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COMPUTER SCIENCE (1202 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 20)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 28)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 14)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 9)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 15)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 6)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 5)
ACM Transactions on Economics and Computation     Hybrid Journal   (Followers: 1)
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 31)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 28)
Advanced Science Letters     Full-text available via subscription   (Followers: 10)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 4)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Computer Science : an International Journal     Open Access   (Followers: 14)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 54)
Advances in Engineering Software     Hybrid Journal   (Followers: 28)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 14)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Human-Computer Interaction     Open Access   (Followers: 20)
Advances in Materials Science     Open Access   (Followers: 14)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 49)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 6)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 9)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal  
Air, Soil & Water Research     Open Access   (Followers: 12)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 5)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 12)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 3)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 8)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 12)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 34)
Applied Medical Informatics     Open Access   (Followers: 10)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 146)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 8)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal   (Followers: 1)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 5)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 12)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 53)
Big Data and Cognitive Computing     Open Access   (Followers: 2)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 304)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 21)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 37)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 48)
British Journal of Educational Technology     Hybrid Journal   (Followers: 144)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 15)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 22)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 2)
Communications in Information Science and Management Engineering     Open Access   (Followers: 4)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 51)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 17)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 30)
Computer     Full-text available via subscription   (Followers: 98)
Computer Aided Surgery     Open Access   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 16)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 24)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)

        1 2 3 4 5 6 7 | Last

Journal Cover
Automation in Construction
Journal Prestige (SJR): 1.613
Citation Impact (citeScore): 5
Number of Followers: 6  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0926-5805
Published by Elsevier Homepage  [3161 journals]
  • Thrust force allocation method for shield tunneling machines under complex
           load conditions
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Kai Guo, Yapeng Xu, Jianfeng LiAbstractThrust system is one of the most important subsystems in the shield tunneling machines. Multiple hydraulic cylinders in the thrust system provide the required thrust force and help to overcome the large load torque in the excavating process, which is a typical over-actuated mechanical system. Therefore, load distribution among thrust cylinders will be uneven in the face of large load torques, which is the primary cause of cracks in lining segments. To handle this problem, most of the existing works focus on thrust system layout optimization for a predetermined geological condition. Consequently, the optimization results cannot adapt to varying thrust load conditions. We aim to provide a more flexible solution for this problem by using a reconfiguration strategy based on a force-on-off principle, which can dynamically determine whether a cylinder in the thrust system outputs force or not. Illustrative examples show that the reconfigurable thrust system ensures more even force distribution among thrust cylinders under varying thrust load conditions compared with the traditional thrust system and does not require extra hardware cost, which verifies the flexibility and effectiveness of the proposed method.
  • Active control of a rod-net formwork system prototype
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): A. Liew, Y.R. Stürz, S. Guillaume, T. Van Mele, R.S. Smith, P. BlockAbstractA prototype rod-net for a fabric formwork system is described, including the fabrication, control of the geometry via turnbuckles, and the measurement of nodal co-ordinates via an image-based theodolite system. Such a net and fabric formwork system consists of a network of tie elements, either discrete or continuous, forming the main falsework structure, onto which is placed a fabric membrane acting as the flexible formwork for the pouring of wet concrete for the forming of a concrete shell. The fabrication of the plastic and steel net components of the prototype is described in detail, including the arrangement of the nodes, rods and boundary conditions. A control system was developed to determine the necessary adjustments at the boundary elements to move the rod-net to a target geometry to eliminate deviations that may arise from fabrication and construction tolerances. This control system showed that with minimal adjustments the rod-net could be directed effectively, resulting in deviations from the target surface reduced from up to 3–9 mm to below 1–2 mm for a 3D rod-net of approximate dimension 2.5 m × 4.5 m × 2.0 m. Additionally, the algorithm provided a more symmetric distribution of deviations around the target. The control system was coupled with 3D point-cloud measurements of markers placed on and around the rod-net by using a motorised image-assisted theodolite and specialised software for spherical and circular targets. This semi-automated process proved to be both efficient and accurate for determining the spatial co-ordinates of the markers and hence the node locations.
  • A unified BIM adoption taxonomy: Conceptual development, empirical
           validation and application
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Ahmed Louay Ahmed, Mohamad KassemAbstractBuilding Information Modelling (BIM) is an innovation that is transforming practices within the Architectural, Engineering, Construction and Operation (AECO) sectors. Many studies have investigated the process of BIM adoption and diffusion and in particular, the drivers affecting adoption at different levels, ranging from individual and team through organisations and supply chains to whole market level. However, in-depth investigations of the stages of the BIM adoption process and the drivers, factors and determinants affecting such stages are still lacking. A comprehensive classification and integration of adoption drivers and factors is absent as these are disjointedly identified across disparate studies. There is also limited attention to the key terms and concepts (i.e. readiness, implementation, diffusion, adoption) in this area of study.This aim in this paper is twofold: (1) to develop and validate a Unified BIM Adoption Taxonomy (UBAT); and (2) to identify the taxonomy's constructs (i.e. three driver clusters and their 17 factors) that have influence on the first three stages of the BIM adoption process namely, awareness, interest, and decision stages, and compare their effects on each of the stages. The research uses: a systematic literature review and knowledge synthesisation to develop the taxonomy; a confirmatory factor analysis for its validation; and an ordinal logistic regression to test the effect of the UBAT's constructs on the BIM adoption process within the UK Architectural sector using a sample of 177 organisations.The paper is primarily intended to enhance the reader's understanding of the BIM adoption process and the constructs that influence its stages. The taxonomy and its sets of drivers and determinants can be used to perform various analyses of the BIM adoption process, delivering evidence and insights for decision makers within organisations and across whole market when formulating BIM diffusion strategies.
  • Tracked walking mechanism for large hydraulic excavators
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Zhixin Dong, Long Quan, Jing YangThe conventional design methods for tracked walking systems of large hydraulic excavators based on empirical formulas, does not take into account the dynamic load of the track. As such, a safety margin factor has to be adopted to ensure adequate working strength. However, the machine weight will be increased, and the hydraulic system will be overmatched. To address this design issue, an electromechanical–hydraulic design approach based on co-simulation is proposed in this study. The proposed design approach consists of four parts, namely, 1) a terramechanics model of the track that considers the pressure–sinkage relationship and soil shear stress of the individual tracked plate, 2) a tracked multibody dynamics (MBD) model that considers the intermittent transmission between the sprocket and the tracks, 3) the hydraulic systems model, and 4) the data communication interface. To demonstrate the proposed approach, it was used to design a large hydraulic excavator with a bucket capacity of 15 m3. Experimental results from the prototype showed that the proposed design principle can accurately reflect the impact load and periodic torque fluctuations on the track. The maximum error between the simulated and experimental results is 5.4% in forward walking and 12.7% in backward walking, thus demonstrating the effectiveness and accuracy of the proposed design approach.Graphical abstractUnlabelled Image
  • Self-correcting neural network in road pavement diagnostics
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Marcin Staniek, Piotr CzechAbstractThe paper focuses on application of the self-correcting neural network in the process of road pavement diagnostics. It provides a discussion on a method of road inspection based on the proposed neural network solution and a measuring station which uses stereo vision of road pavement. The solution proposed was verified in real-life conditions, i.e. in a road with different types of pavement defects. With reference to a comparison of the results, a typical approach to estimation of disparity maps based on matching measures has been limited in favour of the solution in question. Both the results thus obtained and statistical analysis have confirmed legitimacy of the solution devised by the authors.
  • Learning method for knowledge retention in CBR cost models
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Sae-Hyun Ji, Joseph Ahn, Eul-Bum Lee, Yonggu KimAbstractThe case-based reasoning methodology fundamentally relies on historical cases to solve new problems. Supplementing insufficient data by the reproduction of appropriate values can mitigate the potential negative effects on the solutions resulting from sudden changes. However, CBR researchers have rarely examined this issue. To address this challenge, this research proposes a learning method for knowledge retention based on CBR by applying a data-mining approach to manage missing dataset values. A case study on a 164-apartment project was conducted to compare the estimation accuracy of the suggested learning method to that of past research with the same experiment conditions. The learning method with the CBR model achieved higher accuracy of the overall cost estimation and higher stability compared with the previous model. This research shows how cases can be generated and retained as learned cases to overcome the difficulties of continuous updates in a wide range of construction projects, as well as why the case bases need to be continuously updated. The research outcomes could support work related to cost estimation for decision makers ranging from beginners to experts in both academia and industry.
  • Assessing the impacts of mobile technology on public transportation
           project inspection
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Julian Yamaura, Stephen T. MuenchAbstractAdvancements in mobile technology capabilities and affordability allow many Departments of Transportation (DOT) the opportunity to use these technologies to improve the time-consuming nature of collecting, documenting, and distributing project inspection information. A mobile technology system for project inspection, called HeadLight, is piloted with the Washington, Minnesota, and Texas Departments of Transportation on 31 projects over a 3-month time span. Field measurements and interviews are used to quantify improvements offered by mobile technology over current practice. This empirical data is evaluated using standard software and process change evaluation metrics: time savings, data volume, data variety, data completeness, data timeliness, and data availability. Results indicate that project inspectors using the mobile technology system experienced productivity gains on the order of 25%, collected and shared twice as many observations, and improved the timeliness of daily reports and overall data availability. Additionally, the mobile technology solution is found to enable more complete and consistent data, improved accessibility throughout a project office and DOT. All these outcomes indicate mobile technology for project inspection allows the inspection workforce to work more efficiently. Further study into improved data quality and availability may identify more impacts within the construction inspection process and to a DOT's decision making processes.
  • Modeling and problem solving of building defects using point clouds and
           enhanced case-based reasoning
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Zhao Xu, Suhao Li, Heng Li, Qiming LiAbstractMany factors, including improper maintenance and material aging, may lead to the occurrence of defects during the operation of the various functions of buildings. Building defect information is normally stored in a discrete and unstructured way, and for this reason, building a case-based reasoning framework regarding building defects to enhance the level of building maintenance management has become an important field in the related research. At present, there is limited research available on the integration of geometric data models that are built by means of scanning and multi-attribute selection strategies. This study proposes an integrated information management framework for superficial defects in buildings, which is compatible with a point clouds model as a central data source. It features the attributes of defects used in multi-criteria decision analysis. A CBR (case-based reasoning) approach that considers case-based distance is used to enhance the performance of similarity calculations and case retrieval. A case-based distance model is utilized for the data processing stage and concentrates on a smaller case set that contains best alternatives. The potential benefit offered by this approach is that more efficient results can be obtained from classified cases during the retrieval phase process. A comparison of a CBR query with ungrouped sample data is performed to establish patterns to verify the effectiveness of the calculation method of determining case similarity, which is supported by the pre-processing of classified information about the building defects. The analytical results show that the proposed method performs well in solving the multi-attribute classification of building defects and avoiding ambiguous answers retrieved from unrelated subsets. This approach might be capable of investigating the practical problems involved in building maintenance in the AEC domains.
  • Automatic segmentation of 3D point clouds of rubble masonry walls, and its
           application to building surveying, repair and maintenance
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Enrique Valero, Frédéric Bosché, Alan ForsterAbstractChanging climatic conditions are contributing to faster deterioration of building fabric. Increasing number of heavy rainfall events can particularly affect historic and Cultural Heritage (CH) buildings. These evolving and uncertain circumstances demand more frequent survey of building fabric to ensure satisfactory repair and maintenance. However, traditional fabric surveys have been shown to lack efficiency, accuracy and objectivity, hindering essential repair operations. The recent development of reality capture technologies, together with the development of algorithms to effectively process the acquired data, offers the promise of transformation of surveying methods.This paper presents an original algorithm for automatic segmentation of individual masonry units and mortar regions in digitised rubble stone constructions, using geometrical and colour data acquired by Terrestrial Laser Scanning (TLS) devices. The algorithm is based on the 2D Continuous Wavelet Transform (CWT), and uniquely it does not require the wall to be flat or plumb. This characteristic is important because historic structures, in particular, commonly present non-negligible levels of bow, waviness and out-of-verticality.The method is validated through experiments undertaken using data from two relevant and highly significant Scottish CH buildings. The value of such segmentation to building surveying and maintenance regimes is also further demonstrated with application in automated and accurate measurement of mortar recess and pinning. Overall, the results demonstrate the value of the automatic segmentation of masonry units towards more comprehensive and accurate surveys.
  • Sustainable Infrastructure Multi-Criteria Preference Assessment of
           Alternatives for Early Design
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Yasaman Shahtaheri, Madeleine M. Flint, Jesús M. de la GarzaAbstractThe tradeoffs between the economic, social, and environmental aspects of infrastructures are not easily evident to decision makers and stakeholders in the initial design phase. This lack of insight, often leads to designs that compromise the social and environmental aspects of designs in order to reduce the initial construction costs of infrastructure assets. In addition to the lack of insight, currently available methods for analyzing alternative infrastructure configurations with respect to decision maker preferences: require analysis on a case-by-case (e.g., pairwise) basis; are not appropriate for the initial design phase (e.g., are time-consuming); and are not adaptable to a range of alternative design solutions (e.g., adding and removing alternatives might require a re-ranking from the decision maker). This paper presents a modular preference function development strategy that aims to address these issues, termed Sustainable Infrastructure Multi-Criteria Preference assessment of aLternatives for Early Design (SIMPLE-Design). The proposed strategy develops utility functions (indifference curves) for assessing decision maker preferences with regard to various tradeoffs of alternative design options, and leverages available data to provide decision makers with a consistent frame of reference for assessing alternatives. An illustration presented for a decision support tool using the Simple-Design strategy assesses decision maker preferences for commercial buildings with respect to initial construction costs, building damage and business interruption costs, casualty costs (due to the occurrence of natural hazard events), and CO2 emission costs. The designed decision support tool provides streamlined information to support preference assessment with reasonably low cognitive load. Ten out of the twelve decision support tool users stated that allowing the decision makers to define alternatives of equal utility (value) in a systematic manner, and providing information on the various cost types (decision criteria), are the most essential elements of the assessment strategy. The presented modular preference assessment framework, as well as the decision support tool itself, are generalizable and can be adapted to other infrastructure types. The contribution to the body of knowledge is a holistic preference assessment framework that allows decision makers to make more informed decisions—and designers to better incorporate the preferences of the decision makers—during the early design process.
  • Supporting constructability analysis meetings with Immersive Virtual
           Reality-based collaborative BIM 4D simulation
    • Abstract: Publication date: December 2018Source: Automation in Construction, Volume 96Author(s): Conrad BotonAbstractImmersive Virtual Reality-based collaborative BIM 4D simulation can offer a unique, supportive environment for conducting constructability analysis meetings in the construction industry. While many research works have addressed various aspects of VR-based 4D simulation, there is still no comprehensive and neutral framework to help both practitioners and experts to identify the main challenges to address. This paper proposes four main complementary steps with which to define the VR environment, to develop the 4D model, to prepare and transfer the model in the VR system and to conduct constructability analysis meeting. In the current state of the framework, the 4D-based constructability analysis is more about the collaborative use of 4D rather than the collaborative generation and interaction with the 4D model. Each step of the framework is supported by appropriate methods and tools. A collaborative personas-based case study helps to evaluate the framework and to show how it can be used. Compared to recent related works, the proposed framework is more structured and comprehensive, providing a structured approach using concepts from multiple scientific areas.
  • Digital engineering potential in addressing causes of construction
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Hamed Golizadeh, Carol K.H. Hon, Robin Drogemuller, M. Reza HosseiniAbstractWith the emergence of digital engineering in the construction context, significant opportunities have arisen for safer project execution. Several studies in recent years have described various applications of digital engineering to improve safety performance. However, what is missing is a systematic review that shows the direct links between the potential of these approaches and how they address the causes of construction accidents. This study is an attempt to fill this gap by conducting a realist systematic review of the literature published since 2012. The study draws from the Loughborough Construction Accident Causation (ConAC) model to create a comprehensive list of accident causes and relates these causes to the identified digital engineering potential, as reflected in the literature. This approach identifies the research gaps and neglected research domains, particularly six endemic problems, within the current digital engineering literature pertaining to safety, while introducing future areas associated with the identified gaps. This study provides useful insights to investigators who gain direction towards the top priorities for future research. In practical terms, the study collates and presents various areas of potential within digital engineering to address the causes of accidents on construction sites, providing a concise source of knowledge for practitioners.
  • Universal path planning for an indoor drone
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Fangyu Li, Sisi Zlatanova, Martijn Koopman, Xueying Bai, Abdoulaye DiakitéAbstractDuring the construction and maintenance of building, universal path planning for an indoor drone navigation is needed. There are many two-dimensional (2D) path planning methods, but they are not appropriate for a three-dimensional (3D) indoor environment with many obstacles in it. In this study, we present a novel approach to plan universal paths for drones in a known indoor environment using a voxel model. This approach can make the drone fly at some distance from the obstacles by computing a 3D buffer around the obstacles, using our algorithm 3D propagating approximate Euclidean distance transformation (3D PAEDT). Two types of paths are presented using A* and distance transformation algorithms: safe shortest path (SSP) and safe least cost path (SLCP). Both paths ensure that the drone maintains a minimal distance from the obstacles. SLCP ensures that the drone flies at a fixed height. Several experiments are conducted to test the approach in a two-story building.
  • Automated assessment of vertical clearance on highways scanned using
           mobile LiDAR technology
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Suliman A. Gargoum, Lloyd Karsten, Karim El-Basyouny, James C. KochAbstractAssessing vertical clearance at bridges is a preliminary step in most routine bridge inspections. This information is critical when assessing the structural integrity of bridges. Furthermore, clearance information at bridges and other overhead assets on a highway network is also extremely important when routing oversized vehicles on a highway network. Efficient clearance assessment makes critical information readily available to asset owners. As a result, asset owners and transportation agencies are able to address concerns in a timely manner, which would help them avoid prohibitive maintenance costs sustained in case of collisions. Unfortunately, manual clearance assessment using conventional surveying tools is unsafe, time consuming, labour intensive. To overcome these challenges, this paper proposes a novel algorithm whereby mobile LiDAR data could be used to efficiently assess clearance at overhead objects on highways. The proposed algorithm first detects and classifies all overhead objects on a highway segment. The clearance is then assessed at each of those objects and minimum clearance is identified. Detection involves voxel-based segmentation of the point cloud followed by a nearest-neighbour search to locate overhead structures. After detecting the structures and identifying their locations, points representing the same object are clustered and classify into bridges and non-bridges. Furthermore, an estimate of the clearance at each object is also obtained. For objects of long span such as bridges, detailed clearance assessment is performed. The developed algorithm was tested on three highway segments in Alberta, Canada including a 242 km highway corridor. Testing revealed that the method was successful in detecting and classifying all overhead structures at an accuracy level of 97.8% and 96.2%, respectively. The algorithm was also successful in accurately measuring the clearance at those structures with the differences in measurement between ground truth data and the extracted results ranging between 0.03 and 0.47%.
  • Survey of precedence relationships: Classification and algorithms
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Miklos HajduAbstractPrecedence relationships used in project planning mean for most professionals the traditional Start-to-Start-z (SSz), Finish-to-Start-z (FSz), Finish-to-Finish-z (FFz) and Start-to-Finish-z (SFz) relationships where z stands for the minimal necessary duration between the defined endpoints (Start or Finish) of the activities. These relationships have been serving professionals for more than 50 years, and there is not much visible effort for further developing them, despite some well-established critiques on the modeling capability of the Precedence Diagramming Method (PDM). The purpose of this research is: a) gathering those well-known and lesser-known developments of logical relationships that can be used for modeling some, so far, un-modelable problems b) classifying them by using a classification scheme that has been developed for this purpose and c) developing algorithms for time analysis when missing. The following earlier developments are discussed: maximal precedence relationships, point-to-point precedence relationships, continuous precedence relationships, relationships with AND/OR logical switches and bidirectional precedence relations. The classification shows that 24 types of logical relationships exist, but that algorithms exist only in four types, and are missing in twenty cases. The missing algorithms are provided here. The main contributions to the Body of Knowledge are: a) providing a classification scheme for precedence relationships b) definition of 24 precedence relationships based on the classification categories c) developing the missing time analysis algorithms for twenty cases d) presenting a single unified algorithm that handles all the 24 types of precedence relationships.
  • Improved characterization of underground structure defects from two-stage
           Bayesian inversion using crosshole GPR data
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Hui Qin, Jasper A. Vrugt, Xiongyao Xie, Yunxiang ZhouAbstractCrosshole ground-penetrating radar (GPR) is a widely used measurement technique to help inspect the structural integrity of man-made underground structures. In a previous paper, we have introduced a Bayesian framework for inversion of crosshole GPR experiments to help back out defects in concrete underground structures. Here, we evaluate the practical usefulness of our inversion framework by application to waveform data from a real-world GPR survey of a diaphragm wall panel with two embedded structure defects. We also use this case study to further refine our methodology by introducing the elements of a two-stage inversion method to help delineate the exact location and shape of small structure defects. Herein, a low-resolution inversion composed of relatively few inversion coefficients (stage-1) is used to determine roughly the presence of structure defects, followed by a second inversion (stage-2) with much enhanced spatial resolution in those areas classified with anomalous or suspicious permittivity values. This two-stage inversion approach uses more wisely CPU-resources by focusing primarily on those areas of the concrete structure that have been classified as anomalies. We investigate the benefits of this two-stage inversion scheme using a synthetic and real-world case study involving waveform data of a diaphragm wall panel measured with crosshole GPR. Our results demonstrate that the proposed two-stage inversion method recovers successfully the location and shape of structure defects, at a computational cost that is considerably lower than the original inversion framework.
  • Automated Crane Planning and Optimization for modular construction
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Hosein Taghaddos, Ulrich Hermann, ArioBarzan AbbasiAbstractThe majority of industrial projects in Alberta's oil sands are constructed using modular construction. Modules are preassembled components built off-site and transported to the site to be lifted into place with mobile cranes. Heavy lifts include modules as well as major equipment that utilize expensive mobile cranes. Selecting the proper mobile cranes and configurations and finding the best crane position for each lift saves a significant amount of time and cost, while also improving safety. A heavy lift plan facilitates overall site management by reducing extra crane relocations and avoiding dangerous crane clashes. Performing such intensive analysis manually for several hundred lifts and various crane options is a tedious, prolonged exercise. However, no application that carries out such intensive analysis for a number of lifts in modular construction has yet been developed. This paper presents a system, called Automated Crane Planning and Optimization, to automate the above-mentioned analysis for a large-scale project. This system is validated on actual modular projects.
  • Indoor localization strategy based on fault-tolerant area division for
           shipboard surveillance
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Kezhong Liu, Mozi Chen, E Cai, Jie Ma, Shoujun LiuAbstractLocalization based on wireless sensor networks has been shown to be a promising application in ships. Although a considerable number of algorithms have been designed for low-overhead and high-accuracy localization, some problems have been ignored, such as interference in the shipboard environment and the method of using anchor-deploying. In this paper, we present a method for range-free localization called fault-tolerant area division (FAD) to deploy and divide the area in which precise indoor localization is required. Despite the limitations with respect to shipboard environmental interference, sensing irregularity, received signal strength variation, and other unavoidable factors, FAD has been shown to be reliable by improving the fault-tolerant mechanism. In addition, to address the scheme of anchor-node placement, which complicates the localization performance, this paper presents a new deployment strategy for the anchor nodes using optimization methods. This paper presents and analyzes an enhancement method using a series of simulations and real-world ship experiments. The result shows that a well-organized deployment and a fault-tolerant mechanism can make such localization method more reliable and compatible.
  • Automated optimization of formwork design through spatial analysis in
           building information modeling
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Changtaek Hyun, Chengquan Jin, Zhenhua Shen, Hyunjoo KimAbstractFormwork construction for reinforced cast-in-place concrete work is costly, often time-consuming and complex to plan and design. Even though the process of calculating the proper formwork design is lengthy and complex, the responsibility is usually left to a field manager/engineer which may not have enough time and resources identifying all possible options to select the most effective formwork.The design aspects that go into formwork include several parameters such as concrete pressure, bending, deflection, and horizontal shearing. Even though there are equations and calculations for each of those parameters in the design of concrete formwork, the process of performing the calculations for each concrete formwork application is still lengthy. Therefore, construction managers often rely on their previous work experiences and apply similar formwork designs for most situations.By developing a BIM (Building Information Modeling) based automatic formwork design system, this research aims to optimize the formwork design process required to perform the calculations for the design of the formwork by automatically extracting the properties and data from a BIM model. The case study shows that the proposed formwork design approach successfully automates the formwork design in BIM modeling using IFC extension by comparing the different materials and costs. The result of the case study reveals that the efficiency of the formwork design process could be greatly improved by utilizing the proposed formwork design system.
  • Programmable hydraulic control technique in construction machinery:
           Status, challenges and countermeasures
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Ruqi Ding, Junhui Zhang, Bing Xu, Min ChengProgrammable hydraulic control (PHC) technology utilized in construction machinery is superior to the conventional electronic-hydraulic control technology. This paper aims to briefly survey the recent results and upcoming trends in this field. First, major problems encountered using the widespread mobile hydraulic system, including insufficient compatibility, low energy efficiency and poor controllability, are demonstrated. The key element of PHC technology contains independent actuators, integrated sensors and intelligent software control, which transfers functionality from hardware to software. A survey of recent advancements for the three aspects is summarized in detail. Next, several industrial products applied in construction machinery are introduced. Finally, the paper focuses on the challenges facing the PHC technology, which prevented it from becoming widely spread in the market, and the countermeasures are discussed.Graphical abstractUnlabelled Image
  • Automated detection of sewer pipe defects in closed-circuit television
           images using deep learning techniques
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Jack C.P. Cheng, Mingzhu WangAbstractSanitary sewer systems are designed to collect and transport sanitary wastewater and stormwater. Pipe inspection is important in identifying both the type and location of pipe defects to maintain the normal sewer operations. Closed-circuit television (CCTV) has been commonly utilized for sewer pipe inspection. Currently, interpretation of the CCTV images is mostly conducted manually to identify the defect type and location, which is time-consuming, labor-intensive and inaccurate. Conventional computer vision techniques are explored for automated interpretation of CCTV images, but such process requires large amount of image pre-processing and the design of complex feature extractor for certain cases. In this study, an automated approach is developed for detecting sewer pipe defects based on a deep learning technique namely faster region-based convolutional neural network (faster R-CNN). The detection model is trained using 3000 images collected from CCTV inspection videos of sewer pipes. After training, the model is evaluated in terms of detection accuracy and computation cost using mean average precision (mAP), missing rate, detection speed and training time. The proposed approach is demonstrated to be applicable for detecting sewer pipe defects accurately with high accuracy and fast speed. In addition, a new model is constructed and several hyper-parameters are adjusted to study the influential factors of the proposed approach. The experiment results demonstrate that dataset size, initialization network type and training mode, and network hyper-parameters have influence on model performance. Specifically, the increase of dataset size and convolutional layers can improve the model accuracy. The adjustment of hyper-parameters such as filter dimensions or stride values contributes to higher detection accuracy, achieving an mAP of 83%. The study lays the foundation for applying deep learning techniques in sewer pipe defect detection as well as addressing similar issues for construction and facility management.
  • Form finding of nexorades using the translations method
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Romain Mesnil, Cyril Douthe, Olivier Baverel, Tristan GobinAbstractThis article proposes a new computational method for the form-finding of nexorades, also called reciprocal frames in the literature. The method is based on the translations of members forming the initial layout. It is shown that the two geometrical quantities defining nexorades - eccentricity and engagement length - depend linearly on the transformation parameters. The method introduced in this article is thus based on linear algebra, so that fitting problems can be formulated as simple quadratic optimisation problems under linear constraints. The proposed method is therefore fast, simple to implement, robust and can be applied to various grid patterns.Furthermore, the proposed framework preserves planar facets. This paper proposes thus a new structural system where the nexorade is braced by planar facets. The feasibility of this structural system and of the computational framework introduced in this article is demonstrated by the fabrication of a 50 m2 timber pavilion.
  • Morphogenesis of surfaces with planar lines of curvature and application
           to architectural design
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Romain Mesnil, Cyril Douthe, Olivier Baverel, Bruno LégerAbstractThis article presents a methodology to generate surfaces with planar lines of curvature from two or three curves and tailored for architectural design. Meshing with planar quadrilateral facets and optimal offset properties for the structural layout are guaranteed. The methodology relies on the invariance of circular meshes by spherical inversion and discrete Combescure transformations, and uses parametrisation of surfaces with cyclidic patches. The shapes resulting from our methodology are called super-canal surfaces by the authors, as they are an extension of canal surfaces. An interesting connection to shell theory is recalled, as the shapes proposed in this paper are at equilibrium under uniform normal loading. Some applications of these shapes to architecture are shown.
  • Proactive behavior-based system for controlling safety risks in urban
           highway construction megaprojects
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Yongkui Li, Yi Hu, Bo Xia, Martin Skitmore, Heng LiUrban highway construction megaprojects are commonly beset by significant and dynamic safety risks because of their large size, the scattered nature of the works involved, compressed construction schedules, technical difficulties and numerous participants. However, traditional on-site safety inspection cannot fully address all challenges, particularly those with behavior-based safety (BBS) risks. To deal with these challenges, this study describes the novel use of the proactive construction management system (PCMS) with a third-party safety inspection program. The definition, abstraction and implementation processes of the PCMS-aided third-party inspection program are demonstrated and tested through a case study of the Shanghai Central Loop Pudong highway construction project with multi-section sites. Based on a “before and after” comparative study, quantitative and qualitative data are triangulated to evaluate variations in the effectiveness of third-party inspection programs with and without the PCMS aided at the macro, meso, and micro levels. Results indicate the usefulness of the novel idea that applies the PCMS as a part of a third-party inspection program to improve BBS risk control on certain risky sites and incorporates its feedback into third-party inspection on all section sites to strengthen the overall safety training, safety inspection, and timely safety risk responses. These results not only provide an increased understanding of the role of PCMS in the safety management of highway megaprojects and the guidelines required for its future application but also serve as a precursor to future research into megaproject safety management.
  • Building Information Modeling (BIM) outsourcing among general contractors
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): James Fountain, Sandeep LangarAbstractBuilding Information Modeling (BIM) is a process used by Architecture Engineering Construction (AEC) stakeholders which simulates a construction project in a multi-dimensional digital model and provides multitudes of project benefits from project inception to its occupancy. However, a variety of barriers impede a holistic BIM implementation. Due to these barriers, some general contractors outsource the creation and use of BIM models to specialized Information Technology (IT) firms. Since limited literature currently exists for BIM outsourcing, this study aims to identify BIM outsourcing patterns among the general contractors across the US and the perceived impacts it has on construction projects. Analysis of two-hundred and fifty-two complete responses from general contracting firms determines that 45% of responding companies have outsourced BIM, this signifies that outsourcing has become an important facet of BIM implementation. Data was also collected on company demographics, BIM outsourcing locations, strategic reasons for outsourcing, and various other aspects related to BIM outsourcing. The results indicate that respondents perceive BIM outsourcing as less efficient than in-house BIM implementation. However, continued use of outsourcing for BIM functions also displays the adaptability of the industry in meeting challenges and embracing new technology through alternative methods, despite the potential risks.
  • Large-scale 3D printing by a team of mobile robots
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Xu Zhang, Mingyang Li, Jian Hui Lim, Yiwei Weng, Yi Wei Daniel Tay, Hung Pham, Quang-Cuong PhamAbstractScalability is a problem common to most existing 3D printing processes, where the size of the design is strictly constrained by the chamber volume of the 3D printer. This issue is more pronounced in the building and construction industry, where it is impractical to have printers that are larger than actual buildings. One workaround consists in printing smaller pieces, which can then be assembled on-site. This workaround generates however additional design and process complexities, as well as creates potential weaknesses at the assembly interfaces. In this paper, we propose a 3D printing system that employs multiple mobile robots printing concurrently a large, single-piece, structure. We present our system in detail, and report simulation and experimental results. To our knowledge, this is the first physical demonstration of large-scale, concurrent, 3D printing of a concrete structure by multiple mobile robots.
  • Optimized rescheduling of multiple production lines for flowshop
           production of reinforced precast concrete components
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Zhiliang Ma, Zhitian Yang, Shilong Liu, Song WuAbstractFlowshop production is adopted as the major type of production of reinforced precast concrete components and it has higher requirements on shop floor schedules than other types, especially that from rescheduling. However, up to now, very few approach for the optimization of the shop floor rescheduling has been proposed in spite of its vital importance. This research proposes an approach for optimizing shop floor rescheduling of multiple production lines for flowshop production of reinforced precast concrete components. The approach comprehensively utilizes the over-assigned time, which is the difference value between the assigned production time and the estimated one of a production step for a precast component to deal with production emergencies. Meanwhile, it keeps the adjustment of schedules at minimum to avoid massive material re-dispatch. First of all, the optimization objectives and constraints of optimized shop floor rescheduling of multiple production lines for flowshop precast production are analyzed and a mathematic model is thus formulated. Then, the solver of the model is established by using genetic algorithm. Finally, the approach is validated by case studies. It is concluded that the approach contributes to the effective and efficient optimized rescheduling of multiple production lines for flowshop precast production.
  • An integrated ergonomics framework for evaluation and design of
           construction operations
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Alireza Golabchi, Xingzhou Guo, Meiyin Liu, SangUk Han, SangHyun Lee, Simaan AbouRizkAbstractLabor is one of the most critical resources in the construction industry due to its impact on the productivity, safety, quality, and cost of a construction project. Ergonomic assessment, as a tool and method for analyzing human activities and their interactions with the surrounding environment, is thus crucial for designing operations and workplaces that achieve both high productivity and safety. In construction, however, the constantly changing work environments and laborious tasks cause traditional approaches to ergonomic analysis, such as manual observations and measurements, to require substantial time and effort to yield reliable results. Therefore, to simplify and automate the assessment processes, this study explores the adaptation and integration of various existing methods for data collection, analysis, and output representation potentially available for comprehensive ergonomic analysis. The proposed framework integrates sensing for data collection, action recognition and simulation modeling for productivity and ergonomic analysis, and point cloud model generation and human motion animation for output visualization. The proposed framework is demonstrated through a case study using data from an off-site construction job site. The results indicate that integrating the various techniques can facilitate the assessment of manual operations and thereby enhance the implementation of ergonomic practices during a construction project by reducing the time, effort, and complexity required to apply the techniques.
  • Automated detection of faults in sewers using CCTV image sequences
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Joshua Myrans, Richard Everson, Zoran KapelanAbstractRoutine CCTV surveys are vital to the effective maintenance of wastewater networks, but their time-consuming nature makes them very expensive. We present a methodology capable of automatically detecting faults within recorded CCTV footage, aiming to improve surveying efficiency. The procedure calculates a feature descriptor for each video frame, before using a machine learning classifier to predict the contents of individual frames. The sequence of predictions is then smoothed using a Hidden Markov Model and order oblivious filtering, incorporating information from the entire sequence of frames. This technique has been demonstrated on footage collected by the Wessex Water, achieving a detection accuracy of over 80% on still images. Furthermore, temporal smoothing on continuous CCTV footage improved false negative rate by more than 20%, to achieve an accuracy of 80%. This last step enables the method to compete with the performance of trained technicians, showing promise for application in industry.
  • A SPARQL query engine for binary-formatted IFC building models
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Thomas Krijnen, Jakob BeetzAbstractTo date, widely implemented and full-featured query languages for building models in their native exchange formats do not exist. While interesting proposals exist for querying Industry Foundation Classes (IFC) models, their functionality is often incomplete and their semantics not precisely defined. With the introduction of the ifcOWL ontology as an equivalent to the IFC schema in the Web Ontology Language (OWL), an option to represent such models in RDF (Resource Description Framework, a general information modeling method) is provided, and such models can be queried using SPARQL (SPARQL Protocol and RDF Query Language). The size of data sets in complex building projects, however, renders the use of clear-text encoded RDF infeasible in many cases.A SPARQL implementation, compatible with ifcOWL, is proposed, directly atop a standardized binary serialization format for IFC building models. This novel format is the binary equivalent of traditional IFC serialization formats but with more compact storage and less overhead than the graph serialization in RDF. The format is based on ISO 10303-26 and relies on an open standard for organizing large amounts of data: Hierarchical Data Format version 5 (HDF5). Due to hierarchical partitioning and fixed-length records, only small subsets of the data are read to answer queries, improving efficiency.A prototypical implementation of the query engine is provided in the Python programming language. In several realistic use cases, the proposed system performs equivalent to or better than the state of the art in SPARQL querying on building models. For large datasets, the proposed storage format results in files that are 2–3 times smaller than the current, most concise, RDF databases while offering a platform-neutral, containerized exchange file.
  • A framework for integrating BIM and IoT through open standards
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Bhargav Dave, Andrea Buda, Antti Nurminen, Kary FrämlingAbstractThe built environment provides significant opportunities for IoT (Internet of Things) deployment, and can be singled out as one of the most important aspects for IoT related research. While the IoT deployment in the built environment is growing exponentially, there exists a gap in integrating these two in a systematic way through open standards and systems. From technological perspective, there is a need for convergence of diverse fields ranging from Building Information Systems and Building Services to Building Automation Systems, and IoT devices and finally the end user services to develop smart, user oriented applications.This paper outlines the efforts to develop a platform that integrates the built environment data with IoT sensors in a campus wide, web based system called Otaniemi3D that provides information about energy usage, occupancy and user comfort by integrating Building Information Models and IoT devices through open messaging standards (O-MI and O-DF) and IFC models. The paper describes the design criteria, the system architecture, the workflow and a proof of concept with potential use cases that integrate IoT with the built environment. Initial results show that both the end users and other research groups can benefit from such platforms by either consuming the data in their daily life or using the data for more advance research.
  • Schedule risk analysis of infrastructure projects: A hybrid dynamic
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Xiaoxiao Xu, Jiayuan Wang, Clyde Zhengdao Li, Wenke Huang, Nini XiaAbstractSchedule risk is a major concern in infrastructure project management. Existing studies have proposed several models for schedule risk analysis, but few efforts have been made on the dynamics and uncertainty of risks and the generality and practicability of the model. To fill the research gaps, this study develops a hybrid dynamic approach for investigating the effect of risks on infrastructure project schedule performance. This approach combines system dynamics (SD) and discrete event simulation (DES) which have mainly been used to analyze the macroscopic and microcosmic construction issues in isolation, respectively. The model is then verified by data which is collected from a bridge construction project. As an application example, the effect of four selected risks on the schedule was explored. The results show that the proposed SD-DES model could be ease of modifying the model to reflect real situation, performing various sensitivity and uncertainty analysis, and showing simulation results more effectively.
  • A method to optimize mobile crane and crew interactions to minimize
           construction cost and time
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Bo Peng, Forest Lee Flager, Jiaao WuAbstractCranes often play a central role in transporting materials on building construction sites and are therefore critical to project cost and schedule. This paper presents a new model to simulate the interactions between mobile cranes and associated work crews onsite. The model considers crane type and position, the sequence of components transported, and the number and size of crews at the demand point. A novel hybrid multi-objective Genetic Algorithm (MOGA) is utilized to identify optimal crane and crew configurations that minimize construction cost and duration. The proposed method is demonstrated on an example problem involving the installation of curtain wall panels for a mid-rise office building. The results indicate that considering crane and crew decisions in parallel reduces installation cost by 19.5% and duration by 1.7% compared to considering these decisions sequentially. Furthermore, the number of crews used and the number of crane stops had the most significant impact on project cost and schedule, respectively.
  • Optimization modeling of multi-skilled resources in prefabrication:
           Theorizing cost analysis of process integration in off-site construction
    • Abstract: Publication date: November 2018Source: Automation in Construction, Volume 95Author(s): Mehrdad Arashpour, Vineet Kamat, Yu Bai, Ron Wakefield, Babak AbbasiAbstractIn advanced manufacturing of building elements, process integration and utilization of multi-skilled resources enhance the flexibility of production networks against variations in demand and resource availability. This research study aims to incorporate the required cost and time for cross-training multi-skilled resources into resource planning computations. Towards this aim, minimizing the cost of utilizing multi-skilled resources in off-site construction is formulated using integer and probabilistic optimization models. Production data of two prefabrication networks in Brisbane and Melbourne, Australia are used to derive computational results and validate models. The main contribution of this research study is to analyze the costeffectiveness of deploying multi-skilled resources with the aim of improving production flexibility. The modeling methodology and findings are of practical use to off-site manufacturers that experience variations in production demand and resource availability.
School of Mathematical and Computer Sciences
Heriot-Watt University
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