An Approach to Finding a Robust Deep Learning Model by Alexey Boldyrev, Fedor Ratnikov, Andrey Shevelev

“…This growing demand highlights the importance of training models without human supervision, while ensuring that their predictions are reliable. In response to this need, we propose a novel approach for determining model robustness. …”
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Slewing and Active Vibration Control of a Flexible Single-Link Manipulator by Dae W. Kim, Moon K. Kwak, Soo-Min Kim, Brian F. Feeny

“…This research encompasses dynamic modeling, slewing control, and vibration control for the system. Theoretical predictions are compared with experimental results to validate both the theoretical model and the proposed vibration control algorithm.…”
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A Hybrid Grey Based KOHONEN Model and Biogeography-Based Optimization for Project Portfolio Selection by Farshad Faezy Razi, Abbas Toloie Eshlaghy, Jamshid Nazemi, Mahmood Alborzi, Alireza Pourebrahimi

“…Next, each portfolio was evaluated using grey relational analysis (GRA) and then scheduled risk of the project was predicted using Mamdani fuzzy inference method. Finally, the multiobjective biogeography-based optimization algorithm was utilized for drawing risk and rank Pareto analysis. …”
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Improved cluster analysis of Werner solutions for geologic depth estimation using unsupervised machine learning by Daniel Eshimiakhe, Raimi Jimoh, Magaji Suleiman, Kola Lawal

“…Because of the inherent unpredictability of potential field data, the techniques frequently yield unpredictable results and may not always be able to predict the full extent of the geological structures depicted. …”
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Flexible Scheduling Model of Bus Services between Venues of the Beijing Winter Olympic Games by Jiahao Zhang, Ailing Huang, Rui Jiang, Xingang Li

“…In addition, a genetic-simulated annealing hybrid algorithm (GSAHA) is designed to solve the model based on the characteristics of the genetic algorithm (GA) and simulated annealing. …”
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Analysis of Multimedia Combination-Assisted English Teaching Mode Based on Computer Platform by Yitian Zhang, Na Li

“…It also uses the ConvLSTM algorithm and the CF algorithm to implement the active recommendation function of English knowledge. …”
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Weighted mixed regression localization method based on three-dimensional Voronoi diagram division by Fenfang LI, Xiaochao DANG, Zhanjun HAO

“…With the development of the wireless communication technology and sensing technology, various technologies based on wireless sensor networks are applied.These technologies are widely used in the fields of intelligent agriculture, intelligent transportation, fire rescue and so on.Node localization technology is one of the basic technologies of wireless sensor networks.Location information is a part of the sensing data, which determines the specific measures to be taken in the next step.Due to the complexity of the three-dimensional (3D) space localization environment, the application of the plane positioning method in 3D space will have some limitations.Aiming at above problems, the weighted hybrid regression location algorithm WMR-SKR based on a 3D Voronoi diagram was studied.The localization algorithm was divided into two stages: offline training and online testing.The 3D space was divided into Voronoi diagrams according to the anchor nodes in the network.In the offline training stage, the sequence composed of the coordinates of the anchor nodes and Voronoi cell vertices was used as the training set for training.In the online test stage, the coordinates of unknown nodes in the network were predicted through the trained localization model.Simulation results show that the WMR-SKR algorithm can effectively reduce the node localization error and improve the node localization speed in 3D space.…”
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Smart Odour Sensing for Automated Monitoring of Bread Products by Carmen Bax, Bianca di Diodoro, Alessandro Ticozzi, Nicolò Dellarosa, Flavio Corazza, Giacomo Langfelder, Laura Capelli

“…This work proposes an electronic nose (e-nose) system based on resistive gas sensors to predict the cooking evolution of different types of bread. …”
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Application of the SARIMA-LSTM model to evaluate the effectiveness of interventions for Visceral Leishmaniasis by Mengchen Han, Chongqi Hao, Zhiyang Zhao, Peijun Zhang, Bin Wu, Lixia Qiu

“…A paired samples t-test revealed a statistically significant difference between predicted and actual case counts (t = -4.058, p < 0.001), indicating that the actual number of cases was lower than predicted. …”
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Design of a Manned-Unmanned Teaming System and Forward-Formation Control for Crevasse Detection in the Path of a Human-Driven Vehicle by Ji-Wook Kwon, Hyoujun Lee, Taeyoung Uhm, Jongdeuk Lee, Na-Hyun Lee, Young-Ho Choi

“…The stability and performance of the proposed MUM-T system, forward-formation, and motion control algorithm are validated through simulations. Especially, the forward-formation demonstrated more than an 86% improvement in predicting and mimicking the leader&#x2019;s trajectory compared to conventional formation strategies. …”
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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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