Promoting case indexing in case library learning: Effects of indexing prompts on self-explanation and problem solving

In case library learning, an instructional method that promotes case-based problem solving, learners often struggle with indexing cases. Poor case indexing may hamper retention and retrieval of cases, hindering the construction of mental libraries in learners. To address this issue, the authors developed two indexing prompt types, explanation-based and difference-based, and explored their effects on self-explanation and problem solving in case libraries. A total of 105 students across three sections of a career development course participated in the study. Each section was assigned to one of three conditions: explanation-based indexing, difference-based indexing and no indexing prompt. Both indexing prompts facilitated self-explanation, which elaborated corresponding aspects of cases on which the prompts mainly focused. In arguing for a solution, learners relied more heavily on domain knowledge regardless of prompt types. However, both indexing prompt groups outperformed the control group in rebuttals. The authors discussed the theoretical and practical implications of the study.     

Corpus Augmentation for Improving Neural Machine Translation

The translation quality of neural machine translation (NMT) systems depends largely on the quality of large-scale bilingual parallel corpora available. Research shows that under the condition of limited resources, the performance of NMT is greatly reduced, and a large amount of high-quality bilingual parallel data is needed to train a competitive translation model. However, not all languages have large-scale and high-quality bilingual corpus resources available. In these cases, improving the quality of the corpora has become the main focus to increase the accuracy of the NMT results. This paper proposes a new method to improve the quality of data by using data cleaning, data expansion, and other measures to expand the data at the word and sentence-level, thus improving the richness of the bilingual data. The long short-term memory (LSTM) language model is also used to ensure the smoothness of sentence construction in the process of sentence construction. At the same time, it uses a variety of processing methods to improve the quality of the bilingual data. Experiments using three standard test sets are conducted to validate the proposed method; the most advanced fairseq-transformer NMT system is used in the training. The results show that the proposed method has worked well on improving the translation results. Compared with the state-of-the-art methods, the BLEU value of our method is increased by 2.34 compared with that of the baseline.     

经济周期波动与工程项目投资机会选择

为准确把握工程项目投资的时机，在分析经济波动的周期性特点及表现出的繁荣、衰退、萧条和复苏等四个过程的基础上，研究了工程项目投资与经济波动的制约关系及经济周期波动的监测途径，指出工程项目投资的最佳时期应是经济波动处在底部且有复苏迹象的时期．     

从“有理说不清”到“有理说得清”的技术——《论辩巧智：有理说得清的技术》述评

对《论辩巧智：有理说得清的技术》及其作者作了概述，介绍了该书中论辩分析、论辩评价和论辩表达3个部分的主要内容。该书是作者多年来在好几个国家的多所大学授课的讲稿的基础上编写而成的。在许多方面，它不同于传统教科书，它是一部学术性著作，更是一部在诸多领域中实践性非常强的著作。     

下坂地导流泄洪洞洞线方案研究

下坂地工程是塔里木河流域近期综合治理中唯一的山区水库工程, 枢纽建筑物由拦河坝、导流泄洪洞、引水发电洞和电站厂房四部分组成。 文中介绍了下坂地水利枢纽导流泄洪洞工程洞线方案的设计论证,通过枢纽布置、技术设计、施工安排及技术经济等多方面综合论证和研究了不同洞线的方案确定问题。     

张家口市建设项目水资源论证工作存在问题及建议

通过张家口市建设项目水资源论证工作中农业、水利、电力、采掘、交通运输等不同行业存在的一些问题,并以某热电厂为例,笔者提出自己的建议,供同行们参考.     

山区小水电开发建设中进行水资源论证探讨

文章介绍了水电建设项目水资源论证的目的、原则,分析了山区小水电开发建设中水资源论证的主要内容。     

LLDPE装置粉料输送系统安全性论证

对中国石油大庆石化分公司线性低密度聚乙烯装置粉末输送系统进行了安全性论证。通过模拟装置的试验和现场测试,考察了粉末输送了粉末输送管线、粉末储仓在正常生产过程和模拟装置试验过程中产生的静电量、测试分析了粉料仓中电场强度、电位、可燃气体含量,对粉料输送管道内的最大电场强度和料仓内混合物的最小点火能进行了计算,并对危险性进行了理论和实际分析,对危险部位提出了改进意见和建议。     

Automatic generation of matter-of-opinion video documentaries

In this paper we describe a model for automatically generating video documentaries. This allows viewers to specify the subject and the point of view of the documentary to be generated. The domain is matter-of-opinion documentaries based on interviews. The model combines rhetorical presentation patterns used by documentary makers with a data-driven approach. Rhetorical presentation patterns provide the viewer with an engaging viewing experience, while a data-driven approach can be applied to growing media repositories. To date, the modeling of rhetoric has been achieved in a top-down manner using closed repositories, while data-driven generation approaches were unable to implement non-trivial rhetorical presentation patterns. We describe an implementation of our model in a system, Vox Populi, and apply it to an online documentary shot by a group of independent amateur documentarists.