Enhancing Stock Movement Prediction with Adversarial Training

This paper contributes a new machine learning solution for stock movement prediction, which aims to predict whether the price of a stock will be up or down in the near future. The key novelty is that we propose to employ adversarial training to improve the generalization of a neural network prediction model. The rationality of adversarial training here is that the input features to stock prediction are typically based on stock price, which is essentially a stochastic variable and continuously changed with time by nature. As such, normal training with static price-based features (e.g. the close price) can easily overfit the data, being insufficient to obtain reliable models. To address this problem, we propose to add perturbations to simulate the stochasticity of price variable, and train the model to work well under small yet intentional perturbations. Extensive experiments on two real-world stock data show that our method outperforms the state-of-the-art solution with 3.11% relative improvements on average w.r.t. accuracy, validating the usefulness of adversarial training for stock prediction task.Comment: IJCAI 201

Dual-terminal event triggered control for cyber-physical systems under false data injection attacks

summary:This paper deals with the problem of security-based dynamic output feedback control of cyber-physical systems (CPSs) with the dual-terminal event triggered mechanisms (DT-ETM) under false data injection (FDI) attacks. Considering the limited attack energy, FDI attacks taking place in transmission channels are modeled as extra bounded disturbances for the resulting closed-loop system, thus enabling $H_{\infty}$ performance analysis with a suitable $\varrho$ attenuation level. Then two buffers at the controller and actuator sides are skillfully introduced to cope with the different transmission delays in such a way to facilitate the subsequent security analysis. Next, a dynamic output feedback security control (DOFSC) model based on the DT-ETM schemes under FDI attacks is well constructed. Furthermore, novel criteria for stability analysis and robust stabilization are carefully derived by exploiting Lyapunov-Krasovskii theory and LMIs technique. Finally, an illustrative example is provided to show the effectiveness of the proposed method

How reliable are Hanle measurements in metals in a three-terminal geometry?

We test the validity of Hanle measurements in three-terminal devices by using aluminum (Al) and gold (Au). The obtained Hanle and inverted Hanle-like curves show an anomalous behavior. First, we measure Hanle signals 8 orders of magnitude larger than those predicted by standard theory. Second, the temperature and voltage dependences of the signal do not match with the tunneling spin polarization of the ferromagnetic contact. Finally, the spin relaxation times obtained with this method are independent of the choice of the metallic channel. These results are not compatible with spin accumulation in the metal. Furthermore, a scaling of the Hanle signal with the interface resistance of the devices suggests that the measured signal is originated in the tunnel junction.Comment: 9 pages, 5 figure

The impact of microscale physics in continuous time random walks for hydrodynamic dispersion in disordered media

The continuous time random walk (CTRW) approach has been widely applied to model large-scale non-Fickian transport in the flow through disordered media. Often, the underlying microscopic transport mechanisms and disorder characteristics are not known. Their effect on large-scale solute dispersion is encoded by a heavy-tailed transition time distribution. Here we study how the microscale physics manifests in the CTRW framework, and how it affects solute dispersion. To this end, we consider three CTRW models that originate in different microscopic disorder and transport mechanisms, that is, transport under random sorption properties, random flow properties, and a combination thereof. All of these mechanisms can give rise to anomalous transport. We first derive the CTRW models corresponding to each of these physical scenarios, then we explore the impact of the microscale physics on the large-scale dispersion behavior for flux-weighted and uniform solute injection modes. Analytical and numerical results show the differences and similarities in the observed anomalous dispersion behaviors in terms of spatial particle densities, displacement mean and variance, and particle breakthrough curves. While random advection and sorption have similar large-scale transport signatures, they differ in their response to uniform injection conditions, and in general to initial particle distributions that are not flux-weighted. These findings highlight the importance of the microscale physics for the interpretation and prediction of anomalous dispersion phenomena in disordered media.Comment: 29 pages, 6 figure

Modelling vegetation angular signatures from DSCOVR/EPIC and MISR Observations

The angular signatures of reflectance are rich sources of diagnostic information about vegetation canopies, because the geometric structure and foliage optics determine their magnitude and angular distribution. This poster presents angular signatures of Bidirectional Reflectance Factors (BRF) in different biome types for the period of concurrent DSCOVR/EPIC (Earth Polychromatic Imaging Camera onboard the Deep Space Climate Observatory) and MISR (Terra Multi-angle Imaging SpectroRadiometer) observations. We developed a BRF model, which could approximate DSCOVR/EPIC and MISR observations, through analyses of variations in magnitude and shape of angular distribution of canopy reflected radiation and the rigorous use of radiative transfer theory. In this model, the correlation coefficient, visible fraction of leaf area in the direction Ω from the sunlit areas of leaves, is an important parameter that allows us to extend conventional radiative transfer equation to media with finite dimensional scatters and consequently accurately discriminate between sunlit and shaded leaves. Our model was able to capture seasonal variations of reflectance in amazon rain forest, which resulted from changes in both leaf area and solar zenith angle.Published versio

Room-temperature air-stable spin transport in bathocuproine-based spin valves

Organic semiconductors, characterized by weak spin-scattering mechanisms, are attractive materials for those spintronic applications in which the spin information needs to be retained for long times. Prototypical spin-valve devices employing organic interlayers sandwiched between ferromagnetic materials possess a figure of merit (magnetoresistance (MR)) comparable to their fully inorganic counterparts. However, these results are a matter of debate as the conductivity of the devices does not show the expected temperature dependence. Here we show spin valves with an interlayer of bathocuproine in which the transport takes place unambiguously through the organic layer and where the electron spin coherence is maintained over large distances (>60 nm) at room temperature. Additionally, the devices show excellent air stability, with MR values almost unaltered after 70 days of storage under ambient conditions, making bathocuproine an interesting material for future spintronic applications.Fil: Sun, Xiangnan. CIC nanoGUNE; EspañaFil: Gobbi, Marco. Université de Strasbourg; Francia. CIC nanoGUNE; EspañaFil: Bedoya Pinto, Amilcar. CIC nanoGUNE; EspañaFil: Txoperena, Oihana. CIC nanoGUNE; EspañaFil: Golmar, Federico. CIC nanoGUNE; España. Instituto Nacional de Tecnología Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Llopis, Roger. CIC nanoGUNE; EspañaFil: Chuvilin, Andrey. CIC nanoGUNE; España. Fundación Vasca para la Ciencia; EspañaFil: Casanova, Félix. CIC nanoGUNE; España. Fundación Vasca para la Ciencia; EspañaFil: Hueso, Luis E.. CIC nanoGUNE; España. Fundación Vasca para la Ciencia; Españ