Black-Box Model-Based Active Damping of Driveline Oscillations

The paper unveils a black box model-based self healing strategy to suppress the ill effects of stuck-at-faults occurring in combinational circuits. The primary theory endeavours to attach a sense of reliability in the performance of digital systems and makes them insensitive to the negative impact of faults present in the system. The proposed methodology employs a dynamic fault tolerant approach to protect digital systems from the incursion of stuck-at-faults and enables the system to come up with fault free outputs. The simulation results affirm the authenticity of the proposed strategy to cancel out the influence of faults and facilitate the system to heal itself. The work utilizes the attributes of an FPGA to demonstrate the practical viability of the proposed approach. The performance analysis endorses the definite dominance of the proposed healing scheme over the traditional Triple Modular Redundancy [TMR] in terms of fault coverage and area overhead.

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Simulation Model of the Dynamic Behavior of a Tire Running Over an Obstacle

Tire Science and Technology ◽

10.2346/1.2148799 ◽

1988 ◽

Vol 16 (2) ◽

pp. 62-77 ◽

Cited By ~ 20

Author(s):

P. Bandel ◽

C. Monguzzi

Keyword(s):

Simulation Model ◽

Dynamic Behavior ◽

Black Box ◽

Box Model ◽

Vehicle Suspension ◽

Empirical Relationships ◽

Static Tests ◽

High Speeds ◽

Dynamic Forces ◽

Vehicle Suspension System

Abstract A “black box” model is described for simulating the dynamic forces transmitted to the vehicle hub by a tire running over an obstacle at high speeds. The tire is reduced to a damped one-degree-of-freedom oscillating system. The five parameters required can be obtained from a test at a given speed. The model input is composed of a series of empirical relationships between the obstacle dimensions and the displacement of the oscillating system. These relationships can be derived from a small number of static tests or by means of static models of the tire itself. The model can constitute the first part of a broader model for description of the tire and vehicle suspension system, as well as indicating the influence of tire parameters on dynamic behavior at low and medium frequencies (0–150 Hz).

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MODES: model-based optimization on distributed embedded systems

Machine Learning ◽

10.1007/s10994-021-06014-6 ◽

2021 ◽

Author(s):

Junjie Shi ◽

Jiang Bian ◽

Jakob Richter ◽

Kuan-Hsun Chen ◽

Jörg Rahnenführer ◽

...

Keyword(s):

Machine Learning ◽

Embedded Systems ◽

Learning Model ◽

Black Box ◽

Distributed Embedded Systems ◽

Data Set ◽

Individual Model ◽

Model Based ◽

Machine Learning Model ◽

Distributed Machine Learning

AbstractThe predictive performance of a machine learning model highly depends on the corresponding hyper-parameter setting. Hence, hyper-parameter tuning is often indispensable. Normally such tuning requires the dedicated machine learning model to be trained and evaluated on centralized data to obtain a performance estimate. However, in a distributed machine learning scenario, it is not always possible to collect all the data from all nodes due to privacy concerns or storage limitations. Moreover, if data has to be transferred through low bandwidth connections it reduces the time available for tuning. Model-Based Optimization (MBO) is one state-of-the-art method for tuning hyper-parameters but the application on distributed machine learning models or federated learning lacks research. This work proposes a framework $$\textit{MODES}$$ MODES that allows to deploy MBO on resource-constrained distributed embedded systems. Each node trains an individual model based on its local data. The goal is to optimize the combined prediction accuracy. The presented framework offers two optimization modes: (1) $$\textit{MODES}$$ MODES -B considers the whole ensemble as a single black box and optimizes the hyper-parameters of each individual model jointly, and (2) $$\textit{MODES}$$ MODES -I considers all models as clones of the same black box which allows it to efficiently parallelize the optimization in a distributed setting. We evaluate $$\textit{MODES}$$ MODES by conducting experiments on the optimization for the hyper-parameters of a random forest and a multi-layer perceptron. The experimental results demonstrate that, with an improvement in terms of mean accuracy ($$\textit{MODES}$$ MODES -B), run-time efficiency ($$\textit{MODES}$$ MODES -I), and statistical stability for both modes, $$\textit{MODES}$$ MODES outperforms the baseline, i.e., carry out tuning with MBO on each node individually with its local sub-data set.

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MFPP: Morphological Fragmental Perturbation Pyramid for Black-Box Model Explanations

2020 25th International Conference on Pattern Recognition (ICPR) ◽

10.1109/icpr48806.2021.9413046 ◽

2021 ◽

Author(s):

Qing Yang ◽

Xia Zhu ◽

Jong-Kae Fwu ◽

Yun Ye ◽

Ganmei You ◽

...

Keyword(s):

Black Box ◽

Box Model

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Synchronous Machine Winding Modeling Method Based on Broadband Characteristics

Applied Sciences ◽

10.3390/app11104631 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4631

Author(s):

Yu Chen ◽

Xiaoqing Ji ◽

Zhongyong Zhao

Keyword(s):

Equivalent Circuit ◽

High Frequency ◽

Equivalent Circuit Model ◽

Black Box ◽

Synchronous Machine ◽

Circuit Model ◽

Modeling Method ◽

Experimental Results ◽

Box Model ◽

Impedance Curve

The accurate establishment of the equivalent circuit model of the synchronous machine windings’ broadband characteristics is the basis for the study of high-frequency machine problems, such as winding fault diagnosis and electromagnetic interference prediction. Therefore, this paper proposes a modeling method for synchronous machine winding based on broadband characteristics. Firstly, the single-phase high-frequency lumped parameter circuit model of synchronous machine winding is introduced, then the broadband characteristics of the port are analyzed by using the state space model, and then the equivalent circuit parameters are identified by using an optimization algorithm combined with the measured broadband impedance characteristics of port. Finally, experimental verification and comparison experiments are carried out on a 5-kW synchronous machine. The experimental results show that the proposed modeling method identifies the impedance curve of the circuit parameters with a high degree of agreement with the measured impedance curve, which indicates that the modeling method is feasible. In addition, the comparative experimental results show that, compared with the engineering exploratory calculation method, the proposed parameter identification method has stronger adaptability to the measured data and a certain robustness. Compared with the black box model, the parameters of the proposed model have a certain physical meaning, and the agreement with the actual impedance characteristic curve is higher than that of the black box model.

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CYBERNETIC MODEL IN PLANNING AND FORECASTING

STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS. In the frame of the XXIII Agribusiness Forum of the South of Russia and the Exhibition «Interagromash» Volume 2 ◽

10.23947/interagro.2020.2.128-130 ◽

2020 ◽

Author(s):

D.S. Serebryanaya ◽

Keyword(s):

Higher Education ◽

Building Materials ◽

Black Box ◽

Box Model ◽

Sociological Research ◽

Mathematical Approach ◽

Cybernetic Model ◽

Corrective Measures

This article analyzes the mathematical approach to the study of the motives of students to study in higher education. The possibility of using the “black box” model used in the production of building materials for sociological research is considered. This approach allows you to see the most significant causes of discrepancies and develop corrective measures for them.

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