The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distanc...The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distance and Tukey M-estimator.Firstly,we propose a k-distancebased method to compute user suspicion degree(USD).The reliable neighbor model can be constructed through incorporating the user suspicion degree into user neighbor model.The influence of attack profiles on the recommendation results is reduced through adjusting similarities among users.Then,Tukey M-estimator is introduced to construct robust matrix factorization model,which can realize the robust estimation of user feature matrix and item feature matrix and reduce the influence of attack profiles on item feature matrix.Finally,a robust collaborative recommendation algorithm is devised by combining the reliable neighbor model and robust matrix factorization model.Experimental results show that the proposed algorithm outperforms the existing methods in terms of both recommendation accuracy and robustness.展开更多
Stacks of solid oxide cells which can be run as both electrolysers and fuel cells have been tested for robustness towards simulations of stress conditions which are likely to occur during operation of solid oxide elec...Stacks of solid oxide cells which can be run as both electrolysers and fuel cells have been tested for robustness towards simulations of stress conditions which are likely to occur during operation of solid oxide electrolysis systems, for which the energy supply comes from renewable sources, such as wind mills and solar cells. Such conditions are thermo mechanical stress conditions as well as loss of fuel and air supply. The cells have Ni/YSZ （yttria stabilized zirconia） fuel electrodes, YSZ electrolytes, and LSCF （lanthanum strontium cobalt ferrite） oxygen electrodes with a CGO （cerium gadolinium oxide） barrier layer. In the stacks, the cells are separated by chromium rich steel interconnects. The robustness tests of stacks are one step in the development of a SOEC （solid oxide electrolysis cell） core; the core component in a SOEC system, including one or more SOEC stacks, heaters, heat exchangers, insulation, and feed troughs.展开更多
Gauge duality theory was originated by Preund （1987）, and was recently further investigated by Friedlander et al. （2014）. When solving some matrix optimization problems via gauge dual, one is usually able to avoid...Gauge duality theory was originated by Preund （1987）, and was recently further investigated by Friedlander et al. （2014）. When solving some matrix optimization problems via gauge dual, one is usually able to avoid full matrix decompositions such as singular value and/or eigenvalue decompositions. In such an approach, a gauge dual problem is solved in the first stage, and then an optimal solution to the primal problem can be recovered from the dual optimal solution obtained in the first stage. Recently, this theory has been applied to a class of semidefinite programming （SDP） problems with promising numerical results by Friedlander and Mac^to （2016）. We establish some theoretical results on applying the gauge duality theory to robust principal component analysis （PCA） and general SDP. For each problem, we present its gauge dual problem, characterize the optimality conditions for the primal-dual gauge pair, and validate a way to recover a primal optimal solution from a dual one. These results are extensions of Friedlander and Macedo （2016） from nuclear norm regularization to robust PCA and from a special class of SDP which requires the coefficient matrix in the linear objective to be positive definite to SDP problems without this restriction. Our results provide further understanding in the potential advantages and disadvantages of the gauge duality theory.展开更多
基金National Natural Science Foundation of China under Grant No.61379116，Natural Science Foundation of Hebei Province under Grant No.F2015203046 and No.F2013203124，Key Program of Research on Science and Technology of Higher Education Institutions of Hebei Province under Grant No.ZH2012028
文摘The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distance and Tukey M-estimator.Firstly,we propose a k-distancebased method to compute user suspicion degree(USD).The reliable neighbor model can be constructed through incorporating the user suspicion degree into user neighbor model.The influence of attack profiles on the recommendation results is reduced through adjusting similarities among users.Then,Tukey M-estimator is introduced to construct robust matrix factorization model,which can realize the robust estimation of user feature matrix and item feature matrix and reduce the influence of attack profiles on item feature matrix.Finally,a robust collaborative recommendation algorithm is devised by combining the reliable neighbor model and robust matrix factorization model.Experimental results show that the proposed algorithm outperforms the existing methods in terms of both recommendation accuracy and robustness.
文摘Stacks of solid oxide cells which can be run as both electrolysers and fuel cells have been tested for robustness towards simulations of stress conditions which are likely to occur during operation of solid oxide electrolysis systems, for which the energy supply comes from renewable sources, such as wind mills and solar cells. Such conditions are thermo mechanical stress conditions as well as loss of fuel and air supply. The cells have Ni/YSZ （yttria stabilized zirconia） fuel electrodes, YSZ electrolytes, and LSCF （lanthanum strontium cobalt ferrite） oxygen electrodes with a CGO （cerium gadolinium oxide） barrier layer. In the stacks, the cells are separated by chromium rich steel interconnects. The robustness tests of stacks are one step in the development of a SOEC （solid oxide electrolysis cell） core; the core component in a SOEC system, including one or more SOEC stacks, heaters, heat exchangers, insulation, and feed troughs.
基金supported by Hong Kong Research Grants Council General Research Fund (Grant No. 14205314)National Natural Science Foundation of China (Grant No. 11371192)
文摘Gauge duality theory was originated by Preund （1987）, and was recently further investigated by Friedlander et al. （2014）. When solving some matrix optimization problems via gauge dual, one is usually able to avoid full matrix decompositions such as singular value and/or eigenvalue decompositions. In such an approach, a gauge dual problem is solved in the first stage, and then an optimal solution to the primal problem can be recovered from the dual optimal solution obtained in the first stage. Recently, this theory has been applied to a class of semidefinite programming （SDP） problems with promising numerical results by Friedlander and Mac^to （2016）. We establish some theoretical results on applying the gauge duality theory to robust principal component analysis （PCA） and general SDP. For each problem, we present its gauge dual problem, characterize the optimality conditions for the primal-dual gauge pair, and validate a way to recover a primal optimal solution from a dual one. These results are extensions of Friedlander and Macedo （2016） from nuclear norm regularization to robust PCA and from a special class of SDP which requires the coefficient matrix in the linear objective to be positive definite to SDP problems without this restriction. Our results provide further understanding in the potential advantages and disadvantages of the gauge duality theory.
