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
Mugerauer, Robert. (2016). Anthropotechnology: Sloterdijk on Environmental Design and the Foamworlds of Co-Isolation. Architecture And Culture, 4(2), 227 – 248.
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Abstract
The paper has two primary goals. The first is to reexamine the dynamics of cultural change by applying the innovative interpretations of German theorist and cultural historian Peter Sloterdijk, who contends that the ways we traditionally have made and understood our built environment are grossly inadequate in our contemporary media-saturated, war-weary, biotechnological world. The second is to show how such a reinterpretation of space, architecture, and culture could help us to learn to design better and act by way of an anthropotechnology (Sloterdijk's word) that is simultaneously developmental and threatening - that might enable us to find an orientation in a world of complexity, and thus more positively shape our lives and future world. Sloterdijk's intriguing concepts - spheres of immunization (bubbles, globes, foams), co-isolation, dyads, tensegrity - hold great promise for the next pulse of architectural, planning, and construction theory.
Keywords
Peter Sloterdijk; Anthropotechnology; Spheres Of Immunization (bubbles, Globes, Foams); Co-isolation; Housing
Park, Hyoungbae; Kim, Kyeongseok; Kim, Yong-woo; Kim, Hyoungkwan. (2017). Stakeholder Management in Long-Term Complex Megaconstruction Projects: The Saemangeum Project. Journal Of Management In Engineering, 33(4).
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Abstract
This paper identifies 31 critical success factors (CSFs) and suggests a framework for effective stakeholder management in long-term complex megaconstruction (LCM) projects that require more than 10 years for multipurpose development. The results of a survey on the prioritization of these 31 CSFs reveal that LCM projects involve more stakeholders than do general construction projects and require a correspondingly wider range of changes during each project. To identify more systematic and strategic approaches to stakeholder management in LCM projects, a framework was developed through factor analysis and focus-group interviews with project management experts. The framework is composed of the following five agendas: clear understanding of stakeholders, clear definition of the project, effective communication, responding to environmental changes, and social cooperation. The analysis results show that LCM projects require a stronger emphasis on responding to environmental changes and social cooperation. These results, along with the CSF priorities, reveal the necessity of taking customized approaches to LCM projects. The results of this analysis are expected to help LCM project managers effectively manage stakeholders. (C) 2017 American Society of Civil Engineers.
Keywords
Construction; Environmental Management; Project Management; Strategic Planning; Social Cooperation; Environmental Changes; Strategic Approaches; Construction Projects; Saemangeum Project; Long-term Complex Megaconstruction Projects; Stakeholder Management; Critical Success Factors (csfs); Long-term Complex Megaconstruction (lcm) Projects
Mahankali, Ranjeeth; Johnson, Brian R.; Anderson, Alex T. (2018). Deep Learning in Design Workflows: The Elusive Design Pixel. International Journal Of Architectural Computing, 16(4), 328 – 340.
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Abstract
The recent wave of developments and research in the field of deep learning and artificial intelligence is causing the border between the intuitive and deterministic domains to be redrawn, especially in computer vision and natural language processing. As designers frequently invoke vision and language in the context of design, this article takes a step back to ask if deep learning's capabilities might be applied to design workflows, especially in architecture. In addition to addressing this general question, the article discusses one of several prototypes, BIMToVec, developed to examine the use of deep learning in design. It employs techniques like those used in natural language processing to interpret building information models. The article also proposes a homogeneous data format, provisionally called a design pixel, which can store design information as spatial-semantic maps. This would make designers' intuitive thoughts more accessible to deep learning algorithms while also allowing designers to communicate abstractly with design software.
Keywords
Associative Logic; Creative Processes; Deep Learning; Embedding Vectors; Bimtovec; Homogeneous Design Data Format; Design Pixel; Idea Persistence
Kang, Mingyu; Moudon, Anne Vernez; Kim, Haena; Boyle, Linda Ng. (2019). Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS. International Journal Of Environmental Research And Public Health, 16(19).
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Abstract
Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a systematic and replicable protocol was developed in GIS (Geographic Information System) to create a consistent spatial unit of analysis for use in pedestrian crash modelling. Four publicly accessible datasets were used to identify unique intersection and non-intersection locations: Roadway intersection points, roadway lanes, legal speed limits, and pedestrian crash records. Two algorithms were developed and tested using five search radii (ranging from 20 to 100 m) to assess the protocol reliability. The algorithms, which were designed to identify crash-risk locations at intersection and non-intersection areas detected 87.2% of the pedestrian crash locations (r: 20 m). Agreement rates between algorithm results and the crash data were 94.1% for intersection and 98.0% for non-intersection locations, respectively. The buffer size of 20 m generally showed the highest performance in the analyses. The present protocol offered an efficient and reliable method to create spatial analysis units for pedestrian crash modeling. It provided researchers a cost-effective method to identify unique intersection and non-intersection locations. Additional search radii should be tested in future studies to refine the capture of crash-risk locations.
Keywords
Traffic Crash; Walking; Collisions; Accidents; Models; Pedestrian Safety; Spatial Autocorrelation; Algorithm
Cheng, Renée. (2020). Opinion: Change Agency, Value Change. Architect, 109(9), 20 – 20.
Keywords
Attitude Change (psychology); Air Flow; Hand Washing
Shang, Luming; Aziz, Ahmed M. Abdel. (2020). Stackelberg Game Theory-Based Optimization Model for Design of Payment Mechanism in Performance-Based PPPs. Journal Of Construction Engineering And Management, 146(4).
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Abstract
Payment mechanisms lie at the heart of public-private partnership (PPP) contracts. A good design of the payment mechanism should consider the owner's goals in the project, allocate risks appropriately to stakeholders, and assure satisfactory performance by providing reasonable compensation to the private developer. This paper proposes a Stackelberg game theory-based model to assist public agencies in designing payment mechanisms for PPP transportation projects. The interests of both public and private sectors are considered and reflected by a bilevel objective function. The model aims to search for solutions that maximize a project's overall performance for the sake of social welfare while simultaneously maximizing return for the sake of private investment. A variable elimination method and genetic algorithm are used to solve the optimization model. A case study based on a real PPP project is discussed to validate the effectiveness of the proposed model. The solutions provided by the model reveal that the optimal payment mechanism structure could be established such that it would satisfy owners' requirements for overall project performance while optimizing project total payments to contractors.
Keywords
Construction Industry; Contracts; Financial Management; Game Theory; Genetic Algorithms; Investment; Optimisation; Organisational Aspects; Project Management; Public Administration; Transportation; Public-private Partnership Contracts; Good Design; Private Developer; Stackelberg Game Theory-based Model; Ppp Transportation Projects; Public Sectors; Private Sectors; Private Investment; Ppp Project; Optimal Payment Mechanism Structure; Project Performance; Project Total Payments; Stackelberg Game Theory-based Optimization Model; Performance-based Ppps; Public-private Partnerships; Analytic Hierarchy Process; Weighted Sum Method; Multiobjective Optimization; Algorithm; Incentives; Projects; Network; Success; Branch
Wang, Lan; Zhang, Surong; Yang, Zilin; Zhao, Ziyu; Moudon, Anne Vernez; Feng, Huasen; Liang, Junhao; Sun, Wenyao; Cao, Buyang. (2021). What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic. Cities, 118.
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Abstract
Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases. In addition to confirming certain factors found in the existing literature, we uncover six new factors significantly associated with COVID-19 incidence. Furthermore, incidence during the lockdown is found to significantly affect incidence after the reopening, highlighting that timely quarantining and treating of patients is essential to avoid the snowballing transmission over time. These findings suggest ways to mitigate the negative effects of subsequent waves of the pandemic, such as special attention of infection prevention in neighborhoods with unsanitary and overcrowded housing, minimization of social activities organized by neighborhood associations, and contactless home delivery service of healthy food. Also worth noting is the need to provide support to people less capable of complying with the stay-at-home order because of their occupations or socio-economic disadvantage.
Keywords
Pandemics; Covid-19; Covid-19 Pandemic; Infection Prevention; Stay-at-home Orders; Structural Equation Modeling; United States; Communicable Disease Prevention; Influential Factors; Lockdown; Structural Equation Modeling (sem); Prevalence; Disease; Healthy Food; Social Activities; Counties; Neighborhoods; Housing; Built Environment; Prevention; Minimization; Socioeconomic Factors; Intervention; Health Care; Vulnerability; Occupations; Coronaviruses; Food Service; Disease Transmission; United States--us
Van Den Wymelenberg, Kevin; Inanici, Mehlika; Johnson, Peter. (2010). The Effect of Luminance Distribution Patterns on Occupant Preference in a Daylit Office Environment. Leukos, 7(2), 103 – 122.
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Abstract
New research in daylighting metrics and developments in validated digital High Dynamic Range (HDR) photography techniques suggest that luminance based lighting controls have the potential to provide occupant satisfaction and energy saving improvements over traditional illuminance based lighting controls. This paper studies occupant preference and acceptance of patterns of luminance using HDR imaging and a repeated measures design methodology in a daylit office environment. Three existing luminance threshold analysis methods [method1: predetermined absolute luminance threshold (for example, 2000 cd/m(2)), method2: scene based mean luminance threshold, and method3: task based mean luminance threshold] were studied along with additional candidate metrics for their ability to explain luminance variability of 18 participant assessments of 'preferred' and 'just disturbing' scenes under daylighting conditions. Per-pixel luminance data from each scene were used to calculate Daylighting Glare Probability (DGP), Daylight Glare Index (DGI), and other candidate metrics using these three luminance threshold analysis methods. Of the established methods, the most consistent and effective metrics to explain variability in subjective responses were found to be; mean luminance of the task (using method3; (adj)r(2) = 0.59), mean luminance of the entire scene (using method2; (adj)r(2) = 0.44), and DGP using 2000 cd/m(2) as a glare source identifier (using method1; (adj)r(2) = 0.41). Of the 150 candidate metrics tested, the most effective was the 'mean luminance of the glare sources', where the glare sources were identified as 7* the mean luminance of the task position ((adj)r(2) = 0.64). Furthermore, DGP consistently performed better than DGI, confirming previous findings. 'Preferred' scenes never had more than similar to 10 percent of the field of view (FOV) that exceeded 2000 cd/m(2). Standard deviation of the entire scene luminance also proved to be a good predictor of satisfaction with general visual appearance.
Keywords
Glare; Daylight Metrics; Luminance Based Lighting Controls; Discomfort Glare; Occupant Preference; High Dynamic Range
Gatti, U.; Migliaccio, G.; Bogus, S.M.; Priyadarshini, S.; Scharrer, A. (2013). Using Workforce’s Physiological Strain Monitoring to Enhance Social Sustainability of Construction. Journal Of Architectural Engineering, 19(3), 179 – 85.
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Abstract
Sustainability is often described in terms of the triple bottom line, which refers to its environmental, economic, and social dimensions. However, the economic and environmental impacts of decisions have been easier to determine than have been the social impacts. One area of social sustainability that is particularly applicable to construction projects is that of construction workforce safety and well-being. This is a critical part of sustainability, and a socially sustainable construction industry needs to consider the safety and well-being of construction workers. However, construction activities are generally physically demanding and performed in harsh environments. Monitoring workers' physical strain may be an important step toward enhancing the social sustainability of construction. Recently introduced physiological status monitors (PSMs) have overcome the past limitations, allowing physical strain to be monitored without hindering workers' activities. Three commercially available PSMs have been selected and tested to assess their reliability in monitoring a construction workforce during dynamic activities. The results show that two of the PSMs are suitable candidates for monitoring the physiological conditions of construction workers. A survey was also conducted among industry practitioners to gain insight into industry needs and challenges for physical strain monitoring.
Keywords
Construction Industry; Environmental Factors; Labour Resources; Occupational Safety; Socio-economic Effects; Sustainable Development; Workforce Physiological Strain Monitoring; Social Sustainability; Socioeconomic Impacts; Environmental Impacts; Social Impacts; Construction Projects; Construction Workforce Safety; Physical Strain