In this paper, we propose an effective global relation learning algorithm to recommend appropriate location of a building unit for in-game customization residential home complex. Given construction layout, visual context-aware graph generation network that learns the implicit relations among scene components and infers new unit. The proposed takes as input corresponding top-view depth image. It...

There has been a steady need in the medical community to precisely extract temporal relations between clinical events. In particular, information can facilitate variety of downstream applications such as case report retrieval and question answering. Existing methods either require expensive feature engineering or are incapable modeling global relational dependencies among this paper, we propose...

The performance of irrigation schemes around the world has been below expectations. assessment is an essential step towards improving agricultural water use. One primary indicators relative supply (RIS, ratio between amount delivered and crop net requirements). This study presents a worldwide analysis scheme by evaluating key attributes that influence RIS. was based on review reports scientific...

Abstract For the Fröhlich model of large polaron, we prove that ground state energy as a function total momentum has unique global minimum at zero. This implies non-existence translation invariant Hamiltonian and thus excludes possibility localization transition finite coupling.

Differential global surface impedance (DGSI) model, a rigorous approach, has been applied to the analysis of three dimensional plasmonic circuits. This model gives a global relation between the tangential electric field and the equivalent surface electric current on the boundary of an object. This approach helps one bring the unknowns to the boundary surface of an object and so avoid volumetric...

Recognizing genes with distinctive expression levels can help in prevention, diagnosis and treatment of the diseases at the genomic level. In this paper, fast Global k-means (fast GKM) is developed for clustering the gene expression datasets. Fast GKM is a significant improvement of the k-means clustering method. It is an incremental clustering method which starts with one cluster. Iteratively ...