In this study, a new method for designing the damping controller was proposed to improve the transient power system stability in a single machine network connected to an infinite bus. The STATCOM controller problem in a wide area of the system function was considered as an optimization problem with multi-purpose objective function. Also, the Honey Bee Mating Optimization Algorithm was used to d...

In the present study, the effect of material and process parameters on the morphological and hardness properties of friction stir process (FSP) acrylonitrile butadiene styrene (ABS) were investigated. For this purpose, firstly ABS polymeric sheets were injection molded. Then a slot with predetermined depth and width was created on sheets using a horizontal milling machine. Nano type (nanoclay, ...

Natural disasters, such as earthquakes, tsunamis, and hurricanes cause enormous harm during each year. To reduce casualties and economic losses in the response phase, rescue units must be allocated and scheduled efficiently, such that it is a key issues in emergency response. In this paper, a multi-objective mix integer nonlinear programming model (MOMINLP) is proposed to minimize sum of weight...

Minimizing job scheduling time is a fundamental issue in data center networks that has been extensively studied in recent years. The incoming jobs require different CPU and memory units, and span different number of time slots. The traditional solution is to design efficient heuristic algorithms with performance guarantee under certain assumptions. In this paper, we improve a recently proposed ...

Multi-machine scheduling, that is, the assigment of jobs to machines such that certain performance demands like cost and time effectiveness are fulfilled, is a ubiquitous and complex activity in everyday life. This paper presents an approach to multi-machine scheduling that follows the multiagent learning paradigm known from the field of Distributed Artificial Intelligence. According to this ap...

Multi-instance multi-label learning is a learning framework, where every object is represented by a bag of instances and associated with multiple labels simultaneously. The existing degeneration strategy-based methods often suffer from some common drawbacks: (1) the user-specific parameter for the number of clusters may incur the effective problem; (2) SVM may bring a high computational cost wh...

We propose a method for simultaneously translating from a single source language to multiple target languages T1, T2, etc. The motivation behind this method is that if we only have a weak language model for T1 and translations in T1 and T2 are associated, we can use the information from a strong language model over T2 to disambiguate the translations in T1, providing better translation results....

Support Vector Machine (SVM) is originally proposed as a binary classification model with achieving great success in many applications. In reality, it is more often to solve a problem which has more than two classes. So, it is natural to extend SVM to a multi-class classifier. There have been many works proposed to construct a multi-class classifier based on binary SVM, such as one versus rest ...