Code Generation for Collectible Card Games with Complex APIs by John Licato, Logan Fields, Brayden Hollis

“…Given these practical limitations, is it possible to utilize these massive code-generation LMs to write code compatible with a given API? We develop an algorithm that selects code examples using a smaller LM trained to predict which features of an API are likely to be used in the resulting code, which is a simpler problem than actually generating the code. …”
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Control and readout of a 13-level trapped ion qudit by Pei Jiang Low, Brendan White, Crystal Senko

“…Abstract Scaling up the computational space of a quantum system is necessary to demonstrate quantum algorithmic advantage. Currently, including more information carriers is still a physical challenge in general. …”
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Optimization Design on Functionally Graded Cem for Trains Based on LPM Model with Calibrated Parameters by Ruixian Qin, Bingzhi Chen

“…The influence of parameters in graded function on interfacial force and peak acceleration is investigated and optimal design parameters are obtained by Nondominated Sorting Genetic Algorithm (NSGA-II). It is concluded that considering the behavior of the carbody can improve the accuracy of LPM in predicting the longitudinal response, and the gradient CEM is a potential energy configuration mode to improve the crashworthiness of the train in a collision.…”
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A DMPC-based three-dimensional cooperative guidance scheme with impact time and impact angle constraints by Zijie Jiang, Xiuxia Yang, Cong Wang, Yi Zhang, Hao Yu

“…In this paper, a distributed model predictive control (DMPC)-based three-dimensional (3D) cooperative guidance scheme is proposed for multiple interceptors with controllable thrust and constrained acceleration, to simultaneously attack a maneuvering target at desired terminal angles. …”
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A numerical framework for simulating fluid-structure interaction phenomena by A. De Rosis, S. de Miranda, C. Burrafato, F. Ubertini

“…These ingredients are combined through a partitioned staggered explicit strategy, according to an efficient and accurate algorithm recently developed by the authors. The effectiveness of the proposed methodology is tested against two different cases. …”
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Modelling fatigue induced change in hyperelastic response of SBR/NR blends by Adtihya Nambiar, P. Mythravaruni

“…The experimental data obtained from the tensile test is used in an optimisation algorithm to find the model parameters that provide the best fit to the experimental behaviour. …”
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The correlation between histopathological and ultrasound findings regarding Cesarean section scars – A three-year survey study by Oana D. Bălălău, Nicolae Bacalbașa, Cristian Bălălău, Carolina Negrei, Bianca Gălățeanu, Octav Ghinghină, Cristina Răduță, Liana Pleș, Anca D. Stănescu, Vasile A. Dumitru

“…Our study found solid evidence related to possible correlations between histopathological and ultrasound data on the cesarean section scar, which could lead to a possible predictive algorithm with implications for both prognostic and therapeutic fields.…”
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Multiobjective Optimization System of Extrusion Process Parameters for Targeted Microtubes Based on RSM and NSGA-II by Qingqing Zhang, Guobao Jin, Guanghui Dai

“…Finally, the nondominated sorting genetic algorithm II (NSGA-II) and response surface model (RSM) were mixed to find the optimal parameters of the tube extrusion. …”
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Information-extremе machine learning for object identification on the terrain by V. V. Moskalenko, A. H. Korobov

“…Kulbak's information measure, which is a function of false omission rate and positive predictive value of decision-making and it also allows machine learning on imbalanced dataset.…”
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CLINICAL MANIFESTATIONS OF TRAUMATIC INTRACRANIAL HEMATOMAS WITH DIFFERENT OUTCOMES by G. V. Anisimov, Y. I. Kravtsov

“…In addition to the assessment of consciousness and neurological status in the most acute period of TBI a comprehensive study of laboratory indicators of stress reactions should be included in the diagnostic algorithm which will allow to determine compensatory mechanisms status, to predict their changes and the deterioration of the patient.…”
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Analysis of the generalization ability of neural networks based on the NN-MPS-interpolation model by Bo-Tao Wang, Zhe Sun, Li-Yuan Dou

“…A feedforward fully connected neural network interpolation model (NN-MPS-interpolation model) based on the backpropagation algorithm is developed. This model takes parameters with strong correlations to the pressure Poisson equation as inputs to output the desired pressure values, achieving predictions for high-resolution problems using low-resolution examples. …”
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A systematic approach to the scale separation problem in the development of multiscale models. by Pinaki Bhattacharya, Qiao Li, Damien Lacroix, Visakan Kadirkamanathan, Marco Viceconti

“…Throughout engineering there are problems where it is required to predict a quantity based on the measurement of another, but where the two quantities possess characteristic variations over vastly different ranges of time and space. …”
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Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland by Gnat Sebastian

“…The CatBoost model, known for its robust handling of categorical features and strong predictive capabilities, is employed as the machine learning algorithm for this analysis. …”
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Short-range order stabilizes a cubic iron alloy in Earth’s inner core by Zhi Li, Sandro Scandolo

“…Ab-initio methods struggle with the alloy’s vast configurational complexity, limiting reliable property predictions. To overcome this, here we integrate a hybrid Monte Carlo sampling algorithm with a deep-learning interatomic potential to compute the Fe-Si binary phase diagram and sound velocities at inner-core boundary pressures. …”
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Position Control Using Trajectory Tracking and State Estimation of a Quad-rotor by Onur Sarıpınar, Muharrem Mercimek

“…State estimation techniques are used to obtain and predict information about the state of the aircraft. …”
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Energy-efficient wireless sensor network for real-time environmental monitoring: Simulink-based design by Fatai Olatunde Adunola, Victor Nnamdi Omeke, Ashraf Adam Ahmad, Asharimantun Reuben Bunu, Alfred John Nkohon, Emmanual Obiajulu

“…Simulation results showed energy reductions of up to 13.4% and battery life increases of up to 15.49% compared to traditional methods enabling the system to remain in the field for longer. …”
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A Lightweight Model for Shine Muscat Grape Detection in Complex Environments Based on the YOLOv8 Architecture by Changlei Tian, Zhanchong Liu, Haosen Chen, Fanglong Dong, Xiaoxiang Liu, Cong Lin

“…Compared with the latest YOLOv11n, our model achieved a 3.3% improvement in mAP, with reductions of 26.4% in parameters, 14.3% in FLOPs, and 14.6% in inference time, demonstrating comprehensive enhancements. …”
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Numerical study on the suppression effect of potassium salt on the infrared radiation signatures of rocket exhaust plumes by Qinglin Niu, Jie Ma, Wenqiang Gao, Xiaying Meng, Hongli Wang

“…In addition, afterburning is nearly completely suppressed at 4 % KOH, with infrared signature reductions of 79.1 % in the 2.7 μm band and 56.7 % in the 4.3 μm band. …”
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ALLERGIC DISEASES AND METABOLIC SYNDROME: SOME ASPECTS OF THE COMBINED COURSE by V.D. Sakevych, V.I. Sakevych, T.A. Trybrat, S.V. Shut

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Investigating the impact of fatty acid profiles on biodiesel lubricity using artificial intelligence techniques by Atthaphon Maneedaeng, Attasit Wiangkham, Atthaphon Ariyarit, Anupap Pumpuang, Ekarong Sukjit

“…To further analyze the impact of fatty acid composition on lubricity, an artificial intelligence (AI)-based approach using the Adaptive Boosting (AdaBoost) algorithm was implemented. The AI model effectively predicts wear scar diameter, friction coefficient, and film formation, providing insights into the complex interactions between fatty acid profiles and tribological performance. …”
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