Abstract. This paper looks at the task of computing efficient extreme points in multiple objective linear programruing. Vector maximization software is reviewed and the ADBASE solver for computing all efficient extreme points of a multiple objective linear program is described. To create MOLP test problems, models for random problem generation are discussed. In the computational part of the pap...

Smile detection is a specialized task in facial expression analysis with applications such as photo selection, user experience analysis, and patient monitoring. As one of the most important and informative expressions, smile conveys the underlying emotion status such as joy, happiness, and satisfaction. In this paper, an efficient smile detection approach is proposed based on Extreme Learning M...

High Performance Computing (HPC) systems are equipped with a massive number of processors, high-bandwidth networks, large capacity fast storage, and specialized parallel software to provide answers to challenging scientific and engineering questions. Over the past decades, data generation capabilities in these domains have grown rapidly due to the emergence of large-scale instruments such as te...

Cross efficiency is a method with the idea of peer evaluation instead of self-evaluation, and is used for evaluation and ranking Decision Making Units (DMUs) in Data Envelopment Analysis (DEA). Unlike most existing DEA ranking models which can only rank a subset of DMUs, for example non-efficient or extreme efficient DMUs, cross efficiency can rank all DMUs, even non-extreme ones. However, sinc...

<span>Distributed systems and extreme-scale are ubiquitous in recent years have seen throughout academia organizations, business, home, government sectors. Peer-to-peer (P2P) technology is a typical distributed system model that gaining popularity for delivering computing resources services. Distributed try to increase its availability the event of frequent component failures functioning ...

Memory is a key computational bottleneck when solving large-scale convex optimization problems, such as semidefinite programs (SDPs). In this paper, we focus on the regime in which storing an $n\times n$ matrix decision variable prohibitive. To solve SDPs regime, develop randomized algorithm that returns random vector whose covariance near-feasible and near-optimal for SDP. We show how to by mo...

One of the difficulties of Data Envelopment Analysis(DEA) is the problem of deciency discriminationamong efficient Decision Making Units(DMUs) and hence, yielding large number of DMUs as efficientones. The main purpose of this paper is to overcome this inability. One of the methods for rankingefficient DMUs is minimizing the Coefficient of Variation (CV) for inputs-outputs weights. In this pape...

In this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (DMUs) in stochastic data envelopment analysis (DEA) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. It is shown that this deterministic model can be converted to a quadratic programming model. So fa...

Currently more and more agents are involved in human routine activities and a mixed human-agent society is thus formed by the humans and the agents involved. The relationship between humans and agents in this mixed society is subtle and it is vital to explore the influence that agents bring into the society. In this paper, we try to investigate a few questions: will humans act differently towar...

Let X1,X2, . . . , be independent random variables with EXi = 0 and write Sn = ∑ n i=1 Xi and V 2 n = ∑ n i=1 X i . This paper provides an overview of current developments on the functional central limit theorems (invariance principles), absolute and relative errors in the central limit theorems, moderate and large deviation theorems and saddle-point approximations for the self-normalized sum S...