Detection of false data injection in electric energy metering platforms using gradient lifting decision trees and MLP neural networks by Yakui Zhu, Yangrui Zhang, Chao Zhang, Bingyu Zhang, Hongying Wang, Shaokang Feng

“…The predictor was based on a gradient boosting decision tree to predict potential data injection anomalies. The discriminator used a multilayer perceptron (MLP) neural network, combined with difference analysis between the predicted and actual values, to determine false data injection. …”
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Estimation of gas hydrate and free gas saturation using the rock physics model based on constrained least squares and trust region method in the Shenhu Area, South China Sea by Dajiang Meng, Dajiang Meng, Ruwei Zhang, Ruwei Zhang, Yuan Gu, Yuan Gu, Baojin Zhang, Baojin Zhang, Yunqian Lu, Yunqian Lu, Jiangnan Lin, Jiangnan Lin, Lijie Wang, Lijie Wang

“…The gas hydrate saturations predicted for these sites using the rock physics model were found to reach maximum values of 54% and 72%, respectively, while the saturation of free gas could attain up to 22%. …”
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Flood Routing of Tigris River in Baiji Station and Makhoul Dam Reservoir under Supposed Operation of the Dam by Ghassan Shalan Nida Al-Shahry, Sabbar Abdullah Saleh

“…Two mathematical models were used for flood routing purpose, the first is a relationship of discharge-level to predict the level in Baiji station depended on outflow from gates, and the second is the relationship of storage-level to predict the level in the reservoir depended on storage volume when the leave of the flood wave, an algorithm and flow chart were developed to describe and explain the steps of the flood routing program, which can be modified and applied for any dam reservoir in the world, and it is used in current study, also to calculate inflow discharges then inflow volumes, either outflow discharges may assumed for eleven operating scenarios (at 11 supposed levels to receive the flood wave) and predict the equivalent level in Baiji, and the change in storage, and then the accumulated volume and the equivalent level in reservoir, when the end of flood wave. …”
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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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ADAPTIVE QUASICONTINUUM SIMULATION OF ELASTIC-BRITTLE DISORDERED LATTICES by Karel Mikeš, Milan Jirásek

“…In this work, the QC method is combined with an adaptive algorithm, to obtain correct predictions of crack trajectories in failure simulations. …”
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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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