Locally linear discriminant embedding: An efficient method for face recognition

In this paper an efficient feature extraction method named as locally linear discriminant embedding (LLDE) is proposed for face recognition. It is well known that a point can be linearly reconstructed by its neighbors and the reconstruction weights are under the sum-to-one constraint in the classical locally linear embedding (LLE). So the constrained weights obey an important symmetry: for any particular data point, they are invariant to rotations, rescalings and translations. The latter two are introduced to the proposed method to strengthen the classification ability of the original LLE. The data with different class labels are translated by the corresponding vectors and those belonging to the same class are translated by the same vector. In order to cluster the data with the same label closer, they are also rescaled to some extent. So after translation and rescaling, the discriminability of the data will be improved significantly. The proposed method is compared with some related feature extraction methods such as maximum margin criterion (MMC), as well as other supervised manifold learning-based approaches, for example ensemble unified LLE and linear discriminant analysis (En-ULLELDA), locally linear discriminant analysis (LLDA). Experimental results on Yale and CMU PIE face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.     

Small sample improvements in the threshold cointegration test using residual-based moving block bootstrap

A residual-based moving block bootstrap procedure for testing the null hypothesis of linear cointegration versus cointegration with threshold effects is proposed. When the regressors and errors of the models are serially and contemporaneously correlated, our test compares favourably with the Sup LM test proposed by Gonzalo and Pitarakis. Indeed, shortcomings of the former motivated the development of our test. The small sample performance of the bootstrap test is investigated by Monte Carlo simulations, and the results show that the test performs better than the Sup LM test.     

Cracking the walnut: Using a computer game to impact cognition,emotion, and behavior of highly aggressive fifth grade students

Three fifth grade highly aggressive students participated in a study examining effects of an aggression intervention game. Using single-subject multiple baseline research design, the effect of the game was measured across three domains: attribution of peer intent (cognitive), emotional response (affective) and behavior response (behavioral). The results indicate that, while there were observable individual differences, the game had an immediate impact on attribution of peer behavior across all participants, had a less predictable impact on reported behavioral reactions, and had no discernable impact on reported emotional response. Theoretical and practical implications of the study are discussed.     

A COMPLEX-TYPE FOCUSSED MAGNETRON FOR SPUTTERING

ＡＣＯＭＰＬＥＸ－ＴＹＰＥＦＯＣＵＳＳＥＤＭＡＧＮＥＴＲＯＮＦＯＲＳＰＵＴＴＥＲＩＮＧ￥ＺｈｅｎｇＳｉｘｉａｏ（郑思孝）（ＩｎｓｔｉｔｕｔｅｏｆＮｕｃｌｅａｒＳｃｉｅｎｃｅａｎｄＴｅｃｈｎｏｌｏｇｙ,ＳｉｃｈｕａｎＵｎｉｖｅｒｓｉｔｙ,Ｃｈｅｎｇｄｕ...     

辐射换热的波长匹配问题

由于水的选择性吸收特性,辐射换热中水份波长匹配一直是一个有分歧的问题。文章通过理论与计算论证了这个问题,得出的结论否定了波长匹配的重要性。     

Critical Review of Fluorinated Electrolytes for High-Performance Lithium Metal Batteries

Lithium metal batteries (LMBs), due to their ultra-high energy density, are attracting tremendous attentions. However, their commercial application is severely impeded by poor safety and unsatisfactory cycling stability, which are induced by lithium dendrites, side reactions, and inferior anodic stability. Electrolytes, as the indispensable and necessary components in lithium metal batteries, play a crucial role in regulating the electrochemical performance of LMBs. Recently, the fluorinated electrolytes are widely investigated in high-performance LMBs. Thus, the design strategies of fluorinated electrolytes are thoroughly summarized, including fluorinated salts, fluorinated solvents, and fluorinated additives in LMBs, and insights of the fluorinated components in suppressing lithium dendrites, improving anodic stability and cycling stability. Finally, an outlook with several design strategies and challenges will be proposed for novel fluorinated electrolytes.     

SAdaBoundNc: an adaptive subgradient online learning algorithm with logarithmic regret bounds

Neural Computing and Applications - Adaptive (sub)gradient methods have received wide applications such as the training of deep networks. The square-root regret bounds are achieved in convex...     

Proximity-Induced Fully Ferromagnetic Order with Eightfold Magnetic Anisotropy in Heavy Transition Metal Oxide CaRuO3

Ferromagnetic materials with a strong spin-orbit coupling (SOC) have attracted much attention in recent years because of their exotic properties and potential applications in energy-efficient spintronics. However, such materials are scarce in nature. Here, a proximity-induced paramagnetic to ferromagnetic transition for the heavy transition metal oxide CaRuO₃ in (001)-(LaMnO₃/CaRuO₃) superlattices is reported. Anomalous Hall effect is observed in the temperature range up to 180 K. Maximal anomalous Hall conductivity and anomalous Hall angle are as large as ∼15 Ω⁻¹ cm⁻¹ and ∼0.93%, respectively, by one to two orders of magnitude larger than those of the typical 3d ferromagnetic oxides such as La_0.67Sr_0.33MnO₃. Density functional theory calculations indicate the existence of avoid band crossings in the electronic band structure of the ferromagnetic CRO layer, which enhances Berry curvature thus strong anomalous Hall effects. Further evidences from polarized neutron reflectometry show that the CaRuO₃ layers are in a fully ferromagnetic state (∼0.8 μ_B/Ru), in sharp contrast to the proximity-induced canted antiferromagnetic state in 5d oxides SrIrO₃ and CaIrO₃ (∼0.1 μ_B/Ir). More than that, the magnetic anisotropy of the (001)-(LaMnO₃/CaRuO₃) superlattices is eightfold symmetric, showing potential applications in the technology of multistate data storage.     

Graph-based fine-grained model selection for multi-source domain

Pattern Analysis and Applications - The prosperity of datasets and model architectures has led to the development of pretrained source models, which simplified the learning process in multi-domain...     

A quantized set-membership estimation-based heading control method of unmanned surface vessels under unknown-but-bounded wave-induced disturbances

This paper is concerned with the heading tracking control problem for a network-based unmanned surface vessel (USV) under wave-induced disturbances. Considering the characteristics of the wave-induced disturbances, the unknown-but-bounded (UBB) noise model is adopted. Meanwhile, signal quantization is taken into account due to the limited capacity of the communication channel. Based on these considerations, a novel set-membership based control scheme is proposed, which consists of a set-membership filter (SMF) and a set-membership controller (SMC). In the proposed control scheme, the SMF is designed for providing an ellipsoidal estimation set for the USV at each sampling step, and then the SMC uses the estimation set for producing control input for the USV in order to track the reference. Sufficient conditions are derived for the considered USV system to be asymptotically stable and satisfy the modified set-membership performance constraint. Simulation results verifies the effectiveness of the proposed control scheme.