Lin, Xiongbin; Maclachlan, Ian; Ren, Ting; Sun, Feiyang. (2019). Quantifying Economic Effects of Transportation Investment Considering Spatiotemporal Heterogeneity in China: A Spatial Panel Data Model Perspective. The Annals Of Regional Science, 63(3), 437 – 459.
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Abstract
Transportation investment plays a significant role in promoting economic development. However, in what scenario and to what extent transportation investment can stimulate economic growth still remains debatable. For developing countries undergoing rapid urbanization, answering these questions is necessary for evaluating proposals and determining investment plans, especially considering the heterogeneity of spatiotemporal conditions. Current literature lacks systematical research to consider the impacts of panel data and spatial correlation issue in examining the economic effects of transportation investment. To fill this gap, this study collects provincial panel data in China from 1997 to 2015 to evaluate multi-level temporal and spatial effects of transportation investment on economic growth by using spatial panel data analysis. Results show that transportation investment leads to significant and positive effects on growth and spatial concentration of economic activities, but these results vary significantly depending on the temporal and spatial characteristics of each province. The economic impacts of transportation investment are quite positive even considering the time lag effects. This study suggests that both central and local governments should carefully evaluate the multifaceted economic effects of transportation investment, such as a balanced transportation investment and economic development between growing and lagging regions, and considering the spatiotemporal heterogeneity of the economic environment.
Keywords
High-speed Rail; Infrastructure Investment; Causal Relationship; Empirical-analysis; Growth; Impact; Productivity; Efficiency; Spillover; Agglomeration; C33; R40; R58; Spatial Analysis; Time Lag; Urbanization; Transportation; Heterogeneity; Economic Growth; Economic Models; Economic Impact; Data Analysis; Spatial Data; Panel Data; Economic Development; Developing Countries--ldcs; Investments; Economic Analysis; Investment; Local Government; China
Shang-hsien Hsieh; Ken-yu Lin; Nai-wen Chi; Hsien-tang Lin. (2015). Domain Knowledge-Based Information Retrieval for Engineering Technical Documents. Ontology In The AEC Industry. A Decade Of Research And Development In Architecture, Engineering And Construction, chapter 1.
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Abstract
Technical documents with complicated structures are often produced in architecture/engineering/construction (AEC) projects and research. Information retrieval (IR) techniques provide a possible solution for managing the ever-growing volume and contexts of the knowledge embedded in these technical documents. However, applying a general-purpose search engine to a domain-specific technical document collection often produces unsatisfactory results. To address this problem, we research the development of a novel IR system based on passage retrieval techniques. The system employs domain knowledge to assist passage partitioning and supports an interactive concept-based expanded IR for technical documents in an engineering field. The engineering domain selected in this case is earthquake engineering, although the technologies developed and employed by the system should be generally applicable to many other engineering domains that use technical documents with similar characteristics. We carry out the research in a three-step process. In the first step, since the final output of this research is an IR system, as a prerequisite, we created a reference collection which includes 111 earthquake engineering technical documents from Taiwan's National Center for Research on Earthquake Engineering. With this collection, the effectiveness of the IR system can be further evaluated onceit is developed. In the second step, the research focuses on creating a base domain ontology using an earthquake-engineering handbook to represent the domain knowledge and to support the target IR system with the knowledge. In step three, the research focuses on the semantic querying and retrieval mechanisms and develops the OntoPassage approach to help with the mechanisms. The OntoPassage approach partitions a document into smaller passages, each with around 300 terms, according to the main concepts in the document. This approach is then used to implement the target domain knowledge-based IR system that allows users to interact with the system and perform concept-based query expansions. The results show that the proposed domain knowledge-based IR system can achieve not only an effective IR but also inform search engine users with a clear knowledge representation.
Keywords
Architecture; Construction; Engineering; Knowledge Based Systems; Ontologies (artificial Intelligence); Query Processing; Search Engines; Knowledge Representation; Concept-based Query Expansions; Base Domain Ontology; Earthquake Engineering; General-purpose Search Engine; Aec Projects; Architecture/engineering/construction Projects; Complicated Structures; Technical Documents; Domain Knowledge-based Information Retrieval
Lindell, Michael K.; House, Donald H.; Gestring, Jordan; Wu, Hao-Che. (2019). A Tutorial on Dynasearch: A Web-Based System for Collecting Process-Tracing Data in Dynamic Decision Tasks. Behavior Research Methods, 51(6), 2646 – 2660.
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Abstract
This tutorial describes DynaSearch, a Web-based system that supports process-tracing experiments on coupled-system dynamic decision-making tasks. A major need in these tasks is to examine the process by which decision makers search over a succession of situation reports for the information they need in order to make response decisions. DynaSearch provides researchers with the ability to construct and administer Web-based experiments containing both between- and within-subjects factors. Information search pages record participants' acquisition of verbal, numeric, and graphic information. Questionnaire pages query participants' recall of information, inferences from that information, and decisions about appropriate response actions. Experimenters can access this information in an online viewer to verify satisfactory task completion and can download the data in comma-separated text files that can be imported into statistical analysis packages.
Keywords
Downloading; Text Files; Tasks; Access To Information; Statistics; Dynamic Decision Making; Process Tracing; Web-based Experiments; Information Search; Human-behavior; Eye-tracking; Choice; Expectations; Strategies; Mousetrap; Software; Time
Launching the Inspire Fund: An early step for CBE’s Office of Research “For a small college, CBE has a broad range of research paradigms, from history and arts, to social science and engineering.” — Carrie Sturts Dossick, Associate Dean of Research Upon taking on the role of Associate Dean of Research, Carrie Sturts Dossick, professor in the Department of Construction Management, undertook listening sessions to learn about the research needs of faculty, staff and students across the College of Built…
I am interested in developing analysis methods and metrics for accurate daylight analysis. More concretely, I would like to work on developing color accurate sky models through analyzing HDR photographs, and to integrate it to annual daylight simulation method. Additionally, I am also interested in integration of daylight simulation in environmental design.
Julie Kriegh, researcher with the Carbon Leadership Forum and other CBE research centers, and owner of Kriegh Architecture Studios, collaborated with other CBE faculty and external partners to lead a UW CBE studio course in collaboration with Google that developed and delivered a design proposal for a sustainable data center. CBE collaborators included Hyun Woo “Chris” Lee, P.D. Koon Professorship in Construction Management; Jan Whittington, Associate Professor of the Department of Urban Design and Planning, and Director of the Urban…
Sustainable transportation, travel behavior, GIS, geospatial big data
Urban systems, system complexity, big data, artificial intelligence, smart cities, communities, and coupled human-built-environmental systems
Emerging transportation technologies, shared mobility and land use, interaction between human mobility based on shared vehicles and urban land uses. Spatio-temporal analysis and big data. Smart visualization methods
Research interests: Smart cities and transportation systems, Digital transformation, Travel behavior, and Sustainable development