160 research outputs found

    Existence of Nontrivial Solutions for p-Laplacian Equations in {R}^{N}

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    In this paper, we consider a p-Laplacian equation in {R}^{N}with sign-changing potential and subcritical p-superlinear nonlinearity. By using the cohomological linking method for cones developed by Degiovanni and Lancelotti in 2007, an existence result is obtained. We also give a result on the existence of periodic solutions for one-dimensional pp-Laplacian equations which can be proved by the same method.Comment: 19 pages, submitte

    Recent global trends in the Chinese construction industry and its market

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    The rapidly increasing construction demand in China, particularly spurred by the coming 2008 Beijing Olympic Games and the 2010 Shanghai Expo, provides challenging opportunities for overseas construction enterprises. Therefore understanding the structure and dynamics of construction industry in China is crucial, particularly the potential changes of the market after the China\u27s entry into the World Trade Organization. This paper analyses the development of construction economics and institutional regulations in the construction market, and provides a comprehensive image on the Chinese construction sector in the global environment.<br /

    Evolutionary multiobjective optimization in engineering management: an empirical application in infrastructure systems

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    Generally multiple objectives exist in transportation infrastructure management, such as minimum cost and maximum service capacity. Although solution methoak of multiobjective optimization problems have undergone continual development over the part several decades, the methods available to date are not particularly robust, and none of them perform well on the broad classes. Because genetic algorithms work with apopulation ofpoints, they can capture a number of solutions simultaneously, and easily incorporate the concept of a Pareto optimal set in their optimization process. In this paper, a genetic algorithm is modified to deal with an empirical application for the rehabilitation planning of bridge decks, at a network level, by minimizing the rehabilitation cost and deterioration degree simultaneously

    Market effects on forecasting construction prices using vector error correction models

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    Construction price forecasting is an essential component to facilitate decision-making for construction contractors, investors and related financial institutions. Construction economists are increasingly interested in seeking a more analytical method to forecast construction prices. Although many studies have focused on construction price modelling and forecasting, few have considered the impacts of large-scale economic events and seasonality. In this study, an advanced multivariate modelling technique, namely the vector correction (VEC) model with dummy variables, was employed. The impacts of global economic events and seasonality are factored into the model to forecast the construction price in the Australian construction market. Research findings suggest that both long-run and dynamic short-term causal relationships exist among the price and levels of supply and demand in the construction market. These relationships drive the construction price and supply and demand, which interact with one another as a loop system. The reliability of forecasting models was examined by the mean absolute percentage error (MAPE) and the Theil\u27s inequality coefficient U tests. The test results suggest that the conventional VEC model and the VEC model with dummy variable are both acceptable for forecasting the construction price, while the VEC model considering external impacts achieves higher prediction accuracy than the conventional VEC model. &copy; 2014 &copy; 2014 Taylor &amp; Francis

    Critical operational management in international construction

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    The construction activities of a contractor may physically take place in the home country or overseas, and the latter, particularly of a large company, has an increasing proportion with the globalisation. Globalisation of the construction industry and its market is a trend in every country, Which increases the opportunities of both international construction, and competition or collaboration with foreign construction companies. International construction project management is undertaken in a complicated circumstance, and requires a synthetic management approach. This research aims to establish a primary framework for the critical operational management in achieving international construction projects in a novel construction market.<br /

    A comparative study on economic factors of construction industries in Australia and China

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    The construction sector produces the facilities needed for a large majority of the production of goods and services, in which a sizeable proportion of Gross Domestic Product is generated. Recent trends in the globalisation of construction markets indicate that many countries consider construction industry competitiveness as crucial, and are working to increase construction productivity, in particular where the construction industries play an important role in their economic development. This paper first points out the research importance in international construction. Based on economic analyses of construction industries, a study is then carried out to focus on the economic sizes and benefits of the Chinese construction industry and to compare them with the Australian construction industry. Results derived from such an international construction comparison will assist in the Australian construction communities understanding the construction markets and industries in China and will benefit in international construction participation and cooperation.<br /

    Towards Label-free Scene Understanding by Vision Foundation Models

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    Vision foundation models such as Contrastive Vision-Language Pre-training (CLIP) and Segment Anything (SAM) have demonstrated impressive zero-shot performance on image classification and segmentation tasks. However, the incorporation of CLIP and SAM for label-free scene understanding has yet to be explored. In this paper, we investigate the potential of vision foundation models in enabling networks to comprehend 2D and 3D worlds without labelled data. The primary challenge lies in effectively supervising networks under extremely noisy pseudo labels, which are generated by CLIP and further exacerbated during the propagation from the 2D to the 3D domain. To tackle these challenges, we propose a novel Cross-modality Noisy Supervision (CNS) method that leverages the strengths of CLIP and SAM to supervise 2D and 3D networks simultaneously. In particular, we introduce a prediction consistency regularization to co-train 2D and 3D networks, then further impose the networks' latent space consistency using the SAM's robust feature representation. Experiments conducted on diverse indoor and outdoor datasets demonstrate the superior performance of our method in understanding 2D and 3D open environments. Our 2D and 3D network achieves label-free semantic segmentation with 28.4% and 33.5% mIoU on ScanNet, improving 4.7% and 7.9%, respectively. And for nuScenes dataset, our performance is 26.8% with an improvement of 6%. Code will be released (https://github.com/runnanchen/Label-Free-Scene-Understanding)