Cycle commuting in Belgium: Spatial determinants and ‘re-cycling’ strategies

This paper attempts to explain the spatial variation of the use of a bicycle for commuting to work at the level of the 589 municipalities in Belgium. Regression techniques were used and special attention was paid to autocorrelation, heterogeneity and multicollinearity. Spatial lag models were used to correct for the presence of spatial dependence and a disaggregated modelling strategy was adopted for the northern and southern parts of the country. The results show that much of the inter-municipality variation in bicycle use is related to environmental aspects such as the relief, traffic volumes and cycling accidents. Town size, distance travelled and demographic aspects also have some effect. In addition, there are regional differences in the effects of the structural covariates on bicycle use: the impact of variables such as traffic volume and cycling accidents differs substantially between the north and the south of the country. This paper also suggests that high rates of bicycle use in one municipality stimulate cycling in neighbouring municipalities, and hence that a mass effect can be initiated, i.e. more cycle commuting encourages even more commuters in the area to cycle. These findings provide some recommendations for decision-makers wishing to promote a shift from car to bicycle use.     

Synthesis of a new chitosan derivative and assay of Escherichia coli adsorption

A new chitosan derivative is prepared using chitosan.Ethyl chlorocarbonate was first introduced to the hydroxyl group of phthaloylchitosan through a nucleophilic reaction.Hydrazine was then added to recover the amino groups of chitosan and promote cross-l     

圆电极电磁流量计干标定模型及仿真

目前在电磁流量计的干标定研究中，为方便公式推导，通常将实际的圆电极简化为方电极模型．这种简化在电极尺寸较大时，会引入不必要的计算误差，影响流量计的标定精度．本文从圆电极模型出发，论述了其对应权重函数的计算过程．并针对大尺寸圆电极模型进行理想化计算，得到其点电极模型，并运用此模型进行了仿真研究．     

Design and evaluation of an integrated inventory and transportation system

This paper proposes the adoption of an integrated inventory and transportation system (IITS) to minimize the total costs of inventory and transportation. A non-linear programing is developed by analyzing transportation and inventory costs with one supplier and many retailers in the distribution environment. The paper compares the proposed model with the traditional approach in computing total costs with numerical data. The results indicate that the total costs can be optimized by adopting integrated programing rather than the traditional approach, along with achieving improved customer service levels. In particular, sensitivity analysis is applied to determine the performance of the IITS under various transportation costs, holding costs and shortage costs. It shows that the transportation cost per unit is most sensitive in the proposed model. In this situation, the IITS is more effective for cost saving when set-up cost, holding and shortage costs are high, but is less effective for situations involving high per-unit transportation costs.     

Privacy protection method for fine-grained urban traffic modeling using mobile sensors

With the ubiquitous nature of mobile sensing technologies, privacy issues are becoming increasingly important, and need to be carefully addressed. Data needs for transportation modeling and privacy protection should be deliberately balanced for different applications. This paper focuses on developing privacy mechanisms that would simultaneously satisfy privacy protection and data needs for fine-grained urban traffic modeling applications using mobile sensors. To accomplish this, a virtual trip lines (VTLs) zone-based system and related filtering approaches are developed. Traffic-knowledge-based adversary models are proposed and tested to evaluate the effectiveness of such a privacy protection system by making privacy attacks. The results show that in addition to ensuring an acceptable level of privacy, the released datasets from the privacy-enhancing system can also be applied to urban traffic modeling with satisfactory results. Albeit application-specific, such a “Privacy-by-Design” approach would hopefully shed some light on other transportation applications using mobile sensors.     

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.     

波浪模型试验应当注意的一些问题

根据实践经验,按照波浪物理模型试验要求、工作大纲、试验条件、制作模型、试验过程和报告编写等环节,总结了容易疏忽的问题,并给出了解决这些问题的方法和建议,以促进模型试验成果的科学性和可靠性,提高工作效率,避免不必要地失误。可供从事此项工作人员特别是经验不多的年轻人借鉴和参考。     

基于元胞理论的船厂码头移泊作业问题算法

为了解决大规模船厂的码头移泊作业问题，基于船舶移动路径具有过程演进的特性，建立了码头移泊作业问题的元胞数学模型。按照问题元胞模型的演进特性和演变规则，采用蚁群智能算法来对模型进行求解，并论证了该算法的收敛性。通过实例计算，其结果与船厂实际操作安排进行比较和分析，验证了该算法的有效性和优越性。     

Evolving competition between Hong Kong and Shenzhen ports

Shenzhen Port (SZP), once a negligible local port, has risen dramatically to a world-leading container port and an “equal” player with Hong Kong Port (HKP). Will this market share reallocation continue, or will equilibrium be eventually realized for HKP to prosper continuously? We examine the relationship between these two ports to answer this question. We propose a new transformation method to describe the growth of container cargo transport demand, define the quantitative measures of the competition relationship and port competitiveness, and present a rigorous analytical framework with econometric tests and models to understand the true relationship between HKP and SZP. Direct empirical tests suggest that SZP complements HKP; however, the two ports exhibit strong competition when the effect of demand growth is excluded. Considering transshipment separately, we find that the impact of SZP on HKP is negative in transshipment but complementary in direct shipment. We may conclude that HKP does not affect SZP, whereas SZP has competitive power over HKP. These results are consistent with the findings of some previous theoretical studies.