Methodology for identifying gaseous constituents of the atmosphere

Methodology for the analysis of concentrations of gaseous composite of atmosphere by the corresponding infrared (IR) spectrum, measured with the help of trajectory spectroradiometers (TSR) is observed. The developed algorithm for mathematical processing of the measurement results is briefly described, including the detection and estimation of the concentrations of the sought gases using the notch filtration of their spectral components, which makes it possible to significantly reduce the concentration identification error. The spectra of various substances in the mid-IR range are considered, and the results of approbation of the technique based on the TSR model with an external high-temperature radiation source on a 1 m path are presented.

Hazard identification and early warning system based on stochastic forest algorithm in underground coal mine

Aiming at the problem of large error and long time of early warning response in the traditional system, this paper designs a hazard identification early warning system based on random forest algorithm in underground coal mine. By random classification decision forest created dangerous content in different areas of the downhole information input into the decision tree as a test sample, according to the result of the output of the leaf node determine the risk level of decision trees, and USES the high precision of decision forest classification ability the threat level assessment test sample, radically reducing hazards identification error. Then, based on the evaluation results, combined with the threshold value of warning criteria to identify the gas exceeding limit area, and determine the fire source warning level, so as to realize the hazard source identification and warning. The simulation results show that the average hazard location identification error of the system is only 4.1%, and the warning response time can be controlled within 9 s.

Evaluating the Language ENvironment Analysis System for Korean

Purpose The algorithm of the Language ENvironment Analysis (LENA) system for calculating language environment measures was trained on American English; thus, its validity with other languages cannot be assumed. This article evaluates the accuracy of the LENA system applied to Korean. Method We sampled sixty 5-min recording clips involving 38 key children aged 7–18 months from a larger data set. We establish the identification error rate, precision, and recall of LENA classification compared to human coders. We then examine the correlation between standard LENA measures of adult word count, child vocalization count, and conversational turn count and human counts of the same measures. Results Our identification error rate (64% or 67%), including false alarm, confusion, and misses, was similar to the rate found in Cristia, Lavechin, et al. (2020) . The correlation between LENA and human counts for adult word count ( r = .78 or .79) was similar to that found in the other studies, but the same measure for child vocalization count ( r = .34–.47) was lower than the value in Cristia, Lavechin, et al., though it fell within ranges found in other non-European languages. The correlation between LENA and human conversational turn count was not high ( r = .36–.47), similar to the findings in other studies. Conclusions LENA technology is similarly reliable for Korean language environments as it is for other non-English language environments. Factors affecting the accuracy of diarization include speakers' pitch, duration of utterances, age, and the presence of noise and electronic sounds.

Study on the Method of Moving Load Identification Based on Strain Influence Line

In order to improve the accuracy of load identification and study the influence of transverse distribution, a novel method was proposed for the moving load identification based on strain influence line and the load transverse distribution under consideration. The load identification theory based on strain influence line was derived, and the strain integral coefficient was proposed for the identification. A series of numerical simulations and experiments were carried out to verify the method. The numerical results showed that the method without considering the load transverse distribution was not suitable for solving the space problem, and the method with the load transverse distribution under consideration has a high identification accuracy and excellent anti-noise performance. The experimental results showed that the speed identification error was smaller than ±5%, and the vehicle speed had no obvious influence on the identification results of the vehicle weight. Moreover, the average identification error of the vehicle weight was smaller than ±10%, and the error of more than 90% of samples was smaller than ±5%.

Identification of critical moving characteristics in high speed on/off valve based on time derivative of the coil current

This article focuses on accurate identification of the critical moving characteristics of the high speed on/off valve. Typically, there are two strategies for identifying the critical moving characteristics, including calculation strategy based on force balance and strategy for detecting the coil current’s certain points. However, the accuracy of the two above strategies needs to be improved. Therefore, to improve the identification accuracy of the high speed on/off valve’s critical moving characteristics, an identification strategy for detecting the time derivative of the coil current is proposed. First, a mathematical model of the high speed on/off valve (including electromagnetic sub-model and mechanical-fluid sub-model) is established. And on this basis, relationship between the coil current’s derivative and the valve’s critical moving characteristics is analyzed which reveals the changing rule of the coil current’s derivative causing by the ball valve’s moving. Finally, the changing rule of the coil current’s derivative is verified by the comparative simulations and experiments, which also indicate that, with the proposed identification strategy, the maximum identification error of the critical opening/closing time is only within 6%, and the maximum identification error of the total opening/closing time is still small (2.9%), compared to other identification strategies in the previous literatures.

Supplemental Material: Minimal net incision of the northern Sierra Nevada (California, USA) since the Eocene–early Oligocene

Site identification, error analysis, and Ar/Ar dating.<br>

Supplemental Material: Minimal net incision of the northern Sierra Nevada (California, USA) since the Eocene–early Oligocene

Site identification, error analysis, and Ar/Ar dating.<br>

Impact Force Identification of the Variable Pressure Flexible Impact End-Effector in Space Debris Active Detumbling

The security of the space environment is under serious threat due to the increase in space debris in orbit. The active removal of space debris could ensure the sustainable use of the space environment; this removal relies on detumbling technology. According to the characteristics of the mechanical impact-type active detumbling method, this paper discusses a method to accurately identify the impact force using a pressure sensor. In this work, the impact force between a flexible impact end-effector and the space debris was analyzed theoretically and experimentally considering the pressure change during impact. Firstly, a nonlinear impact force model was established for the impact between a flexible end-effector and space debris. Secondly, impact experiments were performed and the friction model was modified. Finally, the effect of detumbling was verified through simulation experiments. The results showed that the identification error of normal impact force was less than 6.7% and the identification error of tangential friction force was less than 6.9%. Therefore, this identification method of impact force met the requirements of space debris detumbling, which has important guiding significance for the active removal technology of space debris.