The neighborhood has had a long history in Iranian urbanization. Since urban plans wereintroduced by the authorities to shape urban development in Iran half a century ago, the concept of Iranian traditional neighborhood has been neglected gradually. The concept of neighborhood has not found the appropriate status in urban design and planning yet. One of the main reasons is that academics, profe...

First-stage feature computation and data rate reduction play a crucial role in an efficient visual information processing system. Hardware-based first stages usually win out where power consumption, dynamic range, and speed are the issue, but have severe limitations with regard to flexibility. In this paper, the local orientation coding (LOC), a nearest neighborhood grayscale operator, is inves...

A novel algorithm called independent subspace analysis (ISA) is introduced to estimate independent subspaces. The algorithm solves the ISA problem by estimating multi-dimensional di erential entropies. Two variants are examined, both of them utilize distances between the k-nearest neighbors of the sample points. Numerical simulations demonstrate the usefulness of the algorithms.

This paper presents a simple and computationally good method for plant species recognition using leaf images. Recognition of plant images is one of the research topics of computer vision. The use of shape for recognizing objects has been actively studied since the beginning of object recognition in 1950s. Several authors suggest that object shape is more informative than its appearance properti...

Conceptual blending is an important area of research for creativity modeling. In this paper we present a creativity model that takes an existing blend and generates new blends using the nearest neighborhood replacements from a lexical ontology. For example “Artificial Intelligence” is a compounded concept comprising of “Artificiality” and “Intelligence” as two sub-concepts. After concept genera...

Collaborative Filtering (CF) is the most popular choice when implementing personalized recommender systems. A classical approach to CF is based on K-nearest-neighborhood (KNN) model, where the precondition for making recommendations is the KNN construction for involved entities. However, when building KNN sets, there exits the dilemma to decide the value of K --a small value will lead to poor r...

The instance-based k-nearest neighbor algorithm (KNN)[1] is an effective classification model. Its classification is simply based on a vote within the neighborhood, consisting of k nearest neighbors of the test instance. Recently, researchers have been interested in deploying a more sophisticated local model, such as naive Bayes, within the neighborhood. It is expected that there are no strong ...

The classical theorems of Riesz [l] on compact operators have been extended by Leray [2] and Williamson [3] to the context of topological linear spaces. Ringrose [4] has shown that if an operator on such a space is compact, the square of its adjoint is also compact, where the topology on the dual space is that of uniform convergence on bounded sets. Thus if an operator is continuous and some po...

Record linkage is an emerging research area which is required by various real-world applications to identify which records in different data sources refer to the same real-world entities. Often privacy concerns and restrictions prevent the use of traditional record linkage applications across different organizations. Linking records in situations where no private or confidential information can...