Polarization-Encoded Fully-Phase Encryption Using Transport-of-Intensity Equation

In this study, we propose a novel method to encrypt fully-phase information combining the concepts of the transport of intensity equation and spatially variant polarization encoding. The transport of intensity equation is a non-iterative and non-interferometric phase-retrieval method which recovers the phase information from defocused intensities. Spatially variant polarization encoding employs defocused intensity measurements. The proposed cryptosystem uses a two-step optical experimentation process—primarily, a simple set-up for defocused intensities recording for phase retrieval and then a set-up for encoding. Strong security, convenient intensity-based measurements, and noise-free decryption are the main features of the proposed method. The simulation results have been presented in support of the proposed idea. However, the TIE section of the cryptosystem, as of now, has been experimentally demonstrated for micro-lens.

Design on adaptive weighted guidance law for underwater intelligent vehicle tracking target

In future naval warfare, the accurate attack of underwater intelligent vehicles on targets will become more and more important. Therefore, it is very important to study the guiding method which has the key influence on tracking targets. In the guidance process of intelligent navigation system, the estimation of guidance information by the agent is influenced by confrontation and interference, which often results in the decrease of the guidance accuracy of UUV under the single guidance law. In this paper, the estimated information is classified according to the different types of guidance target information combining to the advantages of three guidance methods, namely fixed advance angle, extended proportional guidance law and adaptive sliding mode guidance law. Then the fuzzy weight coefficient calculation method is used to get the weight coefficients of all kinds of information to form the adaptive weighted guidance law. The target tracking effects of each guidance method is simulated and compared in the simulation environment of the target maneuver and the target non-maneuver respectively.

Development of intercultural communicative competence in Russian-Chinese discourse

The expansion of intercultural interaction between countries and cultures requires the training of modern specialists who know both foreign languages and intercultural communication. However, in the training of translators, there is a lack of authentic material offered by the native speakers of the corresponding language and culture. The purpose of the article is to suggest strategies for teaching the translation of advertising texts and anthroponyms in the Russian-Chinese discourse. The methodological basis of the research is the theory of skopos considering translation as a practical type of activity, as well as a comparative analysis of anthroponyms. As a result of the research, there proposed strategies for translating advertising texts (working with linguistic forms, cultural content, adding and omitting information, combining these strategies) and anthroponyms (using transliteration from Russian into Chinese, it is necessary not only to choose suitable Chinese hieroglyphs but also take into account their meanings, special cases). Comparing Russian and Chinese names, an important difference is found: transliterating Russian names, a person’s gender information can be expressed through Chinese hieroglyphs but this effect cannot be achieved when transliterating Chinese names. Russian-Chinese discourse has a strong cultural connotation, reflecting the unique way of people’s life. The task of the translator is to reproduce not only the formal but also the cultural information of the original text. The novelty of the work is determined by the need to research the Sino-Tibetan language group in order to improve the methodology of teaching translation and intercultural communication as a practical activity.

Strategies for integrating disparate social information

Social information use is widespread in the animal kingdom, helping individuals rapidly acquire useful knowledge and adjust to novel circumstances. In humans, the highly interconnected world provides ample opportunities to benefit from social information but also requires navigating complex social environments with people holding disparate or conflicting views. It is, however, still largely unclear how people integrate information from multiple social sources that (dis)agree with them, and among each other. We address this issue in three steps. First, we present a judgement task in which participants could adjust their judgements after observing the judgements of three peers. We experimentally varied the distribution of this social information, systematically manipulating its variance (extent of agreement among peers) and its skewness (peer judgements clustering either near or far from the participant's judgement). As expected, higher variance among peers reduced their impact on behaviour. Importantly, observing a single peer confirming a participant's own judgement markedly decreased the influence of other—more distant—peers. Second, we develop a framework for modelling the cognitive processes underlying the integration of disparate social information, combining Bayesian updating with simple heuristics. Our model accurately accounts for observed adjustment strategies and reveals that people particularly heed social information that confirms personal judgements. Moreover, the model exposes strong inter-individual differences in strategy use. Third, using simulations, we explore the possible implications of the observed strategies for belief updating. These simulations show how confirmation-based weighting can hamper the influence of disparate social information, exacerbate filter bubble effects and deepen group polarization. Overall, our results clarify what aspects of the social environment are, and are not, conducive to changing people's minds.

Strategies for integrating disparate social information

**Note that the paper has been published on https://doi.org/10.1098/rspb.2020.2413.** Our increasingly interconnected world provides virtually unlimited opportunities to observe the behavior of others. This affords abundant useful information but also requires navigating complex social environments with people holding disparate or conflicting views. It is, however, still largely unclear how people integrate information from multiple social sources that (dis)agree with them, and among each other. We address this issue in three steps. First, we present a judgment task in which participants could adjust their judgments after observing the judgments of three peers. We experimentally varied the distribution of this social information, systematically manipulating its variance (extent of agreement among peers) and its skewness (peer judgments clustering either near or far from the participant’s). As expected, higher variance among peers reduced their impact on behavior. Importantly, observing a single peer confirming an individual’s judgment markedly decreased the influence of other—more distant—peers. Second, we develop a framework for modelling the cognitive processes underlying the integration of disparate social information, combining Bayesian updating with simple heuristics. Our model accurately accounts for observed adjustment strategies and reveals that people particularly heed social information that confirms personal judgments. Moreover, the model exposes strong inter-individual differences in strategy use. Third, using simulations, we explore the possible implications of identified strategies for belief updating more broadly. They show how confirmation effects can hamper the influence of disparate social information, exacerbate filter bubble effects and worsen group polarization. Overall, our results clarify what aspects of the social environment are, and are not, conducive to changing people’s minds.

Self-Adapting Patch Strategies for Face Recognition

In this paper, we propose two self-adapting patch strategies, which are obtained by employing the integral projection technique on images’ edge images, while the edge images are recovered by the two-dimensional discrete wavelet transform. The patch strategies are equipped with the advantage of considering the single image’s unique properties and maintaining the integrity of some particular local information. Combining the self-adapting patch strategies with local binary pattern feature extraction and the classifier of the forward and backward greedy algorithms under strong sparse constraint, we propose two new face recognition methods. Experiments are run on the Georgia Tech, LFW and AR face databases. The obtained numerical results show that the new methods outperform some related patch-based methods to a larger extent.

Characterization and history of the Helmi streams with Gaia DR2

Context. The halo of the Milky Way has long been hypothesized to harbour significant amounts of merger debris. For more than a decade this view has been supported by wide-field photometric surveys which have revealed the outer halo to be lumpy. Aims. The recent release of Gaia DR2 is allowing us to establish that mergers also have been important and possibly built up the majority of the inner halo. In this work we focus on the Helmi streams, a group of streams crossing the solar vicinity and known for almost two decades. We characterize their properties and relevance for the build-up of the Milky Way’s halo. Methods. We identify new members of the Helmi streams in an unprecedented dataset with full phase-space information combining Gaia DR2, and the APOGEE DR2, RAVE DR5, and LAMOST DR4 spectroscopic surveys. Based on the orbital properties of the stars, we find new stream members up to a distance of 5 kpc from the Sun, which we characterized using photometry and metallicity information. We also perform N-body experiments to constrain the time of accretion and properties of the progenitor of the streams. Results. We find nearly 600 new members of the Helmi streams. Their HR diagram reveals a broad age range, from ≈11 to 13 Gyr, while their metallicity distribution goes from −2.3 to −1.0, and peaks at [Fe/H] ∼ −1.5. These findings confirm that the streams originate in a dwarf galaxy. Furthermore, we find seven globular clusters to be likely associated, and which follow a well-defined age-metallicity sequence whose properties suggest a relatively massive progenitor object. Our N-body simulations favour a system with a stellar mass of ∼108 M⊙ accreted 5 − 8 Gyr ago. Conclusions. The debris from the Helmi streams is an important donor to the Milky Way halo, contributing ≈15% of its mass in field stars and 10% of its globular clusters.