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A Galach & Z Kotulski

Risk assessment in disaster recovery strategies development

Abstract: The paper describes the model for selecting disaster recovery strategies for information system. The risk assessment covers the threats and vulnerabilities related to the problem of losing the availability of information processes in the particular information system model. The analysis takes under consideration the relationships between the components of information system in order to find the risk of availability lost propagation within the system. That is the basis for finding the candidate disaster recovery strategies, which have to fulfil these basic requirements. Such an approach allows sifting these ones, which are basically not suitable for the security requirements of the information system. The preliminary accepted strategies are to be analyzed regarding to the estimated cost of implementation and maintenance. The next phase covers the detailed analysis of confidentiality and integrity risks in the candidate strategies. The level of risk related to the confidentiality and integrity of information processed in the disaster situation using given strategy is to be estimated.

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Full text: content.pdf (232,912 bytes) (available to registered users only)

Series: w78:2005 (browse)
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Permission to reproduce these papers has been graciously provided by the Technische Universität Dresden.


Blanca Quintana, Samuel A. Prieto, Antonio Adan and Frédéric Bosché

Scan-To-BIM for Small Building Components

Abstract: Scan-to-BIM works have so far mainly focused on 'structural' components such as floors, ceiling, walls (with doors and windows). But, the control of new facilities and the production of their corresponding as-is BIM models requires the identification and inspection of numerous other building components and objects, e.g. MEP components such as plugs, switches, ducts, and signs. In this paper, we present a novel 6D-based (XYZ + RGB) approach that processes dense coloured 3D points provided by terrestrial laser scanners to recognize such smaller objects that are commonly located on walls. This paper focuses on the recognition of objects such as sockets, switches, signs, and extinguishers. After segmenting the point clouds corresponding to the walls of a building, a set of candidate objects are detected independently in the colour and geometric spaces, and a consensus procedure integrates both results to infer recognition. The method has been tested on real indoors yielding promising results.

Keywords: Object Recognition, Scan-To-BIM, Automatic BIM, 3D Data Processing

DOI: https://doi.org/10.24928/JC3-2017/0139

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Series: jc3:2017 (browse)
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Daoud Kiomjian, F. Jordan Srour and Issam Srour

Using ABM to Evaluate the Impact of Social Networks on Construction Labor Productivity

Abstract: Labour productivity depends on a wide variety of factors, some of which pertain to characteristics of the construction crews themselves. Several of these factors such as language and demographics are described in the literature as soft or intangible and are of stochastic nature. As such, traditional deterministic modelling techniques are not sufficient to capture the full picture of the factors that come into play when considering construction labour productivity. Agent based modelling (ABM), a simulation technique with growing popularity, presents a powerful candidate for modelling construction sites due to its properties and ability to consider social aspects. This paper demonstrates that ABM is an acceptable paradigm for studying the effect of both tangible and soft features on construction labour productivity.

Keywords: Labour Productivity, Agent Based Modelling, Social Networks, Simulation

DOI: https://doi.org/10.24928/JC3-2017/0112

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Series: jc3:2017 (browse)
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G. Brewer, T. Gajendran & C. Beard

Influences on the adoption of BPM/BIM: an Australian perspective

Abstract: BPM/BIM offer the possibility of faster, more accurate collaborative working thereby offering a solution to many current construction industry challenges, yet their usage remains frustratingly limited. It follows that there are likely be a number of influences and the aim of this research was therefore to identify those that could be considered relevant to the Australian construction industry. It first modeled candidate inhibitors identified from the literature, applying this to a single ‘critical case’ study project. Interviews undertaken with six key stakeholders were triangulated with two industry experts. Coding and abstraction of the data largely confirmed the efficacy of the model, which was subsequently found to be congruent with Brewer’s model of Innovation & Attitude (Brewer 2008) after qualitative meta-analysis was conducted.

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Series: w78:2009 (browse)
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Hongjo Kim, Hyoungkwan Kim, Yong Won Hong and Hyeran Byun

Detection of Construction Equipment Using Deep Convolutional Networks

Abstract: Vision-based monitoring methods have been investigated for understanding construction site contexts. However, detection capabilities of such methods are still insufficient to be utilized in general construction sites due to dynamic outdoor conditions and appearance variances of construction entities. To improve performance of a construction entity detector, we propose a detection method using a region-based fully convolutional network (R-FCN). R-FCN consists of two main parts, which are a fully convolutional network and a region proposal network. The fully convolutional network extracts hierarchical object features through a supervised learning process, while a region proposal network generates a set of object candidate regions in an image to localize target objects. To evaluate the generalization performance of the detection method, a benchmark dataset is collected from ImageNet for five classes (dump truck, excavator, loader, concrete mixer truck, and road roller), having various object appearances within a class in different backgrounds. A state-of-the-art performance, mean average precision of 95.61%, was recorded from the experiment. The proposed method shows a potential for the universal detector that can detect construction equipment on every construction site.

Keywords: Construction Site Monitoring, Object Detection, Convolutional Networks, Benchmark Dataset

DOI: https://doi.org/10.24928/JC3-2017/0335

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Ivan Mutis, Jose Solis

FLOORBOOK: A Social Network System to Enable Effective Interfacing of Project Actors

Abstract: Construction project participants constitute a complex social human network composed of a heterogeneous and fragmented set of stakeholders. The disjoint group of actors that team to work on a project constitutes collective entities, social networks at different scales in time and space. The proposed social network system is a semantic resource that leverages the communication and coordination of exchanging and sharing information. It is expected that it will enable an improvement in efficiency of the interfacing of actors and information. This semantic resource helps actors to minimize human intervention for coordination and information searching and retrieval, which are activities that demand costly resources and the use of specialized labor. Floorbook analyzes the vocabulary of the annotations on the forms of representation used in construction documentation, categorizes and models communities according to the user’s role in the shared form of representation, and makes suggestions to the users to optimize their particular world view, so that the suggested annotation is more precise and personalized. The basic rational of the approach is that the position of the users in a social network impacts their use in the system, and that the content of the annotations are part of a categorization model of a specific domain. The proposed social network system works as an effort of collective intelligence that enables the sharing of the semantics of the tags that are associated with the representations. As an effort of collective intelligence, Floorbook (1) models and extracts semantics from informal communication; (2) categorizes and models communities defined by common interests; and (3) self-learns from the history of user actions in the system to enable new value-added services, such as, for example, suggesting new candidate semantic tags as a result of the analysis of the representations to optimize the particular world view of an individual user.

Keywords: social-networking, communication, collaboration, emerging semantics

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Full text: content.pdf (238,264 bytes) (available to registered users only)

Series: w78:2010 (browse)
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Kosovac B, Vanier D J, Froese T M

Use of Keyphrase Extraction Software for Creation of an AEC/FM Thesaurus

Abstract: The paper describes a method used to collect terms needed for the development of a thesaurus in the roofing domain. This work is part of a larger effort to investigate the potential of thesauri as an aid in product modeling and as a tool for information management in model-based systems. Extractor, a software module that extracts keyphrases from documents, was used for collecting candidate thesaurus terms from Internet sources. The principal advantage of the Internet as a source of candidate terms is that it reflects the language that is actually used in communications concerning buildings and that it covers the widest range of different views on the domain. The advantage of using Extractor or similar software is that it allows processing huge text corpora available on the Internet while eliminating irrelevant terms. The methodology used was found to be highly useful, although it was not sufficient by itself for constructing a thesaurus for the architecture, engineering, construction and facilities management industries, as considerable human intervention was required. Some possibilities for customizing the software and for partially automating a thesaurus construction process are suggested.

Keywords: thesauri, Internet, automatic indexing software, thesaurus construction

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Full text: http://www.itcon.org/2000/2 (available to registered users only)

Series: itcon:2000 (browse)
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Kosovac B, Vanier D J

Use of automatic keyphrase generation for creation of a construction thesaurus

Abstract: The paper describes development of a thesaurus in the roofing domain. This work is part of a larger effort to investigate the potential of thesauri as an aid in product modeling. Extractor, a software module that extracts keyphrases from documents, was used for collecting candidate thesaurus terms from Internet sources. The principal advantage of the Internet as a source of candidate terms is that it reflects colloquial language: -- the language that is actually used by building practitioners and that it covers the widest range of different 'user views' on the domain. The advantage of using Extractor or similar software is that it allows processing huge text corpora available on the Internet and it eliminates irrelevant terms. The methodology used was found to be highly useful, although it was not sufficient by itself for constructing a construction thesaurus, as considerable human intervention was required. Though limited time resources did not allow full exploitation of Extractor's capabilities, some possibilities for customization of the software and for partial automation of a thesaurus construction process are suggested.

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Full text: content.pdf (68,731 bytes) (available to registered users only)

Series: w78:1999 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.retrieve (0.057636) class.collaboration (0.015453) class.man-man (0.010828)
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Permission to reproduce these papers has been graciously provided by the Research Press of the National Research Council of Canada. The support of the editors, particularly Dr. Dana Vanier, is gratefully appreciated.


Robert-Nicoud Y, Raphael B, Smith I

Decision support through multiple models and probabilistic search

Abstract: "A large number of candidate behaviour models may exist for existing civil engineering structures such as bridges. Finding the right model for explaining a given set of observations is a difficult task. Traditionally, modelling assumptions are made without adequate justifications and verifications. Manually constructing multiple models and comparing their behaviour with measurements is arduous and hence, we are developing support tools for engineers. Techniques of model composition and model reuse are used for systematically constructing and evaluating multiple models. In this paper, experiments in model construction for the Lutrive bridge in Switzerland and their results are reported. The Lutrive bridge was constructed in 1972 using the cantilever method with central hinges. It is found that the bridge continues to creep significantly even after twenty-seven years of construction. However, load tests indicate that the bridge possesses unusually high rigidity and earlier theoretical models (constructed manually) gave results that were different from displacement measurements by as much as 100%. It was necessary to evaluate different modelling possibilities in order to obtain reasonable correlation with measurement data. The approach we have used is summarised in the following steps: ? Cases consisting of candidate models are constructed manually. ? Spaces of behaviour represented by each case are defined. ? The total solution space which is a union of the spaces represented by individual cases is searched using a new probability-based algorithm. The following conclusions were drawn from the above approach: ? If a model contains enough number of parameters as observation points it may be possible to get an exact match by tuning values of parameters. However, certain models are capable of representing only a few modes of behaviour and no combination of parameter values might exist that explain the observed behaviour. ? Model creation in a domain such as structural engineering requires considerable amount of skill. Storing cases consisting of complete models is a means of reusing such expertise. ? Model construction is a search problem. Evolutionary and stochastic search techniques produce good results when used in combination with cases."

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Full text: content.pdf (466,067 bytes) (available to registered users only)

Series: w78:2000 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.impact (0.017941) class.retrieve (0.013831) class.environment (0.011624)
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Permission to reproduce these documents have been graciously provided by Icelandic Building Research Institute. The assistance of the editor, Mr. Gudni Gudnason, is gratefully appreciated


Suraj Ravindran, Prakash Kripakaran, Ian F. C. Smith

Evaluating reliability of multiple-model system identification

Abstract: This paper builds upon previous work by providing a statistical basis for multiple-model system identifica-tion. Multiple model system identification is useful because many models representing different sets of modeling as-sumptions may fit the measurements. The presence of errors in modeling and measurement increases the number of possible models. Modeling error depends on inaccuracies in (i) the numerical model, (ii) parameter values (constants) and (iii) boundary conditions. On-site measurement errors are dependent on the sensor type and installation condi-tions. Understanding errors is essential for generating the set of candidate models that predict measurement data. Pre-vious work assumed an upper bound for absolute values of composite errors. In this paper, both modeling and meas-urement errors are characterized as random variables that follow probability distributions. Given error distributions, a new method to evaluate the reliability of identification is proposed. The new method defines thresholds at each meas-urement location. The threshold value pairs at measurement locations are dependent on the required reliability, char-acteristics of sensors used and modeling errors. A model is classified as a candidate model if the difference between prediction and measurement at each location is between the designated threshold values. A timber beam simulation is used as example to illustrate the new methodology. Generation of candidate models using the new objective function is demonstrated. Results show that the proposed methodology allows engineers to statistically evaluate the performance of system identification.

Keywords: system identification, multiple models, error characterization, reliability, measurements, model predic-tion

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Series: w78:2007 (browse)
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