Dibin Zhou, Liang Zhang

“…Finally, weight coefficients are dynamically optimized using the Deep Deterministic Policy Gradient (DDPG) algorithm, and the prediction results of the three base classifiers are combined to produce the final classification outcomes. …”
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Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance by Hui Zhi, Zhixin Zhou, Haiteng Wu, Zheng Chen, Shaohua Tian, Yujiong Zhang, Yongwei Ruan

“…Furthermore, the method is integrated with the Ego-Planner path planning algorithm and nonlinear Model Predictive Control (MPC) algorithm, creating a comprehensive underwater 3D perception, planning, and control system. …”
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Numerical model of cutting tool blade wear by Panchuk V., Onysko O., Kotwica K., Barz C., Borushchak L.

“…The result of the program application, created based on the algorithm proposed in the article, showed that the predicted accuracy of the obtained profile’s half-angle could be in a range from –0.03° to +0.10°, which is equivalent to 4–13 % of tolerance of this dimension.…”
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Enhancing skin lesion classification: a CNN approach with human baseline comparison by Deep Ajabani, Zaffar Ahmed Shaikh, Amr Yousef, Karar Ali, Marwan A. Albahar

“…The algorithm retains high-confidence CNN predictions while replacing low-confidence outputs with expert human assessments to enhance diagnostic accuracy. …”
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Recurrent Deep Learning for Beam Pattern Synthesis in Optimized Antenna Arrays by Armando Arce, Fernando Arce, Enrique Stevens-Navarro, Ulises Pineda-Rico, Marco Cardenas-Juarez, Abel Garcia-Barrientos

“…Idealized and test beam patterns are employed as inputs for the DNN, demonstrating their effectiveness in scenarios with high prediction complexity and closely spaced elements. Additionally, a comparative analysis is conducted among the three DNN architectures. …”
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Testing the Perturbation Sensitivity of Abortion-Crime Regressions by Michał Brzeziński, Maria Halber

“…The hypothesis that the legalisation of abortion contributed significantly to the reduction of crime in the United States in 1990s is one of the most prominent ideas from the recent “economics-made-fun” movement sparked by the book Freakonomics. …”
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Balanced operation strategies of district heating systems based on dynamic hydraulic-thermal modeling by Xiaojie Lin, Ning Zhang, Zheng Luo, Encheng Feng, Wei Zhong

“…The heating supply imbalance of the primary side return temperatures among different heating substations is defined and optimized based on the dynamic hydraulic-thermal model and the particle swarm optimization algorithm. In the case analysis, the results of heating supply imbalance before and after optimization are 0.81 K and 0.47 K, respectively, with a 42.0 % reduction in heating imbalances after optimization. …”
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Multistage power generation planning approach for new power systems with high renewable energy integration considering flexibility constraints by Danyang Li, Hongpeng Liu, Jingwei Zhang, Xu Han, Shuxin Zhang

“…A flexibility-constrained multi-stage generation planning model is formulated, which resolves nonlinearity through auxiliary variable linearization and Benders decomposition algorithm. Case studies demonstrate that the proposed model achieves a 47.3% reduction in total 10-year planning costs for a typical regional system, comprising 39.5% operational cost savings and 46.3% carbon emission cost reduction, while elevating renewable energy accommodation rate to 80%. …”
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Forecasting the vapor pressure deficit in vertical farming facilities aiming to provide optimal indoor conditions by Carlos Alejandro Perez Garcia, Dafni Despoina Avgoustaki, Enrica Santolini, Daniele Torreggiani, Thomas Bartzanas, Patrizia Tassinari, Marco Bovo

“…This research develops and validates a prediction model based on NeuralProphet algorithm to assess the vapor pressure deficit in a vertical farming facility. …”
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Robust personalized pricing under uncertainty of purchase probabilities by Shunnosuke Ikeda, Naoki Nishimura, Noriyoshi Sukegawa, Yuichi Takano

“…While it is essential for personalized pricing to predict the purchase probabilities for each consumer, these predicted values are inherently subject to unavoidable prediction errors that can negatively impact the realized revenues and profits. …”
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Advancing eHealth in Society 5.0: A Fuzzy Logic and Blockchain-Enhanced Framework for Integrating IoMT, Edge, and Cloud With AI by Joy Dutta, Deepak Puthal

“…We introduce the Health Prediction using Cloud Edge 2.0 (HPCE 2.0) algorithm, which employs fuzzy logic to effectively combine historical Electronic Health Records (EHRs) with real-time IoMT data, providing precise and personalized health severity level predictions. …”
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Blockchain Scalability Analysis and Improvement of Bitcoin Network through Enhanced Transaction Adjournment Techniques by Umar Danjuma Maiwada

“…The second part of this research work proposes an effective algorithm that improves scalability of Bitcoin network through efficient transaction deferment. …”
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Landslide Accumulation Ice-Snow Melting for Thermo-Hydromechanical Coupling and Numerical Simulation by Tongqiang Xiong, Jianlin Li, Lehua Wang, Huafeng Deng, Xiaoliang Xu

“…In this paper, we discussed the phase change coupling algorithm of accumulation bank slope under the action of ice-snow melting. …”
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Optimizing low complexity encoding method for systematic polar code by Linhua MA, Shiping LIU, Xing HU, Tianyu HUANG, Bin XU

“…In order to solve the delay caused by step-by-step calculation and the computational complexity caused by iterative “exclusive-or” computation during the encoding process,a dimensionality reduction strategy was proposed and defined.Based on this,system polarization code parallel coding algorithm for cracking strategy was proposed.Simulation and computational complexity analysis were carried out on AWGN channel.The results show that the coding gain of the above algorithm is slightly better than the traditional one or almost the same,but the computational complexity is up to 80.92%,which is more suitable for hardware implementation and engineering application.It is more suitable for hardware implementation and has a certain practical value.…”
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Deep learning for air pollution detection: Analyzing scots pine needles with SEM/EDS by Mirosław Szwed, Witold Żukowski, Dariusz Pasieka

“…The layers (masks) used were an appropriate element to develop a machine learning algorithm identifying pollutants divided into previously defined categories. …”
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Research on the optimization method of inventory management of important spare parts of intercity railway. by Dongyan Wang, Ying Sun, Liang Yu, Kun Shen, Junbo Li, Xia Wu

“…The experimental results indicate that ZOA-LSSVM can provide better prediction accuracy. Based on this fitting method, spare parts inventory management is conducted. …”
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Impact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets by Muhammad Khahfi Zuhanda, Lisya Permata, Hartono, Erianto Ongko, Desniarti

“…This research aims to analyze the impact of the Adaptive Synthetic (ADASYN) oversampling technique on the performance of the Naïve Bayes classification algorithm on datasets with class imbalance. Class imbalance is a common problem in machine learning that can cause bias in prediction results, especially in minority classes. …”
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Implementation of an Active Vibration Control System on a Cogeneration Plant by Emanuele Voltolini, Daniel Pinardi, Andrea Toscani, Marco Binelli, Angelo Farina, Jessica Ferrari, Andrea Zenaro, Stefano Maglia, Enrico Calzavacca

“…This paper presents a noise reduction solution for a cogeneration plant, consisting of an Active Vibration Control (AVC) system applied to the cogenerator enclosure. …”
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Panel Temperature Dependence on Atmospheric Parameters of an Operative Photovoltaic Park in Semi-Arid Zones Using Artificial Neural Networks by Sonia Montecinos, Carlos Rodríguez, Andrea Torrejón, Jorge Cortez, Marcelo Jaque

“…These results demonstrate that the ANN is a powerful tool for predicting panel temperature with high accuracy.…”
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Research on Iterative Learning Semi-active Control for Curve Passing of High-speed Train by Yongjun AI, Chunjun CHEN, Xin LI, Jianrong ZHOU

“…According to the repeatability of train running and the big data, the PD iterative learning control algorithm was designed, and the semi-active control simulation which combined control algorithm with dynamic software was carried out to compare with the results of the passive working conditions. …”
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