1,720,988 research outputs found
Integrated Approach to Construction Risk Management: Cost Implications
No full textManaging risk in construction projects has proven to be a challenge for many project managers and stakeholders involved in projects. The lack of a systematic approach and standardized processes are key factors influencing improper risk management techniques. This research introduces a new model to evaluate and assess risk in terms of cost impact, utilizing a fuzzy Monte Carlo simulation approach for the first time. The method consists of ranking the top risks using a fuzzy logic system utilized in an objective manner by setting criteria for experts to rank the risk based on cost impact and probability to reduce human biases, then evaluating their cost impact through a Monte Carlo simulation both pre- and postmitigation. This work proposes a new strategy to elicit risk for construction projects based on risk cost impact, project type, project location, project contract type, and project delivery method. Based on the findings, implementation of a risk mitigation response plan can decrease the project cost remarkably. This model proved to be beneficial in forecasting risk impact when executed on a commercial construction project in California. This model can be applied as a general tool for risk mitigation processes for the construction industry
CLASSIFICATION OF CONSTRUCTION FIRMS BASED ON BIM ROLES AND BIM LEVELS USING MACHINE LEARNING TECHNIQUES
Full text linkApplication of Building Information Modelling (BIM) within the AEC industry has been evolving. With new developments and increasing capabilities, BIM is reshaping the design, construction, and operation, and maintenance processes and revolutionizing the entire functions of building life cycles. To maximize BIM benefits and take advantage of its capabilities, it is imperative that project stakeholders define specific roles and responsibilities within projects; to employ professionals with high levels of BIM proficiency, expertise, and knowledge. This study aims to classify the construction firms into different clusters based on their BIM capabilities, implementation, BIM levels, and type of BIM roles they employ for construction projects. It will further predict and classify BIM levels at company level according to its usage. The methodology was based on a survey design which consisted of application an online questionnaire that was distributed to AEC professionals in the industry. 61 suitable responses were analysed, using different supervised and unsupervised machine learning algorithms, including Cluster Analysis, K-Nearest Neighbours algorithm (k-NN), Random Forest, and Gradient Boosting. The findings showed most firms were not applying BIM on their projects and the majority of those that did were not utilizing it in its full potential. Firms were further classified in terms of BIM levels and types of BIM applications they utilize on construction projects. The results showed that Random Forest had the highest performance and the most accuracy, comparing with KNN and Gradient Boosting, even though the performance and predictions results produced by all models were in proximity of one another
BIM feasibility for small and medium-sized contractors and subcontractors
No full textBIM adoption for SMEs is an imperative topic. It is assumed that construction contractors and subcontractors play a great part in adopting or neglecting an innovative technology due to different factors. We believe this reluctance attribute would be a common factor between these two groups of construction actors and it would further be an indication of sort of behavior these groups have in common. This study intends to make a major contribution to the body of knowledge by investigating BIM feasibility for SMEs. The research method consists of application of a structured online questionnaire distributed Online, out of which 70 responses from the industry were collected and analyzed. Inferential statistics, and hypothesis testing were applied to check the associations among categorical variables via Wilcoxon Signed Ranks Test and Mann-Whitney U Test. The factors between contractors and subcontractors in terms of organizational, technological, economic, and social attributes were compared. Further, contractors were grouped in terms of BIM and software usage, firm size, and partnership by Cluster Analysis. The results show the rankings for contractors were different from the rankings for subcontractors with respect to technological feasibility and the rankings of contractors were all higher than those of subcontractors when partnership was introduced as a differentiating variable
DEVELOPMENT OF A FRAMEWORK FOR PROCESSING UNSTRUCTURED TEXT DATASET THROUGH NLP IN COST ESTIMATION AEC SECTOR
Full text linkCost estimation is one of the most critical steps in the building construction process. Currently, it requires humans to manually extract information from documents written in natural language, often resulting in human error.
This paper aims to investigate an automated technique for extracting data from documents with the support of NLP techniques, in order to automatize the task of structuring information.
A framework for automatically classifying information from unstructured text was developed leveraging NER techniques. This research supports the cost estimation activity minimizing the loss of resources coming from human error when interpreting NL documents
Analysis of Existing Open Standard Framework and Ontologies in the Construction Sector for the Development of Inference Engines
No full textThe definition of shared dictionaries able to facilitate communication in the construction sector has been an open issue long since. The advent of ICT highlighted the existing issues imposing new challenges to allow the communication between systems. Nowadays, the digital transformation in the construction sector is led by Building Information Modelling. Several efforts have been spent both in research and industry developing open standards like the industry foundation classes and related ontologies to empower interoperability. However, this paper highlights the obstacles limiting use and exchange of information at the state of the art
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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