Statistical Investigation of Casualties Suffered by Certain Types of Vessels

1947 ◽  
Vol 9 (2) ◽  
pp. 141 ◽  
Author(s):  
S. Vajda
Keyword(s):  
Statistical Investigation

A comprehensive study on statistical prediction and reduction of tire/road noise

2021 ◽  
pp. 107754632110131
Author(s):  
Somaye Mohammadi ◽  
Abdolreza Ohadi ◽  
Mostafa Irannejad-Parizi
Keyword(s):  
Neural Network ◽  
Road Transport ◽  
Relevance Vector Machine ◽  
Statistical Investigation ◽  
Statistical Prediction ◽  
Support Vector ◽  
Prediction Ability ◽  
Vector Method ◽  
Tire Noise ◽  
Rolling Noise

Promoting safe tires with low external rolling noise increases the environmental efficiency of road transport. Although tire builders have been striving to reduce emitted noise, the issue’s sophisticated nature has made it difficult. This article aims to make the problem straightforward, relying on recent significant improvements in statistical science. In this regard, the prediction ability of new methods in this field, including support vector machine, relevance vector machine, and convolutional neural network, along with the new architecture of the neural network is compared. Tire noise is measured under the coast-by condition. Two training strategies are proposed: extracting features from a tread pattern image and directly importing an image to the model. The relevance vector method, which is trained using the first strategy, has provided the most accurate results with an error of 0.62 dB(A) in predicting the total noise level. This precise model is used instead of experimentation to analyze the sensitivity of tire noise to its parameters using a small central composite design. The parametric study reveals striking tips for reducing noise, especially in terms of interactions between parameters that have not previously been shown. Finally, a novel two-stage approach for reducing noise by tread pattern optimization is proposed, inspired by two regression models derived from statistical investigation and variance analysis. Changes in tread pattern specifications of two case studies and their randomization have resulted in a reduction of 3.2 dB(A) for a high-noise tire and 0.4 dB(A) decrement for a quieter tire.

scholarly journals Investigation of GIM-TEC disturbances before M ≥ 6.0 inland earthquakes during 2003–2017

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fuying Zhu ◽  
Yingchun Jiang
Keyword(s):  
Rapid Development ◽  
Science Research ◽  
Satellite System ◽  
Statistical Investigation ◽  
Electron Content ◽  
Total Electron ◽  
Spatial And Temporal Distributions ◽  
Before And After ◽  
Global Ionosphere Map ◽  
Global Navigation Satellite

Abstract With the rapid development of the Global Navigation Satellite System (GNSS) and its wide applications to atmospheric science research, the global ionosphere map (GIM) total electron content (TEC) data are extensively used as a potential tool to detect ionospheric disturbances related to seismic activity and they are frequently used to statistically study the relation between the ionosphere and earthquakes (EQs). Indeed, due to the distribution of ground based GPS receivers is very sparse or absent in large areas of ocean, the GIM-TEC data over oceans are results of interpolation between stations and extrapolation in both space and time, and therefore, they are not suitable for studying the marine EQs. In this paper, based on the GIM-TEC data, a statistical investigation of ionospheric TEC variations of 15 days before and after the 276 M ≥ 6.0 inland EQs is undertaken. After eliminating the interference of geomagnetic activities, the spatial and temporal distributions of the ionospheric TEC disturbances before and after the EQs are investigated and compared. There are no particularly distinct features in the time distribution of the ionospheric TEC disturbances before the inland EQs. However, there are some differences in the spatial distribution, and the biggest difference is precisely in the epicenter area. On the other hand, the occurrence rates of ionospheric TEC disturbances within 5 days before the EQs are overall higher than those after EQs, in addition both of them slightly increase with the earthquake magnitude. These results suggest that the anomalous variations of the GIM-TEC before the EQs might be related to the seismic activities.

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