scholarly journals The Effects of the Dynamic Thermophysical Properties of Clothing and the Walking Speed Input Parameter on the Heat Strain of a Human Body Predicted by the PHS Model

2020 ◽  
Vol 17 (18) ◽  
pp. 6475
Author(s):  
Qianqian Huang ◽  
Jun Li
Keyword(s):  
Thermophysical Properties ◽  
Prediction Accuracy ◽  
Walking Speed ◽  
Body Movement ◽  
Input Parameter ◽  
Heat Strain ◽  
Cold Weather ◽  
Good Prediction ◽  
Clothing Insulation ◽  
Predicted Heat Strain

The prediction accuracy of the Predicted Heat Strain (PHS) model is affected by the correction approaches of static thermophysical properties of clothing considering the pumping effects of wind and body movement. In this study, a comparison of different correction algorithms for three types of clothing and their influence on the heat strain predicted by the PHS model was carried out with experimental data obtained from the literature. Results show that the dynamic insulation values calculated by ISO 9920 corrections are larger than those obtained by ISO 7933 when the static insulation values are higher than 0.4 clo, but when the static values are lower than 0.4 clo, it varies contrarily. The dynamic evaporative resistance values calculated with ISO 9920 equations are larger than those with ISO 7933. The prediction accuracy of the PHS model with ISO 9920 corrections and the addition of the walking speed input parameter can be improved for normal clothing (NC) in a hot environment and high clothing insulation. For specialized, insulating, cold weather clothing (SC), ISO 7933 corrections with an added walking speed input parameter to the PHS model have a good prediction precision.

A New Fuzzy Support Vector Machine for Credit Scoring

2011 ◽  
Vol 109 ◽  
pp. 636-640
Author(s):  
Bo Tang ◽  
Min Xia
Keyword(s):  
Support Vector Machine ◽  
Economic Development ◽  
Prediction Accuracy ◽  
Credit Scoring ◽  
Fuzzy Membership ◽  
Support Vector ◽  
Good Prediction ◽  
Support Vector Machine Algorithm ◽  
Fuzzy Support Vector Machine ◽  
Good Prediction Accuracy

With China's rapid economic development, credit scoring has become very important. This paper presents a new fuzzy support vector machine algorithm used to solve the problems of credit scoring. The empirical results show that the proposed fuzzy membership model is valid ,the algorithm has good prediction accuracy and anti-noise ability.

scholarly journals Human responses in heat – comparison of the Predicted Heat Strain and the Fiala multi-node model for a case of intermittent work

2017 ◽  
Vol 70 ◽  
pp. 45-52 ◽  
Author(s):  
Karin Lundgren-Kownacki ◽  
Natividad Martínez ◽  
Bo Johansson ◽  
Agnes Psikuta ◽  
Simon Annaheim ◽  
...  
Keyword(s):  
Heat Strain ◽  
Predicted Heat Strain ◽  
Intermittent Work

scholarly journals Thermophysiological Comfort of Surgeons and Patient in an Operating Room Based on PMV-PPD and PHS Indexes

2020 ◽  
Vol 10 (5) ◽  
pp. 1801 ◽  
Author(s):  
Radostina A. Angelova ◽  
Rositsa Velichkova
Keyword(s):  
At Risk ◽  
Relative Humidity ◽  
Operating Room ◽  
Air Temperature ◽  
Indoor Environment ◽  
Thermal Environment ◽  
Climatic Conditions ◽  
Clothing Insulation ◽  
Indoor Thermal Environment ◽  
Predicted Heat Strain

There are different actors in an operating room (OR), who have controversial requirements for the indoor thermal environment. While the patient is at risk of perioperative hypothermia, the surgeons are in a state of thermophysiological discomfort. The study presents an analysis of the thermophysiological comfort of both patient and surgeons in an OR. Surgical clothing ensembles with three values of clothing insulation are simulated. Different indoor environment conditions (air temperature and relative humidity) are tested. The analysis is based on the calculation of predicted mean vote and predicted percentage of dissatisfied (PMV-PPD) indexes and assessment of the climatic conditions categories. Discussion of the predicted heat strain is also presented. The simulated results and their analysis show considerable discrepancies between the thermophysiological comfort of the patient and the surgeons, even when dressed in a light protective ensemble, in the same indoor environment.

scholarly journals Robust Indoor Localization Methods Using Random Forest-Based Filter against MAC Spoofing Attack

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6756
Author(s):  
DongHyun Ko ◽  
Seok-Hwan Choi ◽  
Sungyong Ahn ◽  
Yoon-Ho Choi
Keyword(s):  
Deep Learning ◽  
Random Forest ◽  
Prediction Accuracy ◽  
Indoor Localization ◽  
Artificial Noise ◽  
Good Prediction ◽  
Localization Method ◽  
Good Prediction Accuracy ◽  
Attack Scenario ◽  
Natural Noise

With the development of wireless networks and mobile devices, interest on indoor localization systems (ILSs) has increased. In particular, Wi-Fi-based ILSs are widely used because of the good prediction accuracy without additional hardware. However, as the prediction accuracy decreases in environments with natural noise, some studies were conducted to remove it. So far, two representative methods, i.e., the filtering-based method and deep learning-based method, have shown a significant effect in removing natural noise. However, the prediction accuracy of these methods severely decreased under artificial noise caused by adversaries. In this paper, we introduce a new media access control (MAC) spoofing attack scenario injecting artificial noise, where the prediction accuracy of Wi-Fi-based indoor localization system significantly decreases. We also propose a new deep learning-based indoor localization method using random forest(RF)-filter to provide the good prediction accuracy under the new MAC spoofing attack scenario. From the experimental results, we show that the proposed indoor localization method provides much higher prediction accuracy than the previous methods in environments with artificial noise.

scholarly journals Research on Rubber Spring Model of High-speed EMU Based on Non-hyperelastic Forces

Mechanika ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 12-21
Author(s):  
Chuanbo XU ◽  
Maoru CHI ◽  
Liangcheng DAI ◽  
Yiping JIANG ◽  
Yongfa CHEN ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Prediction Accuracy ◽  
High Speed ◽  
Dynamic Condition ◽  
Static Condition ◽  
Good Prediction ◽  
Calculation Formula ◽  
Good Prediction Accuracy ◽  
Calculation Results ◽  
Better Than

The research on the mechanical model of rubber spring is one of the hot spots in train dynamics. In order to accurately calculate the viscoelastic force of the rubber spring, especially the non-hyperelastic forces (NHEF) part, a NHEF model is proposed based on the elliptic approximation method. Furthermore, the calculation formula of periodic energy consumption is put forward. The NHEF model is verified by experiments, and the function λ isconstructed to verify the formula of periodic energy consumption. The calculation results showed that the NHEF model had high accuracy in predicting the dynamic and quasi-static NHEF of rubber spring, the prediction accuracy of shear condition was better than that of compression condition, and the accuracy of quasi-static condition was better than that of dynamic condition; the calculation formula of periodic energy consumption had a good prediction accuracy in all working conditions.

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