21 research outputs found
A comparative case study of coordination mechanisms in design and build BIM-based projects in the Netherlands
BIM implementation can affect the project coordination mechanisms in unexpected ways, even
in widely-applied project procurement structures. Apart from the chosen procurement approach, the
BIM technology and the distribution of roles in the project team influence and shape the project
coordination. This paper aims to explore the emerging coordination structures and processes from BIM
implementation in design-build procurement. An exploratory comparative case study has been undertaken.
The findings included two main coordination mechanisms: a centralized and decentralized structure and a
hierarchical ver-sus participative decision-making processes. These two patterns subsequently open a
debate about the rela-tions between BIM implementation and business models in AEC and particularly the
emergence of specialized all-around BIM firms versus BIM-knowledgeable engineering firms
Evaluations of BIM: Frameworks and perspectives
© ASCE 2014. This paper examines the evaluation of BIM-enabled projects. It provides a critical review of the three main areas of measurement, namely: technology, organization/people and process. Using two documented case studies of BIM implementation, the paper illustrates the benefits realized by project owners and contractors, and illustrates a lack of attention relative to contextual factors affecting the adoption and deployment of BIM. The paper has three main contributions. First, it identifies and discusses the lack of and difficulty surrounding standardized assessment methods for evaluating BIM-enabled projects. Second, it proposes a conceptual model that includes contextual attributes and demonstrates how the proposed framework reaches beyond simple evaluation to encompass the documentation of BIM's benefits, lessons learned, challenges and adopted solutions. Third, it shows how the framework can account for existing business processes, organizational process assets, and enterprise level factors. The paper aims to provide a conceptual basis for evaluation and a starting point for benchmarking
Evaluation of the chemical constituents and the antimicrobial activity of the volatile oil of Citrus reticulata fruit(Tangerine fruit peel) from South West Nigeria
The volatile oil of tangerine fruit (Citrus reticulata) was extracted by steam distillation and assessed for antibacterial and antioxidant activity. The volatile oil was tested against some Gram-negative organisms (Escherichia coli ATCC 35218, E. coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Salmonella paratyphi, Proteus mirabilis and Citrobacter spp); Gram-positive organisms such as Staphylococcus aureus ATCC 25923, S. aureus, Enterococcus faecalis and a fungus (Candida albicans). The minimum inhibitory concentration (MIC) was determined with concentrations of oil extract ranging from 0.87 to 445 mg/ml. Result of the study showed that the oil has a broad spectrum antibacterial activity. MIC recorded were S. aureus (0.74 mg/ml), S. aureus ATTC 25923 (2.46 mg/ml), E. faecalis (1.26 mg/ml), S. typhi (2.07 mg/ml), K. pneumoniae (0.56 mg/ml), E. coli ATTC 35218 (0.19 mg/ml), E. coli (1.95 mg/ml), P. aeruginosa (0.97 mg/ml), C. albicans (0.68 mg/ml). Antioxidant screening with 2,2-diphenyl-1-picrylhydrazyl (DPPH) was negative. Analysis of the chemical constituent by GC-MS showed the presence of D-limonene as the major constituent. Other constituents found were a-pinene and β-pinene
A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique
Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications
Managing building and civil engineering project claims to enhance organizational justice and reduce dispute
Annual Research Conference of the Royal Institution of Chartered Surveyors (COBRA
Understanding the skills shortages in the Australian construction industry: An exploratory study of the site management team
Annual Research Conference of the Royal Institution of Chartered Surveyors (COBRA
Conceptualizing and operationalizing team task interdependences: BIM implementation assessment using effort distribution analytics
Building Information Modelling (BIM) is a technological innovation currently at the forefront of digital transformation in the built environment. To achieve satisfactory outcomes with BIM, adopters need to find the most appropriate implementation strategy that is economically efficient. The research discussed here explores why and how distribution of effort spent on various tasks over project life cycle can be used as a metric for assessing and improving the performance of BIM implementation. Using quantitative data collected from a single in-depth case study of a BIM-enabled design and build project and subsequent interviews with three project actors and 11 BIM experts, to validate and triangulate the findings, we explore the use of effort data to analyze and visualize effort distribution patterns. The visualizations revealed the dynamics of team collaboration and task interdependences in BIM-enabled work and their impact on effort distribution. Lack of timely input by the contractor, subcontractors and suppliers influenced unusual patterns in the distribution of efforts indicating potential sources of inefficiency and unnecessary costs in the BIM process; thereby revealing the pivotal role of procurement structure and suggesting the need for timely involvement of key project participants. The contribution of this work is twofold. Methodologically, effort distribution analytics can provide insights that managers can use to improve BIM implementation process. Theoretically, the findings can be used to support informed decision-making, control cost, optimize resources, manage cash flow and to structure fees
Using PLS-SEM technique to model construction organizations' willingness to participate in e-bidding
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