Integrated Intermodal Network Design with Nonlinear Inter-Hub Movement Costs

In this research, transportation mode and load route selection problems are integrated with the hub location problem in a single mathematical formulation to find the optimal design of intermodal transportation networks. Economies of scale are modeled utilizing a stepwise function that relates the per container transportation cost to the amount of flow between two nodes. A heuristic method combining a genetic algorithm and the shortest path algorithm was developed to solve this integrated planning problem. Computational experiments were completed to evaluate the performance of the proposed heuristic for different problem instances. At the end, conclusions are presented and future research directions are discussed

Integrated Intermodal Logistics Network Design

Intermodal freight transportation uses at least two different transportation modes (e.g., truck, rail, ship, air) to move freight loads that are in the same transportation unit (e.g., a shipping container) from origin to destination without handling the goods themselves. The increasing shift to intermodal transportation and the growth of freight transportation demand have resulted in a higher demand for intermodal freight transportation that has been projected to grow even faster in the next few decades. Satisfying this emerging demand will require enhancing the capacity of current intermodal facilities or even the construction of new intermodal facilities. This research addresses the intermodal logistics network design problem which is one of the key strategic planning decisions related to intermodal transportation. To obtain the maximum performance of the intermodal logistics network, two relevant decisions corresponding to the route and mode selection for freight loads were integrated with the facility location problem within the integrated intermodal logistics network design (IILND) problem. To address the IILND problem, two mathematical formulations were developed. One considered making decisions about arcs of the network while the other considered making decisions about routes for origin-destination flows in the network. The arc-based formulation modeled the effect of consolidating freight loads at intermodal terminals on the transportation cost by a stepwise function that relates the per container transportation cost to the amount of flow between two nodes. A heuristic approach that combines a genetic algorithm and the shortest path algorithm was developed to efficiently obtain high quality solutions for the arc-based formulation. Unlike the arc-based formulation, the route-based formulation modeled the effect of consolidating different loads at intermodal terminals on the transportation cost and time using constant discount and delay factors, respectively. Moreover, a composite variable formulation was used for the route-based formulation to incorporate route feasibility constraints within the definition of the composites and avoid explicitly adding them to the model. These modifications reduced the number of variables and constraints significantly when compared to the arc-based formulation. Two solution approaches were developed to find optimal solutions for the route-based formulation, namely a decomposition-based search algorithm and an accelerated Bender’s decomposition method. Several sets of computational experiments were completed to evaluate the performance of the proposed mathematical formulations and solutions approaches. Finally, several general insights about the effects of design parameters on solution characteristics were obtained from the computational experiments and directions for future research were identified

Evaluation of Radicular Dentin Thickness of Danger Zone in Mandibular First Molars

Objective: Better understanding of the furcation anatomy may serve to decrease the risk of root perforation. The purpose of this study was to measure the thickness of root walls in the danger zone in mandibular first molars.Materials and Methods: The roots of 53 extracted human mandibular first molars were sectioned in the horizontal plane 4 mm below the orifice of the mesial and distal root canals.For each cut surface buccal, lingual, mesial, and distal thickness of the root wall wasmeasured. Mean values of the thickness at each location were calculated and compared by ANOVA and t-test.Results: The results showed that the mean thickness in the distal portion of the mesial root was smaller in comparison to all other portions of the roots (P<0.05) and this difference was statistically significant except for the mesial portion of the distal root (P=0.463). The mean thickness of radicular dentin at the distal aspect of mesial roots was 1.2 millimeter.Conclusion: Our study suggests that knowledge of the root dentin thickness in the danger zone is essential for preventing endodontic mishaps leading to failure

Anticipatory freight selection in intermodal long-haul round-trips

We consider the planning problem faced by Logistic Service Providers (LSPs) transporting freights periodically, using long-haul round-trips. In each round-trip, freights are delivered and picked up at different locations within one region. Freights have time-windows and become known gradually over time. Using probabilistic knowledge about future freights, the LSP’s objective is to minimize costs over a multi-period horizon. We propose a look-ahead planning method using Approximate Dynamic Programming. Experiments show that our approach reduces costs up to 25.5% compared to a single-period optimization approach. We provide managerial insights for several intermodal long-haul round-trips settings and provide directions for further research

Privacy-Preserving Approaches to Analyzing Sensitive Trajectory Data

© 2019 Soheila Ghane EzabadiThe evolution of smart devices and sensor-enabled vehicles has brought forward the capability of collecting large and rich datasets. The datasets provide unprecedented opportunities for devising the next generation of location-based decision systems. Analysing detailed continually updated information of a user's status such as location, speed and direction is vital in improving the safety, reliability, mobility and efficiency of any form of location-based services in smart cities. More generally, trajectory data is paramount for studying people's movement patterns, shopping behaviour and preferences (i.e., visited cafes, parks, and their sequence of points of interest). However, such fine-grained data raises significant concerns about the privacy of individuals, which in turn hinders the further development of next generation applications that benefit from trajectory data. Such data can reveal various sensitive information about individuals such as their home and workplace locations, whereabouts over time and health. Recent approaches to address such concerns use a strong privacy guarantee -- known as differential privacy. Their aim is to tackle a core privacy challenge: publishing modified datasets of individuals without compromising their privacy while not sacrificing the utility of the published data. However, the current approaches guaranteeing differential privacy are limited in scalability and utility for real applications which both are crucial for later usage or data analytics. In this thesis, we are concerned with publishing trajectory data which poses privacy risks due to its sequential nature. A key issue is that the known algorithms fail to preserve the utility of published trajectory data when perturbing it to satisfy differential privacy. Critical information of trajectory datasets such as total travel distances and frequent location patterns in trajectories cannot be fully preserved by the existing differentially private algorithms. This thesis investigates three research issues. First, it is known that simple histograms, which is widely studied under differential privacy, are insufficient to capture aggregated information for spatial data. Our first work shows how to use instead spatial histograms to provide accurate distribution of traffic counts with differential privacy guarantee. Spatial histograms must satisfy sequential constraints (spatial) and naively applying differential privacy can destroy sequential constraints. Our proposed algorithm computes new information about trajectory counts without destroying spatial constraints and hence, improves the utility of published data. We further refine the algorithm to improve the utility of the published data by incorporating the traffic distribution. Intuitively, dense regions gain more information about the trajectory counts compared to sparse regions. Since the density of different regions might be uneven, we need to directly use trajectory densities to accurately compute information about the trajectory distribution in the regions for efficiently scaling the added noise to ensure differential privacy. Spatial histogram data has limitations in terms of spatial queries. For example, we cannot ask queries such as ``how many trajectories start from location A and end at location B?''. To address this limitation, in our third work, instead of using count information from trajectories as in spatial histograms we use actual trajectory data. We introduce a graphical model to capture accurate statistics about the movement behaviours in trajectories. Using this model, our algorithm privately generates synthetic trajectories such that the noise is optimally added to capture the movement direction of a trajectory. Our algorithm preserves both the spatial and temporal information of trajectories in the generated dataset, requires less memory and computation than competing approaches, and preserves the properties of original trajectory data in terms of travelled distance, movement patterns and locations of interest. Our extensive theoretical and experimental analysis shows the significant improvement in the utility of published data generated by our algorithms

Integrated Intermodal Network Design with Nonlinear Inter-hub Movement Costs

Poster 1

Assessing the Capacity of the Pacific Northwest as an Intermodal Freight Transportation Hub

This project synthesizes information from multiple sources about the capacity of the Pacific Northwest region to handle intermodal freight transportation demand. The findings from this research are intended to be used as a framework to start a research program focusing on the planning decision making needs of stakeholders in the region. The major sources of information about intermodal capacity were published reports from different stakeholders, online resources, and information obtained through conversations with a small set of stakeholders. Information about the current and future demand for intermodal freight transportation in the region was obtained from the FAF3 database of the Federal Highway Administration (FHWA) and complemented by information available in published reports. The analysis of the current and future gap between capacity and demand for intermodal freight transportation was completed using the Strength, Weaknesses, Opportunities, and Threats (SWOT) approach to develop a more complete understanding of the factors affecting the development and expansion of intermodal freight transportation in the region. Although the accuracy of the quantitative data cannot be considered very high, general trends can be analyzed. Most of the intermodal freight flow in the region is containerized cargo that visits the main marine ports: Port of Seattle, Port of Tacoma, and at a smaller scale Port of Portland. Other port terminals that are able to handle intermodal freight flow exist in the region but represent a small portion of the total flow. Burlington Northern Santa Fe (BNSF) Railway and Union Pacific (UP) Railroad have dedicated intermodal terminals in the region providing service for truck-road intermodal transportation, and rail connectivity to marine ports is also available. An analysis of the difference between intermodal capacity and demand at an aggregate level indicates that the current infrastructure is able to handle the existing demand for containerized international freight flow in the region. However, different scenarios of demand growth show that if capacity expansion does not occur, the existing capacity will not be sufficient to satisfy the demand in the future. Main factors affecting the perception of stakeholders about the level of service and future expansion of intermodal freight transportation in the region include highway congestion in the major metropolitan areas, lack of other generators and receivers of intermodal freight flow, coordination between different stakeholders, and limited availability of ocean carriers providing service to the Port of Portland.Pacific Northwest Transportation Consortium Oregon State Universit

Risk of Obstructive Sleep Apnea in Pregnancy by STOP-BANG Questionnaire

Background and Objective: Obstructive Sleep Apnea Syndrome (OSAS) is common during pregnancy and is associated with adverse maternal and fetal outcomes, including hypertension, preeclampsia, and low birth weight; therefore, screening pregnant women is of particular importance. This study aimed to assess OSAS risk during pregnancy in women referring to health centers in Yazd city, Iran. Materials and Methods: In this cross-sectional study, 400 pregnant women, who referred to Yazd health centers in 2020, were included in the study. Data collection tools included a demographic form and the STOP-BANG questionnaire to determine OSAS risk. The data were analyzed in SPSS software (version 16) using descriptive and inferential statistics and considering the significance level of 0.05. Results: The mean scores of the participants' age and body mass index (BMI) were obtained at 28.44±5.74 years and 27.31±5.28 kg/m2, respectively. The frequency rates of diabetes and hypertension were 8% and 3.3%, respectively. It was found that 94.5% of the women were at low risk of OSAS, while 2.5% and 3% of them were at moderate and high risk, respectively. There was no association between diabetes and OSAS risk (P>0.05); however, a history of hypertension, BMI above 30 kg/m2, and age over 30 years were associated with increased OSAS risk and higher STOP-BANG score (P<0.05). Conclusion: The STOP-BANG questionnaire is a simple tool for screening OSAS in pregnant women. Age over 30, BMI over 30 kg/m2, and a history of hypertension were associated with higher STOP-BANG scores; therefore, pregnant women with these characteristics are at higher risk for developing OSAS and are a higher priority for screening than other groups

Maternal mortality in Yazd Province, Iran

Introduction: Five hundred thousand maternal deaths occur each year worldwide, many of which are in developing countries. The maternal mortality rate is a measure that demonstrates the degree of adequacy of prenatal care and of economic and social conditions. The aim of this study was to determine the frequency and causes of pregnancy-related mortality rates in Yazd Province. Methods: This cross-sectional study examined the maternal deaths related to pregnancy that were recorded in Yazd Province, Iran, from 2002 to 2011. All maternal deaths that occurred during pregnancy, during delivery, and 42 days after birth were analyzed in this study. The data were collected through a questionnaire, and both direct and indirect causes of maternal deaths were determined. Results: Forty pregnancy-related deaths occurred in this period, and the maternal mortality rate was 20.8 deaths per 100,000 live births. The mean age of death in the mothers in this study was 29.17. Fifty-five percent of women of the women who died delivered their babies by cesarean section, and only 20% of them delivered their babies vaginally. Bleeding was the most common cause of maternal mortality (30%), and it was associated directly with maternal mortality. Furthermore 20% of the mothers died due to heart disease and cardiac complications, which were associated indirectly with maternal mortality. Conclusion: Cesarean section and its complications were the main cause of death in many cases. Thus, providing a strategic plan to reduce the use of this procedure, educate mothers, and ensure adequate access to pre- maternal care and to care during pregnancy are the most important measures that can be taken to decrease the maternal mortality rate