The control of multi-agent systems, including multi-robot systems, requires some level of context and environment awareness as well as interaction among the interworked cognitive entities, whether they are artificial or natural. Proper specification of the cognitive functionalities and of the corresponding interfaces helps in achieving the capability to reach interoperability across different o...

We describe ongoing efforts towards and challenges in using an Example-Based Machine Translation (EBMT) system in the context of a multi-national, multi-university and multi-agency transnational digital government project. The project is aimed at applying information technology to the problem of collecting and sharing information securely in a multilingual context. We report on a number of issu...

We consider a single-machine scheduling problem with a multi-level product structure. Setups are required if the machine changes production from one product type to another, and the scheduling decision must satisfy dynamic demand. We propose a lotsizing as well as a scheduling model, and we compare solution procedures for both models on a small set of instances. The multi-level structure compli...

Following paper is focused on the computational intelligence algorithm Multi-Kernel Support Vector Machine application in the cognitive supervision of the robotic system for crisis and disaster management. The robots’ platforms applied for inspection and intervention are shown. The idea of cognitive supervision of the robotic system is presented. The idea of building cognitive map using Multi –...

In this paper, we introduce a new method of designing Venn Machine taxonomy based on Support Vector Machines and k-means clustering for both binary and multi-class problems. We compare this algorithm to some other multi-probabilistic predictors including SVM Venn Machine with homogeneous intervals and a recently developed algorithm called Venn-ABERS predictor. These algorithms were tested on a ...

This paper concerns the optimization and coordination of the conventional FACTS (Flexible AC Transmission Systems) damping controllers in multimachine power system. Firstly, the parameters of FACTS controller are optimized. Then, a hybrid fuzzy logic controller for the coordination of FACTS controllers is presented. This coordination method is well suitable to series connected FACTS devices lik...

Extending phrase-based Statistical Machine Translation systems with a second, dynamic phrase table has been done for multiple purposes. Promising results have been reported for hybrid or multi-engine machine translation, i.e.\ building a phrase table from the knowledge of external MT systems, and for online learning. We argue that, in prior research, dynamic phrase tables are not scored optimal...

-A real time power system simulator has been developed in the Matlab/Simulink environment for testing the prototypes of advanced power system stabilizers and also of the other controllers of new types of energy storage devices such as the Energy Capacitor System composed of electrical double-layer capacitors. The real time transient stability simulations are available on the proposed simulator ...

In this paper, we study how humans perceive the use of images as an additional knowledge source to machine-translate usergenerated product listings in an e-commerce company. We conduct a human evaluation where we assess how a multi-modal neural machine translation (NMT) model compares to two text-only approaches: a conventional state-of-the-art attention-based NMT and a phrase-based statistical...

A novel approach of decoding convolutional codes using a multi-class support vector machine is presented in this paper. Support vector machine is a recently developed and well recognized algorithm for constructing maximum margin classifiers. Unlike traditional adaptive learning approaches such as a multi-layer neural network, it is able to converge to a global optimum solution, hence achieving ...