差压测漏仪微泄漏的建模与仿真

为研究密封件的微泄漏量大小与检测时间之间的关系,实现检测时间与检测可靠性的优化,通过分析密封件微小泄漏的理论,建立了微小泄漏的等效模型。基于此模型,采用AMESim仿真软件对差压测漏仪检测微小泄漏的动态特征进行仿真分析,得出了被测件微小泄漏时的动态P-T关系曲线。结果表明,此仿真试验能反映出密封件微泄漏时压力与时间的动态关系,为制定最优的检测时间提供了依据。     

Trends in youth’s videogame playing, overall computer use, and communication technology use: The impact of self-esteem and the Big Five personality factors

The objective of the current research is to model trends in video game playing, overall computer use, and communication technology use in a longitudinal sample of youths, aged 11-16 over a 3-year interval. In addition, individual difference characteristics that may be predictive of these trends were included, namely, socio-demographic characteristics (gender, ethnicity, and parental income) and personality characteristics (self-esteem, the Big Five personality factors). Findings suggested that youth increased their overall computer and communication technology use but decreased their videogame playing over time. Many individual differences predicted mean levels of these technologies with fewer predicting slopes. Conclusions, implications, and limitations are discussed.     

α-MoO3/TiO2 core/shell nanorods: Controlled-synthesis and low-temperature gas sensing properties

Crystalline α-MoO₃/TiO₂ core/shell nanorods are fabricated by a hydrothermal method and subsequent annealing processes under H₂/Ar flow and in the ambient atmosphere. The shell layer is composed of crystalline TiO₂ particles with a diameter of 2-6 nm, and its thickness can be easily controlled in the range of 15-45 nm. The core/shell nanorods show enhanced sensing properties to ethanol vapor compared to bare α-MoO₃ nanorods. The sensing mechanism is different from that of other one-dimensional metal oxide core/shell nanostructures due to very weak response of TiO₂ nanoparticles to ethanol. The enhanced sensing properties can be explained by the change of type II heterojunction barrier formed at the interface between α-MoO₃ and TiO₂ in the different gas atmosphere. The present results demonstrate a novel sensing mechanism available for gas sensors with high performance.     

Effect of micro-electrode geometry on NO2 gas-sensing characteristics of one-dimensional tin dioxide nanostructure microsensors

Electrodes with micro-gaps are fabricated by using dc-sputtering and FIB techniques. SnO₂ nanowires are deposited on the micro-gap (1-30 μm) by suspension dropping method to fabricate a micro-gas sensor. The sensing ability of various SnO₂ micro-gap sensors is measured. A comparison between sensors reveals that the short-gap electrode has numerous advantages in terms of reliability, high sensitivity and detection of low concentrations of NO₂, while the large-gap electrode is relatively sensitive for high concentrations. Conductance measurements are carried out at different surface temperatures and NO₂ concentrations in order to investigate the effects that the gap size has on the overall sensor conductance. The results suggest that the interface between the electrode and sensitive layer has a very important role for the sensing mechanism of tin dioxide gas sensors.     

基于数据流的启发式文件传输识别系统设计

为了防止文件通过网络泄露,研究了网络传输文件的格式、传送形式以及通信行为特征,提出一种基于网络数据流的文件传输识别方法。通过引入文件数据流的概念,构建了具有特异性的文件特征指纹库,采用自适应深度协议分析技术,对文件传输在通信协议中表现出的内容和行为特征信息进行多层次启发式的检测。测试结果表明,该系统运行高效,检测结果准确。     

Interface feature prioritization for web services: Case of online flight reservations

Acceptance, utility, and usability of system designs have become a focal interest in human–computer interaction (HCI) research, yet at present there is a lack detailed understandings of which system design features influence them. The purpose of the study is to examine the effects of five product design features; customization, adaptive behavior, memory load, content density, and speed on user preference through an experimental study by using conjoint analysis. In experimental study, instead of classical conjoint cards, prototypes were generated for products. Besides, desirability and market segments of product prototypes were identified. In line with the results, among the five product design features, speed is the most and customization is the least important features that affect user preference. Contrary to the expectations, customization has a relatively small importance value in this research. Subsequent design features that influence user preference after speed are minimal memory load, adaptive behavior, and content density, respectively. According to findings, interfaces that have high-speed, minimal memory load, adaptive behavior, low content density, and customization features are more preferable than those that do not.     

The roles of user motivation to perform a task and decision support system (DSS) effectiveness and efficiency in DSS use

The purposes of this study are to: (1) obtain measures of actual decision support system (DSS) use that include the three elements of DSS use proposed by Burton-Jones and Straub (Burton-Jones, A., & Straub, D.W., Jr., (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246), and (2) identify an important psychological construct – a user’s motivation to perform a task – and examine how it interacts with two DSS characteristics – effectiveness and efficiency – to affect actual DSS use. As predicted, the findings indicated that individuals who used a more effective DSS to work on a task that they were motivated in increased usage of the DSS, while DSS use did not differ between individuals who used either a more or less effective DSS to complete a task that they were less motivated in. The results also showed significant difference for two measures of DSS use (i.e., STEP and TIME) and no significant difference for one measure of DSS use (i.e., USE) between individuals who used either a more or less efficient DSS to perform a task that they were more motivated in. As expected, significant differences were found for individuals who used either a more or less efficient DSS to complete a task that they were less motivated in. Finally, the results showed that DSS use increased when perceived ease of use and perceived usefulness of the DSS were high; therefore, these results corroborate the findings of prior research in the context of actual DSS use.     

Predictive models for emission of hydrogen powered car using various artificial intelligent tools

This paper investigates the use of artificial intelligent models as virtual sensors to predict relevant emissions such as carbon dioxide, carbon monoxide, unburnt hydrocarbons and oxides of nitrogen for a hydrogen powered car. The virtual sensors are developed by means of application of various Artificial Intelligent (AI) models namely; AI software built at the University of Tasmania, back-propagation neural networks with Levenberg–Marquardt algorithm, and adaptive neuro-fuzzy inference systems. These predictions are based on the study of qualitative and quantitative effects of engine process parameters such as mass airflow, engine speed, air-to-fuel ratio, exhaust gas temperature and engine power on the harmful exhaust gas emissions. All AI models show good predictive capability in estimating the emissions. However, excellent accuracy is achieved when using back-propagation neural networks with Levenberg–Marquardt algorithm in estimating emissions for various hydrogen engine operating conditions with the predicted values less than 6% of percentage average root mean square error.     

基于氧传感膜荧光特性的溶解氧传感器研制

基于氧传感膜荧光特性研制了一种低成本、小型化的溶解氧传感器.对传统氧传感膜的制备方案进行了优化,结合其透光特性对所制备的传感膜优劣进行甄别和选优.在此基础上,重点研究了水温、浸泡时间等因素对传感膜荧光发射强度的影响.为提高溶解氧的测量精度,设计了一种45°角斜面传感器探头结构,有效降低了水中气泡对溶解氧的测量干扰.实验结果表明:该溶解氧传感器能够准确测量0 ～20 mg/L范围内的待测液体的含氧量,检测误差为±2％,检测精度达±0.1 mg/L,在工农业生产、水质监测及水产养殖等方面具有较好的应用前景.