The place of social impacts in the iterative assessment process: a case study of a highway project in the US State of Georgia

Social impact assessments (SIAs) were conducted in accordance with the National Environmental Policy Act (NEPA) process along the US 441 corridor in Clinch and Atkinson Counties, Georgia. The SIA approach consisted of both quantitative and participatory (public involvement) components. Successes in using this approach included: aligning the roadway with access and optimal benefits for the adjacent communities; support for the project despite the change it will bring to the region; improved relationships with the community, which previously had little trust in government; and, most important of all, education of the design engineers about community impacts.     

自然场景中三维植物的建模

三维植物建模是虚拟自然场景生成过程中的关键问题之一,而植物建模主要考虑分枝结构和叶子这两个重要因素.通过将曲线细分思想引入到上下文相关的L系统推导规则中,并改变传统的线性数组字符存储结构,提高了L系统分枝建模过程的真实感和计算效率;同时在植物叶子造型中采用轴变形方法和纹理映射技术,提高了植物叶子造型的真实感.在此基础上给出了改进的植物生长状态演化算法,并给出了实验算例.     

Weak Precedence Story Parsing Grammar

Story understanding is one of the important branches of natural language understanding research in AI techniques.The story understanding approach based on Story Parsing Grammar (SPG) involves that SPG is used to represent different abstracting processes of stories with different levels in story understanding and that the story understanding process is converted to the recognition process of stories using the syntactic parser of SPG.This kind of story understanding is called story parsing.In this paper,firstly a subclass of SPG,called Weak Precedence SPG(WPSPG),is defined.Afterwards the syntactic parsing algorithm of WPSPG is studied.An example of story parsing is also given.     

Efficient learning of multiple context-free languages with multidimensional substitutability from positive data

Recently Clark and Eyraud (2007) [10] have shown that substitutable context-free languages, which capture an aspect of natural language phenomena, are efficiently identifiable in the limit from positive data. Generalizing their work, this paper presents a polynomial-time learning algorithm for new subclasses of multiple context-free languages with variants of substitutability.     

Contextual heat island assessment for pavement preservation

Pavement preservation (PP) is a planned set of construction and material interventions that can extend the pavement’s service life and may also impact sustainability through Heat Island (HI) mitigation. The HI mitigation potential can vary from location-to-location and with time. For agencies to widely adopt the PP, it is necessary to quantify the benefits based on the context of the project. A method to calculate the Global Warming Potential (GWP) for the HI effect was developed and illustrated for four cities in the US: Chicago, Austin, San Diego and Philadelphia, for hypothetical pavements with three preservation options: chip seals, a concrete inlay, and an asphalt concrete inlay. The use phase GWP with respect to HI was estimated for all cases given a 2-, 5-, 7- or 10-year service life. Overall, the HI in the use phase was found to dominate the total GWP relative to the materials and construction phases. The HI GWP savings increase over time, with the 10-year savings being greatest for San Diego using the concrete inlay (22.5?kg CO₂-eq/m²) and smallest for Chicago with a chip seal (8.0?kg CO₂-eq/m²). The savings were found to increase in areas that have a more pronounced HI and could offset GWP in the other phases. The proposed method allows agencies to estimate HI GWP for a specific preservation strategy, location and service life.     

Extracting Hidden Context

Concept drift due to hidden changes in context complicates learning in many domains including financial prediction, medical diagnosis, and communication network performance. Existing machine learning approaches to this problem use an incremental learning, on-line paradigm. Batch, off-line learners tend to be ineffective in domains with hidden changes in context as they assume that the training set is homogeneous. An off-line, meta-learning approach for the identification of hidden context is presented. The new approach uses an existing batch learner and the process of contextual clustering to identify stable hidden contexts and the associated context specific, locally stable concepts. The approach is broadly applicable to the extraction of context reflected in time and spatial attributes. Several algorithms for the approach are presented and evaluated. A successful application of the approach to a complex flight simulator control task is also presented.     

扩展的分形L-系统与自然景观的动态模拟

介绍了L-系统的概念以及作图原理,在单规则作图机制的基础上,提出了伪L-系统的多规则产生式机制,同时把边长的随机性引入到L-系统中,得到了较为理想的自然景物。将上下文相关的L-系统在理论上进行了扩展,把控制参数引入其中之后,可以使图像按照既定的构想发生变化,得到了更加逼真的动态自然景观。     

面向对象程序的上下文敏感指针分析研究

指针分析是编译优化、程序静态分析中的基础,很多应用都需要基于指针分析,低精度的指针分析会给这些应用带来高误报率和漏报率,通过添加上下文敏感信息是提高指针分析的精度的一个重要手段.自从面向对象的概念被提出来之后,该概念得到了广泛的应用,Java、C++、.NET、C#等主流语言都支持面向对象的特性,面向对象程序的指针分析...     

快速公交道路综合敏感性设计理念应用技术初探

在大力发展公交的政策下快速发展起来的快速公交(Bus Rapid Transit,简称BRT)道路,除了要保证比传统公交更安全、更通畅,还要处理好与其他交通方式、与自然环境以及人文环境等方面的关系。美国等国家兴起的综合敏感性设计理念(CSD),强调设计中的灵活性,提倡项目实施过程中的多学科参与和公众参与,以达到安全、高效及自然人文环境保护之间的平衡。论文结合国内外已建成的快速公交体系应用案例,通过对道路综合敏感性理念在BRT道路设计中若干技术的初步研究,讨论了其部分设计要点,展示了其前景。     

The context-splittable normal form for Church–Rosser language systems

In this paper the context-splittable normal form for rewriting systems defining Church–Rosser languages is introduced. Context-splittable rewriting rules look like rules of context-sensitive grammars with swapped sides. To be more precise, they have the form uvw→uxw with u,v,w being words, v being nonempty and x being a single letter or the empty word. It is proved that this normal form can be achieved for each Church–Rosser language and that the construction is effective. Some interesting consequences of this characterization are given, too.