Optimizing the Long-Term Operating Plan of Railway Marshalling Station for Capacity Utilization Analysis

Not only is the operating plan the basis of organizing marshalling station’s operation, but it is also used to analyze in detail the capacity utilization of each facility in marshalling station. In this paper, a long-term operating plan is optimized mainly for capacity utilization analysis. Firstly, a model is developed to minimize railcars’ average staying time with the constraints of minimum time intervals, marshalling track capacity, and so forth. Secondly, an algorithm is designed to solve this model based on genetic algorithm (GA) and simulation method. It divides the plan of whole planning horizon into many subplans, and optimizes them with GA one by one in order to obtain a satisfactory plan with less computing time. Finally, some numeric examples are constructed to analyze (1) the convergence of the algorithm, (2) the effect of some algorithm parameters, and (3) the influence of arrival train flow on the algorithm

Crew Scheduling Considering both Crew Duty Time Difference and Cost on Urban Rail System

Urban rail crew scheduling problem is to allocate train services to crews based on a given train timetable while satisfying all the operational and contractual requirements. In this paper, we present a new mathematical programming model with the aim of minimizing both the related costs of crew duty and the variance of duty time spreads. In addition to iincorporating the commonly encountered crew scheduling constraints, it also takes into consideration the constraint of arranging crews having a meal in the specific meal period of one day rather than after a minimum continual service time. The proposed model is solved by an ant colony algorithm which is built based on the construction of ant travel network and the design of ant travel path choosing strategy. The performances of the model and the algorithm are evaluated by conducting case study on Changsha urban rail. The results indicate that the proposed method can obtain a satisfactory crew schedule for urban rails with a relatively small computational time

Analysis on the Risk and Supervision of P2P Online Financing Platforms in China

Microcredit is a vital breakthrough to solve the financial problems of low-income groups and small and medium-sized enterprises, while traditional microfinance providers can only meet a small proportion of their capital needs. By using internet technology, P2P online financing extends the innovative development of microcredit with the aim of solving traditional micro-credit problems. This paper mainly explores the existing online financing operation model of P2P in China, and summarizes the relevant problems, such as low entry barriers for P2P online financing enterprises and lack of supervision, Lack of verification on the qualification of borrowers and poor management of the platform, imperfect information revealed or providing false information by platform, etc. Finally, the article put forward some suggestions concerning the healthy development for the P2P online financing platform, including the establishing entry audit system and strengthening the supervision of the P2P platform, strengthening the management of borrowers and improving the credit collection system, and strengthening the disclosure of information by platform

Nonlinear Analysis of Auscultation Signals in TCM Using the Combination of Wavelet Packet Transform and Sample Entropy

Auscultation signals are nonstationary in nature. Wavelet packet transform (WPT) has currently become a very useful tool in analyzing nonstationary signals. Sample entropy (SampEn) has recently been proposed to act as a measurement for quantifying regularity and complexity of time series data. WPT and SampEn were combined in this paper to analyze auscultation signals in traditional Chinese medicine (TCM). SampEns for WPT coefficients were computed to quantify the signals from qi- and yin-deficient, as well as healthy, subjects. The complexity of the signal can be evaluated with this scheme in different time-frequency resolutions. First, the voice signals were decomposed into approximated and detailed WPT coefficients. Then, SampEn values for approximated and detailed coefficients were calculated. Finally, SampEn values with significant differences in the three kinds of samples were chosen as the feature parameters for the support vector machine to identify the three types of auscultation signals. The recognition accuracy rates were higher than 90%

High serum cortisol level is associated with increased risk of delirium after coronary artery bypass graft surgery: a prospective cohort study

Introduction: The pathophysiology of postoperative delirium remains poorly understood. The purpose of this study was to examine the relationship between serum cortisol level and occurrence of early postoperative delirium in patients undergoing coronary artery bypass graft (CABG) surgery. Methods: A total of 243 patients undergoing elective CABG surgery were enrolled. Patients were examined twice daily during the first five postoperative days and postoperative delirium was diagnosed by using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Blood samples were obtained between 7 a. m. and 8 a. m. on the first postoperative day and serum cortisol concentrations were then measured. Multivariate logistic regression analyses were performed to identify risk factors of postoperative delirium. Results: Postoperative delirium occurred in 50.6% (123 of 243) of patients. High serum cortisol level was significantly associated with increased risk of postoperative delirium (OR 3.091, 95% CI 1.763-5.418, P < 0.001). Other independent risk factors of postoperative delirium included increasing age (OR 1.111, 95% CI 1.065-1.159, P < 0.001), history of diabetes mellitus (OR 1.905, 95% CI 1.001-3.622, P = 0.049), prolonged duration of surgery (OR 1.360, 95% CI 1.010-1.831, P = 0.043), and occurrence of complications within the first day after surgery (OR 2.485, 95% CI 1.184-5.214, P = 0.016). Patients who developed postoperative delirium had a higher incidence of postoperative complications and a prolonged duration of postoperative ICU and hospital stay. Conclusions: Delirium was a common complication after CABG surgery. High serum cortisol level was associated with increased risk of postoperative delirium. Patients who developed delirium had outcomes worse than those who did not.Critical Care MedicineSCI(E)PubMed28ARTICLE6R2381

Time-Dependent Pricing for High-Speed Railway in China Based on Revenue Management

High-speed railway (HSR) is recognized as a green transportation mode with lower energy consumption and less pollution emission than other transportation. At present, China has the largest HSR network globally, but the maximum revenue of railway transportation corporations has not been realized. In order to make HSR achieve a favorable position within the fierce competition in the market, increase corporate revenue, and achieve the sustainable development of HSR and railway corporations, we introduce the concept of revenue management in HSR operations and propose an innovative model to optimize the price and seat allocation for HSR simultaneously. In the study, we formulate the optimization problem as a mixed-integer nonlinear programming (MINLP) model, which appropriately captures passengers&rsquo choice behavior. To reduce the computational complexity, we further transform the proposed MINLP model into an equivalent model. Finally, the effectiveness of both the proposed model and solution algorithm are tested and validated by numerical experiments. The research results show that the model can flexibly adjust the price and seat allocation of the corresponding ticketing period according to the passenger demand, and increase the total expected revenue by 5.92% without increasing the capacity. Document type: Articl

TikTalk: A Video-Based Dialogue Dataset for Multi-Modal Chitchat in Real World

To facilitate the research on intelligent and human-like chatbots with multi-modal context, we introduce a new video-based multi-modal dialogue dataset, called TikTalk. We collect 38K videos from a popular video-sharing platform, along with 367K conversations posted by users beneath them. Users engage in spontaneous conversations based on their multi-modal experiences from watching videos, which helps recreate real-world chitchat context. Compared to previous multi-modal dialogue datasets, the richer context types in TikTalk lead to more diverse conversations, but also increase the difficulty in capturing human interests from intricate multi-modal information to generate personalized responses. Moreover, external knowledge is more frequently evoked in our dataset. These facts reveal new challenges for multi-modal dialogue models. We quantitatively demonstrate the characteristics of TikTalk, propose a video-based multi-modal chitchat task, and evaluate several dialogue baselines. Experimental results indicate that the models incorporating large language models (LLM) can generate more diverse responses, while the model utilizing knowledge graphs to introduce external knowledge performs the best overall. Furthermore, no existing model can solve all the above challenges well. There is still a large room for future improvements, even for LLM with visual extensions. Our dataset is available at \url{https://ruc-aimind.github.io/projects/TikTalk/}.Comment: Accepted to ACM Multimedia 202

Spatiotemporal cluster patterns of hand, Foot, and mouth disease at the county level in Mainland China, 2008-2012

Background: Hand, foot, and mouth disease (HFMD) is known to be a highly contagious childhood illness. In recent years, the number of reported cases of HFMD has significantly increased in mainland China. This study aims at the epidemiological features, spatiotemporal patterns of HMFD at the county/district level in mainland China. Methods: Data on reported HFMD cases for each county from 1 January 2008 to 31 December 2012 were obtained from the Chinese Center for Disease Control and Prevention. Cluster analysis, spatial autocorrelation, and retrospective scan methods were used to explore the spatiotemporal patterns of the disease. Results: The annual incidences varied greatly among the counties, ranging from 0 to 74.31‰with the median of 5.42‰ (interquartile range: 1.54‰–13.55‰) during 2008–2012 in mainland China. Counties close to provincial capital cities generally had higher incidences than rural counties. A seasonal distribution was observed between the northern and southern China, of which dual epidemic were shown in southern China and usually only one in northern China. Based on the global and local spatial autocorrelation analysis, we found that the spatial distribution of HFMD was presented a significant clustering pattern for each year (P Conclusions: The spatiotemporal clustering areas of the disease identified in this way were relatively stable, and imminent public health planning and resource allocation should be focused within those areas