Machine Learning Advancements in Urban Traffic Simulation: A Comprehensive Survey by Harshit Maheshwari, Li Yang, Richard W. Pazzi

“…Urban traffic simulation is useful in many ways to understand, manage, and predict the growing complexities of traffic dynamics within a city. …”
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A Case Study on Integrating an AI System into the Fuel Blending Process in a Chemical Refinery by Abdul Gani Abdul Jameel

“…The AI-powered process discussed can predict, with much better accuracy, critical combustion properties of gasoline such as the Research Octane Number (RON), Motor Octane Number (MON), and Antiknock Index (AKI), compared to the classical LP models, with the added advantage of optimization of the blend ratio in real time. …”
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Rotor Dynamic Behaviour of Electro-Rheological Lubricant Operated Multi-Lobe Journal Bearings by Kuldeep Narwat, Vivek Kumar, Simran Jeet Singh, Abhishek Kumar

“…The equation of motion for the journal is solved utilizing the fourth-order Runge-Kutta method to predict journal center locus/trajectories. The utilization of ER lubricant in conjunction with a two-lobe journal bearing notably enhances the minimum film thickness by 63.5%, the direct stiffness parameter by 182.4%, and the damping parameter by 210.14%. …”
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Two-Phase Globally Coupled Low-Density Parity Check Decoding Aided with Early Termination and Forced Convergence by Kun Zhu, Hongwen Yang

“…The initial variant, ET-1, predicts whether local decoding can be successful according to data characteristics and stop the local decoding iteration that is not expected to be successful in time. …”
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Bandage Therapeutic-Optical Keratoplasty in Keratoconus Patients after Intrastromal Corneal Segments Implantation by G. A. Osipyan, V. M. Sheludchenko, N. Y. Youssef, Kh. Khraystin

“…The first group consisted of 7 patients (7 eyes) of 27 ± 3 years old with had past history of CRS implantation followed by the absence of predicted improvement of visual acuity during the observation period of up to 18 months. …”
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Sequence-to-Sequence Text Generation with Discrete Diffusion Models by JIANG Hang, CAI Guoyong, LI Sihui

“…To this end, this paper simplifies the training process of the discrete diffusion model by deriving an upper bound on the training objective, and subsequently introduces and modifies the mask-and-predict decoding strategy from the conditional mask language model as the inference algorithm of the diffusion model. …”
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Cutting guides in mandibular tumor ablation: Are we as accurate as we think? by Omar Suhaym, Loren Moles, Nicholas Callahan

“…Conclusion: The finding of this study suggests that virtual surgical planning is an unambiguous paradigm shift in the predictability of the surgical plan and achievement of the reconstruction goals. …”
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Forced motion control of a mobile robot by T. Yu. Kim, R. A. Prakapovich, A. A. Lobatiy

“…A side result of the developed control system is that when it is scaled to a group of robots, it becomes possible to predict the time and place of their potential collisions, in order to subsequently take into account a group of robots for effective control.Conclusion. …”
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Numerical modeling and experimental estimates of structural member fatigue characteristics by Yu. P. Man’shin, E. Yu. Man’shina

“…Introduction. In the algorithm for predicting the resource of machine parts, models of external actions, fracture resistance, and temporal development of a particular type of damage to these units interact. …”
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Classification of Moral Decision Making in Autonomous Driving: Efficacy of Boosting Procedures by Amandeep Singh, Yovela Murzello, Sushil Pokhrel, Siby Samuel

“…This study investigates machine learning models to predict human decision making in simulated driving scenarios under varying pedestrian configurations and time constraints. …”
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Dynamic topology adaptability of adaptive multimodal transmission strategy based on environment perception in multi-hop routing of 5G vehicle network by Shengxia Tan, Xianshuang Zong, Feng Xiao

“…The features are input into gated recurrent unit (GRU) for time series modeling to predict the link node movement pattern. Then, ad hoc on-demand distance vector routing (AODV), greedy perimeter stateless routing (GPSR) and dynamic source routing (DSR) are integrated, and the best protocol is automatically selected through the classification and regression trees (CART) algorithm. …”
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A novel method for simulating dynamic facades to analysing, and optimizing daylight and visual comfort in office buildings by Mehran Shahmoradi, Mansour Yeganeh

“…Finally, it gives 12 two-variable functions (surface function) based on the sun's position parameters (x: azimuth, y: altitude) to shading device indices; then, these can predict the entire year's ideal position for the shading device. …”
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Multi-objective optimization of residential energy-saving design based on fuzzy multi-criteria decision-making behavior model by Suzhen Pei, Gaoxiang Chen, Jian Yao, Yichen Dang

“…Traditional building energy simulation models often neglect the stochastic nature of occupant behavior and multi-device interaction, leading to discrepancies between predicted and actual energy consumption. This study introduces a multi-objective optimization framework based on a Fuzzy Multi-Criteria Decision-Making (FMCDM) behavioral model. …”
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Single-Step Sampling Approach for Unsupervised Anomaly Detection of Brain MRI Using Denoising Diffusion Models by Mohammed Z. Damudi, Anita S. Kini

“…The output is a binary image showing the predicted anomalous regions, which is then compared to the ground truth to evaluate its segmentation performance. …”
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An Elderly-Oriented Form Design of Low-Speed New Energy Vehicles Based on Rough Set Theory and Support Vector Regression by Zimo Chen

“…Second, the cars’ appearances are deconstructed by morphological analysis, and the key design features affecting elderly-oriented satisfaction are identified by a rough set attribute reduction algorithm. Finally, support vector regression is used to establish a mapping model of elderly-oriented Kansei factors and the key design features to predict the elderly-oriented form design of optimal low-speed NEVs. …”
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A deep operator network for Bayesian parameter identification of self-oscillators by Tobias Sugandi, Bayu Dharmaputra, Nicolas Noiray

“…The proposed approach can directly predict the finite-time KM coefficients, eliminating the intermediate computation of the solution field of the adjoint Fokker–Planck equation. …”
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Downward Convective Moisture Transport Dominated by a Few Overshooting Clouds in Marine and Continental Shallow Convection by Heng Xiao, Adam Varble, Colleen Kaul, Johannes Mülmenstädt

“…We apply a 3‐D cloud‐tracking algorithm to large‐eddy simulations (LESs) of marine and continental shallow convection. …”
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Evaluating the acceptance of CBDCs: experimental research with artificial intelligence (AI) generated synthetic response by Sergio Luis Náñez Alonso, Peterson K. Ozili, Beatriz María Sastre Hernández, Luís Miguel Pacheco

“…Generative AI, with its algorithmic fidelity, has great potential for predicting human behavior in economic contexts. …”
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Optimizing chemotherapeutic targets in non-small cell lung cancer with transfer learning for precision medicine. by Varun Malik, Ruchi Mittal, Deepali Gupta, Sapna Juneja, Khalid Mohiuddin, Swati Kumari

“…Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases, making it the most fatal diseases worldwide. Predicting NSCLC patients' survival outcomes accurately remains a significant challenge despite advancements in treatment. …”
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Short course of glucocorticoids in patients with protracted and chronic gout arthritis. Part I: predictors of therapy efficacy by A A Fedorova, V G Barskova, I A Yakunina, V A Nasonova

“…The study allowed to reveal features which determine efficacy of short course of GC therapy in pts with protracted and chronic gout arthritis: inflamed joint count, duration of the last exacerbation and chronic renal insufficiency. Proposed an algorithm allowing to predict efficacy of GC short course in each pt.…”
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