地铁火灾研究

对世界各国的地铁火灾进行分析,阐述了地铁火灾产生的原因和危险性,介绍了地铁设计中的通风空调系统,探讨了火灾研究的手段,并通过实例进行模拟与分析。     

NONINVASIVE DETECTION OF BRAIN ACTIVITY VARIATION UNDER DIFFERENT DEPTH OF ANESTHESIA BY EEG COMPLEXITY

Objective To detect the change of brain activity under different depth of anesthesia （DOA） noninvasively. A,fethods The Lempel-Ziv complexity C（n） was used to analyze EEG and its four components （delta, theta, alpha, beta）, which was recorded from SD rats under different DOA. The relationship between C（n） and DOA was studied. Results The C（n） of EEG will decrease while the depth of anesthesia increasing and vice versa. It can be used to detect the change of DOA sensitively. Compared with power spectrum, the change of C（n） is opposite to that of power spectrum. Only the C （n） of delta rhythm has obvious variations induced by the change of DOA, and the variations of delta is as similar as the EEG＇s. Conclusion The study shows that the desynchronized EEG is replaced by the synchronized EEG when rat goes into anesthesia state from awake, that is just the reason why complexity and power spectrum appear corresponding changes under different DOA. C（n） of delta rhythm dynamic change leads to the change of EEG, and the delta rhythm is the dominant rhythm during anesthesia for rats.     

A knowledge-transfer-based learning framework for airspace operation complexity evaluation

A sector is a component airspace whose operation is allocated to an air traffic controller. The operation complexity of a sector plays a critical role in the current Air Traffic Management system, e.g. it determines the workload volume of air traffic controllers and serves as a reliable index for airspace configuration and traffic flow management. Therefore, accurately evaluating the sector operation complexity is a problem of paramount importance in both practice and research. Due to numerous interacting factors, traditional methods based on only one single complexity indicator fail to accurately reflect the true complexity, especially when these factors are nonlinearly correlated. In light of these, the attempt to use machine learning models to mine the complex factor-complexity relationship has prevailed recently. The performance of these models however relies heavily on sufficient samples. The high cost of collecting ample data often results in a small training set, adversely impacting on the performance that these machine learning models can achieve. To overcome this problem, this paper for the first time proposes a new sector operation complexity evaluation framework based on knowledge transfer specifically for small-training-sample environment. The proposed framework is able to effectively mine knowledge hidden within the samples of the target sector, i.e. the sector undergoes evaluation, as well as other sectors, i.e. non-target sectors. Moreover, the framework can properly handle the integration between the knowledge derived from different sectors. Extensive experiments on real data of 6 sectors in China illustrate that our proposed framework can achieve promising performance on complexity evaluation when only a small training set of the target sector is available.     

Influence of avenue trees on traffic pollutant dispersion in asymmetric street canyons: Numerical modeling with empirical analysis

The dispersion of traffic-related pollutants in urban street canyons is of importance for the health and quality of lives. To reveal the inherent principle, researchers have performed a lot of investigations; many dispersion phenomena have also been assessed during recent years. However, the presence of avenue trees in street canyons and their capacity for pollutant dispersion remains partly addressed. In this study, we investigated the effects of avenue trees in urban street canyons on traffic pollutant dispersion. The dispersion of CO concentration in asymmetric street canyons was simulated under varied situations. The computational results showed a good agreement with the experimental data, and the numerical model was validated to be adequate for investigating the pollutant dispersion in street canyons. Then, the numerical simulations were extended to explore the impacts of the effects of avenue trees on CO dispersion; the results indicated that avenue trees generally increase CO concentrations in asymmetric street canyons. When the wind direction is perpendicular to the street axis, a terraced building raises pollutant concentrations at the windward wall and reduces concentration at the leeward wall on the pedestrian levels. Findings of this study are expected to provide significant insight into urban road design and strategy making for avenue tree planting, particularly under the existing worldwide sustainable low-carbon urban development.     

Agent-based model of maritime traffic in piracy-affected waters

Contemporary maritime piracy presents a significant threat to global shipping industry, with annual costs estimated at up to US$7bn. To counter the threat, policymakers, shipping operators and navy commanders need new data-driven decision-support tools that will allow them to plan and execute counter-piracy operations most effectively. So far, the provision of such tools has been limited. In cooperation with maritime domain stakeholders, we have therefore developed AgentC, a data-driven agent-based simulation model of maritime traffic that explicitly models pirate activity and piracy countermeasures. Modeling the behavior and interactions of thousands of individually simulated vessels, the model is capable of capturing the complex dynamics of the maritime transportation system threatened by maritime piracy and allows assessing the potential of a range of piracy countermeasures. We demonstrate the what-if analysis capabilities of the model on a real-world case study of designing a new transit corridor system in the Indian Ocean. The simulation results reveal that the positive past experience with the transit corridor in the narrow Gulf of Aden does not directly translate to the vast and open waters of the Indian Ocean and that additional factors have to be considered when designing corridor systems. The agent-based simulation development and calibration process used for building the presented model is general and can be used for developing simulation models of other maritime transportation phenomena.     

三种任务类型对大学生英语写作的影响

本文以写作产出模式为基础,以广西师范大学非英语专业的学生为研究对象,研究根据同一题材编写的三种不同写作任务类型（个人写作任务、话题写作任务、概要写作任务）对非英语专业学习者在英语写作产出的准确度和复杂度上的影响。结果表明：任务类型显著影响三项写作任务语言产出的准确度和复杂度。个人任务准确度显著高于话题任务和概要任务;概要任务复杂度显著高于个人任务和话题任务。最后本文讨论了研究结果对促进写作教学的现实意义。     

On the evaluation of a public transportation network quality: Criteria validation methodology

A public transportation network serves in adequate way a population if it evolves in time following the existent social reality. Changes made in order to improve service must be analyzed and evaluated. The introduction of modern technology to validate the fare card allowed a quick access to important, although incomplete, data. Databases with only the getting in validation information can be used to construct an origin–destination (OD) matrix, allowing a service quality analysis. Here it is presented a basic methodology to rigorously validate service quality criteria considering what might be interesting for the user. The quality analysis philosophy is the following. First, based on automatically gathered data, one reconstructs the origin–destination (OD) matrix, which contains information concerning the number of passengers traveling between zones of a certain region. The OD matrix is used to calculate some criteria characterizing the transportation network quality, such as traveling times, waiting times at a stop or transport occupation. The reconstructed OD matrix always contains errors, which cause errors in the criteria values. How significant are these errors? This question can be answered using our criteria validating methodology, which is based on statistical analysis. It has been implemented at the urban bus transport system of Porto, STCP, allowing the evaluation of the transportation network quality under a number of criteria and guaranteeing rigorous results.     

地铁车站环控系统设计中气流组织方案的数值模拟

针对地铁车站环境控制系统设计中常用的几种典型气流组织方案,使用计算流体力学(CFD)的方法,采用重正化群双方程紊流模型,对待建地铁车站及其隧道内的温度场和气流速度场进行三维数值模拟,得到各种方案下的温度和气流速度分布。通过分析和比较,认为屏蔽门方案能够得到最优的站台候车环境,但会使隧道内的温度有较大的升高,且投资较大;在投资较小的3种方案中,混合回/排风方案的效果最佳,对该方案造成的站台上气流速度分布不均匀的情况提出了相应的改善措施,并对数值模拟方法在地铁车站环控系统设计中的应用进行了探讨。     

ATCEM: a synthetic model for evaluating air traffic complexity

Air traffic complexity, which measures the disorder of air traffic distribution, has become the critical indicator to reflect air traffic controller workload in air traffic management (ATM) system. However, it is hard to assess the system accurately because there are too many correlated factors, which make the air traffic complexity nonlinear. This paper presents an air traffic complexity evaluation model with integrated classification using computational intelligence (ATCEM). To avoid redundant factors, critical factors contributing to complexity are analyzed and selected from numerous factors in the ATCEM. Subsequently, to construct the mapping relationship between selected factors and air traffic complexity, an integrated classifier is built in ATCEM. With efficient training and learning based on aviation domain knowledge, the integrated classifier can effectively and stably reflect the mapping relationship between selected factors and the category of air traffic complexity to ensure the precision of the evaluation. Empirical studies using real data of the southwest airspace of China show that the ATCEM outperforms a number of state‐of‐the‐art models. Moreover, using the critical complexity factors selected in ATCEM, the air traffic complexity could be effectively estimated. Copyright © 2015 John Wiley & Sons, Ltd.     

单向交通对交叉口交通安全影响分析

单向交通作为一种有效的交通组织方式,在缓解城市交通压力方面具有重要作用。依据交通冲突技术分析与交叉口复杂度的计算,对比双向交通组织,单向交通的实施可使交叉口交通组织变得简单,冲突点数目减少,复杂度降低,从而可有效改善交叉口交通运行状况及交通安全状况,降低交通事故率,对保持我国城市交通科学发展,保障市民出行安全具有重要意义。