This paper addresses the problem of detecting coherent motions in crowd scenes and subsequently constructing semantic regions for activity recognition. We first introduce a coarse-to-fine thermal-diffusionbased approach. It processes input motion fields (e.g., optical flow fields) and produces a coherent motion filed, named as thermal energy field. The thermal energy field is able to capture bo...

The interplay between risk aversion and financial derivatives has received increasing attention since the advent of electricity market liberalization. One important challenge in this context is how to develop economically efficient cost-effective models integrate renewable energy sources (RES) market, which constitutes a relatively new exciting field research. This paper proposes game-theoretic...

In this paper, we optimize user scheduling, power allocation and beamforming in distributed multiple-input multiple-output (MIMO) networks implementing user-centric clustering. We study both the coherent non-coherent transmission modes, formulating a weighted sum rate maximization problem for each; finding optimal solution to these problems is known be NP-hard. use tools from fractional program...

Clustering is the method of establishing structure within a collection of unlabeled data. Clusters are organized according to points that are similar to each other as well as different from points in other clusters. Measuring similarity entails either plotting gene expression of each experiment or measuring correlation under different parametric (Pearson or Euclidean) or non-parametric (Spearma...

Given the substitution process of generators using renewable energy sources instead of conventional generators in modern power systems, this paper proposes a Monte Carlo based method to determine an optimal level of this change. At first, LOLE index of the system was calculated without wind power to obtain the reference index. Then, the wind turbine units are replaced with the conventional gene...

The fact that clustering is perhaps the most used technique for exploratory data analysis is only a semaphore that underlines its fundamental importance. The general problem statement that broadly describes clustering as the identification and classification of patterns into coherent groups also implicitly indicates it’s utility in other tasks such as supervised learning. In the past decade and...

Many graph clustering algorithms have been proposed in recent past researches, each algorithm having its own advantages and drawbacks. All these algorithms rely on a very different approach so it’s really hard to say that which one is the most efficient and optimal if we talk in the sense of performance. It is really hard to decide that which algorithm is beneficial in case of highly complex ne...

A coherent presentation of an n-category is a by generators, relations and among relations. Confluent terminating rewriting systems generate presentations, whose are defined confluence diagrams critical branchings. This article introduces procedure to compute presentations when the rewrite modulo set axioms. Our coherence results formulated using structure n-categories enriched in double groupo...