Exhaustive search for novel multicomponent alloys with brute force and machine learning by Viktoriia Zinkovich, Vadim Sotskov, Alexander Shapeev, Evgeny Podryabinkin

“…It is particularly important for high entropy alloys (HEAs), where multiple principal elements can form numerous potential intermetallic compounds during the condensation process, making it challenging to predict the dominant phase. Our algorithm is based on a brute-force evaluation of candidate structures with a fixed underlying lattice (FCC or BCC) accelerated by machine-learning interatomic potentials. …”
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GNSS signal-to-noise snow depth inversion based on robust empirical mode decomposition by Dengao Li, Xinyu Luo, Jumin Zhao, Fanming Wu, Hairong Jiang, Danyang Shi

“…Using global navigation satellite system (GNSS) to monitor snow depth helps scientists study the impacts of climate change and predict future climate patterns. In the process of extracting reflection signals from signal-to-noise ratio (SNR) data, traditional methods usually use low order polynomials for detrending terms. …”
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Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation. by Wenjun Zhao, Erica Larschan, Björn Sandstede, Ritambhara Singh

“…Our algorithm overcomes this limitation by estimating gene velocities using optimal transport. …”
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Automated Symbolic Upscaling: 2. Model Generation for Extended Applicability Regimes by Kyle Pietrzyk, Ilenia Battiato

“…This strategy extends the applicability of homogenized models with respect to classical homogenization theory, as demonstrated in Part 1 where upscaled models are rigorously derived in moderately reactive physical regimes. After encoding the algorithm into Symbolica, an automated upscaling framework, we upscale two reactive mass transport problems and numerically validate the resulting nonlinear homogenized models by showing the absolute error estimates predicted by homogenization theory are satisfied. …”
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Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
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Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
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Fingernail analysis management system using microscopy sensor and blockchain technology by Shih Hsiung Lee, Chu Sing Yang

“…Diagnosis by nail can effectively predict and prevent disease. Human nails have a high degree of uniqueness, and it can be used for biometric recognition. …”
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A Statistical Analysis Based Probabilistic Routing for Resource-Constrained Delay Tolerant Networks by Jixing Xu, Jianbo Li, Shan Jiang, Chenqu Dai, Lei You

“…In this paper, we propose an improved probabilistic routing algorithm that fully takes into account message's time-to-live when predicting the delivery probability. …”
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A tutorial on ‘capped utilisation’ as a metric and key performance target in NHS England’s Model Hospital operating theatres database: caution for international healthcare systems... by Chen Zhang, Claire Dunstan, Jaideep J. Pandit

“…Our interrogation of the database confirmed these predictions. Moreover, we discovered many instances of implausible CTU values and underlying patterns indicating fundamental flaws in the CTU algorithm, rather than data entry errors. …”
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Regulatory T cells and matrix-producing cancer associated fibroblasts contribute on the immune resistance and progression of prognosis related tumor subtypes in ccRCC by Chao Zhang, Yisu Song, Xiaobo Cui, Yina Wang, Jiang Liu, Zhouji Shen

“…In conclusion, our study created a signature to provide opportunities for predicting prognosis and improving treatments of ccRCC.…”
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Model experimental study of filling property of ring-type geotextile tube by LAI Zhiqiang, XU Shuling, ZHAO Lianjun, Chen Lin, ZHANG Ming

“…Leveraging machine learning principles, the heights of the filled tube bags under three different filling methods—counterclockwise, radial, and vertical—were simulated and predicted using the random forest algorithm, based on experimentally measured heights. …”
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Current Feed-forward Control for Buck Converter Based on Extended Kalman Filter by LI Hao, LIU Haitao, GAN Weiwei, ZHONG Yuan, DING Leilei, DU Chao

“…In order to improve the response speed of Buck converter to load mutation, it proposed an inductive current feed-forward control algorithm based on extended Kalman filter (EKF). Based on Buck converter state equation, an inductor current predictor was established based on EKF and the predicted inductor current was compensated for the given current to improve the effect of load current variation on the output voltage. …”
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Cycling Injury Risk in London: Impacts of Road Characteristics and Infrastructure by Thomas Adams, Rachel Aldred

“…It controlled for exposure by using a case-crossover method alongside an algorithm developed by Transport for London to predict cyclist routes. …”
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A GRNN based frame work to test the influence of nano zinc additive biodiesel blends on CI engine performance and emissions by Chiranjeeva Rao Seela, B. Ravisankar, B.M.V.A. Raju

“…The neural network predictions are corroborated with the experimental results and are found in good agreement. …”
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Consistency regularization for few shot multivariate time series forecasting by Yumei She, Yi Hong, Shikai Shen, Bin Yang, Liyi Zhang, Jianxiao Wang

“…Abstract Multivariate time series forecasting aims to accurately predict future trends by capturing and analyzing various features of the time series. …”
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Substrate-aware computational design of two-dimensional materials by Arslan Mazitov, Ivan Kruglov, Alexey V. Yanilkin, Aleksey V. Arsenin, Valentyn S. Volkov, Dmitry G. Kvashnin, Artem R. Oganov, Kostya S. Novoselov

“…This study presents a novel method for predicting the atomic structure of 2D materials on substrates by combining an evolutionary algorithm, a lattice-matching technique, an automated machine-learning interatomic potentials training protocol, and the ab initio thermodynamics approach. …”
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CSearch: chemical space search via virtual synthesis and global optimization by Hakjean Kim, Seongok Ryu, Nuri Jung, Jinsol Yang, Chaok Seok

“…Abstract The two key components of computational molecular design are virtually generating molecules and predicting the properties of these generated molecules. …”
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Road-Adaptive Precise Path Tracking Based on Reinforcement Learning Method by Bingheng Han, Jinhong Sun

“…The framework first analyzes the obstacles around the vehicle and plans an obstacle-free reference path with the minimum curvature using the hybrid A* algorithm. Next, based on the generated reference path, the current state of the vehicle, and the vehicle motor energy efficiency diagram, the optimal speed is calculated in real time, and the vehicle dynamics preview point at the future moment—specifically, the look-ahead distance—is predicted. …”
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Enhancing climate action evaluation using artificial neural networks: An analysis of SDG 13 by Cosimo Magazzino, Zakaria Zoundi

“…It examines seven critical 2023 SDG Global Index indexes to model and predict environmental performance. The innovative use of ANNs allows for capturing complex and non-linear interactions among sustainability indicators, surpassing traditional linear models. …”
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Navigation strategies in Caenorhabditis elegans are differentially altered by learning. by Kevin S Chen, Anuj K Sharma, Jonathan W Pillow, Andrew M Leifer

“…The model trained on natural odors further predicts the animals' learning-dependent response to optogenetically induced odor perception. …”
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