We discuss the choice of polynomial basis for approximation of uncertainty propagation through complex simulation models with capability to output derivative information. Our work is part of a larger research effort in uncertainty quantification using sampling methods augmented with derivative information. The approach has new challenges compared with standard polynomial regression. In particul...

Describes i) necessity of fuzzy DataBase ii) techniques used in the storage and retrieval of fuzzy data in a DataBase or information retrieval system iii) DataBase framework for fuzzy DataBase and iv) the advantages of using object-oriented DataBase framework in fuzzy DataBase. A prototype of fuzzy object-oriented DataBase system, (FOODS), has been developed to demonstrate the feasibility of fu...

In the near future, autonomous systems such as multi-robot are envisioned to increasingly co-exist with hu- mans in our daily lives, from household service large- scale warehouse logistics, agriculture environment sampling, and smart city. these applications, robots humans networked heterogeneous components will frequently inter- act each other a variety of scenarios under uncer- tain, rapidly-...

In this paper, we propose an Efficient Two-Level I/O Caching Architecture (ETICA) for virtualized platforms that can significantly improve latency, endurance, and cost (in terms of cache size) while preserving the reliability write-pending data blocks. As opposed to previous one-level caching schemes in platforms, our proposed architecture 1) provides two levels by employing both Dynamic Random...

We consider a trader who aims to liquidate a large position in the presence of anarbitrageur who hopes to profit from the trader’s activity. The arbitrageur is uncer-tain about the trader’s position and learns from observed price fluctuations. This isa dynamic game with asymmetric information. We present an algorithm for comput-ing perfect Bayesian equilibrium behavior and c...

We describe preliminary results from an effort to quan-tify the uncertainties in parton distribution functionsand the resulting uncertainties in predicted physicalquantities. The production cross section of the Wboson is given as a first example. Constraints due tothe full data sets of the CTEQ global analysis are usedin this study. Two complementary approaches, based<lb...

Traditional Deep Neural Network (DNN) security is mostly related to the well-known adversarial input example attack. Recently, another dimension of attack, namely, attack on DNN weight parameters, has been shown be very powerful. As a representative one, Bit-Flip-based Attack (BFA) injects an extremely small amount faults into parameters hijack executing function. Prior works BFA focus <italic ...

In recent years, memristive crossbar-based neuromorphic computing systems (NCS) have obtained extremely high performance in neural network acceleration. However, adversarial attacks and conductance variations of memristors bring reliability challenges to NCS design. First, can fool the pose a serious threat security critical applications. On other hand, device lead degradation accuracy. this pa...