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Air movement can provide desirable cooling in "warm" conditions, but it can also cause discomfort. This study focuses on the effects of turbulent air movements on human thermal sensations through investigating the preferred air velocity within the temperature range of 26 degrees C and 30.5 degrees C at two relative humidity levels of 35% and 65%. Subjects in an environmental chamber were allowed to adjust air movement as they liked while answering a series of questions about their thermal comfort and draft sensation. The results show that operative temperature, turbulent intensity and relative humidity have significant effects on preferred velocities, and that there is a wide variation among subjects in their thermal comfort votes. Most subjects can achieve thermal comfort under the experimental conditions after adjusting the air velocity as they like, except at the relative high temperature of 30.5 degrees C. The results also indicate that turbulence may reduce draft risk in neutral-to-warm conditions. The annoying effect caused by the air pressure and its drying effect at higher velocities should not be ignored. A new model of Percentage Dissatisfied at Preferred Velocities (PDV) is presented to predict the percentage of feeling draft in warm isothermal conditions.

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Nonfatal heroin overdoses are common among Chinese heroin users. Drug users should be encouraged to participate and remain in methadone treatment to prevent overdose and be educated about proper response to overdose to reduce risk of overdose death.

With the development of the Energy Internet of Things (EIoT), it is of great practical significance to study the security strategy and intelligent control system for solar thermal utilization system to optimize the operation efficiency and carry out intelligent dynamic adjustment. For buildings integrated with solar water heating systems, computational fluid dynamics simulation was used in analyzing the process of solar energy output. A method based on machine learning is proposed to predict energy conversion. Besides, the simulation and analysis are carried out in combination with the possible safety problems such as the vibration of the control system. This paper proposed a novel platform of EIoT for machine learning-based cybersecurity study and implemented the platform for the temperature monitoring system. After the evaluation of the machine learning-based cybersecurity study, the EIoT system demonstrated a high performance with the Extreme Gradient Boosting (XGBoost) training algorithm.

Abstract-This paper mainly based on Moodle network learning system evaluation theory foundation, principle of evaluation, evaluation index system, evaluation system and platform design and implementation in system, depth, and construct the content relatively complete, has the education scientific and practical evaluation system, through this platform to carry out the multiple evaluation practice, has obtained the good effect evaluation.

Fountains formed due to the injection into homogeneous fluids with the combined effect of temperature and concentration occur widely in nature and in environmental improvement and industrial applications such as brine water discharge, living sewage disposal, release of waste hot gases into the atmosphere from chimneys, solar desalination discharge, and sewage wastewater discharge for agriculture irrigation. In this study, the behavior of round fountains with salt water as a homogeneous ambient fluid in a transparent glass tank over 0.25 ≤ Fr T ≤ 2.0, 0 ≤ N ≤ 5.0, and 47 ≤ Re ≤ 824 was studied using particle image velocimetry/planar laser-induced fluorescence (PIV/PLIF). The recorded PIV/PLIF images provide a better understanding of the transient behavior and intrinsic laws of buoyant jets in an ambient fluid and optimally use their transport mechanisms and entrainment characteristics in environmental improvement and industrial applications. Scaling for the initial maximum fountain height at the development stage, the obtained scaling correlation from the experimental results is consistent with previous results from direct numerical simulation results.

A model of emotional interaction agents in intelligent tutoring systems is presented in this paper, and the functionalities of the key components of the agents are described. To improve the emotional interaction between learners and the system, a kind of emotional interaction agents which can deduce users' emotional statues, provide helps needed, and mark emotional difficulty of the learned pedagogical units, is introduced and discussed in detail in order to improve pedagogical effects.