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Cho-Chien Lu, Shih-Chung Kang, Shang-Hsien Hsieh

SimuSurvey: a computer-based simulator for survey training

Abstract: This paper presents the development of a computer-based simulator for survey training, referred to as SimuSurvey. Because modern survey instruments are usually expensive, difficult to maintain, and sensitive to weather conditions, surveying course instructors often find it difficult to supply sufficient high-quality instruments for the class. Also, the instructors often suffer the need to repeat similar instructions about instrument operations to individual stu-dents; and, lack a good means of recording each studentís learning progress. SimuSurvey was designed to address these issues - for use in survey training in a computer-generated virtual environment at a low cost. The functions cur-rently provided by SimuSurvey include: (1) the visualization of a survey instrument and measurement poles involved in an assigned survey task; (2) the simulation of the control interface of a real surveying instrument; (3) the recording of each studentís performed operations; and (4) design of learning activities for students to practice surveying tasks in a simulated environment. The focus of this paper is on the design and implementation of SimuSurvey. An example is pro-vided to demonstrate the applicability and effectiveness of SimuSurvey to survey training.

Keywords: simulator, survey training, engineering education, virtual reality, augmented reality

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Series: w78:2007 (browse)
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Ciftcioglu O, Durmisevic S, Sariyildiz S

Building design support by hierarchical expert networks

Abstract: "Rapid advances in parallel processing technologies gave essential impetus to intelligent information processing, which became the driving source of an emerging technology known as soft computing. This calls for intelligent systems that are able to process information which may be complex, uncertain even incomplete or contradictory. In this context, neural networks and fuzzy logic are the essential tools. Considering the merits of each approach separately, most suitable computational intelligence method can be used for a specific application. Additionally, the combination of these methods can provide enhanced information processing for decision-making with enhanced reliability. For building design, the computational intelligence system use a knowledge base formed by means of neural network and fuzzy logic (neuro-fuzzy) techniques, from a building design database. The application of such a system to a building design task was preliminarily demonstrated earlier [1]. The present research describes a systematic neural fuzzy modelling of data that form a knowledge base in a hierarchical form (s.figure below). Each sub-knowledge base represents a local expert, being level-one expert and the association of local experts forms a more comprehensive expert that becomes a global domain expert as level-two. The association of the experts is accomplished by means of fuzzy-logic-driven gating network that performs, the information handling as required. Although, the present paper describes two-level hierarchical experts as local and global, the associations can be done in more subtle form, i.e., in more than two steps so that the level of experts can be categorised in multi-level form. In such more complex structures, multi-level experts require related gating network that could similarly be designed. The building design support system with the expert network developed, as a whole, is generic enough for decision-makings with a novel systematic approach concept using appropriate database. Accordingly, the research deals with a particular architectural building design with efficiency and consistency features using the hierarchical expert network system described [1] Ciftcioglu O, Sariyildiz S. and Veer P. v.d., 1998 , Information Ordering for decision support in building design, D and DSS, Design and Decision Support Systems 4th International Conference on Design and Decision Support Systems in Architecture and Urban Planning, Castle Vaeshartelt, Maastricht, July 26-29, The Netherlands"

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Full text: content.pdf (519,213 bytes) (available to registered users only)

Series: w78:2000 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.analysis (0.064229) class.synthesis (0.019630) class.man-man (0.013152)
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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


Ciftcioglu O, Durmisevic S, Sariyildiz S

Soft computing in construction information technology

Abstract: Purpose: With this paper a data driven model of knowledge representation for use in construction information technology (CIT) is introduced as a novel implementation and it is effectively implemented by artificial intelligence methods. Although for CIT knowledge base systems as a general framework is available where the user can place the information. Such systems are eventually mere data warehouses or in a more sophisticated form they are decision support systems in the form of rule based expert systems. However, in the case of a framework structure to organise the knowledge base is difficult and cumbersome task to establish an effective product. In the case expert systems, the inference is deductive and therefore the effectiveness of the system is limited to the prescribed rules. Therefore in place of high level data base management software like Prolog ©, the integration of new computational information processing methods and technologies into CIT would be much informative and therefore they are much effective and finally desirable. From the viewpoint of computation, CIT the data are rather soft requiring special methods and techniques to deal with. In this respect, computational intelligence is one of the emerging technologies, which provides CIT with ample possibilities and techniques for the enhancement of CIT products. Computational intelligence is a part of artificial intelligence (AI) and can be defined as a branch of soft computing methodologies including Expert Systems, Fuzzy Logic, Artificial Neural Networks and Evolutionary Computation. Methodology: For the CIT data soft computing methods are invoked. Soft Computing is an emerging approach to computing which parallels the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision. In plain terms, it is the processing of uncertain information with the methods, methodologies, and paradigms of artificial NN, fuzzy logic and evolutionary algorithms. The equivalence of neural networks and fuzzy logic applications is well established. However, the effectiveness of either method is still dependent on the application itself. Each method has its strong merits. However, in general, best performance is obtained when both methods are used in hybrid form. Especially neural system can cope with complex systems while it is relatively difficult for fuzzy systems. On the contrary, it is easier to deal with linguistic variables by fuzzy systems. Such a hybrid model is implemented in the knowledge model accomplished. Results: A novel concept of soft computing in CIT is introduced using actual building design data for design evaluation. The knowledge base contains all the local and global information and their inherent relationships among themselves. The knowledge representation is performed by means of a series of fuzzy systems having their both fuzzy input space and output space. The associations between the spaces are established by learning techniques of AI using the data at hand. Such an 'intelligent' knowledge base can make inference resulting in 'intelligent' due outcomes, which are not explicitly coded, in advance. In other words this is an inductive and computational inference for decision-making compared to conventional knowledge base systems where inference is deductive prescribed by rules. Conclusions: The soft computing in CIT is an important step for processing the relevant effectively and efficiently. In this respect, the paper describes ongoing advanced research and its verifications by actual data at hand.

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Series: w78:2001 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.analysis (0.064489) class.synthesis (0.025964) class.deployment (0.019220)
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Permission to reproduce these documents have been graciously provided by CSIR Building and Construction Technology. The assistance of the editors, Mr. Gustav Coetzee and Mr. Frances Boshoff, is gratefully appreciated.


Conheeney K, Stephenson P, Griffiths A

Issues in knowledge transfer within a construction training and learning organisation

Abstract: "Knowledge transfer with domains such as the construction industry will become increasingly important. Essentially 'transfer' involves the sharing of 'best-practice' between the minority of experienced experts and the majority of those people as recipients. Some means of capturing this information and then applying this to a problem context defines the 'knowledge' component. Three pragmatic issues to the delivery of a variable knowledge transfer system are required and should include the collection, structuring and transferring of information. This paper identifies the issues concerned and the need to establish solutions for a construction training and learning organisation. Particular issues addressed include indexing and the use of XML language for the interchange and sharing of data, and the capture of XML structures within a relational schema for comparisons and queries. Additionally, mechanisms for establishing navigational trails are considered with neural networking for the building of knowledge domain structures for continued extension and navigation in knowledge transfer. The need to take into account organisational and market culture is significant to provide value information and the trade of information. The issues highlighted and discussed indicate a need for manual (human) and automated (neural) processing for the collection, structuring and transfer of information to promote the learning organisation concept, and to provide the opportunity for knowledge utilisation within an organisational environment."

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Series: w78:2000 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.bestPractise (0.171597) class.education (0.135365) class.analysis (0.042236)
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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


Costa F

The S:ITEC model: An integrated system of treatment of data and knowledge in construction

Abstract: Recently, in the field of Computer Aided Design (CAD), notable efforts have been made with theoretical results largely unproven due mainly to the difficulties of the large scale production required. On the other hand, other applications of an excessively practical nature have been developed which, however, present a high degree of difficulty in bringing about their integration. In the first case we would include, for example, representational Models and Classification Systems andin the second case the various CAD systems as well as the partial integration work carried out although often at a high level of specialization. This work means that, although each time we get nearer to reaching the goal where all these efforts would coincide, no concrete systemadaptable to the majority of models proposed has really yet been put forward or used for the various applications developed. A system whichwould meet these needs must do so in a single, integral manner (whicheven could be standardized in the most universal way possible) so that finally-the user could at any moment control in real time each and every one of the various decisions which must be taken along the difficult design path, understood as the process of conception. In order to achieve these objectives, what becomes fundamental is the adequate treatment of the various methods and elements on which we depend, in order to carry out our task so that, in some way or other, we can simplifyand reduce them to two single elements: Data and Knowledge. While it is certain that in the first case there is almost complete coincidenceamong most of the existing proposals in various parts of the world, in the second case there exists a wide range of approaches as well as arelative lack of concretion. The SITEC model (Integrated System for Treatment of Construction Elements), a research project being developedby the Catalan Institute of Construction Technology, is shown to be capable of providing the necessary integrat

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Series: w78:1992 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.synthesis (0.028882) class.impact (0.010540) class.analysis (0.008722)
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Permission to reproduce these papers has been graciously provided by Research Press of the National Research Council of Canada. The support of the editor, Dr. Dana Vanier, is gratefully appreciated.


Craig R. Dubler, John I. Messner

Evaluating the Value of Early Planning for Building Information Modeling using Lean Theory

Abstract: Building Information Modeling (BIM) provides a means for owners, designers, contractors, and operators to generate, organize and use detailed information throughout a project lifecycle. An important aspect to the success of BIM is the process in which information is exchanged between team members. In a theory, information should be both accessible and usable, when required. Because the AEC industry is project centered, and several companies work collaboratively towards the design and construction of a facility, the availability and accuracy of information can become constrained. BIM has the potential to improve the effectiveness of building design and construction; however, if the information exchange process is not planned early in the project, the benefits of using the authored data may be mitigated by process waste. This paper serves to evaluate the value associated with early team planning for BIM on two projects being constructed on the Penn State University campus; one which implemented a BIM planning procedure in the design phase. The rationale behind lean theory is to increase efficiency by eliminating waste, consequently increasing value. Therefore, lean principles were modified to establish categories of building information exchange waste. During the case study process actual information exchanges were captured using a process mapping technique. Once the information exchange process was documented, the data was analyzed using the seven types of waste: overproduction, inventory, extra processing, motivation, defects, waiting, and transportation. When applied to information management, these concepts provide a broad framework for an effective process for standardization. Future work includes analyzing the project and team traits for relationships with the information exchange waste. This information will provide additional insight to the value of early planning for Building Information Modeling by documenting the economic benefits that may be achieved by the industry if the information exchange process is developed early in design.

Keywords: BIM, Lean Thinking, Information Exchange, Knowledge Management

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Series: w78:2010 (browse)
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Cutting-Decelle AF

Standardization in product and process data modelling : the ISO step and mandate standards' contribution to'the integration of the life-cycle of buildings

Abstract: In this paper, the data exchanges during the construction process will be analysed through the presentation of the specificity of the profession, -and the description of the construction process, by means of the merent related models. We will then present the two standards, STEP and MANDATE, both currently under development, first in their main features, then by the concepts they will be able to provide. We will focus on a presentation of MANDATE, since one of the models provided could be useful for the representation of the life cycle of buildings. This paper will end with some perspectives for the building construction domain, based on the integration of the whole construction process.

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Full text: content.pdf (1,962,640 bytes) (available to registered users only)

Series: w78:1995 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.represent (0.049820) class.processing (0.023990) class.standards (0.019855)
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Permission to reproduce these papers has been graciously provided by the Stanford University, USA. The support of the editors, particularly Prof. Fischer is gratefully appreciated.


D Browne, K Menzel

Method for Validation of Building Simulation Results using Sensor Data

Abstract: In general, current Building Energy Simulation Tools are used for pre-construction design and comparison of designs rather than a full exact varying representation of reality. To provide the best level of detail full CFD analysis for the entire building would be required. However this is currently by far outside the scope of current computing power for a building energy system. Because these simulation tools are designed for comparison of potential designs and because of the difficulty in predicting occupant behaviour, very often the predicted results do not correlate with the real actual performance when buildings are in operation. From project experience encountered in the EU FP7 IntUBE project, a deficit has been encountered whereby the correlation between simulation results and real measured data is not entirely accurate. This paper discusses a method of validation, which will provide a means of comparing measured data (e.g. sensors and weather data), and simulated data (e.g. near future simulations). This method for validation of building simulation results initially involves a comparison of data from building simulation and respective measured sensor readings. From this comparison, value is added from correction of simulation results, and/or input to simulation parameters. Further worth can also be provided by gaining knowledge for creation of simulation profiles which are difficult to predict before construction & operation. Additional value can also be derived from identifying conditions of poor results and relevant factors which can be corrected. Simulation data and actual data is available from a housing unit in Barcelona Spain and research building in Cork Ireland.The expected result to be derived from this method is to give an indication of quality of simulated data results and provide feedback. If the difference between simulated and real data is too large, steps to improve results will be suggested. In future it is envisioned that automated adjustments may performed to simulation inputs to correct results. Aside from near future simulation validation, the tool may be able to provide long term commissioning feedback to detect and alert users to long term degradation of systems and possible maintenance or repair remedies.

Keywords: Simulation, Data Modelling, Validation

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Series: w78:2011 (browse)
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Daum S,Borrmann A

Checking spatio-semantic consistency of building information models by means of a query language

Abstract: One of the characteristic features of object-based Building Information Models is the close integration of geometric and semantic information into one model. This concept is thoroughly implemented by the Industry Foundation Classes (IFC), a comprehensive data model designed to provide a sound foundation for complex data exchange scenarios. Besides the provision of a large variety of data types for capturing the semantics of building elements and spaces, the IFC also makes it possible to define relationships between building elements and/or spaces, respectively. In particular, a spatial aggregation hierarchy can be modeled by successively applying the relationship IfcRelAggregates to space objects. However, no validation options currently exist to check whether the semantically defined aggregation hierarchy complies with the geometric setup of the individual spaces and building elements. This lack of consistency between the semantic and the geometric part of the BIM model may lead to serious data interpretation errors at the receiving end. To prevent this, we propose a new method for validating spatio-semantic consistency based on the usage of the Query Language for Building Information Models (QL4BIM) which on the one hand provides a means of accessing the IFC object model and on the other hand provides high-level spatial operators, such as Disjoint, Touching and Containing. The formulation of corresponding queries makes it possible to verify the spatio-semantic consistency of the IFC model. The paper discusses application scenarios and provides a number of relevant examples.

Keywords: BIM,IFC,Topology,Validation,Consistency,Spatial Relationships

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Series: convr:2013 (browse)
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Davide Simeone and Stefano Cursi

A Platform for Enriching BIM Representation Through Semantic Web Technologies

Abstract: This paper investigates the possibilities related to BIM representation enrichment through semantic web approaches, and presents a prototypal application oriented to the integration of the informative model of the building with a knowledge base developed by means of ontologies. Its scope is to enhance the semantic level of representation of building information models, as well as enlarging the representation spectrum including knowledge not directly representable in the BIM schema.

Keywords: Building Information Modelling, Semantic Enrichment, Ontologies, Building Design, BIM Database

DOI: https://doi.org/10.24928/JC3-2017/0323

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