Author: Giuseppe Bruno
Abstract: Inter-modal transportation is based on the combined use of different modes of transport to move passengers and/or freights from their own origins to destinations. The integration of multiple transport resources can produce various benefits either from the point of view of the service efficiency (transportation time and costs) or considering the environmental impact (reduction of congestion, pollutant emissions, fuel consumptions).
In this context a crucial role in the efficiency of an inter-modal system is played by transfer nodes. In the case of passengers' transportation they are transit terminals where users can split line and/or modes of transport during their trips. In the field of freights' logistic they represent cross-docking terminals where inbound vehicles leaves materials that have to be loaded into outbound vehicles and delivered to various destinations with little or no storage in between.
Decisions about inter-modal terminals can rely on different time horizons. Determining the optimal position of a terminal is a typical planning problem, while mid-term management decisions concern the scheduling policies to be adopted in order to guarantee the system performance.
We illustrate a mathematical model which is able to describe the scheduling of vehicles at an inter-modal terminal in both the cases (passenger and freight transportation). The model is based on a time-space representation of the problem and its similarity to other combinatorial optimization models permit to provide results on its computational complexity.
We show different versions of the model in order to take into account specific constraints occurring during the operations. The presentation of computational results indicates the suitability of the models to solve real case studies.

Author: Winston Seah
Abstract: When a radio frequency (RF) signal propagates within a medium, it may be reflected, diffracted, and scattered. The human body comprises liquid, bone and flesh, which selectively absorb, reflect or scatter RF signals, leading to the phenomenon known as radio irregularity. Consequently, in the presence of human activity within a network, the radio irregularity phenomenon is seen as signal strength fluctuations at the receiver, and the degree of signal fluctuation exhibits a significant level of correlation to the level of human activity in the network. With the proliferation of wireless communication devices, radio irregularity which has often been viewed as a problem can instead be exploited for automated people counting with minimal additional hardware and installation costs. We examine the related research on automated people counting with a focus on indoor use cases and then present our approach to indoor automated people counting based on the signal fluctuations arising from radio irregularity. This is followed by the discussion of the experimental study and the application of discriminant analysis to process the results obtained from tests carried out indoors within a building.

Author: Eva K. Lee
Abstract: Population monitoring is a process that begins soon after a radiation incident is reported and continues until all potentially affected people have been monitored and evaluated for: 1) needed medical treatment, 2) the presence of radioactive contamination on the body or clothing, 3) the intake of radioactive materials into the body, 4) the removal of external or internal contamination (decontamination), 5) the radiation dose received and the immediate health risk from the exposure, and 6) long-term health effects. Population monitoring (including people and their pets) is accomplished locally and is the responsibility of state, local, and tribal governments.
The challenges of population monitoring especially in the first few days after a radiation incident are daunting. They are compounded by the fact that many critical components of monitoring should be put in place in the first few hours, before the arrival of federal assets that might be used to assist in the monitoring efforts. In this talk, we will discuss practical considerations for operating a community reception center, and a decision-support software system that can be used for optimizing design of community reception centers, building on the established infrastructure and planning of state and local public health departments throughout the country. The system allows the determination of appropriate layout of screening centers, estimates and optimizes the necessary staffing needs, and provides insight on process flows and optimal throughput that the operations can support. It optimizes the operations efficiency and throughput under limited resources (labor and time). And it allows users users to analyze the risks of radiation contamination spread and determine mitigation strategies. This work is joint with CDC NCEH/EHHE/Radiation Studies Branch Dr. Armin Ansari and Kevin Casper.

Authors: Xiaowen Fu, Tae Hoon Oum, and Jia Yan
Abstract: Major industry and policy changes are taking place in the Japan’s inter-city travel market. This study empirically estimates the air-rail travel demand model with aggregate OD market data. The estimated model is then used to estimate the effects of introducing super high speed rail (HSR), and alternative levels of CO2 emission taxation on the demands for airline and HSR modes. Our key findings are: (a) In Japanese consumers mind there is a substantial product differentiation between air and rail travel modes; (b) Japanese consumers are moderately sensitive to price while being highly sensitive to travel time and frequency of services; (c) The estimated average value of travel time is $42 per hour while the estimated value of airline frequency is about $2 per weekly departure per passenger; (d) The proposed Tokyo-Osaka superconducting maglev HSR services would drive airlines out of business while stimulating substantial new traffic in that market; and (e) CO2 emission taxation would have a moderate but significant impact on modal shift from air to HSR mode.

Author: Xiaowen Fu
Abstract: Demand uncertainty is routinely discussed and evaluated in practical airport planning. However, economic investigations on airport capacity choice have rarely modeled such uncertainty. The implication of such simplification is unknown, and the impacts to related airport planning strategies have not been formally studied. This presentation will report major findings from our economic modeling works concerning (1) the effects of demand uncertainty on capacity choices for airports of alternative ownership forms. (2) circumstances under which expected / average demand forecast can be used without distorting optimal capacity decisions. (3) the application of real options in airport planning. Managerial implications and future studies are discussed at the end of the presentation.