Face recognition via adaptive image combination

Dimension reduction and manifold learning are the two most popular feature extraction methods. The two methods focus on spatial locality as a guiding principle to find a low-dimensional basis for describing high-dimensional data, but no bases or features are more spatially localized than the original image pixels. So, adaptive image combination is presented to represent a class by a combined sample. The combined sample is a linear combination of original samples in the same class. Adaptive image combination (AIC) find the best combination coefficients by minimizing the intrapersonal distance and maximizing the interpersonal distance. Experimental results show that AIC is effective.     

Parameter transfer of common-metric attributes in choice analysis: implications for willingness to pay

There is a growing literature that promotes the presence of a mix of compensatory and semi-compensatory processing strategies in the way that individuals evaluate packages of attributes in real or hypothetical markets, and make choices. This paper proposes a specification for the utility form in a choice model to test if, given a pair of attributes with a common-metric (e.g., components of travel time or cost), the attribute with the dominating level defines the marginal (dis)utility that is assigned to both attributes. We refer to this processing strategy as a parameter transfer rule. We use a stated choice data set, in the context of car driving individuals choosing between tolled and non-tolled routes, to estimate a mixed logit model which incorporates the presence of the parameter transfer rule and the conventional fully compensatory rule, both existing up to a probability. We find that if this parameter transfer heuristic is part of the mix, the WTP is more than 30% higher, on average, than when only a fully compensatory rule is imposed. We also contrast the parameter transfer rule with other semi-compensatory heuristics which have been investigated in other papers, and show that the finding adds further support to the accumulating evidence that a semi-compensatory attribute processing rules tend to result in higher mean WTP estimates compared to the fully compensatory attribute processing rule.     

交通噪声环境影响及互动式规划环评的应对

交通噪声投诉已居各大城市居民投诉之首,但交通噪声污染治理仍处于"先污染后治理"的模式。合理的交通规划和城市土地使用规划是解决城市交通噪声污染问题的治本之道。然而目前城市规划的各个层次对交通噪声预防考虑不足。该文提出了与规划过程互动的规划环评程序和方法,以期得到噪声污染影响最小的城市规划用地布局方案和交通规划方案。     

隧道开挖中两种围护方式综合使用的探讨

该文以宁波火车南站地下车库连接隧道为例,探讨在复杂条件下隧道基坑围护设计碰到的一些问题及其对策,为同类问题提供参考。     

Model-based design of a variable nozzle turbocharger controller

Variable Nozzle Turbocharger (VNT) was invented to solve the problem of matching an ordinary turbocharger with an engine. VNT can harness exhaust energy more efficiently, enhance intake airflow response and reduce engine emissions, especially during transient operating conditions. The difficulty of VNT control lies in how to regulate the position of the nozzle at different engine working conditions. The control strategy designed in this study is a combination of a closed-loop feedback controller and an open-loop feed-forward controller. The gain-scheduled proportional-integral-derivative (PID) controller was implemented as the feedback controller to overcome the nonlinear characteristic. As it is difficult to tune the parameters of the gain-scheduled PID controller on an engine test bench, system identification was used to identify the plant model properties at different working points for a WP10 diesel engine on the test bench. The PID controller parameters were calculated based on the identified first-order-plus-dead-time (FOPDT) plant model. The joint simulation of the controller and the plant model was performed in Matlab/Simulink. The time-domain and frequency-domain performances of the entire system were evaluated. The designed VNT control system was verified with engine tests. The results indicated that the real boosting pressure traced the target boosting pressure well at different working conditions.     

The precautionary principle in maritime affairs

Since the 1980s, the precautionary principle has been drawing more and more international attention. This became particularly clear during the series of Conferences on the Protection of the North Sea, which addressed marine environmental protection, and initiated the application of the principle into maritime affairs. Although a unified concept of the precautionary principle is lacking, some typical formulations have been concluded in regional treaties and international documents, and components of the principle can be summarised (Part I and Part II). The precautionary principle has been adopted by international documents involving different fields of law of the sea, and been addressed by international courts and tribunals (Part III). While the precautionary principle is still not part of customary international law (Part IV), its increasing level of worldwide acceptance suggests that it will become a customary international law in the future.     

分配电箱冲击试验与数值仿真

冲击试验是舰用设备抗冲击特性研究的重要手段。对处于正常通电工作状态下的装有减振器的分配电箱进行冲击试验,采集加速度响应数据,通过处理,将其作为仿真研究的依据。利用有限元分析软件ANSYS计算分配电箱在实际冲击工况下的加速度响应,并与试验结果进行比较,分析造成两者差异的原因,总结分配电箱的抗冲击规律。     

Reliable sensor deployment for network traffic surveillance

New sensor technologies enable synthesis of disaggregated vehicle information from multiple locations. This paper proposes a reliable facility location model to optimize traffic surveillance benefit from synthesized sensor pairs (e.g., for travel time estimation) in addition to individual sensor flow coverage (e.g., for traffic volume statistics), while considering probabilistic sensor failures. Customized greedy and Lagrangian relaxation algorithms are proposed to solve this problem, and their performance is discussed. Numerical results show that the proposed algorithms solve the problem efficiently. We also discuss managerial insights on how optimal sensor deployment and surveillance benefits vary with surveillance objective and system parameters (such as sensor failure probabilities).     

Large-scale application of MILATRAS: case study of the Toronto transit network

This paper documents the efforts to operationalize the conceptual framework of MIcrosimulation Learning-based Approach to TRansit Assignment (MILATRAS) and its component models of departure time and path choices. It presents a large-scale real-world application, namely the multi-modal transit network of Toronto which is operated by the Toronto Transit Commission (TTC). This large-scale network is represented by over 500 branches with more than 10,000 stops. About 332,000 passenger-agents are modelled to represent the demand for the TTC in the AM peak period. A learning-based departure time and path choice model was adopted using the concept of mental models for the modelling of the transit assignment problem. The choice model parameters were calibrated such that the entropy of the simulated route loads was optimized with reference to the observed route loads, and validated with individual choices. A Parallel Genetic Algorithm engine was used for the parameter calibration process. The modelled route loads, based on the calibrated parameters, greatly approximate the distribution underlying the observed loads. 75% of the exact sequence of transfer point choices were correctly predicted by the off-stop/on-stop choice mechanism. The model predictability of the exact sequence of route transfers was about 60%. In this application, transit passengers were assumed to plan their transit trip based on their experience with the transportation network; with no prior (or perfect) knowledge of service performance.     

Simulating the impacts of household travel on greenhouse gas emissions,urban air quality,and population exposure

This paper establishes a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment, emission modelling, and air quality simulation. This provides agent-based output that allows vehicle emissions to be tracked back to individuals and households who are producing them. In addition, roadway emissions are dispersed and the resulting ambient air concentrations are linked with individual time-activity patterns in order to assess population exposure to air pollution. This framework is applied to evaluate the effects of a range of policy interventions and 2031 scenarios on the generation of vehicle emissions and greenhouse gases in the GTA. Results show that the predicted increase of approximately 2.6 million people and 1.3 million jobs in the region by 2031 compared to 2001 levels poses a major challenge in achieving meaningful reductions in GHGs and air pollution.