Intercity travel demand : a utility-consistent simultaneous trip generation and mode choice model

An intercity travel decision includes a complex set of subdecisions, such as when to travel, where to travel, which mode to choose, and others. The main focus of this dissertation is to examine trip frequency and mode choice of intercity non-business travel. The objective of this study is to understand intercity travel behavior using disaggregate models. The proposed conceptual framework for intercity travel behavior leads to a nested logit/continuous choice model that is rigorously linked to the utility maximization theory. Compared to a traditional intercity travel demand model, the proposed model is utility consistent in that trip generation and mode choice models flow from one utility function. Thus, the resultant model embodies the interrelationship of trip generation and mode choice. Applying the model to the NorthEast Corridor, the calibrated results show that trip generation of non-business travelers is interdependent with mode choice. The factors influencing mode choice may exert an impact on trip generation directly or indirectly

Simulation of cargo VOC emissions from petroleum tankers in transit in Canadian waters

The emissions of volatile organic compounds (VOCs) from petroleum product tankers potentially represent a significant source of VOCs in port cities. Emission factors are used to estimate the produced VOCs. VOC emissions from transit operations were simulated using a two part model of heat and mass transfer. Using local meteorological data of air temperatures, solar radiation and wind speed, the heat transfer within the tank was modeled. Results showed that bulk cargo temperature remained relatively steady at 25–28°C, the oil surface oscillated diurnally by 1–2°C, and the deck temperature oscillates diurnally by 15–20°C. The solar insolation had the largest effect on the tank temperatures. VOC emissions for two crude oils and gasoline, two tank configurations, and two meteorological conditions were estimated using a model derived from a mass balance on the tank and the obtained temperature profile. Only 3 of 8 scenarios had pressure increases large enough to cause venting of VOC. C2-C5 compounds constituted the majority of VOCs released from crude oils and ethanol made up the majority of the VOCs released from the gasoline carrying barge. The calculated daily emission factors for crude oil and gasoline (barge) were 10 mg/L/day and 135 mg/L/day respectively

UNCERTAINTY QUANTIFICATION IN ENGINEERING OPTIMIZATION APPLICATIONS

Ph.DDOCTOR OF PHILOSOPH

Isolated angiitis of the central nervous system with tumor-like lesion, mimicking brain malignant glioma: a case report and review of the literature

<p>Abstract</p> <p>Background</p> <p>Isolated angiitis of the central nervous system (IACNS) is a rare but severe vascular disease, which could present like an isolated inflammatory lesion on magnetic resonance imaging (MRI). To date, only a few such cases with tumor-like IACNS have been reported.</p> <p>Case Presentation</p> <p>A 35-year-old woman presented with headache and left-sided weakness. MRI scans initially mislead us to a diagnosis of glioblastoma (GBM). Surgery was performed. The mass was sub-totally resected. Pathological examination confirmed a cerebral vasculitis. Radiological features, such as disproportionate mass effect, striped hemorrhage and abnormal enhancement of adjacent vessels, could be helpful to distinguish a tumor-like IACNS from a GBM. Single therapy with high doses of steroid did not improve the patient's condition. Combined therapy with prednisolone and cyclophosphamide showed great benefit to the patient. No relapse occurred during the period of 18 months follow-up.</p> <p>Conclusions</p> <p>Although a tumor-like IACNS has no established imaging features, a diagnosis of tumor-like IACNS should be suspected when MRI shows inappropriate presentations of a tumor. Greater awareness of this potential manifestation of IACNS may facilitate more prompt diagnosis and treatment.</p

Quantifying strange property of attractors in quasiperiodically forced systems

This work is supported by the National Natural Science Foundation of China (Nos. 11832009, 12002300, 12072291 and 12362002), and the Natural Science Foundation of Hebei Province, China (Grant No. A2021203013).Peer reviewedPostprin

CROLoss: Towards a Customizable Loss for Retrieval Models in Recommender Systems

In large-scale recommender systems, retrieving top N relevant candidates accurately with resource constrain is crucial. To evaluate the performance of such retrieval models, Recall@N, the frequency of positive samples being retrieved in the top N ranking, is widely used. However, most of the conventional loss functions for retrieval models such as softmax cross-entropy and pairwise comparison methods do not directly optimize Recall@N. Moreover, those conventional loss functions cannot be customized for the specific retrieval size N required by each application and thus may lead to sub-optimal performance. In this paper, we proposed the Customizable Recall@N Optimization Loss (CROLoss), a loss function that can directly optimize the Recall@N metrics and is customizable for different choices of N. This proposed CROLoss formulation defines a more generalized loss function space, covering most of the conventional loss functions as special cases. Furthermore, we develop the Lambda method, a gradient-based method that invites more flexibility and can further boost the system performance. We evaluate the proposed CROLoss on two public benchmark datasets. The results show that CROLoss achieves SOTA results over conventional loss functions for both datasets with various choices of retrieval size N. CROLoss has been deployed onto our online E-commerce advertising platform, where a fourteen-day online A/B test demonstrated that CROLoss contributes to a significant business revenue growth of 4.75%.Comment: 9 pages, 5 figures. Accepted by by CIKM 202