We construct a provably secure mix-net from any CCA2 secure cryptosystem. The mix-net is secure against active adversaries that statically corrupt less than λ out of k mix-servers, where λ is a threshold parameter, and it is robust provided that at most min(λ− 1, k − λ) mix-servers are corrupted. The main component of our construction is a mix-net that outputs the correct result if all mix-serv...

We present a new type of probabilistic model which we call DISsimilarity COefficient Networks (DISCO Nets). DISCO Nets allow us to efficiently sample from a posterior distribution parametrised by a neural network. During training, DISCO Nets are learned by minimising the dissimilarity coefficient between the true distribution and the estimated distribution. This allows us to tailor the training...

a critical protection requirement for grid connected distributed generators (dg) is anti-islanding protection. in this paper, a new islanding detection method for any possible network loading is proposed based on utilizing and combining various system parameter indices. in order to secure the detection of islanding, eight intentional disturbances are imposed to the system under study in which t...

The generation of a pleasant pitch contour is an important issue for the naturalness of each TTS system. Till now the results are far from being satisfactory. In this paper we present a speakerand task specific approach realized by a neural network. Personal and task specific characteristics are maintained and the demand of gcneralization decreases. So the results in application can signilicant...

Please cite this article in press as: Moridis, C. N network-based method. Computers & Education Building computerized mechanisms that will accurately, immediately and continually recognize a learner’s affective state and activate an appropriate response based on integrated pedagogical models is becoming one of the main aims of artificial intelligence in education. The goal of this paper is to d...

as is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. weibull distribution involves in reliability studies frequently and has many applications in engineering. however estimating the parameters of weibull distribution is crucial in classical ways. this distribution has t...

Model based learning systems usually face to a problem of forgetting as a result of the incremental learning of new instances. Normally, the systems have to re-learn past instances to avoid this problem. However, the re-learning process wastes substantial learning time. To reduce learning time, we propose a novel incremental learning system, which consists of two neural networks: a main-learnin...

fouling is one of the main parameters in design of any exchanger. ignoring this parameter causes problems such as overheating or under- heating of process streams. in this article a heat exchanger network was designed using process streams data in cdu of tehran refinery. then using tema fouling factors, network exchangers were designed and area and cost were estimated. by changing fouling facto...