加强行车组织管理提高机车运用效率

在机车运用效率指标体系的基础上,加强行车组织管理,合理调配运用机车,提出提高机车运用效率的有效措施。     

仿真技术在物流配送中的实际应用

为了使物流配送成本降低到最少,现利用仿真技术（extendsim6.0版）来实现物流配送作业中资源的合理利用和优化,从而降低作业成本。通过建立仿真模型,并多次的运行后输出数据,如：平均队长（Ave length）、平均等待时间（AveWait）以及每个资源的有效利用率（Utilization）。对以上数据进行分析和研究进而设计出最优的资源利用及合理分配的方案。     

浅谈技术性贸易壁垒的影响及对策

技术壁垒是当前国际贸易中最突出的非关税壁垒之一,也是近年我国出口贸易中面临的重要挑战。在对技术壁垒影响机制的静态和动态、短期和长期分析的基础上．得到应对技术壁垒的启示：我国应建立预警机制,出口企业要实施“以质取胜”战略,重视贸易对象国的产品认证要求．积极申请相应产品认证充分利用行业协会的作用,合理利用世界贸易组织《技术性贸易壁垒协议》等相关规则保护自身的合法权益。     

债券资本成本计算方法的改进

资本成本是财务决策的重要指标。本文阐述了资本成本的内涵及其特点,分析了现行债券资本成本计算方法的局限性。用等值平均法对费用进行调整,推导出了在不同情况下计算债券资本成本的正确公式。     

Multivariate time series analysis of traffic congestion measures in urban areas as they relate to socioeconomic indicators

Traffic congestion has significant adverse implications for the environment and economy. Many state and local transportation agencies have implemented traffic congestion management practices to alleviate the negative implications of urban traffic. One of the major drawbacks of traffic congestion management practices is that they do not account for socio-demographic and economic factors, which have a significant impact on traffic congestion. Understanding the influence of these factors is very crucial because they can help to communicate the system's performance management and target setting. Only a few studies analyzed the relationship between traffic conditions (e.g., traffic demand and vehicular traveling speed) with a limited number of socio-economic factors. Moreover, most of the existing models ignore the temporal and spatial autocorrelations of traffic congestion, which may significantly limit their reliability and effectiveness. This study is developed with the purpose of identifying the most relevant external factors that affect traffic congestion performance measures. To conduct the research, we have used three urban congestion performance measures collected from 51 metropolitan areas across the U.S. over a four-year period, 2013–2016: travel time index, planning time index, and congested hours. We have used multivariate time series models to account for the complex inter-relationships among the performance measures and socioeconomic factors to identify the most influential factors affecting system performance. We have finally developed predictive models to estimate the traffic congestion measures using these factors. The results of rigorous modeling show that the factors influencing the traffic congestion measures are monthly average daily traffic (MADT), the number of employed, rental vacancy rate, building permits, fuel price index, and Economic Conditions Index (ECI). The prediction models indicated that the effects of these factors are statistically significant and could be used to forecast future trends in three performance measures accurately.     

Hip‐hop and Urban Studies

How can urban studies research engage fruitfully with hip‐hop? This contribution responds to the essays by David Beer and Martin Lamotte on ‘street music’, urban ethnography and ghettoized communities. It discusses how a social science engagement with hip‐hop texts might differ from cultural studies approaches, and how the study of hip‐hop culture can contribute to social movements studies. The essay argues that academics can utilize this form of ‘urban’ culture in various ways when undertaking urban research, teaching urban studies and engaging a broader public in academic research.     

Economics of tourism investment in data scarce countries

Ex-ante economic impact analyses are required to demonstrate the development impact and viability of multilateral loans. These assessments are often performed under tight timelines, in data scarce environments and with limited opportunity for primary data collection. This paper develops a framework for assessing tourism interventions under these challenging conditions and evaluates a US$15 million tourism investment in Belize. This paper contributes to the literature by: (i) developing a generalizable approach to building economy-wide models in data scarce environments; (ii) generating realistic expectations of agent responses with quasi-contingent valuation and auto-regressive integrated moving average methods. Applying the first economy-wide model for Belize, results show that the investment would stimulate GDP by 3% and reduce unemployment from 12% to 10% by 2040.     

规则与统计相结合的中文新词识别研究

针对目前分词方法无法识别网络中不断出现的普通新词,设计了一种新的基于规则与统计相结合的分词方法。针对新词不同的构词模式特点,利用语言学的知识把新词识别问题分类细化,将单字串模式的新词和后缀串模式的新词作为本文的主要识别对象。对于单字串模式的候选新词,在使用内部词概率模型的基础上,通过分析候选新词的内部紧密结合度以及上下文环境依赖程度等特征信息,采用平均互信息和左右邻接信息熵相结合的方法进行识别;对于后缀模式的候选新词,通过大规模语料训练得到的噪声尾词典进行噪声串的过滤得到新词.     

信用会拉大“贫富差距”吗

在市场经济条件下,信用表现出嫌贫爱富的特征.任由信用工具在市场上自由投放,会产生在地域上和对不同社会阶层人群的投放量不均匀性,以至于成为拉大贫富差距的元凶之一.在我国的市场上,以地理上的胡焕庸线分界,已存在信用投放东高西低不均衡问题.信用投放不均匀不仅会拉大贫富差距,还致使信用弱势人群在知识、观念和行为上落后于时代,固化在较低的社会阶层,由此产生其他社会问题.     

Forecast performance of WASDE price projections for U.S. corn

We conduct a comprehensive evaluation of the season‐average price projections for U.S. corn as published by the U.S. Department of Agriculture's World Agricultural Supply and Demand Estimates (WASDE), an important issue given reduced resources and increased program scrutiny within the Federal Government. This study is the first in the literature to evaluate the WASDE corn projections relative to futures adjusted forecasts throughout the forecasting cycle using a lengthy evaluation period (1980/81–2012/13). We find that WASDE projections provide lower RMSEs relative to futures adjusted forecasts for 9 of the 16 forecast periods, 4 of which are statistically different. Encompassing tests show that WASDE projections often provide incremental information not present in the futures adjusted forecasts. Composite forecasts based on futures adjusted forecasts and WASDE projections reduced the RMSEs over all forecast periods by an average 12–16%. Favorable average trading profits may be generated for some forecast months using WASDE projections. Overall, our results suggest that WASDE projections of the U.S. corn season‐average price provide useful information to the market and could enhance the efficiency of the agricultural sector.