36 resultados para international construction joint venture


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Mobile technology has not yet achieved widespread acceptance in the Architectural, Engineering, and Construction (AEC) industry. This paper presents work that is part of an ongoing research project focusing on the development of multimodal mobile applications for use in the AEC industry. This paper focuses specifically on a context-relevant lab-based evaluation of two input modalities – stylus and soft-keyboard v. speech-based input – for use with a mobile data collection application for concrete test technicians. The manner in which the evaluation was conducted as well as the results obtained are discussed in detail.

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Mobile technologies have yet to be widely adopted by the Architectural, Engineering, and Construction (AEC) industry despite being one of the major growth areas in computing in recent years. This lack of uptake in the AEC industry is likely due, in large part, to the combination of small screen size and inappropriate interaction demands of current mobile technologies. This paper discusses the scope for multimodal interaction design with a specific focus on speech-based interaction to enhance the suitability of mobile technology use within the AEC industry by broadening the field data input capabilities of such technologies. To investigate the appropriateness of using multimodal technology for field data collection in the AEC industry, we have developed a prototype Multimodal Field Data Entry (MFDE) application. This application, which allows concrete testing technicians to record quality control data in the field, has been designed to support two different modalities of data input speech-based data entry and stylus-based data entry. To compare the effectiveness or usability of, and user preference for, the different input options, we have designed a comprehensive lab-based evaluation of the application. To appropriately reflect the anticipated context of use within the study design, careful consideration had to be given to the key elements of a construction site that would potentially influence a test technician's ability to use the input techniques. These considerations and the resultant evaluation design are discussed in detail in this paper.

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The aim of this study is to address the main deficiencies with the prevailing project cost and time control practices for construction projects in the UK. A questionnaire survey was carried out with 250 top companies followed by in-depth interviews with 15 experienced practitioners from these companies in order to gain further insights of the identified problems, and their experience of good practice on how these problems can be tackled. On the basis of these interviews and syntheses with literature, a list of 65 good practice recommendations have been developed for the key project control tasks: planning, monitoring, reporting and analysing. The Delphi method was then used, with the participation of a panel of 8 practitioner experts, to evaluate these improvement recommendations and to establish their degree of relevance. After two rounds of Delphi, these recommendations are put forward as "critical", "important", or "helpful" measures for improving project control practice.

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This colloquium was organised by Ryuko Kubota (University of British Columbia, Canada) and Sue Garton (Aston University, UK) as part of the collaboration between the American Association for Applied Linguistics (AAAL) and TESOL International Association.

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Since wind has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safety and economics of wind energy utilization. In this paper, we investigate a combination of numeric and probabilistic models: one-day-ahead wind power forecasts were made with Gaussian Processes (GPs) applied to the outputs of a Numerical Weather Prediction (NWP) model. Firstly the wind speed data from NWP was corrected by a GP. Then, as there is always a defined limit on power generated in a wind turbine due the turbine controlling strategy, a Censored GP was used to model the relationship between the corrected wind speed and power output. To validate the proposed approach, two real world datasets were used for model construction and testing. The simulation results were compared with the persistence method and Artificial Neural Networks (ANNs); the proposed model achieves about 11% improvement in forecasting accuracy (Mean Absolute Error) compared to the ANN model on one dataset, and nearly 5% improvement on another.

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The Indian economy characterized variously as a slumbering giant, powerful tiger, and the most promising market has witnessed a slowdown, occasional disturbances in the industrial relations space, and attention of the world in the last five years. In this special issue, we raise pertinent questions and present research on multiple dimensions of the dynamic and rapidly changing business environment of India. The suitability of management models and frameworks developed in the North American contexts in emerging markets like India and China is questioned. One example of how the well-established models in the literature on success of international joint ventures were insufficient to explain the success of three international joint ventures in the insurance space in India is presented as case in point. Finally, the nine papers that materially contribute to the theme of this special issue are introduced. © 2016 Wiley Periodicals, Inc.