Social media accounts are valuable for hackers for spreading phishing links, malware and spam. Furthermore, some people deliberately hack an acquaintance to damage his image. In this paper, a classification model is described for detecting these hacked Twitter accounts by examining changing features in behaviour. We look at changes in language, source, URL, retweets, frequency and time. Our mod...

Micro-array data has enabled us to obtain an overview of the cell by measuring the expression levels of thousands of genes simultaneously. It has also opened the possibility for predicting possible cancerous cells accurately. Since these data sets are very large, we need to utilize machine learning techniques to analyse them efficiently. However, micro-array data also poses challenging problems...

Meta-heuristic algorithms are applied in optimization problems in a variety of fields, including engineering, economics, and computer science. In this paper, seven population-based meta-heuristic algorithms are employed for size and geometry optimization of truss structures. These algorithms consist of the Artificial Bee Colony algorithm, Cyclical Parthenogenesis Algorithm, Cuckoo Search algori...

We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) with the least squares temporal difference (LSTD) algorithm, LSTD(λ), in an exploration-enhanced learning context, where policy costs are computed from observations of a Markov chain different from the one corresponding to the policy under evaluation. We establish for the discounted cost criter...

Oil production from tight oil reservoirs has become economically feasible because of the combination horizontal drilling and multistage hydraulic fracturing. Optimal fracture design plays a critical role in successful economical reservoir. However, many complex parameters such as spacing half-length make fracturing treatments costly uncertain. To improve design, it is essential to determine rea...

this paper proposes an optimized control policy over type one diabetes. type one diabetes is taken into consideration as a nonlinear model (augmented minimal model), which is implemented in matlab-simulink. this model is developed in consideration of the patient's conditions. there are some uncertainties in the regarded model due to factors such as blood glucose concentration, daily meals ...

We present an algorithm that achieves general syndrome decoding of a (n; k; r) linear rank distance code over GF(q m) in O((nr + m) 3 q (m?r)(r?1)) elementary operations. As a consequence, the cryptographic Al schemes Che94, Che96] which rely on this problem are not secure with the proposed parameters. We also derive from our algorithm a bound on the minimal rank distance of a linear code which...