Developing a chaotic pattern of dynamic Hazmat routing problem

The present paper proposes an iterative procedure based on chaos theory on dynamic risk definition to determine the best route for transporting hazardous materials (Hazmat). In the case of possible natural disasters, the safety of roads may be seriously affected. So the main objective of this paper is to simultaneously improve the travel time and risk to satisfy the local and national authorities in the transportation network. Based on the proposed procedure, four important risk components including accident information, population, environment, and infrastructure aspects have been presented under linguistic variables. Furthermore, the extent analysis method was utilized to convert them to crisp values. To apply the proposed procedure, a road network that consists of fifty nine nodes and eighty two-way edges with a pre-specified affected area has been considered. The results indicate that applying the dynamic risk is more appropriate than having a constant risk. The application of the proposed model indicates that, while chaotic variables depend on the initial conditions, the most frequent path will remain independent. The points that would help authorities to come to the better decision when they are dealing with Hazmat transportation route selection.     

Lubrication and tribology in seawater hydraulic piston pump

Water hydraulic systems have provoked major interest because of the human friendly and environmental safety aspects. Piston pump is one of the most frequently used hydraulic units in recent engineering technique. In water hydraulic piston pump, poor lubrication is more likely to happen than in oil hydraulic one because of difference in properties between water and oil. So there are some key problems such as corrosive wear and erosion, which are investigated briefly. Many new materials have been developed, which give longer life expectancies with water without corrosion and erosion. A new type of seawater hydraulic piston pumps with better suction characteristics had been developed at HUST. Much of this research has concentrated on new materials, structure and experiments, which are also specially introduced.     

Research on Motion Estimation Algorithm of Star Point Based on Nonlinear Gaussian Fitting

The energy distribution model of motion blurred star point is analyzed. The distribution of the star point approximates to a two-dimensional (2D) Gaussian distribution under degeneration. Two multi-parameter nonlinear Gaussian fitting methods (GFMs) are proposed, and the relationship between fitting parameters and motion blur parameters is analyzed. Estimation of the parameters of motion blur by fitting parameters is calculated to realize the error compensation of the motion blur. The simulation results show the effectiveness and accuracy.     

The role of individual characteristics in car ownership shortly after relationship dissolution

The dissolution of a relationship is a life event that often coincides with many other changes in life, such as a decline in income level or household size or a change in place of residence. This study aims to provide more insight into the ways in which circumstances shortly following the disruption of a relationship affect travel behaviour. Register data that combines information on the Dutch population, income and vehicle registration are used to understand how personal situations that are closely related to relationship disruption affect car ownership. The study shows that several characteristics of singles and single partners shortly after a breakup negatively affect car ownership. For instance, a relatively low income level, unemployment, living in a city or a residential move all affect car ownership negatively. This study focuses on the role of circumstances shortly after relationship disruption, demonstrating the importance of such an event.     

Consideration of different travel strategies and choice set sizes in transit path choice modelling

Transportation - Path choice modelling is typically conducted by considering a subset of paths, not the universal set of all feasible paths as this is computationally challenging. This study...     

Numeric-based XML labeling schema by generalized dynamic method

Most efficient indeces and query techniques over XML (extensible markup language) data are based on a certain labeling scheme, which can quickly determine ancestor-descendant and parent-child relationship between two nodes. The current basic labeling schemes such as containment scheme and prefix scheme cannot avoid relabeling when XML documents are updated. After analyzing the essence of existing dynamic XML labels such as compact dynamic binary string (CDBS) and vector encoding, this paper gives a common unifying framework for the numeric-based generalized dynamic label, which can be implemented into a variety of dynamic labels according to the different user-defined value comparison methods. This paper also proposes a novel dynamic labeling scheme called radical sign label. Extensive experiments show that the radical sign label performs well for the initialization, insertion and query operations, and especially for skewed insertion where the storage cost of the radical sign label is better than that of former methods.     

Skin detection method based on cascaded AdaBoost classifier

Skin detection has been considered as the principal step in many machine vision systems, such as face detection and adult image filtering. Among all these techniques, skin color is the most welcome cue because of its robustness. However, traditional color-based approaches poorly perform on the classification of skin-like pixels. In this paper, we propose a new skin detection method based on the cascaded adaptive boosting (AdaBoost) classifier, which consists of minimum-risk based Bayesian classifier and models in different color spaces such as HSV (hue-saturation-value), YCgCb (brightness-green-blue) and YCgCr (brightness-green-red). In addition, we have constructed our own database that is larger and more suitable for training and testing on filtering adult images than the Compaq data set. Experimental results show that our method behaves better than the state-of-the-art pixel-based skin detection techniques on processing images with skin-like background.     

Degradation of selected indoor air pollutants: Comparison study of photocatalytic,ozone-assisted photocatalytic and amine adsorption processes

Indoor air pollutants impact human health, comfort and productivity. The method of photocatalysis has been applied mainly in flow reactors and little information is available on indoor air pollutant removal in airtight reactors. In the paper, experiments were carried out to remove formaldehyde (HCHO), ammonia (NH₃) and volatile organic compounds (VOCs) in the airtight and ventilated chambers. Results demonstrated that 90.4% of HCHO, 92.3% of NH₃ and 57.9% of VOCs were removed in the amine adsorption process, while 67.5% (hereinbefore, these are the mass fraction) of HCHO, 60.0% of NH₃, and 61.2% of VOCs were removed in the photocatalytic process. However, ozone-assisted photocatalytic process showed great potential to degrade indoor air pollutants in the ventilated chamber. Factors and mechanisms of the photocatalytic degradation of HCHO, NH₃ and VOCs were also discussed.     

Simultaneous localization and mapping of autonomous underwater vehicle using looking forward sonar

A method of underwater simultaneous localization and mapping (SLAM) based on on-board looking forward sonar is proposed. The real-time data flow is obtained to form the underwater acoustic images and these images are pre-processed and positions of objects are extracted for SLAM. Extended Kalman filter (EKF) is selected as the kernel approach to enable the underwater vehicle to construct a feature map, and the EKF can locate the underwater vehicle through the map. In order to improve the association efficiency, a novel association method based on ant colony algorithm is introduced. Results obtained on simulation data and real acoustic vision data in tank are displayed and discussed. The proposed method maintains better association efficiency and reduces navigation error, and is effective and feasible.     

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通行能力预测是公路设施规划、设计与运营中的基础环节.本文基于埃及曼努菲亚省12条农村双车道路段数据,研究了公路线形等几何特征对通行能力的影响以及线形由切线变为平曲线时通行能力的损失.所选取的路段线形包括直线和随后的平曲线.同时,采集了各路段上车流量及速度数据,利用基于基本图的外推法研究流量和密度关系.路段上不同车型的车辆均转换为小客车当量.此外,针对不同情形（切线、平曲线及对应流量损失）,分别建立了最佳回归模型.结果表明,切线型道路的关键自变量是路宽、肩宽以及切线长;平曲线道路的关键变量是曲线半径和路宽.通行能力和几何特征关系最佳模型的自变量为曲线半径.本文的模型可用于分析评价农村双车道道路的通行能力,尤其是评价文中所研究路段的通行能力.