Normalizing flow-assisted nested sampling on Type-II Seesaw model by Rajneil Baruah, Subhadeep Mondal, Sunando Kumar Patra, Satyajit Roy

“…Abstract We propose a novel technique for sampling particle physics model parameter space. The main sampling method applied is nested sampling (NS), which is boosted by the application of multiple machine learning (ML) networks, e.g., self-normalizing network (SNN) and Normalizing Flow (specifically RealNVP). …”
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Komparasi Metode Klasifikasi untuk Deteksi Ekspresi Wajah Dengan Fitur Facial Landmark by Fitra A. Bachtiar, Muhammad Wafi

“… Human machine interaction, khususnya pada facial behavior mulai banyak diperhatikan untuk dapat digunakan sebagai salah satu cara untuk personalisasi pengguna. …”
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Predicting properties of quantum systems by regression on a quantum computer by Andrey Kardashin, Yerassyl Balkybek, Vladimir V. Palyulin, Konstantin Antipin

“…Quantum computers can be considered as a natural means for performing machine learning tasks for inherently quantum labeled data. …”
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Efficient Bayesian inference for stochastic agent-based models. by Andreas Christ Sølvsten Jørgensen, Atiyo Ghosh, Marc Sturrock, Vahid Shahrezaei

“…We demonstrate that good accuracy in inference can be achieved with a relatively small number of simulations, making our machine learning approaches orders of magnitude faster than classical simulation-based methods that rely on sampling the parameter space. …”
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缝纫机送料机构运动学与动力学建模及仿真研究 by 畅博彦, 金国光, 梁栋

“…Planner six-bar mechanism is widely used in the textile industry.A six-bar feed mechanism of sewing machine is studied.The mathematical model of kinematics and dynamics for this mechanism is established.On these bases,the simulation is implemented based on the platform of Matlab/ simulink.Thus,the motion rules and stress state of all parts in mechanism are obtained and described vividly according to two different working conditions.The simulation results show that stitch density of mechanism is affected by the parameter in different working conditions and changing this parameter can adjust the stitch density.Meanwhile,the results can provide a theoretical foundation for the further research of the mechanism.…”
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棘轮机构的参数化设计 by 王良文, 李安生, 唐维纲, 张小辉

“…Using the tooth ratchet mechanism using in all kinds of machine as an example,a mathematical model for parametric design about ratchet mechanism is established.The parametric design is realized by using second developing technology for AutoCAD in VB.When the design parameter in the system is selected,the relating parameter can be calculated and the design results can be checked automatically,the ratchet mechanism engineering drawing can be given out automatically,label dimension and technology terms can be marked,the efficiency is improved.A theoretical basis of digital design and manufacture for ratchet mechanism is provided.…”
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Cooperation-Controlled Learning for Explicit Class Structure in Self-Organizing Maps by Ryotaro Kamimura

“…On the other hand, when the parameter is small, individual neurons play a more important role. …”
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Quantifying the impact of external and internal factors and their interactions on thermal load behaviour of a building by Christoph Matschi, Isabell Nemeth

“…Taking these parameters into account, a simple method for heating load profiling is developed using a machine learning algorithm. …”
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Implementation of Efficient Artificial Neural Network Data Fusion Classification Technique for Induction Motor Fault Detection by Altaf S., Mehmood M. S., Imran M.

“…In this study single sensor method is applied for fault diagnosis depending on identification of single parameter. At early stages it is hard to diagnose machine fault due to ambiguities in modeling environment. …”
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Indirect Estimation of the Volumetric Throughput Performance in the Shredding of Solid Waste by Christoph Feyerer, Karim Khodier, Tatjana Lasch, Roland Pomberger, Renato Sarc

“…Here, a methodical approach is pursued which enables an indirect estimation of the volume throughput capacity based on further machine parameters, such as the drum speed and the drum torque. …”
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Research on Mathematical Model and Flank Deviation Correction of Spiral Bevel Gear by Duplex Helical Method by Longlong Geng, Jing Deng, Shaowu Nie, Xiaozhong Deng, Chuang Jiang, Zhengyang Han

“…Based on the meshing principle of the gear， the digital representation of the spiral bevel gear tooth surface processed by the double helix method and the construction of discrete tooth surface points are completed， and the influence degree of each machine parameter error on tooth surface topology structure are analyzed. …”
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Modeling and Simulation Analysis of Bionic Flapping-Wing Flight Attitude Control Based on L1 Adaptive by Lun Li, Fan Bai, Wencheng Wang, Xiaojin Wu, Yihua Dong

“…At the same time, the Monte Carlo-support vector machine method is used to optimize the boundary of the control parameters in the flight control to obtain the control parameters that can meet the control expectations, and the obtained parameters are classified and judged according to the stable level flight conditions. …”
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Review of communication optimization methods in federated learning by YANG Zhikai, LIU Yaping, ZHANG Shuo, SUN Zhe, YAN Dingyu

“…Federated learning, as a distributed machine learning paradigm with privacy protection capabilities, exchanges model parameters through frequent communication between clients and parameter servers, training a joint model without the raw data leaving the local area. …”
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Transmuted Generalized Weibull Lindley (TGWL) distribution: Bayesian inference and Bayesian neural network approaches for lifetime data modeling by Pius Marthin, Gadde Srinivasa Rao

“…We presented frequentist, Bayesian, and machine-learning approaches for parameter estimation. …”
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Turbofan engine health status prediction with artificial neural network by Slawomir Szrama, Tomasz Lodygowski

“…As a result of research engine health status index is calculated in order to determine the engine degradation level. The calculated parameter is then used as a response parameter for the machine learning algorithm. …”
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基于MF-DFA和SVM的齿轮箱故障诊断 by 刘春林, 潘宏侠, 史斐娜, 蒋红军

“…The fault signal of the gearbox is the complex signal of the non-stationary and nonlinear characteristics,by using the multifractal detrended fluctuation analysis（MF-DFA）and the support vector machine（SVM）to diagnose the fault of the gearbox.The multifractal detrended fluctuation analysis is employed to the extract multifractal singularity index of the gearbox fault,largest singular index,minimum singular index,the width of the singular spectrum,the singular index of extreme value point and so on,and this four fractal parameters are as characteristic parameter.And then the sample of the gearbox different fault state is built,by using the new method of support vector machine,the gearbox fault diagnosis and identification is achieved.Through the study,a new method for mechanical fault diagnosis is provided through the combination of this two methods.There is of great significance for the fault diagnosis and identification of gearbox.…”
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基于多重分形与SVM的齿轮箱故障诊断研究 by 朱云博, 冯广斌, 孙华刚, 李顺德

“…Aiming at that the gearbox vibration signals are nonlinear and non-stationary,a fault diagnosis method based on the theory of multi-fractal and support vector machine（SVM） is proposed.First the multi-fractal theory are applied to analyze gearbox vibration signals,the analysis results show that multi-fractal spectrum and general dimension give a good presentation for gearbox working condition.Then particle swarm optimization is applied to optimize the parameter of support vector machine.The multi-fractal characteristic parameters of gearbox vibration signals are regarded as the fault characteristic vectors and served as input parameters of SVM classifier to classify the fault types of the gearbox.The experimental results show that in the case of small number of samples,this method can classify the different fault types of gearbox accurately.…”
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Application of Six Sigma Methodology for Enhancement of Soft Plastic Extrusion Process by Muhammad Mansoor Uz Zaman Siddiqui, Adeel Tabassum

“…Root causes were identified and targeted improvements based on the data were introduced including optimized production planning, machine parameter optimization and standardization, improvement of production execution planning and storage availability, temperature controls on welding machines and encoder wheel knurling for magnetic insertion machine. …”
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TOOL WEAR STATE MONITORING BASED ON WAVELET PACKET BP＿ADABOOST ALGORITHM by ZHU Xiang, XIE Feng

“…Tools are the key parts in the process of NC milling machine. They are in high-speed processing for a long time and are prone to failure. …”
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Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

“…The best model obtained a coefficient of determination (R2) of 0.9831. Machine learning of median grain size from conventional logging data was systematically carried out through conventional logging sensitivity curve optimization, algorithm modeling, network parameter optimization, median grain size prediction, and validation, and the relative error in its quantitative prediction met application requirements. …”
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