11,640 research outputs found
Modeling the Flux-Charge Relation of Memristor with Neural Network of Smooth Hinge Functions
The memristor was proposed to characterize the flux-charge relation. We propose the generalized flux-charge relation model of memristor with neural network of smooth hinge functions. There is effective identification algorithm for the neural network of smooth hinge functions. The representation capability of this model is theoretically guaranteed. Any functional flux-charge relation of a memristor can be approximated by the model. We also give application examples to show that the given model can approximate the flux-charge relation of existing piecewise linear memristor model, window function memristor model, and a physical memristor device
Data-Driven and Deep Learning Methodology for Deceptive Advertising and Phone Scams Detection
The advance of smartphones and cellular networks boosts the need of mobile
advertising and targeted marketing. However, it also triggers the unseen
security threats. We found that the phone scams with fake calling numbers of
very short lifetime are increasingly popular and have been used to trick the
users. The harm is worldwide. On the other hand, deceptive advertising
(deceptive ads), the fake ads that tricks users to install unnecessary apps via
either alluring or daunting texts and pictures, is an emerging threat that
seriously harms the reputation of the advertiser. To counter against these two
new threats, the conventional blacklist (or whitelist) approach and the machine
learning approach with predefined features have been proven useless.
Nevertheless, due to the success of deep learning in developing the highly
intelligent program, our system can efficiently and effectively detect phone
scams and deceptive ads by taking advantage of our unified framework on deep
neural network (DNN) and convolutional neural network (CNN). The proposed
system has been deployed for operational use and the experimental results
proved the effectiveness of our proposed system. Furthermore, we keep our
research results and release experiment material on
http://DeceptiveAds.TWMAN.ORG and http://PhoneScams.TWMAN.ORG if there is any
update.Comment: 6 pages, TAAI 2017 versio
A Viable Flavor Model for Quarks and Leptons in RS with T' Family Symmetry
We propose a Randall-Sundrum model with a bulk family symmetry based on the
double tetrahedral group, T', which generates the tri-bimaximal neutrino mixing
pattern and a realistic CKM matrix. The T' symmetry forbids tree-level
flavor-changing-neutral-currents in both the quark and lepton sectors, as
different generations of fermions are unified into multiplets of T'. This
results in a low first KK mass scale and thus the model can be tested at
collider experiments.Comment: 4 pages; based on talk presented at the 17th International Conference
on Supersymmetry and the Unification of Fundamental Interactions (SUSY09),
Boston, MA, June 5-10, 200
- …