Mechanisms for overcoming semantic heterogeneity in diverse information sources are critical components of any interoperable system. In the case of diverse geographic information sources, such mechanisms present particular difficulties since the semantic structure of geographic information cannot be considered independently of its spatial structure. This paper develops an approach to the integr...

We deal with a wide range of colors in our daily life. They are such ubiquitous phenomena that is hard and next to impossible to imagine even a single entity (be it an object, place, living creature, etc) devoid of them. They are like death and tax which nobody can dispense with. This omnipresence of colors around us has also made its way through abstract and less tangible entities via the inte...

In this paper, we present a novel framework for detecting individual trees in densely sampled 3D point cloud data acquired in urban areas. Given a 3D point cloud, the objective is to assign point-wise labels that are both class-aware and instance-aware, a task that is known as instance-level segmentation. To achieve this, our framework addresses two successive steps. The first step of our frame...

Trajectory data play a fundamental role to an increasing number of applications, such as traffic control, transportation management, animal migration, and tourism. These data are normally available as sample points. However, for many applications, meaningful patterns cannot be extracted from sample points without considering the background geographic information. In this paper we present a fram...

background: adult stem cells (asc) are undifferentiated cells found throughout the body. these cells are promising tools for cell replacement therapy in neurodegenerative disease. adipose tissue is the most abundant and accessible source of asc. this study was conducted to evaluate effect of selegiline on differentiation of adipose-derived stem cells (adsc) into functional neuron-like cells (nl...

State-of-the-art methods in automatic summarization rely almost exclusively on extracting salient sentences from input texts. Such extractive methods succeed in producing summaries which capture salient information but fail to produce fluent and coherent summaries. Recent progress in robust semantic analysis makes the application of semantic techniques to summarization relevant. We review in th...