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Jiao Y.,Fudan University | Jiao Y.,Shanghai Ruanzhong Information Technology Co. | Zhang S.,Shanghai Ruanzhong Information Technology Co. | Li Y.,Tongji University | And 2 more authors.
Automation in Construction | Year: 2013

Huge progress has been made on 'Augmented Reality' (AR) techniques such as registration, tracking, and display hardware. However, a construction AR system should be more convenient and combined with in-use applications to support multi-disciplinary users throughout construction lifecycle. This paper presents a video-based on-line AR environment and a pilot cloud framework. The contribution lies in two aspects: firstly, an environment utilizing web3D is demonstrated, in which on-site images are rendered to box nodes and registered with virtual objects through a three-step method; secondly, it is further extended to be "cloud" through federation of BIM (building information modeling) and BSNS (business social networking services). Technical solutions to key issues such as authoring, publishing, and composition are designed. The proposed environment is seamlessly integrated into in-use information systems and therefore enjoys greater usability. Implementations demonstrate how this framework and environment work. Although preliminary, it is conclusive for proof of concept. © 2012 Elsevier B.V.


Jiao Y.,Fudan University | Li Y.,Shanghai Ruanzhong Information Technology Co. | Wang Y.,Shanghai Ruanzhong Information Technology Co.
Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014 | Year: 2014

Lifecycle and effective dada management has become and still remains a difficult task in architecture, engineering, and construction domain. Recently, the emerging Building Information Modeling (BIM) gains more and more momentum in construction data presenting, processing, and sharing. With precise 3D digital geometry graphs, BIM has the potential to integrate diverse data from construction phases (design, construction, maintenance) and therefore becomes a promising collaboration platform for involved personnel. High efficiency BIM model processing is one of the critical issues for construction industry to truly embrace BIM technology. However, this topic has been rarely studied compared with other issues in BIM research. This paper presents an augmented version of MapReduce (MR), the popular distributed parallel computing model, to solve this problem. The main contribution lies in two points: 1) BIM models are extracted into uneven partitions according to construction domain features, followed by a specifically designed pre-process mechanism, which solves the unsuitability of classical MR's even blocking in construction domain and further greatly improves performance; 2) process and thread level parallel computing techniques are introduced into MR in single node to form a two-tier hybrid parallel architecture, which is more adaptive to BIM's massive graphical data processing. The proposed framework has been successfully used in real business applications of project quantity computation and BIM model collision detection. Experiment result from lab environment proves its efficiency and usability. © 2014 IEEE.


Jiao Y.,Fudan University | Jiao Y.,Shanghai Ruanzhong Information Technology Co. | Wang Y.,Shanghai Ruanzhong Information Technology Co. | Zhang S.,Shanghai Ruanzhong Information Technology Co. | And 3 more authors.
Advanced Engineering Informatics | Year: 2013

The problem of data integration throughout the lifecycle of a construction project among multiple collaborative enterprises remains unsolved due to the dynamics and fragmented nature of the construction industry. This study presents a novel cloud approach that, focusing on China's special construction requirements, proposes a series of as-built BIM (building information modeling) tools and a self-organised application model that correlates project engineering data and project management data through a seamless BIM and BSNS (business social networking services) federation. To achieve a logically centralised single-source data structure, a unified data model is constructed that integrates two categories of heterogeneous databases through the adoption of handlers. Based on these models, key technical mechanisms that are critical to the successful management of large amounts of data are proposed and implemented, including permission, data manipulation and file version control. Specifically, a dynamic Generalised List series is proposed to address the sophisticated construction file versioning issue. The proposed cloud has been successfully used in real applications in China. This research work can enable data sharing not only by individuals and project teams but also by enterprises in a consistent and sustainable way throughout the life of a construction project. This system will reduce costs for construction firms by providing effective and efficient means and guides to complex project management, and by facilitating the conversion of project data into enterprise-owned properties.© 2012 Elsevier Ltd. All rights reserved.


Jiao Y.,Fudan University | Li L.,Shanghai Key Laboratory of Software Testing and Evaluation | Ye N.,Shanghai Ruanzhong Information Technology Co.
Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2011 | Year: 2011

Cloud computing has become an emerging new computing paradigm. However, the issue of providing complex enterprise product family cloud is not well addressed so far. This article presents a framework featuring an in-depth extension to WSDL and an application oriented semi-automation semantic web service composition algorithm to solve the problem. The extension captures critical factors required by real world service composition scenario. The algorithm presents a complete step set which effectively addresses real application issues in service composition. The presented framework has been applied in three real business applications. Statistical software engineering data verifies its efficiency and applicability on solving the major challenges in complex enterprise product family cloud. © 2011 IEEE.


Jiao Y.,Fudan University | Jiao Y.,Shanghai Key Laboratory of Software Testing and Evaluation | Jiao Y.,Shanghai Ruanzhong Information Technology Co. | Wang Y.,Shanghai Ruanzhong Information Technology Co. | And 2 more authors.
Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2012 | Year: 2012

The intrinsic construction project nature of one-of-a-kind and the requirement of massive data exchange make collaboration one of the critical factors towards success. However, due to the complexity of multiple phases and multi-disciplinary participants in project life cycle, industry level collaboration in Architecture, Engineering, and Construction (AEC) sector remains a challenge. This paper proposes an integrated solution based mainly on social network services (SNS) and cloud computing. We present a novel platform named Construction Business Social Network Service (CBSNS), which is promising to be adopted as an industrial scope collaboration cloud. We describe its main functions as well as its privacy control mechanism. To better support its deployment as a community cloud, a three-pass load balance algorithm is proposed. The first pass sorts initial virtual machines (VMs) and physical machines (PMs) using bubble algorithm, during which parameters such as hungry threshold are considered. The second pass builds mappings between allocable PM queue and requesting VM queue using first come first served strategy, and groups Non-allocable VMs after designated time slice. The third pass handles possible exceptions when finally such ones existing. The actual time complexity of the algorithm is O(n). While the commercial implementation of the algorithm is ongoing, the proposed CBSNS has been developed and used in real life application. © 2012 IEEE.


Jiao Y.,Fudan University | Jiao Y.,Shanghai Key Laboratory of Computer Software Testing and Evaluating | Jiao Y.,Shanghai Ruanzhong Information Technology Co. | Li L.,Shanghai Ruanzhong Information Technology Co. | Ye N.,Shanghai Ruanzhong Information Technology Co.
Proceedings of the 2010 14th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2010 | Year: 2010

The demand for quickly delivering robust enterprise applications has increasingly become a business imperative today. Semantic web technologies have received much interest due to their prospect in facilitating seamless legacy system integration in support of new functionality development. In this article, we present a team collaboration oriented development framework (SSC-I) for designing and developing enterprise applications by applying technologies and methodologies offered by software engineering, Web 2.0(AJAX), and semantic web technologies, together with a set of semantic tools to facilitate both the integration of heterogeneous relational databases and reuse of software functionalities. We adopt a component-based and lightweight framework aims at flexibly interleaving manual labor and automated functionality in environments where annotations are incomplete and even inconsistent. An initial version of this framework has been implemented and applied in SSTAMS Project. © 2010 IEEE.


Zhang Y.,East China University of Science and Technology | Wang Y.,Shanghai Ruanzhong Information Technology Co. | Jin J.,East China University of Science and Technology | Wang X.,East China University of Science and Technology
International Journal of Neural Systems | Year: 2016

Effective common spatial pattern (CSP) feature extraction for motor imagery (MI) electroencephalogram (EEG) recordings usually depends on the filter band selection to a large extent. Subband optimization has been suggested to enhance classification accuracy of MI. Accordingly, this study introduces a new method that implements sparse Bayesian learning of frequency bands (named SBLFB) from EEG for MI classification. CSP features are extracted on a set of signals that are generated by a filter bank with multiple overlapping subbands from raw EEG data. Sparse Bayesian learning is then exploited to implement selection of significant features with a linear discriminant criterion for classification. The effectiveness of SBLFB is demonstrated on the BCI Competition IV IIb dataset, in comparison with several other competing methods. Experimental results indicate that the SBLFB method is promising for development of an effective classifier to improve MI classification. © 2016 World Scientific Publishing Company


Zhang Y.,East China University of Science and Technology | Jin J.,East China University of Science and Technology | Wang X.,East China University of Science and Technology | Wang Y.,Shanghai Ruanzhong Information Technology Co.
6th International Conference on Information Science and Technology, ICIST 2016 | Year: 2016

Motor imagery is usually hard to be classified with a high accuracy, since the task-related electroencephalogram (EEG) responses are likely to be contaminated by some ongoing noises. Design of an efficient classifier is considerably important for the realization of a brain-computer interface (BCI) system based on motor imagery. This study introduces a Bayesian extreme learning machine (BELM) based method for accurate classification of motor imagery. By combing ELM and Bayesian inference, BELM achieves the smallest norm of output weights with automatically estimated regularization for alleviating the possible overfitting during calibration procedure. Effectiveness of the BELM-based method is validated on a public BCI dataset, in comparison with other two competing methods. © 2016 IEEE.

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